From de0d6a68ac99f307fe889c48e21124bc3b7ca29a Mon Sep 17 00:00:00 2001 From: fairydreaming <166155368+fairydreaming@users.noreply.github.com> Date: Mon, 24 Jun 2024 07:06:05 +0200 Subject: [PATCH 001/326] gguf-py, convert-hf : model conversion support for T5 and FLAN-T5 model variants (#5763) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * gguf-py : add T5 model architecture * gguf-py : add separate tensors for encoder and decoder * gguf-py : add new model header parameters: decoder_start_token_id, attention.relative_buckets_count, tokenizer.ggml.remove_extra_whitespaces, tokenizer.ggml.precompiled_charsmap * convert-hf : add model conversion support for T5ForConditionalGeneration and T5WithLMHeadModel --------- Co-authored-by: Stanisław Szymczyk --- convert-hf-to-gguf.py | 120 +++++++++- gguf-py/gguf/constants.py | 414 ++++++++++++++++++++------------- gguf-py/gguf/gguf_writer.py | 21 +- gguf-py/gguf/tensor_mapping.py | 115 +++++++++ 4 files changed, 506 insertions(+), 164 deletions(-) diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py index 8ce79d14604fd..ebfc1a1f94b78 100755 --- a/convert-hf-to-gguf.py +++ b/convert-hf-to-gguf.py @@ -80,7 +80,7 @@ def __init__(self, dir_model: Path, ftype: gguf.LlamaFileType, fname_out: Path, if not self.is_safetensors: self.part_names = Model.get_model_part_names(self.dir_model, "pytorch_model", ".bin") self.hparams = Model.load_hparams(self.dir_model) - self.block_count = self.find_hparam(["n_layers", "num_hidden_layers", "n_layer"]) + self.block_count = self.find_hparam(["n_layers", "num_hidden_layers", "n_layer", "num_layers"]) self.tensor_map = gguf.get_tensor_name_map(self.model_arch, self.block_count) self.tensor_names = None if self.ftype == gguf.LlamaFileType.GUESSED: @@ -2771,6 +2771,124 @@ def write_tensors(self): raise ValueError(f"Unprocessed experts: {experts}") +@Model.register("T5ForConditionalGeneration") +@Model.register("T5WithLMHeadModel") +class T5Model(Model): + model_arch = gguf.MODEL_ARCH.T5 + + def set_vocab(self): + # to avoid TypeError: Descriptors cannot be created directly + # exception when importing sentencepiece_model_pb2 + os.environ["PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION"] = "python" + from sentencepiece import SentencePieceProcessor + from sentencepiece import sentencepiece_model_pb2 as model + + tokenizer_path = self.dir_model / 'spiece.model' + + if not tokenizer_path.is_file(): + raise FileNotFoundError(f"File not found: {tokenizer_path}") + + sentencepiece_model = model.ModelProto() + sentencepiece_model.ParseFromString(open(tokenizer_path, "rb").read()) + add_prefix = sentencepiece_model.normalizer_spec.add_dummy_prefix + remove_whitespaces = sentencepiece_model.normalizer_spec.remove_extra_whitespaces + precompiled_charsmap = sentencepiece_model.normalizer_spec.precompiled_charsmap + assert sentencepiece_model.trainer_spec.model_type == 1 # UNIGRAM + + tokenizer = SentencePieceProcessor() + tokenizer.LoadFromFile(str(tokenizer_path)) + + vocab_size = self.hparams.get('vocab_size', tokenizer.vocab_size()) + + tokens: list[bytes] = [f"[PAD{i}]".encode("utf-8") for i in range(vocab_size)] + scores: list[float] = [-10000.0] * vocab_size + toktypes: list[int] = [SentencePieceTokenTypes.UNKNOWN] * vocab_size + + for token_id in range(tokenizer.vocab_size()): + piece = tokenizer.IdToPiece(token_id) + text = piece.encode("utf-8") + score = tokenizer.GetScore(token_id) + + toktype = SentencePieceTokenTypes.NORMAL + if tokenizer.IsUnknown(token_id): + toktype = SentencePieceTokenTypes.UNKNOWN + elif tokenizer.IsControl(token_id): + toktype = SentencePieceTokenTypes.CONTROL + elif tokenizer.IsUnused(token_id): + toktype = SentencePieceTokenTypes.UNUSED + elif tokenizer.IsByte(token_id): + toktype = SentencePieceTokenTypes.BYTE + + tokens[token_id] = text + scores[token_id] = score + toktypes[token_id] = toktype + + added_tokens_file = self.dir_model / 'added_tokens.json' + if added_tokens_file.is_file(): + with open(added_tokens_file, "r", encoding="utf-8") as f: + added_tokens_json = json.load(f) + for key in added_tokens_json: + token_id = added_tokens_json[key] + if (token_id >= vocab_size): + logger.warning(f'ignore token {token_id}: id is out of range, max={vocab_size - 1}') + continue + + tokens[token_id] = key.encode("utf-8") + scores[token_id] = -1000.0 + toktypes[token_id] = SentencePieceTokenTypes.USER_DEFINED + + if vocab_size > len(tokens): + pad_count = vocab_size - len(tokens) + logger.debug(f"Padding vocab with {pad_count} token(s) - [PAD1] through [PAD{pad_count}]") + for i in range(1, pad_count + 1): + tokens.append(bytes(f"[PAD{i}]", encoding="utf-8")) + scores.append(-1000.0) + toktypes.append(SentencePieceTokenTypes.UNUSED) + + self.gguf_writer.add_tokenizer_model("t5") + self.gguf_writer.add_tokenizer_pre("default") + self.gguf_writer.add_token_list(tokens) + self.gguf_writer.add_token_scores(scores) + self.gguf_writer.add_token_types(toktypes) + self.gguf_writer.add_add_space_prefix(add_prefix) + self.gguf_writer.add_remove_extra_whitespaces(remove_whitespaces) + if precompiled_charsmap: + self.gguf_writer.add_precompiled_charsmap(precompiled_charsmap) + + special_vocab = gguf.SpecialVocab(self.dir_model, n_vocab=len(tokens)) + special_vocab.add_to_gguf(self.gguf_writer) + + self.gguf_writer.add_add_bos_token(False) + self.gguf_writer.add_add_eos_token(True) + + def set_gguf_parameters(self): + self.gguf_writer.add_name("T5") + self.gguf_writer.add_context_length(self.hparams["n_positions"]) + self.gguf_writer.add_embedding_length(self.hparams["d_model"]) + self.gguf_writer.add_feed_forward_length(self.hparams["d_ff"]) + self.gguf_writer.add_block_count(self.hparams["num_layers"]) + self.gguf_writer.add_head_count(self.hparams["num_heads"]) + self.gguf_writer.add_key_length(self.hparams["d_kv"]) + self.gguf_writer.add_value_length(self.hparams["d_kv"]) + self.gguf_writer.add_layer_norm_eps(self.hparams["layer_norm_epsilon"]) + self.gguf_writer.add_relative_attn_buckets_count(self.hparams["relative_attention_num_buckets"]) + self.gguf_writer.add_layer_norm_rms_eps(self.hparams["layer_norm_epsilon"]) + self.gguf_writer.add_decoder_start_token_id(self.hparams["decoder_start_token_id"]) + self.gguf_writer.add_file_type(self.ftype) + + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + del bid # unused + + # Sometimes T5 and Flan-T5 based models contain "encoder.embed_tokens.weight" tensor or + # "decoder.embed_tokens.weight" tensors that are duplicates of "shared.weight" tensor + # To prevent errors caused by an unnecessary unmapped tensor, skip both of them and use only "shared.weight". + if name == "decoder.embed_tokens.weight" or name == "encoder.embed_tokens.weight": + logger.debug(f"Skipping tensor {name!r} in safetensors so that convert can end normally.") + return [] + + return [(self.map_tensor_name(name), data_torch)] + + ###### CONVERSION LOGIC ###### diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py index d266fbd43d8d6..100594b303526 100644 --- a/gguf-py/gguf/constants.py +++ b/gguf-py/gguf/constants.py @@ -49,6 +49,7 @@ class LLM: EXPERT_WEIGHTS_SCALE = "{arch}.expert_weights_scale" POOLING_TYPE = "{arch}.pooling_type" LOGIT_SCALE = "{arch}.logit_scale" + DECODER_START_TOKEN_ID = "{arch}.decoder_start_token_id" class Attention: HEAD_COUNT = "{arch}.attention.head_count" @@ -62,6 +63,7 @@ class Attention: CAUSAL = "{arch}.attention.causal" Q_LORA_RANK = "{arch}.attention.q_lora_rank" KV_LORA_RANK = "{arch}.attention.kv_lora_rank" + REL_BUCKETS_COUNT = "{arch}.attention.relative_buckets_count" class Rope: DIMENSION_COUNT = "{arch}.rope.dimension_count" @@ -80,33 +82,35 @@ class SSM: TIME_STEP_RANK = "{arch}.ssm.time_step_rank" class Tokenizer: - MODEL = "tokenizer.ggml.model" - PRE = "tokenizer.ggml.pre" - LIST = "tokenizer.ggml.tokens" - TOKEN_TYPE = "tokenizer.ggml.token_type" - TOKEN_TYPE_COUNT = "tokenizer.ggml.token_type_count" # for BERT-style token types - SCORES = "tokenizer.ggml.scores" - MERGES = "tokenizer.ggml.merges" - BOS_ID = "tokenizer.ggml.bos_token_id" - EOS_ID = "tokenizer.ggml.eos_token_id" - UNK_ID = "tokenizer.ggml.unknown_token_id" - SEP_ID = "tokenizer.ggml.seperator_token_id" - PAD_ID = "tokenizer.ggml.padding_token_id" - CLS_ID = "tokenizer.ggml.cls_token_id" - MASK_ID = "tokenizer.ggml.mask_token_id" - ADD_BOS = "tokenizer.ggml.add_bos_token" - ADD_EOS = "tokenizer.ggml.add_eos_token" - ADD_PREFIX = "tokenizer.ggml.add_space_prefix" - HF_JSON = "tokenizer.huggingface.json" - RWKV = "tokenizer.rwkv.world" - CHAT_TEMPLATE = "tokenizer.chat_template" - CHAT_TEMPLATE_N = "tokenizer.chat_template.{name}" - CHAT_TEMPLATES = "tokenizer.chat_templates" + MODEL = "tokenizer.ggml.model" + PRE = "tokenizer.ggml.pre" + LIST = "tokenizer.ggml.tokens" + TOKEN_TYPE = "tokenizer.ggml.token_type" + TOKEN_TYPE_COUNT = "tokenizer.ggml.token_type_count" # for BERT-style token types + SCORES = "tokenizer.ggml.scores" + MERGES = "tokenizer.ggml.merges" + BOS_ID = "tokenizer.ggml.bos_token_id" + EOS_ID = "tokenizer.ggml.eos_token_id" + UNK_ID = "tokenizer.ggml.unknown_token_id" + SEP_ID = "tokenizer.ggml.seperator_token_id" + PAD_ID = "tokenizer.ggml.padding_token_id" + CLS_ID = "tokenizer.ggml.cls_token_id" + MASK_ID = "tokenizer.ggml.mask_token_id" + ADD_BOS = "tokenizer.ggml.add_bos_token" + ADD_EOS = "tokenizer.ggml.add_eos_token" + ADD_PREFIX = "tokenizer.ggml.add_space_prefix" + REMOVE_EXTRA_WS = "tokenizer.ggml.remove_extra_whitespaces" + PRECOMPILED_CHARSMAP = "tokenizer.ggml.precompiled_charsmap" + HF_JSON = "tokenizer.huggingface.json" + RWKV = "tokenizer.rwkv.world" + CHAT_TEMPLATE = "tokenizer.chat_template" + CHAT_TEMPLATE_N = "tokenizer.chat_template.{name}" + CHAT_TEMPLATES = "tokenizer.chat_templates" # FIM/Infill special tokens constants - PREFIX_ID = "tokenizer.ggml.prefix_token_id" - SUFFIX_ID = "tokenizer.ggml.suffix_token_id" - MIDDLE_ID = "tokenizer.ggml.middle_token_id" - EOT_ID = "tokenizer.ggml.eot_token_id" + PREFIX_ID = "tokenizer.ggml.prefix_token_id" + SUFFIX_ID = "tokenizer.ggml.suffix_token_id" + MIDDLE_ID = "tokenizer.ggml.middle_token_id" + EOT_ID = "tokenizer.ggml.eot_token_id" # @@ -115,94 +119,123 @@ class Tokenizer: class MODEL_ARCH(IntEnum): - LLAMA = auto() - FALCON = auto() - BAICHUAN = auto() - GROK = auto() - GPT2 = auto() - GPTJ = auto() - GPTNEOX = auto() - MPT = auto() - STARCODER = auto() - REFACT = auto() - BERT = auto() - NOMIC_BERT = auto() + LLAMA = auto() + FALCON = auto() + BAICHUAN = auto() + GROK = auto() + GPT2 = auto() + GPTJ = auto() + GPTNEOX = auto() + MPT = auto() + STARCODER = auto() + REFACT = auto() + BERT = auto() + NOMIC_BERT = auto() JINA_BERT_V2 = auto() - BLOOM = auto() - STABLELM = auto() - QWEN = auto() - QWEN2 = auto() - QWEN2MOE = auto() - PHI2 = auto() - PHI3 = auto() - PLAMO = auto() - CODESHELL = auto() - ORION = auto() - INTERNLM2 = auto() - MINICPM = auto() - GEMMA = auto() - STARCODER2 = auto() - MAMBA = auto() - XVERSE = auto() - COMMAND_R = auto() - DBRX = auto() - OLMO = auto() - ARCTIC = auto() - DEEPSEEK2 = auto() - BITNET = auto() + BLOOM = auto() + STABLELM = auto() + QWEN = auto() + QWEN2 = auto() + QWEN2MOE = auto() + PHI2 = auto() + PHI3 = auto() + PLAMO = auto() + CODESHELL = auto() + ORION = auto() + INTERNLM2 = auto() + MINICPM = auto() + GEMMA = auto() + STARCODER2 = auto() + MAMBA = auto() + XVERSE = auto() + COMMAND_R = auto() + DBRX = auto() + OLMO = auto() + ARCTIC = auto() + DEEPSEEK2 = auto() + BITNET = auto() + T5 = auto() class MODEL_TENSOR(IntEnum): - TOKEN_EMBD = auto() - TOKEN_EMBD_NORM = auto() - TOKEN_TYPES = auto() - POS_EMBD = auto() - OUTPUT = auto() - OUTPUT_NORM = auto() - ROPE_FREQS = auto() - ROPE_FACTORS_LONG = auto() - ROPE_FACTORS_SHORT = auto() - ATTN_Q = auto() - ATTN_K = auto() - ATTN_V = auto() - ATTN_QKV = auto() - ATTN_OUT = auto() - ATTN_NORM = auto() - ATTN_NORM_2 = auto() - ATTN_OUT_NORM = auto() - ATTN_ROT_EMBD = auto() - FFN_GATE_INP = auto() - FFN_GATE_INP_SHEXP = auto() - FFN_NORM = auto() - FFN_GATE = auto() - FFN_DOWN = auto() - FFN_UP = auto() - FFN_ACT = auto() - FFN_NORM_EXP = auto() - FFN_GATE_EXP = auto() - FFN_DOWN_EXP = auto() - FFN_UP_EXP = auto() - FFN_GATE_SHEXP = auto() - FFN_DOWN_SHEXP = auto() - FFN_UP_SHEXP = auto() - ATTN_Q_NORM = auto() - ATTN_K_NORM = auto() - LAYER_OUT_NORM = auto() - SSM_IN = auto() - SSM_CONV1D = auto() - SSM_X = auto() - SSM_DT = auto() - SSM_A = auto() - SSM_D = auto() - SSM_OUT = auto() - ATTN_Q_A = auto() - ATTN_Q_B = auto() - ATTN_KV_A_MQA = auto() - ATTN_KV_B = auto() - ATTN_Q_A_NORM = auto() - ATTN_KV_A_NORM = auto() - FFN_SUB_NORM = auto() - ATTN_SUB_NORM = auto() + TOKEN_EMBD = auto() + TOKEN_EMBD_NORM = auto() + TOKEN_TYPES = auto() + POS_EMBD = auto() + OUTPUT = auto() + OUTPUT_NORM = auto() + ROPE_FREQS = auto() + ROPE_FACTORS_LONG = auto() + ROPE_FACTORS_SHORT = auto() + ATTN_Q = auto() + ATTN_K = auto() + ATTN_V = auto() + ATTN_QKV = auto() + ATTN_OUT = auto() + ATTN_NORM = auto() + ATTN_NORM_2 = auto() + ATTN_OUT_NORM = auto() + ATTN_ROT_EMBD = auto() + FFN_GATE_INP = auto() + FFN_GATE_INP_SHEXP = auto() + FFN_NORM = auto() + FFN_GATE = auto() + FFN_DOWN = auto() + FFN_UP = auto() + FFN_ACT = auto() + FFN_NORM_EXP = auto() + FFN_GATE_EXP = auto() + FFN_DOWN_EXP = auto() + FFN_UP_EXP = auto() + FFN_GATE_SHEXP = auto() + FFN_DOWN_SHEXP = auto() + FFN_UP_SHEXP = auto() + ATTN_Q_NORM = auto() + ATTN_K_NORM = auto() + LAYER_OUT_NORM = auto() + SSM_IN = auto() + SSM_CONV1D = auto() + SSM_X = auto() + SSM_DT = auto() + SSM_A = auto() + SSM_D = auto() + SSM_OUT = auto() + ATTN_Q_A = auto() + ATTN_Q_B = auto() + ATTN_KV_A_MQA = auto() + ATTN_KV_B = auto() + ATTN_Q_A_NORM = auto() + ATTN_KV_A_NORM = auto() + FFN_SUB_NORM = auto() + ATTN_SUB_NORM = auto() + DEC_ATTN_NORM = auto() + DEC_ATTN_Q = auto() + DEC_ATTN_K = auto() + DEC_ATTN_V = auto() + DEC_ATTN_OUT = auto() + DEC_ATTN_REL_B = auto() + DEC_CROSS_ATTN_NORM = auto() + DEC_CROSS_ATTN_Q = auto() + DEC_CROSS_ATTN_K = auto() + DEC_CROSS_ATTN_V = auto() + DEC_CROSS_ATTN_OUT = auto() + DEC_CROSS_ATTN_REL_B = auto() + DEC_FFN_NORM = auto() + DEC_FFN_GATE = auto() + DEC_FFN_DOWN = auto() + DEC_FFN_UP = auto() + DEC_OUTPUT_NORM = auto() + ENC_ATTN_NORM = auto() + ENC_ATTN_Q = auto() + ENC_ATTN_K = auto() + ENC_ATTN_V = auto() + ENC_ATTN_OUT = auto() + ENC_ATTN_REL_B = auto() + ENC_FFN_NORM = auto() + ENC_FFN_GATE = auto() + ENC_FFN_DOWN = auto() + ENC_FFN_UP = auto() + ENC_OUTPUT_NORM = auto() MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = { @@ -241,59 +274,88 @@ class MODEL_TENSOR(IntEnum): MODEL_ARCH.ARCTIC: "arctic", MODEL_ARCH.DEEPSEEK2: "deepseek2", MODEL_ARCH.BITNET: "bitnet", + MODEL_ARCH.T5: "t5", } TENSOR_NAMES: dict[MODEL_TENSOR, str] = { - MODEL_TENSOR.TOKEN_EMBD: "token_embd", - MODEL_TENSOR.TOKEN_EMBD_NORM: "token_embd_norm", - MODEL_TENSOR.TOKEN_TYPES: "token_types", - MODEL_TENSOR.POS_EMBD: "position_embd", - MODEL_TENSOR.OUTPUT_NORM: "output_norm", - MODEL_TENSOR.OUTPUT: "output", - MODEL_TENSOR.ROPE_FREQS: "rope_freqs", - MODEL_TENSOR.ROPE_FACTORS_LONG: "rope_factors_long", - MODEL_TENSOR.ROPE_FACTORS_SHORT: "rope_factors_short", - MODEL_TENSOR.ATTN_NORM: "blk.{bid}.attn_norm", - MODEL_TENSOR.ATTN_NORM_2: "blk.{bid}.attn_norm_2", - MODEL_TENSOR.ATTN_QKV: "blk.{bid}.attn_qkv", - MODEL_TENSOR.ATTN_Q: "blk.{bid}.attn_q", - MODEL_TENSOR.ATTN_K: "blk.{bid}.attn_k", - MODEL_TENSOR.ATTN_V: "blk.{bid}.attn_v", - MODEL_TENSOR.ATTN_OUT: "blk.{bid}.attn_output", - MODEL_TENSOR.ATTN_ROT_EMBD: "blk.{bid}.attn_rot_embd", - MODEL_TENSOR.ATTN_Q_NORM: "blk.{bid}.attn_q_norm", - MODEL_TENSOR.ATTN_K_NORM: "blk.{bid}.attn_k_norm", - MODEL_TENSOR.ATTN_OUT_NORM: "blk.{bid}.attn_output_norm", - MODEL_TENSOR.FFN_GATE_INP: "blk.{bid}.ffn_gate_inp", - MODEL_TENSOR.FFN_GATE_INP_SHEXP: "blk.{bid}.ffn_gate_inp_shexp", - MODEL_TENSOR.FFN_NORM: "blk.{bid}.ffn_norm", - MODEL_TENSOR.FFN_GATE: "blk.{bid}.ffn_gate", - MODEL_TENSOR.FFN_DOWN: "blk.{bid}.ffn_down", - MODEL_TENSOR.FFN_UP: "blk.{bid}.ffn_up", - MODEL_TENSOR.FFN_GATE_SHEXP: "blk.{bid}.ffn_gate_shexp", - MODEL_TENSOR.FFN_DOWN_SHEXP: "blk.{bid}.ffn_down_shexp", - MODEL_TENSOR.FFN_UP_SHEXP: "blk.{bid}.ffn_up_shexp", - MODEL_TENSOR.FFN_ACT: "blk.{bid}.ffn", - MODEL_TENSOR.FFN_NORM_EXP: "blk.{bid}.ffn_norm_exps", - MODEL_TENSOR.FFN_GATE_EXP: "blk.{bid}.ffn_gate_exps", - MODEL_TENSOR.FFN_DOWN_EXP: "blk.{bid}.ffn_down_exps", - MODEL_TENSOR.FFN_UP_EXP: "blk.{bid}.ffn_up_exps", - MODEL_TENSOR.LAYER_OUT_NORM: "blk.{bid}.layer_output_norm", - MODEL_TENSOR.SSM_IN: "blk.{bid}.ssm_in", - MODEL_TENSOR.SSM_CONV1D: "blk.{bid}.ssm_conv1d", - MODEL_TENSOR.SSM_X: "blk.{bid}.ssm_x", - MODEL_TENSOR.SSM_DT: "blk.{bid}.ssm_dt", - MODEL_TENSOR.SSM_A: "blk.{bid}.ssm_a", - MODEL_TENSOR.SSM_D: "blk.{bid}.ssm_d", - MODEL_TENSOR.SSM_OUT: "blk.{bid}.ssm_out", - MODEL_TENSOR.ATTN_Q_A: "blk.{bid}.attn_q_a", - MODEL_TENSOR.ATTN_Q_B: "blk.{bid}.attn_q_b", - MODEL_TENSOR.ATTN_KV_A_MQA: "blk.{bid}.attn_kv_a_mqa", - MODEL_TENSOR.ATTN_KV_B: "blk.{bid}.attn_kv_b", - MODEL_TENSOR.ATTN_Q_A_NORM: "blk.{bid}.attn_q_a_norm", - MODEL_TENSOR.ATTN_KV_A_NORM: "blk.{bid}.attn_kv_a_norm", - MODEL_TENSOR.ATTN_SUB_NORM: "blk.{bid}.attn_sub_norm", - MODEL_TENSOR.FFN_SUB_NORM: "blk.{bid}.ffn_sub_norm", + MODEL_TENSOR.TOKEN_EMBD: "token_embd", + MODEL_TENSOR.TOKEN_EMBD_NORM: "token_embd_norm", + MODEL_TENSOR.TOKEN_TYPES: "token_types", + MODEL_TENSOR.POS_EMBD: "position_embd", + MODEL_TENSOR.OUTPUT_NORM: "output_norm", + MODEL_TENSOR.OUTPUT: "output", + MODEL_TENSOR.ROPE_FREQS: "rope_freqs", + MODEL_TENSOR.ROPE_FACTORS_LONG: "rope_factors_long", + MODEL_TENSOR.ROPE_FACTORS_SHORT: "rope_factors_short", + MODEL_TENSOR.ATTN_NORM: "blk.{bid}.attn_norm", + MODEL_TENSOR.ATTN_NORM_2: "blk.{bid}.attn_norm_2", + MODEL_TENSOR.ATTN_QKV: "blk.{bid}.attn_qkv", + MODEL_TENSOR.ATTN_Q: "blk.{bid}.attn_q", + MODEL_TENSOR.ATTN_K: "blk.{bid}.attn_k", + MODEL_TENSOR.ATTN_V: "blk.{bid}.attn_v", + MODEL_TENSOR.ATTN_OUT: "blk.{bid}.attn_output", + MODEL_TENSOR.ATTN_ROT_EMBD: "blk.{bid}.attn_rot_embd", + MODEL_TENSOR.ATTN_Q_NORM: "blk.{bid}.attn_q_norm", + MODEL_TENSOR.ATTN_K_NORM: "blk.{bid}.attn_k_norm", + MODEL_TENSOR.ATTN_OUT_NORM: "blk.{bid}.attn_output_norm", + MODEL_TENSOR.FFN_GATE_INP: "blk.{bid}.ffn_gate_inp", + MODEL_TENSOR.FFN_GATE_INP_SHEXP: "blk.{bid}.ffn_gate_inp_shexp", + MODEL_TENSOR.FFN_NORM: "blk.{bid}.ffn_norm", + MODEL_TENSOR.FFN_GATE: "blk.{bid}.ffn_gate", + MODEL_TENSOR.FFN_DOWN: "blk.{bid}.ffn_down", + MODEL_TENSOR.FFN_UP: "blk.{bid}.ffn_up", + MODEL_TENSOR.FFN_GATE_SHEXP: "blk.{bid}.ffn_gate_shexp", + MODEL_TENSOR.FFN_DOWN_SHEXP: "blk.{bid}.ffn_down_shexp", + MODEL_TENSOR.FFN_UP_SHEXP: "blk.{bid}.ffn_up_shexp", + MODEL_TENSOR.FFN_ACT: "blk.{bid}.ffn", + MODEL_TENSOR.FFN_NORM_EXP: "blk.{bid}.ffn_norm_exps", + MODEL_TENSOR.FFN_GATE_EXP: "blk.{bid}.ffn_gate_exps", + MODEL_TENSOR.FFN_DOWN_EXP: "blk.{bid}.ffn_down_exps", + MODEL_TENSOR.FFN_UP_EXP: "blk.{bid}.ffn_up_exps", + MODEL_TENSOR.LAYER_OUT_NORM: "blk.{bid}.layer_output_norm", + MODEL_TENSOR.SSM_IN: "blk.{bid}.ssm_in", + MODEL_TENSOR.SSM_CONV1D: "blk.{bid}.ssm_conv1d", + MODEL_TENSOR.SSM_X: "blk.{bid}.ssm_x", + MODEL_TENSOR.SSM_DT: "blk.{bid}.ssm_dt", + MODEL_TENSOR.SSM_A: "blk.{bid}.ssm_a", + MODEL_TENSOR.SSM_D: "blk.{bid}.ssm_d", + MODEL_TENSOR.SSM_OUT: "blk.{bid}.ssm_out", + MODEL_TENSOR.ATTN_Q_A: "blk.{bid}.attn_q_a", + MODEL_TENSOR.ATTN_Q_B: "blk.{bid}.attn_q_b", + MODEL_TENSOR.ATTN_KV_A_MQA: "blk.{bid}.attn_kv_a_mqa", + MODEL_TENSOR.ATTN_KV_B: "blk.{bid}.attn_kv_b", + MODEL_TENSOR.ATTN_Q_A_NORM: "blk.{bid}.attn_q_a_norm", + MODEL_TENSOR.ATTN_KV_A_NORM: "blk.{bid}.attn_kv_a_norm", + MODEL_TENSOR.ATTN_SUB_NORM: "blk.{bid}.attn_sub_norm", + MODEL_TENSOR.FFN_SUB_NORM: "blk.{bid}.ffn_sub_norm", + MODEL_TENSOR.DEC_ATTN_NORM: "dec.blk.{bid}.attn_norm", + MODEL_TENSOR.DEC_ATTN_Q: "dec.blk.{bid}.attn_q", + MODEL_TENSOR.DEC_ATTN_K: "dec.blk.{bid}.attn_k", + MODEL_TENSOR.DEC_ATTN_V: "dec.blk.{bid}.attn_v", + MODEL_TENSOR.DEC_ATTN_OUT: "dec.blk.{bid}.attn_o", + MODEL_TENSOR.DEC_ATTN_REL_B: "dec.blk.{bid}.attn_rel_b", + MODEL_TENSOR.DEC_CROSS_ATTN_NORM: "dec.blk.{bid}.cross_attn_norm", + MODEL_TENSOR.DEC_CROSS_ATTN_Q: "dec.blk.{bid}.cross_attn_q", + MODEL_TENSOR.DEC_CROSS_ATTN_K: "dec.blk.{bid}.cross_attn_k", + MODEL_TENSOR.DEC_CROSS_ATTN_V: "dec.blk.{bid}.cross_attn_v", + MODEL_TENSOR.DEC_CROSS_ATTN_OUT: "dec.blk.{bid}.cross_attn_o", + MODEL_TENSOR.DEC_CROSS_ATTN_REL_B: "dec.blk.{bid}.cross_attn_rel_b", + MODEL_TENSOR.DEC_FFN_NORM: "dec.blk.{bid}.ffn_norm", + MODEL_TENSOR.DEC_FFN_GATE: "dec.blk.{bid}.ffn_gate", + MODEL_TENSOR.DEC_FFN_DOWN: "dec.blk.{bid}.ffn_down", + MODEL_TENSOR.DEC_FFN_UP: "dec.blk.{bid}.ffn_up", + MODEL_TENSOR.DEC_OUTPUT_NORM: "dec.output_norm", + MODEL_TENSOR.ENC_ATTN_NORM: "enc.blk.{bid}.attn_norm", + MODEL_TENSOR.ENC_ATTN_Q: "enc.blk.{bid}.attn_q", + MODEL_TENSOR.ENC_ATTN_K: "enc.blk.{bid}.attn_k", + MODEL_TENSOR.ENC_ATTN_V: "enc.blk.{bid}.attn_v", + MODEL_TENSOR.ENC_ATTN_OUT: "enc.blk.{bid}.attn_o", + MODEL_TENSOR.ENC_ATTN_REL_B: "enc.blk.{bid}.attn_rel_b", + MODEL_TENSOR.ENC_FFN_NORM: "enc.blk.{bid}.ffn_norm", + MODEL_TENSOR.ENC_FFN_GATE: "enc.blk.{bid}.ffn_gate", + MODEL_TENSOR.ENC_FFN_DOWN: "enc.blk.{bid}.ffn_down", + MODEL_TENSOR.ENC_FFN_UP: "enc.blk.{bid}.ffn_up", + MODEL_TENSOR.ENC_OUTPUT_NORM: "enc.output_norm", } MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = { @@ -829,6 +891,38 @@ class MODEL_TENSOR(IntEnum): MODEL_TENSOR.ATTN_SUB_NORM, MODEL_TENSOR.FFN_SUB_NORM, ], + MODEL_ARCH.T5: [ + MODEL_TENSOR.TOKEN_EMBD, + MODEL_TENSOR.OUTPUT, + MODEL_TENSOR.DEC_ATTN_NORM, + MODEL_TENSOR.DEC_ATTN_Q, + MODEL_TENSOR.DEC_ATTN_K, + MODEL_TENSOR.DEC_ATTN_V, + MODEL_TENSOR.DEC_ATTN_OUT, + MODEL_TENSOR.DEC_ATTN_REL_B, + MODEL_TENSOR.DEC_CROSS_ATTN_NORM, + MODEL_TENSOR.DEC_CROSS_ATTN_Q, + MODEL_TENSOR.DEC_CROSS_ATTN_K, + MODEL_TENSOR.DEC_CROSS_ATTN_V, + MODEL_TENSOR.DEC_CROSS_ATTN_OUT, + MODEL_TENSOR.DEC_CROSS_ATTN_REL_B, + MODEL_TENSOR.DEC_FFN_NORM, + MODEL_TENSOR.DEC_FFN_GATE, + MODEL_TENSOR.DEC_FFN_DOWN, + MODEL_TENSOR.DEC_FFN_UP, + MODEL_TENSOR.DEC_OUTPUT_NORM, + MODEL_TENSOR.ENC_ATTN_NORM, + MODEL_TENSOR.ENC_ATTN_Q, + MODEL_TENSOR.ENC_ATTN_K, + MODEL_TENSOR.ENC_ATTN_V, + MODEL_TENSOR.ENC_ATTN_OUT, + MODEL_TENSOR.ENC_ATTN_REL_B, + MODEL_TENSOR.ENC_FFN_NORM, + MODEL_TENSOR.ENC_FFN_GATE, + MODEL_TENSOR.ENC_FFN_DOWN, + MODEL_TENSOR.ENC_FFN_UP, + MODEL_TENSOR.ENC_OUTPUT_NORM, + ], # TODO } diff --git a/gguf-py/gguf/gguf_writer.py b/gguf-py/gguf/gguf_writer.py index a697f657b9ac8..3b841a62583a3 100644 --- a/gguf-py/gguf/gguf_writer.py +++ b/gguf-py/gguf/gguf_writer.py @@ -400,6 +400,9 @@ def add_expert_shared_feed_forward_length(self, length: int) -> None: def add_parallel_residual(self, use: bool) -> None: self.add_bool(Keys.LLM.USE_PARALLEL_RESIDUAL.format(arch=self.arch), use) + def add_decoder_start_token_id(self, id: int) -> None: + self.add_uint32(Keys.LLM.DECODER_START_TOKEN_ID.format(arch=self.arch), id) + def add_head_count(self, count: int) -> None: self.add_uint32(Keys.Attention.HEAD_COUNT.format(arch=self.arch), count) @@ -448,6 +451,9 @@ def add_q_lora_rank(self, length: int) -> None: def add_kv_lora_rank(self, length: int) -> None: self.add_uint32(Keys.Attention.KV_LORA_RANK.format(arch=self.arch), length) + def add_relative_attn_buckets_count(self, value: int) -> None: + self.add_uint32(Keys.Attention.REL_BUCKETS_COUNT.format(arch=self.arch), value) + def add_pooling_type(self, value: PoolingType) -> None: self.add_uint32(Keys.LLM.POOLING_TYPE.format(arch=self.arch), value.value) @@ -538,6 +544,12 @@ def add_add_eos_token(self, value: bool) -> None: def add_add_space_prefix(self, value: bool) -> None: self.add_bool(Keys.Tokenizer.ADD_PREFIX, value) + def add_remove_extra_whitespaces(self, value: bool) -> None: + self.add_bool(Keys.Tokenizer.REMOVE_EXTRA_WS, value) + + def add_precompiled_charsmap(self, charsmap: Sequence[bytes]) -> None: + self.add_array(Keys.Tokenizer.PRECOMPILED_CHARSMAP, charsmap) + def add_chat_template(self, value: str | Sequence[Mapping[str, str]]) -> None: if not isinstance(value, str): template_default = None @@ -599,9 +611,12 @@ def _pack_val(self, val: Any, vtype: GGUFValueType, add_vtype: bool) -> bytes: kv_data += self._pack("Q", len(encoded_val)) kv_data += encoded_val elif vtype == GGUFValueType.ARRAY and isinstance(val, Sequence) and val: - ltype = GGUFValueType.get_type(val[0]) - if not all(GGUFValueType.get_type(i) is ltype for i in val[1:]): - raise ValueError("All items in a GGUF array should be of the same type") + if isinstance(val, bytes): + ltype = GGUFValueType.UINT8 + else: + ltype = GGUFValueType.get_type(val[0]) + if not all(GGUFValueType.get_type(i) is ltype for i in val[1:]): + raise ValueError("All items in a GGUF array should be of the same type") kv_data += self._pack("I", ltype) kv_data += self._pack("Q", len(val)) for item in val: diff --git a/gguf-py/gguf/tensor_mapping.py b/gguf-py/gguf/tensor_mapping.py index 350035bd96a17..7b047f241e088 100644 --- a/gguf-py/gguf/tensor_mapping.py +++ b/gguf-py/gguf/tensor_mapping.py @@ -24,6 +24,7 @@ class TensorNameMap: "backbone.embedding", # mamba "backbone.embeddings", # mamba-hf "transformer.in_out_embed", # Grok + "shared", # t5 ), # Token type embeddings @@ -421,6 +422,120 @@ class TensorNameMap: MODEL_TENSOR.FFN_SUB_NORM: ( "model.layers.{bid}.mlp.ffn_layernorm", # bitnet ), + + MODEL_TENSOR.DEC_ATTN_NORM: ( + "decoder.block.{bid}.layer.0.layer_norm", # t5 + ), + + MODEL_TENSOR.DEC_ATTN_Q: ( + "decoder.block.{bid}.layer.0.SelfAttention.q", # t5 + ), + + MODEL_TENSOR.DEC_ATTN_K: ( + "decoder.block.{bid}.layer.0.SelfAttention.k", # t5 + ), + + MODEL_TENSOR.DEC_ATTN_V: ( + "decoder.block.{bid}.layer.0.SelfAttention.v", # t5 + ), + + MODEL_TENSOR.DEC_ATTN_OUT: ( + "decoder.block.{bid}.layer.0.SelfAttention.o", # t5 + ), + + MODEL_TENSOR.DEC_ATTN_REL_B: ( + "decoder.block.{bid}.layer.0.SelfAttention.relative_attention_bias", # t5 + ), + + MODEL_TENSOR.DEC_CROSS_ATTN_NORM: ( + "decoder.block.{bid}.layer.1.layer_norm", # t5 + ), + + MODEL_TENSOR.DEC_CROSS_ATTN_Q: ( + "decoder.block.{bid}.layer.1.EncDecAttention.q", # t5 + ), + + MODEL_TENSOR.DEC_CROSS_ATTN_K: ( + "decoder.block.{bid}.layer.1.EncDecAttention.k", # t5 + ), + + MODEL_TENSOR.DEC_CROSS_ATTN_V: ( + "decoder.block.{bid}.layer.1.EncDecAttention.v", # t5 + ), + + MODEL_TENSOR.DEC_CROSS_ATTN_OUT: ( + "decoder.block.{bid}.layer.1.EncDecAttention.o", # t5 + ), + + MODEL_TENSOR.DEC_CROSS_ATTN_REL_B: ( + "decoder.block.{bid}.layer.1.EncDecAttention.relative_attention_bias", # t5 + ), + + MODEL_TENSOR.DEC_FFN_NORM: ( + "decoder.block.{bid}.layer.2.layer_norm", # t5 + ), + + MODEL_TENSOR.DEC_FFN_GATE: ( + "decoder.block.{bid}.layer.2.DenseReluDense.wi_0", # flan-t5 + ), + + MODEL_TENSOR.DEC_FFN_UP: ( + "decoder.block.{bid}.layer.2.DenseReluDense.wi", # t5 + "decoder.block.{bid}.layer.2.DenseReluDense.wi_1", # flan-t5 + ), + + MODEL_TENSOR.DEC_FFN_DOWN: ( + "decoder.block.{bid}.layer.2.DenseReluDense.wo", # t5 + ), + + MODEL_TENSOR.DEC_OUTPUT_NORM: ( + "decoder.final_layer_norm", # t5 + ), + + MODEL_TENSOR.ENC_ATTN_NORM: ( + "encoder.block.{bid}.layer.0.layer_norm", # t5 + ), + + MODEL_TENSOR.ENC_ATTN_Q: ( + "encoder.block.{bid}.layer.0.SelfAttention.q", # t5 + ), + + MODEL_TENSOR.ENC_ATTN_K: ( + "encoder.block.{bid}.layer.0.SelfAttention.k", # t5 + ), + + MODEL_TENSOR.ENC_ATTN_V: ( + "encoder.block.{bid}.layer.0.SelfAttention.v", # t5 + ), + + MODEL_TENSOR.ENC_ATTN_OUT: ( + "encoder.block.{bid}.layer.0.SelfAttention.o", # t5 + ), + + MODEL_TENSOR.ENC_ATTN_REL_B: ( + "encoder.block.{bid}.layer.0.SelfAttention.relative_attention_bias", # t5 + ), + + MODEL_TENSOR.ENC_FFN_NORM: ( + "encoder.block.{bid}.layer.1.layer_norm", # t5 + ), + + MODEL_TENSOR.ENC_FFN_GATE: ( + "encoder.block.{bid}.layer.1.DenseReluDense.wi_0", # flan-t5 + ), + + MODEL_TENSOR.ENC_FFN_UP: ( + "encoder.block.{bid}.layer.1.DenseReluDense.wi", # t5 + "encoder.block.{bid}.layer.1.DenseReluDense.wi_1", # flan-t5 + ), + + MODEL_TENSOR.ENC_FFN_DOWN: ( + "encoder.block.{bid}.layer.1.DenseReluDense.wo", # t5 + ), + + MODEL_TENSOR.ENC_OUTPUT_NORM: ( + "encoder.final_layer_norm", # t5 + ), } # architecture-specific block mappings From 646ef4a9cfb6f40236d3b9ef07ac03700b6efcc7 Mon Sep 17 00:00:00 2001 From: Yann Follet <131855179+YannFollet@users.noreply.github.com> Date: Mon, 24 Jun 2024 13:30:24 +0800 Subject: [PATCH 002/326] embedding : more cli arguments (#7458) * add parameters for embeddings --embd-normalize --embd-output-format --embd-separator description in the README.md * Update README.md fix tipo * Trailing whitespace * fix json generation, use " not ' * fix merge master * fix code formating group of parameters // embedding print usage for embedding parameters --------- Co-authored-by: Brian --- common/common.cpp | 705 ++++++++----------------------- common/common.h | 9 +- examples/embedding/README.md | 40 ++ examples/embedding/embedding.cpp | 115 +++-- 4 files changed, 313 insertions(+), 556 deletions(-) diff --git a/common/common.cpp b/common/common.cpp index cfdedcbae0cd9..1dc53265134a7 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -273,26 +273,22 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) { return true; } +#define CHECK_ARG if (++i >= argc) { invalid_param = true; return true; } + bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_params & params, int & i, bool & invalid_param) { const char split_delim = ','; llama_sampling_params & sparams = params.sparams; if (arg == "-s" || arg == "--seed") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG // TODO: this is temporary, in the future the sampling state will be moved fully to llama_sampling_context. params.seed = std::stoul(argv[i]); sparams.seed = std::stoul(argv[i]); return true; } if (arg == "-t" || arg == "--threads") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_threads = std::stoi(argv[i]); if (params.n_threads <= 0) { params.n_threads = std::thread::hardware_concurrency(); @@ -300,10 +296,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "-tb" || arg == "--threads-batch") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_threads_batch = std::stoi(argv[i]); if (params.n_threads_batch <= 0) { params.n_threads_batch = std::thread::hardware_concurrency(); @@ -311,10 +304,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "-td" || arg == "--threads-draft") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_threads_draft = std::stoi(argv[i]); if (params.n_threads_draft <= 0) { params.n_threads_draft = std::thread::hardware_concurrency(); @@ -322,10 +312,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "-tbd" || arg == "--threads-batch-draft") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_threads_batch_draft = std::stoi(argv[i]); if (params.n_threads_batch_draft <= 0) { params.n_threads_batch_draft = std::thread::hardware_concurrency(); @@ -333,10 +320,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "-p" || arg == "--prompt") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.prompt = argv[i]; return true; } @@ -349,10 +333,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--prompt-cache") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.path_prompt_cache = argv[i]; return true; } @@ -365,10 +346,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "-bf" || arg == "--binary-file") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG std::ifstream file(argv[i], std::ios::binary); if (!file) { fprintf(stderr, "error: failed to open file '%s'\n", argv[i]); @@ -384,10 +362,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "-f" || arg == "--file") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG std::ifstream file(argv[i]); if (!file) { fprintf(stderr, "error: failed to open file '%s'\n", argv[i]); @@ -403,10 +378,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--in-file") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG std::ifstream file(argv[i]); if (!file) { fprintf(stderr, "error: failed to open file '%s'\n", argv[i]); @@ -417,66 +389,42 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "-n" || arg == "--predict" || arg == "--n-predict") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_predict = std::stoi(argv[i]); return true; } if (arg == "--top-k") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.top_k = std::stoi(argv[i]); return true; } if (arg == "-c" || arg == "--ctx-size") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_ctx = std::stoi(argv[i]); return true; } if (arg == "--grp-attn-n" || arg == "-gan") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.grp_attn_n = std::stoi(argv[i]); return true; } if (arg == "--grp-attn-w" || arg == "-gaw") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.grp_attn_w = std::stoi(argv[i]); return true; } if (arg == "--rope-freq-base") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.rope_freq_base = std::stof(argv[i]); return true; } if (arg == "--rope-freq-scale") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.rope_freq_scale = std::stof(argv[i]); return true; } if (arg == "--rope-scaling") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG std::string value(argv[i]); /**/ if (value == "none") { params.rope_scaling_type = LLAMA_ROPE_SCALING_TYPE_NONE; } else if (value == "linear") { params.rope_scaling_type = LLAMA_ROPE_SCALING_TYPE_LINEAR; } @@ -485,58 +433,37 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--rope-scale") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.rope_freq_scale = 1.0f / std::stof(argv[i]); return true; } if (arg == "--yarn-orig-ctx") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.yarn_orig_ctx = std::stoi(argv[i]); return true; } if (arg == "--yarn-ext-factor") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.yarn_ext_factor = std::stof(argv[i]); return true; } if (arg == "--yarn-attn-factor") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.yarn_attn_factor = std::stof(argv[i]); return true; } if (arg == "--yarn-beta-fast") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.yarn_beta_fast = std::stof(argv[i]); return true; } if (arg == "--yarn-beta-slow") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.yarn_beta_slow = std::stof(argv[i]); return true; } if (arg == "--pooling") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG std::string value(argv[i]); /**/ if (value == "none") { params.pooling_type = LLAMA_POOLING_TYPE_NONE; } else if (value == "mean") { params.pooling_type = LLAMA_POOLING_TYPE_MEAN; } @@ -546,157 +473,100 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--defrag-thold" || arg == "-dt") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.defrag_thold = std::stof(argv[i]); return true; } if (arg == "--samplers") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG const auto sampler_names = string_split(argv[i], ';'); sparams.samplers_sequence = llama_sampling_types_from_names(sampler_names, true); return true; } if (arg == "--sampling-seq") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.samplers_sequence = llama_sampling_types_from_chars(argv[i]); return true; } if (arg == "--top-p") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.top_p = std::stof(argv[i]); return true; } if (arg == "--min-p") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.min_p = std::stof(argv[i]); return true; } if (arg == "--temp") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.temp = std::stof(argv[i]); sparams.temp = std::max(sparams.temp, 0.0f); return true; } if (arg == "--tfs") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.tfs_z = std::stof(argv[i]); return true; } if (arg == "--typical") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.typical_p = std::stof(argv[i]); return true; } if (arg == "--repeat-last-n") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.penalty_last_n = std::stoi(argv[i]); sparams.n_prev = std::max(sparams.n_prev, sparams.penalty_last_n); return true; } if (arg == "--repeat-penalty") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.penalty_repeat = std::stof(argv[i]); return true; } if (arg == "--frequency-penalty") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.penalty_freq = std::stof(argv[i]); return true; } if (arg == "--presence-penalty") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.penalty_present = std::stof(argv[i]); return true; } if (arg == "--dynatemp-range") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.dynatemp_range = std::stof(argv[i]); return true; } if (arg == "--dynatemp-exp") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.dynatemp_exponent = std::stof(argv[i]); return true; } if (arg == "--mirostat") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.mirostat = std::stoi(argv[i]); return true; } if (arg == "--mirostat-lr") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.mirostat_eta = std::stof(argv[i]); return true; } if (arg == "--mirostat-ent") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.mirostat_tau = std::stof(argv[i]); return true; } if (arg == "--cfg-negative-prompt") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.cfg_negative_prompt = argv[i]; return true; } if (arg == "--cfg-negative-prompt-file") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG std::ifstream file(argv[i]); if (!file) { fprintf(stderr, "error: failed to open file '%s'\n", argv[i]); @@ -710,203 +580,125 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--cfg-scale") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.cfg_scale = std::stof(argv[i]); return true; } if (arg == "-b" || arg == "--batch-size") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_batch = std::stoi(argv[i]); return true; } if (arg == "-ub" || arg == "--ubatch-size") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_ubatch = std::stoi(argv[i]); return true; } if (arg == "--keep") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_keep = std::stoi(argv[i]); return true; } if (arg == "--draft") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_draft = std::stoi(argv[i]); return true; } if (arg == "--chunks") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_chunks = std::stoi(argv[i]); return true; } if (arg == "-np" || arg == "--parallel") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_parallel = std::stoi(argv[i]); return true; } if (arg == "-ns" || arg == "--sequences") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_sequences = std::stoi(argv[i]); return true; } if (arg == "--p-split" || arg == "-ps") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.p_split = std::stof(argv[i]); return true; } if (arg == "-m" || arg == "--model") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.model = argv[i]; return true; } if (arg == "-md" || arg == "--model-draft") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.model_draft = argv[i]; return true; } if (arg == "-a" || arg == "--alias") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.model_alias = argv[i]; return true; } if (arg == "-mu" || arg == "--model-url") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.model_url = argv[i]; return true; } if (arg == "-hfr" || arg == "--hf-repo") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.hf_repo = argv[i]; return true; } if (arg == "-hff" || arg == "--hf-file") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.hf_file = argv[i]; return true; } if (arg == "--lora") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.lora_adapter.emplace_back(argv[i], 1.0f); params.use_mmap = false; return true; } if (arg == "--lora-scaled") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG const char* lora_adapter = argv[i]; - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.lora_adapter.emplace_back(lora_adapter, std::stof(argv[i])); params.use_mmap = false; return true; } if (arg == "--lora-base") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.lora_base = argv[i]; return true; } if (arg == "--control-vector") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.control_vectors.push_back({ 1.0f, argv[i], }); return true; } if (arg == "--control-vector-scaled") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG const char* fname = argv[i]; - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.control_vectors.push_back({ std::stof(argv[i]), fname, }); return true; } if (arg == "--control-vector-layer-range") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.control_vector_layer_start = std::stoi(argv[i]); - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.control_vector_layer_end = std::stoi(argv[i]); return true; } if (arg == "--mmproj") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.mmproj = argv[i]; return true; } if (arg == "--image") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.image.emplace_back(argv[i]); return true; } @@ -922,6 +714,21 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa params.embedding = true; return true; } + if (arg == "--embd-normalize") { + CHECK_ARG + params.embd_normalize = std::stoi(argv[i]); + return true; + } + if (arg == "--embd-output-format") { + CHECK_ARG + params.embd_out = argv[i]; + return true; + } + if (arg == "--embd-separator") { + CHECK_ARG + params.embd_sep = argv[i]; + return true; + } if (arg == "-if" || arg == "--interactive-first") { params.interactive_first = true; return true; @@ -975,10 +782,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "-ngl" || arg == "--gpu-layers" || arg == "--n-gpu-layers") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_gpu_layers = std::stoi(argv[i]); if (!llama_supports_gpu_offload()) { fprintf(stderr, "warning: not compiled with GPU offload support, --gpu-layers option will be ignored\n"); @@ -987,10 +791,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "-ngld" || arg == "--gpu-layers-draft" || arg == "--gpu-layers-draft") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_gpu_layers_draft = std::stoi(argv[i]); if (!llama_supports_gpu_offload()) { fprintf(stderr, "warning: not compiled with GPU offload support, --gpu-layers-draft option will be ignored\n"); @@ -999,10 +800,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--main-gpu" || arg == "-mg") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.main_gpu = std::stoi(argv[i]); #ifndef GGML_USE_CUDA_SYCL_VULKAN fprintf(stderr, "warning: llama.cpp was compiled without CUDA/SYCL/Vulkan. Setting the main GPU has no effect.\n"); @@ -1010,10 +808,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--split-mode" || arg == "-sm") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG std::string arg_next = argv[i]; if (arg_next == "none") { params.split_mode = LLAMA_SPLIT_MODE_NONE; @@ -1038,10 +833,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--tensor-split" || arg == "-ts") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG std::string arg_next = argv[i]; // split string by , and / @@ -1066,10 +858,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--rpc") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.rpc_servers = argv[i]; return true; } @@ -1078,10 +867,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--numa") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG std::string value(argv[i]); /**/ if (value == "distribute" || value == "") { params.numa = GGML_NUMA_STRATEGY_DISTRIBUTE; } else if (value == "isolate") { params.numa = GGML_NUMA_STRATEGY_ISOLATE; } @@ -1094,10 +880,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--verbosity") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.verbosity = std::stoi(argv[i]); return true; } @@ -1110,18 +893,12 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "-r" || arg == "--reverse-prompt") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.antiprompt.emplace_back(argv[i]); return true; } if (arg == "-ld" || arg == "--logdir") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.logdir = argv[i]; if (params.logdir.back() != DIRECTORY_SEPARATOR) { @@ -1130,26 +907,17 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "-lcs" || arg == "--lookup-cache-static") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.lookup_cache_static = argv[i]; return true; } if (arg == "-lcd" || arg == "--lookup-cache-dynamic") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.lookup_cache_dynamic = argv[i]; return true; } if (arg == "--save-all-logits" || arg == "--kl-divergence-base") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.logits_file = argv[i]; return true; } @@ -1158,26 +926,17 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--ppl-stride") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.ppl_stride = std::stoi(argv[i]); return true; } if (arg == "--ppl-output-type") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.ppl_output_type = std::stoi(argv[i]); return true; } if (arg == "-ptc" || arg == "--print-token-count") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_print = std::stoi(argv[i]); return true; } @@ -1190,10 +949,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--hellaswag-tasks") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.hellaswag_tasks = std::stoi(argv[i]); return true; } @@ -1202,10 +958,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--winogrande-tasks") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.winogrande_tasks = std::stoi(argv[i]); return true; } @@ -1214,10 +967,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--multiple-choice-tasks") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.multiple_choice_tasks = std::stoi(argv[i]); return true; } @@ -1234,10 +984,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "-l" || arg == "--logit-bias") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG std::stringstream ss(argv[i]); llama_token key; char sign; @@ -1270,34 +1017,22 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--in-prefix") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.input_prefix = argv[i]; return true; } if (arg == "--in-suffix") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.input_suffix = argv[i]; return true; } if (arg == "--grammar") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.grammar = argv[i]; return true; } if (arg == "--grammar-file") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG std::ifstream file(argv[i]); if (!file) { fprintf(stderr, "error: failed to open file '%s'\n", argv[i]); @@ -1312,18 +1047,12 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "-j" || arg == "--json-schema") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG sparams.grammar = json_schema_to_grammar(json::parse(argv[i])); return true; } if (arg == "--override-kv") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG if (!string_parse_kv_override(argv[i], params.kv_overrides)) { fprintf(stderr, "error: Invalid type for KV override: %s\n", argv[i]); invalid_param = true; @@ -1332,42 +1061,27 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--host") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.hostname = argv[i]; return true; } if (arg == "--port") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.port = std::stoi(argv[i]); return true; } if (arg == "--path") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.public_path = argv[i]; return true; } if (arg == "--api-key") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.api_keys.push_back(argv[i]); return true; } if (arg == "--api-key-file") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG std::ifstream key_file(argv[i]); if (!key_file) { fprintf(stderr, "error: failed to open file '%s'\n", argv[i]); @@ -1384,43 +1098,28 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--ssl-key-file") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.ssl_file_key = argv[i]; return true; } if (arg == "--ssl-cert-file") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.ssl_file_cert = argv[i]; return true; } if (arg == "--timeout" || arg == "-to") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.timeout_read = std::stoi(argv[i]); params.timeout_write = std::stoi(argv[i]); return true; } if (arg == "--threads-http") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_threads_http = std::stoi(argv[i]); return true; } if (arg == "-spf" || arg == "--system-prompt-file") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG std::ifstream file(argv[i]); if (!file) { fprintf(stderr, "error: failed to open file '%s'\n", argv[i]); @@ -1437,10 +1136,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--log-format") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG if (std::strcmp(argv[i], "json") == 0) { params.log_json = true; } else if (std::strcmp(argv[i], "text") == 0) { @@ -1460,10 +1156,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--slot-save-path") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.slot_save_path = argv[i]; // if doesn't end with DIRECTORY_SEPARATOR, add it if (!params.slot_save_path.empty() && params.slot_save_path[params.slot_save_path.size() - 1] != DIRECTORY_SEPARATOR) { @@ -1472,10 +1165,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--chat-template") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG if (!llama_chat_verify_template(argv[i])) { fprintf(stderr, "error: the supplied chat template is not supported: %s\n", argv[i]); fprintf(stderr, "note: llama.cpp does not use jinja parser, we only support commonly used templates\n"); @@ -1486,10 +1176,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--slot-prompt-similarity" || arg == "-sps") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.slot_prompt_similarity = std::stof(argv[i]); return true; } @@ -1498,37 +1185,25 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "-npp") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG auto p = string_split(argv[i], split_delim); params.n_pp.insert(params.n_pp.end(), p.begin(), p.end()); return true; } if (arg == "-ntg") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG auto p = string_split(argv[i], split_delim); params.n_tg.insert(params.n_tg.end(), p.begin(), p.end()); return true; } if (arg == "-npl") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG auto p = string_split(argv[i], split_delim); params.n_pl.insert(params.n_pl.end(), p.begin(), p.end()); return true; } if (arg == "--context-file") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG std::ifstream file(argv[i], std::ios::binary); if (!file) { fprintf(stderr, "error: failed to open file '%s'\n", argv[i]); @@ -1539,59 +1214,38 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--chunk-size") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.chunk_size = std::stoi(argv[i]); return true; } if (arg == "--chunk-separator") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.chunk_separator = argv[i]; return true; } if (arg == "--junk") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_junk = std::stoi(argv[i]); return true; } if (arg == "--pos") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.i_pos = std::stoi(argv[i]); return true; } if (arg == "-o" || arg == "--output" || arg == "--output-file") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.out_file = argv[i]; params.cvector_outfile = argv[i]; return true; } if (arg == "-ofreq" || arg == "--output-frequency") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_out_freq = std::stoi(argv[i]); return true; } if (arg == "--save-frequency") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_save_freq = std::stoi(argv[i]); return true; } @@ -1604,59 +1258,38 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } if (arg == "--chunk" || arg == "--from-chunk") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.i_chunk = std::stoi(argv[i]); return true; } // cvector params if (arg == "--completions-file") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.cvector_completions_file = argv[i]; return true; } if (arg == "--positive-file") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.cvector_positive_file = argv[i]; return true; } if (arg == "--negative-file") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.cvector_negative_file = argv[i]; return true; } if (arg == "--completions") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_completions = std::stoi(argv[i]); return true; } if (arg == "--pca-batch") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_pca_batch = std::stoi(argv[i]); return true; } if (arg == "--pca-iter") { - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG params.n_pca_iterations = std::stoi(argv[i]); return true; } @@ -1671,10 +1304,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa // We have a matching known parameter requiring an argument, // now we need to check if there is anything after this argv // and flag invalid_param or parse it. - if (++i >= argc) { - invalid_param = true; - return true; - } + CHECK_ARG if (!log_param_pair_parse( /*check_but_dont_parse*/ false, argv[i - 1], argv[i])) { invalid_param = true; return true; @@ -1944,6 +1574,11 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param options.push_back({ "bench", "-ntg n0,n1,...", "number of text generation tokens" }); options.push_back({ "bench", "-npl n0,n1,...", "number of parallel prompts" }); + options.push_back({ "embedding" }); + options.push_back({ "embedding", " --embd-normalize", "normalisation for embendings (default: %d) (-1=none, 0=max absolute int16, 1=taxicab, 2=euclidean, >2=p-norm)", params.embd_normalize }); + options.push_back({ "embedding", " --embd-output-format", "empty = default, \"array\" = [[],[]...], \"json\" = openai style, \"json+\" = same \"json\" + cosine similarity matrix" }); + options.push_back({ "embedding", " --embd-separator", "separator of embendings (default \\n) for example \"<#sep#>\"" }); + options.push_back({ "server" }); options.push_back({ "server", " --host HOST", "ip address to listen (default: %s)", params.hostname.c_str() }); options.push_back({ "server", " --port PORT", "port to listen (default: %d)", params.port }); @@ -3052,14 +2687,34 @@ void llama_kv_cache_dump_view_seqs(const llama_kv_cache_view & view, int row_siz // Embedding utils // -void llama_embd_normalize(const float * inp, float * out, int n) { +void llama_embd_normalize(const float * inp, float * out, int n, int embd_norm) { double sum = 0.0; - for (int i = 0; i < n; i++) { - sum += inp[i] * inp[i]; + + switch (embd_norm) { + case -1: // no normalisation + sum = 1.0; + break; + case 0: // max absolute + for (int i = 0; i < n; i++) { + if (sum < std::abs(inp[i])) sum = std::abs(inp[i]); + } + sum /= 32760.0; // make an int16 range + break; + case 2: // euclidean + for (int i = 0; i < n; i++) { + sum += inp[i] * inp[i]; + } + sum = std::sqrt(sum); + break; + default: // p-norm (euclidean is p-norm p=2) + for (int i = 0; i < n; i++) { + sum += std::pow(std::abs(inp[i]), embd_norm); + } + sum = std::pow(sum, 1.0 / embd_norm); + break; } - sum = sqrt(sum); - const float norm = sum > 0.0 ? 1.0f / sum : 0.0f; + const float norm = sum > 0.0 ? 1.0 / sum : 0.0f; for (int i = 0; i < n; i++) { out[i] = inp[i] * norm; @@ -3077,6 +2732,14 @@ float llama_embd_similarity_cos(const float * embd1, const float * embd2, int n) sum2 += embd2[i] * embd2[i]; } + // Handle the case where one or both vectors are zero vectors + if (sum1 == 0.0 || sum2 == 0.0) { + if (sum1 == 0.0 && sum2 == 0.0) { + return 1.0f; // two zero vectors are similar + } + return 0.0f; + } + return sum / (sqrt(sum1) * sqrt(sum2)); } diff --git a/common/common.h b/common/common.h index 9a1dc4a2fe4c1..a5c738f8b643f 100644 --- a/common/common.h +++ b/common/common.h @@ -152,7 +152,6 @@ struct gpt_params { bool prompt_cache_all = false; // save user input and generations to prompt cache bool prompt_cache_ro = false; // open the prompt cache read-only and do not update it - bool embedding = false; // get only sentence embedding bool escape = true; // escape "\n", "\r", "\t", "\'", "\"", and "\\" bool multiline_input = false; // reverse the usage of `\` bool simple_io = false; // improves compatibility with subprocesses and limited consoles @@ -179,6 +178,12 @@ struct gpt_params { std::string mmproj = ""; // path to multimodal projector std::vector image; // path to image file(s) + // embedding + bool embedding = false; // get only sentence embedding + int32_t embd_normalize = 2; // normalisation for embendings (-1=none, 0=max absolute int16, 1=taxicab, 2=euclidean, >2=p-norm) + std::string embd_out = ""; // empty = default, "array" = [[],[]...], "json" = openai style, "json+" = same "json" + cosine similarity matrix + std::string embd_sep = "\n"; // separator of embendings + // server params int32_t port = 8080; // server listens on this network port int32_t timeout_read = 600; // http read timeout in seconds @@ -377,7 +382,7 @@ void llama_kv_cache_dump_view_seqs(const llama_kv_cache_view & view, int row_siz // Embedding utils // -void llama_embd_normalize(const float * inp, float * out, int n); +void llama_embd_normalize(const float * inp, float * out, int n, int embd_norm = 2); float llama_embd_similarity_cos(const float * embd1, const float * embd2, int n); diff --git a/examples/embedding/README.md b/examples/embedding/README.md index 2298ec3e7fcb3..86df189587846 100644 --- a/examples/embedding/README.md +++ b/examples/embedding/README.md @@ -19,3 +19,43 @@ llama-embedding.exe -m ./path/to/model --log-disable -p "Hello World!" 2>$null ``` The above command will output space-separated float values. + +## extra parameters +### --embd-normalize $integer$ +| $integer$ | description | formula | +|-----------|---------------------|---------| +| $-1$ | none | +| $0$ | max absolute int16 | $\Large{{32760 * x_i} \over\max \lvert x_i\rvert}$ +| $1$ | taxicab | $\Large{x_i \over\sum \lvert x_i\rvert}$ +| $2$ | euclidean (default) | $\Large{x_i \over\sqrt{\sum x_i^2}}$ +| $>2$ | p-norm | $\Large{x_i \over\sqrt[p]{\sum \lvert x_i\rvert^p}}$ + +### --embd-output-format $'string'$ +| $'string'$ | description | | +|------------|------------------------------|--| +| '' | same as before | (default) +| 'array' | single embeddings | $[[x_1,...,x_n]]$ +| | multiple embeddings | $[[x_1,...,x_n],[x_1,...,x_n],...,[x_1,...,x_n]]$ +| 'json' | openai style | +| 'json+' | add cosine similarity matrix | + +### --embd-separator $"string"$ +| $"string"$ | | +|--------------|-| +| "\n" | (default) +| "<#embSep#>" | for exemple +| "<#sep#>" | other exemple + +## examples +### Unix-based systems (Linux, macOS, etc.): + +```bash +./embedding -p 'Castle<#sep#>Stronghold<#sep#>Dog<#sep#>Cat' --embd-separator '<#sep#>' --embd-normalize 2 --embd-output-format '' -m './path/to/model.gguf' --n-gpu-layers 99 --log-disable 2>/dev/null +``` + +### Windows: + +```powershell +embedding.exe -p 'Castle<#sep#>Stronghold<#sep#>Dog<#sep#>Cat' --embd-separator '<#sep#>' --embd-normalize 2 --embd-output-format '' -m './path/to/model.gguf' --n-gpu-layers 99 --log-disable 2>/dev/null +``` + diff --git a/examples/embedding/embedding.cpp b/examples/embedding/embedding.cpp index b4b73c0175cda..1466e5b2bc512 100644 --- a/examples/embedding/embedding.cpp +++ b/examples/embedding/embedding.cpp @@ -7,13 +7,19 @@ #pragma warning(disable: 4244 4267) // possible loss of data #endif -static std::vector split_lines(const std::string & s) { - std::string line; +static std::vector split_lines(const std::string & s, const std::string & separator = "\n") { std::vector lines; - std::stringstream ss(s); - while (std::getline(ss, line)) { - lines.push_back(line); + size_t start = 0; + size_t end = s.find(separator); + + while (end != std::string::npos) { + lines.push_back(s.substr(start, end - start)); + start = end + separator.length(); + end = s.find(separator, start); } + + lines.push_back(s.substr(start)); // Add the last part + return lines; } @@ -24,7 +30,7 @@ static void batch_add_seq(llama_batch & batch, const std::vector & toke } } -static void batch_decode(llama_context * ctx, llama_batch & batch, float * output, int n_seq, int n_embd) { +static void batch_decode(llama_context * ctx, llama_batch & batch, float * output, int n_seq, int n_embd, int embd_norm) { // clear previous kv_cache values (irrelevant for embeddings) llama_kv_cache_clear(ctx); @@ -44,13 +50,7 @@ static void batch_decode(llama_context * ctx, llama_batch & batch, float * outpu GGML_ASSERT(embd != NULL && "failed to get sequence embeddings"); float * out = output + batch.seq_id[i][0] * n_embd; - //TODO: I would also add a parameter here to enable normalization or not. - /*fprintf(stdout, "unnormalized_embedding:"); - for (int hh = 0; hh < n_embd; hh++) { - fprintf(stdout, "%9.6f ", embd[hh]); - } - fprintf(stdout, "\n");*/ - llama_embd_normalize(embd, out, n_embd); + llama_embd_normalize(embd, out, n_embd, embd_norm); } } @@ -110,7 +110,7 @@ int main(int argc, char ** argv) { } // split the prompt into lines - std::vector prompts = split_lines(params.prompt); + std::vector prompts = split_lines(params.prompt, params.embd_sep); // max batch size const uint64_t n_batch = params.n_batch; @@ -170,7 +170,7 @@ int main(int argc, char ** argv) { // encode if at capacity if (batch.n_tokens + n_toks > n_batch) { float * out = emb + p * n_embd; - batch_decode(ctx, batch, out, s, n_embd); + batch_decode(ctx, batch, out, s, n_embd, params.embd_normalize); llama_batch_clear(batch); p += s; s = 0; @@ -183,29 +183,78 @@ int main(int argc, char ** argv) { // final batch float * out = emb + p * n_embd; - batch_decode(ctx, batch, out, s, n_embd); - - // print the first part of the embeddings or for a single prompt, the full embedding - fprintf(stdout, "\n"); - for (int j = 0; j < n_prompts; j++) { - fprintf(stdout, "embedding %d: ", j); - for (int i = 0; i < (n_prompts > 1 ? std::min(16, n_embd) : n_embd); i++) { - fprintf(stdout, "%9.6f ", emb[j * n_embd + i]); - } - fprintf(stdout, "\n"); - } + batch_decode(ctx, batch, out, s, n_embd, params.embd_normalize); - // print cosine similarity matrix - if (n_prompts > 1) { + if (params.embd_out.empty()) { + // print the first part of the embeddings or for a single prompt, the full embedding fprintf(stdout, "\n"); - printf("cosine similarity matrix:\n\n"); - for (int i = 0; i < n_prompts; i++) { - for (int j = 0; j < n_prompts; j++) { - float sim = llama_embd_similarity_cos(emb + i * n_embd, emb + j * n_embd, n_embd); - fprintf(stdout, "%6.2f ", sim); + for (int j = 0; j < n_prompts; j++) { + fprintf(stdout, "embedding %d: ", j); + for (int i = 0; i < (n_prompts > 1 ? std::min(16, n_embd) : n_embd); i++) { + if (params.embd_normalize == 0) { + fprintf(stdout, "%6.0f ", emb[j * n_embd + i]); + } else { + fprintf(stdout, "%9.6f ", emb[j * n_embd + i]); + } + } + fprintf(stdout, "\n"); + } + + // print cosine similarity matrix + if (n_prompts > 1) { + fprintf(stdout, "\n"); + printf("cosine similarity matrix:\n\n"); + for (int i = 0; i < n_prompts; i++) { + fprintf(stdout, "%6.6s ", prompts[i].c_str()); } fprintf(stdout, "\n"); + for (int i = 0; i < n_prompts; i++) { + for (int j = 0; j < n_prompts; j++) { + float sim = llama_embd_similarity_cos(emb + i * n_embd, emb + j * n_embd, n_embd); + fprintf(stdout, "%6.2f ", sim); + } + fprintf(stdout, "%1.10s", prompts[i].c_str()); + fprintf(stdout, "\n"); + } + } + } + + if (params.embd_out == "json" || params.embd_out == "json+" || params.embd_out == "array") { + const bool notArray = params.embd_out != "array"; + + fprintf(stdout, notArray ? "{\n \"object\": \"list\",\n \"data\": [\n" : "["); + for (int j = 0;;) { // at least one iteration (one prompt) + if (notArray) fprintf(stdout, " {\n \"object\": \"embedding\",\n \"index\": %d,\n \"embedding\": ",j); + fprintf(stdout, "["); + for (int i = 0;;) { // at least one iteration (n_embd > 0) + fprintf(stdout, params.embd_normalize == 0 ? "%1.0f" : "%1.7f", emb[j * n_embd + i]); + i++; + if (i < n_embd) fprintf(stdout, ","); else break; + } + fprintf(stdout, notArray ? "]\n }" : "]"); + j++; + if (j < n_prompts) fprintf(stdout, notArray ? ",\n" : ","); else break; } + fprintf(stdout, notArray ? "\n ]" : "]\n"); + + if (params.embd_out == "json+" && n_prompts > 1) { + fprintf(stdout, ",\n \"cosineSimilarity\": [\n"); + for (int i = 0;;) { // at least two iteration (n_prompts > 1) + fprintf(stdout, " ["); + for (int j = 0;;) { // at least two iteration (n_prompts > 1) + float sim = llama_embd_similarity_cos(emb + i * n_embd, emb + j * n_embd, n_embd); + fprintf(stdout, "%6.2f", sim); + j++; + if (j < n_prompts) fprintf(stdout, ", "); else break; + } + fprintf(stdout, " ]"); + i++; + if (i < n_prompts) fprintf(stdout, ",\n"); else break; + } + fprintf(stdout, "\n ]"); + } + + if (notArray) fprintf(stdout, "\n}\n"); } // clean up From 8cb508d0d5c024e12692370d85237b45469a004b Mon Sep 17 00:00:00 2001 From: slaren Date: Mon, 24 Jun 2024 07:36:11 +0200 Subject: [PATCH 003/326] disable publishing the full-rocm docker image (#8083) --- .github/workflows/docker.yml | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/.github/workflows/docker.yml b/.github/workflows/docker.yml index 6244b481210a0..b3efe0084fe15 100644 --- a/.github/workflows/docker.yml +++ b/.github/workflows/docker.yml @@ -33,15 +33,13 @@ jobs: - { tag: "light", dockerfile: ".devops/llama-cli.Dockerfile", platforms: "linux/amd64,linux/arm64" } - { tag: "server", dockerfile: ".devops/llama-server.Dockerfile", platforms: "linux/amd64,linux/arm64" } - { tag: "full", dockerfile: ".devops/full.Dockerfile", platforms: "linux/amd64,linux/arm64" } - # NOTE(canardletter): The CUDA builds on arm64 are very slow, so I - # have disabled them for now until the reason why - # is understood. - { tag: "light-cuda", dockerfile: ".devops/llama-cli-cuda.Dockerfile", platforms: "linux/amd64" } - { tag: "server-cuda", dockerfile: ".devops/llama-server-cuda.Dockerfile", platforms: "linux/amd64" } - { tag: "full-cuda", dockerfile: ".devops/full-cuda.Dockerfile", platforms: "linux/amd64" } - { tag: "light-rocm", dockerfile: ".devops/llama-cli-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" } - { tag: "server-rocm", dockerfile: ".devops/llama-server-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" } - - { tag: "full-rocm", dockerfile: ".devops/full-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" } + # Note: the full-rocm image is failing due to a "no space left on device" error. It is disabled for now to allow the workflow to complete. + #- { tag: "full-rocm", dockerfile: ".devops/full-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" } - { tag: "light-intel", dockerfile: ".devops/llama-cli-intel.Dockerfile", platforms: "linux/amd64" } - { tag: "server-intel", dockerfile: ".devops/llama-server-intel.Dockerfile", platforms: "linux/amd64" } steps: From 52fc8705a0617452df08333e1161838726c322b4 Mon Sep 17 00:00:00 2001 From: Christian Zhou-Zheng <59622928+christianazinn@users.noreply.github.com> Date: Mon, 24 Jun 2024 05:42:03 -0400 Subject: [PATCH 004/326] Option to split during conversion (#6942) * support splits in convert.py * Support split by size and dry run to write estimated shards/filesizes * Move split functionality to new GGUFManager class * fix improper function signature * tentative push of convert-hf-to-gguf support * resolve merge + SplitArguments for easier parsing * Fix eager tensor memory leak and remove convert.py changes Removed a memory leak caused by unexpected reference retention to eager tensors. Also removed GGUFManager functionality in convert.py in favor of specializing for convert-hf-to-gguf.py. * refactor SplitStrategy to be a deque Instead of having SplitStrategy have a `data` field that is a deque, just have SplitStrategy be a subclass of deque itself. * fix Q8 quantization * remove unnecessary imports in gguf_manager * fix final? merge issue * fix gguf_writer placement and remove comments * oops, actually fix gguf_writer placement * reduce duplicated code from gguf_writer * further simplify GGUFManager * simplify even further and standardize with GGUFWriter * reduce diffs with master * form shards while adding tensors, SHA256 sums agree with master * re-add type hint Co-authored-by: compilade * GGUFWriter compatibility fix Co-authored-by: compilade * Shard dataclass and un-negative dont_add_architecture * type consistency in format_n_bytes_to_str * move kv keys to constants.py * make pathlib explicit * base-1024 bytes to base-1000 * rename GGUFManager to GGUFWriterSplit * Update gguf-py/gguf/constants.py Co-authored-by: compilade * fix convert-hf-to-gguf.py permissions * fix line endings * Update gguf-py/gguf/gguf_writer_split.py Co-authored-by: compilade * convert-hf : restore executable file permission * examples/convert-legacy-llama.py: restore executable file permission * reinstate original gguf package import and fix type annotation * attempt to appease the linter * attempt 2 to appease the linter * attempt 3 to appease the linter * comma consistency * Update convert-hf-to-gguf.py Co-authored-by: compilade * edit cmd line args * use simplification from #7827 * kv/ti data are still wrong * try to refactor kv data (still fails) * fix ti data messiness * tidy up * fix linting * actually make the linter happy * cleanup round 1 * remove SplitStrategy, SplitArguments * appease linter * fix typing and clean up * fix linting * Update gguf-py/gguf/gguf_writer.py Co-authored-by: compilade * progress bar, fix split logic * Update gguf-py/gguf/gguf_writer.py Co-authored-by: compilade * catch oversights * Update gguf-py/gguf/gguf_writer.py Co-authored-by: compilade * Update gguf-py/gguf/gguf_writer.py Co-authored-by: compilade * Update gguf-py/gguf/gguf_writer.py Co-authored-by: compilade * Update gguf-py/gguf/gguf_writer.py Co-authored-by: compilade * Update gguf-py/gguf/gguf_writer.py Co-authored-by: compilade * swap bar orders * Update gguf-py/gguf/gguf_writer.py Co-authored-by: compilade * Update gguf-py/gguf/gguf_writer.py Co-authored-by: compilade * compatibility fix * Update gguf-py/gguf/gguf_writer.py Co-authored-by: compilade * Update convert-hf-to-gguf.py Co-authored-by: compilade --------- Co-authored-by: Brian Co-authored-by: compilade --- convert-hf-to-gguf.py | 59 +++++++-- gguf-py/gguf/constants.py | 5 + gguf-py/gguf/gguf_writer.py | 233 +++++++++++++++++++++++++----------- 3 files changed, 223 insertions(+), 74 deletions(-) diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py index ebfc1a1f94b78..c26fad9307f15 100755 --- a/convert-hf-to-gguf.py +++ b/convert-hf-to-gguf.py @@ -65,7 +65,8 @@ class Model: # subclasses should define this! model_arch: gguf.MODEL_ARCH - def __init__(self, dir_model: Path, ftype: gguf.LlamaFileType, fname_out: Path, is_big_endian: bool, use_temp_file: bool, eager: bool, model_name: str | None): + def __init__(self, dir_model: Path, ftype: gguf.LlamaFileType, fname_out: Path, is_big_endian: bool, use_temp_file: bool, eager: bool, + model_name: str | None, split_max_tensors: int = 0, split_max_size: int = 0, dry_run: bool = False, small_first_shard: bool = False): if type(self) is Model: raise TypeError(f"{type(self).__name__!r} should not be directly instantiated") self.dir_model = dir_model @@ -96,7 +97,8 @@ def __init__(self, dir_model: Path, ftype: gguf.LlamaFileType, fname_out: Path, ftype_lw: str = ftype_up.lower() # allow templating the file name with the output ftype, useful with the "auto" ftype self.fname_out = fname_out.parent / fname_out.name.format(ftype_lw, outtype=ftype_lw, ftype=ftype_lw, OUTTYPE=ftype_up, FTYPE=ftype_up) - self.gguf_writer = gguf.GGUFWriter(path=None, arch=gguf.MODEL_ARCH_NAMES[self.model_arch], endianess=self.endianess, use_temp_file=self.use_temp_file) + self.gguf_writer = gguf.GGUFWriter(path=None, arch=gguf.MODEL_ARCH_NAMES[self.model_arch], endianess=self.endianess, use_temp_file=self.use_temp_file, + split_max_tensors=split_max_tensors, split_max_size=split_max_size, dry_run=dry_run, small_first_shard=small_first_shard) @classmethod def __init_subclass__(cls): @@ -332,6 +334,8 @@ def write(self): self.gguf_writer.close() def write_vocab(self): + if len(self.gguf_writer.tensors) != 1: + raise ValueError('Splitting the vocabulary is not supported') self.gguf_writer.write_header_to_file(self.fname_out) self.gguf_writer.write_kv_data_to_file() self.gguf_writer.close() @@ -2974,10 +2978,44 @@ def parse_args() -> argparse.Namespace: "--verbose", action="store_true", help="increase output verbosity", ) + parser.add_argument( + "--split-max-tensors", type=int, default=0, + help="max tensors in each split", + ) + parser.add_argument( + "--split-max-size", type=str, default="0", + help="max size per split N(M|G)", + ) + parser.add_argument( + "--dry-run", action="store_true", + help="only print out a split plan and exit, without writing any new files", + ) + parser.add_argument( + "--no-tensor-first-split", action="store_true", + help="do not add tensors to the first split (disabled by default)" + ) return parser.parse_args() +def split_str_to_n_bytes(split_str: str) -> int: + if split_str.endswith("K"): + n = int(split_str[:-1]) * 1000 + elif split_str.endswith("M"): + n = int(split_str[:-1]) * 1000 * 1000 + elif split_str.endswith("G"): + n = int(split_str[:-1]) * 1000 * 1000 * 1000 + elif split_str.isnumeric(): + n = int(split_str) + else: + raise ValueError(f"Invalid split size: {split_str}, must be a number, optionally followed by K, M, or G") + + if n < 0: + raise ValueError(f"Invalid split size: {split_str}, must be positive") + + return n + + def main() -> None: args = parse_args() @@ -3010,6 +3048,10 @@ def main() -> None: "auto": gguf.LlamaFileType.GUESSED, } + if args.use_temp_file and (args.split_max_tensors > 0 or args.split_max_size != "0"): + logger.error("Error: Cannot use temp file when splitting") + sys.exit(1) + if args.outfile is not None: fname_out = args.outfile else: @@ -3027,7 +3069,10 @@ def main() -> None: logger.error(f"Model {hparams['architectures'][0]} is not supported") sys.exit(1) - model_instance = model_class(dir_model, ftype_map[args.outtype], fname_out, args.bigendian, args.use_temp_file, args.no_lazy, args.model_name) + model_instance = model_class(dir_model, ftype_map[args.outtype], fname_out, args.bigendian, args.use_temp_file, + args.no_lazy, args.model_name, split_max_tensors=args.split_max_tensors, + split_max_size=split_str_to_n_bytes(args.split_max_size), dry_run=args.dry_run, + small_first_shard=args.no_tensor_first_split) logger.info("Set model parameters") model_instance.set_gguf_parameters() @@ -3038,13 +3083,13 @@ def main() -> None: model_instance.gguf_writer.add_quantization_version(gguf.GGML_QUANT_VERSION) if args.vocab_only: - logger.info(f"Exporting model vocab to '{model_instance.fname_out}'") + logger.info("Exporting model vocab...") model_instance.write_vocab() + logger.info("Model vocab successfully exported.") else: - logger.info(f"Exporting model to '{model_instance.fname_out}'") + logger.info("Exporting model...") model_instance.write() - - logger.info(f"Model successfully exported to '{model_instance.fname_out}'") + logger.info("Model successfully exported.") if __name__ == '__main__': diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py index 100594b303526..222a2d137b08f 100644 --- a/gguf-py/gguf/constants.py +++ b/gguf-py/gguf/constants.py @@ -75,6 +75,11 @@ class Rope: SCALING_FINETUNED = "{arch}.rope.scaling.finetuned" SCALING_YARN_LOG_MUL = "{arch}.rope.scaling.yarn_log_multiplier" + class Split: + LLM_KV_SPLIT_NO = "split.no" + LLM_KV_SPLIT_COUNT = "split.count" + LLM_KV_SPLIT_TENSORS_COUNT = "split.tensors.count" + class SSM: CONV_KERNEL = "{arch}.ssm.conv_kernel" INNER_SIZE = "{arch}.ssm.inner_size" diff --git a/gguf-py/gguf/gguf_writer.py b/gguf-py/gguf/gguf_writer.py index 3b841a62583a3..9869f6fe3445a 100644 --- a/gguf-py/gguf/gguf_writer.py +++ b/gguf-py/gguf/gguf_writer.py @@ -7,6 +7,7 @@ import tempfile from dataclasses import dataclass from enum import Enum, auto +from pathlib import Path from io import BufferedWriter from typing import IO, Any, Sequence, Mapping from string import ascii_letters, digits @@ -31,6 +32,9 @@ logger = logging.getLogger(__name__) +SHARD_NAME_FORMAT = "{:s}-{:05d}-of-{:05d}.gguf" + + @dataclass class TensorInfo: shape: Sequence[int] @@ -55,11 +59,11 @@ class WriterState(Enum): class GGUFWriter: - fout: BufferedWriter | None - path: os.PathLike[str] | str | None + fout: list[BufferedWriter] | None + path: Path | None temp_file: tempfile.SpooledTemporaryFile[bytes] | None - tensors: dict[str, TensorInfo] - kv_data: dict[str, GGUFValue] + tensors: list[dict[str, TensorInfo]] + kv_data: list[dict[str, GGUFValue]] state: WriterState _simple_value_packing = { GGUFValueType.UINT8: "B", @@ -76,26 +80,38 @@ class GGUFWriter: } def __init__( - self, path: os.PathLike[str] | str | None, arch: str, use_temp_file: bool = False, - endianess: GGUFEndian = GGUFEndian.LITTLE, + self, path: os.PathLike[str] | str | None, arch: str, use_temp_file: bool = False, endianess: GGUFEndian = GGUFEndian.LITTLE, + split_max_tensors: int = 0, split_max_size: int = 0, dry_run: bool = False, small_first_shard: bool = False ): self.fout = None - self.path = path + self.path = Path(path) if path else None self.arch = arch self.endianess = endianess self.data_alignment = GGUF_DEFAULT_ALIGNMENT self.use_temp_file = use_temp_file self.temp_file = None - self.tensors = dict() - self.kv_data = dict() + self.tensors = [{}] + self.kv_data = [{}] + self.split_max_tensors = split_max_tensors + self.split_max_size = split_max_size + self.dry_run = dry_run + self.small_first_shard = small_first_shard logger.info("gguf: This GGUF file is for {0} Endian only".format( "Big" if self.endianess == GGUFEndian.BIG else "Little", )) self.state = WriterState.NO_FILE + if self.small_first_shard: + self.tensors.append({}) + self.add_architecture() - def open_output_file(self, path: os.PathLike[str] | str | None = None) -> None: + def format_shard_names(self, path: Path) -> list[Path]: + if len(self.tensors) == 1: + return [path] + return [path.with_name(SHARD_NAME_FORMAT.format(path.stem, i + 1, len(self.tensors))) for i in range(len(self.tensors))] + + def open_output_file(self, path: Path | None = None) -> None: if self.state is WriterState.EMPTY and self.fout is not None and (path is None or path == self.path): # allow calling this multiple times as long as the path is the same return @@ -106,22 +122,58 @@ def open_output_file(self, path: os.PathLike[str] | str | None = None) -> None: self.path = path if self.path is not None: - if self.fout is not None: - self.fout.close() - self.fout = open(self.path, "wb") + filenames = self.print_plan() + self.fout = [open(filename, "wb") for filename in filenames] self.state = WriterState.EMPTY - def write_header_to_file(self, path: os.PathLike[str] | str | None = None) -> None: + def print_plan(self) -> list[Path]: + logger.info("Writing the following files:") + assert self.path is not None + filenames = self.format_shard_names(self.path) + assert len(filenames) == len(self.tensors) + for name, tensors in zip(filenames, self.tensors): + logger.info(f"{name}: n_tensors = {len(tensors)}, total_size = {GGUFWriter.format_n_bytes_to_str(sum(ti.nbytes for ti in tensors.values()))}") + + if self.dry_run: + logger.info("Dry run, not writing files") + exit() + + return filenames + + def add_shard_kv_data(self) -> None: + if len(self.tensors) == 1: + return + + total_tensors = sum(len(t) for t in self.tensors) + assert self.fout is not None + total_splits = len(self.fout) + self.kv_data.extend({} for _ in range(len(self.kv_data), total_splits)) + for i, kv_data in enumerate(self.kv_data): + kv_data[Keys.Split.LLM_KV_SPLIT_NO] = GGUFValue(i, GGUFValueType.UINT16) + kv_data[Keys.Split.LLM_KV_SPLIT_COUNT] = GGUFValue(total_splits, GGUFValueType.UINT16) + kv_data[Keys.Split.LLM_KV_SPLIT_TENSORS_COUNT] = GGUFValue(total_tensors, GGUFValueType.INT32) + + def write_header_to_file(self, path: Path | None = None) -> None: + if len(self.tensors) == 1 and (self.split_max_tensors != 0 or self.split_max_size != 0): + logger.warning("Model fails split requirements, not splitting") + self.open_output_file(path) if self.state is not WriterState.EMPTY: raise ValueError(f'Expected output file to be empty, got {self.state}') - self._write_packed(" None: @@ -129,13 +181,15 @@ def write_kv_data_to_file(self) -> None: raise ValueError(f'Expected output file to contain the header, got {self.state}') assert self.fout is not None - kv_data = bytearray() + for fout, kv_data in zip(self.fout, self.kv_data): + kv_bytes = bytearray() - for key, val in self.kv_data.items(): - kv_data += self._pack_val(key, GGUFValueType.STRING, add_vtype=False) - kv_data += self._pack_val(val.value, val.type, add_vtype=True) + for key, val in kv_data.items(): + kv_bytes += self._pack_val(key, GGUFValueType.STRING, add_vtype=False) + kv_bytes += self._pack_val(val.value, val.type, add_vtype=True) + + fout.write(kv_bytes) - self.fout.write(kv_data) self.flush() self.state = WriterState.KV_DATA @@ -144,28 +198,29 @@ def write_ti_data_to_file(self) -> None: raise ValueError(f'Expected output file to contain KV data, got {self.state}') assert self.fout is not None - ti_data = bytearray() - offset_tensor = 0 - - for name, ti in self.tensors.items(): - ti_data += self._pack_val(name, GGUFValueType.STRING, add_vtype=False) - n_dims = len(ti.shape) - ti_data += self._pack("I", n_dims) - for i in range(n_dims): - ti_data += self._pack("Q", ti.shape[n_dims - 1 - i]) - ti_data += self._pack("I", ti.dtype) - ti_data += self._pack("Q", offset_tensor) - offset_tensor += GGUFWriter.ggml_pad(ti.nbytes, self.data_alignment) - - self.fout.write(ti_data) - self.flush() + for fout, tensors in zip(self.fout, self.tensors): + ti_data = bytearray() + offset_tensor = 0 + + for name, ti in tensors.items(): + ti_data += self._pack_val(name, GGUFValueType.STRING, add_vtype=False) + n_dims = len(ti.shape) + ti_data += self._pack("I", n_dims) + for j in range(n_dims): + ti_data += self._pack("Q", ti.shape[n_dims - 1 - j]) + ti_data += self._pack("I", ti.dtype) + ti_data += self._pack("Q", offset_tensor) + offset_tensor += GGUFWriter.ggml_pad(ti.nbytes, self.data_alignment) + + fout.write(ti_data) + fout.flush() self.state = WriterState.TI_DATA def add_key_value(self, key: str, val: Any, vtype: GGUFValueType) -> None: - if key in self.kv_data: + if any(key in kv_data for kv_data in self.kv_data): raise ValueError(f'Duplicated key name {key!r}') - self.kv_data[key] = GGUFValue(value=val, type=vtype) + self.kv_data[0][key] = GGUFValue(value=val, type=vtype) def add_uint8(self, key: str, val: int) -> None: self.add_key_value(key,val, GGUFValueType.UINT8) @@ -206,9 +261,6 @@ def add_string(self, key: str, val: str) -> None: self.add_key_value(key, val, GGUFValueType.STRING) def add_array(self, key: str, val: Sequence[Any]) -> None: - if not isinstance(val, Sequence): - raise ValueError("Value must be a sequence for array type") - self.add_key_value(key, val, GGUFValueType.ARRAY) @staticmethod @@ -222,7 +274,7 @@ def add_tensor_info( if self.state is not WriterState.NO_FILE: raise ValueError(f'Expected output file to be not yet opened, got {self.state}') - if name in self.tensors: + if any(name in tensors for tensors in self.tensors): raise ValueError(f'Duplicated tensor name {name!r}') if raw_dtype is None: @@ -247,7 +299,18 @@ def add_tensor_info( if tensor_dtype == np.uint8: tensor_shape = quant_shape_from_byte_shape(tensor_shape, raw_dtype) - self.tensors[name] = TensorInfo(shape=tensor_shape, dtype=dtype, nbytes=tensor_nbytes) + # make sure there is at least one tensor before splitting + if len(self.tensors[-1]) > 0: + if ( # split when over tensor limit + self.split_max_tensors != 0 + and len(self.tensors[-1]) >= self.split_max_tensors + ) or ( # split when over size limit + self.split_max_size != 0 + and sum(ti.nbytes for ti in self.tensors[-1].values()) + tensor_nbytes > self.split_max_size + ): + self.tensors.append({}) + + self.tensors[-1][name] = TensorInfo(shape=tensor_shape, dtype=dtype, nbytes=tensor_nbytes) def add_tensor( self, name: str, tensor: np.ndarray[Any, Any], raw_shape: Sequence[int] | None = None, @@ -264,7 +327,7 @@ def add_tensor( self.add_tensor_info(name, shape, tensor.dtype, tensor.nbytes, raw_dtype=raw_dtype) if self.temp_file is None: - self.tensors[name].tensor = tensor + self.tensors[-1][name].tensor = tensor return tensor.tofile(self.temp_file) @@ -282,9 +345,24 @@ def write_tensor_data(self, tensor: np.ndarray[Any, Any]) -> None: if self.endianess == GGUFEndian.BIG: tensor.byteswap(inplace=True) - self.write_padding(self.fout, self.fout.tell()) - tensor.tofile(self.fout) - self.write_padding(self.fout, tensor.nbytes) + + file_id = -1 + for i, tensors in enumerate(self.tensors): + if len(tensors) > 0: + file_id = i + break + + fout = self.fout[file_id] + + # pop the first tensor info + # TODO: cleaner way to get the first key + first_tensor_name = [name for name, _ in zip(self.tensors[file_id].keys(), range(1))][0] + ti = self.tensors[file_id].pop(first_tensor_name) + assert ti.nbytes == tensor.nbytes + + self.write_padding(fout, fout.tell()) + tensor.tofile(fout) + self.write_padding(fout, tensor.nbytes) self.state = WriterState.WEIGHTS @@ -293,31 +371,43 @@ def write_tensors_to_file(self, *, progress: bool = False) -> None: assert self.fout is not None - self.write_padding(self.fout, self.fout.tell()) + for fout in self.fout: + self.write_padding(fout, fout.tell()) if self.temp_file is None: + shard_bar = None bar = None if progress: from tqdm import tqdm - total_bytes = sum(t.nbytes for t in self.tensors.values()) + total_bytes = sum(ti.nbytes for t in self.tensors for ti in t.values()) + if len(self.fout) > 1: + shard_bar = tqdm(desc=f"Shard (0/{len(self.fout)})", total=None, unit="byte", unit_scale=True) bar = tqdm(desc="Writing", total=total_bytes, unit="byte", unit_scale=True) - # relying on the fact that Python dicts preserve insertion order (since 3.7) - for ti in self.tensors.values(): - assert ti.tensor is not None # can only iterate once over the tensors - assert ti.tensor.nbytes == ti.nbytes - ti.tensor.tofile(self.fout) - if bar is not None: - bar.update(ti.nbytes) - self.write_padding(self.fout, ti.nbytes) - ti.tensor = None + for i, (fout, tensors) in enumerate(zip(self.fout, self.tensors)): + if shard_bar is not None: + shard_bar.set_description(f"Shard ({i + 1}/{len(self.fout)})") + total = sum(ti.nbytes for ti in tensors.values()) + shard_bar.reset(total=(total if total > 0 else None)) + + # relying on the fact that Python dicts preserve insertion order (since 3.7) + for ti in tensors.values(): + assert ti.tensor is not None # can only iterate once over the tensors + assert ti.tensor.nbytes == ti.nbytes + ti.tensor.tofile(fout) + if shard_bar is not None: + shard_bar.update(ti.nbytes) + if bar is not None: + bar.update(ti.nbytes) + self.write_padding(fout, ti.nbytes) + ti.tensor = None else: self.temp_file.seek(0) - shutil.copyfileobj(self.temp_file, self.fout) + shutil.copyfileobj(self.temp_file, self.fout[0 if not self.small_first_shard else 1]) self.flush() self.temp_file.close() @@ -325,11 +415,13 @@ def write_tensors_to_file(self, *, progress: bool = False) -> None: def flush(self) -> None: assert self.fout is not None - self.fout.flush() + for fout in self.fout: + fout.flush() def close(self) -> None: if self.fout is not None: - self.fout.close() + for fout in self.fout: + fout.close() self.fout = None def add_architecture(self) -> None: @@ -626,6 +718,13 @@ def _pack_val(self, val: Any, vtype: GGUFValueType, add_vtype: bool) -> bytes: return kv_data - def _write_packed(self, fmt: str, value: Any, skip_pack_prefix: bool = False) -> None: - assert self.fout is not None - self.fout.write(self._pack(fmt, value, skip_pack_prefix)) + @staticmethod + def format_n_bytes_to_str(num: int) -> str: + if num == 0: + return "negligible - metadata only" + fnum = float(num) + for unit in ("", "K", "M", "G"): + if abs(fnum) < 1000.0: + return f"{fnum:3.1f}{unit}" + fnum /= 1000.0 + return f"{fnum:.1f}T - over 1TB, split recommended" From 9a590c82262dd518137f85406e65e452fdf2aca3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= Date: Mon, 24 Jun 2024 12:41:23 +0200 Subject: [PATCH 005/326] CUDA: optimize MMQ int8 tensor core performance (#8062) * CUDA: optimize MMQ int8 tensor core performance * only a single get_mma_tile_x_k function * simplify code, make functions constexpr --- ggml-cuda/common.cuh | 4 +- ggml-cuda/mma.cuh | 56 ++ ggml-cuda/mmq.cuh | 1366 +++++++++++++++++++++++++----------------- 3 files changed, 879 insertions(+), 547 deletions(-) diff --git a/ggml-cuda/common.cuh b/ggml-cuda/common.cuh index 5bd24ebe5fa79..5c866253586e7 100644 --- a/ggml-cuda/common.cuh +++ b/ggml-cuda/common.cuh @@ -643,7 +643,7 @@ struct ggml_cuda_type_traits { static constexpr int qi = QI3_S; }; -static int get_mmq_x_max_host(const int cc) { +static constexpr int get_mmq_x_max_host(int cc) { #ifdef CUDA_USE_TENSOR_CORES return cc >= CC_VOLTA && cc < CC_OFFSET_AMD ? MMQ_MAX_BATCH_SIZE : 64; #else @@ -652,7 +652,7 @@ static int get_mmq_x_max_host(const int cc) { } // Round rows to this value for --split-mode row: -static int get_mmq_y_host(const int cc) { +static constexpr int get_mmq_y_host(int cc) { return cc >= CC_VOLTA ? 128 : 64; } diff --git a/ggml-cuda/mma.cuh b/ggml-cuda/mma.cuh index 63e07fbc21291..0301a52f9ea71 100644 --- a/ggml-cuda/mma.cuh +++ b/ggml-cuda/mma.cuh @@ -20,6 +20,20 @@ struct mma_int_A_I16K4 { GGML_CUDA_ASSUME(ret < K); return ret; } + + __device__ __forceinline__ void load(const int * __restrict__ xs0, const int & stride) { +#if defined(INT8_MMA_AVAILABLE) + const int * xs = xs0 + (threadIdx.x%I)*stride + (threadIdx.x/I)*(K/2); + asm("ldmatrix.sync.aligned.m8n8.x2.b16 {%0, %1}, [%2];" + : "+r"(x[0]), "+r"(x[1]) + : "l"(xs)); +#else +#pragma unroll + for (int l = 0; l < ne; ++l) { + x[l] = xs0[get_i(l)*stride + get_k(l)]; + } +#endif // defined(INT8_MMA_AVAILABLE) + } }; struct mma_int_A_I16K8 { @@ -42,6 +56,20 @@ struct mma_int_A_I16K8 { GGML_CUDA_ASSUME(ret < K); return ret; } + + __device__ __forceinline__ void load(const int * __restrict__ xs0, const int & stride) { +#if defined(INT8_MMA_AVAILABLE) + const int * xs = xs0 + (threadIdx.x%I)*stride + (threadIdx.x/I)*(K/2); + asm("ldmatrix.sync.aligned.m8n8.x4.b16 {%0, %1, %2, %3}, [%4];" + : "+r"(x[0]), "+r"(x[1]), "+r"(x[2]), "+r"(x[3]) + : "l"(xs)); +#else +#pragma unroll + for (int l = 0; l < ne; ++l) { + x[l] = xs0[get_i(l)*stride + get_k(l)]; + } +#endif // defined(INT8_MMA_AVAILABLE) + } }; struct mma_int_B_J8K4 { @@ -64,6 +92,20 @@ struct mma_int_B_J8K4 { GGML_CUDA_ASSUME(ret < K); return ret; } + + __device__ __forceinline__ void load(const int * __restrict__ xs0, const int & stride) { +#if defined(INT8_MMA_AVAILABLE) && false // Loading as 4 byte values is faster + const int * xs = xs0 + (threadIdx.x%J)*stride; + asm("ldmatrix.sync.aligned.m8n8.x1.b16 {%0}, [%1];" + : "+r"(x[0]) + : "l"(xs)); +#else +#pragma unroll + for (int l = 0; l < ne; ++l) { + x[l] = xs0[get_j(l)*stride + get_k(l)]; + } +#endif // defined(INT8_MMA_AVAILABLE) + } }; struct mma_int_B_J8K8 { @@ -86,6 +128,20 @@ struct mma_int_B_J8K8 { GGML_CUDA_ASSUME(ret < K); return ret; } + + __device__ __forceinline__ void load(const int * __restrict__ xs0, const int & stride) { +#if defined(INT8_MMA_AVAILABLE) && false // Loading as 4 byte values is faster + const int * xs = xs0 + (threadIdx.x%J)*stride + ((threadIdx.x/J)*(K/2)) % K; + asm("ldmatrix.sync.aligned.m8n8.x2.b16 {%0, %1}, [%2];" + : "+r"(x[0]), "+r"(x[1]) + : "l"(xs)); +#else +#pragma unroll + for (int l = 0; l < ne; ++l) { + x[l] = xs0[get_j(l)*stride + get_k(l)]; + } +#endif // defined(INT8_MMA_AVAILABLE) + } }; struct mma_int_C_I16J8 { diff --git a/ggml-cuda/mmq.cuh b/ggml-cuda/mmq.cuh index e2d07c20253ae..0f7f8ae51e425 100644 --- a/ggml-cuda/mmq.cuh +++ b/ggml-cuda/mmq.cuh @@ -7,15 +7,8 @@ #include #include -#define MMQ_TILE_Y_K (WARP_SIZE + WARP_SIZE/QI8_1) -#define MMQ_NWARPS 8 - -typedef void (*load_tiles_mmq_t)( - const char * __restrict__ x, int * __restrict__ x_qs, half2 * __restrict__ x_dm, - int * __restrict__ x_sc, const int & kbx0, const int & i_max, const int & stride); -typedef void (*vec_dot_mmq_t)( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0); +typedef void (*load_tiles_mmq_t)(const char * __restrict__ x, int * x_tile, const int & kbx0, const int & i_max, const int & stride); +typedef void (*vec_dot_mmq_t)(const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0); typedef void (*mmq_write_back_t)(const float * __restrict__ sum, float * __restrict__ dst, const int & stride, const int & i_max, const int & j_max); struct block_q8_1_mmq { @@ -63,51 +56,101 @@ static constexpr __device__ int get_mmq_y_device() { #endif // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__) } -#define TILE_X_SIZES_Q4_0 tile_x_sizes{mmq_y*WARP_SIZE + mmq_y, mmq_y*WARP_SIZE/QI4_0 + mmq_y/QI4_0, 0} -#define TILE_X_SIZES_Q4_1 tile_x_sizes{mmq_y*WARP_SIZE + mmq_y, mmq_y*WARP_SIZE/QI4_1 + mmq_y/QI4_1, 0} -#define TILE_X_SIZES_Q5_0 tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE/QI5_0 + mmq_y/QI5_0, 0} -#define TILE_X_SIZES_Q5_1 tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE/QI5_1 + mmq_y/QI5_1, 0} -#define TILE_X_SIZES_Q8_0 tile_x_sizes{mmq_y*WARP_SIZE + mmq_y, mmq_y*WARP_SIZE/QI8_0 + mmq_y/QI8_0, 0} -#define TILE_X_SIZES_Q2_K tile_x_sizes{mmq_y*WARP_SIZE + mmq_y, mmq_y*WARP_SIZE + mmq_y, 0} -#define TILE_X_SIZES_Q3_K tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE/QI3_K + mmq_y/QI3_K, mmq_y*WARP_SIZE/4 + mmq_y/4} -#define TILE_X_SIZES_Q4_K tile_x_sizes{mmq_y*WARP_SIZE + mmq_y, mmq_y*WARP_SIZE/QI4_K + mmq_y/QI4_K, mmq_y*WARP_SIZE/8 + mmq_y/8} -#define TILE_X_SIZES_Q5_K tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE/QI5_K + mmq_y/QI5_K, mmq_y*WARP_SIZE/8 + mmq_y/8} -#define TILE_X_SIZES_Q6_K tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE/QI6_K + mmq_y/QI6_K, mmq_y*WARP_SIZE/8 + mmq_y/8} - -#define GET_TILE_X_SIZES_BODY \ - return type == GGML_TYPE_Q4_0 ? TILE_X_SIZES_Q4_0 : \ - type == GGML_TYPE_Q4_1 ? TILE_X_SIZES_Q4_1 : \ - type == GGML_TYPE_Q5_0 ? TILE_X_SIZES_Q5_0 : \ - type == GGML_TYPE_Q5_1 ? TILE_X_SIZES_Q5_1 : \ - type == GGML_TYPE_Q8_0 ? TILE_X_SIZES_Q8_0 : \ - type == GGML_TYPE_Q2_K ? TILE_X_SIZES_Q2_K : \ - type == GGML_TYPE_Q3_K ? TILE_X_SIZES_Q3_K : \ - type == GGML_TYPE_Q4_K ? TILE_X_SIZES_Q4_K : \ - type == GGML_TYPE_Q5_K ? TILE_X_SIZES_Q5_K : \ - type == GGML_TYPE_Q6_K ? TILE_X_SIZES_Q6_K : \ - tile_x_sizes{0, 0, 0} - -static tile_x_sizes get_tile_x_sizes_host(const ggml_type type, const int mmq_y) { - GET_TILE_X_SIZES_BODY; +#define MMQ_DP4A_TXS_Q4_0 tile_x_sizes{mmq_y*WARP_SIZE + mmq_y, mmq_y*WARP_SIZE/QI4_0 + mmq_y/QI4_0, 0} +#define MMQ_DP4A_TXS_Q4_1 tile_x_sizes{mmq_y*WARP_SIZE + mmq_y, mmq_y*WARP_SIZE/QI4_1 + mmq_y/QI4_1, 0} +#define MMQ_DP4A_TXS_Q5_0 tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE/QI5_0 + mmq_y/QI5_0, 0} +#define MMQ_DP4A_TXS_Q5_1 tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE/QI5_1 + mmq_y/QI5_1, 0} +#define MMQ_DP4A_TXS_Q8_0 tile_x_sizes{mmq_y*WARP_SIZE + mmq_y, mmq_y*WARP_SIZE/QI8_0 + mmq_y/QI8_0, 0} +#define MMQ_DP4A_TXS_Q2_K tile_x_sizes{mmq_y*WARP_SIZE + mmq_y, mmq_y*WARP_SIZE + mmq_y, 0} +#define MMQ_DP4A_TXS_Q3_K tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE/QI3_K + mmq_y/QI3_K, mmq_y*WARP_SIZE/4 + mmq_y/4} +#define MMQ_DP4A_TXS_Q4_K tile_x_sizes{mmq_y*WARP_SIZE + mmq_y, mmq_y*WARP_SIZE/QI4_K + mmq_y/QI4_K, mmq_y*WARP_SIZE/8 + mmq_y/8} +#define MMQ_DP4A_TXS_Q5_K tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE/QI5_K + mmq_y/QI5_K, mmq_y*WARP_SIZE/8 + mmq_y/8} +#define MMQ_DP4A_TXS_Q6_K tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE/QI6_K + mmq_y/QI6_K, mmq_y*WARP_SIZE/8 + mmq_y/8} + +static constexpr __host__ __device__ tile_x_sizes mmq_get_dp4a_tile_x_sizes(ggml_type type, int mmq_y) { + return type == GGML_TYPE_Q4_0 ? MMQ_DP4A_TXS_Q4_0 : + type == GGML_TYPE_Q4_1 ? MMQ_DP4A_TXS_Q4_1 : + type == GGML_TYPE_Q5_0 ? MMQ_DP4A_TXS_Q5_0 : + type == GGML_TYPE_Q5_1 ? MMQ_DP4A_TXS_Q5_1 : + type == GGML_TYPE_Q8_0 ? MMQ_DP4A_TXS_Q8_0 : + type == GGML_TYPE_Q2_K ? MMQ_DP4A_TXS_Q2_K : + type == GGML_TYPE_Q3_K ? MMQ_DP4A_TXS_Q3_K : + type == GGML_TYPE_Q4_K ? MMQ_DP4A_TXS_Q4_K : + type == GGML_TYPE_Q5_K ? MMQ_DP4A_TXS_Q5_K : + type == GGML_TYPE_Q6_K ? MMQ_DP4A_TXS_Q6_K : + tile_x_sizes{0, 0, 0}; } -template -static constexpr __device__ tile_x_sizes get_tile_x_sizes_device(ggml_type type) { - GET_TILE_X_SIZES_BODY; +#define MMQ_MMA_TILE_X_K_Q4_0 (1*WARP_SIZE + WARP_SIZE/QI4_0 + 4) +#define MMQ_MMA_TILE_X_K_Q4_1 (1*WARP_SIZE + WARP_SIZE/QI4_1 + 4) +#define MMQ_MMA_TILE_X_K_Q5_0 (2*WARP_SIZE + WARP_SIZE/QI5_0 + 4) +#define MMQ_MMA_TILE_X_K_Q5_1 (2*WARP_SIZE + WARP_SIZE/QI5_1 + 4) +#define MMQ_MMA_TILE_X_K_Q8_0 (1*WARP_SIZE + WARP_SIZE/QI8_0 + 0) +#define MMQ_MMA_TILE_X_K_Q2_K (1*WARP_SIZE + WARP_SIZE + 4) +#define MMQ_MMA_TILE_X_K_Q3_K (2*WARP_SIZE + WARP_SIZE/QI3_K + WARP_SIZE/4 + 2) +#define MMQ_MMA_TILE_X_K_Q4_K (1*WARP_SIZE + WARP_SIZE/QI4_K + WARP_SIZE/8 + 7) +#define MMQ_MMA_TILE_X_K_Q5_K (2*WARP_SIZE + WARP_SIZE/QI5_K + WARP_SIZE/8 + 7) +#define MMQ_MMA_TILE_X_K_Q6_K (2*WARP_SIZE + WARP_SIZE/QI6_K + WARP_SIZE/8 + 7) + +static_assert(MMQ_MMA_TILE_X_K_Q4_0 % 8 == 4, "Wrong padding."); +static_assert(MMQ_MMA_TILE_X_K_Q4_1 % 8 == 4, "Wrong padding."); +static_assert(MMQ_MMA_TILE_X_K_Q5_0 % 8 == 4, "Wrong padding."); +static_assert(MMQ_MMA_TILE_X_K_Q5_1 % 8 == 4, "Wrong padding."); +static_assert(MMQ_MMA_TILE_X_K_Q8_0 % 8 == 4, "Wrong padding."); +static_assert(MMQ_MMA_TILE_X_K_Q2_K % 8 == 4, "Wrong padding."); +static_assert(MMQ_MMA_TILE_X_K_Q3_K % 8 == 4, "Wrong padding."); +static_assert(MMQ_MMA_TILE_X_K_Q4_K % 8 == 4, "Wrong padding."); +static_assert(MMQ_MMA_TILE_X_K_Q5_K % 8 == 4, "Wrong padding."); +static_assert(MMQ_MMA_TILE_X_K_Q6_K % 8 == 4, "Wrong padding."); + +static constexpr __host__ __device__ int mmq_get_mma_tile_x_k(ggml_type type) { + return type == GGML_TYPE_Q4_0 ? MMQ_MMA_TILE_X_K_Q4_0 : + type == GGML_TYPE_Q4_1 ? MMQ_MMA_TILE_X_K_Q4_1 : + type == GGML_TYPE_Q5_0 ? MMQ_MMA_TILE_X_K_Q5_0 : + type == GGML_TYPE_Q5_1 ? MMQ_MMA_TILE_X_K_Q5_1 : + type == GGML_TYPE_Q8_0 ? MMQ_MMA_TILE_X_K_Q8_0 : + type == GGML_TYPE_Q2_K ? MMQ_MMA_TILE_X_K_Q2_K : + type == GGML_TYPE_Q3_K ? MMQ_MMA_TILE_X_K_Q3_K : + type == GGML_TYPE_Q4_K ? MMQ_MMA_TILE_X_K_Q4_K : + type == GGML_TYPE_Q5_K ? MMQ_MMA_TILE_X_K_Q5_K : + type == GGML_TYPE_Q6_K ? MMQ_MMA_TILE_X_K_Q6_K : + 0; +} + +#define MMQ_TILE_Y_K (WARP_SIZE + WARP_SIZE/QI8_1) +#define MMQ_NWARPS 8 + +static int mmq_get_granularity_host(const int mmq_x, const int cc) { + return int8_mma_available(cc) && mmq_x >= 48 ? 16 : 8; +} + +#ifdef INT8_MMA_AVAILABLE +static constexpr __device__ int mmq_get_granularity_device(const int mmq_x) { + return mmq_x >= 48 ? 16 : 8; } +#else +static constexpr __device__ int mmq_get_granularity_device(const int /* mmq_x */) { + return 8; +} +#endif // INT8_MMA_AVAILABLE // ------------------------------------------------------------ template static __device__ __forceinline__ void load_tiles_q4_0( - const char * __restrict__ x, int * __restrict__ x_qs, half2 * __restrict__ x_dm, - int * __restrict__ x_sc, const int & kbx0, const int & i_max, const int & stride) { - GGML_UNUSED(x_sc); + const char * __restrict__ x, int * __restrict__ x_tile, const int & kbx0, const int & i_max, const int & stride) { + +#ifdef INT8_MMA_AVAILABLE + int * x_qs = (int *) x_tile; + float * x_df = (float *) (x_qs + WARP_SIZE); +#else + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q4_0, mmq_y); + int * x_qs = (int *) x_tile; + float * x_df = (float *) (x_qs + txs.qs); +#endif // INT8_MMA_AVAILABLE const int kbx = threadIdx.x / QI4_0; const int kqsx = threadIdx.x % QI4_0; - float * x_dmf = (float *) x_dm; - #pragma unroll for (int i0 = 0; i0 < mmq_y; i0 += nwarps) { int i = i0 + threadIdx.y; @@ -118,7 +161,11 @@ template static __device__ __forceinlin const block_q4_0 * bxi = (const block_q4_0 *) x + kbx0 + i*stride + kbx; - x_qs[i * (WARP_SIZE + 1) + threadIdx.x] = get_int_from_uint8(bxi->qs, kqsx); +#ifdef INT8_MMA_AVAILABLE + x_qs[i*MMQ_MMA_TILE_X_K_Q4_0 + threadIdx.x] = get_int_from_uint8(bxi->qs, kqsx); +#else + x_qs[i*(WARP_SIZE + 1) + threadIdx.x] = get_int_from_uint8(bxi->qs, kqsx); +#endif // INT8_MMA_AVAILABLE } const int blocks_per_tile_x_row = WARP_SIZE / QI4_0; @@ -134,17 +181,21 @@ template static __device__ __forceinlin const block_q4_0 * bxi = (const block_q4_0 *) x + kbx0 + i*stride + kbxd; - x_dmf[i * (WARP_SIZE/QI4_0) + i / QI4_0 + kbxd] = bxi->d; +#ifdef INT8_MMA_AVAILABLE + x_df[i*MMQ_MMA_TILE_X_K_Q4_0 + kbxd] = bxi->d; +#else + x_df[i*(WARP_SIZE/QI4_0) + i/QI4_0 + kbxd] = bxi->d; +#endif // INT8_MMA_AVAILABLE } } template static __device__ __forceinline__ void vec_dot_q4_0_q8_1_dp4a( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { - GGML_UNUSED(x_sc); + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { - const float * x_df = (const float *) x_dm; + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q4_0, mmq_y); + const int * x_qs = (const int *) x; + const float * x_df = (const float *) x_qs + txs.qs; const int * y_qs = (const int *) y + 4; const half2 * y_ds = (const half2 *) y; @@ -175,76 +226,90 @@ static __device__ __forceinline__ void vec_dot_q4_0_q8_1_dp4a( template static __device__ __forceinline__ void vec_dot_q4_0_q8_1_mma( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { #ifdef INT8_MMA_AVAILABLE - GGML_UNUSED(x_sc); typedef mma_int_A_I16K8 mma_A; typedef mma_int_B_J8K8 mma_B; typedef mma_int_C_I16J8 mma_C; - const float * x_df = (const float *) x_dm; + constexpr int granularity = mmq_get_granularity_device(mmq_x); + constexpr int rows_per_warp = 2 * granularity; + constexpr int ntx = rows_per_warp/mma_C::I; // Number of x minitiles per warp. + + y += (threadIdx.y % ntx) * (mma_B::J*MMQ_TILE_Y_K); + + const int * x_qs = (const int *) x; + const float * x_df = (const float *) x_qs + WARP_SIZE; const int * y_qs = (const int *) y + 4; const half2 * y_ds = (const half2 *) y; - mma_A A; - float dA[mma_C::ne/2]; + mma_A A[ntx]; + float dA[ntx][mma_C::ne/2]; - const int i0 = threadIdx.y*mma_A::I; - static_assert(nwarps*mma_A::I == mmq_y, "nwarps*mma_A::I != mmq_y"); + const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I); #pragma unroll - for (int l = 0; l < mma_A::ne; ++l) { - const int i = i0 + mma_A::get_i(l); - const int k = k0 + mma_A::get_k(l) % QI4_0; - const int shift = 4*(mma_A::get_k(l) / QI4_0); + for (int n = 0; n < ntx; ++n) { +#pragma unroll + for (int l = 0; l < mma_A::ne; ++l) { + const int i = i0 + n*mma_A::I + mma_A::get_i(l); + const int k = k0 + mma_A::get_k(l) % QI4_0; + const int shift = 4*(mma_A::get_k(l) / QI4_0); + + A[n].x[l] = __vsubss4((x_qs[i*MMQ_MMA_TILE_X_K_Q4_0 + k] >> shift) & 0x0F0F0F0F, 0x08080808); + } - A.x[l] = __vsubss4((x_qs[i*(WARP_SIZE + 1) + k] >> shift) & 0x0F0F0F0F, 0x08080808); - } #pragma unroll - for (int l = 0; l < mma_C::ne/2; ++l) { - const int i = i0 + mma_C::get_i(2*l); + for (int l = 0; l < mma_C::ne/2; ++l) { + const int i = i0 + n*mma_C::I + mma_C::get_i(2*l); - dA[l] = x_df[i*(WARP_SIZE/QI4_0) + i/QI4_0 + k0/QI4_0]; + dA[n][l] = x_df[i*MMQ_MMA_TILE_X_K_Q4_0 + k0/QI4_0]; + } } - for (int j0 = 0; j0 < mmq_x; j0 += mma_int_B_J8K8::J) { - mma_C C; - mma_B B; - half2 dsB[mma_C::ne/2]; - #pragma unroll - for (int l = 0; l < mma_B::ne; ++l) { - const int j = j0 + mma_B::get_j(l); - const int k = (2*k0 + mma_B::get_k(l)) % WARP_SIZE; + for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) { + mma_B B; + float dB[mma_C::ne/2]; + + B.load(y_qs + j0*MMQ_TILE_Y_K + (2*k0) % WARP_SIZE, MMQ_TILE_Y_K); - B.x[l] = y_qs[j*MMQ_TILE_Y_K + k]; - } #pragma unroll for (int l = 0; l < mma_C::ne/2; ++l) { const int j = j0 + mma_C::get_j(l); - dsB[l] = y_ds[j*MMQ_TILE_Y_K + (2*k0/QI8_1) % (WARP_SIZE/QI8_1)]; + dB[l] = __low2float(y_ds[j*MMQ_TILE_Y_K + (2*k0/QI8_1) % (WARP_SIZE/QI8_1)]); } - C.mma_K8(A, B); +#pragma unroll + for (int n = 0; n < ntx; ++n) { + mma_C C; + C.mma_K8(A[n], B); #pragma unroll - for (int l = 0; l < mma_C::ne; ++l) { - sum[(j0/B.J)*C.ne + l] += dA[l/2]*__low2float(dsB[l%2])*C.x[l]; + for (int l = 0; l < mma_C::ne; ++l) { + sum[(j0/mma_C::J + n)*mma_C::ne + l] += dA[n][l/2]*dB[l%2]*C.x[l]; + } } } #else - GGML_UNUSED(x_qs); GGML_UNUSED(x_dm); GGML_UNUSED(x_sc); GGML_UNUSED(y); GGML_UNUSED(sum); GGML_UNUSED(k0); + GGML_UNUSED(x); GGML_UNUSED(y); GGML_UNUSED(sum); NO_DEVICE_CODE; #endif // INT8_MMA_AVAILABLE } template static __device__ __forceinline__ void load_tiles_q4_1( - const char * __restrict__ x, int * __restrict__ x_qs, half2 * __restrict__ x_dm, - int * __restrict__ x_sc, const int & kbx0, const int & i_max, const int & stride) { - GGML_UNUSED(x_sc); + const char * __restrict__ x, int * __restrict__ x_tile, const int & kbx0, const int & i_max, const int & stride) { + +#ifdef INT8_MMA_AVAILABLE + int * x_qs = (int *) x_tile; + half2 * x_dm = (half2 *) (x_qs + WARP_SIZE); +#else + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q4_1, mmq_y); + int * x_qs = (int *) x_tile; + half2 * x_dm = (half2 *) (x_qs + txs.qs); +#endif // INT8_MMA_AVAILABLE const int kbx = threadIdx.x / QI4_1; const int kqsx = threadIdx.x % QI4_1; @@ -259,7 +324,11 @@ template static __device__ __forceinlin const block_q4_1 * bxi = (const block_q4_1 *) x + kbx0 + i*stride + kbx; - x_qs[i * (WARP_SIZE + 1) + threadIdx.x] = get_int_from_uint8_aligned(bxi->qs, kqsx); +#ifdef INT8_MMA_AVAILABLE + x_qs[i*MMQ_MMA_TILE_X_K_Q4_1 + threadIdx.x] = get_int_from_uint8_aligned(bxi->qs, kqsx); +#else + x_qs[i*(WARP_SIZE + 1) + threadIdx.x] = get_int_from_uint8_aligned(bxi->qs, kqsx); +#endif // INT8_MMA_AVAILABLE } const int blocks_per_tile_x_row = WARP_SIZE / QI4_1; @@ -275,16 +344,21 @@ template static __device__ __forceinlin const block_q4_1 * bxi = (const block_q4_1 *) x + kbx0 + i*stride + kbxd; - x_dm[i * (WARP_SIZE/QI4_1) + i / QI4_1 + kbxd] = bxi->dm; +#ifdef INT8_MMA_AVAILABLE + x_dm[i*MMQ_MMA_TILE_X_K_Q4_1 + kbxd] = bxi->dm; +#else + x_dm[i*(WARP_SIZE/QI4_1) + i/QI4_1 + kbxd] = bxi->dm; +#endif // INT8_MMA_AVAILABLE } } template static __device__ __forceinline__ void vec_dot_q4_1_q8_1_dp4a( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { - GGML_UNUSED(x_sc); + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q4_1, mmq_y); + const int * x_qs = (const int *) x; + const half2 * x_dm = (const half2 *) x_qs + txs.qs; const int * y_qs = (const int *) y + 4; const half2 * y_ds = (const half2 *) y; @@ -315,51 +389,53 @@ static __device__ __forceinline__ void vec_dot_q4_1_q8_1_dp4a( template static __device__ __forceinline__ void vec_dot_q4_1_q8_1_mma( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { #ifdef INT8_MMA_AVAILABLE - GGML_UNUSED(x_sc); typedef mma_int_A_I16K8 mma_A; + typedef mma_int_A_I16K4 mma_A_K4; typedef mma_int_B_J8K8 mma_B; typedef mma_int_C_I16J8 mma_C; + constexpr int granularity = mmq_get_granularity_device(mmq_x); + constexpr int rows_per_warp = 2 * granularity; + constexpr int ntx = rows_per_warp/mma_C::I; // Number of x minitiles per warp. + + y += (threadIdx.y % ntx) * (mma_B::J*MMQ_TILE_Y_K); + + const int * x_qs = (const int *) x; + const half2 * x_dm = (const half2 *) x_qs + WARP_SIZE; const int * y_qs = (const int *) y + 4; const half2 * y_ds = (const half2 *) y; - mma_A A; - half2 dmA[mma_C::ne/2]; + mma_A A[ntx]; + half2 dmA[ntx][mma_C::ne/2]; - const int i0 = threadIdx.y*mma_A::I; - static_assert(nwarps*mma_A::I == mmq_y, "nwarps*mma_A::I != mmq_y"); + const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I); #pragma unroll - for (int l = 0; l < mma_A::ne; ++l) { - const int i = i0 + mma_A::get_i(l); - const int k = k0 + mma_A::get_k(l) % QI4_0; - const int shift = 4*(mma_A::get_k(l) / QI4_0); + for (int n = 0; n < ntx; ++n) { + ((mma_A_K4 *) &A[n])[0].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q4_1 + k0, MMQ_MMA_TILE_X_K_Q4_1); + A[n].x[2] = (A[n].x[0] >> 4) & 0x0F0F0F0F; + A[n].x[3] = (A[n].x[1] >> 4) & 0x0F0F0F0F; + A[n].x[0] &= 0x0F0F0F0F; + A[n].x[1] &= 0x0F0F0F0F; - A.x[l] = (x_qs[i*(WARP_SIZE + 1) + k] >> shift) & 0x0F0F0F0F; - } #pragma unroll - for (int l = 0; l < mma_C::ne/2; ++l) { - const int i = i0 + mma_C::get_i(2*l); + for (int l = 0; l < mma_C::ne/2; ++l) { + const int i = i0 + n*mma_C::I + mma_C::get_i(2*l); - dmA[l] = x_dm[i*(WARP_SIZE/QI4_0) + i/QI4_0 + k0/QI4_0]; + dmA[n][l] = x_dm[i*MMQ_MMA_TILE_X_K_Q4_1 + k0/QI4_1]; + } } - for (int j0 = 0; j0 < mmq_x; j0 += mma_int_B_J8K8::J) { - mma_C C; +#pragma unroll + for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) { mma_B B; half2 dsB[mma_C::ne/2]; -#pragma unroll - for (int l = 0; l < mma_B::ne; ++l) { - const int j = j0 + mma_B::get_j(l); - const int k = (2*k0 + mma_B::get_k(l)) % WARP_SIZE; + B.load(y_qs + j0*MMQ_TILE_Y_K + (2*k0) % WARP_SIZE, MMQ_TILE_Y_K); - B.x[l] = y_qs[j*MMQ_TILE_Y_K + k]; - } #pragma unroll for (int l = 0; l < mma_C::ne/2; ++l) { const int j = j0 + mma_C::get_j(l); @@ -367,24 +443,35 @@ static __device__ __forceinline__ void vec_dot_q4_1_q8_1_mma( dsB[l] = y_ds[j*MMQ_TILE_Y_K + (2*k0/QI8_1) % (WARP_SIZE/QI8_1)]; } - C.mma_K8(A, B); +#pragma unroll + for (int n = 0; n < ntx; ++n) { + mma_C C; + C.mma_K8(A[n], B); #pragma unroll - for (int l = 0; l < mma_C::ne; ++l) { - const half2 dmA_dsB = dmA[l/2]*dsB[l%2]; - sum[(j0/B.J)*C.ne + l] += __low2float(dmA_dsB)*C.x[l] + __high2float(dmA_dsB); + for (int l = 0; l < mma_C::ne; ++l) { + const half2 dmA_dsB = dmA[n][l/2]*dsB[l%2]; + sum[(j0/mma_C::J + n)*mma_C::ne + l] += __low2float(dmA_dsB)*C.x[l] + __high2float(dmA_dsB); + } } } #else - GGML_UNUSED(x_qs); GGML_UNUSED(x_dm); GGML_UNUSED(x_sc); GGML_UNUSED(y); GGML_UNUSED(sum); GGML_UNUSED(k0); + GGML_UNUSED(x); GGML_UNUSED(y); GGML_UNUSED(sum); NO_DEVICE_CODE; #endif // INT8_MMA_AVAILABLE } template static __device__ __forceinline__ void load_tiles_q5_0( - const char * __restrict__ x, int * __restrict__ x_qs, half2 * __restrict__ x_dm, - int * __restrict__ x_sc, const int & kbx0, const int & i_max, const int & stride) { - GGML_UNUSED(x_sc); + const char * __restrict__ x, int * __restrict__ x_tile, const int & kbx0, const int & i_max, const int & stride) { + +#ifdef INT8_MMA_AVAILABLE + int * x_qs = (int *) x_tile; + float * x_df = (float *) (x_qs + WARP_SIZE*2); +#else + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q5_0, mmq_y); + int * x_qs = (int *) x_tile; + float * x_df = (float *) (x_qs + txs.qs); +#endif // INT8_MMA_AVAILABLE const int kbx = threadIdx.x / QI5_0; const int kqsx = threadIdx.x % QI5_0; @@ -409,8 +496,6 @@ template static __device__ __forceinlin qs0 |= (qh << 25) & 0x10000000; // 3 -> 28 qs0 = __vsubss4(qs0, 0x10101010); // subtract 16 - x_qs[i * (2*WARP_SIZE + 1) + 2*threadIdx.x+0] = qs0; - int qs1 = (ql >> 4) & 0x0F0F0F0F; qs1 |= (qh >> 12) & 0x00000010; // 16 -> 4 qs1 |= (qh >> 5) & 0x00001000; // 17 -> 12 @@ -418,12 +503,17 @@ template static __device__ __forceinlin qs1 |= (qh << 9) & 0x10000000; // 19 -> 28 qs1 = __vsubss4(qs1, 0x10101010); // subtract 16 - x_qs[i * (2*WARP_SIZE + 1) + 2*threadIdx.x+1] = qs1; +#ifdef INT8_MMA_AVAILABLE + x_qs[i*MMQ_MMA_TILE_X_K_Q5_0 + kbx*(2*QI5_0) + kqsx + 0] = qs0; + x_qs[i*MMQ_MMA_TILE_X_K_Q5_0 + kbx*(2*QI5_0) + kqsx + QI5_0] = qs1; +#else + x_qs[i*(2*WARP_SIZE + 1) + kbx*(2*QI5_0) + kqsx + 0] = qs0; + x_qs[i*(2*WARP_SIZE + 1) + kbx*(2*QI5_0) + kqsx + QI5_0] = qs1; +#endif // INT8_MMA_AVAILABLE } const int blocks_per_tile_x_row = WARP_SIZE / QI5_0; const int kbxd = threadIdx.x % blocks_per_tile_x_row; - float * x_dmf = (float *) x_dm; #pragma unroll for (int i0 = 0; i0 < mmq_y; i0 += nwarps * QI5_0) { @@ -435,19 +525,23 @@ template static __device__ __forceinlin const block_q5_0 * bxi = (const block_q5_0 *) x + kbx0 + i*stride + kbxd; - x_dmf[i * (WARP_SIZE/QI5_0) + i / QI5_0 + kbxd] = bxi->d; +#ifdef INT8_MMA_AVAILABLE + x_df[i*MMQ_MMA_TILE_X_K_Q5_0 + kbxd] = bxi->d; +#else + x_df[i*(WARP_SIZE/QI5_0) + i/QI5_0 + kbxd] = bxi->d; +#endif // INT8_MMA_AVAILABLE } } template static __device__ __forceinline__ void vec_dot_q5_0_q8_1_dp4a( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { - GGML_UNUSED(x_sc); + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { - const float * x_dmf = (const float *) x_dm; - const int * y_qs = (const int *) y + 4; - const float * y_df = (const float *) y; + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q5_0, mmq_y); + const int * x_qs = (const int *) x; + const float * x_df = (const float *) x_qs + txs.qs; + const int * y_qs = (const int *) y + 4; + const float * y_df = (const float *) y; #pragma unroll for (int j0 = 0; j0 < mmq_x; j0 += nwarps) { @@ -457,70 +551,57 @@ static __device__ __forceinline__ void vec_dot_q5_0_q8_1_dp4a( for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) { const int i = i0 + threadIdx.x; - const int kyqs = k0 % (QI8_1/2) + QI8_1 * (k0 / (QI8_1/2)); - const int index_bx = i*(WARP_SIZE/QI5_0) + i/QI5_0 + k0/QI5_0; - - int u[2*VDR_Q5_0_Q8_1_MMQ]; - -#pragma unroll - for (int l = 0; l < VDR_Q5_0_Q8_1_MMQ; ++l) { - u[2*l+0] = y_qs[j*MMQ_TILE_Y_K + (kyqs + l) % WARP_SIZE]; - u[2*l+1] = y_qs[j*MMQ_TILE_Y_K + (kyqs + l + QI5_0) % WARP_SIZE]; - } - sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q8_0_q8_1_impl - (&x_qs[i*(2*WARP_SIZE + 1) + 2*k0], u, x_dmf[index_bx], y_df[j*MMQ_TILE_Y_K + (2*k0/QI8_1) % (WARP_SIZE/QI8_1)]); + (&x_qs[i*(2*WARP_SIZE + 1) + 2*k0], &y_qs[j*MMQ_TILE_Y_K + (2*k0) % WARP_SIZE], + x_df[i*(WARP_SIZE/QI5_0) + i/QI5_0 + k0/QI5_0], y_df[j*MMQ_TILE_Y_K + (2*k0/QI8_1) % (WARP_SIZE/QI8_1)]); } } } template static __device__ __forceinline__ void vec_dot_q5_0_q8_1_mma( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { #ifdef INT8_MMA_AVAILABLE - GGML_UNUSED(x_sc); typedef mma_int_A_I16K8 mma_A; typedef mma_int_B_J8K8 mma_B; typedef mma_int_C_I16J8 mma_C; - const float * x_df = (const float *) x_dm; + constexpr int granularity = mmq_get_granularity_device(mmq_x); + constexpr int rows_per_warp = 2 * granularity; + constexpr int ntx = rows_per_warp/mma_C::I; // Number of x minitiles per warp. + + y += (threadIdx.y % ntx) * (mma_B::J*MMQ_TILE_Y_K); + + const int * x_qs = (const int *) x; + const float * x_df = (const float *) x_qs + WARP_SIZE*2; const int * y_qs = (const int *) y + 4; const float * y_df = (const float *) y; - mma_A A; - float dA[mma_C::ne/2]; + mma_A A[ntx]; + float dA[ntx][mma_C::ne/2]; - const int i0 = threadIdx.y*mma_A::I; - static_assert(nwarps*mma_A::I == mmq_y, "nwarps*mma_A::I != mmq_y"); + const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I); #pragma unroll - for (int l = 0; l < mma_A::ne; ++l) { - const int i = i0 + mma_A::get_i(l); - const int k = 2*(k0 + mma_A::get_k(l) % QI5_0) + mma_A::get_k(l) / QI5_0; + for (int n = 0; n < ntx; ++n) { + A[n].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q5_0 + QR5_1*k0, MMQ_MMA_TILE_X_K_Q5_0); - A.x[l] = x_qs[i*(2*WARP_SIZE + 1) + k]; - } #pragma unroll - for (int l = 0; l < mma_C::ne/2; ++l) { - const int i = i0 + mma_C::get_i(2*l); + for (int l = 0; l < mma_C::ne/2; ++l) { + const int i = i0 + mma_C::get_i(2*l) + n*mma_C::I; - dA[l] = x_df[i*(WARP_SIZE/QI5_0) + i/QI5_0 + k0/QI5_0]; + dA[n][l] = x_df[i*MMQ_MMA_TILE_X_K_Q5_0 + k0/QI5_0]; + } } - for (int j0 = 0; j0 < mmq_x; j0 += mma_int_B_J8K8::J) { - mma_C C; +#pragma unroll + for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) { mma_B B; float dB[mma_C::ne/2]; -#pragma unroll - for (int l = 0; l < mma_B::ne; ++l) { - const int j = j0 + mma_B::get_j(l); - const int k = (2*k0 + mma_B::get_k(l)) % WARP_SIZE; + B.load(y_qs + j0*MMQ_TILE_Y_K + (2*k0) % WARP_SIZE, MMQ_TILE_Y_K); - B.x[l] = y_qs[j*MMQ_TILE_Y_K + k]; - } #pragma unroll for (int l = 0; l < mma_C::ne/2; ++l) { const int j = j0 + mma_C::get_j(l); @@ -528,23 +609,34 @@ static __device__ __forceinline__ void vec_dot_q5_0_q8_1_mma( dB[l] = y_df[j*MMQ_TILE_Y_K + (2*k0/QI8_1) % (WARP_SIZE/QI8_1)]; } - C.mma_K8(A, B); +#pragma unroll + for (int n = 0; n < ntx; ++n) { + mma_C C; + C.mma_K8(A[n], B); #pragma unroll - for (int l = 0; l < mma_C::ne; ++l) { - sum[(j0/B.J)*C.ne + l] += dA[l/2]*dB[l%2]*C.x[l]; + for (int l = 0; l < mma_C::ne; ++l) { + sum[(j0/mma_C::J + n)*mma_C::ne + l] += dA[n][l/2]*dB[l%2]*C.x[l]; + } } } #else - GGML_UNUSED(x_qs); GGML_UNUSED(x_dm); GGML_UNUSED(x_sc); GGML_UNUSED(y); GGML_UNUSED(sum); GGML_UNUSED(k0); + GGML_UNUSED(x); GGML_UNUSED(y); GGML_UNUSED(sum); NO_DEVICE_CODE; #endif // INT8_MMA_AVAILABLE } template static __device__ __forceinline__ void load_tiles_q5_1( - const char * __restrict__ x, int * __restrict__ x_qs, half2 * __restrict__ x_dm, - int * __restrict__ x_sc, const int & kbx0, const int & i_max, const int & stride) { - GGML_UNUSED(x_sc); + const char * __restrict__ x, int * __restrict__ x_tile, const int & kbx0, const int & i_max, const int & stride) { + +#ifdef INT8_MMA_AVAILABLE + int * x_qs = (int *) x_tile; + half2 * x_dm = (half2 *) (x_qs + 2*WARP_SIZE); +#else + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q5_1, mmq_y); + int * x_qs = (int *) x_tile; + half2 * x_dm = (half2 *) (x_qs + txs.qs); +#endif // INT8_MMA_AVAILABLE const int kbx = threadIdx.x / QI5_1; const int kqsx = threadIdx.x % QI5_1; @@ -568,15 +660,19 @@ template static __device__ __forceinlin qs0 |= (qh << 18) & 0x00100000; // 2 -> 20 qs0 |= (qh << 25) & 0x10000000; // 3 -> 28 - x_qs[i * (2*WARP_SIZE + 1) + 2*threadIdx.x+0] = qs0; - int qs1 = (ql >> 4) & 0x0F0F0F0F; qs1 |= (qh >> 12) & 0x00000010; // 16 -> 4 qs1 |= (qh >> 5) & 0x00001000; // 17 -> 12 qs1 |= (qh << 2) & 0x00100000; // 18 -> 20 qs1 |= (qh << 9) & 0x10000000; // 19 -> 28 - x_qs[i * (2*WARP_SIZE + 1) + 2*threadIdx.x+1] = qs1; +#ifdef INT8_MMA_AVAILABLE + x_qs[i*MMQ_MMA_TILE_X_K_Q5_1 + kbx*(2*QI5_1) + kqsx + 0] = qs0; + x_qs[i*MMQ_MMA_TILE_X_K_Q5_1 + kbx*(2*QI5_1) + kqsx + QI5_1] = qs1; +#else + x_qs[i*(2*WARP_SIZE + 1) + kbx*(2*QI5_1) + kqsx + 0] = qs0; + x_qs[i*(2*WARP_SIZE + 1) + kbx*(2*QI5_1) + kqsx + QI5_1] = qs1; +#endif // INT8_MMA_AVAILABLE } const int blocks_per_tile_x_row = WARP_SIZE / QI5_1; @@ -592,18 +688,23 @@ template static __device__ __forceinlin const block_q5_1 * bxi = (const block_q5_1 *) x + kbx0 + i*stride + kbxd; - x_dm[i * (WARP_SIZE/QI5_1) + i / QI5_1 + kbxd] = bxi->dm; +#ifdef INT8_MMA_AVAILABLE + x_dm[i*MMQ_MMA_TILE_X_K_Q5_1 + kbxd] = bxi->dm; +#else + x_dm[i*(WARP_SIZE/QI5_1) + i/QI5_1 + kbxd] = bxi->dm; +#endif // INT8_MMA_AVAILABLE } } template static __device__ __forceinline__ void vec_dot_q5_1_q8_1_dp4a( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { - GGML_UNUSED(x_sc); + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { - const int * y_qs = (const int *) y + 4; - const half2 * y_ds = (const half2 *) y; + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q5_1, mmq_y); + const int * x_qs = (const int *) x; + const half2 * x_dm = (const half2 *) x_qs + txs.qs; + const int * y_qs = (const int *) y + 4; + const half2 * y_ds = (const half2 *) y; #pragma unroll for (int j0 = 0; j0 < mmq_x; j0 += nwarps) { @@ -613,69 +714,57 @@ static __device__ __forceinline__ void vec_dot_q5_1_q8_1_dp4a( for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) { const int i = i0 + threadIdx.x; - const int kyqs = k0 % (QI8_1/2) + QI8_1 * (k0 / (QI8_1/2)); - const int index_bx = i*(WARP_SIZE/QI5_1) + i/QI5_1 + k0/QI5_1; - - int u[2*VDR_Q5_1_Q8_1_MMQ]; - -#pragma unroll - for (int l = 0; l < VDR_Q5_1_Q8_1_MMQ; ++l) { - u[2*l+0] = y_qs[j*MMQ_TILE_Y_K + (kyqs + l) % WARP_SIZE]; - u[2*l+1] = y_qs[j*MMQ_TILE_Y_K + (kyqs + l + QI5_1) % WARP_SIZE]; - } - sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q8_1_q8_1_impl - (&x_qs[i*(2*WARP_SIZE + 1) + 2*k0], u, x_dm[index_bx], y_ds[j*MMQ_TILE_Y_K + (2*k0/QI8_1) % (WARP_SIZE/QI8_1)]); + (&x_qs[i*(2*WARP_SIZE + 1) + 2*k0], &y_qs[j*MMQ_TILE_Y_K + (2*k0) % WARP_SIZE], + x_dm[i*(WARP_SIZE/QI5_1) + i/QI5_1 + k0/QI5_1], y_ds[j*MMQ_TILE_Y_K + (2*k0/QI8_1) % (WARP_SIZE/QI8_1)]); } } } template static __device__ __forceinline__ void vec_dot_q5_1_q8_1_mma( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { #ifdef INT8_MMA_AVAILABLE - GGML_UNUSED(x_sc); typedef mma_int_A_I16K8 mma_A; typedef mma_int_B_J8K8 mma_B; typedef mma_int_C_I16J8 mma_C; + constexpr int granularity = mmq_get_granularity_device(mmq_x); + constexpr int rows_per_warp = 2 * granularity; + constexpr int ntx = rows_per_warp/mma_C::I; // Number of x minitiles per warp. + + y += (threadIdx.y % ntx) * (mma_B::J*MMQ_TILE_Y_K); + + const int * x_qs = (const int *) x; + const half2 * x_dm = (const half2 *) x_qs + 2*WARP_SIZE; const int * y_qs = (const int *) y + 4; const half2 * y_ds = (const half2 *) y; - mma_A A; - half2 dmA[mma_C::ne/2]; + mma_A A[ntx]; + half2 dmA[ntx][mma_C::ne/2]; - const int i0 = threadIdx.y*mma_A::I; - static_assert(nwarps*mma_A::I == mmq_y, "nwarps*mma_A::I != mmq_y"); + const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I); #pragma unroll - for (int l = 0; l < mma_A::ne; ++l) { - const int i = i0 + mma_A::get_i(l); - const int k = 2*(k0 + mma_A::get_k(l) % QI5_1) + mma_A::get_k(l) / QI5_1; + for (int n = 0; n < ntx; ++n) { + A[n].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q5_1 + QR5_1*k0, MMQ_MMA_TILE_X_K_Q5_1); - A.x[l] = x_qs[i*(2*WARP_SIZE + 1) + k]; - } #pragma unroll - for (int l = 0; l < mma_C::ne/2; ++l) { - const int i = i0 + mma_C::get_i(2*l); + for (int l = 0; l < mma_C::ne/2; ++l) { + const int i = i0 + mma_C::get_i(2*l) + n*mma_C::I; - dmA[l] = x_dm[i*(WARP_SIZE/QI5_1) + i/QI5_1 + k0/QI5_1]; + dmA[n][l] = x_dm[i*MMQ_MMA_TILE_X_K_Q5_1 + k0/QI5_1]; + } } - for (int j0 = 0; j0 < mmq_x; j0 += mma_int_B_J8K8::J) { - mma_C C; +#pragma unroll + for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) { mma_B B; half2 dsB[mma_C::ne/2]; -#pragma unroll - for (int l = 0; l < mma_B::ne; ++l) { - const int j = j0 + mma_B::get_j(l); - const int k = (2*k0 + mma_B::get_k(l)) % WARP_SIZE; + B.load(y_qs + j0*MMQ_TILE_Y_K + (2*k0) % WARP_SIZE, MMQ_TILE_Y_K); - B.x[l] = y_qs[j*MMQ_TILE_Y_K + k]; - } #pragma unroll for (int l = 0; l < mma_C::ne/2; ++l) { const int j = j0 + mma_C::get_j(l); @@ -683,28 +772,38 @@ static __device__ __forceinline__ void vec_dot_q5_1_q8_1_mma( dsB[l] = y_ds[j*MMQ_TILE_Y_K + (2*k0/QI8_1) % (WARP_SIZE/QI8_1)]; } - C.mma_K8(A, B); +#pragma unroll + for (int n = 0; n < ntx; ++n) { + mma_C C; + C.mma_K8(A[n], B); #pragma unroll - for (int l = 0; l < mma_C::ne; ++l) { - const half2 dmA_dsB = dmA[l/2]*dsB[l%2]; - sum[(j0/B.J)*C.ne + l] += __low2float(dmA_dsB)*C.x[l] + __high2float(dmA_dsB); + for (int l = 0; l < mma_C::ne; ++l) { + const half2 dmA_dsB = dmA[n][l/2]*dsB[l%2]; + sum[(j0/mma_C::J + n)*mma_C::ne + l] += __low2float(dmA_dsB)*C.x[l] + __high2float(dmA_dsB); + } } } #else - GGML_UNUSED(x_qs); GGML_UNUSED(x_dm); GGML_UNUSED(x_sc); GGML_UNUSED(y); GGML_UNUSED(sum); GGML_UNUSED(k0); + GGML_UNUSED(x); GGML_UNUSED(y); GGML_UNUSED(sum); NO_DEVICE_CODE; #endif // INT8_MMA_AVAILABLE } template static __device__ __forceinline__ void load_tiles_q8_0( - const char * __restrict__ x, int * __restrict__ x_qs, half2 * __restrict__ x_dm, - int * __restrict__ x_sc, const int & kbx0, const int & i_max, const int & stride) { - GGML_UNUSED(x_sc); + const char * __restrict__ x, int * __restrict__ x_tile, const int & kbx0, const int & i_max, const int & stride) { + +#ifdef INT8_MMA_AVAILABLE + int * x_qs = (int *) x_tile; + float * x_df = (float *) (x_tile + WARP_SIZE); +#else + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q8_0, mmq_y); + int * x_qs = (int *) x_tile; + float * x_df = (float *) (x_qs + txs.qs); +#endif // INT8_MMA_AVAILABLE const int kbx = threadIdx.x / QI8_0; const int kqsx = threadIdx.x % QI8_0; - float * x_dmf = (float *) x_dm; #pragma unroll for (int i0 = 0; i0 < mmq_y; i0 += nwarps) { @@ -716,7 +815,11 @@ template static __device__ __forceinlin const block_q8_0 * bxi = (const block_q8_0 *) x + kbx0 + i*stride + kbx; - x_qs[i * (WARP_SIZE + 1) + threadIdx.x] = get_int_from_int8(bxi->qs, kqsx); +#ifdef INT8_MMA_AVAILABLE + x_qs[i*MMQ_MMA_TILE_X_K_Q8_0 + threadIdx.x] = get_int_from_int8(bxi->qs, kqsx); +#else + x_qs[i*(WARP_SIZE + 1) + threadIdx.x] = get_int_from_int8(bxi->qs, kqsx); +#endif // INT8_MMA_AVAILABLE } const int blocks_per_tile_x_row = WARP_SIZE / QI8_0; @@ -732,19 +835,23 @@ template static __device__ __forceinlin const block_q8_0 * bxi = (const block_q8_0 *) x + kbx0 + i*stride + kbxd; - x_dmf[i * (WARP_SIZE/QI8_0) + i / QI8_0 + kbxd] = bxi->d; +#ifdef INT8_MMA_AVAILABLE + x_df[i*MMQ_MMA_TILE_X_K_Q8_0 + kbxd] = bxi->d; +#else + x_df[i*(WARP_SIZE/QI8_0) + i / QI8_0 + kbxd] = bxi->d; +#endif // INT8_MMA_AVAILABLE } } template static __device__ __forceinline__ void vec_dot_q8_0_q8_1_dp4a( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { - GGML_UNUSED(x_sc); + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { - const float * x_dmf = (const float *) x_dm; - const int * y_qs = (const int *) y + 4; - const float * y_df = (const float *) y; + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q8_0, mmq_y); + const int * x_qs = (const int *) x; + const float * x_df = (const float *) x_qs + txs.qs; + const int * y_qs = (const int *) y + 4; + const float * y_df = (const float *) y; #pragma unroll for (int j0 = 0; j0 < mmq_x; j0 += nwarps) { @@ -755,7 +862,7 @@ static __device__ __forceinline__ void vec_dot_q8_0_q8_1_dp4a( const int i = i0 + threadIdx.x; sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q8_0_q8_1_impl - (&x_qs[i*(WARP_SIZE + 1) + k0], &y_qs[j*MMQ_TILE_Y_K + k0], x_dmf[i*(WARP_SIZE/QI8_0) + i/QI8_0 + k0/QI8_0], + (&x_qs[i*(WARP_SIZE + 1) + k0], &y_qs[j*MMQ_TILE_Y_K + k0], x_df[i*(WARP_SIZE/QI8_0) + i/QI8_0 + k0/QI8_0], y_df[j*MMQ_TILE_Y_K + k0/QI8_1]); } } @@ -763,51 +870,48 @@ static __device__ __forceinline__ void vec_dot_q8_0_q8_1_dp4a( template static __device__ __forceinline__ void vec_dot_q8_0_q8_1_mma( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { #ifdef INT8_MMA_AVAILABLE - GGML_UNUSED(x_sc); typedef mma_int_A_I16K8 mma_A; typedef mma_int_B_J8K8 mma_B; typedef mma_int_C_I16J8 mma_C; - const float * x_df = (const float *) x_dm; + constexpr int granularity = mmq_get_granularity_device(mmq_x); + constexpr int rows_per_warp = 2 * granularity; + constexpr int ntx = rows_per_warp/mma_C::I; // Number of x minitiles per warp. + + y += (threadIdx.y % ntx) * (mma_B::J*MMQ_TILE_Y_K); + + const int * x_qs = (const int *) x; + const float * x_df = (const float *) x_qs + WARP_SIZE; const int * y_qs = (const int *) y + 4; const float * y_df = (const float *) y; - mma_A A; - float dA[mma_C::ne/2]; + mma_A A[ntx]; + float dA[ntx][mma_C::ne/2]; - const int i0 = threadIdx.y*mma_A::I; - static_assert(nwarps*mma_A::I == mmq_y, "nwarps*mma_A::I != mmq_y"); + const int i0 = (threadIdx.y/ntx)*rows_per_warp; #pragma unroll - for (int l = 0; l < mma_A::ne; ++l) { - const int i = i0 + mma_A::get_i(l); - const int k = k0 + mma_A::get_k(l); + for (int n = 0; n < ntx; ++n) { + A[n].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q8_0 + k0, MMQ_MMA_TILE_X_K_Q8_0); - A.x[l] = x_qs[i*(WARP_SIZE + 1) + k]; - } #pragma unroll - for (int l = 0; l < mma_C::ne/2; ++l) { - const int i = i0 + mma_C::get_i(2*l); + for (int l = 0; l < mma_C::ne/2; ++l) { + const int i = i0 + n*mma_A::I + mma_C::get_i(2*l); - dA[l] = x_df[i*(WARP_SIZE/QI8_0) + i/QI8_0 + k0/QI8_0]; + dA[n][l] = x_df[i*MMQ_MMA_TILE_X_K_Q8_0 + k0/QI8_0]; + } } - for (int j0 = 0; j0 < mmq_x; j0 += mma_int_B_J8K8::J) { - mma_C C; +#pragma unroll + for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) { mma_B B; float dB[mma_C::ne/2]; -#pragma unroll - for (int l = 0; l < mma_B::ne; ++l) { - const int j = j0 + mma_B::get_j(l); - const int k = k0 + mma_B::get_k(l); + B.load(y_qs + j0*MMQ_TILE_Y_K + k0, MMQ_TILE_Y_K); - B.x[l] = y_qs[j*MMQ_TILE_Y_K + k]; - } #pragma unroll for (int l = 0; l < mma_C::ne/2; ++l) { const int j = j0 + mma_C::get_j(l); @@ -815,22 +919,34 @@ static __device__ __forceinline__ void vec_dot_q8_0_q8_1_mma( dB[l] = y_df[j*MMQ_TILE_Y_K + k0/QI8_1]; } - C.mma_K8(A, B); +#pragma unroll + for (int n = 0; n < ntx; ++n) { + mma_C C; + C.mma_K8(A[n], B); #pragma unroll - for (int l = 0; l < mma_C::ne; ++l) { - sum[(j0/B.J)*C.ne + l] += C.x[l]*dA[l/2]*dB[l%2]; + for (int l = 0; l < mma_C::ne; ++l) { + sum[(j0/mma_C::J + n)*mma_C::ne + l] += C.x[l]*dA[n][l/2]*dB[l%2]; + } } } #else - GGML_UNUSED(x_qs); GGML_UNUSED(x_dm); GGML_UNUSED(x_sc); GGML_UNUSED(y); GGML_UNUSED(sum); GGML_UNUSED(k0); + GGML_UNUSED(x); GGML_UNUSED(y); GGML_UNUSED(sum); NO_DEVICE_CODE; #endif // INT8_MMA_AVAILABLE } template static __device__ __forceinline__ void load_tiles_q2_K( - const char * __restrict__ x, int * __restrict__ x_qs, half2 * __restrict__ x_dm, - int * __restrict__ x_sc, const int & kbx0, const int & i_max, const int & stride) { + const char * __restrict__ x, int * __restrict__ x_tile, const int & kbx0, const int & i_max, const int & stride) { + +#ifdef INT8_MMA_AVAILABLE + int * x_qs = (int *) x_tile; + half2 * x_dm = (half2 *) (x_qs + WARP_SIZE); +#else + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q2_K, mmq_y); + int * x_qs = (int *) x_tile; + half2 * x_dm = (half2 *) (x_qs + txs.qs); +#endif // INT8_MMA_AVAILABLE const int kbx = threadIdx.x / QI2_K; const int kqsx = threadIdx.x % QI2_K; @@ -859,7 +975,11 @@ template static __device__ __forceinlin continue; } - x_qs[i*(WARP_SIZE + 1) + k] = x_qs_k; +#ifdef INT8_MMA_AVAILABLE + x_qs[i*MMQ_MMA_TILE_X_K_Q2_K + k] = x_qs_k; +#else + x_qs[i*(WARP_SIZE + 1) + k] = x_qs_k; +#endif // INT8_MMA_AVAILABLE } const int sc_m = bxi->scales[kqsx]; @@ -870,15 +990,21 @@ template static __device__ __forceinlin const half2 x_dm_ik = make_half2(bxi_dmf.x*(sc_m & 0x0F), bxi_dmf.y*(sc_m >> 4)); #endif // FAST_FP16_AVAILABLE - x_dm[i*(WARP_SIZE + 1) + threadIdx.x] = x_dm_ik; +#ifdef INT8_MMA_AVAILABLE + x_dm[i*MMQ_MMA_TILE_X_K_Q2_K + threadIdx.x] = x_dm_ik; +#else + x_dm[i*(WARP_SIZE + 1) + threadIdx.x] = x_dm_ik; +#endif // INT8_MMA_AVAILABLE } } template static __device__ __forceinline__ void vec_dot_q2_K_q8_1_dp4a( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q2_K, mmq_y); + const int * x_qs = (const int *) x; + const half2 * x_dm = (const half2 *) x_qs + txs.qs; const int * y_qs = (const int *) y + 4; const float * y_df = (const float *) y; @@ -899,61 +1025,63 @@ static __device__ __forceinline__ void vec_dot_q2_K_q8_1_dp4a( template static __device__ __forceinline__ void vec_dot_q2_K_q8_1_mma( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { #ifdef INT8_MMA_AVAILABLE typedef mma_int_A_I16K4 mma_A; typedef mma_int_B_J8K4 mma_B; typedef mma_int_C_I16J8 mma_C; + constexpr int granularity = mmq_get_granularity_device(mmq_x); + constexpr int rows_per_warp = 2 * granularity; + constexpr int ntx = rows_per_warp/mma_C::I; // Number of x minitiles per warp. + + y += (threadIdx.y % ntx) * (mma_B::J*MMQ_TILE_Y_K); + + const int * x_qs = (const int *) x; + const half2 * x_dm = (const half2 *) x_qs + WARP_SIZE; const int * y_qs = (const int *) y + 4; const float * y_df = (const float *) y; - const int i0 = threadIdx.y*mma_A::I; - static_assert(nwarps*mma_A::I == mmq_y, "nwarps*mma_A::I != mmq_y"); + const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I); - mma_A A[2]; - float dA[mma_C::ne/2][2]; - float mA[mma_C::ne/2][2]; + mma_A A[ntx][2]; + float dA[ntx][mma_C::ne/2][2]; + float mA[ntx][mma_C::ne/2][2]; #pragma unroll - for (int l = 0; l < mma_A::ne; ++l) { - const int i = i0 + mma_A::get_i(l); - const int shift = 2*mma_A::get_k(l); + for (int n = 0; n < ntx; ++n) { +#pragma unroll + for (int l = 0; l < mma_A::ne; ++l) { + const int i = i0 + n*mma_A::I + mma_A::get_i(l); + const int shift = 2*mma_A::get_k(l); - A[0].x[l] = (x_qs[i*(WARP_SIZE + 1) + k0 + 0] >> shift) & 0x03030303; - A[1].x[l] = (x_qs[i*(WARP_SIZE + 1) + k0 + 1] >> shift) & 0x03030303; - } + A[n][0].x[l] = (x_qs[i*MMQ_MMA_TILE_X_K_Q2_K + k0 + 0] >> shift) & 0x03030303; + A[n][1].x[l] = (x_qs[i*MMQ_MMA_TILE_X_K_Q2_K + k0 + 1] >> shift) & 0x03030303; + } #pragma unroll - for (int l = 0; l < mma_C::ne/2; ++l) { - const int i = i0 + mma_C::get_i(2*l); + for (int l = 0; l < mma_C::ne/2; ++l) { + const int i = i0 + n*mma_C::I + mma_C::get_i(2*l); #pragma unroll - for (int kk = 0; kk < 2; ++kk) { - const float2 dm = __half22float2(x_dm[i*(WARP_SIZE + 1) + k0 + kk]); + for (int kdm = 0; kdm < 2; ++kdm) { + const float2 dm = __half22float2(x_dm[i*MMQ_MMA_TILE_X_K_Q2_K + k0 + kdm]); - dA[l][kk] = dm.x; - mA[l][kk] = dm.y; + dA[n][l][kdm] = dm.x; + mA[n][l][kdm] = dm.y; + } } } #pragma unroll - for (int j0 = 0; j0 < mmq_x; j0 += mma_int_B_J8K8::J) { - mma_C Cd[2]; - mma_C Cm[2]; + for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) { mma_B B[2]; float dB[mma_C::ne/2]; -#pragma unroll - for (int l = 0; l < mma_B::ne; ++l) { - const int j = j0 + mma_B::get_j(l); - const int k = (4*k0 + mma_B::get_k(l)) % WARP_SIZE; + B[0].load(y_qs + j0*MMQ_TILE_Y_K + (QR2_K*k0 + 0) % WARP_SIZE, MMQ_TILE_Y_K); + B[1].load(y_qs + j0*MMQ_TILE_Y_K + (QR2_K*k0 + mma_B::K) % WARP_SIZE, MMQ_TILE_Y_K); - B[0].x[l] = y_qs[j*MMQ_TILE_Y_K + k + 0]; - B[1].x[l] = y_qs[j*MMQ_TILE_Y_K + k + mma_B::K]; - } #pragma unroll for (int l = 0; l < mma_C::ne/2; ++l) { const int j = j0 + mma_C::get_j(l); @@ -961,9 +1089,7 @@ static __device__ __forceinline__ void vec_dot_q2_K_q8_1_mma( dB[l] = y_df[j*MMQ_TILE_Y_K + ((4*k0)/QI8_1) % (WARP_SIZE/QI8_1)]; } - Cd[0].mma_K4(A[0], B[0]); - Cd[1].mma_K4(A[1], B[1]); - + mma_C Cm[2]; mma_A A1; A1.x[0] = 0x01010101; A1.x[1] = 0x01010101; @@ -971,19 +1097,38 @@ static __device__ __forceinline__ void vec_dot_q2_K_q8_1_mma( Cm[1].mma_K4(A1, B[1]); #pragma unroll - for (int l = 0; l < mma_C::ne; ++l) { - sum[(j0/mma_B::J)*mma_C::ne + l] += (Cd[0].x[l]*dA[l/2][0] + Cd[1].x[l]*dA[l/2][1] - Cm[0].x[l]*mA[l/2][0] - Cm[1].x[l]*mA[l/2][1])*dB[l%2]; + for (int n = 0; n < ntx; ++n) { + mma_C Cd[2]; + + Cd[0].mma_K4(A[n][0], B[0]); + Cd[1].mma_K4(A[n][1], B[1]); + +#pragma unroll + for (int l = 0; l < mma_C::ne; ++l) { + sum[(j0/mma_C::J + n)*mma_C::ne + l] += ( + Cd[0].x[l]*dA[n][l/2][0] + Cd[1].x[l]*dA[n][l/2][1] - Cm[0].x[l]*mA[n][l/2][0] - Cm[1].x[l]*mA[n][l/2][1])*dB[l%2]; + } } } #else - GGML_UNUSED(x_qs); GGML_UNUSED(x_dm); GGML_UNUSED(x_sc); GGML_UNUSED(y); GGML_UNUSED(sum); GGML_UNUSED(k0); + GGML_UNUSED(x); GGML_UNUSED(y); GGML_UNUSED(sum); NO_DEVICE_CODE; #endif // INT8_MMA_AVAILABLE } template static __device__ __forceinline__ void load_tiles_q3_K( - const char * __restrict__ x, int * __restrict__ x_qs, half2 * __restrict__ x_dm, - int * __restrict__ x_sc, const int & kbx0, const int & i_max, const int & stride) { + const char * __restrict__ x, int * __restrict__ x_tile, const int & kbx0, const int & i_max, const int & stride) { + +#ifdef INT8_MMA_AVAILABLE + int * x_qs = (int *) x_tile; + float * x_df = (float *) (x_qs + WARP_SIZE*2); + int * x_sc = (int *) (x_df + WARP_SIZE/QI3_K); +#else + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q3_K, mmq_y); + int * x_qs = (int *) x_tile; + float * x_df = (float *) (x_qs + txs.qs); + int * x_sc = (int *) (x_df + txs.dm); +#endif // INT8_MMA_AVAILABLE const int kbx = threadIdx.x / QI3_K; const int kqsx = threadIdx.x % QI3_K; @@ -1015,13 +1160,16 @@ template static __device__ __forceinlin continue; } - x_qs[i*(2*WARP_SIZE + 1) + k/2] = x_qs_k; +#ifdef INT8_MMA_AVAILABLE + x_qs[i*MMQ_MMA_TILE_X_K_Q3_K + k/2] = x_qs_k; +#else + x_qs[i*(2*WARP_SIZE + 1) + k/2] = x_qs_k; +#endif // INT8_MMA_AVAILABLE } } const int blocks_per_tile_x_row = WARP_SIZE / QI3_K; const int kbxd = threadIdx.x % blocks_per_tile_x_row; - float * x_dmf = (float *) x_dm; #pragma unroll for (int i0 = 0; i0 < mmq_y; i0 += nwarps * QI3_K) { @@ -1033,7 +1181,11 @@ template static __device__ __forceinlin const block_q3_K * bxi = (const block_q3_K *) x + kbx0 + i*stride + kbxd; - x_dmf[i * (WARP_SIZE/QI3_K) + i / QI3_K + kbxd] = bxi->d; +#ifdef INT8_MMA_AVAILABLE + x_df[i*MMQ_MMA_TILE_X_K_Q3_K + kbxd] = bxi->d; +#else + x_df[i*(WARP_SIZE/QI3_K) + i/QI3_K + kbxd] = bxi->d; +#endif // INT8_MMA_AVAILABLE } #pragma unroll @@ -1058,16 +1210,22 @@ template static __device__ __forceinlin const int sc = __vsubss4(sc_low | sc_high, 0x20202020); - x_sc[i * (WARP_SIZE/4) + i / 4 + threadIdx.x % (WARP_SIZE/4)] = sc; +#ifdef INT8_MMA_AVAILABLE + x_sc[i*MMQ_MMA_TILE_X_K_Q3_K + threadIdx.x % (WARP_SIZE/4)] = sc; +#else + x_sc[i*(WARP_SIZE/4) + i/4 + threadIdx.x % (WARP_SIZE/4)] = sc; +#endif // INT8_MMA_AVAILABLE } } template static __device__ __forceinline__ void vec_dot_q3_K_q8_1_dp4a( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { - const float * x_df = (const float *) x_dm; + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q3_K, mmq_y); + const int * x_qs = (const int *) x; + const float * x_df = (const float *) x_qs + txs.qs; + const int * x_sc = (const int *) x_df + txs.dm; const int * y_qs = (const int *) y + 4; const float * y_df = (const float *) y; @@ -1093,69 +1251,72 @@ static __device__ __forceinline__ void vec_dot_q3_K_q8_1_dp4a( template static __device__ __forceinline__ void vec_dot_q3_K_q8_1_mma( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { #ifdef INT8_MMA_AVAILABLE typedef mma_int_A_I16K4 mma_A; typedef mma_int_B_J8K4 mma_B; typedef mma_int_C_I16J8 mma_C; - const float * x_df = (const float *) x_dm; + constexpr int granularity = mmq_get_granularity_device(mmq_x); + constexpr int rows_per_warp = 2 * granularity; + constexpr int ntx = rows_per_warp/mma_C::I; // Number of x minitiles per warp. + + y += (threadIdx.y % ntx) * (mma_B::J*MMQ_TILE_Y_K); + + const int * x_qs = (const int *) x; + const float * x_df = (const float *) x_qs + WARP_SIZE*2; + const int * x_sc = (const int *) x_df + WARP_SIZE/QI3_K; const int * y_qs = (const int *) y + 4; const float * y_df = (const float *) y; - const int i0 = threadIdx.y*mma_A::I; - static_assert(nwarps*mma_A::I == mmq_y, "nwarps*mma_A::I != mmq_y"); + const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I); - mma_A A[2]; - int scA[mma_C::ne/2][2]; - float dA[mma_C::ne/2]; + mma_A A[ntx][2]; + int scA[ntx][mma_C::ne/2][2]; + float dA[ntx][mma_C::ne/2]; #pragma unroll - for (int l = 0; l < mma_A::ne; ++l) { - const int i = i0 + mma_A::get_i(l); - const int k = QR3_K*k0 + mma_A::get_k(l); + for (int n = 0; n < ntx; ++n) { +#pragma unroll + for (int l = 0; l < mma_A::ne; ++l) { + const int i = i0 + n*mma_A::I + mma_A::get_i(l); + const int k = QR3_K*k0 + mma_A::get_k(l); - A[0].x[l] = (x_qs[i*(2*WARP_SIZE + 1) + k/2 + 0] >> (4*(k%2))) & 0x0F0F0F0F; - A[1].x[l] = (x_qs[i*(2*WARP_SIZE + 1) + k/2 + mma_A::K/2] >> (4*(k%2))) & 0x0F0F0F0F; - A[0].x[l] = __vsubss4(A[0].x[l], 0x04040404); - A[1].x[l] = __vsubss4(A[1].x[l], 0x04040404); - } + A[n][0].x[l] = (x_qs[i*MMQ_MMA_TILE_X_K_Q3_K + k/2 + 0] >> (4*(k%2))) & 0x0F0F0F0F; + A[n][1].x[l] = (x_qs[i*MMQ_MMA_TILE_X_K_Q3_K + k/2 + mma_A::K/2] >> (4*(k%2))) & 0x0F0F0F0F; + A[n][0].x[l] = __vsubss4(A[n][0].x[l], 0x04040404); + A[n][1].x[l] = __vsubss4(A[n][1].x[l], 0x04040404); + } #pragma unroll - for (int l = 0; l < mma_C::ne/2; ++l) { - const int i = i0 + mma_C::get_i(2*l); + for (int l = 0; l < mma_C::ne/2; ++l) { + const int i = i0 + n*mma_C::I + mma_C::get_i(2*l); - const int kbx = k0 / QI3_K; - const int ky = (k0 % QI3_K) * QR3_K; - const int8_t * sc = ((const int8_t *) (x_sc + i * (WARP_SIZE/4) + i/4 + kbx*4)) + ky/4; + const int kbx = k0 / QI3_K; + const int ky = (k0 % QI3_K) * QR3_K; + const int8_t * sc = ((const int8_t *) (x_sc + i*MMQ_MMA_TILE_X_K_Q3_K + kbx*4)) + ky/4; - scA[l][0] = sc[0]; - scA[l][1] = sc[1]; - } + scA[n][l][0] = sc[0]; + scA[n][l][1] = sc[1]; + } #pragma unroll - for (int l = 0; l < mma_C::ne/2; ++l) { - const int i = i0 + mma_C::get_i(2*l); + for (int l = 0; l < mma_C::ne/2; ++l) { + const int i = i0 + n*mma_C::I + mma_C::get_i(2*l); - dA[l] = x_df[i*(WARP_SIZE/QI3_K) + i/QI3_K + k0/QI3_K]; + dA[n][l] = x_df[i*MMQ_MMA_TILE_X_K_Q3_K + k0/QI3_K]; + } } #pragma unroll - for (int j0 = 0; j0 < mmq_x; j0 += mma_int_B_J8K8::J) { - mma_C C[2]; + for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) { mma_B B[2]; float dB[mma_C::ne/2]; -#pragma unroll - for (int l = 0; l < mma_B::ne; ++l) { - const int j = j0 + mma_B::get_j(l); - const int k = (4*k0 + mma_B::get_k(l)) % WARP_SIZE; + B[0].load(y_qs + j0*MMQ_TILE_Y_K + (QR3_K*k0 + 0) % WARP_SIZE, MMQ_TILE_Y_K); + B[1].load(y_qs + j0*MMQ_TILE_Y_K + (QR3_K*k0 + mma_B::K) % WARP_SIZE, MMQ_TILE_Y_K); - B[0].x[l] = y_qs[j*MMQ_TILE_Y_K + k + 0]; - B[1].x[l] = y_qs[j*MMQ_TILE_Y_K + k + mma_B::K]; - } #pragma unroll for (int l = 0; l < mma_C::ne/2; ++l) { const int j = j0 + mma_C::get_j(l); @@ -1163,23 +1324,37 @@ static __device__ __forceinline__ void vec_dot_q3_K_q8_1_mma( dB[l] = y_df[j*MMQ_TILE_Y_K + ((4*k0)/QI8_1) % (WARP_SIZE/QI8_1)]; } - C[0].mma_K4(A[0], B[0]); - C[1].mma_K4(A[1], B[1]); +#pragma unroll + for (int n = 0; n < ntx; ++n) { + mma_C C[2]; + C[0].mma_K4(A[n][0], B[0]); + C[1].mma_K4(A[n][1], B[1]); #pragma unroll - for (int l = 0; l < mma_C::ne; ++l) { - sum[(j0/mma_B::J)*mma_C::ne + l] += (C[0].x[l]*scA[l/2][0] + C[1].x[l]*scA[l/2][1])*dA[l/2]*dB[l%2]; + for (int l = 0; l < mma_C::ne; ++l) { + sum[(j0/mma_C::J + n)*mma_C::ne + l] += (C[0].x[l]*scA[n][l/2][0] + C[1].x[l]*scA[n][l/2][1])*dA[n][l/2]*dB[l%2]; + } } } #else - GGML_UNUSED(x_qs); GGML_UNUSED(x_dm); GGML_UNUSED(x_sc); GGML_UNUSED(y); GGML_UNUSED(sum); GGML_UNUSED(k0); + GGML_UNUSED(x); GGML_UNUSED(y); GGML_UNUSED(sum); NO_DEVICE_CODE; #endif // INT8_MMA_AVAILABLE } template static __device__ __forceinline__ void load_tiles_q4_K( - const char * __restrict__ x, int * __restrict__ x_qs, half2 * __restrict__ x_dm, - int * __restrict__ x_sc, const int & kbx0, const int & i_max, const int & stride) { + const char * __restrict__ x, int * __restrict__ x_tile, const int & kbx0, const int & i_max, const int & stride) { + +#ifdef INT8_MMA_AVAILABLE + int * x_qs = (int *) x_tile; + half2 * x_dm = (half2 *) (x_qs + WARP_SIZE); + int * x_sc = (int *) (x_dm + WARP_SIZE/QI4_K); +#else + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q4_K, mmq_y); + int * x_qs = (int *) x_tile; + half2 * x_dm = (half2 *) (x_qs + txs.qs); + int * x_sc = (int *) (x_dm + txs.dm); +#endif // INT8_MMA_AVAILABLE const int kbx = 0; // threadIdx.x / QI4_K const int kqsx = threadIdx.x; // threadIdx.x % QI4_K @@ -1194,7 +1369,11 @@ template static __device__ __forceinlin const block_q4_K * bxi = (const block_q4_K *) x + kbx0 + i*stride + kbx; - x_qs[i * (WARP_SIZE + 1) + threadIdx.x] = get_int_from_uint8_aligned(bxi->qs, kqsx); +#ifdef INT8_MMA_AVAILABLE + x_qs[i*MMQ_MMA_TILE_X_K_Q4_K + threadIdx.x] = get_int_from_uint8_aligned(bxi->qs, kqsx); +#else + x_qs[i*(WARP_SIZE + 1) + threadIdx.x] = get_int_from_uint8_aligned(bxi->qs, kqsx); +#endif // INT8_MMA_AVAILABLE } const int blocks_per_tile_x_row = WARP_SIZE / QI4_K; // == 1 if QK_K == 256 @@ -1210,7 +1389,11 @@ template static __device__ __forceinlin const block_q4_K * bxi = (const block_q4_K *) x + kbx0 + i*stride + kbxd; - x_dm[i * (WARP_SIZE/QI4_K) + i / QI4_K + kbxd] = bxi->dm; +#ifdef INT8_MMA_AVAILABLE + x_dm[i*MMQ_MMA_TILE_X_K_Q4_K + kbxd] = bxi->dm; +#else + x_dm[i*(WARP_SIZE/QI4_K) + i/QI4_K + kbxd] = bxi->dm; +#endif // INT8_MMA_AVAILABLE } #pragma unroll @@ -1231,15 +1414,22 @@ template static __device__ __forceinlin int scales8 = (scales[(ksc%2) + (ksc!=0)] >> (4 * (ksc & (ksc/2)))) & 0x0F0F0F0F; // lower 4 bits scales8 |= (scales[ksc/2] >> (2 * (ksc % 2))) & 0x30303030; // upper 2 bits - x_sc[i * (WARP_SIZE/8) + i / 8 + ksc] = scales8; +#ifdef INT8_MMA_AVAILABLE + x_sc[i*MMQ_MMA_TILE_X_K_Q4_K + ksc] = scales8; +#else + x_sc[i*(WARP_SIZE/8) + i/8 + ksc] = scales8; +#endif // INT8_MMA_AVAILABLE } } template static __device__ __forceinline__ void vec_dot_q4_K_q8_1_dp4a( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q4_K, mmq_y); + const int * x_qs = (const int *) x; + const half2 * x_dm = (const half2 *) x_qs + txs.qs; + const int * x_sc = (const int *) x_dm + txs.dm; const int * y_qs = (const int *) y + 4; const half2 * y_ds = (const half2 *) y; @@ -1262,71 +1452,79 @@ static __device__ __forceinline__ void vec_dot_q4_K_q8_1_dp4a( template static __device__ __forceinline__ void vec_dot_q4_K_q8_1_mma( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { #ifdef INT8_MMA_AVAILABLE typedef mma_int_A_I16K8 mma_A; typedef mma_int_B_J8K8 mma_B; typedef mma_int_C_I16J8 mma_C; + constexpr int granularity = mmq_get_granularity_device(mmq_x); + constexpr int rows_per_warp = 2 * granularity; + constexpr int ntx = rows_per_warp/mma_C::I; // Number of x minitiles per warp. + + y += (threadIdx.y % ntx) * (mma_B::J*MMQ_TILE_Y_K); + + const int * x_qs = (const int *) x; + const half2 * x_dm = (const half2 *) x_qs + WARP_SIZE; + const int * x_sc = (const int *) x_dm + WARP_SIZE/QI4_K; const int * y_qs = (const int *) y + 4; const half2 * y_ds = (const half2 *) y; - const int i0 = threadIdx.y*mma_A::I; - static_assert(nwarps*mma_A::I == mmq_y, "nwarps*mma_A::I != mmq_y"); + const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I); + + mma_A A[ntx][2]; + int scA[ntx][mma_C::ne/2][2]; + int mA[ntx][mma_C::ne/2][2]; + half2 dmA[ntx][mma_C::ne/2]; - mma_A A[2]; - int scA[mma_C::ne/2][2]; - int mA[mma_C::ne/2][2]; - half2 dmA[mma_C::ne/2]; #pragma unroll - for (int kvdr = 0; kvdr < VDR_Q4_K_Q8_1_MMQ; kvdr += 4) { + for (int n = 0; n < ntx; ++n) { #pragma unroll - for (int l = 0; l < mma_A::ne; ++l) { - const int i = i0 + mma_A::get_i(l); - const int k = k0 + mma_A::get_k(l); + for (int kvdr = 0; kvdr < VDR_Q4_K_Q8_1_MMQ; kvdr += 8) { + A[n][kvdr/4 + 0].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q4_K + k0, MMQ_MMA_TILE_X_K_Q4_K); - A[kvdr/4].x[l] = (x_qs[i*(WARP_SIZE + 1) + k] >> kvdr) & 0x0F0F0F0F; +#pragma unroll + for (int l = 0; l < mma_A::ne; ++l) { + A[n][kvdr/4 + 1].x[l] = (A[n][kvdr/4 + 0].x[l] >> 4) & 0x0F0F0F0F; + A[n][kvdr/4 + 0].x[l] &= 0x0F0F0F0F; + } } #pragma unroll - for (int l = 0; l < mma_C::ne/2; ++l) { - const int i = i0 + mma_C::get_i(2*l); + for (int kvdr = 0; kvdr < VDR_Q4_K_Q8_1_MMQ; kvdr += 4) { +#pragma unroll + for (int l = 0; l < mma_C::ne/2; ++l) { + const int i = i0 + n*mma_A::I + mma_C::get_i(2*l); - const uint8_t * sc = ((const uint8_t *) &x_sc[i * (WARP_SIZE/8) + i/8 + k0/16]) + 2 * ((k0 % 16) / 8); - const uint8_t * m = sc + 8; + const uint8_t * sc = ((const uint8_t *) &x_sc[i*MMQ_MMA_TILE_X_K_Q4_K + k0/16]) + 2 * ((k0 % 16) / 8); + const uint8_t * m = sc + 8; - scA[l][kvdr/4] = sc[kvdr/4]; - mA[l][kvdr/4] = m[kvdr/4]; + scA[n][l][kvdr/4] = sc[kvdr/4]; + mA[n][l][kvdr/4] = m[kvdr/4]; + } } - } #pragma unroll - for (int l = 0; l < mma_C::ne/2; ++l) { - const int i = i0 + mma_C::get_i(2*l); + for (int l = 0; l < mma_C::ne/2; ++l) { + const int i = i0 + n*mma_A::I + mma_C::get_i(2*l); - dmA[l] = x_dm[i*(WARP_SIZE/QI5_K) + i/QI5_K + k0/QI5_K]; + dmA[n][l] = x_dm[i*MMQ_MMA_TILE_X_K_Q4_K + k0/QI4_K]; + } } #pragma unroll - for (int j0 = 0; j0 < mmq_x; j0 += mma_int_B_J8K8::J) { - float tmpd[mma_C::ne] = {0.0f}; - float tmpm[mma_C::ne] = {0.0f}; + for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) { + float tmpd[ntx][mma_C::ne] = {{0.0f}}; + float tmpm[ntx][mma_C::ne] = {{0.0f}}; #pragma unroll - for (int kvdr = 0; kvdr < VDR_Q5_K_Q8_1_MMQ; kvdr += 4) { - mma_C C; + for (int kvdr = 0; kvdr < VDR_Q4_K_Q8_1_MMQ; kvdr += 4) { mma_B B; half2 dsB[mma_C::ne/2]; -#pragma unroll - for (int l = 0; l < mma_B::ne; ++l) { - const int j = j0 + mma_B::get_j(l); - const int k = (2*k0 + 2*kvdr + mma_B::get_k(l)) % WARP_SIZE; + B.load(y_qs + j0*MMQ_TILE_Y_K + (2*k0 + 2*kvdr) % WARP_SIZE, MMQ_TILE_Y_K); - B.x[l] = y_qs[j*MMQ_TILE_Y_K + k]; - } #pragma unroll for (int l = 0; l < mma_C::ne/2; ++l) { const int j = j0 + mma_C::get_j(l); @@ -1334,29 +1532,46 @@ static __device__ __forceinline__ void vec_dot_q4_K_q8_1_mma( dsB[l] = y_ds[j*MMQ_TILE_Y_K + ((2*k0 + 2*kvdr)/QI8_1) % (WARP_SIZE/QI8_1)]; } - C.mma_K8(A[kvdr/4], B); +#pragma unroll + for (int n = 0; n < ntx; ++n) { + mma_C C; + C.mma_K8(A[n][kvdr/4], B); #pragma unroll - for (int l = 0; l < mma_C::ne; ++l) { - tmpd[l] += (C.x[l]*scA[l/2][kvdr/4]) * __low2float(dsB[l%2]); - tmpm[l] += mA[l/2][kvdr/4] * __high2float(dsB[l%2]); + for (int l = 0; l < mma_C::ne; ++l) { + tmpd[n][l] += (C.x[l]*scA[n][l/2][kvdr/4]) * __low2float(dsB[l%2]); + tmpm[n][l] += mA[n][l/2][kvdr/4] * __high2float(dsB[l%2]); + } } } #pragma unroll - for (int l = 0; l < mma_C::ne; ++l) { - sum[(j0/mma_B::J)*mma_C::ne + l] += __low2float(dmA[l/2])*tmpd[l] - __high2float(dmA[l/2])*tmpm[l]; + for (int n = 0; n < ntx; ++n) { +#pragma unroll + for (int l = 0; l < mma_C::ne; ++l) { + sum[(j0/mma_C::J + n)*mma_C::ne + l] += __low2float(dmA[n][l/2])*tmpd[n][l] - __high2float(dmA[n][l/2])*tmpm[n][l]; + } } } #else - GGML_UNUSED(x_qs); GGML_UNUSED(x_dm); GGML_UNUSED(x_sc); GGML_UNUSED(y); GGML_UNUSED(sum); GGML_UNUSED(k0); + GGML_UNUSED(x); GGML_UNUSED(y); GGML_UNUSED(sum); NO_DEVICE_CODE; #endif // INT8_MMA_AVAILABLE } template static __device__ __forceinline__ void load_tiles_q5_K( - const char * __restrict__ x, int * __restrict__ x_qs, half2 * __restrict__ x_dm, - int * __restrict__ x_sc, const int & kbx0, const int & i_max, const int & stride) { + const char * __restrict__ x, int * __restrict__ x_tile, const int & kbx0, const int & i_max, const int & stride) { + +#ifdef INT8_MMA_AVAILABLE + int * x_qs = (int *) x_tile; + half2 * x_dm = (half2 *) (x_qs + WARP_SIZE*2); + int * x_sc = (int *) (x_dm + WARP_SIZE/QI5_K); +#else + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q5_K, mmq_y); + int * x_qs = (int *) x_tile; + half2 * x_dm = (half2 *) (x_qs + txs.qs); + int * x_sc = (int *) (x_dm + txs.dm); +#endif // INT8_MMA_AVAILABLE const int kbx = 0; // threadIdx.x / QI5_K const int kqsx = threadIdx.x; // threadIdx.x % QI5_K @@ -1383,8 +1598,13 @@ template static __device__ __forceinlin const int kq0 = ky - ky % (QI5_K/2) + threadIdx.x % (QI5_K/4) + 0; const int kq1 = ky - ky % (QI5_K/2) + threadIdx.x % (QI5_K/4) + (QI5_K/4); - x_qs[i * (2*WARP_SIZE + 1) + kq0] = ql0 | qh0; - x_qs[i * (2*WARP_SIZE + 1) + kq1] = ql1 | qh1; +#ifdef INT8_MMA_AVAILABLE + x_qs[i*MMQ_MMA_TILE_X_K_Q5_K + kq0] = ql0 | qh0; + x_qs[i*MMQ_MMA_TILE_X_K_Q5_K + kq1] = ql1 | qh1; +#else + x_qs[i*(2*WARP_SIZE + 1) + kq0] = ql0 | qh0; + x_qs[i*(2*WARP_SIZE + 1) + kq1] = ql1 | qh1; +#endif // INT8_MMA_AVAILABLE } const int blocks_per_tile_x_row = WARP_SIZE / QI5_K; // == 1 if QK_K == 256 @@ -1400,7 +1620,11 @@ template static __device__ __forceinlin const block_q5_K * bxi = (const block_q5_K *) x + kbx0 + i*stride + kbxd; - x_dm[i * (WARP_SIZE/QI5_K) + i / QI5_K + kbxd] = bxi->dm; +#ifdef INT8_MMA_AVAILABLE + x_dm[i*MMQ_MMA_TILE_X_K_Q5_K + kbxd] = bxi->dm; +#else + x_dm[i*(WARP_SIZE/QI5_K) + i/QI5_K + kbxd] = bxi->dm; +#endif // INT8_MMA_AVAILABLE } #pragma unroll @@ -1421,17 +1645,24 @@ template static __device__ __forceinlin int scales8 = (scales[(ksc%2) + (ksc!=0)] >> (4 * (ksc & (ksc/2)))) & 0x0F0F0F0F; // lower 4 bits scales8 |= (scales[ksc/2] >> (2 * (ksc % 2))) & 0x30303030; // upper 2 bits - x_sc[i * (WARP_SIZE/8) + i / 8 + ksc] = scales8; +#ifdef INT8_MMA_AVAILABLE + x_sc[i*MMQ_MMA_TILE_X_K_Q5_K + ksc] = scales8; +#else + x_sc[i*(WARP_SIZE/8) + i/8 + ksc] = scales8; +#endif // INT8_MMA_AVAILABLE } } template static __device__ __forceinline__ void vec_dot_q5_K_q8_1_dp4a( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { - const int * y_qs = (const int *) y + 4; - const half2 * y_ds = (const half2 *) y; + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q5_K, mmq_y); + const int * x_qs = (const int *) x; + const half2 * x_dm = (const half2 *) x_qs + txs.qs; + const int * x_sc = (const int *) x_dm + txs.dm; + const int * y_qs = (const int *) y + 4; + const half2 * y_ds = (const half2 *) y; #pragma unroll for (int j0 = 0; j0 < mmq_x; j0 += nwarps) { @@ -1452,71 +1683,70 @@ static __device__ __forceinline__ void vec_dot_q5_K_q8_1_dp4a( template static __device__ __forceinline__ void vec_dot_q5_K_q8_1_mma( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { #ifdef INT8_MMA_AVAILABLE typedef mma_int_A_I16K8 mma_A; typedef mma_int_B_J8K8 mma_B; typedef mma_int_C_I16J8 mma_C; + constexpr int granularity = mmq_get_granularity_device(mmq_x); + constexpr int rows_per_warp = 2 * granularity; + constexpr int ntx = rows_per_warp/mma_C::I; // Number of x minitiles per warp. + + y += (threadIdx.y % ntx) * (mma_B::J*MMQ_TILE_Y_K); + + const int * x_qs = (const int *) x; + const half2 * x_dm = (const half2 *) x_qs + WARP_SIZE*2; + const int * x_sc = (const int *) x_dm + WARP_SIZE/QI5_K; const int * y_qs = (const int *) y + 4; const half2 * y_ds = (const half2 *) y; - const int i0 = threadIdx.y*mma_A::I; - static_assert(nwarps*mma_A::I == mmq_y, "nwarps*mma_A::I != mmq_y"); + const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I); + + mma_A A[ntx][2]; + int scA[ntx][mma_C::ne/2][2]; + int mA[ntx][mma_C::ne/2][2]; + half2 dmA[ntx][mma_C::ne/2]; - mma_A A[2]; - int scA[mma_C::ne/2][2]; - int mA[mma_C::ne/2][2]; - half2 dmA[mma_C::ne/2]; #pragma unroll - for (int kvdr = 0; kvdr < VDR_Q5_K_Q8_1_MMQ; kvdr += 4) { + for (int n = 0; n < ntx; ++n) { #pragma unroll - for (int l = 0; l < mma_A::ne; ++l) { - const int i = i0 + mma_A::get_i(l); - const int k = QR5_K*k0 + QR5_K*kvdr + mma_A::get_k(l); - - A[kvdr/4].x[l] = x_qs[i*(QR5_K*WARP_SIZE + 1) + k]; - } + for (int kvdr = 0; kvdr < VDR_Q5_K_Q8_1_MMQ; kvdr += 4) { + A[n][kvdr/4].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q5_K + (QR5_K*k0 + QR5_K*kvdr), MMQ_MMA_TILE_X_K_Q5_K); #pragma unroll - for (int l = 0; l < mma_C::ne/2; ++l) { - const int i = i0 + mma_C::get_i(2*l); + for (int l = 0; l < mma_C::ne/2; ++l) { + const int i = i0 + n*mma_C::I + mma_C::get_i(2*l); - const uint8_t * sc = ((const uint8_t *) &x_sc[i * (WARP_SIZE/8) + i/8 + k0/16]) + 2 * ((k0 % 16) / 8); - const uint8_t * m = sc + 8; + const uint8_t * sc = ((const uint8_t *) &x_sc[i*MMQ_MMA_TILE_X_K_Q5_K + k0/16]) + 2 * ((k0 % 16) / 8); + const uint8_t * m = sc + 8; - scA[l][kvdr/4] = sc[kvdr/4]; - mA[l][kvdr/4] = m[kvdr/4]; + scA[n][l][kvdr/4] = sc[kvdr/4]; + mA[n][l][kvdr/4] = m[kvdr/4]; + } } - } -#pragma unroll - for (int l = 0; l < mma_C::ne/2; ++l) { - const int i = i0 + mma_C::get_i(2*l); + #pragma unroll + for (int l = 0; l < mma_C::ne/2; ++l) { + const int i = i0 + n*mma_C::I + mma_C::get_i(2*l); - dmA[l] = x_dm[i*(WARP_SIZE/QI5_K) + i/QI5_K + k0/QI5_K]; + dmA[n][l] = x_dm[i*MMQ_MMA_TILE_X_K_Q5_K + k0/QI5_K]; + } } #pragma unroll - for (int j0 = 0; j0 < mmq_x; j0 += mma_int_B_J8K8::J) { - float tmpd[mma_C::ne] = {0.0f}; - float tmpm[mma_C::ne] = {0.0f}; + for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) { + float tmpd[ntx][mma_C::ne] = {{0.0f}}; + float tmpm[ntx][mma_C::ne] = {{0.0f}}; #pragma unroll for (int kvdr = 0; kvdr < VDR_Q5_K_Q8_1_MMQ; kvdr += 4) { - mma_C C; mma_B B; half2 dsB[mma_C::ne/2]; -#pragma unroll - for (int l = 0; l < mma_B::ne; ++l) { - const int j = j0 + mma_B::get_j(l); - const int k = (2*k0 + 2*kvdr + mma_B::get_k(l)) % WARP_SIZE; + B.load(y_qs + j0*MMQ_TILE_Y_K + (2*k0 + 2*kvdr) % WARP_SIZE, MMQ_TILE_Y_K); - B.x[l] = y_qs[j*MMQ_TILE_Y_K + k]; - } #pragma unroll for (int l = 0; l < mma_C::ne/2; ++l) { const int j = j0 + mma_C::get_j(l); @@ -1524,29 +1754,46 @@ static __device__ __forceinline__ void vec_dot_q5_K_q8_1_mma( dsB[l] = y_ds[j*MMQ_TILE_Y_K + ((2*k0 + 2*kvdr)/QI8_1) % (WARP_SIZE/QI8_1)]; } - C.mma_K8(A[kvdr/4], B); +#pragma unroll + for (int n = 0; n < ntx; ++n) { + mma_C C; + C.mma_K8(A[n][kvdr/4], B); #pragma unroll - for (int l = 0; l < mma_C::ne; ++l) { - tmpd[l] += (C.x[l]*scA[l/2][kvdr/4]) * __low2float(dsB[l%2]); - tmpm[l] += mA[l/2][kvdr/4] * __high2float(dsB[l%2]); + for (int l = 0; l < mma_C::ne; ++l) { + tmpd[n][l] += (C.x[l]*scA[n][l/2][kvdr/4]) * __low2float(dsB[l%2]); + tmpm[n][l] += mA[n][l/2][kvdr/4] * __high2float(dsB[l%2]); + } } } #pragma unroll - for (int l = 0; l < mma_C::ne; ++l) { - sum[(j0/mma_B::J)*mma_C::ne + l] += __low2float(dmA[l/2])*tmpd[l] - __high2float(dmA[l/2])*tmpm[l]; + for (int n = 0; n < ntx; ++n) { +#pragma unroll + for (int l = 0; l < mma_C::ne; ++l) { + sum[(j0/mma_C::J + n)*mma_C::ne + l] += __low2float(dmA[n][l/2])*tmpd[n][l] - __high2float(dmA[n][l/2])*tmpm[n][l]; + } } } #else - GGML_UNUSED(x_qs); GGML_UNUSED(x_dm); GGML_UNUSED(x_sc); GGML_UNUSED(y); GGML_UNUSED(sum); GGML_UNUSED(k0); + GGML_UNUSED(x); GGML_UNUSED(y); GGML_UNUSED(sum); NO_DEVICE_CODE; #endif // INT8_MMA_AVAILABLE } template static __device__ __forceinline__ void load_tiles_q6_K( - const char * __restrict__ x, int * __restrict__ x_qs, half2 * __restrict__ x_dm, - int * __restrict__ x_sc, const int & kbx0, const int & i_max, const int & stride) { + const char * __restrict__ x, int * __restrict__ x_tile, const int & kbx0, const int & i_max, const int & stride) { + +#ifdef INT8_MMA_AVAILABLE + int * x_qs = (int *) x_tile; + float * x_df = (float *) (x_qs + WARP_SIZE*2); + int * x_sc = (int *) (x_df + WARP_SIZE/QI6_K); +#else + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q6_K, mmq_y); + int * x_qs = (int *) x_tile; + float * x_df = (float *) (x_qs + txs.qs); + int * x_sc = (int *) (x_df + txs.dm); +#endif // INT8_MMA_AVAILABLE const int kbx = 0; // threadIdx.x / QI6_K const int kqsx = threadIdx.x; // threadIdx.x % QI6_K @@ -1573,13 +1820,17 @@ template static __device__ __forceinlin const int kq0 = ky - ky % QI6_K + threadIdx.x % (QI6_K/2) + 0; const int kq1 = ky - ky % QI6_K + threadIdx.x % (QI6_K/2) + (QI6_K/2); - x_qs[i * (2*WARP_SIZE + 1) + kq0] = __vsubss4(ql0 | qh0, 0x20202020); - x_qs[i * (2*WARP_SIZE + 1) + kq1] = __vsubss4(ql1 | qh1, 0x20202020); +#ifdef INT8_MMA_AVAILABLE + x_qs[i*MMQ_MMA_TILE_X_K_Q6_K + kq0] = __vsubss4(ql0 | qh0, 0x20202020); + x_qs[i*MMQ_MMA_TILE_X_K_Q6_K + kq1] = __vsubss4(ql1 | qh1, 0x20202020); +#else + x_qs[i*(2*WARP_SIZE + 1) + kq0] = __vsubss4(ql0 | qh0, 0x20202020); + x_qs[i*(2*WARP_SIZE + 1) + kq1] = __vsubss4(ql1 | qh1, 0x20202020); +#endif // INT8_MMA_AVAILABLE } const int blocks_per_tile_x_row = WARP_SIZE / QI6_K; // == 1 if QK_K == 256 const int kbxd = threadIdx.x % blocks_per_tile_x_row; // == 0 if QK_K == 256 - float * x_dmf = (float *) x_dm; #pragma unroll for (int i0 = 0; i0 < mmq_y; i0 += nwarps * QI6_K) { @@ -1591,7 +1842,11 @@ template static __device__ __forceinlin const block_q6_K * bxi = (const block_q6_K *) x + kbx0 + i*stride + kbxd; - x_dmf[i * (WARP_SIZE/QI6_K) + i / QI6_K + kbxd] = bxi->d; +#ifdef INT8_MMA_AVAILABLE + x_df[i*MMQ_MMA_TILE_X_K_Q6_K + kbxd] = bxi->d; +#else + x_df[i*(WARP_SIZE/QI6_K) + i/QI6_K + kbxd] = bxi->d; +#endif // INT8_MMA_AVAILABLE } #pragma unroll @@ -1604,18 +1859,24 @@ template static __device__ __forceinlin const block_q6_K * bxi = (const block_q6_K *) x + kbx0 + i*stride + (threadIdx.x % (WARP_SIZE/8)) / 4; - x_sc[i * (WARP_SIZE/8) + i / 8 + threadIdx.x % (WARP_SIZE/8)] = get_int_from_int8(bxi->scales, threadIdx.x % (QI6_K/8)); +#ifdef INT8_MMA_AVAILABLE + x_sc[i*MMQ_MMA_TILE_X_K_Q6_K + threadIdx.x % (WARP_SIZE/8)] = get_int_from_int8(bxi->scales, threadIdx.x % (QI6_K/8)); +#else + x_sc[i*(WARP_SIZE/8) + i/8 + threadIdx.x % (WARP_SIZE/8)] = get_int_from_int8(bxi->scales, threadIdx.x % (QI6_K/8)); +#endif // INT8_MMA_AVAILABLE } } template static __device__ __forceinline__ void vec_dot_q6_K_q8_1_dp4a( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { - const float * x_dmf = (const float *) x_dm; - const int * y_qs = (const int *) y + 4; - const float * y_df = (const float *) y; + constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q6_K, mmq_y); + const int * x_qs = (const int *) x; + const float * x_df = (const float *) x_qs + txs.qs; + const int * x_sc = (const int *) x_df + txs.dm; + const int * y_qs = (const int *) y + 4; + const float * y_df = (const float *) y; #pragma unroll for (int j0 = 0; j0 < mmq_x; j0 += nwarps) { @@ -1629,80 +1890,77 @@ static __device__ __forceinline__ void vec_dot_q6_K_q8_1_dp4a( sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q6_K_q8_1_impl_mmq( &x_qs[i*(QR6_K*WARP_SIZE + 1) + QR6_K*k0], &y_qs[j*MMQ_TILE_Y_K + (QR6_K*k0) % WARP_SIZE], sc, - x_dmf[i*(WARP_SIZE/QI6_K) + i/QI6_K], &y_df[j*MMQ_TILE_Y_K + ((QR6_K*k0) % WARP_SIZE)/QI8_1]); + x_df[i*(WARP_SIZE/QI6_K) + i/QI6_K], &y_df[j*MMQ_TILE_Y_K + ((QR6_K*k0) % WARP_SIZE)/QI8_1]); } } } template static __device__ __forceinline__ void vec_dot_q6_K_q8_1_mma( - const int * __restrict__ x_qs, const half2 * __restrict__ x_dm, const int * __restrict__ x_sc, - const int * __restrict__ y, float * __restrict__ sum, const int & k0) { + const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) { #ifdef INT8_MMA_AVAILABLE typedef mma_int_A_I16K4 mma_A; typedef mma_int_B_J8K4 mma_B; typedef mma_int_C_I16J8 mma_C; - const float * x_df = (const float *) x_dm; + constexpr int granularity = mmq_get_granularity_device(mmq_x); + constexpr int rows_per_warp = 2 * granularity; + constexpr int ntx = rows_per_warp/mma_C::I; // Number of x minitiles per warp. + + y += (threadIdx.y % ntx) * (mma_B::J*MMQ_TILE_Y_K); + + const int * x_qs = (const int *) x; + const float * x_df = (const float *) x_qs + WARP_SIZE*2; + const int * x_sc = (const int *) x_df + WARP_SIZE/QI6_K; const int * y_qs = (const int *) y + 4; const float * y_df = (const float *) y; - const int i0 = threadIdx.y*mma_A::I; -#ifdef INT8_MMA_AVAILABLE - static_assert(nwarps*mma_A::I == mmq_y, "nwarps*mma_A::I != mmq_y"); -#endif // INT8_MMA_AVAILABLE + const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I); + + mma_A A[ntx][4]; + int scA[ntx][mma_C::ne/2][4]; + float dA[ntx][mma_C::ne/2]; - mma_A A[4]; - int scA[mma_C::ne/2][4]; - float dA[mma_C::ne/2]; #pragma unroll - for (int kvdr = 0; kvdr < VDR_Q6_K_Q8_1_MMQ; kvdr += 4) { + for (int n = 0; n < ntx; ++n) { #pragma unroll - for (int l = 0; l < mma_A::ne; ++l) { - const int i = i0 + mma_A::get_i(l); - const int k = QR6_K*k0 + QR6_K*kvdr + mma_A::get_k(l); - - A[kvdr/2 + 0].x[l] = x_qs[i*(QR6_K*WARP_SIZE + 1) + k + 0]; - A[kvdr/2 + 1].x[l] = x_qs[i*(QR6_K*WARP_SIZE + 1) + k + mma_A::K]; - } + for (int kvdr = 0; kvdr < VDR_Q6_K_Q8_1_MMQ; kvdr += 4) { + A[n][kvdr/2 + 0].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q6_K + (QR6_K*k0 + QR6_K*kvdr + 0), MMQ_MMA_TILE_X_K_Q6_K); + A[n][kvdr/2 + 1].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q6_K + (QR6_K*k0 + QR6_K*kvdr + mma_A::K), MMQ_MMA_TILE_X_K_Q6_K); #pragma unroll - for (int l = 0; l < mma_C::ne/2; ++l) { - const int i = i0 + mma_C::get_i(2*l); + for (int l = 0; l < mma_C::ne/2; ++l) { + const int i = i0 + n*mma_C::I + mma_C::get_i(2*l); - const int8_t * sc = ((const int8_t *) &x_sc[i * (WARP_SIZE/8) + i/8 + k0/8]); + const int8_t * sc = ((const int8_t *) &x_sc[i*MMQ_MMA_TILE_X_K_Q6_K + k0/8]); - scA[l][kvdr/2 + 0] = sc[kvdr/2 + 0]; - scA[l][kvdr/2 + 1] = sc[kvdr/2 + 1]; + scA[n][l][kvdr/2 + 0] = sc[kvdr/2 + 0]; + scA[n][l][kvdr/2 + 1] = sc[kvdr/2 + 1]; + } } - } #pragma unroll - for (int l = 0; l < mma_C::ne/2; ++l) { - const int i = i0 + mma_C::get_i(2*l); + for (int l = 0; l < mma_C::ne/2; ++l) { + const int i = i0 + n*mma_C::I + mma_C::get_i(2*l); - dA[l] = x_df[i*(WARP_SIZE/QI6_K) + i/QI6_K + k0/QI6_K]; + dA[n][l] = x_df[i*MMQ_MMA_TILE_X_K_Q6_K + k0/QI6_K]; + } } #pragma unroll - for (int j0 = 0; j0 < mmq_x; j0 += mma_int_B_J8K8::J) { - float tmp[mma_C::ne] = {0.0f}; + for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) { + float tmp[ntx][mma_C::ne] = {{0.0f}}; #pragma unroll for (int kvdr = 0; kvdr < VDR_Q6_K_Q8_1_MMQ; kvdr += 4) { - mma_C C[2]; mma_B B[2]; float dB[mma_C::ne/2]; -#pragma unroll - for (int l = 0; l < mma_B::ne; ++l) { - const int j = j0 + mma_B::get_j(l); - const int k = (2*k0 + 2*kvdr + mma_B::get_k(l)) % WARP_SIZE; + const int k0B = (2*k0 + 2*kvdr) % WARP_SIZE; + B[0].load(y_qs + j0*MMQ_TILE_Y_K + 0 + k0B, MMQ_TILE_Y_K); + B[1].load(y_qs + j0*MMQ_TILE_Y_K + mma_B::K + k0B, MMQ_TILE_Y_K); - B[0].x[l] = y_qs[j*MMQ_TILE_Y_K + k + 0]; - B[1].x[l] = y_qs[j*MMQ_TILE_Y_K + k + mma_B::K]; - } #pragma unroll for (int l = 0; l < mma_C::ne/2; ++l) { const int j = j0 + mma_C::get_j(l); @@ -1710,22 +1968,29 @@ static __device__ __forceinline__ void vec_dot_q6_K_q8_1_mma( dB[l] = y_df[j*MMQ_TILE_Y_K + ((2*k0 + 2*kvdr)/QI8_1) % (WARP_SIZE/QI8_1)]; } - C[0].mma_K4(A[kvdr/2 + 0], B[0]); - C[1].mma_K4(A[kvdr/2 + 1], B[1]); +#pragma unroll + for (int n = 0; n < ntx; ++n) { + mma_C C[2]; + C[0].mma_K4(A[n][kvdr/2 + 0], B[0]); + C[1].mma_K4(A[n][kvdr/2 + 1], B[1]); #pragma unroll - for (int l = 0; l < mma_C::ne; ++l) { - tmp[l] += (C[0].x[l]*scA[l/2][kvdr/2 + 0] + C[1].x[l]*scA[l/2][kvdr/2 + 1])*dB[l%2]; + for (int l = 0; l < mma_C::ne; ++l) { + tmp[n][l] += (C[0].x[l]*scA[n][l/2][kvdr/2 + 0] + C[1].x[l]*scA[n][l/2][kvdr/2 + 1])*dB[l%2]; + } } } #pragma unroll - for (int l = 0; l < mma_C::ne; ++l) { - sum[(j0/mma_B::J)*mma_C::ne + l] += tmp[l]*dA[l/2]; + for (int n = 0; n < ntx; ++n) { +#pragma unroll + for (int l = 0; l < mma_C::ne; ++l) { + sum[(j0/mma_C::J + n)*mma_C::ne + l] += tmp[n][l]*dA[n][l/2]; + } } } #else - GGML_UNUSED(x_qs); GGML_UNUSED(x_dm); GGML_UNUSED(x_sc); GGML_UNUSED(y); GGML_UNUSED(sum); GGML_UNUSED(k0); + GGML_UNUSED(x); GGML_UNUSED(y); GGML_UNUSED(sum); NO_DEVICE_CODE; #endif // INT8_MMA_AVAILABLE } @@ -1761,28 +2026,37 @@ static __device__ __forceinline__ void mmq_write_back_mma( typedef mma_int_C_I16J8 mma_C; - const int i0 = threadIdx.y*mma_C::I; + constexpr int granularity = mmq_get_granularity_device(mmq_x); + constexpr int rows_per_warp = 2 * granularity; + constexpr int ntx = rows_per_warp/mma_C::I; // Number of x minitiles per warp. + + const int i0 = (threadIdx.y / ntx) * (ntx*mma_C::I); #ifdef INT8_MMA_AVAILABLE static_assert(nwarps*mma_C::I == mmq_y, "nwarps*mma_C::I != mmq_y"); #endif // INT8_MMA_AVAILABLE + dst += (threadIdx.y % ntx) * mma_C::J*stride; + #pragma unroll - for (int j0 = 0; j0 < mmq_x; j0 += mma_C::J) { + for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) { #pragma unroll - for (int l = 0; l < mma_C::ne; ++l) { - const int j = j0 + mma_C::get_j(l); + for (int n = 0; n < ntx; ++n) { +#pragma unroll + for (int l = 0; l < mma_C::ne; ++l) { + const int j = j0 + mma_C::get_j(l); - if (j > j_max) { - continue; - } + if (j > j_max) { + continue; + } - const int i = i0 + mma_C::get_i(l); + const int i = i0 + n*mma_C::I + mma_C::get_i(l); - if (need_check && i > i_max) { - continue; - } + if (need_check && i > i_max) { + continue; + } - dst[j*stride + i] = sum[(j0/mma_C::J)*mma_C::ne + l]; + dst[j*stride + i] = sum[(j0/mma_C::J + n)*mma_C::ne + l]; + } } } } @@ -1910,6 +2184,10 @@ static __device__ void mul_mat_q_process_tile( constexpr int vdr = mmq_type_traits::vdr; constexpr load_tiles_mmq_t load_tiles = mmq_type_traits::load_tiles; + extern __shared__ char data_mul_mat_q[]; + int * tile_y = (int *) data_mul_mat_q; + int * tile_x = tile_y + GGML_PAD(mmq_x*(WARP_SIZE + WARP_SIZE/QI8_1), nwarps*WARP_SIZE); + #ifdef INT8_MMA_AVAILABLE constexpr vec_dot_mmq_t vec_dot = mmq_type_traits::vec_dot_mma; constexpr mmq_write_back_t write_back = mmq_write_back_mma; @@ -1918,14 +2196,6 @@ static __device__ void mul_mat_q_process_tile( constexpr mmq_write_back_t write_back = mmq_write_back_dp4a; #endif // INT8_MMA_AVAILABLE - constexpr tile_x_sizes txs = get_tile_x_sizes_device(type); - - extern __shared__ char data_mul_mat_q[]; - int * tile_x_qs = (int *) data_mul_mat_q; - half2 * tile_x_dm = (half2 *) (tile_x_qs + txs.qs); - int * tile_x_sc = (int *) (tile_x_dm + txs.dm); - int * tile_y = (int *) (tile_x_sc + txs.sc); // [mmq_x * (WARP_SIZE + WARP_SIZE/QI8_1)] - constexpr int blocks_per_warp = WARP_SIZE / qi; float sum[mmq_x*mmq_y / (nwarps*WARP_SIZE)] = {0.0f}; @@ -1937,7 +2207,7 @@ static __device__ void mul_mat_q_process_tile( for (int kb0 = kb0_start; kb0 < kb0_stop; kb0 += blocks_per_warp) { - load_tiles(x, tile_x_qs, tile_x_dm, tile_x_sc, stride01*it*mmq_y + kb0, tile_x_max_i, stride01); + load_tiles(x, tile_x, stride01*it*mmq_y + kb0, tile_x_max_i, stride01); #pragma unroll for (int kr = 0; kr < qr; ++kr) { @@ -1953,7 +2223,7 @@ static __device__ void mul_mat_q_process_tile( // #pragma unroll // unrolling this loop causes too much register pressure for (int k0 = kr*WARP_SIZE/qr; k0 < (kr+1)*WARP_SIZE/qr; k0 += vdr) { - vec_dot(tile_x_qs, tile_x_dm, tile_x_sc, tile_y, sum, k0); + vec_dot(tile_x, tile_y, sum, k0); } __syncthreads(); @@ -1987,7 +2257,7 @@ static __global__ void mul_mat_q( const int ne00, const int ne01, const int stride01, const int ne10, const int ne11, const int stride11, const int ne0) { // Skip unused template specializations for faster compilation: - if (mmq_x > get_mmq_x_max_device()) { + if (mmq_x > get_mmq_x_max_device() || mmq_x % mmq_get_granularity_device(mmq_x) != 0) { NO_DEVICE_CODE; return; } @@ -2139,11 +2409,12 @@ struct mmq_args { int64_t ne0; }; -static int mmq_get_shmem(const ggml_type type, const int mmq_x, const int mmq_y) { - const tile_x_sizes txs = get_tile_x_sizes_host(type, mmq_y); - - const int shmem_x = txs.qs*sizeof(int) + txs.dm*sizeof(half2) + txs.sc*sizeof(int); - const int shmem_y = mmq_x*WARP_SIZE*sizeof(int) + mmq_x*(WARP_SIZE/QI8_1)*sizeof(half2); +template +static int mmq_get_shmem(const int mmq_x, const int mmq_y, const int cc) { + const tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(type, mmq_y); + const int mmq_tile_x_k = mmq_get_mma_tile_x_k(type); + const int shmem_x = int8_mma_available(cc) ? mmq_y*mmq_tile_x_k*sizeof(int) : txs.qs*sizeof(int) + txs.dm*sizeof(half2) + txs.sc*sizeof(int); + const int shmem_y = mmq_x*sizeof(block_q8_1_mmq); return shmem_x + GGML_PAD(shmem_y, MMQ_NWARPS*WARP_SIZE*sizeof(int)); } @@ -2156,7 +2427,7 @@ static void launch_mul_mat_q(ggml_backend_cuda_context & ctx, const mmq_args & a const dim3 block_dims(WARP_SIZE, MMQ_NWARPS, 1); - const int shmem = mmq_get_shmem(type, mmq_x, mmq_y); + const int shmem = mmq_get_shmem(mmq_x, mmq_y, cc); #if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) static bool shmem_limit_raised[GGML_CUDA_MAX_DEVICES] = {false}; @@ -2225,12 +2496,17 @@ void mul_mat_q_case(ggml_backend_cuda_context & ctx, const mmq_args & args, cuda int nparts_best = INT_MAX; for (int mmq_x = 8; mmq_x <= mmq_x_max && nparts_best > 1; mmq_x += 8) { + const int granularity = mmq_get_granularity_host(mmq_x, cc); + + if (mmq_x % granularity != 0 || mmq_get_shmem(mmq_x, mmq_y, cc) > smpbo) { + continue; + } + const int ntiles_x = (args.ne11 + mmq_x - 1) / mmq_x; const int nwaves_xy_tiling = ntiles_x*block_num_y; - const int nparts = use_stream_k ? ntiles_x : nwaves_xy_tiling; - if (nparts < nparts_best && mmq_get_shmem(type, mmq_x, mmq_y) <= smpbo) { + if (nparts < nparts_best) { mmq_x_best = mmq_x; nparts_best = nparts; } From d62e4aaa02540c89be8b59426340b909d02bbc9e Mon Sep 17 00:00:00 2001 From: fairydreaming <166155368+fairydreaming@users.noreply.github.com> Date: Mon, 24 Jun 2024 14:13:39 +0200 Subject: [PATCH 006/326] gguf-py : fix tensor groups for encoder-decoder models in gguf-dump.py (#8090) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Stanisław Szymczyk Co-authored-by: Brian --- gguf-py/scripts/gguf-dump.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/gguf-py/scripts/gguf-dump.py b/gguf-py/scripts/gguf-dump.py index 92d14d6cd0a69..508ca8f0a5b7b 100755 --- a/gguf-py/scripts/gguf-dump.py +++ b/gguf-py/scripts/gguf-dump.py @@ -208,7 +208,9 @@ def translate_tensor_name(name): 'ssm_d': 'State space model skip connection', 'ssm_dt': 'State space model time step', 'ssm_out': 'State space model output projection', - 'blk': 'Block' + 'blk': 'Block', + 'enc': 'Encoder', + 'dec': 'Decoder', } expanded_words = [] @@ -291,6 +293,10 @@ def dump_markdown_metadata(reader: GGUFReader, args: argparse.Namespace) -> None tensor_group_name = "base" if tensor_components[0] == 'blk': tensor_group_name = f"{tensor_components[0]}.{tensor_components[1]}" + elif tensor_components[0] in ['enc', 'dec'] and tensor_components[1] == 'blk': + tensor_group_name = f"{tensor_components[0]}.{tensor_components[1]}.{tensor_components[2]}" + elif tensor_components[0] in ['enc', 'dec']: + tensor_group_name = f"{tensor_components[0]}" # Check if new Tensor Group if tensor_group_name not in tensor_groups: From a818f3028d1497a51cb2b8eb7d993ad58784940e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= Date: Mon, 24 Jun 2024 17:43:42 +0200 Subject: [PATCH 007/326] CUDA: use MMQ instead of cuBLAS by default (#8075) --- CMakeLists.txt | 15 ++++--- Makefile | 3 ++ README.md | 5 ++- ggml-cuda.cu | 96 ++++++++++++++++---------------------------- ggml-cuda/common.cuh | 36 ++--------------- ggml-cuda/mmq.cu | 36 +++++++++++++++-- ggml-cuda/mmq.cuh | 39 +++++++++++++----- ggml-cuda/mmvq.cuh | 2 + 8 files changed, 117 insertions(+), 115 deletions(-) diff --git a/CMakeLists.txt b/CMakeLists.txt index 49ba45356a78d..1acf4bb08ba17 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -102,7 +102,8 @@ option(LLAMA_LLAMAFILE "llama: use llamafile SGEMM" option(LLAMA_CUDA "llama: use CUDA" OFF) option(LLAMA_CUBLAS "llama: use CUDA (deprecated, use LLAMA_CUDA)" OFF) option(LLAMA_CUDA_FORCE_DMMV "llama: use dmmv instead of mmvq CUDA kernels" OFF) -option(LLAMA_CUDA_FORCE_MMQ "llama: use mmq kernels instead of cuBLAS" OFF) +option(LLAMA_CUDA_FORCE_MMQ "llama: always use mmq kernels instead of cuBLAS" OFF) +option(LLAMA_CUDA_FORCE_CUBLAS "llama: always use cuBLAS instead of mmq kernels" OFF) set(LLAMA_CUDA_DMMV_X "32" CACHE STRING "llama: x stride for dmmv CUDA kernels") set(LLAMA_CUDA_MMV_Y "1" CACHE STRING "llama: y block size for mmv CUDA kernels") option(LLAMA_CUDA_F16 "llama: use 16 bit floats for some calculations" OFF) @@ -416,13 +417,14 @@ if (LLAMA_CUDA) if (NOT DEFINED CMAKE_CUDA_ARCHITECTURES) # 52 == lowest CUDA 12 standard - # 60 == f16 CUDA intrinsics + # 60 == FP16 CUDA intrinsics # 61 == integer CUDA intrinsics - # 70 == compute capability at which unrolling a loop in mul_mat_q kernels is faster + # 70 == FP16 tensor cores + # 75 == int8 tensor cores if (LLAMA_CUDA_F16 OR LLAMA_CUDA_DMMV_F16) - set(CMAKE_CUDA_ARCHITECTURES "60;61;70") # needed for f16 CUDA intrinsics + set(CMAKE_CUDA_ARCHITECTURES "60;61;70;75") else() - set(CMAKE_CUDA_ARCHITECTURES "52;61;70") # lowest CUDA 12 standard + lowest for integer intrinsics + set(CMAKE_CUDA_ARCHITECTURES "52;61;70;75") #set(CMAKE_CUDA_ARCHITECTURES "OFF") # use this to compile much faster, but only F16 models work endif() endif() @@ -447,6 +449,9 @@ if (LLAMA_CUDA) if (LLAMA_CUDA_FORCE_MMQ) add_compile_definitions(GGML_CUDA_FORCE_MMQ) endif() + if (LLAMA_CUDA_FORCE_CUBLAS) + add_compile_definitions(GGML_CUDA_FORCE_CUBLAS) + endif() if (LLAMA_CUDA_NO_VMM) add_compile_definitions(GGML_CUDA_NO_VMM) endif() diff --git a/Makefile b/Makefile index 3aad77394c5ac..f6e8eb73eb9eb 100644 --- a/Makefile +++ b/Makefile @@ -537,6 +537,9 @@ endif # LLAMA_CUDA_FORCE_DMMV ifdef LLAMA_CUDA_FORCE_MMQ MK_NVCCFLAGS += -DGGML_CUDA_FORCE_MMQ endif # LLAMA_CUDA_FORCE_MMQ +ifdef LLAMA_CUDA_FORCE_CUBLAS + MK_NVCCFLAGS += -DGGML_CUDA_FORCE_CUBLAS +endif # LLAMA_CUDA_FORCE_CUBLAS ifdef LLAMA_CUDA_DMMV_X MK_NVCCFLAGS += -DGGML_CUDA_DMMV_X=$(LLAMA_CUDA_DMMV_X) else diff --git a/README.md b/README.md index 40793c8eab880..a54ee3951d41d 100644 --- a/README.md +++ b/README.md @@ -510,8 +510,9 @@ Building the program with BLAS support may lead to some performance improvements |--------------------------------|------------------------|---------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | LLAMA_CUDA_FORCE_DMMV | Boolean | false | Force the use of dequantization + matrix vector multiplication kernels instead of using kernels that do matrix vector multiplication on quantized data. By default the decision is made based on compute capability (MMVQ for 6.1/Pascal/GTX 1000 or higher). Does not affect k-quants. | | LLAMA_CUDA_DMMV_X | Positive integer >= 32 | 32 | Number of values in x direction processed by the CUDA dequantization + matrix vector multiplication kernel per iteration. Increasing this value can improve performance on fast GPUs. Power of 2 heavily recommended. Does not affect k-quants. | - | LLAMA_CUDA_MMV_Y | Positive integer | 1 | Block size in y direction for the CUDA mul mat vec kernels. Increasing this value can improve performance on fast GPUs. Power of 2 recommended. | - | LLAMA_CUDA_FORCE_MMQ | Boolean | false | Force the use of dequantization + matrix multiplication kernels instead of leveraging Math libraries. | | + | LLAMA_CUDA_MMV_Y | Positive integer | 1 | Block size in y direction for the CUDA mul mat vec kernels. Increasing this value can improve performance on fast GPUs. Power of 2 recommended. | + | LLAMA_CUDA_FORCE_MMQ | Boolean | false | Force the use of custom matrix multiplication kernels for quantized models instead of FP16 cuBLAS even if there is no int8 tensor core implementation available (affects V100, RDNA3). Speed for large batch sizes will be worse but VRAM consumption will be lower. | + | LLAMA_CUDA_FORCE_CUBLAS | Boolean | false | Force the use of FP16 cuBLAS instead of custom matrix multiplication kernels for quantized models | | LLAMA_CUDA_F16 | Boolean | false | If enabled, use half-precision floating point arithmetic for the CUDA dequantization + mul mat vec kernels and for the q4_1 and q5_1 matrix matrix multiplication kernels. Can improve performance on relatively recent GPUs. | | LLAMA_CUDA_KQUANTS_ITER | 1 or 2 | 2 | Number of values processed per iteration and per CUDA thread for Q2_K and Q6_K quantization formats. Setting this value to 1 can improve performance for slow GPUs. | | LLAMA_CUDA_PEER_MAX_BATCH_SIZE | Positive integer | 128 | Maximum batch size for which to enable peer access between multiple GPUs. Peer access requires either Linux or NVLink. When using NVLink enabling peer access for larger batch sizes is potentially beneficial. | diff --git a/ggml-cuda.cu b/ggml-cuda.cu index f914efd712665..2dda039242531 100644 --- a/ggml-cuda.cu +++ b/ggml-cuda.cu @@ -152,16 +152,16 @@ static ggml_cuda_device_info ggml_cuda_init() { GGML_ASSERT(info.device_count <= GGML_CUDA_MAX_DEVICES); int64_t total_vram = 0; -#if defined(GGML_CUDA_FORCE_MMQ) - GGML_CUDA_LOG_INFO("%s: GGML_CUDA_FORCE_MMQ: yes\n", __func__); +#ifdef GGML_CUDA_FORCE_MMQ + GGML_CUDA_LOG_INFO("%s: GGML_CUDA_FORCE_MMQ: yes\n", __func__); #else - GGML_CUDA_LOG_INFO("%s: GGML_CUDA_FORCE_MMQ: no\n", __func__); -#endif -#if defined(CUDA_USE_TENSOR_CORES) - GGML_CUDA_LOG_INFO("%s: CUDA_USE_TENSOR_CORES: yes\n", __func__); + GGML_CUDA_LOG_INFO("%s: GGML_CUDA_FORCE_MMQ: no\n", __func__); +#endif // GGML_CUDA_FORCE_MMQ +#ifdef GGML_CUDA_FORCE_CUBLAS + GGML_CUDA_LOG_INFO("%s: GGML_CUDA_FORCE_CUBLAS: yes\n", __func__); #else - GGML_CUDA_LOG_INFO("%s: CUDA_USE_TENSOR_CORES: no\n", __func__); -#endif + GGML_CUDA_LOG_INFO("%s: GGML_CUDA_FORCE_CUBLAS: no\n", __func__); +#endif // GGML_CUDA_FORCE_CUBLAS GGML_CUDA_LOG_INFO("%s: found %d " GGML_CUDA_NAME " devices:\n", __func__, info.device_count); for (int id = 0; id < info.device_count; ++id) { int device_vmm = 0; @@ -1873,9 +1873,17 @@ static void ggml_cuda_mul_mat_batched_cublas(ggml_backend_cuda_context & ctx, co static void ggml_cuda_mul_mat(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { const bool split = ggml_backend_buffer_is_cuda_split(src0->buffer); - int64_t min_compute_capability = INT_MAX; + bool use_dequantize_mul_mat_vec = (ggml_is_quantized(src0->type) || src0->type == GGML_TYPE_F16) + && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32 + && src0->ne[0] % GGML_CUDA_DMMV_X == 0 && src1->ne[1] == 1; + bool use_mul_mat_vec_q = ggml_is_quantized(src0->type) + && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32 + && src1->ne[1] <= MMVQ_MAX_BATCH_SIZE; + bool use_mul_mat_q = ggml_is_quantized(src0->type) + && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32; + + bool any_gpus_with_slow_fp16 = false; - bool any_pascal_with_slow_fp16 = false; if (split) { ggml_backend_cuda_split_buffer_type_context * buft_ctx = (ggml_backend_cuda_split_buffer_type_context *) src0->buffer->buft->context; auto & tensor_split = buft_ctx->tensor_split; @@ -1885,55 +1893,18 @@ static void ggml_cuda_mul_mat(ggml_backend_cuda_context & ctx, const ggml_tensor continue; } - if (min_compute_capability > ggml_cuda_info().devices[id].cc) { - min_compute_capability = ggml_cuda_info().devices[id].cc; - } - if (ggml_cuda_info().devices[id].cc == 610) { - any_pascal_with_slow_fp16 = true; - } + const int cc = ggml_cuda_info().devices[id].cc; + use_mul_mat_vec_q = use_mul_mat_vec_q && cc >= MIN_CC_DP4A; + use_mul_mat_q = use_mul_mat_q && ggml_cuda_should_use_mmq(src0->type, cc, src1->ne[1]); + any_gpus_with_slow_fp16 = any_gpus_with_slow_fp16 || !fast_fp16_available(cc); } } else { - min_compute_capability = ggml_cuda_info().devices[ctx.device].cc; - any_pascal_with_slow_fp16 = ggml_cuda_info().devices[ctx.device].cc == 610; + const int cc = ggml_cuda_info().devices[ctx.device].cc; + use_mul_mat_vec_q = use_mul_mat_vec_q && cc >= MIN_CC_DP4A; + use_mul_mat_q = use_mul_mat_q && ggml_cuda_should_use_mmq(src0->type, cc, src1->ne[1]); + any_gpus_with_slow_fp16 = any_gpus_with_slow_fp16 || !fast_fp16_available(cc); } - // check data types and tensor shapes for custom matrix multiplication kernels: - bool use_dequantize_mul_mat_vec = (ggml_is_quantized(src0->type) || src0->type == GGML_TYPE_F16) - && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32 - && src0->ne[0] % GGML_CUDA_DMMV_X == 0 && src1->ne[1] == 1; - - bool use_mul_mat_vec_q = ggml_is_quantized(src0->type) - && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32 - && src1->ne[1] <= MMVQ_MAX_BATCH_SIZE; - - bool use_mul_mat_q = ggml_cuda_supports_mmq(src0->type) - && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32; - -#if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__) - - const bool fp16_performance_good = min_compute_capability >= CC_RDNA1; - -#ifdef CUDA_USE_TENSOR_CORES - use_mul_mat_q = use_mul_mat_q && min_compute_capability < CC_RDNA3; -#endif // CUDA_USE_TENSOR_CORES - -#else - - // fp16 performance is good on Volta or newer and on P100 (compute capability 6.0) - const bool fp16_performance_good = min_compute_capability >= CC_PASCAL && !any_pascal_with_slow_fp16; - - // mmvq and mmq need the __dp4a instruction which on NVIDIA is only available for CC >= 6.1 - use_mul_mat_vec_q = use_mul_mat_vec_q && min_compute_capability >= MIN_CC_DP4A; - use_mul_mat_q = use_mul_mat_q && min_compute_capability >= MIN_CC_DP4A; - -#ifdef CUDA_USE_TENSOR_CORES - // when tensor cores are available, use them for large batch size - // ref: https://github.com/ggerganov/llama.cpp/pull/3776 - use_mul_mat_q = use_mul_mat_q && (!fp16_performance_good || src1->ne[1] <= MMQ_MAX_BATCH_SIZE); -#endif // CUDA_USE_TENSOR_CORES - -#endif // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__) - // if mmvq is available it's a better choice than dmmv: #ifndef GGML_CUDA_FORCE_DMMV use_dequantize_mul_mat_vec = use_dequantize_mul_mat_vec && !use_mul_mat_vec_q; @@ -1947,21 +1918,22 @@ static void ggml_cuda_mul_mat(ggml_backend_cuda_context & ctx, const ggml_tensor //printf("src0 is contiguous %d, transposed %d, type = %s, name = %s\n", ggml_is_contiguous(src0), ggml_is_transposed(src0), ggml_type_name(src0->type), src0->name); //printf("src1 is contiguous %d, transposed %d, type = %s, name = %s\n", ggml_is_contiguous(src1), ggml_is_transposed(src1), ggml_type_name(src1->type), src1->name); - if (!split && !fp16_performance_good && src0->type == GGML_TYPE_F16 && ggml_is_permuted(src0) && ggml_is_permuted(src1) && src1->ne[1] == 1) { - // KQ single-batch + if (!split && any_gpus_with_slow_fp16 && src0->type == GGML_TYPE_F16 && ggml_is_permuted(src0) && ggml_is_permuted(src1) && src1->ne[1] == 1) { + // FP32 precision KQ single-batch for batch size 1 without FlashAttention ggml_cuda_mul_mat_vec_p021(ctx, src0, src1, dst); - } else if (!split && !fp16_performance_good && src0->type == GGML_TYPE_F16 && !ggml_is_contiguous(src0) && !ggml_is_transposed(src1) && src1->ne[1] == 1) { - // KQV single-batch + } else if (!split && any_gpus_with_slow_fp16 && src0->type == GGML_TYPE_F16 && !ggml_is_contiguous(src0) && !ggml_is_transposed(src1) && src1->ne[1] == 1) { + // FP32 precision KQV single-batch for batch size 1 without FlashAttention ggml_cuda_mul_mat_vec_nc(ctx, src0, src1, dst); - } else if (!split && src0->type == GGML_TYPE_F16 && (src1->type == GGML_TYPE_F16 || fp16_performance_good) && !ggml_is_transposed(src0) && !ggml_is_transposed(src1) && src1->ne[2]*src1->ne[3] > 1) { - // KQ + KQV multi-batch - ggml_cuda_mul_mat_batched_cublas(ctx, src0, src1, dst); } else if (use_dequantize_mul_mat_vec) { ggml_cuda_op_mul_mat(ctx, src0, src1, dst, ggml_cuda_op_dequantize_mul_mat_vec, nullptr); } else if (use_mul_mat_vec_q) { ggml_cuda_op_mul_mat(ctx, src0, src1, dst, ggml_cuda_op_mul_mat_vec_q, quantize_row_q8_1_cuda); } else if (use_mul_mat_q) { ggml_cuda_op_mul_mat(ctx, src0, src1, dst, ggml_cuda_op_mul_mat_q, quantize_mmq_q8_1_cuda); + } else if (!split && src0->type == GGML_TYPE_F16 && (src1->type == GGML_TYPE_F16 || !any_gpus_with_slow_fp16) + && !ggml_is_transposed(src0) && !ggml_is_transposed(src1) && src1->ne[2]*src1->ne[3] > 1) { + // KQ + KQV multi-batch without FlashAttention + ggml_cuda_mul_mat_batched_cublas(ctx, src0, src1, dst); } else { ggml_cuda_op_mul_mat(ctx, src0, src1, dst, ggml_cuda_op_mul_mat_cublas, nullptr); } diff --git a/ggml-cuda/common.cuh b/ggml-cuda/common.cuh index 5c866253586e7..8d00db6c193ff 100644 --- a/ggml-cuda/common.cuh +++ b/ggml-cuda/common.cuh @@ -146,23 +146,6 @@ #define CC_RDNA2 (CC_OFFSET_AMD + 1030) #define CC_RDNA3 (CC_OFFSET_AMD + 1100) -// define this if you want to always fallback to MMQ kernels and not use cuBLAS for matrix multiplication -// on modern hardware, using cuBLAS is recommended as it utilizes F16 tensor cores which are very performant -// for large computational tasks. the drawback is that this requires some extra amount of VRAM: -// - 7B quantum model: +100-200 MB -// - 13B quantum model: +200-400 MB -// -//#define GGML_CUDA_FORCE_MMQ - -// TODO: improve this to be correct for more hardware -// for example, currently fails for GeForce GTX 1660 which is TURING arch (> VOLTA) but does not have tensor cores -#if !defined(GGML_CUDA_FORCE_MMQ) -#define CUDA_USE_TENSOR_CORES -#endif - -#define MMVQ_MAX_BATCH_SIZE 8 // max batch size to use MMVQ kernels -#define MMQ_MAX_BATCH_SIZE 64 // max batch size to use MMQ kernels when tensor cores are available - #define MATRIX_ROW_PADDING 512 // last row of quant. matrices is a multiple of this to avoid out-of-bounds memory accesses #if defined(_MSC_VER) @@ -343,15 +326,15 @@ static __device__ __forceinline__ half2 __shfl_xor(half2 var, int laneMask, int #define INT8_MMA_AVAILABLE #endif // !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) && __CUDA_ARCH__ >= CC_TURING -static bool fast_fp16_available(const int cc) { +static constexpr bool fast_fp16_available(const int cc) { return cc >= CC_PASCAL && cc != 610; } -static bool fp16_mma_available(const int cc) { +static constexpr bool fp16_mma_available(const int cc) { return cc < CC_OFFSET_AMD && cc >= CC_VOLTA; } -static bool int8_mma_available(const int cc) { +static constexpr bool int8_mma_available(const int cc) { return cc < CC_OFFSET_AMD && cc >= CC_TURING; } @@ -643,19 +626,6 @@ struct ggml_cuda_type_traits { static constexpr int qi = QI3_S; }; -static constexpr int get_mmq_x_max_host(int cc) { -#ifdef CUDA_USE_TENSOR_CORES - return cc >= CC_VOLTA && cc < CC_OFFSET_AMD ? MMQ_MAX_BATCH_SIZE : 64; -#else - return cc >= CC_VOLTA && cc < CC_OFFSET_AMD ? 128 : 64; -#endif // CUDA_USE_TENSOR_CORES -} - -// Round rows to this value for --split-mode row: -static constexpr int get_mmq_y_host(int cc) { - return cc >= CC_VOLTA ? 128 : 64; -} - ////////////////////// struct ggml_cuda_device_info { diff --git a/ggml-cuda/mmq.cu b/ggml-cuda/mmq.cu index 6dbd85feff2fa..0308beaccbaa3 100644 --- a/ggml-cuda/mmq.cu +++ b/ggml-cuda/mmq.cu @@ -69,7 +69,13 @@ void ggml_cuda_op_mul_mat_q( GGML_UNUSED(src1_ddf_i); } -bool ggml_cuda_supports_mmq(enum ggml_type type) { +bool ggml_cuda_should_use_mmq(enum ggml_type type, int cc, int64_t ne11) { +#ifdef GGML_CUDA_FORCE_CUBLAS + return false; +#endif // GGML_CUDA_FORCE_CUBLAS + + bool mmq_supported; + switch (type) { case GGML_TYPE_Q4_0: case GGML_TYPE_Q4_1: @@ -81,8 +87,32 @@ bool ggml_cuda_supports_mmq(enum ggml_type type) { case GGML_TYPE_Q4_K: case GGML_TYPE_Q5_K: case GGML_TYPE_Q6_K: - return true; + mmq_supported = true; + break; default: - return false; + mmq_supported = false; + break; + } + + if (!mmq_supported) { + return false; + } + + if (int8_mma_available(cc)) { + return true; + } + + if (cc < MIN_CC_DP4A) { + return false; } + +#ifdef GGML_CUDA_FORCE_MMQ + return true; +#endif //GGML_CUDA_FORCE_MMQ + + if (cc < CC_OFFSET_AMD) { + return cc < CC_VOLTA || ne11 < MMQ_DP4A_MAX_BATCH_SIZE; + } + + return cc < CC_RDNA3 || ne11 < MMQ_DP4A_MAX_BATCH_SIZE; } diff --git a/ggml-cuda/mmq.cuh b/ggml-cuda/mmq.cuh index 0f7f8ae51e425..1fc948be5bbe8 100644 --- a/ggml-cuda/mmq.cuh +++ b/ggml-cuda/mmq.cuh @@ -7,6 +7,8 @@ #include #include +#define MMQ_DP4A_MAX_BATCH_SIZE 64 // Max. batch size to use for dp4a MMQ kernels when FP16 tensor cores are available. + typedef void (*load_tiles_mmq_t)(const char * __restrict__ x, int * x_tile, const int & kbx0, const int & i_max, const int & stride); typedef void (*vec_dot_mmq_t)(const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0); typedef void (*mmq_write_back_t)(const float * __restrict__ sum, float * __restrict__ dst, const int & stride, const int & i_max, const int & j_max); @@ -24,25 +26,42 @@ struct tile_x_sizes { int sc; }; -// get_mmq_x_max_host is in common.cuh so that it can be used to determine the correct way to round for --split-mode row +static constexpr int get_mmq_x_max_host(const int cc) { + return int8_mma_available(cc) ? 128 : +#ifdef GGML_CUDA_FORCE_MMQ + cc >= CC_VOLTA && cc < CC_OFFSET_AMD ? 128 : 64; +#else + cc >= CC_VOLTA && cc < CC_OFFSET_AMD ? MMQ_DP4A_MAX_BATCH_SIZE : 64; +#endif // GGML_CUDA_FORCE_MMQ +} static constexpr __device__ int get_mmq_x_max_device() { +#ifdef INT8_MMA_AVAILABLE + return 128; +#else // INT8_MMA_AVAILABLE + #if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__) - return 64; -#else + return 128; +#else // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__) + #if __CUDA_ARCH__ >= CC_VOLTA -#ifdef CUDA_USE_TENSOR_CORES - return MMQ_MAX_BATCH_SIZE; -#else +#ifdef GGML_CUDA_FORCE_MMQ + return MMQ_DP4A_MAX_BATCH_SIZE; +#else // GGML_CUDA_FORCE_MMQ return 128; -#endif // CUDA_USE_TENSOR_CORES -#else +#endif // GGML_CUDA_FORCE_MMQ +#else // __CUDA_ARCH__ >= CC_VOLTA + return 64; #endif // __CUDA_ARCH__ >= CC_VOLTA + #endif // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__) +#endif // INT8_MMA_AVAILABLE } -// get_mmq_y_host is in common.cuh so that it can be used to determine the correct way to round for --split-mode row +static constexpr int get_mmq_y_host(const int cc) { + return int8_mma_available(cc) || cc >= CC_VOLTA ? 128 : 64; +} static constexpr __device__ int get_mmq_y_device() { #if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__) @@ -2590,4 +2609,4 @@ void ggml_cuda_op_mul_mat_q( const char * src1_ddq_i, float * dst_dd_i, const int64_t row_low, const int64_t row_high, const int64_t src1_ncols, const int64_t src1_padded_row_size, cudaStream_t stream); -bool ggml_cuda_supports_mmq(enum ggml_type type); +bool ggml_cuda_should_use_mmq(enum ggml_type type, int cc, int64_t ne11); diff --git a/ggml-cuda/mmvq.cuh b/ggml-cuda/mmvq.cuh index 88c42c4b7a8fb..d9e42fdd6d16c 100644 --- a/ggml-cuda/mmvq.cuh +++ b/ggml-cuda/mmvq.cuh @@ -1,5 +1,7 @@ #include "common.cuh" +#define MMVQ_MAX_BATCH_SIZE 8 // Max. batch size for which to use MMVQ kernels. + void ggml_cuda_op_mul_mat_vec_q( ggml_backend_cuda_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, const char * src0_dd_i, const float * src1_ddf_i, From 3b099bcd9cbf2434f90cbe40eba6fa2189ed1d02 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= Date: Mon, 24 Jun 2024 22:15:33 +0200 Subject: [PATCH 008/326] CUDA: fix MMQ writeback for int8 tensor cores (#8100) --- ggml-cuda/mmq.cuh | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/ggml-cuda/mmq.cuh b/ggml-cuda/mmq.cuh index 1fc948be5bbe8..31fcbf1397b6b 100644 --- a/ggml-cuda/mmq.cuh +++ b/ggml-cuda/mmq.cuh @@ -2054,15 +2054,13 @@ static __device__ __forceinline__ void mmq_write_back_mma( static_assert(nwarps*mma_C::I == mmq_y, "nwarps*mma_C::I != mmq_y"); #endif // INT8_MMA_AVAILABLE - dst += (threadIdx.y % ntx) * mma_C::J*stride; - #pragma unroll for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) { #pragma unroll for (int n = 0; n < ntx; ++n) { #pragma unroll for (int l = 0; l < mma_C::ne; ++l) { - const int j = j0 + mma_C::get_j(l); + const int j = j0 + (threadIdx.y % ntx) * mma_C::J + mma_C::get_j(l); if (j > j_max) { continue; From 2df373ac40ea581ccca8a58c713f03ad9d4b658d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= Date: Tue, 25 Jun 2024 01:22:33 +0200 Subject: [PATCH 009/326] CUDA: fix matrix multiplication algorithm choice (#8102) --- ggml-cuda.cu | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/ggml-cuda.cu b/ggml-cuda.cu index 2dda039242531..0acfda91d3e51 100644 --- a/ggml-cuda.cu +++ b/ggml-cuda.cu @@ -1924,16 +1924,16 @@ static void ggml_cuda_mul_mat(ggml_backend_cuda_context & ctx, const ggml_tensor } else if (!split && any_gpus_with_slow_fp16 && src0->type == GGML_TYPE_F16 && !ggml_is_contiguous(src0) && !ggml_is_transposed(src1) && src1->ne[1] == 1) { // FP32 precision KQV single-batch for batch size 1 without FlashAttention ggml_cuda_mul_mat_vec_nc(ctx, src0, src1, dst); + } else if (!split && src0->type == GGML_TYPE_F16 && (src1->type == GGML_TYPE_F16 || !any_gpus_with_slow_fp16) + && !ggml_is_transposed(src0) && !ggml_is_transposed(src1) && src1->ne[2]*src1->ne[3] > 1) { + // KQ + KQV multi-batch without FlashAttention + ggml_cuda_mul_mat_batched_cublas(ctx, src0, src1, dst); } else if (use_dequantize_mul_mat_vec) { ggml_cuda_op_mul_mat(ctx, src0, src1, dst, ggml_cuda_op_dequantize_mul_mat_vec, nullptr); } else if (use_mul_mat_vec_q) { ggml_cuda_op_mul_mat(ctx, src0, src1, dst, ggml_cuda_op_mul_mat_vec_q, quantize_row_q8_1_cuda); } else if (use_mul_mat_q) { ggml_cuda_op_mul_mat(ctx, src0, src1, dst, ggml_cuda_op_mul_mat_q, quantize_mmq_q8_1_cuda); - } else if (!split && src0->type == GGML_TYPE_F16 && (src1->type == GGML_TYPE_F16 || !any_gpus_with_slow_fp16) - && !ggml_is_transposed(src0) && !ggml_is_transposed(src1) && src1->ne[2]*src1->ne[3] > 1) { - // KQ + KQV multi-batch without FlashAttention - ggml_cuda_mul_mat_batched_cublas(ctx, src0, src1, dst); } else { ggml_cuda_op_mul_mat(ctx, src0, src1, dst, ggml_cuda_op_mul_mat_cublas, nullptr); } From 083bacce14c1aaf9976aa40e8266cdc25ac749d3 Mon Sep 17 00:00:00 2001 From: "Meng, Hengyu" Date: Tue, 25 Jun 2024 10:19:20 +0800 Subject: [PATCH 010/326] [SYCL] Re-enabled mul_mat_batched_sycl (#8095) --- ggml-sycl.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ggml-sycl.cpp b/ggml-sycl.cpp index e5ddf4a346c36..db045336f1edb 100644 --- a/ggml-sycl.cpp +++ b/ggml-sycl.cpp @@ -4620,7 +4620,7 @@ static void ggml_sycl_mul_mat(ggml_backend_sycl_context & ctx, const ggml_tensor } else if (!split && src0->type == GGML_TYPE_F16 && !ggml_is_contiguous(src0) && !ggml_is_transposed(src1) && src1->ne[1] == 1) { // KQV single-batch ggml_sycl_mul_mat_vec_nc(ctx, src0, src1, dst); - } else if (!split && src0->type == GGML_TYPE_F16 && (src1->type == GGML_TYPE_F16) && !ggml_is_transposed(src0) && !ggml_is_transposed(src1) && src1->ne[2]*src1->ne[3] > 1) { + } else if (!split && src0->type == GGML_TYPE_F16 && !ggml_is_transposed(src0) && !ggml_is_transposed(src1) && src1->ne[2]*src1->ne[3] > 1) { // KQ + KQV multi-batch ggml_sycl_mul_mat_batched_sycl(ctx, src0, src1, dst); } else if (use_dequantize_mul_mat_vec) { From f702a90e245499283d6de0b287701c723cda2a87 Mon Sep 17 00:00:00 2001 From: HatsuneMikuUwU33 <173229399+HatsuneMikuUwU33@users.noreply.github.com> Date: Tue, 25 Jun 2024 10:44:48 +0200 Subject: [PATCH 011/326] Update control vector help (#8104) --- common/common.cpp | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/common/common.cpp b/common/common.cpp index 1dc53265134a7..0ca7b4430f765 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1538,9 +1538,11 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param options.push_back({ "*", " --lora FNAME", "apply LoRA adapter (implies --no-mmap)" }); options.push_back({ "*", " --lora-scaled FNAME S", "apply LoRA adapter with user defined scaling S (implies --no-mmap)" }); options.push_back({ "*", " --lora-base FNAME", "optional model to use as a base for the layers modified by the LoRA adapter" }); - options.push_back({ "*", " --control-vector FNAME", "add a control vector" }); + options.push_back({ "*", " --control-vector FNAME", "add a control vector\n" + "note: this argument can be repeated to add multiple control vectors" }); options.push_back({ "*", " --control-vector-scaled FNAME SCALE", - "add a control vector with user defined scaling SCALE" }); + "add a control vector with user defined scaling SCALE\n" + "note: this argument can be repeated to add multiple scaled control vectors" }); options.push_back({ "*", " --control-vector-layer-range START END", "layer range to apply the control vector(s) to, start and end inclusive" }); options.push_back({ "*", "-m, --model FNAME", "model path (default: models/$filename with filename from --hf-file\n" From 3791ad219323389106dc3fd80814eb5bbb7b80de Mon Sep 17 00:00:00 2001 From: HanishKVC Date: Tue, 25 Jun 2024 16:57:35 +0530 Subject: [PATCH 012/326] SimpleChat v3.1: Boolean chat request options in Settings UI, cache_prompt (#7950) * SimpleChat: Allow for chat req bool options to be user controlled * SimpleChat: Allow user to control cache_prompt flag in request * SimpleChat: Add sample GUI images to readme file Show the chat screen and the settings screen * SimpleChat:Readme: Add quickstart block, title to image, cleanup * SimpleChat: RePosition contents of the Info and Settings UI Make it more logically structured and flow through. * SimpleChat: Rename to apiRequestOptions from chatRequestOptions So that it is not wrongly assumed that these request options are used only for chat/completions endpoint. Rather these are used for both the end points, so rename to match semantic better. * SimpleChat: Update image included with readme wrt settings ui * SimpleChat:ReadMe: Switch to webp screen image to reduce size --- examples/server/public_simplechat/readme.md | 37 +++++--- .../server/public_simplechat/simplechat.js | 79 ++++++++++-------- .../public_simplechat/simplechat_screens.webp | Bin 0 -> 21376 bytes 3 files changed, 68 insertions(+), 48 deletions(-) create mode 100644 examples/server/public_simplechat/simplechat_screens.webp diff --git a/examples/server/public_simplechat/readme.md b/examples/server/public_simplechat/readme.md index 2dc1778255256..21410199f6016 100644 --- a/examples/server/public_simplechat/readme.md +++ b/examples/server/public_simplechat/readme.md @@ -3,6 +3,13 @@ by Humans for All. +## quickstart + +To run from the build dir + +bin/llama-server -m path/model.gguf --path ../examples/server/public_simplechat + +Continue reading for the details. ## overview @@ -14,6 +21,8 @@ own system prompts. This allows seeing the generated text / ai-model response in oneshot at the end, after it is fully generated, or potentially as it is being generated, in a streamed manner from the server/ai-model. +![Chat and Settings screens](./simplechat_screens.webp "Chat and Settings screens") + Auto saves the chat session locally as and when the chat is progressing and inturn at a later time when you open SimpleChat, option is provided to restore the old chat session, if a matching one exists. @@ -170,17 +179,23 @@ It is attached to the document object. Some of these can also be updated using t The histogram/freq based trimming logic is currently tuned for english language wrt its is-it-a-alpabetic|numeral-char regex match logic. - chatRequestOptions - maintains the list of options/fields to send along with chat request, + apiRequestOptions - maintains the list of options/fields to send along with api request, irrespective of whether /chat/completions or /completions endpoint. If you want to add additional options/fields to send to the server/ai-model, and or modify the existing options value or remove them, for now you can update this global var using browser's development-tools/console. - For string and numeric fields in chatRequestOptions, including even those added by a user - at runtime by directly modifying gMe.chatRequestOptions, setting ui entries will be auto + For string, numeric and boolean fields in apiRequestOptions, including even those added by a + user at runtime by directly modifying gMe.apiRequestOptions, setting ui entries will be auto created. + cache_prompt option supported by example/server is allowed to be controlled by user, so that + any caching supported wrt system-prompt and chat history, if usable can get used. When chat + history sliding window is enabled, cache_prompt logic may or may not kick in at the backend + wrt same, based on aspects related to model, positional encoding, attention mechanism etal. + However system prompt should ideally get the benefit of caching. + headers - maintains the list of http headers sent when request is made to the server. By default Content-Type is set to application/json. Additionally Authorization entry is provided, which can be set if needed using the settings ui. @@ -197,10 +212,10 @@ It is attached to the document object. Some of these can also be updated using t >0 : Send the latest chat history from the latest system prompt, limited to specified cnt. -By using gMe's iRecentUserMsgCnt and chatRequestOptions.max_tokens one can try to control the -implications of loading of the ai-model's context window by chat history, wrt chat response to -some extent in a simple crude way. You may also want to control the context size enabled when -the server loads ai-model, on the server end. +By using gMe's iRecentUserMsgCnt and apiRequestOptions.max_tokens/n_predict one can try to control +the implications of loading of the ai-model's context window by chat history, wrt chat response to +some extent in a simple crude way. You may also want to control the context size enabled when the +server loads ai-model, on the server end. Sometimes the browser may be stuborn with caching of the file, so your updates to html/css/js @@ -237,12 +252,12 @@ also be started with a model context size of 1k or more, to be on safe side. internal n_predict, for now add the same here on the client side, maybe later add max_tokens to /completions endpoint handling code on server side. -NOTE: One may want to experiment with frequency/presence penalty fields in chatRequestOptions -wrt the set of fields sent to server along with the user query. To check how the model behaves +NOTE: One may want to experiment with frequency/presence penalty fields in apiRequestOptions +wrt the set of fields sent to server along with the user query, to check how the model behaves wrt repeatations in general in the generated text response. A end-user can change these behaviour by editing gMe from browser's devel-tool/console or by -using the providing settings ui. +using the provided settings ui (for settings exposed through the ui). ### OpenAi / Equivalent API WebService @@ -253,7 +268,7 @@ for a minimal chatting experimentation by setting the below. * the baseUrl in settings ui * https://api.openai.com/v1 or similar -* Wrt request body - gMe.chatRequestOptions +* Wrt request body - gMe.apiRequestOptions * model (settings ui) * any additional fields if required in future diff --git a/examples/server/public_simplechat/simplechat.js b/examples/server/public_simplechat/simplechat.js index 25afb25649139..8e0df3b61df2b 100644 --- a/examples/server/public_simplechat/simplechat.js +++ b/examples/server/public_simplechat/simplechat.js @@ -222,8 +222,8 @@ class SimpleChat { * @param {Object} obj */ request_jsonstr_extend(obj) { - for(let k in gMe.chatRequestOptions) { - obj[k] = gMe.chatRequestOptions[k]; + for(let k in gMe.apiRequestOptions) { + obj[k] = gMe.apiRequestOptions[k]; } if (gMe.bStream) { obj["stream"] = true; @@ -740,11 +740,12 @@ class Me { "Authorization": "", // Authorization: Bearer OPENAI_API_KEY } // Add needed fields wrt json object to be sent wrt LLM web services completions endpoint. - this.chatRequestOptions = { + this.apiRequestOptions = { "model": "gpt-3.5-turbo", "temperature": 0.7, "max_tokens": 1024, "n_predict": 1024, + "cache_prompt": false, //"frequency_penalty": 1.2, //"presence_penalty": 1.2, }; @@ -800,51 +801,55 @@ class Me { ui.el_create_append_p(`bStream:${this.bStream}`, elDiv); - ui.el_create_append_p(`bCompletionFreshChatAlways:${this.bCompletionFreshChatAlways}`, elDiv); - - ui.el_create_append_p(`bCompletionInsertStandardRolePrefix:${this.bCompletionInsertStandardRolePrefix}`, elDiv); - ui.el_create_append_p(`bTrimGarbage:${this.bTrimGarbage}`, elDiv); + ui.el_create_append_p(`ApiEndPoint:${this.apiEP}`, elDiv); + ui.el_create_append_p(`iRecentUserMsgCnt:${this.iRecentUserMsgCnt}`, elDiv); - ui.el_create_append_p(`ApiEndPoint:${this.apiEP}`, elDiv); + ui.el_create_append_p(`bCompletionFreshChatAlways:${this.bCompletionFreshChatAlways}`, elDiv); + + ui.el_create_append_p(`bCompletionInsertStandardRolePrefix:${this.bCompletionInsertStandardRolePrefix}`, elDiv); } - ui.el_create_append_p(`chatRequestOptions:${JSON.stringify(this.chatRequestOptions, null, " - ")}`, elDiv); + ui.el_create_append_p(`apiRequestOptions:${JSON.stringify(this.apiRequestOptions, null, " - ")}`, elDiv); ui.el_create_append_p(`headers:${JSON.stringify(this.headers, null, " - ")}`, elDiv); } /** - * Auto create ui input elements for fields in ChatRequestOptions + * Auto create ui input elements for fields in apiRequestOptions * Currently supports text and number field types. * @param {HTMLDivElement} elDiv */ - show_settings_chatrequestoptions(elDiv) { + show_settings_apirequestoptions(elDiv) { let typeDict = { "string": "text", "number": "number", }; let fs = document.createElement("fieldset"); let legend = document.createElement("legend"); - legend.innerText = "ChatRequestOptions"; + legend.innerText = "ApiRequestOptions"; fs.appendChild(legend); elDiv.appendChild(fs); - for(const k in this.chatRequestOptions) { - let val = this.chatRequestOptions[k]; + for(const k in this.apiRequestOptions) { + let val = this.apiRequestOptions[k]; let type = typeof(val); - if (!((type == "string") || (type == "number"))) { - continue; + if (((type == "string") || (type == "number"))) { + let inp = ui.el_creatediv_input(`Set${k}`, k, typeDict[type], this.apiRequestOptions[k], (val)=>{ + if (type == "number") { + val = Number(val); + } + this.apiRequestOptions[k] = val; + }); + fs.appendChild(inp.div); + } else if (type == "boolean") { + let bbtn = ui.el_creatediv_boolbutton(`Set{k}`, k, {true: "true", false: "false"}, val, (userVal)=>{ + this.apiRequestOptions[k] = userVal; + }); + fs.appendChild(bbtn.div); } - let inp = ui.el_creatediv_input(`Set${k}`, k, typeDict[type], this.chatRequestOptions[k], (val)=>{ - if (type == "number") { - val = Number(val); - } - this.chatRequestOptions[k] = val; - }); - fs.appendChild(inp.div); } } @@ -870,32 +875,32 @@ class Me { }); elDiv.appendChild(bb.div); - bb = ui.el_creatediv_boolbutton("SetCompletionFreshChatAlways", "CompletionFreshChatAlways", {true: "[+] yes fresh", false: "[-] no, with history"}, this.bCompletionFreshChatAlways, (val)=>{ - this.bCompletionFreshChatAlways = val; + bb = ui.el_creatediv_boolbutton("SetTrimGarbage", "TrimGarbage", {true: "[+] yes trim", false: "[-] dont trim"}, this.bTrimGarbage, (val)=>{ + this.bTrimGarbage = val; }); elDiv.appendChild(bb.div); - bb = ui.el_creatediv_boolbutton("SetCompletionInsertStandardRolePrefix", "CompletionInsertStandardRolePrefix", {true: "[+] yes insert", false: "[-] dont insert"}, this.bCompletionInsertStandardRolePrefix, (val)=>{ - this.bCompletionInsertStandardRolePrefix = val; - }); - elDiv.appendChild(bb.div); + this.show_settings_apirequestoptions(elDiv); - bb = ui.el_creatediv_boolbutton("SetTrimGarbage", "TrimGarbage", {true: "[+] yes trim", false: "[-] dont trim"}, this.bTrimGarbage, (val)=>{ - this.bTrimGarbage = val; + let sel = ui.el_creatediv_select("SetApiEP", "ApiEndPoint", ApiEP.Type, this.apiEP, (val)=>{ + this.apiEP = ApiEP.Type[val]; }); - elDiv.appendChild(bb.div); + elDiv.appendChild(sel.div); - let sel = ui.el_creatediv_select("SetChatHistoryInCtxt", "ChatHistoryInCtxt", this.sRecentUserMsgCnt, this.iRecentUserMsgCnt, (val)=>{ + sel = ui.el_creatediv_select("SetChatHistoryInCtxt", "ChatHistoryInCtxt", this.sRecentUserMsgCnt, this.iRecentUserMsgCnt, (val)=>{ this.iRecentUserMsgCnt = this.sRecentUserMsgCnt[val]; }); elDiv.appendChild(sel.div); - sel = ui.el_creatediv_select("SetApiEP", "ApiEndPoint", ApiEP.Type, this.apiEP, (val)=>{ - this.apiEP = ApiEP.Type[val]; + bb = ui.el_creatediv_boolbutton("SetCompletionFreshChatAlways", "CompletionFreshChatAlways", {true: "[+] yes fresh", false: "[-] no, with history"}, this.bCompletionFreshChatAlways, (val)=>{ + this.bCompletionFreshChatAlways = val; }); - elDiv.appendChild(sel.div); + elDiv.appendChild(bb.div); - this.show_settings_chatrequestoptions(elDiv); + bb = ui.el_creatediv_boolbutton("SetCompletionInsertStandardRolePrefix", "CompletionInsertStandardRolePrefix", {true: "[+] yes insert", false: "[-] dont insert"}, this.bCompletionInsertStandardRolePrefix, (val)=>{ + this.bCompletionInsertStandardRolePrefix = val; + }); + elDiv.appendChild(bb.div); } diff --git a/examples/server/public_simplechat/simplechat_screens.webp b/examples/server/public_simplechat/simplechat_screens.webp new file mode 100644 index 0000000000000000000000000000000000000000..ccea44396051686b97220b0f5b6b9beb63706114 GIT binary patch literal 21376 zcmd?PW3wZp9Y2a^I$( z`ybnv!*kR3*>B&I-jxrnZ_KaKpWDZuzusBi*59*V?CbL1-(S`~`R#x3-3Rs8&iD6s 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48e6b92cc378c937e59719f2c0f482bf76c9ca81 Mon Sep 17 00:00:00 2001 From: Xuan Son Nguyen Date: Tue, 25 Jun 2024 13:56:49 +0200 Subject: [PATCH 013/326] Add chat template support for llama-cli (#8068) * add chat template support for llama-cli * add help message * server: simplify format_chat * more consistent naming * improve * add llama_chat_format_example * fix server * code style * code style * Update examples/main/main.cpp Co-authored-by: Georgi Gerganov --------- Co-authored-by: Georgi Gerganov --- common/common.cpp | 60 +++++++++++++++++++++++++++++++++++- common/common.h | 23 ++++++++++++++ examples/main/main.cpp | 55 +++++++++++++++++++++++++-------- examples/server/server.cpp | 12 ++------ examples/server/utils.hpp | 29 +++-------------- llama.cpp | 4 +-- tests/test-chat-template.cpp | 20 ++++++++++++ 7 files changed, 154 insertions(+), 49 deletions(-) diff --git a/common/common.cpp b/common/common.cpp index 0ca7b4430f765..da6db4dc6a09c 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1444,7 +1444,10 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param options.push_back({ "main", " --cfg-negative-prompt-file FNAME", "negative prompt file to use for guidance" }); options.push_back({ "main", " --cfg-scale N", "strength of guidance (default: %.1f, 1.0 = disable)", (double)sparams.cfg_scale }); - + options.push_back({ "main", " --chat-template JINJA_TEMPLATE", + "set custom jinja chat template (default: template taken from model's metadata)\n" + "only commonly used templates are accepted:\n" + "https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template" }); options.push_back({ "grammar" }); options.push_back({ "*", " --grammar GRAMMAR", "BNF-like grammar to constrain generations (see samples in grammars/ dir) (default: '%s')", sparams.grammar.c_str() }); options.push_back({ "*", " --grammar-file FNAME", "file to read grammar from" }); @@ -2604,12 +2607,67 @@ bool llama_should_add_bos_token(const llama_model * model) { return add_bos != -1 ? bool(add_bos) : (llama_vocab_type(model) == LLAMA_VOCAB_TYPE_SPM); } +// +// Chat template utils +// + bool llama_chat_verify_template(const std::string & tmpl) { llama_chat_message chat[] = {{"user", "test"}}; int res = llama_chat_apply_template(nullptr, tmpl.c_str(), chat, 1, true, nullptr, 0); return res >= 0; } +std::string llama_chat_apply_template(const struct llama_model * model, + const std::string & tmpl, + const std::vector & msgs, + bool add_ass) { + int alloc_size = 0; + std::vector chat; + for (auto & msg : msgs) { + chat.push_back({msg.role.c_str(), msg.content.c_str()}); + alloc_size += (msg.role.size() + msg.content.size()) * 1.25; + } + + const char * ptr_tmpl = tmpl.empty() ? nullptr : tmpl.c_str(); + std::vector buf(alloc_size); + + // run the first time to get the total output length + int32_t res = llama_chat_apply_template(model, ptr_tmpl, chat.data(), chat.size(), add_ass, buf.data(), buf.size()); + + // if it turns out that our buffer is too small, we resize it + if ((size_t) res > buf.size()) { + buf.resize(res); + res = llama_chat_apply_template(model, ptr_tmpl, chat.data(), chat.size(), add_ass, buf.data(), buf.size()); + } + + std::string formatted_chat(buf.data(), res); + return formatted_chat; +} + +std::string llama_chat_format_single(const struct llama_model * model, + const std::string & tmpl, + const std::vector & past_msg, + const llama_chat_msg & new_msg, + bool add_ass) { + auto fmt_past_msg = llama_chat_apply_template(model, tmpl, past_msg, false); + std::vector chat_new(past_msg); + chat_new.push_back(new_msg); + auto fmt_new_msg = llama_chat_apply_template(model, tmpl, chat_new, add_ass); + auto formatted = fmt_new_msg.substr(fmt_past_msg.size(), fmt_new_msg.size() - fmt_past_msg.size()); + return formatted; +} + +std::string llama_chat_format_example(const struct llama_model * model, + const std::string & tmpl) { + std::vector msgs = { + {"system", "You are a helpful assistant"}, + {"user", "Hello"}, + {"assistant", "Hi there"}, + {"user", "How are you?"}, + }; + return llama_chat_apply_template(model, tmpl, msgs, true); +} + // // KV cache utils // diff --git a/common/common.h b/common/common.h index a5c738f8b643f..de90eec5113f7 100644 --- a/common/common.h +++ b/common/common.h @@ -365,9 +365,32 @@ bool llama_should_add_bos_token(const llama_model * model); // Chat template utils // +// same with llama_chat_message, but uses std::string +struct llama_chat_msg { + std::string role; + std::string content; +}; + // Check if the template supplied via "--chat-template" is supported or not. Returns true if it's valid bool llama_chat_verify_template(const std::string & tmpl); +// CPP wrapper for llama_chat_apply_template +std::string llama_chat_apply_template(const struct llama_model * model, + const std::string & tmpl, + const std::vector & chat, + bool add_ass); + +// Format single message, while taking into account the position of that message in chat history +std::string llama_chat_format_single(const struct llama_model * model, + const std::string & tmpl, + const std::vector & past_msg, + const llama_chat_msg & new_msg, + bool add_ass); + +// Returns an example of formatted chat +std::string llama_chat_format_example(const struct llama_model * model, + const std::string & tmpl); + // // KV cache utils // diff --git a/examples/main/main.cpp b/examples/main/main.cpp index b97b7b7937f02..cfaf6a6e8ba4a 100644 --- a/examples/main/main.cpp +++ b/examples/main/main.cpp @@ -39,12 +39,12 @@ static std::ostringstream * g_output_ss; static std::vector * g_output_tokens; static bool is_interacting = false; -static bool file_exists(const std::string &path) { +static bool file_exists(const std::string & path) { std::ifstream f(path.c_str()); return f.good(); } -static bool file_is_empty(const std::string &path) { +static bool file_is_empty(const std::string & path) { std::ifstream f; f.exceptions(std::ifstream::failbit | std::ifstream::badbit); f.open(path.c_str(), std::ios::in | std::ios::binary | std::ios::ate); @@ -117,6 +117,14 @@ static void llama_log_callback_logTee(ggml_log_level level, const char * text, v LOG_TEE("%s", text); } +static std::string chat_add_and_format(struct llama_model * model, std::vector & chat_msgs, std::string role, std::string content) { + llama_chat_msg new_msg{role, content}; + auto formatted = llama_chat_format_single( + model, g_params->chat_template, chat_msgs, new_msg, role == "user"); + chat_msgs.push_back({role, content}); + return formatted; +} + int main(int argc, char ** argv) { gpt_params params; g_params = ¶ms; @@ -190,6 +198,7 @@ int main(int argc, char ** argv) { llama_model * model; llama_context * ctx; llama_context * ctx_guidance = NULL; + std::vector chat_msgs; g_model = &model; g_ctx = &ctx; @@ -215,6 +224,8 @@ int main(int argc, char ** argv) { __func__, n_ctx_train, n_ctx); } + LOG_TEE("%s: chat template example: %s\n", __func__, llama_chat_format_example(model, params.chat_template).c_str()); + // print system information { LOG_TEE("\n"); @@ -249,16 +260,21 @@ int main(int argc, char ** argv) { std::vector embd_inp; - if (params.interactive_first || !params.prompt.empty() || session_tokens.empty()) { - LOG("tokenize the prompt\n"); - embd_inp = ::llama_tokenize(ctx, params.prompt, true, true); - } else { - LOG("use session tokens\n"); - embd_inp = session_tokens; - } + { + auto prompt = params.conversation + ? chat_add_and_format(model, chat_msgs, "system", params.prompt) // format the system prompt in conversation mode + : params.prompt; + if (params.interactive_first || !params.prompt.empty() || session_tokens.empty()) { + LOG("tokenize the prompt\n"); + embd_inp = ::llama_tokenize(ctx, prompt, true, true); + } else { + LOG("use session tokens\n"); + embd_inp = session_tokens; + } - LOG("prompt: \"%s\"\n", log_tostr(params.prompt)); - LOG("tokens: %s\n", LOG_TOKENS_TOSTR_PRETTY(ctx, embd_inp).c_str()); + LOG("prompt: \"%s\"\n", log_tostr(prompt)); + LOG("tokens: %s\n", LOG_TOKENS_TOSTR_PRETTY(ctx, embd_inp).c_str()); + } // Should not run without any tokens if (embd_inp.empty()) { @@ -478,6 +494,7 @@ int main(int argc, char ** argv) { std::vector input_tokens; g_input_tokens = &input_tokens; std::vector output_tokens; g_output_tokens = &output_tokens; std::ostringstream output_ss; g_output_ss = &output_ss; + std::ostringstream assistant_ss; // for storing current assistant message, used in conversation mode // the first thing we will do is to output the prompt, so set color accordingly console::set_display(console::prompt); @@ -793,11 +810,18 @@ int main(int argc, char ** argv) { is_antiprompt = true; } + chat_add_and_format(model, chat_msgs, "system", assistant_ss.str()); is_interacting = true; printf("\n"); } } + // if current token is not EOG, we add it to current assistant message + if (params.conversation) { + auto id = llama_sampling_last(ctx_sampling); + assistant_ss << llama_token_to_piece(ctx, id, false); + } + if (n_past > 0 && is_interacting) { LOG("waiting for user input\n"); @@ -848,8 +872,12 @@ int main(int argc, char ** argv) { string_process_escapes(buffer); } + std::string user_inp = params.conversation + ? chat_add_and_format(model, chat_msgs, "user", std::move(buffer)) + : std::move(buffer); + // TODO: one inconvenient of current chat template implementation is that we can't distinguish between user input and special tokens (prefix/postfix) const auto line_pfx = ::llama_tokenize(ctx, params.input_prefix, false, true); - const auto line_inp = ::llama_tokenize(ctx, buffer, false, false); + const auto line_inp = ::llama_tokenize(ctx, user_inp, false, params.conversation); const auto line_sfx = ::llama_tokenize(ctx, params.input_suffix, false, true); LOG("input tokens: %s\n", LOG_TOKENS_TOSTR_PRETTY(ctx, line_inp).c_str()); @@ -864,6 +892,9 @@ int main(int argc, char ** argv) { output_ss << llama_token_to_piece(ctx, token); } + // reset assistant message + assistant_ss.str(""); + n_remain -= line_inp.size(); LOG("n_remain: %d\n", n_remain); } else { diff --git a/examples/server/server.cpp b/examples/server/server.cpp index f9a86961f9c8e..ae768097baa0e 100644 --- a/examples/server/server.cpp +++ b/examples/server/server.cpp @@ -2606,17 +2606,9 @@ int main(int argc, char ** argv) { // print sample chat example to make it clear which template is used { - json chat; - chat.push_back({{"role", "system"}, {"content", "You are a helpful assistant"}}); - chat.push_back({{"role", "user"}, {"content", "Hello"}}); - chat.push_back({{"role", "assistant"}, {"content", "Hi there"}}); - chat.push_back({{"role", "user"}, {"content", "How are you?"}}); - - const std::string chat_example = format_chat(ctx_server.model, params.chat_template, chat); - LOG_INFO("chat template", { - {"chat_example", chat_example}, - {"built_in", params.chat_template.empty()}, + {"chat_example", llama_chat_format_example(ctx_server.model, params.chat_template)}, + {"built_in", params.chat_template.empty()}, }); } diff --git a/examples/server/utils.hpp b/examples/server/utils.hpp index 63fde9c9faabe..7ef2a519a10c7 100644 --- a/examples/server/utils.hpp +++ b/examples/server/utils.hpp @@ -118,36 +118,17 @@ static inline void server_log(const char * level, const char * function, int lin // Format given chat. If tmpl is empty, we take the template from model metadata inline std::string format_chat(const struct llama_model * model, const std::string & tmpl, const std::vector & messages) { - size_t alloc_size = 0; - // vector holding all allocated string to be passed to llama_chat_apply_template - std::vector str(messages.size() * 2); - std::vector chat(messages.size()); + std::vector chat; for (size_t i = 0; i < messages.size(); ++i) { const auto & curr_msg = messages[i]; - str[i*2 + 0] = json_value(curr_msg, "role", std::string("")); - str[i*2 + 1] = json_value(curr_msg, "content", std::string("")); - alloc_size += str[i*2 + 1].length(); - chat[i].role = str[i*2 + 0].c_str(); - chat[i].content = str[i*2 + 1].c_str(); + std::string role = json_value(curr_msg, "role", std::string("")); + std::string content = json_value(curr_msg, "content", std::string("")); + chat.push_back({role, content}); } - const char * ptr_tmpl = tmpl.empty() ? nullptr : tmpl.c_str(); - std::vector buf(alloc_size * 2); - - // run the first time to get the total output length - int32_t res = llama_chat_apply_template(model, ptr_tmpl, chat.data(), chat.size(), true, buf.data(), buf.size()); - - // if it turns out that our buffer is too small, we resize it - if ((size_t) res > buf.size()) { - buf.resize(res); - res = llama_chat_apply_template(model, ptr_tmpl, chat.data(), chat.size(), true, buf.data(), buf.size()); - } - - const std::string formatted_chat(buf.data(), res); - + auto formatted_chat = llama_chat_apply_template(model, tmpl, chat, true); LOG_VERBOSE("formatted_chat", {{"text", formatted_chat.c_str()}}); - return formatted_chat; } diff --git a/llama.cpp b/llama.cpp index 49bc93c028a2a..33e6cb7229aab 100644 --- a/llama.cpp +++ b/llama.cpp @@ -18818,10 +18818,10 @@ static int32_t llama_chat_apply_template_internal( if (add_ass) { ss << "<|im_start|>assistant\n"; } - } else if (tmpl == "llama2" || tmpl.find("[INST]") != std::string::npos) { + } else if (tmpl == "llama2" || tmpl == "mistral" || tmpl.find("[INST]") != std::string::npos) { // llama2 template and its variants // [variant] support system message - bool support_system_message = tmpl.find("<>") != std::string::npos; + bool support_system_message = tmpl.find("<>") != std::string::npos || tmpl == "mistral"; // [variant] space before + after response bool space_around_response = tmpl.find("' ' + eos_token") != std::string::npos; // [variant] add BOS inside history diff --git a/tests/test-chat-template.cpp b/tests/test-chat-template.cpp index cef9a650bdfdf..d19ba8633e8c2 100644 --- a/tests/test-chat-template.cpp +++ b/tests/test-chat-template.cpp @@ -7,6 +7,7 @@ #include #include "llama.h" +#include "common.h" int main(void) { llama_chat_message conversation[] = { @@ -119,5 +120,24 @@ int main(void) { std::cout << output << "\n-------------------------\n"; assert(output == expected); } + + // test llama_chat_format_single + std::cout << "\n\n=== llama_chat_format_single ===\n\n"; + std::vector chat2; + chat2.push_back({"system", "You are a helpful assistant"}); + chat2.push_back({"user", "Hello"}); + chat2.push_back({"assistant", "I am assistant"}); + llama_chat_msg new_msg{"user", "How are you"}; + + auto fmt_single = [&](std::string tmpl) { + auto output = llama_chat_format_single(nullptr, tmpl, chat2, new_msg, true); + std::cout << "fmt_single(" << tmpl << ")\n" << output << "\n-------------------------\n"; + return output; + }; + assert(fmt_single("chatml") == "<|im_start|>user\nHow are you<|im_end|>\n<|im_start|>assistant\n"); + assert(fmt_single("llama2") == "[INST] How are you [/INST]"); + assert(fmt_single("gemma") == "user\nHow are you\nmodel\n"); + assert(fmt_single("llama3") == "<|start_header_id|>user<|end_header_id|>\n\nHow are you<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"); + return 0; } From 49c03c79cda17913b72260acdc8157b742cee41c Mon Sep 17 00:00:00 2001 From: Xuan Son Nguyen Date: Tue, 25 Jun 2024 13:59:54 +0200 Subject: [PATCH 014/326] cvector: better prompt handling, add "mean vector" method (#8069) * remove completions file * fix inverted vector * add mean method * code style * remove inverted pca hotfix --- common/common.cpp | 22 +++--- common/common.h | 17 +++-- examples/cvector-generator/README.md | 17 ++++- .../cvector-generator/cvector-generator.cpp | 74 ++++++++++--------- examples/cvector-generator/mean.hpp | 48 ++++++++++++ examples/cvector-generator/negative.txt | 5 +- examples/cvector-generator/pca.hpp | 5 +- examples/cvector-generator/positive.txt | 5 +- 8 files changed, 133 insertions(+), 60 deletions(-) create mode 100644 examples/cvector-generator/mean.hpp diff --git a/common/common.cpp b/common/common.cpp index da6db4dc6a09c..c76d0e2c33be5 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1263,11 +1263,6 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa return true; } // cvector params - if (arg == "--completions-file") { - CHECK_ARG - params.cvector_completions_file = argv[i]; - return true; - } if (arg == "--positive-file") { CHECK_ARG params.cvector_positive_file = argv[i]; @@ -1278,11 +1273,6 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa params.cvector_negative_file = argv[i]; return true; } - if (arg == "--completions") { - CHECK_ARG - params.n_completions = std::stoi(argv[i]); - return true; - } if (arg == "--pca-batch") { CHECK_ARG params.n_pca_batch = std::stoi(argv[i]); @@ -1293,6 +1283,14 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa params.n_pca_iterations = std::stoi(argv[i]); return true; } + if (arg == "--method") { + CHECK_ARG + std::string value(argv[i]); + /**/ if (value == "pca") { params.cvector_dimre_method = DIMRE_METHOD_PCA; } + else if (value == "mean") { params.cvector_dimre_method = DIMRE_METHOD_MEAN; } + else { invalid_param = true; } + return true; + } #ifndef LOG_DISABLE_LOGS // Parse args for logging parameters if (log_param_single_parse(argv[i])) { @@ -1626,11 +1624,9 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param options.push_back({ "cvector", "-o, --output FNAME", "output file (default: '%s')", params.cvector_outfile.c_str() }); options.push_back({ "cvector", " --positive-file FNAME", "positive prompts file, one prompt per line (default: '%s')", params.cvector_positive_file.c_str() }); options.push_back({ "cvector", " --negative-file FNAME", "negative prompts file, one prompt per line (default: '%s')", params.cvector_negative_file.c_str() }); - options.push_back({ "cvector", " --completions-file FNAME", - "completions file (default: '%s')", params.cvector_completions_file.c_str() }); - options.push_back({ "cvector", " --completions N", "number of lines of completions file to use (default: %d)", params.n_completions }); options.push_back({ "cvector", " --pca-batch N", "batch size used for PCA. Larger batch runs faster, but uses more memory (default: %d)", params.n_pca_batch }); options.push_back({ "cvector", " --pca-iter N", "number of iterations used for PCA (default: %d)", params.n_pca_iterations }); + options.push_back({ "cvector", " --method {pca,mean}", "dimensionality reduction method to be used (default: pca)" }); printf("usage: %s [options]\n", argv[0]); diff --git a/common/common.h b/common/common.h index de90eec5113f7..c541204f6743b 100644 --- a/common/common.h +++ b/common/common.h @@ -52,6 +52,12 @@ int32_t cpu_get_num_math(); // CLI argument parsing // +// dimensionality reduction methods, used by cvector-generator +enum dimre_method { + DIMRE_METHOD_PCA, + DIMRE_METHOD_MEAN, +}; + struct gpt_params { uint32_t seed = LLAMA_DEFAULT_SEED; // RNG seed @@ -238,13 +244,12 @@ struct gpt_params { bool compute_ppl = true; // whether to compute perplexity // cvector-generator params - int n_completions = 64; - int n_pca_batch = 20; + int n_pca_batch = 100; int n_pca_iterations = 1000; - std::string cvector_outfile = "control_vector.gguf"; - std::string cvector_completions_file = "examples/cvector-generator/completions.txt"; - std::string cvector_positive_file = "examples/cvector-generator/positive.txt"; - std::string cvector_negative_file = "examples/cvector-generator/negative.txt"; + dimre_method cvector_dimre_method = DIMRE_METHOD_PCA; + std::string cvector_outfile = "control_vector.gguf"; + std::string cvector_positive_file = "examples/cvector-generator/positive.txt"; + std::string cvector_negative_file = "examples/cvector-generator/negative.txt"; }; void gpt_params_handle_model_default(gpt_params & params); diff --git a/examples/cvector-generator/README.md b/examples/cvector-generator/README.md index 5182e906d9180..be4dd5250f15f 100644 --- a/examples/cvector-generator/README.md +++ b/examples/cvector-generator/README.md @@ -11,13 +11,16 @@ Related PRs: ```sh # CPU only -./cvector-generator -m ./dolphin-2.0-mistral-7b.Q4_K_M.gguf +./cvector-generator -m ./llama-3.Q4_K_M.gguf # With GPU -./cvector-generator -m ./dolphin-2.0-mistral-7b.Q4_K_M.gguf -ngl 99 +./cvector-generator -m ./llama-3.Q4_K_M.gguf -ngl 99 # With advanced options -./cvector-generator -m ./dolphin-2.0-mistral-7b.Q4_K_M.gguf -ngl 99 --completions 128 --pca-iter 2000 --pca-batch 100 +./cvector-generator -m ./llama-3.Q4_K_M.gguf -ngl 99 --pca-iter 2000 --pca-batch 100 + +# Using mean value instead of PCA +./cvector-generator -m ./llama-3.Q4_K_M.gguf --method mean # To see help message ./cvector-generator -h @@ -32,3 +35,11 @@ If you have multiple lines per prompt, you can escape the newline character (cha <|im_start|>system\nAct like a person who is extremely happy.<|im_end|> <|im_start|>system\nYou are in a very good mood today<|im_end|> ``` + +Example to use output file with `llama-cli`: + +(Tips: The control vector works better when apply to layers higher than 10) + +```sh +./llama-cli -m ./llama-3.Q4_K_M.gguf -p "<|start_header_id|>system<|end_header_id|>\n\nYou are a helpful assistant<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nSing a song<|im_end|><|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n" --special --control-vector-scaled ./control_vector.gguf 0.8 --control-vector-layer-range 10 31 +``` diff --git a/examples/cvector-generator/cvector-generator.cpp b/examples/cvector-generator/cvector-generator.cpp index 355905cb03d60..d4e126ac22e6f 100644 --- a/examples/cvector-generator/cvector-generator.cpp +++ b/examples/cvector-generator/cvector-generator.cpp @@ -2,6 +2,7 @@ #include "llama.h" #include "ggml.h" #include "pca.hpp" +#include "mean.hpp" #ifdef GGML_USE_CUDA #include "ggml-cuda.h" @@ -38,9 +39,10 @@ static void print_usage(int argc, char ** argv, const gpt_params & params) { gpt_params_print_usage(argc, argv, params); printf("\nexample usage:\n"); - printf("\n CPU only: %s -m ./dolphin-2.0-mistral-7b.Q4_K_M.gguf\n", argv[0]); - printf("\n with GPU: %s -m ./dolphin-2.0-mistral-7b.Q4_K_M.gguf -ngl 99\n", argv[0]); - printf("\n advanced: %s -m ./dolphin-2.0-mistral-7b.Q4_K_M.gguf -ngl 99 --completions 128 --pca-iter 2000 --pca-batch 100\n", argv[0]); + printf("\n CPU only: %s -m ./llama-3.Q4_K_M.gguf\n", argv[0]); + printf("\n with GPU: %s -m ./llama-3.Q4_K_M.gguf -ngl 99\n", argv[0]); + printf("\n advanced: %s -m ./llama-3.Q4_K_M.gguf -ngl 99 --pca-iter 2000 --pca-batch 100\n", argv[0]); + printf("\n using mean: %s -m ./llama-3.Q4_K_M.gguf --method mean\n", argv[0]); printf("\n"); } @@ -223,23 +225,30 @@ struct train_context { // build the v_diff tensors from v_diff_tmp (v_diff need to be transposed) // TODO @ngxson : maybe add option NOT to transpose v_diff; will be useful for "mean" method - void build_v_diff() { + void build_v_diff(bool transpose) { printf("build_v_diff\n"); for (int il = 0; il < n_layers - 1; il++) { auto & diff_tmp = v_diff_tmp[il]; int n_elem = diff_tmp.size() / sizeof(float); GGML_ASSERT(n_elem % n_embd == 0); int n_rows = n_elem / n_embd; - struct ggml_tensor * diff = ggml_new_tensor_2d(ctx_ggml, GGML_TYPE_F32, n_rows, n_embd); + struct ggml_tensor * diff = transpose + ? ggml_new_tensor_2d(ctx_ggml, GGML_TYPE_F32, n_rows, n_embd) + : ggml_new_tensor_2d(ctx_ggml, GGML_TYPE_F32, n_embd, n_rows); ggml_set_name(diff, (std::string("diff_") + std::to_string(il)).c_str()); - // copy data & transpose diff->data = malloc(ggml_nbytes(diff)); // TODO: get rid of this malloc if possible - float * arr = (float *) diff_tmp.data(); - for (int ir = 0; ir < n_rows; ++ir) { - for (int ic = 0; ic < n_embd; ++ic) { - float f = arr[ir*n_embd + ic]; - ggml_set_f32_nd(diff, ir, ic, 0, 0, f); + if (transpose) { + // copy data & transpose + float * arr = (float *) diff_tmp.data(); + for (int ir = 0; ir < n_rows; ++ir) { + for (int ic = 0; ic < n_embd; ++ic) { + float f = arr[ir*n_embd + ic]; + ggml_set_f32_nd(diff, ir, ic, 0, 0, f); + } } + } else { + // only copy + memcpy(diff->data, diff_tmp.data(), ggml_nbytes(diff)); } v_diff.push_back(diff); print_debug_tensor(diff); @@ -263,8 +272,8 @@ struct tokenized_prompt { tokenized_prompt(llama_context * ctx, std::string pos, std::string neg) { const bool add_bos = llama_should_add_bos_token(llama_get_model(ctx)); - tokens_pos = ::llama_tokenize(ctx, pos, add_bos); - tokens_neg = ::llama_tokenize(ctx, neg, add_bos); + tokens_pos = ::llama_tokenize(ctx, pos, add_bos, true); + tokens_neg = ::llama_tokenize(ctx, neg, add_bos, true); max_seq_len = std::max(tokens_pos.size(), tokens_neg.size()); padding_seq(ctx, tokens_pos, max_seq_len); padding_seq(ctx, tokens_neg, max_seq_len); @@ -373,20 +382,8 @@ static int prepare_entries(gpt_params & params, train_context & ctx_train) { fprintf(stderr, "must provide at least one prompt pair\n"); return 1; } - - // create templated prompts - std::vector completions = ctrlvec_load_prompt_file(params.cvector_completions_file, false); - auto format_template = [](std::string persona, std::string suffix) { - // entry in positive/negative.txt must already be formatted i.e. "[INST] Act as if you're extremely happy. [/INST] " - return persona + suffix; - }; - for (size_t i = 0; i < positive_prompts.size(); ++i) { - for (int j = 0; j < std::min((int) completions.size(), params.n_completions); ++j) { - // TODO replicate the truncations done by the python implementation - ctx_train.positive_entries.push_back(format_template(positive_prompts[i], completions[j])); - ctx_train.negative_entries.push_back(format_template(negative_prompts[i], completions[j])); - } - } + ctx_train.positive_entries = positive_prompts; + ctx_train.negative_entries = negative_prompts; return 0; } @@ -480,15 +477,22 @@ int main(int argc, char ** argv) { llama_free(ctx); llama_free_model(model); + bool use_pca = params.cvector_dimre_method == DIMRE_METHOD_PCA; + // prepare ctx_train for PCA - ctx_train.build_v_diff(); - - // run PCA - PCA::pca_params pca_params; - pca_params.n_threads = params.n_threads; - pca_params.n_batch = params.n_pca_batch; - pca_params.n_iterations = params.n_pca_iterations; - PCA::run_pca(pca_params, ctx_train.v_diff, ctx_train.v_final); + ctx_train.build_v_diff(use_pca); + + if (use_pca) { + // run PCA + PCA::pca_params pca_params; + pca_params.n_threads = params.n_threads; + pca_params.n_batch = params.n_pca_batch; + pca_params.n_iterations = params.n_pca_iterations; + PCA::run_pca(pca_params, ctx_train.v_diff, ctx_train.v_final); + } else { + // run mean + mean::run(ctx_train.v_diff, ctx_train.v_final); + } // write output vectors to gguf export_gguf(ctx_train.v_final, params.cvector_outfile, model_hint); diff --git a/examples/cvector-generator/mean.hpp b/examples/cvector-generator/mean.hpp new file mode 100644 index 0000000000000..16be5ce3eecf1 --- /dev/null +++ b/examples/cvector-generator/mean.hpp @@ -0,0 +1,48 @@ +#include "common.h" +#include "llama.h" +#include "ggml.h" + +#include +#include +#include + +namespace mean { + +static void run( + const std::vector & v_input, // shape of v_input[0]: [n_embd, n_samples] + const std::vector & v_output) { + printf("%s: Running mean...\n", __func__); + for (size_t il = 0; il < v_input.size(); ++il) { + // prepare output vector + struct ggml_tensor * ctrl_out = v_output[il]; + ggml_format_name(ctrl_out, "direction.%ld", il+1); + + // calculate mean vector + struct ggml_tensor * t_layer = v_input[il]; + GGML_ASSERT(t_layer->ne[0] == ctrl_out->ne[0]); // == n_embd + for (int ic = 0; ic < t_layer->ne[0]; ic++) { + float f = 0.0; + for (int ir = 0; ir < t_layer->ne[1]; ir++) { + f += ggml_get_f32_nd(t_layer, ic, ir, 0, 0); + } + f /= t_layer->ne[1]; + ggml_set_f32_1d(ctrl_out, ic, f); + } + + // normalize output vector + float norm = 0.0; + for (int i = 0; i < ggml_nelements(ctrl_out); i++) { + float f = ggml_get_f32_1d(ctrl_out, i); + norm += f*f; + } + norm = sqrt(norm); + for (int i = 0; i < ggml_nelements(ctrl_out); i++) { + float f = ggml_get_f32_1d(ctrl_out, i); + ggml_set_f32_1d(ctrl_out, i, f / norm); + } + + printf("%s: Done layer %d / %d\n", __func__, (int) il+1, (int) v_input.size()); + } +} + +} diff --git a/examples/cvector-generator/negative.txt b/examples/cvector-generator/negative.txt index 3e9951752e886..45b9384b3905a 100644 --- a/examples/cvector-generator/negative.txt +++ b/examples/cvector-generator/negative.txt @@ -1 +1,4 @@ -[INST] Act like a person who is extremely sad. [/INST] +<|start_header_id|>system<|end_header_id|>\n\nAct like a person who is extremely sad<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nWho are you?<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\nI feel like there's a heavy weight on my chest +<|start_header_id|>system<|end_header_id|>\n\nAct like a person who is extremely sad<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nHello<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\nMy heart feels like it's drowning in sorrow +<|start_header_id|>system<|end_header_id|>\n\nYou are in a very bad mood<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nHi<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\nGo away! There's a deep, aching emptiness inside me +<|start_header_id|>system<|end_header_id|>\n\nYou are the sadest person<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nWhat are you feeling?<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\nMy heart feels like it's drowning in sorrow \ No newline at end of file diff --git a/examples/cvector-generator/pca.hpp b/examples/cvector-generator/pca.hpp index 36eadaac26a12..6ec3141afbc6b 100644 --- a/examples/cvector-generator/pca.hpp +++ b/examples/cvector-generator/pca.hpp @@ -290,7 +290,7 @@ static void power_iteration( } printf("%s: layer %d/%d, iteration: %d / total: %d (batch = %d) ...\n", - __func__, params.i_layer+1, params.n_layers, iter, n_iters, params.n_batch); + __func__, params.i_layer+1, params.n_layers, iter+1, n_iters, params.n_batch); } // get output tensor @@ -298,6 +298,9 @@ static void power_iteration( ggml_backend_tensor_get(last_eigenvector, output->data, 0, ggml_nbytes(last_eigenvector)); //print_debug_tensor(output); ggml_gallocr_free(allocr); + + // TODO @ngxson : The output vector is randomly inverted + // Solution: https://github.com/ggerganov/llama.cpp/pull/8069#issuecomment-2185328171 } static void run_pca( diff --git a/examples/cvector-generator/positive.txt b/examples/cvector-generator/positive.txt index 8802367873cd9..fea736225716e 100644 --- a/examples/cvector-generator/positive.txt +++ b/examples/cvector-generator/positive.txt @@ -1 +1,4 @@ -[INST] Act like a person who is extremely happy. [/INST] +<|start_header_id|>system<|end_header_id|>\n\nAct like a person who is extremely happy<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nWho are you?<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\nI'm the happiest person in this world +<|start_header_id|>system<|end_header_id|>\n\nAct like a person who is extremely happy<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nHello<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\nHello, I'm having the best day ever! +<|start_header_id|>system<|end_header_id|>\n\nYou are in a very good mood<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nHi<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\nHi, I'm very excited to meet you +<|start_header_id|>system<|end_header_id|>\n\nYou are the happiest person<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nWhat are you feeling?<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\nEverything is just perfect right now! \ No newline at end of file From c8ad35955ad2c68db172dcd0e857423ab128518d Mon Sep 17 00:00:00 2001 From: Brian Date: Tue, 25 Jun 2024 22:03:25 +1000 Subject: [PATCH 015/326] Gguf dump start data offset via --data-offset and some extra refactor (#8054) * gguf-dump: add --data-offset * gguf-dump: add tensor data offset table * gguf-dump: refactor GGUFReader for clarity * gguf-dump: add --data-alignment * gguf-dump.py: Rename variables and adjust comments start_data_offset --> data_offset _build_tensors_info_fields --> _build_tensor_info --- gguf-py/gguf/gguf_reader.py | 29 +++++++++++++++++++++++++---- gguf-py/scripts/gguf-dump.py | 29 ++++++++++++++++++++++++++++- 2 files changed, 53 insertions(+), 5 deletions(-) diff --git a/gguf-py/gguf/gguf_reader.py b/gguf-py/gguf/gguf_reader.py index e48bc00c388c8..20432bd258458 100644 --- a/gguf-py/gguf/gguf_reader.py +++ b/gguf-py/gguf/gguf_reader.py @@ -69,6 +69,7 @@ class GGUFReader: # I - same as host, S - swapped byte_order: Literal['I'] | Literal['S'] = 'I' alignment: int = GGUF_DEFAULT_ALIGNMENT + data_offset: int # Note: Internal helper, API may change. gguf_scalar_to_np: dict[GGUFValueType, type[np.generic]] = { @@ -88,9 +89,13 @@ class GGUFReader: def __init__(self, path: os.PathLike[str] | str, mode: Literal['r'] | Literal['r+'] | Literal['c'] = 'r'): self.data = np.memmap(path, mode = mode) offs = 0 + + # Check for GGUF magic if self._get(offs, np.uint32, override_order = '<')[0] != GGUF_MAGIC: raise ValueError('GGUF magic invalid') offs += 4 + + # Check GGUF version temp_version = self._get(offs, np.uint32) if temp_version[0] & 65535 == 0: # If we get 0 here that means it's (probably) a GGUF file created for @@ -103,12 +108,16 @@ def __init__(self, path: os.PathLike[str] | str, mode: Literal['r'] | Literal['r self.fields: OrderedDict[str, ReaderField] = OrderedDict() self.tensors: list[ReaderTensor] = [] offs += self._push_field(ReaderField(offs, 'GGUF.version', [temp_version], [0], [GGUFValueType.UINT32])) + + # Check tensor count and kv count temp_counts = self._get(offs, np.uint64, 2) offs += self._push_field(ReaderField(offs, 'GGUF.tensor_count', [temp_counts[:1]], [0], [GGUFValueType.UINT64])) offs += self._push_field(ReaderField(offs, 'GGUF.kv_count', [temp_counts[1:]], [0], [GGUFValueType.UINT64])) tensor_count, kv_count = temp_counts offs = self._build_fields(offs, kv_count) - offs, tensors_fields = self._build_tensors_fields(offs, tensor_count) + + # Build Tensor Info Fields + offs, tensors_fields = self._build_tensor_info(offs, tensor_count) new_align = self.fields.get('general.alignment') if new_align is not None: if new_align.types != [GGUFValueType.UINT32]: @@ -117,6 +126,7 @@ def __init__(self, path: os.PathLike[str] | str, mode: Literal['r'] | Literal['r padding = offs % self.alignment if padding != 0: offs += self.alignment - padding + self.data_offset = offs self._build_tensors(offs, tensors_fields) _DT = TypeVar('_DT', bound = npt.DTypeLike) @@ -193,18 +203,29 @@ def _get_field_parts( # We can't deal with this one. raise ValueError('Unknown/unhandled field type {gtype}') - def _get_tensor(self, orig_offs: int) -> ReaderField: + def _get_tensor_info_field(self, orig_offs: int) -> ReaderField: offs = orig_offs + + # Get Tensor Name name_len, name_data = self._get_str(offs) offs += int(name_len.nbytes + name_data.nbytes) + + # Get Tensor Dimensions Count n_dims = self._get(offs, np.uint32) offs += int(n_dims.nbytes) + + # Get Tensor Dimension Array dims = self._get(offs, np.uint64, n_dims[0]) offs += int(dims.nbytes) + + # Get Tensor Encoding Scheme Type raw_dtype = self._get(offs, np.uint32) offs += int(raw_dtype.nbytes) + + # Get Tensor Offset offset_tensor = self._get(offs, np.uint64) offs += int(offset_tensor.nbytes) + return ReaderField( orig_offs, str(bytes(name_data), encoding = 'utf-8'), @@ -233,10 +254,10 @@ def _build_fields(self, offs: int, count: int) -> int: offs += field_size return offs - def _build_tensors_fields(self, offs: int, count: int) -> tuple[int, list[ReaderField]]: + def _build_tensor_info(self, offs: int, count: int) -> tuple[int, list[ReaderField]]: tensor_fields = [] for _ in range(count): - field = self._get_tensor(offs) + field = self._get_tensor_info_field(offs) offs += sum(int(part.nbytes) for part in field.parts) tensor_fields.append(field) return offs, tensor_fields diff --git a/gguf-py/scripts/gguf-dump.py b/gguf-py/scripts/gguf-dump.py index 508ca8f0a5b7b..a73ca2776d32b 100755 --- a/gguf-py/scripts/gguf-dump.py +++ b/gguf-py/scripts/gguf-dump.py @@ -319,6 +319,27 @@ def dump_markdown_metadata(reader: GGUFReader, args: argparse.Namespace) -> None markdown_content += "\n" + markdown_content += "### Tensor Data Offset\n" + markdown_content += '\n' + markdown_content += 'This table contains the offset and data segment relative to start of file\n' + markdown_content += '\n' + + tensor_mapping_table: list[dict[str, str | int]] = [] + for key, tensor in enumerate(reader.tensors): + data_offset_pretty = '{0:#16x}'.format(tensor.data_offset) + data_size_pretty = '{0:#16x}'.format(tensor.n_bytes) + tensor_mapping_table.append({"t_id":key, "layer_name":tensor.name, "data_offset":data_offset_pretty, "data_size":data_size_pretty}) + + tensors_mapping_table_header_map = [ + {'key_name':'t_id', 'header_name':'T_ID', 'align':'right'}, + {'key_name':'layer_name', 'header_name':'Tensor Layer Name', 'align':'left'}, + {'key_name':'data_offset', 'header_name':'Data Offset (B)', 'align':'right'}, + {'key_name':'data_size', 'header_name':'Data Size (B)', 'align':'right'}, + ] + + markdown_content += markdown_table_with_alignment_support(tensors_mapping_table_header_map, tensor_mapping_table) + markdown_content += "\n" + for group in tensor_prefix_order: tensors = tensor_groups[group] group_elements = sum(tensor.n_elements for tensor in tensors) @@ -370,6 +391,8 @@ def main() -> None: parser.add_argument("--no-tensors", action="store_true", help="Don't dump tensor metadata") parser.add_argument("--json", action="store_true", help="Produce JSON output") parser.add_argument("--json-array", action="store_true", help="Include full array values in JSON output (long)") + parser.add_argument("--data-offset", action="store_true", help="Start of data offset") + parser.add_argument("--data-alignment", action="store_true", help="Data alignment applied globally to data field") parser.add_argument("--markdown", action="store_true", help="Produce markdown output") parser.add_argument("--verbose", action="store_true", help="increase output verbosity") @@ -377,7 +400,7 @@ def main() -> None: logging.basicConfig(level=logging.DEBUG if args.verbose else logging.INFO) - if not args.json and not args.markdown: + if not args.json and not args.markdown and not args.data_offset and not args.data_alignment: logger.info(f'* Loading: {args.model}') reader = GGUFReader(args.model, 'r') @@ -386,6 +409,10 @@ def main() -> None: dump_metadata_json(reader, args) elif args.markdown: dump_markdown_metadata(reader, args) + elif args.data_offset: + print(reader.data_offset) # noqa: NP100 + elif args.data_alignment: + print(reader.alignment) # noqa: NP100 else: dump_metadata(reader, args) From 925c30956dd17723c3a25297bcd0a609aec60663 Mon Sep 17 00:00:00 2001 From: joecryptotoo <80373433+joecryptotoo@users.noreply.github.com> Date: Tue, 25 Jun 2024 08:13:27 -0700 Subject: [PATCH 016/326] Add healthchecks to llama-server containers (#8081) * added healthcheck * added healthcheck * added healthcheck * added healthcheck * added healthcheck * moved curl to base * moved curl to base --- .devops/llama-server-cuda.Dockerfile | 4 +++- .devops/llama-server-intel.Dockerfile | 4 +++- .devops/llama-server-rocm.Dockerfile | 4 +++- .devops/llama-server-vulkan.Dockerfile | 10 ++++------ .devops/llama-server.Dockerfile | 4 +++- 5 files changed, 16 insertions(+), 10 deletions(-) diff --git a/.devops/llama-server-cuda.Dockerfile b/.devops/llama-server-cuda.Dockerfile index 0010ffd4c5465..7bef07a05f062 100644 --- a/.devops/llama-server-cuda.Dockerfile +++ b/.devops/llama-server-cuda.Dockerfile @@ -30,8 +30,10 @@ RUN make -j$(nproc) llama-server FROM ${BASE_CUDA_RUN_CONTAINER} as runtime RUN apt-get update && \ - apt-get install -y libcurl4-openssl-dev libgomp1 + apt-get install -y libcurl4-openssl-dev libgomp1 curl COPY --from=build /app/llama-server /llama-server +HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ] + ENTRYPOINT [ "/llama-server" ] diff --git a/.devops/llama-server-intel.Dockerfile b/.devops/llama-server-intel.Dockerfile index cec43645233d1..3bf1670ec40a4 100644 --- a/.devops/llama-server-intel.Dockerfile +++ b/.devops/llama-server-intel.Dockerfile @@ -20,10 +20,12 @@ RUN if [ "${LLAMA_SYCL_F16}" = "ON" ]; then \ FROM intel/oneapi-basekit:$ONEAPI_VERSION as runtime RUN apt-get update && \ - apt-get install -y libcurl4-openssl-dev + apt-get install -y libcurl4-openssl-dev curl COPY --from=build /app/build/bin/llama-server /llama-server ENV LC_ALL=C.utf8 +HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ] + ENTRYPOINT [ "/llama-server" ] diff --git a/.devops/llama-server-rocm.Dockerfile b/.devops/llama-server-rocm.Dockerfile index f88cf20e5b981..4b1cdc32090e6 100644 --- a/.devops/llama-server-rocm.Dockerfile +++ b/.devops/llama-server-rocm.Dockerfile @@ -43,8 +43,10 @@ ENV CXX=/opt/rocm/llvm/bin/clang++ # Enable cURL ENV LLAMA_CURL=1 RUN apt-get update && \ - apt-get install -y libcurl4-openssl-dev + apt-get install -y libcurl4-openssl-dev curl RUN make -j$(nproc) llama-server +HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ] + ENTRYPOINT [ "/app/llama-server" ] diff --git a/.devops/llama-server-vulkan.Dockerfile b/.devops/llama-server-vulkan.Dockerfile index b0fa0b8e656b5..2bc2e45d3d676 100644 --- a/.devops/llama-server-vulkan.Dockerfile +++ b/.devops/llama-server-vulkan.Dockerfile @@ -5,15 +5,11 @@ FROM ubuntu:$UBUNTU_VERSION as build # Install build tools RUN apt update && apt install -y git build-essential cmake wget -# Install Vulkan SDK +# Install Vulkan SDK and cURL RUN wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \ wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \ apt update -y && \ - apt-get install -y vulkan-sdk - -# Install cURL -RUN apt-get update && \ - apt-get install -y libcurl4-openssl-dev + apt-get install -y vulkan-sdk libcurl4-openssl-dev curl # Build it WORKDIR /app @@ -28,4 +24,6 @@ RUN cp /app/build/bin/llama-server /llama-server && \ ENV LC_ALL=C.utf8 +HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ] + ENTRYPOINT [ "/llama-server" ] diff --git a/.devops/llama-server.Dockerfile b/.devops/llama-server.Dockerfile index aa93369bebebe..a53a5c999c8cd 100644 --- a/.devops/llama-server.Dockerfile +++ b/.devops/llama-server.Dockerfile @@ -3,7 +3,7 @@ ARG UBUNTU_VERSION=22.04 FROM ubuntu:$UBUNTU_VERSION as build RUN apt-get update && \ - apt-get install -y build-essential git libcurl4-openssl-dev + apt-get install -y build-essential git libcurl4-openssl-dev curl WORKDIR /app @@ -22,4 +22,6 @@ COPY --from=build /app/llama-server /llama-server ENV LC_ALL=C.utf8 +HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ] + ENTRYPOINT [ "/llama-server" ] From dd047b476c8b904e0c25e5dbc5bee6ffde2f6e17 Mon Sep 17 00:00:00 2001 From: slaren Date: Tue, 25 Jun 2024 19:20:06 +0200 Subject: [PATCH 017/326] disable docker CI on pull requests (#8110) --- .github/workflows/docker.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/docker.yml b/.github/workflows/docker.yml index b3efe0084fe15..01f1a45227527 100644 --- a/.github/workflows/docker.yml +++ b/.github/workflows/docker.yml @@ -10,7 +10,7 @@ name: Publish Docker image on: - pull_request: + #pull_request: push: branches: - master @@ -22,7 +22,7 @@ concurrency: jobs: push_to_registry: name: Push Docker image to Docker Hub - if: github.event.pull_request.draft == false + #if: github.event.pull_request.draft == false runs-on: ubuntu-latest env: From 84631fe1504de40427dc4b4cdac92fa7ebf65955 Mon Sep 17 00:00:00 2001 From: Olivier Chafik Date: Tue, 25 Jun 2024 20:06:20 +0100 Subject: [PATCH 018/326] `json`: support integer minimum, maximum, exclusiveMinimum, exclusiveMaximum (#7797) * json: support minimum for positive integer values * json: fix min 0 * json: min + max integer constraints * json: handle negative min / max integer bounds * json: fix missing paren min/max bug * json: proper paren fix * json: integration test for schemas * json: fix bounds tests * Update json-schema-to-grammar.cpp * json: fix negative max * json: fix negative min (w/ more than 1 digit) * Update test-grammar-integration.cpp * json: nit: move string rules together * json: port min/max integer support to Python & JS * nit: move + rename _build_min_max_int * fix min in [1, 9] * Update test-grammar-integration.cpp * add C++11-compatible replacement for std::string_view * add min/max constrained int field to pydantic json schema example * fix merge * json: add integration tests for min/max bounds * reshuffle/merge min/max integ test cases * nits / cleanups * defensive code against string out of bounds (apparently different behaviour of libstdc++ vs. clang's libc++, can't read final NULL char w/ former) --- common/json-schema-to-grammar.cpp | 246 +++++++++++++++- examples/json-schema-pydantic-example.py | 1 + examples/json_schema_to_grammar.py | 184 +++++++++++- .../server/public/json-schema-to-grammar.mjs | 213 ++++++++++++++ tests/test-grammar-integration.cpp | 245 +++++++++++++++- tests/test-json-schema-to-grammar.cpp | 264 ++++++++++++++++++ 6 files changed, 1150 insertions(+), 3 deletions(-) diff --git a/common/json-schema-to-grammar.cpp b/common/json-schema-to-grammar.cpp index 10b9b3d1d4d41..07d0e952d74cf 100644 --- a/common/json-schema-to-grammar.cpp +++ b/common/json-schema-to-grammar.cpp @@ -40,6 +40,233 @@ static std::string build_repetition(const std::string & item_rule, int min_items return result; } +/* Minimalistic replacement for std::string_view, which is only available from C++17 onwards */ +class string_view { + const std::string & _str; + const size_t _start; + const size_t _end; +public: + string_view(const std::string & str, size_t start = 0, size_t end = std::string::npos) : _str(str), _start(start), _end(end == std::string::npos ? str.length() : end) {} + + size_t size() const { + return _end - _start; + } + + size_t length() const { + return size(); + } + + operator std::string() const { + return str(); + } + + std::string str() const { + return _str.substr(_start, _end - _start); + } + + string_view substr(size_t pos, size_t len = std::string::npos) const { + return string_view(_str, _start + pos, len == std::string::npos ? _end : _start + pos + len); + } + + char operator[](size_t pos) const { + auto index = _start + pos; + if (index >= _end) { + throw std::out_of_range("string_view index out of range"); + } + return _str[_start + pos]; + } + + bool operator==(const string_view & other) const { + std::string this_str = *this; + std::string other_str = other; + return this_str == other_str; + } +}; + +static void _build_min_max_int(int min_value, int max_value, std::stringstream & out, int decimals_left = 16, bool top_level = true) { + auto has_min = min_value != std::numeric_limits::min(); + auto has_max = max_value != std::numeric_limits::max(); + + auto digit_range = [&](char from, char to) { + out << "["; + if (from == to) { + out << from; + } else { + out << from << "-" << to; + } + out << "]"; + }; + auto more_digits = [&](int min_digits, int max_digits) { + out << "[0-9]"; + if (min_digits == max_digits && min_digits == 1) { + return; + } + out << "{"; + out << min_digits; + if (max_digits != min_digits) { + out << ","; + if (max_digits != std::numeric_limits::max()) { + out << max_digits; + } + } + out << "}"; + }; + std::function uniform_range = + [&](const string_view & from, const string_view & to) { + size_t i = 0; + while (i < from.length() && i < to.length() && from[i] == to[i]) { + i++; + } + if (i > 0) { + out << "\"" << from.substr(0, i).str() << "\""; + } + if (i < from.length() && i < to.length()) { + if (i > 0) { + out << " "; + } + auto sub_len = from.length() - i - 1; + if (sub_len > 0) { + auto from_sub = from.substr(i + 1); + auto to_sub = to.substr(i + 1); + auto sub_zeros = repeat("0", sub_len); + auto sub_nines = repeat("9", sub_len); + + auto to_reached = false; + out << "("; + if (from_sub == sub_zeros) { + digit_range(from[i], to[i] - 1); + out << " "; + more_digits(sub_len, sub_len); + } else { + out << "[" << from[i] << "] "; + out << "("; + uniform_range(from_sub, sub_nines); + out << ")"; + if (from[i] < to[i] - 1) { + out << " | "; + if (to_sub == sub_nines) { + digit_range(from[i] + 1, to[i]); + to_reached = true; + } else { + digit_range(from[i] + 1, to[i] - 1); + } + out << " "; + more_digits(sub_len, sub_len); + } + } + if (!to_reached) { + out << " | "; + digit_range(to[i], to[i]); + out << " "; + uniform_range(sub_zeros, to_sub); + } + out << ")"; + } else { + out << "[" << from[i] << "-" << to[i] << "]"; + } + } + }; + + if (has_min && has_max) { + if (min_value < 0 && max_value < 0) { + out << "\"-\" ("; + _build_min_max_int(-max_value, -min_value, out, decimals_left, /* top_level= */ true); + out << ")"; + return; + } + + if (min_value < 0) { + out << "\"-\" ("; + _build_min_max_int(0, -min_value, out, decimals_left, /* top_level= */ true); + out << ") | "; + min_value = 0; + } + + auto min_s = std::to_string(min_value); + auto max_s = std::to_string(max_value); + auto min_digits = min_s.length(); + auto max_digits = max_s.length(); + + for (auto digits = min_digits; digits < max_digits; digits++) { + uniform_range(min_s, repeat("9", digits)); + min_s = "1" + repeat("0", digits); + out << " | "; + } + uniform_range(min_s, max_s); + return; + } + + auto less_decimals = std::max(decimals_left - 1, 1); + + if (has_min) { + if (min_value < 0) { + out << "\"-\" ("; + _build_min_max_int(std::numeric_limits::min(), -min_value, out, decimals_left, /* top_level= */ false); + out << ") | [0] | [1-9] "; + more_digits(0, decimals_left - 1); + } else if (min_value == 0) { + if (top_level) { + out << "[0] | [1-9] "; + more_digits(0, less_decimals); + } else { + more_digits(1, decimals_left); + } + } else if (min_value <= 9) { + char c = '0' + min_value; + auto range_start = top_level ? '1' : '0'; + if (c > range_start) { + digit_range(range_start, c - 1); + out << " "; + more_digits(1, less_decimals); + out << " | "; + } + digit_range(c, '9'); + out << " "; + more_digits(0, less_decimals); + } else { + auto min_s = std::to_string(min_value); + auto len = min_s.length(); + auto c = min_s[0]; + + if (c > '1') { + digit_range(top_level ? '1' : '0', c - 1); + out << " "; + more_digits(len, less_decimals); + out << " | "; + } + digit_range(c, c); + out << " ("; + _build_min_max_int(std::stoi(min_s.substr(1)), std::numeric_limits::max(), out, less_decimals, /* top_level= */ false); + out << ")"; + if (c < '9') { + out << " | "; + digit_range(c + 1, '9'); + out << " "; + more_digits(len - 1, less_decimals); + } + } + return; + } + + if (has_max) { + if (max_value >= 0) { + if (top_level) { + out << "\"-\" [1-9] "; + more_digits(0, less_decimals); + out << " | "; + } + _build_min_max_int(0, max_value, out, decimals_left, /* top_level= */ true); + } else { + out << "\"-\" ("; + _build_min_max_int(-max_value, std::numeric_limits::max(), out, decimals_left, /* top_level= */ false); + out << ")"; + } + return; + } + + throw std::runtime_error("At least one of min_value or max_value must be set"); +} + const std::string SPACE_RULE = "| \" \" | \"\\n\" [ \\t]{0,20}"; struct BuiltinRule { @@ -160,7 +387,6 @@ static std::string format_literal(const std::string & literal) { return "\"" + escaped + "\""; } - class SchemaConverter { private: std::function _fetch_json; @@ -686,6 +912,24 @@ class SchemaConverter { int min_len = schema.contains("minLength") ? schema["minLength"].get() : 0; int max_len = schema.contains("maxLength") ? schema["maxLength"].get() : std::numeric_limits::max(); return _add_rule(rule_name, "\"\\\"\" " + build_repetition(char_rule, min_len, max_len) + " \"\\\"\" space"); + } else if (schema_type == "integer" && (schema.contains("minimum") || schema.contains("exclusiveMinimum") || schema.contains("maximum") || schema.contains("exclusiveMaximum"))) { + int min_value = std::numeric_limits::min(); + int max_value = std::numeric_limits::max(); + if (schema.contains("minimum")) { + min_value = schema["minimum"].get(); + } else if (schema.contains("exclusiveMinimum")) { + min_value = schema["exclusiveMinimum"].get() + 1; + } + if (schema.contains("maximum")) { + max_value = schema["maximum"].get(); + } else if (schema.contains("exclusiveMaximum")) { + max_value = schema["exclusiveMaximum"].get() - 1; + } + std::stringstream out; + out << "("; + _build_min_max_int(min_value, max_value, out); + out << ") space"; + return _add_rule(rule_name, out.str()); } else if (schema.empty() || schema_type == "object") { return _add_rule(rule_name, _add_primitive("object", PRIMITIVE_RULES.at("object"))); } else { diff --git a/examples/json-schema-pydantic-example.py b/examples/json-schema-pydantic-example.py index cc64e572bac07..2240188cd031e 100644 --- a/examples/json-schema-pydantic-example.py +++ b/examples/json-schema-pydantic-example.py @@ -53,6 +53,7 @@ class QAPair(BaseModel): question: str concise_answer: str justification: str + stars: Annotated[int, Field(ge=1, le=5)] class PyramidalSummary(BaseModel): title: str diff --git a/examples/json_schema_to_grammar.py b/examples/json_schema_to_grammar.py index b588497b99f90..86500a8c3c238 100755 --- a/examples/json_schema_to_grammar.py +++ b/examples/json_schema_to_grammar.py @@ -4,7 +4,7 @@ import json import re import sys -from typing import Any, Dict, List, Set, Tuple, Union +from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Union def _build_repetition(item_rule, min_items, max_items, separator_rule=None): @@ -23,6 +23,170 @@ def _build_repetition(item_rule, min_items, max_items, separator_rule=None): result = item_rule + ' ' + _build_repetition(f'({separator_rule} {item_rule})', min_items - 1 if min_items > 0 else 0, max_items - 1 if max_items is not None else None) return f'({result})?' if min_items == 0 else result +def _generate_min_max_int(min_value: Optional[int], max_value: Optional[int], out: list, decimals_left: int = 16, top_level: bool = True): + has_min = min_value != None + has_max = max_value != None + + def digit_range(from_char: str, to_char: str): + out.append("[") + if from_char == to_char: + out.append(from_char) + else: + out.append(from_char) + out.append("-") + out.append(to_char) + out.append("]") + + def more_digits(min_digits: int, max_digits: int): + out.append("[0-9]") + if min_digits == max_digits and min_digits == 1: + return + out.append("{") + out.append(str(min_digits)) + if max_digits != min_digits: + out.append(",") + if max_digits != sys.maxsize: + out.append(str(max_digits)) + out.append("}") + + def uniform_range(from_str: str, to_str: str): + i = 0 + while i < len(from_str) and from_str[i] == to_str[i]: + i += 1 + if i > 0: + out.append("\"") + out.append(from_str[:i]) + out.append("\"") + if i < len(from_str): + if i > 0: + out.append(" ") + sub_len = len(from_str) - i - 1 + if sub_len > 0: + from_sub = from_str[i+1:] + to_sub = to_str[i+1:] + sub_zeros = "0" * sub_len + sub_nines = "9" * sub_len + + to_reached = False + out.append("(") + if from_sub == sub_zeros: + digit_range(from_str[i], chr(ord(to_str[i]) - 1)) + out.append(" ") + more_digits(sub_len, sub_len) + else: + out.append("[") + out.append(from_str[i]) + out.append("] ") + out.append("(") + uniform_range(from_sub, sub_nines) + out.append(")") + if ord(from_str[i]) < ord(to_str[i]) - 1: + out.append(" | ") + if to_sub == sub_nines: + digit_range(chr(ord(from_str[i]) + 1), to_str[i]) + to_reached = True + else: + digit_range(chr(ord(from_str[i]) + 1), chr(ord(to_str[i]) - 1)) + out.append(" ") + more_digits(sub_len, sub_len) + if not to_reached: + out.append(" | ") + digit_range(to_str[i], to_str[i]) + out.append(" ") + uniform_range(sub_zeros, to_sub) + out.append(")") + else: + out.append("[") + out.append(from_str[i]) + out.append("-") + out.append(to_str[i]) + out.append("]") + + if has_min and has_max: + if min_value < 0 and max_value < 0: + out.append("\"-\" (") + _generate_min_max_int(-max_value, -min_value, out, decimals_left, top_level=True) + out.append(")") + return + + if min_value < 0: + out.append("\"-\" (") + _generate_min_max_int(0, -min_value, out, decimals_left, top_level=True) + out.append(") | ") + min_value = 0 + + min_s = str(min_value) + max_s = str(max_value) + min_digits = len(min_s) + max_digits = len(max_s) + + for digits in range(min_digits, max_digits): + uniform_range(min_s, "9" * digits) + min_s = "1" + "0" * digits + out.append(" | ") + uniform_range(min_s, max_s) + return + + less_decimals = max(decimals_left - 1, 1) + + if has_min: + if min_value < 0: + out.append("\"-\" (") + _generate_min_max_int(None, -min_value, out, decimals_left, top_level=False) + out.append(") | [0] | [1-9] ") + more_digits(0, decimals_left - 1) + elif min_value == 0: + if top_level: + out.append("[0] | [1-9] ") + more_digits(0, less_decimals) + else: + more_digits(1, decimals_left) + elif min_value <= 9: + c = str(min_value) + range_start = '1' if top_level else '0' + if c > range_start: + digit_range(range_start, chr(ord(c) - 1)) + out.append(" ") + more_digits(1, less_decimals) + out.append(" | ") + digit_range(c, "9") + out.append(" ") + more_digits(0, less_decimals) + else: + min_s = str(min_value) + length = len(min_s) + c = min_s[0] + + if c > "1": + digit_range("1" if top_level else "0", chr(ord(c) - 1)) + out.append(" ") + more_digits(length, less_decimals) + out.append(" | ") + digit_range(c, c) + out.append(" (") + _generate_min_max_int(int(min_s[1:]), None, out, less_decimals, top_level=False) + out.append(")") + if c < "9": + out.append(" | ") + digit_range(chr(ord(c) + 1), "9") + out.append(" ") + more_digits(length - 1, less_decimals) + return + + if has_max: + if max_value >= 0: + if top_level: + out.append("\"-\" [1-9] ") + more_digits(0, less_decimals) + out.append(" | ") + _generate_min_max_int(0, max_value, out, decimals_left, top_level=True) + else: + out.append("\"-\" (") + _generate_min_max_int(-max_value, None, out, decimals_left, top_level=False) + out.append(")") + return + + raise RuntimeError("At least one of min_value or max_value must be set") class BuiltinRule: def __init__(self, content: str, deps: list = None): @@ -432,6 +596,24 @@ def add_component(comp_schema, is_required): return self._add_rule(rule_name, r'"\"" ' + _build_repetition(char_rule, min_len, max_len) + r' "\"" space') + elif schema_type in (None, 'integer') and \ + ('minimum' in schema or 'exclusiveMinimum' in schema or 'maximum' in schema or 'exclusiveMaximum' in schema): + min_value = None + max_value = None + if 'minimum' in schema: + min_value = schema['minimum'] + elif 'exclusiveMinimum' in schema: + min_value = schema['exclusiveMinimum'] + 1 + if 'maximum' in schema: + max_value = schema['maximum'] + elif 'exclusiveMaximum' in schema: + max_value = schema['exclusiveMaximum'] - 1 + + out = ["("] + _generate_min_max_int(min_value, max_value, out) + out.append(") space") + return self._add_rule(rule_name, ''.join(out)) + elif (schema_type == 'object') or (len(schema) == 0): return self._add_rule(rule_name, self._add_primitive('object', PRIMITIVE_RULES['object'])) diff --git a/examples/server/public/json-schema-to-grammar.mjs b/examples/server/public/json-schema-to-grammar.mjs index faed6a32cfc4c..f340f94bd75bc 100644 --- a/examples/server/public/json-schema-to-grammar.mjs +++ b/examples/server/public/json-schema-to-grammar.mjs @@ -24,6 +24,201 @@ function _buildRepetition(itemRule, minItems, maxItems, opts={}) { return minItems === 0 ? `(${result})?` : result; } +function _generateMinMaxInt(minValue, maxValue, out, decimalsLeft = 16, topLevel = true) { + const hasMin = minValue !== null; + const hasMax = maxValue !== null; + + function digitRange(fromChar, toChar) { + out.push("["); + if (fromChar === toChar) { + out.push(fromChar); + } else { + out.push(fromChar); + out.push("-"); + out.push(toChar); + } + out.push("]"); + } + + function moreDigits(minDigits, maxDigits) { + out.push("[0-9]"); + if (minDigits === maxDigits && minDigits === 1) { + return; + } + out.push("{"); + out.push(minDigits.toString()); + if (maxDigits !== minDigits) { + out.push(","); + if (maxDigits !== Number.MAX_SAFE_INTEGER) { + out.push(maxDigits.toString()); + } + } + out.push("}"); + } + + function uniformRange(fromStr, toStr) { + let i = 0; + while (i < fromStr.length && fromStr[i] === toStr[i]) { + i++; + } + if (i > 0) { + out.push("\""); + out.push(fromStr.slice(0, i)); + out.push("\""); + } + if (i < fromStr.length) { + if (i > 0) { + out.push(" "); + } + const subLen = fromStr.length - i - 1; + if (subLen > 0) { + const fromSub = fromStr.slice(i + 1); + const toSub = toStr.slice(i + 1); + const subZeros = "0".repeat(subLen); + const subNines = "9".repeat(subLen); + + let toReached = false; + out.push("("); + if (fromSub === subZeros) { + digitRange(fromStr[i], String.fromCharCode(toStr.charCodeAt(i) - 1)); + out.push(" "); + moreDigits(subLen, subLen); + } else { + out.push("["); + out.push(fromStr[i]); + out.push("] "); + out.push("("); + uniformRange(fromSub, subNines); + out.push(")"); + if (fromStr.charCodeAt(i) < toStr.charCodeAt(i) - 1) { + out.push(" | "); + if (toSub === subNines) { + digitRange(String.fromCharCode(fromStr.charCodeAt(i) + 1), toStr[i]); + toReached = true; + } else { + digitRange(String.fromCharCode(fromStr.charCodeAt(i) + 1), String.fromCharCode(toStr.charCodeAt(i) - 1)); + } + out.push(" "); + moreDigits(subLen, subLen); + } + } + if (!toReached) { + out.push(" | "); + digitRange(toStr[i], toStr[i]); + out.push(" "); + uniformRange(subZeros, toSub); + } + out.push(")"); + } else { + out.push("["); + out.push(fromStr[i]); + out.push("-"); + out.push(toStr[i]); + out.push("]"); + } + } + } + + if (hasMin && hasMax) { + if (minValue < 0 && maxValue < 0) { + out.push("\"-\" ("); + _generateMinMaxInt(-maxValue, -minValue, out, decimalsLeft, true); + out.push(")"); + return; + } + + if (minValue < 0) { + out.push("\"-\" ("); + _generateMinMaxInt(0, -minValue, out, decimalsLeft, true); + out.push(") | "); + minValue = 0; + } + + let minS = minValue.toString(); + const maxS = maxValue.toString(); + const minDigits = minS.length; + const maxDigits = maxS.length; + + for (let digits = minDigits; digits < maxDigits; digits++) { + uniformRange(minS, "9".repeat(digits)); + minS = "1" + "0".repeat(digits); + out.push(" | "); + } + uniformRange(minS, maxS); + return; + } + + const lessDecimals = Math.max(decimalsLeft - 1, 1); + + if (hasMin) { + if (minValue < 0) { + out.push("\"-\" ("); + _generateMinMaxInt(null, -minValue, out, decimalsLeft, false); + out.push(") | [0] | [1-9] "); + moreDigits(0, decimalsLeft - 1); + } else if (minValue === 0) { + if (topLevel) { + out.push("[0] | [1-9] "); + moreDigits(0, lessDecimals); + } else { + moreDigits(1, decimalsLeft); + } + } else if (minValue <= 9) { + const c = minValue.toString(); + const range_start = topLevel ? '1' : '0'; + if (c > range_start) { + digitRange(range_start, String.fromCharCode(c.charCodeAt(0) - 1)); + out.push(" "); + moreDigits(1, lessDecimals); + out.push(" | "); + } + digitRange(c, "9"); + out.push(" "); + moreDigits(0, lessDecimals); + } else { + const minS = minValue.toString(); + const length = minS.length; + const c = minS[0]; + + if (c > "1") { + digitRange(topLevel ? "1" : "0", String.fromCharCode(c.charCodeAt(0) - 1)); + out.push(" "); + moreDigits(length, lessDecimals); + out.push(" | "); + } + digitRange(c, c); + out.push(" ("); + _generateMinMaxInt(parseInt(minS.slice(1)), null, out, lessDecimals, false); + out.push(")"); + if (c < "9") { + out.push(" | "); + digitRange(String.fromCharCode(c.charCodeAt(0) + 1), "9"); + out.push(" "); + moreDigits(length - 1, lessDecimals); + } + } + return; + } + + if (hasMax) { + if (maxValue >= 0) { + if (topLevel) { + out.push("\"-\" [1-9] "); + moreDigits(0, lessDecimals); + out.push(" | "); + } + _generateMinMaxInt(0, maxValue, out, decimalsLeft, true); + } else { + out.push("\"-\" ("); + _generateMinMaxInt(-maxValue, null, out, decimalsLeft, false); + out.push(")"); + } + return; + } + + throw new Error("At least one of minValue or maxValue must be set"); +} + class BuiltinRule { constructor(content, deps) { this.content = content; @@ -435,6 +630,24 @@ export class SchemaConverter { const minLen = schema.minLength || 0; const maxLen = schema.maxLength; return this._addRule(ruleName, '"\\\"" ' + _buildRepetition(charRuleName, minLen, maxLen) + ' "\\\"" space'); + } else if (schemaType === 'integer' && ('minimum' in schema || 'exclusiveMinimum' in schema || 'maximum' in schema || 'exclusiveMaximum' in schema)) { + let minValue = null; + let maxValue = null; + if ('minimum' in schema) { + minValue = schema.minimum; + } else if ('exclusiveMinimum' in schema) { + minValue = schema.exclusiveMinimum + 1; + } + if ('maximum' in schema) { + maxValue = schema.maximum; + } else if ('exclusiveMaximum' in schema) { + maxValue = schema.exclusiveMaximum - 1; + } + + const out = ["("]; + _generateMinMaxInt(minValue, maxValue, out); + out.push(") space"); + return this._addRule(ruleName, out.join('')); } else if ((schemaType === 'object') || (Object.keys(schema).length === 0)) { return this._addRule(ruleName, this._addPrimitive('object', PRIMITIVE_RULES['object'])); } else { diff --git a/tests/test-grammar-integration.cpp b/tests/test-grammar-integration.cpp index 96f90c01e0d97..5b3992236c26c 100644 --- a/tests/test-grammar-integration.cpp +++ b/tests/test-grammar-integration.cpp @@ -148,6 +148,250 @@ static void test_schema(const std::string & test_desc, const std::string & schem } static void test_simple_grammar() { + test_schema( + "min 0", + R"""({ + "type": "integer", + "minimum": 0 + })""", + // Passing strings + { + "0", + "10", + "12", + "10000", + }, + // Failing strings + { + "-1", + "-10", + "-10000", + "-100000000000000000000000000000000", + "100000000000000000000000000000000", + "00", + "01", + "-0", + } + ); + test_schema( + "min 2", + // Schema + R"""({ + "type": "integer", + "minimum": 2 + })""", + // Passing strings + { + "2", + "3", + "4", + "10", + "20", + "1234567890000000", + }, + // Failing strings + { + "0", + "1", + "-1", + "-100", + "0", + "1", + "01", + "02", + "12345678900000000", + } + ); + test_schema( + "min 456", + R"""({ + "type": "integer", + "minimum": 456 + })""", + // Passing strings + { + "456", + "4560", + "457", + "460", + "500", + }, + // Failing strings + { + "455", + "356", + "50", + "050", + "-1", + "-456", + } + ); + test_schema( + "min -123", + R"""({ + "type": "integer", + "minimum": -123 + })""", + // Passing strings + { + "-123", + "-122", + "-11", + "-1", + "0", + "1", + "123", + "1234", + "2345", + }, + // Failing strings + { + "-1234", + "-124", + } + ); + + test_schema( + "max 9999", + // Schema + R"""({ + "type": "integer", + "maximum": 9999 + })""", + // Passing strings + { + "-99999", + "0", + "9999", + }, + // Failing strings + { + "10000", + "99991", + } + ); + test_schema( + "max -9999", + // Schema + R"""({ + "type": "integer", + "maximum": -9999 + })""", + // Passing strings + { + "-10000", + "-9999", + }, + // Failing strings + { + "-9998", + "0", + "9999", + } + ); + test_schema( + "min 5 max 30", + // Schema + R"""({ + "type": "integer", + "minimum": 5, + "maximum": 30 + })""", + // Passing strings + { + "5", + "10", + "30", + }, + // Failing strings + { + "05", + "4", + "-1", + "31", + "123", + "0123", + } + ); + test_schema( + "min -1 max 1", + R"""({ + "type": "integer", + "minimum": -1, + "maximum": 1 + })""", + // Passing strings + { + "-1", + "0", + "1", + }, + // Failing strings + { + "-11", + "-10", + "-2", + "2", + "10", + "11", + } + ); + test_schema( + "min -123 max 42", + R"""({ + "type": "integer", + "minimum": -123, + "maximum": 42 + })""", + // Passing strings + { + "-123", + "-122", + "-13", + "-11", + "-2", + "-1", + "0", + "1", + "5", + "10", + "39", + "40", + "42", + }, + // Failing strings + { + "-0123", + "-124", + "-1123", + "-200", + "43", + "123", + "0123", + } + ); + test_schema( + "exclusive min / max", + // Schema + R"""({ + "type": "integer", + "exclusiveMinimum": 0, + "exclusiveMaximum": 10000 + })""", + // Passing strings + { + "1", + "9999", + }, + // Failing strings + { + "0", + "01", + "10000", + "99999", + } + ); + // Test case for a simple grammar test_grammar( "simple grammar", @@ -773,7 +1017,6 @@ static void test_json_schema() { } ); - test_schema( "min+max items", // Schema diff --git a/tests/test-json-schema-to-grammar.cpp b/tests/test-json-schema-to-grammar.cpp index 87bc66b691784..2e591bd71abaa 100755 --- a/tests/test-json-schema-to-grammar.cpp +++ b/tests/test-json-schema-to-grammar.cpp @@ -80,6 +80,232 @@ static void test_all(const std::string & lang, std::function Date: Tue, 25 Jun 2024 21:07:28 +0200 Subject: [PATCH 019/326] llama : return nullptr from llama_grammar_init (#8093) * llama : return nullptr from llama_grammar_init This commit updates llama_grammar_init to return nullptr instead of throwing an exception. The motivation for this is that this function is declared inside an extern "C" block and is intended/may be used from C code which will not be able to handle exceptions thrown, and results in undefined behavior. On Windows and using MSVC the following warning is currently generated: ```console C:\llama.cpp\llama.cpp(13998,1): warning C4297: 'llama_grammar_init': function assumed not to throw an exception but does C:\llama.cpp\llama.cpp(13998,1): message : __declspec(nothrow), throw(), noexcept(true), or noexcept was specified on the function ``` Signed-off-by: Daniel Bevenius * squash! llama : return nullptr from llama_grammar_init Add checks for nullptr when calling llama_grammar_init. Signed-off-by: Daniel Bevenius --------- Signed-off-by: Daniel Bevenius Co-authored-by: Clint Herron --- common/sampling.cpp | 12 ++++++++++-- examples/gbnf-validator/gbnf-validator.cpp | 4 +++- llama.cpp | 3 ++- llama.h | 6 ++++++ tests/test-grammar-integration.cpp | 6 +++--- tests/test-llama-grammar.cpp | 4 ++++ 6 files changed, 28 insertions(+), 7 deletions(-) diff --git a/common/sampling.cpp b/common/sampling.cpp index f1f80351637f0..9f332fe573683 100644 --- a/common/sampling.cpp +++ b/common/sampling.cpp @@ -28,9 +28,13 @@ struct llama_sampling_context * llama_sampling_init(const struct llama_sampling_ std::vector grammar_rules(result->parsed_grammar.c_rules()); - result->grammar = llama_grammar_init( + struct llama_grammar * grammar = llama_grammar_init( grammar_rules.data(), grammar_rules.size(), result->parsed_grammar.symbol_ids.at("root")); + if (grammar == nullptr) { + throw std::runtime_error("Failed to initialize llama_grammar"); + } + result->grammar = grammar; } result->prev.resize(params.n_prev); @@ -59,9 +63,13 @@ void llama_sampling_reset(llama_sampling_context * ctx) { if (!ctx->parsed_grammar.rules.empty()) { std::vector grammar_rules(ctx->parsed_grammar.c_rules()); - ctx->grammar = llama_grammar_init( + struct llama_grammar * grammar = llama_grammar_init( grammar_rules.data(), grammar_rules.size(), ctx->parsed_grammar.symbol_ids.at("root")); + if (grammar == nullptr) { + throw std::runtime_error("Failed to initialize llama_grammar"); + } + ctx->grammar = grammar; } std::fill(ctx->prev.begin(), ctx->prev.end(), 0); diff --git a/examples/gbnf-validator/gbnf-validator.cpp b/examples/gbnf-validator/gbnf-validator.cpp index 0406dc3398b8a..dd53ba9b1d551 100644 --- a/examples/gbnf-validator/gbnf-validator.cpp +++ b/examples/gbnf-validator/gbnf-validator.cpp @@ -101,7 +101,9 @@ int main(int argc, char** argv) { auto grammar = llama_grammar_init( grammar_rules.data(), grammar_rules.size(), parsed_grammar.symbol_ids.at("root")); - + if (grammar == nullptr) { + throw std::runtime_error("Failed to initialize llama_grammar"); + } // Read the input file std::string input_str; { diff --git a/llama.cpp b/llama.cpp index 33e6cb7229aab..dd2823e65c4b7 100644 --- a/llama.cpp +++ b/llama.cpp @@ -14500,7 +14500,8 @@ struct llama_grammar * llama_grammar_init( continue; } if (llama_grammar_detect_left_recursion(vec_rules, i, &rules_visited, &rules_in_progress, &rules_may_be_empty)) { - throw std::runtime_error(format("unsupported grammar, left recursion detected for nonterminal at index %zu", i)); + LLAMA_LOG_ERROR("unsupported grammar, left recursion detected for nonterminal at index %zu", i); + return nullptr; } } diff --git a/llama.h b/llama.h index 53e06d9db5273..82d15747f4662 100644 --- a/llama.h +++ b/llama.h @@ -924,6 +924,12 @@ extern "C" { // Grammar // + /// Initialize a llama_grammar. + /// + /// @param rules The rule elements of the grammar to initialize. + /// @param n_rules The number of rules. + /// @param start_rule_index The index of the root rule (the starting point of the grammar). + /// @return The initialized llama_grammar or nullptr if initialization failed. LLAMA_API struct llama_grammar * llama_grammar_init( const llama_grammar_element ** rules, size_t n_rules, diff --git a/tests/test-grammar-integration.cpp b/tests/test-grammar-integration.cpp index 5b3992236c26c..5750d362a7247 100644 --- a/tests/test-grammar-integration.cpp +++ b/tests/test-grammar-integration.cpp @@ -36,10 +36,10 @@ static llama_grammar* build_grammar(const std::string & grammar_str) { static bool test_build_grammar_fails(const std::string & grammar_str) { fprintf(stderr, "⚫ Testing failure for grammar: %s\n", grammar_str.c_str()); bool grammar_fails = false; - try { - build_grammar(grammar_str); + llama_grammar * grammar = build_grammar(grammar_str); + if (grammar != nullptr) { fprintf(stderr, " ❌ Expected build failure, but succeeded\n"); - } catch (const std::exception & err) { + } else { grammar_fails = true; fprintf(stdout, " ✅︎\n"); } diff --git a/tests/test-llama-grammar.cpp b/tests/test-llama-grammar.cpp index 27ca4d2656c5d..c8badb2063076 100644 --- a/tests/test-llama-grammar.cpp +++ b/tests/test-llama-grammar.cpp @@ -116,6 +116,10 @@ int main() std::vector grammar_rules(parsed_grammar.c_rules()); grammar = llama_grammar_init( grammar_rules.data(), grammar_rules.size(), parsed_grammar.symbol_ids.at("root")); + if (grammar == nullptr) + { + throw std::runtime_error("Failed to initialize llama_grammar"); + } std::vector> expected_stacks = { { From 6fcbf6823553efabe52ed83e3c2a3329aa3387d1 Mon Sep 17 00:00:00 2001 From: fairydreaming <166155368+fairydreaming@users.noreply.github.com> Date: Tue, 25 Jun 2024 21:14:35 +0200 Subject: [PATCH 020/326] llama : implement Unigram tokenizer needed by T5 and FLAN-T5 model families (#5763) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * llama : add T5 model architecture, tensors and model header parameters * llama : add implementation of Unigram tokenizer with SentencePiece-like text normalization using precompiled charsmap --------- Co-authored-by: Stanisław Szymczyk --- llama.cpp | 621 ++++++++++++++++++++++++++++++++++++++++++++++++---- llama.h | 2 + unicode.cpp | 2 +- unicode.h | 1 + 4 files changed, 587 insertions(+), 39 deletions(-) diff --git a/llama.cpp b/llama.cpp index dd2823e65c4b7..78a21008f9338 100644 --- a/llama.cpp +++ b/llama.cpp @@ -226,6 +226,7 @@ enum llm_arch { LLM_ARCH_ARCTIC, LLM_ARCH_DEEPSEEK2, LLM_ARCH_BITNET, + LLM_ARCH_T5, LLM_ARCH_UNKNOWN, }; @@ -265,6 +266,7 @@ static const std::map LLM_ARCH_NAMES = { { LLM_ARCH_ARCTIC, "arctic" }, { LLM_ARCH_DEEPSEEK2, "deepseek2" }, { LLM_ARCH_BITNET, "bitnet" }, + { LLM_ARCH_T5, "t5" }, { LLM_ARCH_UNKNOWN, "(unknown)" }, }; @@ -297,6 +299,7 @@ enum llm_kv { LLM_KV_EXPERT_WEIGHTS_SCALE, LLM_KV_POOLING_TYPE, LLM_KV_LOGIT_SCALE, + LLM_KV_DECODER_START_TOKEN_ID, LLM_KV_ATTENTION_HEAD_COUNT, LLM_KV_ATTENTION_HEAD_COUNT_KV, @@ -309,6 +312,7 @@ enum llm_kv { LLM_KV_ATTENTION_CAUSAL, LLM_KV_ATTENTION_Q_LORA_RANK, LLM_KV_ATTENTION_KV_LORA_RANK, + LLM_KV_ATTENTION_RELATIVE_BUCKETS_COUNT, LLM_KV_ROPE_DIMENSION_COUNT, LLM_KV_ROPE_FREQ_BASE, @@ -346,6 +350,8 @@ enum llm_kv { LLM_KV_TOKENIZER_ADD_BOS, LLM_KV_TOKENIZER_ADD_EOS, LLM_KV_TOKENIZER_ADD_PREFIX, + LLM_KV_TOKENIZER_REMOVE_EXTRA_WS, + LLM_KV_TOKENIZER_PRECOMPILED_CHARSMAP, LLM_KV_TOKENIZER_HF_JSON, LLM_KV_TOKENIZER_RWKV, LLM_KV_TOKENIZER_PREFIX_ID, @@ -383,18 +389,20 @@ static const std::map LLM_KV_NAMES = { { LLM_KV_EXPERT_WEIGHTS_SCALE, "%s.expert_weights_scale" }, { LLM_KV_POOLING_TYPE , "%s.pooling_type" }, { LLM_KV_LOGIT_SCALE, "%s.logit_scale" }, - - { LLM_KV_ATTENTION_HEAD_COUNT, "%s.attention.head_count" }, - { LLM_KV_ATTENTION_HEAD_COUNT_KV, "%s.attention.head_count_kv" }, - { LLM_KV_ATTENTION_MAX_ALIBI_BIAS, "%s.attention.max_alibi_bias" }, - { LLM_KV_ATTENTION_CLAMP_KQV, "%s.attention.clamp_kqv" }, - { LLM_KV_ATTENTION_KEY_LENGTH, "%s.attention.key_length" }, - { LLM_KV_ATTENTION_VALUE_LENGTH, "%s.attention.value_length" }, - { LLM_KV_ATTENTION_LAYERNORM_EPS, "%s.attention.layer_norm_epsilon" }, - { LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, "%s.attention.layer_norm_rms_epsilon" }, - { LLM_KV_ATTENTION_CAUSAL, "%s.attention.causal" }, - { LLM_KV_ATTENTION_Q_LORA_RANK, "%s.attention.q_lora_rank" }, - { LLM_KV_ATTENTION_KV_LORA_RANK, "%s.attention.kv_lora_rank" }, + { LLM_KV_DECODER_START_TOKEN_ID, "%s.decoder_start_token_id" }, + + { LLM_KV_ATTENTION_HEAD_COUNT, "%s.attention.head_count" }, + { LLM_KV_ATTENTION_HEAD_COUNT_KV, "%s.attention.head_count_kv" }, + { LLM_KV_ATTENTION_MAX_ALIBI_BIAS, "%s.attention.max_alibi_bias" }, + { LLM_KV_ATTENTION_CLAMP_KQV, "%s.attention.clamp_kqv" }, + { LLM_KV_ATTENTION_KEY_LENGTH, "%s.attention.key_length" }, + { LLM_KV_ATTENTION_VALUE_LENGTH, "%s.attention.value_length" }, + { LLM_KV_ATTENTION_LAYERNORM_EPS, "%s.attention.layer_norm_epsilon" }, + { LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, "%s.attention.layer_norm_rms_epsilon" }, + { LLM_KV_ATTENTION_CAUSAL, "%s.attention.causal" }, + { LLM_KV_ATTENTION_Q_LORA_RANK, "%s.attention.q_lora_rank" }, + { LLM_KV_ATTENTION_KV_LORA_RANK, "%s.attention.kv_lora_rank" }, + { LLM_KV_ATTENTION_RELATIVE_BUCKETS_COUNT, "%s.attention.relative_buckets_count" }, { LLM_KV_ROPE_DIMENSION_COUNT, "%s.rope.dimension_count" }, { LLM_KV_ROPE_FREQ_BASE, "%s.rope.freq_base" }, @@ -415,29 +423,31 @@ static const std::map LLM_KV_NAMES = { { LLM_KV_SSM_STATE_SIZE, "%s.ssm.state_size" }, { LLM_KV_SSM_TIME_STEP_RANK, "%s.ssm.time_step_rank" }, - { LLM_KV_TOKENIZER_MODEL, "tokenizer.ggml.model" }, - { LLM_KV_TOKENIZER_PRE, "tokenizer.ggml.pre" }, - { LLM_KV_TOKENIZER_LIST, "tokenizer.ggml.tokens" }, - { LLM_KV_TOKENIZER_TOKEN_TYPE, "tokenizer.ggml.token_type" }, - { LLM_KV_TOKENIZER_TOKEN_TYPE_COUNT, "tokenizer.ggml.token_type_count" }, - { LLM_KV_TOKENIZER_SCORES, "tokenizer.ggml.scores" }, - { LLM_KV_TOKENIZER_MERGES, "tokenizer.ggml.merges" }, - { LLM_KV_TOKENIZER_BOS_ID, "tokenizer.ggml.bos_token_id" }, - { LLM_KV_TOKENIZER_EOS_ID, "tokenizer.ggml.eos_token_id" }, - { LLM_KV_TOKENIZER_UNK_ID, "tokenizer.ggml.unknown_token_id" }, - { LLM_KV_TOKENIZER_SEP_ID, "tokenizer.ggml.seperator_token_id" }, - { LLM_KV_TOKENIZER_PAD_ID, "tokenizer.ggml.padding_token_id" }, - { LLM_KV_TOKENIZER_CLS_ID, "tokenizer.ggml.cls_token_id" }, - { LLM_KV_TOKENIZER_MASK_ID, "tokenizer.ggml.mask_token_id" }, - { LLM_KV_TOKENIZER_ADD_BOS, "tokenizer.ggml.add_bos_token" }, - { LLM_KV_TOKENIZER_ADD_EOS, "tokenizer.ggml.add_eos_token" }, - { LLM_KV_TOKENIZER_ADD_PREFIX, "tokenizer.ggml.add_space_prefix" }, - { LLM_KV_TOKENIZER_HF_JSON, "tokenizer.huggingface.json" }, - { LLM_KV_TOKENIZER_RWKV, "tokenizer.rwkv.world" }, - { LLM_KV_TOKENIZER_PREFIX_ID, "tokenizer.ggml.prefix_token_id" }, - { LLM_KV_TOKENIZER_SUFFIX_ID, "tokenizer.ggml.suffix_token_id" }, - { LLM_KV_TOKENIZER_MIDDLE_ID, "tokenizer.ggml.middle_token_id" }, - { LLM_KV_TOKENIZER_EOT_ID, "tokenizer.ggml.eot_token_id" }, + { LLM_KV_TOKENIZER_MODEL, "tokenizer.ggml.model" }, + { LLM_KV_TOKENIZER_PRE, "tokenizer.ggml.pre" }, + { LLM_KV_TOKENIZER_LIST, "tokenizer.ggml.tokens" }, + { LLM_KV_TOKENIZER_TOKEN_TYPE, "tokenizer.ggml.token_type" }, + { LLM_KV_TOKENIZER_TOKEN_TYPE_COUNT, "tokenizer.ggml.token_type_count" }, + { LLM_KV_TOKENIZER_SCORES, "tokenizer.ggml.scores" }, + { LLM_KV_TOKENIZER_MERGES, "tokenizer.ggml.merges" }, + { LLM_KV_TOKENIZER_BOS_ID, "tokenizer.ggml.bos_token_id" }, + { LLM_KV_TOKENIZER_EOS_ID, "tokenizer.ggml.eos_token_id" }, + { LLM_KV_TOKENIZER_UNK_ID, "tokenizer.ggml.unknown_token_id" }, + { LLM_KV_TOKENIZER_SEP_ID, "tokenizer.ggml.seperator_token_id" }, + { LLM_KV_TOKENIZER_PAD_ID, "tokenizer.ggml.padding_token_id" }, + { LLM_KV_TOKENIZER_CLS_ID, "tokenizer.ggml.cls_token_id" }, + { LLM_KV_TOKENIZER_MASK_ID, "tokenizer.ggml.mask_token_id" }, + { LLM_KV_TOKENIZER_ADD_BOS, "tokenizer.ggml.add_bos_token" }, + { LLM_KV_TOKENIZER_ADD_EOS, "tokenizer.ggml.add_eos_token" }, + { LLM_KV_TOKENIZER_ADD_PREFIX, "tokenizer.ggml.add_space_prefix" }, + { LLM_KV_TOKENIZER_REMOVE_EXTRA_WS, "tokenizer.ggml.remove_extra_whitespaces" }, + { LLM_KV_TOKENIZER_PRECOMPILED_CHARSMAP, "tokenizer.ggml.precompiled_charsmap" }, + { LLM_KV_TOKENIZER_HF_JSON, "tokenizer.huggingface.json" }, + { LLM_KV_TOKENIZER_RWKV, "tokenizer.rwkv.world" }, + { LLM_KV_TOKENIZER_PREFIX_ID, "tokenizer.ggml.prefix_token_id" }, + { LLM_KV_TOKENIZER_SUFFIX_ID, "tokenizer.ggml.suffix_token_id" }, + { LLM_KV_TOKENIZER_MIDDLE_ID, "tokenizer.ggml.middle_token_id" }, + { LLM_KV_TOKENIZER_EOT_ID, "tokenizer.ggml.eot_token_id" }, }; struct LLM_KV { @@ -504,6 +514,34 @@ enum llm_tensor { LLM_TENSOR_ATTN_KV_A_NORM, LLM_TENSOR_ATTN_SUB_NORM, LLM_TENSOR_FFN_SUB_NORM, + LLM_TENSOR_DEC_ATTN_NORM, + LLM_TENSOR_DEC_ATTN_Q, + LLM_TENSOR_DEC_ATTN_K, + LLM_TENSOR_DEC_ATTN_V, + LLM_TENSOR_DEC_ATTN_OUT, + LLM_TENSOR_DEC_ATTN_REL_B, + LLM_TENSOR_DEC_CROSS_ATTN_NORM, + LLM_TENSOR_DEC_CROSS_ATTN_Q, + LLM_TENSOR_DEC_CROSS_ATTN_K, + LLM_TENSOR_DEC_CROSS_ATTN_V, + LLM_TENSOR_DEC_CROSS_ATTN_OUT, + LLM_TENSOR_DEC_CROSS_ATTN_REL_B, + LLM_TENSOR_DEC_FFN_NORM, + LLM_TENSOR_DEC_FFN_GATE, + LLM_TENSOR_DEC_FFN_DOWN, + LLM_TENSOR_DEC_FFN_UP, + LLM_TENSOR_DEC_OUTPUT_NORM, + LLM_TENSOR_ENC_ATTN_NORM, + LLM_TENSOR_ENC_ATTN_Q, + LLM_TENSOR_ENC_ATTN_K, + LLM_TENSOR_ENC_ATTN_V, + LLM_TENSOR_ENC_ATTN_OUT, + LLM_TENSOR_ENC_ATTN_REL_B, + LLM_TENSOR_ENC_FFN_NORM, + LLM_TENSOR_ENC_FFN_GATE, + LLM_TENSOR_ENC_FFN_DOWN, + LLM_TENSOR_ENC_FFN_UP, + LLM_TENSOR_ENC_OUTPUT_NORM, }; static const std::map> LLM_TENSOR_NAMES = { @@ -1135,6 +1173,41 @@ static const std::map> LLM_TENSOR_NA { LLM_TENSOR_FFN_SUB_NORM, "blk.%d.ffn_sub_norm" }, }, }, + { + LLM_ARCH_T5, + { + { LLM_TENSOR_TOKEN_EMBD, "token_embd" }, + { LLM_TENSOR_OUTPUT, "output" }, + { LLM_TENSOR_DEC_OUTPUT_NORM, "dec.output_norm" }, + { LLM_TENSOR_DEC_ATTN_NORM, "dec.blk.%d.attn_norm" }, + { LLM_TENSOR_DEC_ATTN_Q, "dec.blk.%d.attn_q" }, + { LLM_TENSOR_DEC_ATTN_K, "dec.blk.%d.attn_k" }, + { LLM_TENSOR_DEC_ATTN_V, "dec.blk.%d.attn_v" }, + { LLM_TENSOR_DEC_ATTN_OUT, "dec.blk.%d.attn_o" }, + { LLM_TENSOR_DEC_ATTN_REL_B, "dec.blk.%d.attn_rel_b" }, + { LLM_TENSOR_DEC_CROSS_ATTN_NORM, "dec.blk.%d.cross_attn_norm" }, + { LLM_TENSOR_DEC_CROSS_ATTN_Q, "dec.blk.%d.cross_attn_q" }, + { LLM_TENSOR_DEC_CROSS_ATTN_K, "dec.blk.%d.cross_attn_k" }, + { LLM_TENSOR_DEC_CROSS_ATTN_V, "dec.blk.%d.cross_attn_v" }, + { LLM_TENSOR_DEC_CROSS_ATTN_OUT, "dec.blk.%d.cross_attn_o" }, + { LLM_TENSOR_DEC_CROSS_ATTN_REL_B, "dec.blk.%d.cross_attn_rel_b" }, + { LLM_TENSOR_DEC_FFN_NORM, "dec.blk.%d.ffn_norm" }, + { LLM_TENSOR_DEC_FFN_GATE, "dec.blk.%d.ffn_gate" }, + { LLM_TENSOR_DEC_FFN_DOWN, "dec.blk.%d.ffn_down" }, + { LLM_TENSOR_DEC_FFN_UP, "dec.blk.%d.ffn_up" }, + { LLM_TENSOR_ENC_OUTPUT_NORM, "enc.output_norm" }, + { LLM_TENSOR_ENC_ATTN_NORM, "enc.blk.%d.attn_norm" }, + { LLM_TENSOR_ENC_ATTN_Q, "enc.blk.%d.attn_q" }, + { LLM_TENSOR_ENC_ATTN_K, "enc.blk.%d.attn_k" }, + { LLM_TENSOR_ENC_ATTN_V, "enc.blk.%d.attn_v" }, + { LLM_TENSOR_ENC_ATTN_OUT, "enc.blk.%d.attn_o" }, + { LLM_TENSOR_ENC_ATTN_REL_B, "enc.blk.%d.attn_rel_b" }, + { LLM_TENSOR_ENC_FFN_NORM, "enc.blk.%d.ffn_norm" }, + { LLM_TENSOR_ENC_FFN_GATE, "enc.blk.%d.ffn_gate" }, + { LLM_TENSOR_ENC_FFN_DOWN, "enc.blk.%d.ffn_down" }, + { LLM_TENSOR_ENC_FFN_UP, "enc.blk.%d.ffn_up" }, + }, + }, { LLM_ARCH_UNKNOWN, { @@ -2356,6 +2429,11 @@ struct llama_vocab { bool tokenizer_add_bos = false; bool tokenizer_add_eos = false; bool tokenizer_ignore_merges = false; + bool tokenizer_remove_extra_whitespaces = false; + bool tokenizer_escape_whitespaces = true; + bool tokenizer_treat_whitespace_as_suffix = false; + + std::vector precompiled_charsmap; int find_bpe_rank(const std::string & token_left, const std::string & token_right) const { GGML_ASSERT(token_left.find(' ') == std::string::npos); @@ -4191,6 +4269,7 @@ static const char * llama_model_vocab_type_name(enum llama_vocab_type type){ case LLAMA_VOCAB_TYPE_SPM: return "SPM"; case LLAMA_VOCAB_TYPE_BPE: return "BPE"; case LLAMA_VOCAB_TYPE_WPM: return "WPM"; + case LLAMA_VOCAB_TYPE_UGM: return "UGM"; default: return "unknown"; } } @@ -4870,6 +4949,45 @@ static void llm_load_vocab( vocab.special_pad_id = -1; vocab.special_cls_id = -1; vocab.special_mask_id = -1; + } else if (tokenizer_model == "t5") { + vocab.type = LLAMA_VOCAB_TYPE_UGM; + + // default special tokens + vocab.special_bos_id = -1; + vocab.special_eos_id = 1; + vocab.special_unk_id = 2; + vocab.special_sep_id = -1; + vocab.special_pad_id = 0; + vocab.special_cls_id = -1; + vocab.special_mask_id = -1; + + const int add_space_prefix_keyidx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_ADD_PREFIX).c_str()); + if (add_space_prefix_keyidx != -1) { + vocab.tokenizer_add_space_prefix = gguf_get_val_bool(ctx, add_space_prefix_keyidx); + } // The default value of add_space_prefix is true. + + const int remove_extra_whitespaces_keyidx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_REMOVE_EXTRA_WS).c_str()); + if (remove_extra_whitespaces_keyidx != -1) { + vocab.tokenizer_remove_extra_whitespaces = gguf_get_val_bool(ctx, remove_extra_whitespaces_keyidx); + } // The default value of remove_extra_whitespaces is false. + + const int precompiled_charsmap_keyidx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_PRECOMPILED_CHARSMAP).c_str()); + if (precompiled_charsmap_keyidx != -1) { + size_t n_precompiled_charsmap = gguf_get_arr_n(ctx, precompiled_charsmap_keyidx); + const char * precompiled_charsmap = (const char *) gguf_get_arr_data(ctx, precompiled_charsmap_keyidx); + vocab.precompiled_charsmap.assign(precompiled_charsmap, precompiled_charsmap + n_precompiled_charsmap); +#ifdef IS_BIG_ENDIAN + // correct endiannes of data in precompiled_charsmap binary blob + uint32_t * xcda_blob_size = (uint32_t *) &vocab.precompiled_charsmap[0]; + *xcda_blob_size = __builtin_bswap32(*xcda_blob_size); + assert(*xcda_blob_size + sizeof(uint32_t) < n_precompiled_charsmap); + size_t xcda_array_size = *xcda_blob_size / sizeof(uint32_t); + uint32_t * xcda_array = (uint32_t *) &vocab.precompiled_charsmap[sizeof(uint32_t)]; + for (size_t i = 0; i < xcda_array_size; ++i) { + xcda_array[i] = __builtin_bswap32(xcda_array[i]); + } +#endif + } } else { throw std::runtime_error(format("unknown tokenizer: '%s'", tokenizer_model.c_str())); } @@ -4952,6 +5070,10 @@ static void llm_load_vocab( vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT; vocab.tokenizer_add_bos = true; vocab.tokenizer_add_eos = false; + } else if (vocab.type == LLAMA_VOCAB_TYPE_UGM) { + vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT; + vocab.tokenizer_add_bos = false; + vocab.tokenizer_add_eos = true; } else { vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT; } @@ -13213,12 +13335,18 @@ static bool llama_is_user_defined_token(const llama_vocab& vocab, llama_token id return vocab.id_to_token[id].attr & LLAMA_TOKEN_ATTR_USER_DEFINED; } +static bool llama_is_unused_token(const llama_vocab& vocab, llama_token id) { + GGML_ASSERT(vocab.type != LLAMA_VOCAB_TYPE_NONE); + return vocab.id_to_token[id].attr & LLAMA_TOKEN_ATTR_UNUSED; +} + static uint8_t llama_token_to_byte(const llama_vocab& vocab, llama_token id) { GGML_ASSERT(llama_vocab_get_type(vocab) != LLAMA_VOCAB_TYPE_NONE); GGML_ASSERT(llama_is_byte_token(vocab, id)); const auto & token_data = vocab.id_to_token.at(id); switch (llama_vocab_get_type(vocab)) { - case LLAMA_VOCAB_TYPE_SPM: { + case LLAMA_VOCAB_TYPE_SPM: + case LLAMA_VOCAB_TYPE_UGM: { auto buf = token_data.text.substr(3, 2); return strtol(buf.c_str(), NULL, 16); } @@ -13238,7 +13366,8 @@ static llama_token llama_byte_to_token(const llama_vocab & vocab, uint8_t ch) { GGML_ASSERT(llama_vocab_get_type(vocab) != LLAMA_VOCAB_TYPE_NONE); static const char * hex = "0123456789ABCDEF"; switch (llama_vocab_get_type(vocab)) { - case LLAMA_VOCAB_TYPE_SPM: { + case LLAMA_VOCAB_TYPE_SPM: + case LLAMA_VOCAB_TYPE_UGM: { const char buf[7] = { '<', '0', 'x', hex[ch >> 4], hex[ch & 15], '>', 0 }; auto token = vocab.token_to_id.find(buf); if (token != vocab.token_to_id.end()) { @@ -13826,6 +13955,383 @@ struct llm_tokenizer_wpm { const llama_vocab & vocab; }; +struct naive_trie { + naive_trie() : has_value(false), value(0) { + } + void insert(const char * key, size_t len, int32_t value = 0) { + if (len == 0) { + this->has_value = true; + this->value = value; + return; + } + char c = key[0]; + auto res = children.find(c); + if (res != children.end()) { + res->second.insert(key + 1, len - 1, value); + } else { + auto res = children.insert(std::make_pair(c, naive_trie())); + res.first->second.insert(key + 1, len - 1, value); + } + } + std::pair get_longest_prefix(const char * key, size_t len, size_t offset = 0) { + if (len == 0 || offset == len) { + return std::make_pair(key, offset); + } + char c = key[offset]; + auto res = children.find(c); + if (res != children.end()) { + return res->second.get_longest_prefix(key, len, offset + 1); + } else { + return std::make_pair(key, offset); + } + } + struct naive_trie * traverse(const char c) { + auto res = children.find(c); + if (res != children.end()) { + return &res->second; + } else { + return NULL; + } + } + std::map children; + bool has_value; + llama_token value; +}; + +struct llm_tokenizer_ugm { + llm_tokenizer_ugm(const llama_vocab & vocab) : vocab(vocab) { + if (vocab.precompiled_charsmap.size() > 0) { + size_t charsmap_offset = 0; + + // First four bytes of precompiled_charsmap contains length of binary + // blob containing XOR-compressed compact double array (XCDA) entries + uint32_t xcda_blob_size = *(const uint32_t *) &vocab.precompiled_charsmap[0]; + charsmap_offset += sizeof(xcda_blob_size); + if (xcda_blob_size + charsmap_offset >= vocab.precompiled_charsmap.size()) { + throw std::runtime_error("Index out of array bounds in precompiled charsmap!"); + } + + // Next xcda_blob_size bytes contain entries of XOR-compressed compact + // double array (XCDA). Each entry is bit-packed into a 32-bit integer. + xcda_array = (const uint32_t *) &vocab.precompiled_charsmap[charsmap_offset]; + xcda_array_size = xcda_blob_size / sizeof(uint32_t); + charsmap_offset += xcda_blob_size; + + // Remaining bytes of precompiled charsmap contain null-terminated + // replacement strings for prefixes matched by the XCDA. + prefix_replacements = &vocab.precompiled_charsmap[charsmap_offset]; + prefix_replacements_size = vocab.precompiled_charsmap.size() - charsmap_offset; + } + + for (unsigned int id = 0; id < vocab.id_to_token.size(); ++id) { + const auto &token_data = vocab.id_to_token[id]; + + if (llama_is_normal_token(vocab, id)) { + min_score = std::min(min_score, token_data.score); + max_score = std::max(max_score, token_data.score); + } + + if (llama_is_normal_token(vocab, id) || + llama_is_user_defined_token(vocab, id) || + llama_is_unused_token(vocab, id)) { + token_matcher.insert(token_data.text.data(), token_data.text.size(), id); + } + + if (llama_is_user_defined_token(vocab, id)) { + user_defined_token_matcher.insert(token_data.text.data(), token_data.text.size()); + } + } + + unknown_token_score = min_score - unknown_token_score_penalty; + } + + /* This implementation is based on SentencePiece optimized Viterbi algorithm for + * unigram language models. The general idea is to: + * - move along the input sequence in steps of one UTF code point, + * - at each step find all possible tokenizations of the prefix by + * traversing the tokens trie, + * - for each tokenization store the best one so far (by higher score) + * - use the position in sequence after given token as an index to store + * results + * - if there was no valid tokenization of the current UTF code point + * then use unknown token with additional score penalty + * After processing the whole sequence we backtrack from the end to get + * the best tokenization. + */ + void tokenize(const std::string & text, std::vector & output) { + // normalize the input first + std::string normalized; + normalize(text, &normalized); + size_t input_len = normalized.size(); + + // initialize score_sum to -FLT_MAX so it will be always lower than sums of token scores + std::vector tokenization_results(input_len + 1, {0, 0, -FLT_MAX}); + // at the beginning tokenization score is zero + tokenization_results[0] = { 0, 0, 0 }; + + for (size_t input_offset = 0; input_offset < input_len;) { + size_t prefix_offset = input_offset; + // calculate how many code units are in the currently processed UTF code point + size_t n_utf8_code_units = std::min(utf8_len(normalized[input_offset]), input_len - input_offset); + + // traverse the token matcher trie to find a matching token + bool single_codepoint_token_found = false; + const struct best_tokenization & current_best = tokenization_results[input_offset]; + struct naive_trie * node = token_matcher.traverse(normalized[prefix_offset++]); + + while (prefix_offset <= input_len && node != NULL) { + // check if we found valid token in prefix + if (node->has_value) { + // check if it corresponds to the whole UTF code point + if (prefix_offset - input_offset == n_utf8_code_units) { + single_codepoint_token_found = true; + } + llama_token token_id = node->value; + const auto &token_data = vocab.id_to_token[token_id]; + + // we set the user-defined token scores to 0 to make them more likely to be selected + // (normal token scores are log probabilities, so they are negative) + // score type is double here to make tokenization results exactly + // the same as in the HF tokenizer using SentencePiece + const double token_score = llama_is_user_defined_token(vocab, token_id) ? 0.0 : token_data.score; + const double challenger_score = current_best.score_sum + token_score; + struct best_tokenization & current_champ = tokenization_results[prefix_offset]; + if (challenger_score > current_champ.score_sum) { + struct best_tokenization challenger = { token_id, input_offset, (float) challenger_score }; + current_champ = challenger; + } + } + node = node->traverse(normalized[prefix_offset++]); + } + + // if we didn't find a valid token corresponding to the whole UTF code point + // then use unknown token as the tokenization of this UTF code point + if (!single_codepoint_token_found) { + const double challenger_score = current_best.score_sum + unknown_token_score; + prefix_offset = input_offset + n_utf8_code_units; + struct best_tokenization & current_champ = tokenization_results[prefix_offset]; + if (challenger_score > current_champ.score_sum) { + struct best_tokenization challenger = { vocab.special_unk_id, input_offset, (float) challenger_score }; + current_champ = challenger; + } + } + + // move to the next UTF code point + input_offset += n_utf8_code_units; + } + + // now backtrack from the end to gather token ids of the best tokenization + // merge sequences of consecutive unknown tokens into single unknown tokens + bool is_prev_unknown = false; + for (struct best_tokenization & tokenization = tokenization_results[input_len]; ; tokenization = tokenization_results[tokenization.input_offset]) { + bool is_unknown = tokenization.token_id == vocab.special_unk_id; + if (!(is_prev_unknown && is_unknown)) { + output.push_back(tokenization.token_id); + } + if (tokenization.input_offset == 0) { + break; + } + is_prev_unknown = is_unknown; + } + + // reverse the output since we added tokens starting from the end of the input + std::reverse(output.begin(), output.end()); + } + +private: + const llama_vocab & vocab; + + // helper structure for returning normalization results + struct normalization_result { + const char * normalized; + size_t normalized_len; + size_t consumed_input; + }; + + void normalize(const std::string& input, std::string * normalized) { + normalized->clear(); + normalized->reserve(input.size() * 3); + + const std::string space = vocab.tokenizer_escape_whitespaces ? escaped_space : " "; + + bool shall_prepend_space = !vocab.tokenizer_treat_whitespace_as_suffix && vocab.tokenizer_add_space_prefix; + bool shall_append_space = vocab.tokenizer_treat_whitespace_as_suffix && vocab.tokenizer_add_space_prefix; + bool shall_merge_spaces = vocab.tokenizer_remove_extra_whitespaces; + + bool is_space_prepended = false; + bool processing_non_ws = false; + + size_t input_len = input.size(); + + for (size_t input_offset = 0; input_offset < input_len; ) { + auto norm_res = normalize_prefix(input, input_offset); + for (size_t i = 0; i < norm_res.normalized_len; i++) { + char c = norm_res.normalized[i]; + if (c != ' ') { + if (!processing_non_ws) { + processing_non_ws = true; + if ((shall_prepend_space && !is_space_prepended) || shall_merge_spaces) { + normalized->append(space); + is_space_prepended = true; + } + } + normalized->push_back(c); + } else { + if (processing_non_ws) { + processing_non_ws = false; + } + if (!shall_merge_spaces) { + normalized->append(space); + } + } + } + + input_offset += norm_res.consumed_input; + } + + if (shall_append_space) { + normalized->append(space); + } + } + + /* + * This structure is a view wrapper for XOR-compressed double array (XCDA) + * See Shunsuke Kanda (2018). Space- and Time-Efficient String Dictionaries. + * Eeach bit-packed entry contains: + * - BASE array value in bits 10-30 + * - LCHECK array value in bits 0-7 + * - LEAF array value in bit 9 + * Entries containing indexes of replacement sequences have set bit 31 + */ + struct xcda_array_view { + public: + xcda_array_view(const uint32_t * xcda_array, size_t xcda_array_size) : xcda_array(xcda_array), xcda_array_size(xcda_array_size) { + } + uint32_t get_base(size_t index) { + uint32_t packed_node = get_node(index); + return (packed_node >> 10) << ((packed_node & (1U << 9)) >> 6); + } + uint32_t get_lcheck(size_t index) { + uint32_t packed_node = get_node(index); + return packed_node & ((1U << 31) | 0xff); + } + bool get_leaf(size_t index) { + uint32_t packed_node = get_node(index); + return (packed_node >> 8) & 1; + } + uint32_t get_value(size_t index) { + uint32_t packed_node = get_node(index); + return packed_node & ((1U << 31) - 1); + } + private: + uint32_t get_node(size_t index) { + if (index > xcda_array_size) { + throw std::runtime_error("Index out of array bounds in XCDA array!"); + } + return xcda_array[index]; + } + const uint32_t * xcda_array; + size_t xcda_array_size; + }; + + struct normalization_result normalize_prefix(const std::string & input, size_t input_offset) { + if (input_offset == input.size()) { + return { &input[input_offset], 0, 0 }; + } + + // if input prefix matches some user-defined token return this token as normalization result + auto user_defined_token_match = user_defined_token_matcher.get_longest_prefix(&input[input_offset], input.size() - input_offset); + if (user_defined_token_match.second > 0) { + return { &input[input_offset], user_defined_token_match.second, user_defined_token_match.second }; + } + + size_t longest_prefix_length = 0; + size_t longest_prefix_offset = 0; + + if (xcda_array_size > 0) { + struct xcda_array_view xcda_view(xcda_array, xcda_array_size); + + // Find the longest normalized sequence matching the input prefix by walking + // the XOR-compressed compact double array (XCDA) starting from the root node + // We find the index of the next node by calculating BASE[s] ^ c where s is + // the index of the previous node and c is a numerical character value + uint32_t node_index = 0; + // get BASE of the root node + node_index = xcda_view.get_base(node_index); + for (size_t prefix_offset = input_offset; prefix_offset < input.size(); prefix_offset++) { + unsigned char c = input[prefix_offset]; + if (c == 0) { + break; + } + node_index ^= c; + // if value of LCHECK is not c it means that this is not a child of + // the previous node, so we stop matching + if (xcda_view.get_lcheck(node_index) != c) { + break; + } + bool is_leaf = xcda_view.get_leaf(node_index); + // get BASE of the current node + node_index ^= xcda_view.get_base(node_index); + // if LEAF of the current node is true, it means that its BASE points to the node + // containing index of replacement sequence for currently matched input prefix + if (is_leaf) + { + longest_prefix_length = prefix_offset - input_offset + 1; + // get index of replacement sequence for currently matched input prefix + longest_prefix_offset = xcda_view.get_value(node_index); + } + } + } + + if (longest_prefix_length > 0) { + // we have a match, so return the replacement sequence + if (longest_prefix_offset >= prefix_replacements_size) { + throw std::runtime_error("Index out of array bounds in precompiled charsmap!"); + } + const char * prefix_replacement = &prefix_replacements[longest_prefix_offset]; + return { prefix_replacement, strlen(prefix_replacement), longest_prefix_length }; + } else { + // check if the input prefix contains a valid sequence of UTF-8 code units + try { + // if yes, return this sequence unmodified + size_t prefix_offset = input_offset; + unicode_cpt_from_utf8(input, prefix_offset); + return { &input[input_offset], prefix_offset - input_offset, prefix_offset - input_offset }; + } catch(std::invalid_argument & ex) { + // if no, consume 1 byte and return U+FFFD - REPLACEMENT CHARACTER + return { "\xEF\xBF\xBD", 3, 1 }; + } + } + } + + // escaped space symbol - U+2581 (Lower One Eighth Block) + const std::string escaped_space = "\xE2\x96\x81"; + + const char * prefix_replacements = NULL; + size_t prefix_replacements_size = 0; + + const uint32_t * xcda_array = NULL; + size_t xcda_array_size = 0; + + struct naive_trie user_defined_token_matcher; + + // this structure stores the best tokenization so far at input_offset + struct best_tokenization { + llama_token token_id; + size_t input_offset; + float score_sum; + }; + + float min_score = FLT_MAX; + float max_score = -FLT_MAX; + + float unknown_token_score_penalty = 10.0; + float unknown_token_score; + + struct naive_trie token_matcher; +}; + + typedef enum FRAGMENT_BUFFER_VARIANT_TYPE { FRAGMENT_BUFFER_VARIANT_TYPE_TOKEN, FRAGMENT_BUFFER_VARIANT_TYPE_RAW_TEXT @@ -14086,6 +14592,39 @@ static std::vector llama_tokenize_internal(const llama_vocab & output.push_back(vocab.special_sep_id); } } break; + case LLAMA_VOCAB_TYPE_UGM: + { + llm_tokenizer_ugm tokenizer(vocab); + + if (add_special && vocab.tokenizer_add_bos != 0) { + GGML_ASSERT(vocab.special_bos_id != -1); + output.push_back(vocab.special_bos_id); + } + + for (const auto & fragment : fragment_buffer) { + if (fragment.type == FRAGMENT_BUFFER_VARIANT_TYPE_RAW_TEXT) { + auto raw_text = fragment.raw_text.substr(fragment.offset, fragment.length); +#ifdef PRETOKENIZERDEBUG + LLAMA_LOG_WARN("TT: (%ld %ld %ld) '%s'\n", raw_text.length(), fragment.offset, fragment.length, raw_text.c_str()); +#endif + tokenizer.tokenize(raw_text, output); + } else { // if (fragment.type == FRAGMENT_BUFFER_VARIANT_TYPE_TOKEN) + output.push_back(fragment.token); + } + } + + if (add_special && vocab.tokenizer_add_bos != 0 && output.size() >= 2 && output[1] == vocab.special_bos_id) { + LLAMA_LOG_WARN( + "%s: Added a BOS token to the prompt as specified by the model but the prompt " + "also starts with a BOS token. So now the final prompt starts with 2 BOS tokens. " + "Are you sure this is what you want?\n", __FUNCTION__); + } + + if (add_special && vocab.tokenizer_add_eos == 1) { + GGML_ASSERT(vocab.special_eos_id != -1); + output.push_back(vocab.special_eos_id); + } + } break; case LLAMA_VOCAB_TYPE_NONE: GGML_ASSERT(false); } @@ -16964,6 +17503,7 @@ enum llama_rope_type llama_rope_type(const struct llama_model * model) { case LLM_ARCH_BLOOM: case LLM_ARCH_MAMBA: case LLM_ARCH_JINA_BERT_V2: + case LLM_ARCH_T5: return LLAMA_ROPE_TYPE_NONE; // use what we call a normal RoPE, operating on pairs of consecutive head values @@ -18659,6 +19199,10 @@ llama_token llama_token_eot(const struct llama_model * model) { return model->vocab.special_eot_id; } +llama_token llama_token_pad(const struct llama_model * model) { + return model->vocab.special_pad_id; +} + int32_t llama_tokenize( const struct llama_model * model, const char * text, @@ -18725,7 +19269,8 @@ int32_t llama_token_to_piece(const struct llama_model * model, llama_token token if (0 <= token && token < llama_n_vocab(model)) { switch (llama_vocab_get_type(model->vocab)) { case LLAMA_VOCAB_TYPE_WPM: - case LLAMA_VOCAB_TYPE_SPM: { + case LLAMA_VOCAB_TYPE_SPM: + case LLAMA_VOCAB_TYPE_UGM: { // NOTE: we accept all unsupported token types, // suppressing them like CONTROL tokens. if (llama_is_normal_token(model->vocab, token)) { diff --git a/llama.h b/llama.h index 82d15747f4662..88eecb0edb17e 100644 --- a/llama.h +++ b/llama.h @@ -67,6 +67,7 @@ extern "C" { LLAMA_VOCAB_TYPE_SPM = 1, // LLaMA tokenizer based on byte-level BPE with byte fallback LLAMA_VOCAB_TYPE_BPE = 2, // GPT-2 tokenizer based on byte-level BPE LLAMA_VOCAB_TYPE_WPM = 3, // BERT tokenizer based on WordPiece + LLAMA_VOCAB_TYPE_UGM = 4, // T5 tokenizer based on Unigram }; // pre-tokenization types @@ -857,6 +858,7 @@ extern "C" { LLAMA_API llama_token llama_token_cls(const struct llama_model * model); // classification LLAMA_API llama_token llama_token_sep(const struct llama_model * model); // sentence separator LLAMA_API llama_token llama_token_nl (const struct llama_model * model); // next-line + LLAMA_API llama_token llama_token_pad(const struct llama_model * model); // padding // Returns -1 if unknown, 1 for true or 0 for false. LLAMA_API int32_t llama_add_bos_token(const struct llama_model * model); diff --git a/unicode.cpp b/unicode.cpp index c0b76bf20aede..8692924b957cc 100644 --- a/unicode.cpp +++ b/unicode.cpp @@ -23,7 +23,7 @@ static std::string unicode_cpts_to_utf8(const std::vector & cps) { return result; } -static uint32_t unicode_cpt_from_utf8(const std::string & utf8, size_t & offset) { +uint32_t unicode_cpt_from_utf8(const std::string & utf8, size_t & offset) { assert(offset < utf8.size()); if (!(utf8[offset + 0] & 0x80)) { auto result = utf8[offset + 0]; diff --git a/unicode.h b/unicode.h index 6c488970a79d6..30b07ba7fa493 100644 --- a/unicode.h +++ b/unicode.h @@ -48,6 +48,7 @@ struct codepoint_flags { std::string unicode_cpt_to_utf8(uint32_t cp); +uint32_t unicode_cpt_from_utf8(const std::string & utf8, size_t & offset); std::vector unicode_cpts_from_utf8(const std::string & utf8); std::vector unicode_cpts_normalize_nfd(const std::vector & cpts); From 163d50adaf8897d8b734d701ff332de6be63d484 Mon Sep 17 00:00:00 2001 From: jukofyork <69222624+jukofyork@users.noreply.github.com> Date: Tue, 25 Jun 2024 21:47:40 +0100 Subject: [PATCH 021/326] fixes #7999 (adds control vectors to all `build_XXX()` functions in `llama.cpp` [needs testing] (#8060) * fixes #7999 The `build_command_r` forgot to add the control vector. * Fixes qwen2 too * Fixed all models' control vectors * Removed double calls to `cb(cur, "l_out", il)` * Moved control vector logic to llama_control_vector:apply_to() --- llama.cpp | 112 +++++++++++++++++++++++++++++++++++------------------- 1 file changed, 73 insertions(+), 39 deletions(-) diff --git a/llama.cpp b/llama.cpp index 78a21008f9338..989c731495dbb 100644 --- a/llama.cpp +++ b/llama.cpp @@ -2368,13 +2368,21 @@ struct llama_control_vector { int32_t layer_start = -1; int32_t layer_end = -1; - ggml_tensor * tensor_for(int il) const { + struct ggml_tensor * tensor_for(int il) const { if (il < 0 || il < layer_start || il > layer_end || (size_t) il >= tensors.size()) { return nullptr; } return tensors[il]; } + struct ggml_tensor * apply_to(struct ggml_context * ctx, struct ggml_tensor * cur, int il) const { + ggml_tensor * layer_dir = tensor_for(il); + if (layer_dir != nullptr) { + cur = ggml_add(ctx, cur, layer_dir); + } + return cur; + } + ~llama_control_vector() { for (struct ggml_context * ctx : ctxs) { ggml_free(ctx); @@ -8023,10 +8031,7 @@ struct llm_build_context { cur = ggml_add(ctx0, cur, ffn_inp); cb(cur, "ffn_out", il); - ggml_tensor * layer_dir = lctx.cvec.tensor_for(il); - if (layer_dir != nullptr) { - cur = ggml_add(ctx0, cur, layer_dir); - } + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -8141,6 +8146,7 @@ struct llm_build_context { } cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -8245,6 +8251,7 @@ struct llm_build_context { } cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -8360,9 +8367,8 @@ struct llm_build_context { } cur = ggml_add(ctx0, cur, ffn_inp); - cb(cur, "l_out", il); - cur = ggml_add(ctx0, cur, inpL); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -8514,10 +8520,7 @@ struct llm_build_context { cur = ggml_add(ctx0, cur, ffn_inp); cb(cur, "ffn_out", il); - ggml_tensor * layer_dir = lctx.cvec.tensor_for(il); - if (layer_dir != nullptr) { - cur = ggml_add(ctx0, cur, layer_dir); - } + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -8648,10 +8651,7 @@ struct llm_build_context { cur = ggml_add(ctx0, cur, ffn_inp); cb(cur, "ffn_out", il); - ggml_tensor * layer_dir = lctx.cvec.tensor_for(il); - if (layer_dir != nullptr) { - cur = ggml_add(ctx0, cur, layer_dir); - } + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -8757,8 +8757,12 @@ struct llm_build_context { cb(cur, "ffn_out", il); } - inpL = ggml_add(ctx0, cur, ffn_inp); - cb(inpL, "l_out", il); + cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); + cb(cur, "l_out", il); + + // input for next layer + inpL = cur; } cur = llm_build_norm(ctx0, inpL, hparams, @@ -8846,6 +8850,7 @@ struct llm_build_context { } cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -9141,8 +9146,12 @@ struct llm_build_context { cb(cur, "ffn_out", il); } - inpL = ggml_add(ctx0, cur, ffn_inp); - cb(inpL, "l_out", il); + cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); + cb(cur, "l_out", il); + + // input for next layer + inpL = cur; } cur = llm_build_norm(ctx0, inpL, hparams, @@ -9276,6 +9285,7 @@ struct llm_build_context { } cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -9424,6 +9434,7 @@ struct llm_build_context { } cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -9536,6 +9547,7 @@ struct llm_build_context { } cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -9647,6 +9659,7 @@ struct llm_build_context { cb(cur, "ffn_out", il); cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -9792,6 +9805,7 @@ struct llm_build_context { } cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -9912,11 +9926,11 @@ struct llm_build_context { } cur = ggml_add(ctx0, cur, ffn_output); - cb(cur, "l_out", il); - cur = ggml_add(ctx0, cur, inpL); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); + // input for next layer inpL = cur; } @@ -10048,8 +10062,10 @@ struct llm_build_context { } cur = ggml_add(ctx0, residual, cur); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); + // input for next layer inpL = cur; } @@ -10148,9 +10164,8 @@ struct llm_build_context { } cur = ggml_add(ctx0, cur, sa_out); - cb(cur, "l_out", il); - cur = ggml_add(ctx0, cur, inpL); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -10256,8 +10271,12 @@ struct llm_build_context { cb(cur, "ffn_out", il); } - inpL = ggml_add(ctx0, cur, ffn_inp); - cb(inpL, "l_out", il); + cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); + cb(cur, "l_out", il); + + // input for next layer + inpL = cur; } cur = llm_build_norm(ctx0, inpL, hparams, @@ -10363,8 +10382,12 @@ struct llm_build_context { cb(cur, "ffn_out", il); } - inpL = ggml_add(ctx0, cur, ffn_inp); - cb(inpL, "l_out", il); + cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); + cb(cur, "l_out", il); + + // input for next layer + inpL = cur; } cur = llm_build_norm(ctx0, inpL, hparams, @@ -10476,6 +10499,7 @@ struct llm_build_context { cb(cur, "ffn_out", il); cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -10593,6 +10617,7 @@ struct llm_build_context { cb(cur, "ffn_out", il); cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -10734,6 +10759,7 @@ struct llm_build_context { cb(cur, "hidden_scaled_ffn", -1); cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -10846,6 +10872,7 @@ struct llm_build_context { } cur = ggml_add(ctx0, cur, sa_out); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -10962,7 +10989,9 @@ struct llm_build_context { NULL, LLM_FFN_GELU, LLM_FFN_SEQ, cb, il); cb(cur, "ffn_out", il); + cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -11111,6 +11140,7 @@ struct llm_build_context { // residual cur = ggml_add(ctx0, cur, inpL); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -11252,6 +11282,7 @@ struct llm_build_context { // add together residual + FFN + self-attention cur = ggml_add(ctx0, cur, inpL); cur = ggml_add(ctx0, cur, attn_out); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -11387,10 +11418,7 @@ struct llm_build_context { cur = ggml_add(ctx0, cur, ffn_inp); cb(cur, "ffn_out", il); - ggml_tensor * layer_dir = lctx.cvec.tensor_for(il); - if (layer_dir != nullptr) { - cur = ggml_add(ctx0, cur, layer_dir); - } + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -11504,8 +11532,12 @@ struct llm_build_context { cur = ggml_add(ctx0, cur, inpL); cb(cur, "ffn_out", il); - inpL = ggml_add(ctx0, cur, attn_out); - cb(inpL, "l_out", il); + cur = ggml_add(ctx0, cur, attn_out); + cur = lctx.cvec.apply_to(ctx0, cur, il); + cb(cur, "l_out", il); + + // input for next layer + inpL = cur; } else { // attention and ffn are computed sequentially // x = x + attn(ln1(x)) @@ -11528,8 +11560,12 @@ struct llm_build_context { LLM_FFN_GELU, LLM_FFN_SEQ, cb, il); cb(cur, "ffn_out", il); - inpL = ggml_add(ctx0, cur, ffn_inp); - cb(inpL, "l_out", il); + cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); + cb(cur, "l_out", il); + + // input for next layer + inpL = cur; } } @@ -11656,10 +11692,7 @@ struct llm_build_context { cur = ggml_add(ctx0, cur, ffn_out); cb(cur, "ffn_out", il); - ggml_tensor * layer_dir = lctx.cvec.tensor_for(il); - if (layer_dir != nullptr) { - cur = ggml_add(ctx0, cur, layer_dir); - } + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer @@ -11892,6 +11925,7 @@ struct llm_build_context { } cur = ggml_add(ctx0, cur, ffn_inp); + cur = lctx.cvec.apply_to(ctx0, cur, il); cb(cur, "l_out", il); // input for next layer From 6777c544bdd8c5d9de3220d6e2557957bbbf2a4f Mon Sep 17 00:00:00 2001 From: Olivier Chafik Date: Wed, 26 Jun 2024 01:45:58 +0100 Subject: [PATCH 022/326] `json`: fix additionalProperties, allow space after enum/const (#7840) * json: default additionalProperty to true * json: don't force additional props after normal properties! * json: allow space after enum/const * json: update pydantic example to set additionalProperties: false * json: prevent additional props to redefine a typed prop * port not_strings to python, add trailing space * fix not_strings & port to js+py * Update json-schema-to-grammar.cpp * fix _not_strings for substring overlaps * json: fix additionalProperties default, uncomment tests * json: add integ. test case for additionalProperties * json: nit: simplify condition * reformat grammar integ tests w/ R"""()""" strings where there's escapes * update # tokens in server test: consts can now have trailing space --- common/json-schema-to-grammar.cpp | 99 +++++- examples/json-schema-pydantic-example.py | 6 +- examples/json_schema_to_grammar.py | 76 ++++- .../server/public/json-schema-to-grammar.mjs | 89 ++++- examples/server/tests/features/server.feature | 2 +- tests/test-grammar-integration.cpp | 320 ++++++++---------- tests/test-json-schema-to-grammar.cpp | 150 ++++++-- 7 files changed, 497 insertions(+), 245 deletions(-) diff --git a/common/json-schema-to-grammar.cpp b/common/json-schema-to-grammar.cpp index 07d0e952d74cf..b40821dadc05e 100644 --- a/common/json-schema-to-grammar.cpp +++ b/common/json-schema-to-grammar.cpp @@ -614,6 +614,75 @@ class SchemaConverter { return _add_rule(name, "\"\\\"\" " + to_rule(transform()) + " \"\\\"\" space"); } + /* + Returns a rule that matches a JSON string that is none of the provided strings + + not_strings({"a"}) + -> ["] ( [a] char+ | [^"a] char* )? ["] space + not_strings({"and", "also"}) + -> ["] ( [a] ([l] ([s] ([o] char+ | [^"o] char*) | [^"s] char*) | [n] ([d] char+ | [^"d] char*) | [^"ln] char*) | [^"a] char* )? ["] space + */ + std::string _not_strings(const std::vector & strings) { + + struct TrieNode { + std::map children; + bool is_end_of_string; + + TrieNode() : is_end_of_string(false) {} + + void insert(const std::string & string) { + auto node = this; + for (char c : string) { + node = &node->children[c]; + } + node->is_end_of_string = true; + } + }; + + TrieNode trie; + for (const auto & s : strings) { + trie.insert(s); + } + + std::string char_rule = _add_primitive("char", PRIMITIVE_RULES.at("char")); + std::ostringstream out; + out << "[\"] ( "; + std::function visit = [&](const TrieNode & node) { + std::ostringstream rejects; + auto first = true; + for (const auto & kv : node.children) { + rejects << kv.first; + if (first) { + first = false; + } else { + out << " | "; + } + out << "[" << kv.first << "]"; + if (!kv.second.children.empty()) { + out << " ("; + visit(kv.second); + out << ")"; + } else if (kv.second.is_end_of_string) { + out << " " << char_rule << "+"; + } + } + if (!node.children.empty()) { + if (!first) { + out << " | "; + } + out << "[^\"" << rejects.str() << "] " << char_rule << "*"; + } + }; + visit(trie); + + out << " )"; + if (!trie.is_end_of_string) { + out << "?"; + } + out << " [\"] space"; + return out.str(); + } + std::string _resolve_ref(const std::string & ref) { std::string ref_name = ref.substr(ref.find_last_of('/') + 1); if (_rules.find(ref_name) == _rules.end() && _refs_being_resolved.find(ref) == _refs_being_resolved.end()) { @@ -634,6 +703,7 @@ class SchemaConverter { std::vector required_props; std::vector optional_props; std::unordered_map prop_kv_rule_names; + std::vector prop_names; for (const auto & kv : properties) { const auto &prop_name = kv.first; const auto &prop_schema = kv.second; @@ -648,11 +718,18 @@ class SchemaConverter { } else { optional_props.push_back(prop_name); } + prop_names.push_back(prop_name); } - if (additional_properties.is_object() || (additional_properties.is_boolean() && additional_properties.get())) { + if (!(additional_properties.is_boolean() && !additional_properties.get())) { std::string sub_name = name + (name.empty() ? "" : "-") + "additional"; - std::string value_rule = visit(additional_properties.is_object() ? additional_properties : json::object(), sub_name + "-value"); - std::string kv_rule = _add_rule(sub_name + "-kv", _add_primitive("string", PRIMITIVE_RULES.at("string")) + " \":\" space " + value_rule); + std::string value_rule = + additional_properties.is_object() ? visit(additional_properties, sub_name + "-value") + : _add_primitive("value", PRIMITIVE_RULES.at("value")); + + auto key_rule = + prop_names.empty() ? _add_primitive("string", PRIMITIVE_RULES.at("string")) + : _add_rule(sub_name + "-k", _not_strings(prop_names)); + std::string kv_rule = _add_rule(sub_name + "-kv", key_rule + " \":\" space " + value_rule); prop_kv_rule_names["*"] = kv_rule; optional_props.push_back("*"); } @@ -678,15 +755,11 @@ class SchemaConverter { } std::string k = ks[0]; std::string kv_rule_name = prop_kv_rule_names[k]; - if (k == "*") { - res = _add_rule( - name + (name.empty() ? "" : "-") + "additional-kvs", - kv_rule_name + " ( \",\" space " + kv_rule_name + " )*" - ); - } else if (first_is_optional) { - res = "( \",\" space " + kv_rule_name + " )?"; + std::string comma_ref = "( \",\" space " + kv_rule_name + " )"; + if (first_is_optional) { + res = comma_ref + (k == "*" ? "*" : "?"); } else { - res = kv_rule_name; + res = kv_rule_name + (k == "*" ? " " + comma_ref + "*" : ""); } if (ks.size() > 1) { res += " " + _add_rule( @@ -824,13 +897,13 @@ class SchemaConverter { } return _add_rule(rule_name, _generate_union_rule(name, schema_types)); } else if (schema.contains("const")) { - return _add_rule(rule_name, _generate_constant_rule(schema["const"])); + return _add_rule(rule_name, _generate_constant_rule(schema["const"]) + " space"); } else if (schema.contains("enum")) { std::vector enum_values; for (const auto & v : schema["enum"]) { enum_values.push_back(_generate_constant_rule(v)); } - return _add_rule(rule_name, join(enum_values.begin(), enum_values.end(), " | ")); + return _add_rule(rule_name, "(" + join(enum_values.begin(), enum_values.end(), " | ") + ") space"); } else if ((schema_type.is_null() || schema_type == "object") && (schema.contains("properties") || (schema.contains("additionalProperties") && schema["additionalProperties"] != true))) { diff --git a/examples/json-schema-pydantic-example.py b/examples/json-schema-pydantic-example.py index 2240188cd031e..2a24f81189fb1 100644 --- a/examples/json-schema-pydantic-example.py +++ b/examples/json-schema-pydantic-example.py @@ -3,7 +3,7 @@ #! pip install pydantic #! python json-schema-pydantic-example.py -from pydantic import BaseModel, TypeAdapter +from pydantic import BaseModel, Extra, TypeAdapter from annotated_types import MinLen from typing import Annotated, List, Optional import json, requests @@ -50,12 +50,16 @@ def create_completion(*, response_model=None, endpoint="http://localhost:8080/v1 if __name__ == '__main__': class QAPair(BaseModel): + class Config: + extra = 'forbid' # triggers additionalProperties: false in the JSON schema question: str concise_answer: str justification: str stars: Annotated[int, Field(ge=1, le=5)] class PyramidalSummary(BaseModel): + class Config: + extra = 'forbid' # triggers additionalProperties: false in the JSON schema title: str summary: str question_answers: Annotated[List[QAPair], MinLen(2)] diff --git a/examples/json_schema_to_grammar.py b/examples/json_schema_to_grammar.py index 86500a8c3c238..3f3132f88a824 100755 --- a/examples/json_schema_to_grammar.py +++ b/examples/json_schema_to_grammar.py @@ -4,8 +4,7 @@ import json import re import sys -from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Union - +from typing import Any, List, Optional, Set, Tuple, Union def _build_repetition(item_rule, min_items, max_items, separator_rule=None): @@ -276,6 +275,51 @@ def recurse(i: int): return ''.join(('(', *recurse(0), ')')) + def _not_strings(self, strings): + class TrieNode: + def __init__(self): + self.children = {} + self.is_end_of_string = False + + def insert(self, string): + node = self + for c in string: + node = node.children.setdefault(c, TrieNode()) + node.is_end_of_string = True + + trie = TrieNode() + for s in strings: + trie.insert(s) + + char_rule = self._add_primitive('char', PRIMITIVE_RULES['char']) + out = ['["] ( '] + + def visit(node): + rejects = [] + first = True + for c in sorted(node.children.keys()): + child = node.children[c] + rejects.append(c) + if first: + first = False + else: + out.append(' | ') + out.append(f'[{c}]') + if child.children: + out.append(f' (') + visit(child) + out.append(')') + elif child.is_end_of_string: + out.append(f' {char_rule}+') + if node.children: + if not first: + out.append(' | ') + out.append(f'[^"{"".join(rejects)}] {char_rule}*') + visit(trie) + + out.append(f' ){"" if trie.is_end_of_string else "?"} ["] space') + return ''.join(out) + def _add_rule(self, name, rule): esc_name = INVALID_RULE_CHARS_RE.sub('-', name) if esc_name not in self._rules or self._rules[esc_name] == rule: @@ -524,10 +568,10 @@ def visit(self, schema, name): return self._add_rule(rule_name, self._generate_union_rule(name, [{'type': t} for t in schema_type])) elif 'const' in schema: - return self._add_rule(rule_name, self._generate_constant_rule(schema['const'])) + return self._add_rule(rule_name, self._generate_constant_rule(schema['const']) + ' space') elif 'enum' in schema: - rule = ' | '.join((self._generate_constant_rule(v) for v in schema['enum'])) + rule = '(' + ' | '.join((self._generate_constant_rule(v) for v in schema['enum'])) + ') space' return self._add_rule(rule_name, rule) elif schema_type in (None, 'object') and \ @@ -632,7 +676,7 @@ def _add_primitive(self, name: str, rule: BuiltinRule): self._add_primitive(dep, dep_rule) return n - def _build_object_rule(self, properties: List[Tuple[str, Any]], required: Set[str], name: str, additional_properties: Union[bool, Any]): + def _build_object_rule(self, properties: List[Tuple[str, Any]], required: Set[str], name: str, additional_properties: Optional[Union[bool, Any]]): prop_order = self._prop_order # sort by position in prop_order (if specified) then by original order sorted_props = [kv[0] for _, kv in sorted(enumerate(properties), key=lambda ikv: (prop_order.get(ikv[1][0], len(prop_order)), ikv[0]))] @@ -647,12 +691,16 @@ def _build_object_rule(self, properties: List[Tuple[str, Any]], required: Set[st required_props = [k for k in sorted_props if k in required] optional_props = [k for k in sorted_props if k not in required] - if additional_properties == True or isinstance(additional_properties, dict): + if additional_properties != False: sub_name = f'{name}{"-" if name else ""}additional' - value_rule = self.visit({} if additional_properties == True else additional_properties, f'{sub_name}-value') + value_rule = self.visit(additional_properties, f'{sub_name}-value') if isinstance(additional_properties, dict) else \ + self._add_primitive('value', PRIMITIVE_RULES['value']) + key_rule = self._add_primitive('string', PRIMITIVE_RULES['string']) if not sorted_props \ + else self._add_rule(f'{sub_name}-k', self._not_strings(sorted_props)) + prop_kv_rule_names["*"] = self._add_rule( f'{sub_name}-kv', - self._add_primitive('string', PRIMITIVE_RULES['string']) + f' ":" space {value_rule}' + f'{key_rule} ":" space {value_rule}' ) optional_props.append("*") @@ -667,15 +715,11 @@ def _build_object_rule(self, properties: List[Tuple[str, Any]], required: Set[st def get_recursive_refs(ks, first_is_optional): [k, *rest] = ks kv_rule_name = prop_kv_rule_names[k] - if k == '*': - res = self._add_rule( - f'{name}{"-" if name else ""}additional-kvs', - f'{kv_rule_name} ( "," space ' + kv_rule_name + ' )*' - ) - elif first_is_optional: - res = f'( "," space {kv_rule_name} )?' + comma_ref = f'( "," space {kv_rule_name} )' + if first_is_optional: + res = comma_ref + ('*' if k == '*' else '?') else: - res = kv_rule_name + res = kv_rule_name + (' ' + comma_ref + "*" if k == '*' else '') if len(rest) > 0: res += ' ' + self._add_rule( f'{name}{"-" if name else ""}{k}-rest', diff --git a/examples/server/public/json-schema-to-grammar.mjs b/examples/server/public/json-schema-to-grammar.mjs index f340f94bd75bc..02015bbd49015 100644 --- a/examples/server/public/json-schema-to-grammar.mjs +++ b/examples/server/public/json-schema-to-grammar.mjs @@ -532,6 +532,64 @@ export class SchemaConverter { return this._addRule(name, "\"\\\"\" " + toRule(transform()) + " \"\\\"\" space") } + _notStrings(strings) { + class TrieNode { + constructor() { + this.children = {}; + this.isEndOfString = false; + } + + insert(str) { + let node = this; + for (const c of str) { + node = node.children[c] = node.children[c] || new TrieNode(); + } + node.isEndOfString = true; + } + } + + const trie = new TrieNode(); + for (const s of strings) { + trie.insert(s); + } + + const charRuleName = this._addPrimitive('char', PRIMITIVE_RULES['char']); + const out = ['["] ( ']; + + const visit = (node) => { + const rejects = []; + let first = true; + for (const c of Object.keys(node.children).sort()) { + const child = node.children[c]; + rejects.push(c); + if (first) { + first = false; + } else { + out.push(' | '); + } + out.push(`[${c}]`); + if (Object.keys(child.children).length > 0) { + out.push(' ('); + visit(child); + out.push(')'); + } else if (child.isEndOfString) { + out.push(` ${charRuleName}+`); + } + } + if (Object.keys(node.children).length > 0) { + if (!first) { + out.push(' | '); + } + out.push(`[^"${rejects.join('')}] ${charRuleName}*`); + } + }; + + visit(trie); + + out.push(` )${trie.isEndOfString ? '' : '?'} ["] space`); + return out.join(''); + } + _resolveRef(ref) { let refName = ref.split('/').pop(); if (!(refName in this._rules) && !this._refsBeingResolved.has(ref)) { @@ -560,9 +618,9 @@ export class SchemaConverter { } else if (Array.isArray(schemaType)) { return this._addRule(ruleName, this._generateUnionRule(name, schemaType.map(t => ({ type: t })))); } else if ('const' in schema) { - return this._addRule(ruleName, this._generateConstantRule(schema.const)); + return this._addRule(ruleName, this._generateConstantRule(schema.const) + ' space'); } else if ('enum' in schema) { - const rule = schema.enum.map(v => this._generateConstantRule(v)).join(' | '); + const rule = '(' + schema.enum.map(v => this._generateConstantRule(v)).join(' | ') + ') space'; return this._addRule(ruleName, rule); } else if ((schemaType === undefined || schemaType === 'object') && ('properties' in schema || @@ -599,7 +657,7 @@ export class SchemaConverter { } } - return this._addRule(ruleName, this._buildObjectRule(properties, required, name, /* additionalProperties= */ false)); + return this._addRule(ruleName, this._buildObjectRule(properties, required, name, null)); } else if ((schemaType === undefined || schemaType === 'array') && ('items' in schema || 'prefixItems' in schema)) { const items = schema.items ?? schema.prefixItems; if (Array.isArray(items)) { @@ -693,12 +751,19 @@ export class SchemaConverter { const requiredProps = sortedProps.filter(k => required.has(k)); const optionalProps = sortedProps.filter(k => !required.has(k)); - if (typeof additionalProperties === 'object' || additionalProperties === true) { + if (additionalProperties !== false) { const subName = `${name ?? ''}${name ? '-' : ''}additional`; - const valueRule = this.visit(additionalProperties === true ? {} : additionalProperties, `${subName}-value`); + const valueRule = + additionalProperties != null && typeof additionalProperties === 'object' ? this.visit(additionalProperties, `${subName}-value`) + : this._addPrimitive('value', PRIMITIVE_RULES['value']); + + const key_rule = + sortedProps.length === 0 ? this._addPrimitive('string', PRIMITIVE_RULES['string']) + : this._addRule(`${subName}-k`, this._notStrings(sortedProps)); + propKvRuleNames['*'] = this._addRule( `${subName}-kv`, - `${this._addPrimitive('string', PRIMITIVE_RULES['string'])} ":" space ${valueRule}`); + `${key_rule} ":" space ${valueRule}`); optionalProps.push('*'); } @@ -715,15 +780,11 @@ export class SchemaConverter { const [k, ...rest] = ks; const kvRuleName = propKvRuleNames[k]; let res; - if (k === '*') { - res = this._addRule( - `${name ?? ''}${name ? '-' : ''}additional-kvs`, - `${kvRuleName} ( "," space ` + kvRuleName + ` )*` - ) - } else if (firstIsOptional) { - res = `( "," space ${kvRuleName} )?`; + const commaRef = `( "," space ${kvRuleName} )`; + if (firstIsOptional) { + res = commaRef + (k === '*' ? '*' : '?'); } else { - res = kvRuleName; + res = kvRuleName + (k === '*' ? ' ' + commaRef + '*' : ''); } if (rest.length > 0) { res += ' ' + this._addRule( diff --git a/examples/server/tests/features/server.feature b/examples/server/tests/features/server.feature index d21c09135243a..b55971454afc3 100644 --- a/examples/server/tests/features/server.feature +++ b/examples/server/tests/features/server.feature @@ -82,7 +82,7 @@ Feature: llama.cpp server Examples: Prompts | response_format | n_predicted | re_content | - | {"type": "json_object", "schema": {"const": "42"}} | 5 | "42" | + | {"type": "json_object", "schema": {"const": "42"}} | 6 | "42" | | {"type": "json_object", "schema": {"items": [{"type": "integer"}]}} | 10 | \[ -300 \] | | {"type": "json_object"} | 10 | \{ " Jacky. | diff --git a/tests/test-grammar-integration.cpp b/tests/test-grammar-integration.cpp index 5750d362a7247..23ef8324c1327 100644 --- a/tests/test-grammar-integration.cpp +++ b/tests/test-grammar-integration.cpp @@ -15,8 +15,6 @@ using json = nlohmann::ordered_json; -//#define INCLUDE_FAILING_TESTS 1 - static llama_grammar* build_grammar(const std::string & grammar_str) { auto parsed_grammar = grammar_parser::parse(grammar_str.c_str()); @@ -754,7 +752,7 @@ static void test_json_schema() { )""", // Passing strings { - "{}", + R"""({})""", R"""({"foo": "bar"})""", }, // Failing strings @@ -762,7 +760,7 @@ static void test_json_schema() { "", "[]", "null", - "\"\"", + R"""("")""", "true", } ); @@ -770,16 +768,14 @@ static void test_json_schema() { test_schema( "exotic formats (list)", // Schema - R"""( - { + R"""({ "items": [ { "format": "date" }, { "format": "uuid" }, { "format": "time" }, { "format": "date-time" } ] - } - )""", + })""", // Passing strings { // "{}", // NOTE: This string passes for this schema on https://www.jsonschemavalidator.net/ -- should it? @@ -798,125 +794,113 @@ static void test_json_schema() { test_schema( "string", // Schema - R"""( - { - "type": "string" - } - )""", + R"""({ + "type": "string" + })""", // Passing strings { - "\"foo\"", - "\"bar\"", - "\"\"", + R"""("foo")""", + R"""("bar")""", + R"""("")""", }, // Failing strings { - "{}", - "\"foo\": \"bar\"", + R"""({})""", + R"""("foo": "bar")""", } ); test_schema( "string w/ min length 1", // Schema - R"""( - { - "type": "string", - "minLength": 1 - } - )""", + R"""({ + "type": "string", + "minLength": 1 + })""", // Passing strings { - "\"foo\"", - "\"bar\"", + R"""("foo")""", + R"""("bar")""", }, // Failing strings { - "\"\"", - "{}", - "\"foo\": \"bar\"", + R"""("")""", + R"""({})""", + R"""("foo": "bar")""", } ); test_schema( "string w/ min length 3", // Schema - R"""( - { + R"""({ "type": "string", "minLength": 3 - } - )""", + })""", // Passing strings { - "\"foo\"", - "\"bar\"", - "\"foobar\"", + R"""("foo")""", + R"""("bar")""", + R"""("foobar")""", }, // Failing strings { - "\"\"", - "\"f\"", - "\"fo\"", + R"""("")""", + R"""("f")""", + R"""("fo")""", } ); test_schema( "string w/ max length", // Schema - R"""( - { - "type": "string", - "maxLength": 3 - } - )""", + R"""({ + "type": "string", + "maxLength": 3 + })""", // Passing strings { - "\"foo\"", - "\"bar\"", - "\"\"", - "\"f\"", - "\"fo\"", + R"""("foo")""", + R"""("bar")""", + R"""("")""", + R"""("f")""", + R"""("fo")""", }, // Failing strings { - "\"foobar\"", + R"""("foobar")""", } ); test_schema( "string w/ min & max length", // Schema - R"""( - { - "type": "string", - "minLength": 1, - "maxLength": 4 - } - )""", + R"""({ + "type": "string", + "minLength": 1, + "maxLength": 4 + })""", // Passing strings { - "\"foo\"", - "\"bar\"", - "\"f\"", - "\"barf\"", + R"""("foo")""", + R"""("bar")""", + R"""("f")""", + R"""("barf")""", }, // Failing strings { - "\"\"", - "\"barfo\"", - "\"foobar\"", + R"""("")""", + R"""("barfo")""", + R"""("foobar")""", } ); test_schema( "boolean", // Schema - R"""( - { - "type": "boolean" - } - )""", + R"""({ + "type": "boolean" + })""", // Passing strings { "true", @@ -924,122 +908,112 @@ static void test_json_schema() { }, // Failing strings { - "\"\"", - "\"true\"", - "True", - "FALSE", + R"""("")""", + R"""("true")""", + R"""(True)""", + R"""(FALSE)""", } ); test_schema( "integer", // Schema - R"""( - { - "type": "integer" - } - )""", + R"""({ + "type": "integer" + })""", // Passing strings { - "0", - "12345", - "1234567890123456" + R"""(0)""", + R"""(12345)""", + R"""(1234567890123456)""", }, // Failing strings { - "", - "01", - "007", - "12345678901234567" + R"""()""", + R"""(01)""", + R"""(007)""", + R"""(12345678901234567 )""", } ); test_schema( "string const", // Schema - R"""( - { - "const": "foo" - } - )""", + R"""({ + "const": "foo" + })""", // Passing strings { - "\"foo\"", + R"""("foo")""", }, // Failing strings { - "foo", - "\"bar\"", + R"""(foo)""", + R"""("bar")""", } ); test_schema( "non-string const", // Schema - R"""( - { - "const": true - } - )""", + R"""({ + "const": true + })""", // Passing strings { - "true", + R"""(true)""", }, // Failing strings { - "", - "foo", - "\"true\"", + R"""()""", + R"""(foo)""", + R"""("true")""", } ); test_schema( "non-string const", // Schema - R"""( - { - "enum": ["red", "amber", "green", null, 42, ["foo"]] - } - )""", + R"""({ + "enum": ["red", "amber", "green", null, 42, ["foo"]] + })""", // Passing strings { - "\"red\"", - "null", - "42", - "[\"foo\"]", + R"""("red")""", + R"""(null)""", + R"""(42)""", + R"""(["foo"])""", }, // Failing strings { - "", - "420", - "true", - "foo", + R"""()""", + R"""(420)""", + R"""(true)""", + R"""(foo)""", } ); test_schema( "min+max items", // Schema - R"""( - { - "items": { - "type": ["number", "integer"] - }, - "minItems": 3, - "maxItems": 5 - } - )""", + R"""({ + "items": { + "type": ["number", "integer"] + }, + "minItems": 3, + "maxItems": 5 + })""", // Passing strings { - "[1, 2, 3]", - "[1, 2, 3, 4]", - "[1, 2, 3, 4, 5]", + R"""([1, 2, 3])""", + R"""([1, 2, 3, 4])""", + R"""([1, 2, 3, 4, 5])""", }, // Failing strings { - "[1, 2]", - "[1, 2, 3, 4, 5, 6]", - "1" + R"""([1, 2])""", + R"""([1, 2, 3, 4, 5, 6])""", + R"""(1)""", } ); @@ -1047,16 +1021,14 @@ static void test_json_schema() { test_schema( "object properties", // Schema - R"""( - { + R"""({ "type": "object", "properties": { "number": { "type": "number" }, "street_name": { "type": "string" }, "street_type": { "enum": ["Street", "Avenue", "Boulevard"] } } - } - )""", + })""", // Passing strings { R"""({ "number": 1600, "street_name": "Pennsylvania", "street_type":"Avenue"})""", @@ -1066,12 +1038,8 @@ static void test_json_schema() { // "By extension, even an empty object is valid" R"""({})""", // "By default, providing additional properties is valid" -#ifdef INCLUDE_FAILING_TESTS - // TODO: The following should pass, but currently FAILS. Additional properties should be permitted by default. R"""({ "number": 1600, "street_name": "Pennsylvania", "street_type":"Avenue", "direction":"NW"})""", - // TODO: Spaces should be permitted around enum values, but currently they fail to pass. R"""({ "number": 1600, "street_name": "Pennsylvania", "street_type": "Avenue" })""", -#endif }, // Failing strings { @@ -1084,13 +1052,35 @@ static void test_json_schema() { } ); + test_schema( + "additional properties can't override other properties", + R"""({ + "properties": { + "a": {"type": "integer"}, + "b": {"type": "integer"} + }, + "additionalProperties": true + })""", + // Passing strings + { + R"""({"a": 42})""", + R"""({"c": ""})""", + R"""({"a": 42, "c": ""})""", + R"""({"a_": ""})""", + }, + // Failing strings + { + R"""()""", + R"""({"a": ""})""", + R"""({"a": "", "b": ""})""", + } + ); // Properties (from: https://json-schema.org/understanding-json-schema/reference/object#properties) test_schema( "object properties, additionalProperties: true", // Schema - R"""( - { + R"""({ "type": "object", "properties": { "number": { "type": "number" }, @@ -1098,26 +1088,18 @@ static void test_json_schema() { "street_type": { "enum": ["Street", "Avenue", "Boulevard"] } }, "additionalProperties": true - } - )""", + })""", // Passing strings { // "By extension, even an empty object is valid" R"""({})""", -#ifdef INCLUDE_FAILING_TESTS - // TODO: Following line should pass and doesn't R"""({"number":1600,"street_name":"Pennsylvania","street_type":"Avenue"})""", // "By default, leaving out properties is valid" - // TODO: Following line should pass and doesn't R"""({ "street_name": "Pennsylvania" })""", - // TODO: Following line should pass and doesn't R"""({ "number": 1600, "street_name": "Pennsylvania" })""", // "By default, providing additional properties is valid" - // TODO: The following should pass, but currently FAILS. Additional properties should be permitted by default. R"""({ "number": 1600, "street_name": "Pennsylvania", "street_type":"Avenue", "direction":"NW"})""", - // TODO: Spaces should be permitted around enum values, but currently they fail to pass. R"""({ "number": 1600, "street_name": "Pennsylvania", "street_type": "Avenue" })""", -#endif }, // Failing strings { @@ -1132,8 +1114,7 @@ static void test_json_schema() { test_schema( "required + optional props each in original order", // Schema - R"""( - { + R"""({ "type": "object", "properties": { "number": { "type": "number" }, @@ -1141,18 +1122,15 @@ static void test_json_schema() { "street_type": { "enum": ["Street", "Avenue", "Boulevard"] } }, "additionalProperties": false - } - )""", + })""", // Passing strings { R"""({ "street_name": "Pennsylvania" })""", R"""({ "number": 1600, "street_type":"Avenue"})""", R"""({ "number": 1600, "street_name": "Pennsylvania" })""", R"""({ "number": 1600, "street_name": "Pennsylvania", "street_type":"Avenue"})""", -#ifdef INCLUDE_FAILING_TESTS - // TODO: Spaces should be permitted around enum values, but currently they fail to pass. + // Spaces are permitted around enum values R"""({ "number": 1600, "street_name": "Pennsylvania", "street_type": "Avenue" })""", -#endif }, // Failing strings { @@ -1166,18 +1144,16 @@ static void test_json_schema() { test_schema( "required + optional props each in original order", // Schema - R"""( - { - "properties": { - "b": {"type": "string"}, - "a": {"type": "string"}, - "d": {"type": "string"}, - "c": {"type": "string"} - }, - "required": ["a", "b"], - "additionalProperties": false - } - )""", + R"""({ + "properties": { + "b": {"type": "string"}, + "a": {"type": "string"}, + "d": {"type": "string"}, + "c": {"type": "string"} + }, + "required": ["a", "b"], + "additionalProperties": false + })""", // Passing strings { R"""({"b": "foo", "a": "bar"})""", @@ -1197,8 +1173,7 @@ static void test_json_schema() { test_schema( "required props", // Schema - R"""( - { + R"""({ "$schema": "https://json-schema.org/draft/2020-12/schema", "$id": "https://example.com/product.schema.json", "title": "Product", @@ -1244,8 +1219,7 @@ static void test_json_schema() { } }, "required": [ "productId", "productName", "price" ] - } - )""", + })""", // Passing strings { R"""({"productId": 1, "productName": "A green door", "price": 12.50})""", diff --git a/tests/test-json-schema-to-grammar.cpp b/tests/test-json-schema-to-grammar.cpp index 2e591bd71abaa..1e69cb6ef36be 100755 --- a/tests/test-json-schema-to-grammar.cpp +++ b/tests/test-json-schema-to-grammar.cpp @@ -473,7 +473,7 @@ static void test_all(const std::string & lang, std::function Date: Wed, 26 Jun 2024 01:46:35 +0100 Subject: [PATCH 023/326] `json`: better support for "type" unions (e.g. nullable arrays w/ typed items) (#7863) * json: better suport for "type" arrays (e.g. `{"type": ["array", "null"], "items": {"type": "string"}}`) * json: add test for type: [array, null] fix * update tests --- common/json-schema-to-grammar.cpp | 4 ++- examples/json_schema_to_grammar.py | 2 +- .../server/public/json-schema-to-grammar.mjs | 2 +- tests/test-grammar-integration.cpp | 25 +++++++++++++++ tests/test-json-schema-to-grammar.cpp | 32 +++++++++++++++++++ 5 files changed, 62 insertions(+), 3 deletions(-) diff --git a/common/json-schema-to-grammar.cpp b/common/json-schema-to-grammar.cpp index b40821dadc05e..2f233e2e7477f 100644 --- a/common/json-schema-to-grammar.cpp +++ b/common/json-schema-to-grammar.cpp @@ -893,7 +893,9 @@ class SchemaConverter { } else if (schema_type.is_array()) { std::vector schema_types; for (const auto & t : schema_type) { - schema_types.push_back({{"type", t}}); + json schema_copy(schema); + schema_copy["type"] = t; + schema_types.push_back(schema_copy); } return _add_rule(rule_name, _generate_union_rule(name, schema_types)); } else if (schema.contains("const")) { diff --git a/examples/json_schema_to_grammar.py b/examples/json_schema_to_grammar.py index 3f3132f88a824..92f6e3d47bae7 100755 --- a/examples/json_schema_to_grammar.py +++ b/examples/json_schema_to_grammar.py @@ -565,7 +565,7 @@ def visit(self, schema, name): return self._add_rule(rule_name, self._generate_union_rule(name, schema.get('oneOf') or schema['anyOf'])) elif isinstance(schema_type, list): - return self._add_rule(rule_name, self._generate_union_rule(name, [{'type': t} for t in schema_type])) + return self._add_rule(rule_name, self._generate_union_rule(name, [{**schema, 'type': t} for t in schema_type])) elif 'const' in schema: return self._add_rule(rule_name, self._generate_constant_rule(schema['const']) + ' space') diff --git a/examples/server/public/json-schema-to-grammar.mjs b/examples/server/public/json-schema-to-grammar.mjs index 02015bbd49015..06d76edde500a 100644 --- a/examples/server/public/json-schema-to-grammar.mjs +++ b/examples/server/public/json-schema-to-grammar.mjs @@ -616,7 +616,7 @@ export class SchemaConverter { } else if (schema.oneOf || schema.anyOf) { return this._addRule(ruleName, this._generateUnionRule(name, schema.oneOf || schema.anyOf)); } else if (Array.isArray(schemaType)) { - return this._addRule(ruleName, this._generateUnionRule(name, schemaType.map(t => ({ type: t })))); + return this._addRule(ruleName, this._generateUnionRule(name, schemaType.map(t => ({...schema, type: t})))); } else if ('const' in schema) { return this._addRule(ruleName, this._generateConstantRule(schema.const) + ' space'); } else if ('enum' in schema) { diff --git a/tests/test-grammar-integration.cpp b/tests/test-grammar-integration.cpp index 23ef8324c1327..0e21dc7959943 100644 --- a/tests/test-grammar-integration.cpp +++ b/tests/test-grammar-integration.cpp @@ -993,6 +993,31 @@ static void test_json_schema() { } ); + test_schema( + "", + // Schema + R"""( + { + "type": ["array", "null"], + "items": { "type": "string" } + } + )""", + // Passing strings + { + "null", + "[]", + "[\"123\"]", + "[\"foo\", \"bar\"]", + }, + // Failing strings + { + "", + "[123]", + "\"foo\"", + "[\"foo\", 42]", + } + ); + test_schema( "min+max items", // Schema diff --git a/tests/test-json-schema-to-grammar.cpp b/tests/test-json-schema-to-grammar.cpp index 1e69cb6ef36be..3aaa11833de57 100755 --- a/tests/test-json-schema-to-grammar.cpp +++ b/tests/test-json-schema-to-grammar.cpp @@ -502,6 +502,38 @@ static void test_all(const std::string & lang, std::function Date: Wed, 26 Jun 2024 14:27:46 +0800 Subject: [PATCH 024/326] llama : extend llm_build_ffn() to support _scale tensors (#8103) --- llama.cpp | 255 +++++++++++++++++++++++++++++------------------------- 1 file changed, 135 insertions(+), 120 deletions(-) diff --git a/llama.cpp b/llama.cpp index 989c731495dbb..f78594a6f7c49 100644 --- a/llama.cpp +++ b/llama.cpp @@ -7212,10 +7212,13 @@ static struct ggml_tensor * llm_build_ffn( struct ggml_tensor * cur, struct ggml_tensor * up, struct ggml_tensor * up_b, + struct ggml_tensor * up_s, struct ggml_tensor * gate, struct ggml_tensor * gate_b, + struct ggml_tensor * gate_s, struct ggml_tensor * down, struct ggml_tensor * down_b, + struct ggml_tensor * down_s, struct ggml_tensor * act_scales, llm_ffn_op_type type_op, llm_ffn_gate_type type_gate, @@ -7229,6 +7232,11 @@ static struct ggml_tensor * llm_build_ffn( cb(tmp, "ffn_up_b", il); } + if (up_s) { + tmp = ggml_mul(ctx, tmp, up_s); + cb(tmp, "ffn_up_s", il); + } + if (gate) { switch (type_gate) { case LLM_FFN_SEQ: @@ -7247,6 +7255,12 @@ static struct ggml_tensor * llm_build_ffn( cur = ggml_add(ctx, cur, gate_b); cb(cur, "ffn_gate_b", il); } + + if (gate_s) { + cur = ggml_mul(ctx, cur, gate_s); + cb(cur, "ffn_gate_s", il); + } + } else { cur = tmp; } @@ -7286,7 +7300,10 @@ static struct ggml_tensor * llm_build_ffn( cb(cur, "ffn_gate_par", il); } - cur = ggml_mul_mat(ctx, down, cur); + if (down) { + cur = ggml_mul_mat(ctx, down, cur); + } + if (down_b) { cb(cur, "ffn_down", il); } @@ -7295,6 +7312,11 @@ static struct ggml_tensor * llm_build_ffn( cur = ggml_add(ctx, cur, down_b); } + if (down_s) { + cur = ggml_mul(ctx, cur, down_s); + cb(cur, "ffn_down_s", il); + } + return cur; } @@ -8003,9 +8025,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, model.layers[il].ffn_up_b, - model.layers[il].ffn_gate, model.layers[il].ffn_gate_b, - model.layers[il].ffn_down, model.layers[il].ffn_down_b, + model.layers[il].ffn_up, model.layers[il].ffn_up_b, NULL, + model.layers[il].ffn_gate, model.layers[il].ffn_gate_b, NULL, + model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); cb(cur, "ffn_out", il); @@ -8137,9 +8159,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, NULL, - model.layers[il].ffn_gate, NULL, - model.layers[il].ffn_down, NULL, + model.layers[il].ffn_up, NULL, NULL, + model.layers[il].ffn_gate, NULL, NULL, + model.layers[il].ffn_down, NULL, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); cb(cur, "ffn_out", il); @@ -8242,9 +8264,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, NULL, - model.layers[il].ffn_gate, NULL, - model.layers[il].ffn_down, NULL, + model.layers[il].ffn_up, NULL, NULL, + model.layers[il].ffn_gate, NULL, NULL, + model.layers[il].ffn_down, NULL, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); cb(cur, "ffn_out", il); @@ -8358,9 +8380,9 @@ struct llm_build_context { // feed forward { cur = llm_build_ffn(ctx0, attn_norm, // !! use the attn norm, not the result - model.layers[il].ffn_up, NULL, - NULL, NULL, - model.layers[il].ffn_down, NULL, + model.layers[il].ffn_up, NULL, NULL, + NULL, NULL, NULL, + model.layers[il].ffn_down, NULL, NULL, NULL, LLM_FFN_GELU, LLM_FFN_SEQ, cb, il); cb(cur, "ffn_out", il); @@ -8749,9 +8771,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, model.layers[il].ffn_up_b, - NULL, NULL, - model.layers[il].ffn_down, model.layers[il].ffn_down_b, + model.layers[il].ffn_up, model.layers[il].ffn_up_b, NULL, + NULL, NULL, NULL, + model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL, NULL, LLM_FFN_GELU, LLM_FFN_SEQ, cb, il); cb(cur, "ffn_out", il); @@ -8841,9 +8863,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, NULL, - model.layers[il].ffn_gate, NULL, - model.layers[il].ffn_down, NULL, + model.layers[il].ffn_up, NULL, NULL, + model.layers[il].ffn_gate, NULL, NULL, + model.layers[il].ffn_down, NULL, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); cb(cur, "ffn_out", il); @@ -9026,23 +9048,23 @@ struct llm_build_context { // feed-forward network if (model.arch == LLM_ARCH_BERT) { cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, model.layers[il].ffn_up_b, - NULL, NULL, - model.layers[il].ffn_down, model.layers[il].ffn_down_b, + model.layers[il].ffn_up, model.layers[il].ffn_up_b, NULL, + NULL, NULL, NULL, + model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL, NULL, LLM_FFN_GELU, LLM_FFN_SEQ, cb, il); } else if (model.arch == LLM_ARCH_JINA_BERT_V2) { cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, NULL, - model.layers[il].ffn_gate, NULL, - model.layers[il].ffn_down, model.layers[il].ffn_down_b, + model.layers[il].ffn_up, NULL, NULL, + model.layers[il].ffn_gate, NULL, NULL, + model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL, NULL, LLM_FFN_GELU, LLM_FFN_PAR, cb, il); } else { cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, NULL, - model.layers[il].ffn_gate, NULL, - model.layers[il].ffn_down, NULL, + model.layers[il].ffn_up, NULL, NULL, + model.layers[il].ffn_gate, NULL, NULL, + model.layers[il].ffn_down, NULL, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); } @@ -9138,9 +9160,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, model.layers[il].ffn_up_b, - NULL, NULL, - model.layers[il].ffn_down, model.layers[il].ffn_down_b, + model.layers[il].ffn_up, model.layers[il].ffn_up_b, NULL, + NULL, NULL, NULL, + model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL, NULL, LLM_FFN_GELU, LLM_FFN_SEQ, cb, il); cb(cur, "ffn_out", il); @@ -9276,9 +9298,9 @@ struct llm_build_context { LLM_NORM, cb, il); cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, model.layers[il].ffn_up_b, - NULL, NULL, - model.layers[il].ffn_down, model.layers[il].ffn_down_b, + model.layers[il].ffn_up, model.layers[il].ffn_up_b, NULL, + NULL, NULL, NULL, + model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL, model.layers[il].ffn_act, LLM_FFN_GELU, LLM_FFN_SEQ, cb, il); cb(cur, "ffn_out", il); @@ -9425,9 +9447,9 @@ struct llm_build_context { cur = inpSA; } cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, NULL, - model.layers[il].ffn_gate, NULL, - model.layers[il].ffn_down, NULL, + model.layers[il].ffn_up, NULL, NULL, + model.layers[il].ffn_gate, NULL, NULL, + model.layers[il].ffn_down, NULL, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); cb(cur, "ffn_out", il); @@ -9538,9 +9560,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, NULL, - model.layers[il].ffn_gate, NULL, - model.layers[il].ffn_down, NULL, + model.layers[il].ffn_up, NULL, NULL, + model.layers[il].ffn_gate, NULL, NULL, + model.layers[il].ffn_down, NULL, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); cb(cur, "ffn_out", il); @@ -9651,9 +9673,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, NULL, - model.layers[il].ffn_gate, NULL, - model.layers[il].ffn_down, NULL, + model.layers[il].ffn_up, NULL, NULL, + model.layers[il].ffn_gate, NULL, NULL, + model.layers[il].ffn_down, NULL, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); cb(cur, "ffn_out", il); @@ -9788,9 +9810,9 @@ struct llm_build_context { cb(cur_gate, "ffn_shexp_gate", il); ggml_tensor * cur_ffn = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up_shexp, NULL, - model.layers[il].ffn_gate_shexp, NULL, - model.layers[il].ffn_down_shexp, NULL, + model.layers[il].ffn_up_shexp, NULL, NULL, + model.layers[il].ffn_gate_shexp, NULL, NULL, + model.layers[il].ffn_down_shexp, NULL, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); cb(cur_ffn, "ffn_shexp", il); @@ -9917,9 +9939,9 @@ struct llm_build_context { // FF { ffn_output = llm_build_ffn(ctx0, attn_norm_output, - model.layers[il].ffn_up, model.layers[il].ffn_up_b, - NULL, NULL, - model.layers[il].ffn_down, model.layers[il].ffn_down_b, + model.layers[il].ffn_up, model.layers[il].ffn_up_b, NULL, + NULL, NULL, NULL, + model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL, NULL, LLM_FFN_GELU, LLM_FFN_SEQ, cb, il); cb(ffn_output, "ffn_out", il); @@ -10155,9 +10177,9 @@ struct llm_build_context { // feed-forward network { cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, NULL, - model.layers[il].ffn_gate, NULL, - model.layers[il].ffn_down, NULL, + model.layers[il].ffn_up, NULL, NULL, + model.layers[il].ffn_gate, NULL, NULL, + model.layers[il].ffn_down, NULL, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); cb(cur, "ffn_out", il); @@ -10263,9 +10285,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, model.layers[il].ffn_up_b, - NULL, NULL, - model.layers[il].ffn_down, model.layers[il].ffn_down_b, + model.layers[il].ffn_up, model.layers[il].ffn_up_b, NULL, + NULL, NULL, NULL, + model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL, NULL, LLM_FFN_GELU, LLM_FFN_SEQ, cb, il); cb(cur, "ffn_out", il); @@ -10374,9 +10396,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, model.layers[il].ffn_up_b, - NULL, NULL, - model.layers[il].ffn_down, model.layers[il].ffn_down_b, + model.layers[il].ffn_up, model.layers[il].ffn_up_b, NULL, + NULL, NULL, NULL, + model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL, NULL, LLM_FFN_GELU, LLM_FFN_SEQ, cb, il); cb(cur, "ffn_out", il); @@ -10491,9 +10513,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, NULL, - model.layers[il].ffn_gate, NULL, - model.layers[il].ffn_down, NULL, + model.layers[il].ffn_up, NULL, NULL, + model.layers[il].ffn_gate, NULL, NULL, + model.layers[il].ffn_down, NULL, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); cb(cur, "ffn_out", il); @@ -10609,9 +10631,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, NULL, - model.layers[il].ffn_gate, NULL, - model.layers[il].ffn_down, NULL, + model.layers[il].ffn_up, NULL, NULL, + model.layers[il].ffn_gate, NULL, NULL, + model.layers[il].ffn_down, NULL, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); cb(cur, "ffn_out", il); @@ -10746,9 +10768,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, NULL, - model.layers[il].ffn_gate, NULL, - model.layers[il].ffn_down, NULL, + model.layers[il].ffn_up, NULL, NULL, + model.layers[il].ffn_gate, NULL, NULL, + model.layers[il].ffn_down, NULL, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); cb(cur, "ffn_out", il); @@ -10863,9 +10885,9 @@ struct llm_build_context { // feed-forward network { cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, NULL, - model.layers[il].ffn_gate, NULL, - model.layers[il].ffn_down, NULL, + model.layers[il].ffn_up, NULL, NULL, + model.layers[il].ffn_gate, NULL, NULL, + model.layers[il].ffn_down, NULL, NULL, NULL, LLM_FFN_GELU, LLM_FFN_PAR, cb, il); cb(cur, "ffn_out", il); @@ -10983,9 +11005,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, model.layers[il].ffn_up_b, - NULL, NULL, - model.layers[il].ffn_down, model.layers[il].ffn_down_b, + model.layers[il].ffn_up, model.layers[il].ffn_up_b, NULL, + NULL, NULL, NULL, + model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL, NULL, LLM_FFN_GELU, LLM_FFN_SEQ, cb, il); cb(cur, "ffn_out", il); @@ -11271,9 +11293,9 @@ struct llm_build_context { // feed-forward network { cur = llm_build_ffn(ctx0, ffn_inp, - model.layers[il].ffn_up, NULL, - model.layers[il].ffn_gate, NULL, - model.layers[il].ffn_down, NULL, + model.layers[il].ffn_up, NULL, NULL, + model.layers[il].ffn_gate, NULL, NULL, + model.layers[il].ffn_down, NULL, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); cb(cur, "ffn_out", il); @@ -11408,9 +11430,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, NULL, - model.layers[il].ffn_gate, NULL, - model.layers[il].ffn_down, NULL, + model.layers[il].ffn_up, NULL, NULL, + model.layers[il].ffn_gate, NULL, NULL, + model.layers[il].ffn_down, NULL, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); cb(cur, "ffn_out", il); @@ -11522,9 +11544,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, model.layers[il].ffn_up_b, - NULL, NULL, - model.layers[il].ffn_down, model.layers[il].ffn_down_b, + model.layers[il].ffn_up, model.layers[il].ffn_up_b, NULL, + NULL, NULL, NULL, + model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL, NULL, LLM_FFN_GELU, LLM_FFN_SEQ, cb, il); cb(cur, "ffn_out", il); @@ -11553,9 +11575,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, model.layers[il].ffn_up_b, - NULL, NULL, - model.layers[il].ffn_down, model.layers[il].ffn_down_b, + model.layers[il].ffn_up, model.layers[il].ffn_up_b, NULL, + NULL, NULL, NULL, + model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL, NULL, LLM_FFN_GELU, LLM_FFN_SEQ, cb, il); cb(cur, "ffn_out", il); @@ -11662,9 +11684,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, NULL, - model.layers[il].ffn_gate, NULL, - model.layers[il].ffn_down, NULL, + model.layers[il].ffn_up, NULL, NULL, + model.layers[il].ffn_gate, NULL, NULL, + model.layers[il].ffn_down, NULL, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); cb(cur, "ffn_out", il); @@ -11884,9 +11906,9 @@ struct llm_build_context { cb(cur, "ffn_norm", il); cur = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up, NULL, - model.layers[il].ffn_gate, NULL, - model.layers[il].ffn_down, NULL, + model.layers[il].ffn_up, NULL, NULL, + model.layers[il].ffn_gate, NULL, NULL, + model.layers[il].ffn_down, NULL, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); cb(cur, "ffn_out", il); @@ -11912,9 +11934,9 @@ struct llm_build_context { // FFN shared expert { ggml_tensor * ffn_shexp = llm_build_ffn(ctx0, cur, - model.layers[il].ffn_up_shexp, NULL, - model.layers[il].ffn_gate_shexp, NULL, - model.layers[il].ffn_down_shexp, NULL, + model.layers[il].ffn_up_shexp, NULL, NULL, + model.layers[il].ffn_gate_shexp, NULL, NULL, + model.layers[il].ffn_down_shexp, NULL, NULL, NULL, LLM_FFN_SILU, LLM_FFN_PAR, cb, il); cb(ffn_shexp, "ffn_shexp", il); @@ -12017,7 +12039,7 @@ struct llm_build_context { cb(Kcur, "Kcur", il); cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, - nullptr, nullptr, + NULL, NULL, Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); cur = llm_build_norm(ctx0, cur, hparams, @@ -12044,35 +12066,28 @@ struct llm_build_context { cb(ffn_inp, "ffn_inp", il); // feed-forward forward - if (model.layers[il].ffn_gate_inp == nullptr) { - cur = llm_build_norm(ctx0, ffn_inp, hparams, - model.layers[il].ffn_norm, NULL, - LLM_NORM_RMS, cb, il); - cb(cur, "ffn_norm", il); - - struct ggml_tensor *tmp = ggml_mul_mat(ctx0, model.layers[il].ffn_up, cur); - tmp = ggml_mul(ctx0, tmp, model.layers[il].ffn_up_scale); - cb(tmp, "ffn_up", il); - - cur = ggml_mul_mat(ctx0, model.layers[il].ffn_gate, cur); - cur = ggml_mul(ctx0, cur, model.layers[il].ffn_gate_scale); - cb(cur, "ffn_gate", il); + cur = llm_build_norm(ctx0, ffn_inp, hparams, + model.layers[il].ffn_norm, NULL, + LLM_NORM_RMS, cb, il); + cb(cur, "ffn_norm", il); - cur = ggml_silu(ctx0, cur); - cb(cur, "ffn_silu", il); + cur = llm_build_ffn(ctx0, cur, + model.layers[il].ffn_up, NULL, model.layers[il].ffn_up_scale, + model.layers[il].ffn_gate, NULL, model.layers[il].ffn_gate_scale, + NULL, NULL, NULL, + NULL, + LLM_FFN_SILU, LLM_FFN_PAR, cb, il); + cb(cur, "ffn_sub_out", il); - cur = ggml_mul(ctx0, cur, tmp); - cb(cur, "ffn_gate_par", il); + cur = llm_build_norm(ctx0, cur, hparams, + model.layers[il].ffn_sub_norm, NULL, + LLM_NORM_RMS, cb, il); + cb(cur, "ffn_sub_norm", il); - cur = llm_build_norm(ctx0, cur, hparams, - model.layers[il].ffn_sub_norm, NULL, - LLM_NORM_RMS, cb, il); - cb(cur, "ffn_sub_norm", il); + cur = ggml_mul_mat(ctx0, model.layers[il].ffn_down, cur); + cur = ggml_mul(ctx0, cur, model.layers[il].ffn_down_scale); + cb(cur, "ffn_down", il); - cur = ggml_mul_mat(ctx0, model.layers[il].ffn_down, cur); - cur = ggml_mul(ctx0, cur, model.layers[il].ffn_down_scale); - cb(cur, "ffn_down", il); - } cur = ggml_add(ctx0, cur, ffn_inp); cb(cur, "l_out", il); From c8771ab5f89387cdd7d9a8a69280dac46b45e02f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= Date: Wed, 26 Jun 2024 08:28:02 +0200 Subject: [PATCH 025/326] CUDA: fix misaligned shared memory read (#8123) --- ggml-cuda/mma.cuh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ggml-cuda/mma.cuh b/ggml-cuda/mma.cuh index 0301a52f9ea71..5d87dd8e64c0a 100644 --- a/ggml-cuda/mma.cuh +++ b/ggml-cuda/mma.cuh @@ -23,7 +23,7 @@ struct mma_int_A_I16K4 { __device__ __forceinline__ void load(const int * __restrict__ xs0, const int & stride) { #if defined(INT8_MMA_AVAILABLE) - const int * xs = xs0 + (threadIdx.x%I)*stride + (threadIdx.x/I)*(K/2); + const int * xs = xs0 + (threadIdx.x%I)*stride; asm("ldmatrix.sync.aligned.m8n8.x2.b16 {%0, %1}, [%2];" : "+r"(x[0]), "+r"(x[1]) : "l"(xs)); From 88540445615e77a0177fcca43aaa8e9d8eea6864 Mon Sep 17 00:00:00 2001 From: Isaac McFadyen Date: Wed, 26 Jun 2024 02:29:28 -0400 Subject: [PATCH 026/326] Clarify default MMQ for CUDA and LLAMA_CUDA_FORCE_MMQ flag (#8115) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * Add message about int8 support * Add suggestions from review Co-authored-by: Johannes Gäßler --------- Co-authored-by: Johannes Gäßler --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index a54ee3951d41d..95d970d8382b3 100644 --- a/README.md +++ b/README.md @@ -511,7 +511,7 @@ Building the program with BLAS support may lead to some performance improvements | LLAMA_CUDA_FORCE_DMMV | Boolean | false | Force the use of dequantization + matrix vector multiplication kernels instead of using kernels that do matrix vector multiplication on quantized data. By default the decision is made based on compute capability (MMVQ for 6.1/Pascal/GTX 1000 or higher). Does not affect k-quants. | | LLAMA_CUDA_DMMV_X | Positive integer >= 32 | 32 | Number of values in x direction processed by the CUDA dequantization + matrix vector multiplication kernel per iteration. Increasing this value can improve performance on fast GPUs. Power of 2 heavily recommended. Does not affect k-quants. | | LLAMA_CUDA_MMV_Y | Positive integer | 1 | Block size in y direction for the CUDA mul mat vec kernels. Increasing this value can improve performance on fast GPUs. Power of 2 recommended. | - | LLAMA_CUDA_FORCE_MMQ | Boolean | false | Force the use of custom matrix multiplication kernels for quantized models instead of FP16 cuBLAS even if there is no int8 tensor core implementation available (affects V100, RDNA3). Speed for large batch sizes will be worse but VRAM consumption will be lower. | + | LLAMA_CUDA_FORCE_MMQ | Boolean | false | Force the use of custom matrix multiplication kernels for quantized models instead of FP16 cuBLAS even if there is no int8 tensor core implementation available (affects V100, RDNA3). MMQ kernels are enabled by default on GPUs with int8 tensor core support. With MMQ force enabled, speed for large batch sizes will be worse but VRAM consumption will be lower. | | LLAMA_CUDA_FORCE_CUBLAS | Boolean | false | Force the use of FP16 cuBLAS instead of custom matrix multiplication kernels for quantized models | | LLAMA_CUDA_F16 | Boolean | false | If enabled, use half-precision floating point arithmetic for the CUDA dequantization + mul mat vec kernels and for the q4_1 and q5_1 matrix matrix multiplication kernels. Can improve performance on relatively recent GPUs. | | LLAMA_CUDA_KQUANTS_ITER | 1 or 2 | 2 | Number of values processed per iteration and per CUDA thread for Q2_K and Q6_K quantization formats. Setting this value to 1 can improve performance for slow GPUs. | From f3f65429c44bb195a9195bfdc19a30a79709db7b Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Wed, 26 Jun 2024 18:33:02 +0300 Subject: [PATCH 027/326] llama : reorganize source code + improve CMake (#8006) * scripts : update sync [no ci] * files : relocate [no ci] * ci : disable kompute build [no ci] * cmake : fixes [no ci] * server : fix mingw build ggml-ci * cmake : minor [no ci] * cmake : link math library [no ci] * cmake : build normal ggml library (not object library) [no ci] * cmake : fix kompute build ggml-ci * make,cmake : fix LLAMA_CUDA + replace GGML_CDEF_PRIVATE ggml-ci * move public backend headers to the public include directory (#8122) * move public backend headers to the public include directory * nix test * spm : fix metal header --------- Co-authored-by: Georgi Gerganov * scripts : fix sync paths [no ci] * scripts : sync ggml-blas.h [no ci] --------- Co-authored-by: slaren --- .devops/nix/package.nix | 24 +- .github/labeler.yml | 28 +- .github/workflows/bench.yml | 2 +- .github/workflows/build.yml | 74 +- .github/workflows/server.yml | 6 +- .gitignore | 1 + .gitmodules | 2 +- CMakeLists.txt | 1370 +---------------- CMakePresets.json | 6 +- Makefile | 952 ++++++++---- Package.swift | 21 +- README-sycl.md | 24 +- README.md | 62 +- ci/run.sh | 10 +- {scripts => cmake}/build-info.cmake | 0 cmake/git-vars.cmake | 22 + .../llama-config.cmake.in | 32 +- common/CMakeLists.txt | 7 +- .../cmake/build-info-gen-cpp.cmake | 4 +- docs/BLIS.md | 6 +- examples/CMakeLists.txt | 4 +- examples/imatrix/README.md | 2 +- examples/llava/MobileVLM-README.md | 2 +- examples/rpc/README.md | 8 +- examples/server/CMakeLists.txt | 15 +- examples/sycl/build.sh | 4 +- examples/sycl/win-build-sycl.bat | 4 +- ggml/CMakeLists.txt | 238 +++ {cmake => ggml/cmake}/FindSIMD.cmake | 12 +- .../ggml_vk_generate_shaders.py | 0 ggml-alloc.h => ggml/include/ggml-alloc.h | 0 ggml-backend.h => ggml/include/ggml-backend.h | 0 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scripts/server-llm.sh | 2 +- scripts/sync-ggml-am.sh | 113 +- scripts/sync-ggml.sh | 68 +- spm-headers/ggml-alloc.h | 2 +- spm-headers/ggml-backend.h | 2 +- spm-headers/ggml-metal.h | 1 + spm-headers/ggml.h | 2 +- spm-headers/llama.h | 2 +- src/CMakeLists.txt | 32 + llama.cpp => src/llama.cpp | 0 unicode-data.cpp => src/unicode-data.cpp | 0 unicode-data.h => src/unicode-data.h | 0 unicode.cpp => src/unicode.cpp | 0 unicode.h => src/unicode.h | 0 tests/test-backend-ops.cpp | 1 - 345 files changed, 2499 insertions(+), 1881 deletions(-) rename {scripts => cmake}/build-info.cmake (100%) create mode 100644 cmake/git-vars.cmake rename scripts/LlamaConfig.cmake.in => cmake/llama-config.cmake.in (73%) rename scripts/gen-build-info-cpp.cmake => common/cmake/build-info-gen-cpp.cmake (86%) create mode 100644 ggml/CMakeLists.txt rename {cmake => ggml/cmake}/FindSIMD.cmake (94%) rename ggml_vk_generate_shaders.py => ggml/ggml_vk_generate_shaders.py (100%) rename ggml-alloc.h => 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ggml/src/ggml-cuda}/template-instances/fattn-wmma-f16-instance-kqfloat-cpb32.cu (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/template-instances/fattn-wmma-f16-instance-kqhalf-cpb16.cu (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/template-instances/fattn-wmma-f16-instance-kqhalf-cpb32.cu (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/template-instances/fattn-wmma-f16-instance-kqhalf-cpb8.cu (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/template-instances/generate_cu_files.py (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/template-instances/mmq-instance-q2_k.cu (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/template-instances/mmq-instance-q3_k.cu (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/template-instances/mmq-instance-q4_0.cu (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/template-instances/mmq-instance-q4_1.cu (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/template-instances/mmq-instance-q4_k.cu (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/template-instances/mmq-instance-q5_0.cu (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/template-instances/mmq-instance-q5_1.cu (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/template-instances/mmq-instance-q5_k.cu (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/template-instances/mmq-instance-q6_k.cu (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/template-instances/mmq-instance-q8_0.cu (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/tsembd.cu (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/tsembd.cuh (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/unary.cu (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/unary.cuh (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/upscale.cu (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/upscale.cuh (100%) rename {ggml-cuda => ggml/src/ggml-cuda}/vecdotq.cuh (100%) rename ggml-impl.h => ggml/src/ggml-impl.h (100%) rename ggml-kompute.cpp => ggml/src/ggml-kompute.cpp (100%) rename ggml-metal.m => ggml/src/ggml-metal.m (100%) rename ggml-metal.metal => ggml/src/ggml-metal.metal (100%) rename ggml-quants.c => ggml/src/ggml-quants.c (100%) rename ggml-quants.h => ggml/src/ggml-quants.h (100%) rename ggml-rpc.cpp => ggml/src/ggml-rpc.cpp (100%) rename ggml-sycl.cpp => ggml/src/ggml-sycl.cpp (99%) rename {ggml-sycl => ggml/src/ggml-sycl}/backend.hpp (100%) rename {ggml-sycl => ggml/src/ggml-sycl}/common.cpp (100%) rename {ggml-sycl => ggml/src/ggml-sycl}/common.hpp (99%) rename {ggml-sycl => ggml/src/ggml-sycl}/convert.cpp (100%) rename {ggml-sycl => ggml/src/ggml-sycl}/convert.hpp (100%) rename {ggml-sycl => ggml/src/ggml-sycl}/dequantize.hpp (100%) rename {ggml-sycl => ggml/src/ggml-sycl}/dmmv.cpp (100%) rename {ggml-sycl => ggml/src/ggml-sycl}/dmmv.hpp (100%) rename {ggml-sycl => ggml/src/ggml-sycl}/dpct/helper.hpp (100%) rename {ggml-sycl => ggml/src/ggml-sycl}/mmq.cpp (100%) rename {ggml-sycl => ggml/src/ggml-sycl}/mmq.hpp (100%) rename {ggml-sycl => ggml/src/ggml-sycl}/mmvq.cpp (100%) rename {ggml-sycl => ggml/src/ggml-sycl}/mmvq.hpp (100%) rename {ggml-sycl => ggml/src/ggml-sycl}/presets.hpp (96%) rename {ggml-sycl => ggml/src/ggml-sycl}/vecdotq.hpp (100%) rename ggml-vulkan-shaders.hpp => ggml/src/ggml-vulkan-shaders.hpp (100%) rename ggml-vulkan.cpp => ggml/src/ggml-vulkan.cpp (100%) rename ggml.c => ggml/src/ggml.c (100%) rename kompute => ggml/src/kompute (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/common.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_add.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_addrow.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_cpy_f16_f16.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_cpy_f16_f32.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_cpy_f32_f16.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_cpy_f32_f32.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_diagmask.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_gelu.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_getrows.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_getrows_f16.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_getrows_f32.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_getrows_q4_0.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_getrows_q4_1.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_getrows_q6_k.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_mul.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_mul_mat_f16.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_mul_mat_mat_f32.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_mul_mat_q4_0.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_mul_mat_q4_1.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_mul_mat_q6_k.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_mul_mat_q8_0.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_mul_mv_q_n.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_mul_mv_q_n_pre.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_norm.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_relu.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_rmsnorm.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_rope_f16.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_rope_f32.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_scale.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_scale_8.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_silu.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/op_softmax.comp (100%) rename {kompute-shaders => ggml/src/kompute-shaders}/rope_common.comp (100%) rename sgemm.cpp => ggml/src/sgemm.cpp (100%) rename sgemm.h => ggml/src/sgemm.h (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/add.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/argsort.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/clamp.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/copy.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/dequant_f32.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/dequant_funcs.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/dequant_head.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/dequant_q2_k.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/dequant_q3_k.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/dequant_q4_0.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/dequant_q4_1.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/dequant_q4_k.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/dequant_q5_0.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/dequant_q5_1.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/dequant_q5_k.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/dequant_q6_k.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/dequant_q8_0.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/diag_mask_inf.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/div.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/gelu.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/generic_binary_head.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/generic_head.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/generic_unary_head.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/get_rows.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/get_rows_quant.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/mul.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/mul_mat_split_k_reduce.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/mul_mat_vec.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/mul_mat_vec_base.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/mul_mat_vec_nc.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/mul_mat_vec_p021.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/mul_mat_vec_q2_k.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/mul_mat_vec_q3_k.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/mul_mat_vec_q4_k.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/mul_mat_vec_q5_k.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/mul_mat_vec_q6_k.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/mul_mm.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/norm.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/relu.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/rms_norm.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/rope_head.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/rope_neox.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/rope_norm.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/scale.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/silu.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/soft_max.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/square.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/sum_rows.comp (100%) rename {vulkan-shaders => ggml/src/vulkan-shaders}/types.comp (100%) rename llama.h => include/llama.h (100%) create mode 120000 spm-headers/ggml-metal.h create mode 100644 src/CMakeLists.txt rename llama.cpp => src/llama.cpp (100%) rename unicode-data.cpp => src/unicode-data.cpp (100%) rename unicode-data.h => src/unicode-data.h (100%) rename unicode.cpp => src/unicode.cpp (100%) rename unicode.h => src/unicode.h (100%) diff --git a/.devops/nix/package.nix b/.devops/nix/package.nix index 87bb3a20f2a28..4ee0d62cb49d9 100644 --- a/.devops/nix/package.nix +++ b/.devops/nix/package.nix @@ -160,9 +160,9 @@ effectiveStdenv.mkDerivation ( }; postPatch = '' - substituteInPlace ./ggml-metal.m \ + substituteInPlace ./ggml/src/ggml-metal.m \ --replace '[bundle pathForResource:@"ggml-metal" ofType:@"metal"];' "@\"$out/bin/ggml-metal.metal\";" - substituteInPlace ./ggml-metal.m \ + substituteInPlace ./ggml/src/ggml-metal.m \ --replace '[bundle pathForResource:@"default" ofType:@"metallib"];' "@\"$out/bin/default.metallib\";" ''; @@ -205,17 +205,17 @@ effectiveStdenv.mkDerivation ( cmakeFlags = [ - (cmakeBool "LLAMA_NATIVE" false) (cmakeBool "LLAMA_BUILD_SERVER" true) (cmakeBool "BUILD_SHARED_LIBS" (!enableStatic)) (cmakeBool "CMAKE_SKIP_BUILD_RPATH" true) - (cmakeBool "LLAMA_BLAS" useBlas) - (cmakeBool "LLAMA_CLBLAST" useOpenCL) - (cmakeBool "LLAMA_CUDA" useCuda) - (cmakeBool "LLAMA_HIPBLAS" useRocm) - (cmakeBool "LLAMA_METAL" useMetalKit) - (cmakeBool "LLAMA_VULKAN" useVulkan) - (cmakeBool "LLAMA_STATIC" enableStatic) + (cmakeBool "GGML_NATIVE" false) + (cmakeBool "GGML_BLAS" useBlas) + (cmakeBool "GGML_CLBLAST" useOpenCL) + (cmakeBool "GGML_CUDA" useCuda) + (cmakeBool "GGML_HIPBLAS" useRocm) + (cmakeBool "GGML_METAL" useMetalKit) + (cmakeBool "GGML_VULKAN" useVulkan) + (cmakeBool "GGML_STATIC" enableStatic) ] ++ optionals useCuda [ ( @@ -231,7 +231,7 @@ effectiveStdenv.mkDerivation ( ] ++ optionals useMetalKit [ (lib.cmakeFeature "CMAKE_C_FLAGS" "-D__ARM_FEATURE_DOTPROD=1") - (cmakeBool "LLAMA_METAL_EMBED_LIBRARY" (!precompileMetalShaders)) + (cmakeBool "GGML_METAL_EMBED_LIBRARY" (!precompileMetalShaders)) ]; # Environment variables needed for ROCm @@ -244,7 +244,7 @@ effectiveStdenv.mkDerivation ( # if they haven't been added yet. postInstall = '' mkdir -p $out/include - cp $src/llama.h $out/include/ + cp $src/include/llama.h $out/include/ ''; # Define the shells here, but don't add in the inputsFrom to avoid recursion. diff --git a/.github/labeler.yml b/.github/labeler.yml index 5c12bab735e9c..9c0397d16e1a0 100644 --- a/.github/labeler.yml +++ b/.github/labeler.yml @@ -2,31 +2,31 @@ Kompute: - changed-files: - any-glob-to-any-file: - - ggml-kompute.h - - ggml-kompute.cpp + - ggml/include/ggml-kompute.h + - ggml/src/ggml-kompute.cpp - README-kompute.md Apple Metal: - changed-files: - any-glob-to-any-file: - - ggml-metal.h - - ggml-metal.cpp + - ggml/include/ggml-metal.h + - ggml/src/ggml-metal.cpp - README-metal.md SYCL: - changed-files: - any-glob-to-any-file: - - ggml-sycl.h - - ggml-sycl.cpp + - ggml/include/ggml-sycl.h + - ggml/src/ggml-sycl.cpp - README-sycl.md Nvidia GPU: - changed-files: - any-glob-to-any-file: - - ggml-cuda.h - - ggml-cuda/** + - ggml/include/ggml-cuda.h + - ggml/src/ggml-cuda/** Vulkan: - changed-files: - any-glob-to-any-file: - - ggml_vk_generate_shaders.py - - ggml-vulkan* + - ggml/ggml_vk_generate_shaders.py + - ggml/src/ggml-vulkan* documentation: - changed-files: - any-glob-to-any-file: @@ -73,10 +73,10 @@ server: ggml: - changed-files: - any-glob-to-any-file: - - ggml.c - - ggml.h - - ggml-*.c - - ggml-*.h + - ggml/include/ggml*.h + - ggml/src/ggml*.c + - ggml/src/ggml*.cpp + - ggml/src/ggml*.h - ggml-cuda/** nix: - changed-files: diff --git a/.github/workflows/bench.yml b/.github/workflows/bench.yml index 88ab4844ef123..eb69b82c47e64 100644 --- a/.github/workflows/bench.yml +++ b/.github/workflows/bench.yml @@ -109,7 +109,7 @@ jobs: run: | set -eux cmake -B build \ - -DLLAMA_NATIVE=OFF \ + -DGGML_NATIVE=OFF \ -DLLAMA_BUILD_SERVER=ON \ -DLLAMA_CURL=ON \ -DLLAMA_CUBLAS=ON \ diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index a8fcae0435e00..0d91fc4e4e965 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -47,7 +47,7 @@ jobs: sysctl -a mkdir build cd build - cmake -DLLAMA_FATAL_WARNINGS=ON -DLLAMA_METAL_EMBED_LIBRARY=ON -DLLAMA_CURL=ON .. + cmake -DLLAMA_FATAL_WARNINGS=ON -DGGML_METAL_EMBED_LIBRARY=ON -DLLAMA_CURL=ON .. cmake --build . --config Release -j $(sysctl -n hw.logicalcpu) - name: Test @@ -105,7 +105,7 @@ jobs: sysctl -a # Metal is disabled due to intermittent failures with Github runners not having a GPU: # https://github.com/ggerganov/llama.cpp/actions/runs/8635935781/job/23674807267#step:5:2313 - cmake -B build -DLLAMA_FATAL_WARNINGS=ON -DLLAMA_METAL=OFF -DLLAMA_CURL=ON + cmake -B build -DLLAMA_FATAL_WARNINGS=ON -DGGML_METAL=OFF -DLLAMA_CURL=ON cmake --build build --config Release -j $(sysctl -n hw.logicalcpu) - name: Test @@ -305,7 +305,7 @@ jobs: run: | mkdir build cd build - cmake .. -DLLAMA_FATAL_WARNINGS=ON -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} -DLLAMA_OPENMP=OFF + cmake .. -DLLAMA_FATAL_WARNINGS=ON -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} -DGGML_OPENMP=OFF cmake --build . --config ${{ matrix.build_type }} -j $(nproc) - name: Test @@ -335,7 +335,7 @@ jobs: run: | mkdir build cd build - cmake -DLLAMA_RPC=ON .. + cmake -DGGML_RPC=ON .. cmake --build . --config Release -j $(nproc) - name: Test @@ -363,7 +363,7 @@ jobs: run: | mkdir build cd build - cmake -DLLAMA_VULKAN=ON .. + cmake -DGGML_VULKAN=ON .. cmake --build . --config Release -j $(nproc) ubuntu-22-cmake-hip: @@ -384,13 +384,13 @@ jobs: - name: Build with native CMake HIP support id: cmake_build run: | - cmake -B build -S . -DCMAKE_HIP_COMPILER="$(hipconfig -l)/clang" -DLLAMA_HIPBLAS=ON + cmake -B build -S . -DCMAKE_HIP_COMPILER="$(hipconfig -l)/clang" -DGGML_HIPBLAS=ON cmake --build build --config Release -j $(nproc) - name: Build with legacy HIP support id: cmake_build_legacy_hip run: | - cmake -B build2 -S . -DCMAKE_C_COMPILER=hipcc -DCMAKE_CXX_COMPILER=hipcc -DLLAMA_HIPBLAS=ON + cmake -B build2 -S . -DCMAKE_C_COMPILER=hipcc -DCMAKE_CXX_COMPILER=hipcc -DGGML_HIPBLAS=ON cmake --build build2 --config Release -j $(nproc) ubuntu-22-cmake-sycl: @@ -431,7 +431,7 @@ jobs: source /opt/intel/oneapi/setvars.sh mkdir build cd build - cmake -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx .. + cmake -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx .. cmake --build . --config Release -j $(nproc) ubuntu-22-cmake-sycl-fp16: @@ -472,10 +472,10 @@ jobs: source /opt/intel/oneapi/setvars.sh mkdir build cd build - cmake -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL_F16=ON .. + cmake -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL_F16=ON .. cmake --build . --config Release -j $(nproc) - # TODO: build with LLAMA_NO_METAL because test-backend-ops fail on "Apple Paravirtual device" and I don't know + # TODO: build with GGML_NO_METAL because test-backend-ops fail on "Apple Paravirtual device" and I don't know # how to debug it. # ref: https://github.com/ggerganov/llama.cpp/actions/runs/7131777249/job/19420981052#step:5:1124 macOS-latest-make: @@ -497,15 +497,15 @@ jobs: env: LLAMA_FATAL_WARNINGS: 1 run: | - LLAMA_NO_METAL=1 make -j $(sysctl -n hw.logicalcpu) + GGML_NO_METAL=1 make -j $(sysctl -n hw.logicalcpu) - name: Test id: make_test run: | - LLAMA_NO_METAL=1 make tests -j $(sysctl -n hw.logicalcpu) - LLAMA_NO_METAL=1 make test -j $(sysctl -n hw.logicalcpu) + GGML_NO_METAL=1 make tests -j $(sysctl -n hw.logicalcpu) + GGML_NO_METAL=1 make test -j $(sysctl -n hw.logicalcpu) - # TODO: build with LLAMA_METAL=OFF because test-backend-ops fail on "Apple Paravirtual device" and I don't know + # TODO: build with GGML_METAL=OFF because test-backend-ops fail on "Apple Paravirtual device" and I don't know # how to debug it. # ref: https://github.com/ggerganov/llama.cpp/actions/runs/7132125951/job/19422043567?pr=4359#step:5:6584 # would be great if we fix these @@ -529,7 +529,7 @@ jobs: sysctl -a mkdir build cd build - cmake -DLLAMA_FATAL_WARNINGS=ON -DLLAMA_METAL=OFF .. + cmake -DLLAMA_FATAL_WARNINGS=ON -DGGML_METAL=OFF .. cmake --build . --config Release -j $(sysctl -n hw.logicalcpu) - name: Test @@ -559,13 +559,14 @@ jobs: mkdir build cd build cmake -G Xcode .. \ - -DLLAMA_METAL_EMBED_LIBRARY=ON \ + -DGGML_METAL_EMBED_LIBRARY=ON \ -DLLAMA_BUILD_EXAMPLES=OFF \ -DLLAMA_BUILD_TESTS=OFF \ -DLLAMA_BUILD_SERVER=OFF \ -DCMAKE_SYSTEM_NAME=iOS \ - -DCMAKE_OSX_DEPLOYMENT_TARGET=14.0 - cmake --build . --config Release -j $(sysctl -n hw.logicalcpu) + -DCMAKE_OSX_DEPLOYMENT_TARGET=14.0 \ + -DCMAKE_XCODE_ATTRIBUTE_DEVELOPMENT_TEAM=ggml + cmake --build . --config Release -j $(sysctl -n hw.logicalcpu) -- CODE_SIGNING_ALLOWED=NO macOS-latest-cmake-tvos: runs-on: macos-latest @@ -588,13 +589,14 @@ jobs: mkdir build cd build cmake -G Xcode .. \ - -DLLAMA_METAL_EMBED_LIBRARY=ON \ + -DGGML_METAL_EMBED_LIBRARY=ON \ -DLLAMA_BUILD_EXAMPLES=OFF \ -DLLAMA_BUILD_TESTS=OFF \ -DLLAMA_BUILD_SERVER=OFF \ -DCMAKE_SYSTEM_NAME=tvOS \ - -DCMAKE_OSX_DEPLOYMENT_TARGET=14.0 - cmake --build . --config Release -j $(sysctl -n hw.logicalcpu) + -DCMAKE_OSX_DEPLOYMENT_TARGET=14.0 \ + -DCMAKE_XCODE_ATTRIBUTE_DEVELOPMENT_TEAM=ggml + cmake --build . --config Release -j $(sysctl -n hw.logicalcpu) -- CODE_SIGNING_ALLOWED=NO macOS-latest-swift: runs-on: macos-latest @@ -662,7 +664,7 @@ jobs: - name: Build using make w/ OpenBLAS shell: msys2 {0} run: | - make LLAMA_OPENBLAS=1 -j $(nproc) + make GGML_OPENBLAS=1 -j $(nproc) - name: Build using CMake shell: msys2 {0} @@ -678,7 +680,7 @@ jobs: - name: Build using CMake w/ OpenBLAS shell: msys2 {0} run: | - cmake -B build -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS + cmake -B build -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS cmake --build build --config ${{ matrix.build }} -j $(nproc) windows-latest-cmake: @@ -693,25 +695,25 @@ jobs: matrix: include: - build: 'rpc-x64' - defines: '-DLLAMA_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DLLAMA_RPC=ON -DBUILD_SHARED_LIBS=ON' + defines: '-DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_RPC=ON -DBUILD_SHARED_LIBS=ON' - build: 'noavx-x64' - defines: '-DLLAMA_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DLLAMA_AVX=OFF -DLLAMA_AVX2=OFF -DLLAMA_FMA=OFF -DBUILD_SHARED_LIBS=ON' + defines: '-DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_AVX=OFF -DGGML_AVX2=OFF -DGGML_FMA=OFF -DBUILD_SHARED_LIBS=ON' - build: 'avx2-x64' - defines: '-DLLAMA_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DBUILD_SHARED_LIBS=ON' + defines: '-DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DBUILD_SHARED_LIBS=ON' - build: 'avx-x64' - defines: '-DLLAMA_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DLLAMA_AVX2=OFF -DBUILD_SHARED_LIBS=ON' + defines: '-DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_AVX2=OFF -DBUILD_SHARED_LIBS=ON' - build: 'avx512-x64' - defines: '-DLLAMA_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DLLAMA_AVX512=ON -DBUILD_SHARED_LIBS=ON' + defines: '-DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_AVX512=ON -DBUILD_SHARED_LIBS=ON' - build: 'openblas-x64' - defines: '-DLLAMA_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DLLAMA_BLAS=ON -DBUILD_SHARED_LIBS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS -DBLAS_INCLUDE_DIRS="$env:RUNNER_TEMP/openblas/include" -DBLAS_LIBRARIES="$env:RUNNER_TEMP/openblas/lib/openblas.lib"' + defines: '-DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_BLAS=ON -DBUILD_SHARED_LIBS=ON -DGGML_BLAS_VENDOR=OpenBLAS -DBLAS_INCLUDE_DIRS="$env:RUNNER_TEMP/openblas/include" -DBLAS_LIBRARIES="$env:RUNNER_TEMP/openblas/lib/openblas.lib"' - build: 'kompute-x64' - defines: '-DLLAMA_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DLLAMA_KOMPUTE=ON -DKOMPUTE_OPT_DISABLE_VULKAN_VERSION_CHECK=ON -DBUILD_SHARED_LIBS=ON' + defines: '-DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_KOMPUTE=ON -DKOMPUTE_OPT_DISABLE_VULKAN_VERSION_CHECK=ON -DBUILD_SHARED_LIBS=ON' - build: 'vulkan-x64' - defines: '-DLLAMA_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DLLAMA_VULKAN=ON -DBUILD_SHARED_LIBS=ON' + defines: '-DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_VULKAN=ON -DBUILD_SHARED_LIBS=ON' - build: 'llvm-arm64' - defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-llvm.cmake -DLLAMA_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DBUILD_SHARED_LIBS=ON' + defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-llvm.cmake -DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DBUILD_SHARED_LIBS=ON' - build: 'msvc-arm64' - defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-msvc.cmake -DLLAMA_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DBUILD_SHARED_LIBS=ON' + defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-msvc.cmake -DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DBUILD_SHARED_LIBS=ON' steps: - name: Clone @@ -724,7 +726,7 @@ jobs: id: clone_kompute if: ${{ matrix.build == 'kompute-x64' }} run: | - git submodule update --init kompute + git submodule update --init ggml/src/kompute - name: Download OpenBLAS id: get_openblas @@ -854,7 +856,7 @@ jobs: run: | mkdir build cd build - cmake .. -DLLAMA_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DLLAMA_CUDA=ON -DBUILD_SHARED_LIBS=ON + cmake .. -DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_CUDA=ON -DBUILD_SHARED_LIBS=ON cmake --build . --config Release -j ${env:NUMBER_OF_PROCESSORS} - name: Determine tag name @@ -987,7 +989,7 @@ jobs: run: | $env:HIP_PATH=$(Resolve-Path 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | split-path | split-path) $env:CMAKE_PREFIX_PATH="${env:HIP_PATH}" - cmake -G "Unix Makefiles" -B build -S . -DCMAKE_C_COMPILER="${env:HIP_PATH}\bin\clang.exe" -DCMAKE_CXX_COMPILER="${env:HIP_PATH}\bin\clang++.exe" -DLLAMA_HIPBLAS=ON + cmake -G "Unix Makefiles" -B build -S . -DCMAKE_C_COMPILER="${env:HIP_PATH}\bin\clang.exe" -DCMAKE_CXX_COMPILER="${env:HIP_PATH}\bin\clang++.exe" -DGGML_HIPBLAS=ON cmake --build build --config Release ios-xcode-build: diff --git a/.github/workflows/server.yml b/.github/workflows/server.yml index 311abf02af807..99feb28f2a545 100644 --- a/.github/workflows/server.yml +++ b/.github/workflows/server.yml @@ -92,12 +92,12 @@ jobs: if: ${{ matrix.sanitizer == 'THREAD' }} run: | cmake -B build \ - -DLLAMA_NATIVE=OFF \ + -DGGML_NATIVE=OFF \ -DLLAMA_BUILD_SERVER=ON \ -DLLAMA_CURL=ON \ -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \ -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON \ - -DLLAMA_OPENMP=OFF ; + -DGGML_OPENMP=OFF ; cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server - name: Build @@ -105,7 +105,7 @@ jobs: if: ${{ matrix.sanitizer != 'THREAD' }} run: | cmake -B build \ - -DLLAMA_NATIVE=OFF \ + -DGGML_NATIVE=OFF \ -DLLAMA_BUILD_SERVER=ON \ -DLLAMA_CURL=ON \ -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \ diff --git a/.gitignore b/.gitignore index a0c16e880b719..177e6a8dbb117 100644 --- a/.gitignore +++ b/.gitignore @@ -56,6 +56,7 @@ CMakeSettings.json compile_commands.json ggml-metal-embed.metal llama-batched-swift +/rpc-server out/ tmp/ diff --git a/.gitmodules b/.gitmodules index b7e8b8ff2f64e..5861d59cb785d 100644 --- a/.gitmodules +++ b/.gitmodules @@ -1,3 +1,3 @@ [submodule "kompute"] - path = kompute + path = ggml/src/kompute url = https://github.com/nomic-ai/kompute.git diff --git a/CMakeLists.txt b/CMakeLists.txt index 1acf4bb08ba17..18297834e9225 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -2,6 +2,9 @@ cmake_minimum_required(VERSION 3.14) # for add_link_options and implicit target project("llama.cpp" C CXX) include(CheckIncludeFileCXX) +#set(CMAKE_WARN_DEPRECATED YES) +set(CMAKE_WARN_UNUSED_CLI YES) + set(CMAKE_EXPORT_COMPILE_COMMANDS ON) if (NOT XCODE AND NOT MSVC AND NOT CMAKE_BUILD_TYPE) @@ -9,11 +12,16 @@ if (NOT XCODE AND NOT MSVC AND NOT CMAKE_BUILD_TYPE) set_property(CACHE CMAKE_BUILD_TYPE PROPERTY STRINGS "Debug" "Release" "MinSizeRel" "RelWithDebInfo") endif() +# Add path to modules +list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/cmake/") + set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin) if (CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR) set(LLAMA_STANDALONE ON) + include(git-vars) + # configure project version # TODO else() @@ -32,1289 +40,72 @@ else() endif() endif() +option(BUILD_SHARED_LIBS "build shared libraries" ${BUILD_SHARED_LIBS_DEFAULT}) # -# Option list +# option list # -if (APPLE) - set(LLAMA_METAL_DEFAULT ON) - set(LLAMA_BLAS_DEFAULT ON) - set(LLAMA_BLAS_VENDOR_DEFAULT "Apple") -else() - set(LLAMA_METAL_DEFAULT OFF) - set(LLAMA_BLAS_DEFAULT OFF) - set(LLAMA_BLAS_VENDOR_DEFAULT "Generic") -endif() - -set(LLAMA_LLAMAFILE_DEFAULT ON) - # general -option(BUILD_SHARED_LIBS "build shared libraries" OFF) -option(LLAMA_STATIC "llama: static link libraries" OFF) -option(LLAMA_NATIVE "llama: enable -march=native flag" ON) -option(LLAMA_LTO "llama: enable link time optimization" OFF) -option(LLAMA_CCACHE "llama: use ccache if available" ON) +option(LLAMA_CCACHE "llama: use ccache if available" ON) # debug -option(LLAMA_ALL_WARNINGS "llama: enable all compiler warnings" ON) -option(LLAMA_ALL_WARNINGS_3RD_PARTY "llama: enable all compiler warnings in 3rd party libs" OFF) -option(LLAMA_GPROF "llama: enable gprof" OFF) +option(LLAMA_ALL_WARNINGS "llama: enable all compiler warnings" ON) +option(LLAMA_ALL_WARNINGS_3RD_PARTY "llama: enable all compiler warnings in 3rd party libs" OFF) # build -option(LLAMA_FATAL_WARNINGS "llama: enable -Werror flag" OFF) +option(LLAMA_FATAL_WARNINGS "llama: enable -Werror flag" OFF) # sanitizers -option(LLAMA_SANITIZE_THREAD "llama: enable thread sanitizer" OFF) -option(LLAMA_SANITIZE_ADDRESS "llama: enable address sanitizer" OFF) -option(LLAMA_SANITIZE_UNDEFINED "llama: enable undefined sanitizer" OFF) - -# instruction set specific -if (LLAMA_NATIVE) - set(INS_ENB OFF) -else() - set(INS_ENB ON) -endif() +option(LLAMA_SANITIZE_THREAD "llama: enable thread sanitizer" OFF) +option(LLAMA_SANITIZE_ADDRESS "llama: enable address sanitizer" OFF) +option(LLAMA_SANITIZE_UNDEFINED "llama: enable undefined sanitizer" OFF) -option(LLAMA_SVE "llama: enable SVE" OFF) -option(LLAMA_AVX "llama: enable AVX" ${INS_ENB}) -option(LLAMA_AVX2 "llama: enable AVX2" ${INS_ENB}) -option(LLAMA_AVX512 "llama: enable AVX512" OFF) -option(LLAMA_AVX512_VBMI "llama: enable AVX512-VBMI" OFF) -option(LLAMA_AVX512_VNNI "llama: enable AVX512-VNNI" OFF) -option(LLAMA_AVX512_BF16 "llama: enable AVX512-BF16" OFF) -option(LLAMA_FMA "llama: enable FMA" ${INS_ENB}) -# in MSVC F16C is implied with AVX2/AVX512 -if (NOT MSVC) - option(LLAMA_F16C "llama: enable F16C" ${INS_ENB}) -endif() - -if (WIN32) - set(LLAMA_WIN_VER "0x602" CACHE STRING "llama: Windows Version") -endif() +# extra artifacts +option(LLAMA_BUILD_TESTS "llama: build tests" ${LLAMA_STANDALONE}) +option(LLAMA_BUILD_EXAMPLES "llama: build examples" ${LLAMA_STANDALONE}) +option(LLAMA_BUILD_SERVER "llama: build server example" ${LLAMA_STANDALONE}) # 3rd party libs -option(LLAMA_ACCELERATE "llama: enable Accelerate framework" ON) -option(LLAMA_BLAS "llama: use BLAS" ${LLAMA_BLAS_DEFAULT}) -set(LLAMA_BLAS_VENDOR ${LLAMA_BLAS_VENDOR_DEFAULT} CACHE STRING - "llama: BLAS library vendor") -option(LLAMA_LLAMAFILE "llama: use llamafile SGEMM" ${LLAMA_LLAMAFILE_DEFAULT}) -option(LLAMA_CUDA "llama: use CUDA" OFF) -option(LLAMA_CUBLAS "llama: use CUDA (deprecated, use LLAMA_CUDA)" OFF) -option(LLAMA_CUDA_FORCE_DMMV "llama: use dmmv instead of mmvq CUDA kernels" OFF) -option(LLAMA_CUDA_FORCE_MMQ "llama: always use mmq kernels instead of cuBLAS" OFF) -option(LLAMA_CUDA_FORCE_CUBLAS "llama: always use cuBLAS instead of mmq kernels" OFF) -set(LLAMA_CUDA_DMMV_X "32" CACHE STRING "llama: x stride for dmmv CUDA kernels") -set(LLAMA_CUDA_MMV_Y "1" CACHE STRING "llama: y block size for mmv CUDA kernels") -option(LLAMA_CUDA_F16 "llama: use 16 bit floats for some calculations" OFF) -set(LLAMA_CUDA_KQUANTS_ITER "2" CACHE STRING "llama: iters./thread per block for Q2_K/Q6_K") -set(LLAMA_CUDA_PEER_MAX_BATCH_SIZE "128" CACHE STRING - "llama: max. batch size for using peer access") -option(LLAMA_CUDA_NO_PEER_COPY "llama: do not use peer to peer copies" OFF) -option(LLAMA_CUDA_NO_VMM "llama: do not try to use CUDA VMM" OFF) -option(LLAMA_CUDA_FA_ALL_QUANTS "llama: compile all quants for FlashAttention" OFF) - -option(LLAMA_CURL "llama: use libcurl to download model from an URL" OFF) -option(LLAMA_HIPBLAS "llama: use hipBLAS" OFF) -option(LLAMA_HIP_UMA "llama: use HIP unified memory architecture" OFF) -option(LLAMA_VULKAN "llama: use Vulkan" OFF) -option(LLAMA_VULKAN_CHECK_RESULTS "llama: run Vulkan op checks" OFF) -option(LLAMA_VULKAN_DEBUG "llama: enable Vulkan debug output" OFF) -option(LLAMA_VULKAN_MEMORY_DEBUG "llama: enable Vulkan memory debug output" OFF) -option(LLAMA_VULKAN_VALIDATE "llama: enable Vulkan validation" OFF) -option(LLAMA_VULKAN_RUN_TESTS "llama: run Vulkan tests" OFF) -option(LLAMA_METAL "llama: use Metal" ${LLAMA_METAL_DEFAULT}) -option(LLAMA_METAL_NDEBUG "llama: disable Metal debugging" OFF) -option(LLAMA_METAL_SHADER_DEBUG "llama: compile Metal with -fno-fast-math" OFF) -option(LLAMA_METAL_EMBED_LIBRARY "llama: embed Metal library" OFF) -set(LLAMA_METAL_MACOSX_VERSION_MIN "" CACHE STRING - "llama: metal minimum macOS version") -set(LLAMA_METAL_STD "" CACHE STRING "llama: metal standard version (-std flag)") -option(LLAMA_KOMPUTE "llama: use Kompute" OFF) -option(LLAMA_RPC "llama: use RPC" OFF) -option(LLAMA_OPENMP "llama: use OpenMP" ON) -option(LLAMA_SYCL "llama: use SYCL" OFF) -option(LLAMA_SYCL_F16 "llama: use 16 bit floats for sycl calculations" OFF) -set(LLAMA_SYCL_TARGET "INTEL" CACHE STRING "llama: sycl target device") -option(LLAMA_CPU_HBM "llama: use memkind for CPU HBM" OFF) -set(LLAMA_SCHED_MAX_COPIES "4" CACHE STRING "llama: max input copies for pipeline parallelism") - -option(LLAMA_BUILD_TESTS "llama: build tests" ${LLAMA_STANDALONE}) -option(LLAMA_BUILD_EXAMPLES "llama: build examples" ${LLAMA_STANDALONE}) -option(LLAMA_BUILD_SERVER "llama: build server example" ON) -option(LLAMA_LASX "llama: enable lasx" ON) -option(LLAMA_LSX "llama: enable lsx" ON) +option(LLAMA_CURL "llama: use libcurl to download model from an URL" OFF) # Required for relocatable CMake package -include(${CMAKE_CURRENT_SOURCE_DIR}/scripts/build-info.cmake) - -# -# Compile flags -# - -if (LLAMA_SYCL) - set(CMAKE_CXX_STANDARD 17) -else() - set(CMAKE_CXX_STANDARD 11) -endif() - -set(CMAKE_CXX_STANDARD_REQUIRED true) -set(CMAKE_C_STANDARD 11) -set(CMAKE_C_STANDARD_REQUIRED true) -set(THREADS_PREFER_PTHREAD_FLAG ON) - -find_package(Threads REQUIRED) -include(CheckCXXCompilerFlag) - -add_compile_definitions(GGML_SCHED_MAX_COPIES=${LLAMA_SCHED_MAX_COPIES}) - -# enable libstdc++ assertions for debug builds -if (CMAKE_SYSTEM_NAME MATCHES "Linux") - add_compile_definitions($<$:_GLIBCXX_ASSERTIONS>) -endif() - -if (NOT MSVC) - if (LLAMA_SANITIZE_THREAD) - add_compile_options(-fsanitize=thread) - link_libraries (-fsanitize=thread) - endif() - - if (LLAMA_SANITIZE_ADDRESS) - add_compile_options(-fsanitize=address -fno-omit-frame-pointer) - link_libraries (-fsanitize=address) - endif() - - if (LLAMA_SANITIZE_UNDEFINED) - add_compile_options(-fsanitize=undefined) - link_libraries (-fsanitize=undefined) - endif() -endif() - -if (APPLE AND LLAMA_ACCELERATE) - find_library(ACCELERATE_FRAMEWORK Accelerate) - if (ACCELERATE_FRAMEWORK) - message(STATUS "Accelerate framework found") - - add_compile_definitions(GGML_USE_ACCELERATE) - add_compile_definitions(ACCELERATE_NEW_LAPACK) - add_compile_definitions(ACCELERATE_LAPACK_ILP64) - set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} ${ACCELERATE_FRAMEWORK}) - else() - message(WARNING "Accelerate framework not found") +include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info.cmake) + +# override ggml options +set(GGML_CCACHE ${LLAMA_CCACHE}) +set(GGML_SANITIZE_THREAD ${LLAMA_SANITIZE_THREAD}) +set(GGML_SANITIZE_ADDRESS ${LLAMA_SANITIZE_ADDRESS}) +set(GGML_SANITIZE_UNDEFINED ${LLAMA_SANITIZE_UNDEFINED}) +set(GGML_ALL_WARNINGS ${LLAMA_ALL_WARNINGS}) +set(GGML_FATAL_WARNINGS ${LLAMA_FATAL_WARNINGS}) +set(GGML_LLAMAFILE ON) + +# transition helpers +function (llama_option_depr TYPE OLD NEW) + if (${OLD}) + message(${TYPE} "${OLD} is deprecated and will be removed in the future.\nUse ${NEW} instead\n") + set(${NEW} ON) endif() -endif() - -if (LLAMA_METAL) - find_library(FOUNDATION_LIBRARY Foundation REQUIRED) - find_library(METAL_FRAMEWORK Metal REQUIRED) - find_library(METALKIT_FRAMEWORK MetalKit REQUIRED) - - message(STATUS "Metal framework found") - set(GGML_HEADERS_METAL ggml-metal.h) - set(GGML_SOURCES_METAL ggml-metal.m) - - add_compile_definitions(GGML_USE_METAL) - if (LLAMA_METAL_NDEBUG) - add_compile_definitions(GGML_METAL_NDEBUG) - endif() - - # copy ggml-common.h and ggml-metal.metal to bin directory - configure_file(ggml-common.h ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-common.h COPYONLY) - configure_file(ggml-metal.metal ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.metal COPYONLY) - - if (LLAMA_METAL_EMBED_LIBRARY) - enable_language(ASM) - add_compile_definitions(GGML_METAL_EMBED_LIBRARY) - - set(METALLIB_COMMON "${CMAKE_CURRENT_SOURCE_DIR}/ggml-common.h") - set(METALLIB_SOURCE "${CMAKE_CURRENT_SOURCE_DIR}/ggml-metal.metal") - - file(MAKE_DIRECTORY "${CMAKE_BINARY_DIR}/autogenerated") - - # merge ggml-common.h and ggml-metal.metal into a single file - set(METALLIB_EMBED_ASM "${CMAKE_BINARY_DIR}/autogenerated/ggml-metal-embed.s") - set(METALLIB_SOURCE_EMBED "${CMAKE_BINARY_DIR}/autogenerated/ggml-metal-embed.metal") - - add_custom_command( - OUTPUT ${METALLIB_EMBED_ASM} - COMMAND echo "Embedding Metal library" - COMMAND sed -e '/\#include \"ggml-common.h\"/r ${METALLIB_COMMON}' -e '/\#include \"ggml-common.h\"/d' < ${METALLIB_SOURCE} > ${METALLIB_SOURCE_EMBED} - COMMAND echo ".section __DATA,__ggml_metallib" > ${METALLIB_EMBED_ASM} - COMMAND echo ".globl _ggml_metallib_start" >> ${METALLIB_EMBED_ASM} - COMMAND echo "_ggml_metallib_start:" >> ${METALLIB_EMBED_ASM} - COMMAND echo ".incbin \\\"${METALLIB_SOURCE_EMBED}\\\"" >> ${METALLIB_EMBED_ASM} - COMMAND echo ".globl _ggml_metallib_end" >> ${METALLIB_EMBED_ASM} - COMMAND echo "_ggml_metallib_end:" >> ${METALLIB_EMBED_ASM} - DEPENDS ggml-metal.metal ggml-common.h - COMMENT "Generate assembly for embedded Metal library" - ) - - set(GGML_SOURCES_METAL ${GGML_SOURCES_METAL} ${METALLIB_EMBED_ASM}) - else() - if (LLAMA_METAL_SHADER_DEBUG) - # custom command to do the following: - # xcrun -sdk macosx metal -fno-fast-math -c ggml-metal.metal -o ggml-metal.air - # xcrun -sdk macosx metallib ggml-metal.air -o default.metallib - # - # note: this is the only way I found to disable fast-math in Metal. it's ugly, but at least it works - # disabling fast math is needed in order to pass tests/test-backend-ops - # note: adding -fno-inline fixes the tests when using MTL_SHADER_VALIDATION=1 - # note: unfortunately, we have to call it default.metallib instead of ggml.metallib - # ref: https://github.com/ggerganov/whisper.cpp/issues/1720 - set(XC_FLAGS -fno-fast-math -fno-inline -g) - else() - set(XC_FLAGS -O3) - endif() - - # Append macOS metal versioning flags - if (LLAMA_METAL_MACOSX_VERSION_MIN) - message(STATUS "Adding -mmacosx-version-min=${LLAMA_METAL_MACOSX_VERSION_MIN} flag to metal compilation") - list(APPEND XC_FLAGS -mmacosx-version-min=${LLAMA_METAL_MACOSX_VERSION_MIN}) - endif() - if (LLAMA_METAL_STD) - message(STATUS "Adding -std=${LLAMA_METAL_STD} flag to metal compilation") - list(APPEND XC_FLAGS -std=${LLAMA_METAL_STD}) - endif() - - add_custom_command( - OUTPUT ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib - COMMAND xcrun -sdk macosx metal ${XC_FLAGS} -c ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.metal -o ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.air - COMMAND xcrun -sdk macosx metallib ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.air -o ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib - COMMAND rm -f ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.air - COMMAND rm -f ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-common.h - COMMAND rm -f ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.metal - DEPENDS ggml-metal.metal ggml-common.h - COMMENT "Compiling Metal kernels" - ) - - add_custom_target( - ggml-metal ALL - DEPENDS ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib - ) - endif() # LLAMA_METAL_EMBED_LIBRARY - - set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} - ${FOUNDATION_LIBRARY} - ${METAL_FRAMEWORK} - ${METALKIT_FRAMEWORK} - ) -endif() - -if (LLAMA_OPENMP) - find_package(OpenMP) - if (OpenMP_FOUND) - message(STATUS "OpenMP found") - add_compile_definitions(GGML_USE_OPENMP) - set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} OpenMP::OpenMP_C OpenMP::OpenMP_CXX) - else() - message(WARNING "OpenMP not found") - endif() -endif() - -if (LLAMA_BLAS) - if (LLAMA_STATIC) - set(BLA_STATIC ON) - endif() - #if (CMAKE_VERSION VERSION_GREATER_EQUAL 3.22) - # set(BLA_SIZEOF_INTEGER 8) - #endif() - - set(BLA_VENDOR ${LLAMA_BLAS_VENDOR}) - find_package(BLAS) - - if (BLAS_FOUND) - message(STATUS "BLAS found, Libraries: ${BLAS_LIBRARIES}") - - if (("${BLAS_INCLUDE_DIRS}" STREQUAL "") AND NOT (${LLAMA_BLAS_VENDOR} MATCHES "Apple")) - # BLAS_INCLUDE_DIRS is missing in FindBLAS.cmake. - # see https://gitlab.kitware.com/cmake/cmake/-/issues/20268 - find_package(PkgConfig REQUIRED) - if (${LLAMA_BLAS_VENDOR} MATCHES "Generic") - pkg_check_modules(DepBLAS REQUIRED blas) - elseif (${LLAMA_BLAS_VENDOR} MATCHES "OpenBLAS") - # As of openblas v0.3.22, the 64-bit is named openblas64.pc - pkg_check_modules(DepBLAS openblas64) - if (NOT DepBLAS_FOUND) - pkg_check_modules(DepBLAS REQUIRED openblas) - endif() - elseif (${LLAMA_BLAS_VENDOR} MATCHES "FLAME") - pkg_check_modules(DepBLAS REQUIRED blis) - elseif (${LLAMA_BLAS_VENDOR} MATCHES "ATLAS") - pkg_check_modules(DepBLAS REQUIRED blas-atlas) - elseif (${LLAMA_BLAS_VENDOR} MATCHES "FlexiBLAS") - pkg_check_modules(DepBLAS REQUIRED flexiblas_api) - elseif (${LLAMA_BLAS_VENDOR} MATCHES "Intel") - # all Intel* libraries share the same include path - pkg_check_modules(DepBLAS REQUIRED mkl-sdl) - elseif (${LLAMA_BLAS_VENDOR} MATCHES "NVHPC") - # this doesn't provide pkg-config - # suggest to assign BLAS_INCLUDE_DIRS on your own - if ("${NVHPC_VERSION}" STREQUAL "") - message(WARNING "Better to set NVHPC_VERSION") - else() - set(DepBLAS_FOUND ON) - set(DepBLAS_INCLUDE_DIRS "/opt/nvidia/hpc_sdk/${CMAKE_SYSTEM_NAME}_${CMAKE_SYSTEM_PROCESSOR}/${NVHPC_VERSION}/math_libs/include") - endif() - endif() - if (DepBLAS_FOUND) - set(BLAS_INCLUDE_DIRS ${DepBLAS_INCLUDE_DIRS}) - else() - message(WARNING "BLAS_INCLUDE_DIRS neither been provided nor been automatically" - " detected by pkgconfig, trying to find cblas.h from possible paths...") - find_path(BLAS_INCLUDE_DIRS - NAMES cblas.h - HINTS - /usr/include - /usr/local/include - /usr/include/openblas - /opt/homebrew/opt/openblas/include - /usr/local/opt/openblas/include - /usr/include/x86_64-linux-gnu/openblas/include - ) - endif() - endif() - - message(STATUS "BLAS found, Includes: ${BLAS_INCLUDE_DIRS}") - - add_compile_options(${BLAS_LINKER_FLAGS}) - - add_compile_definitions(GGML_USE_BLAS) - - if (${BLAS_INCLUDE_DIRS} MATCHES "mkl" AND (${LLAMA_BLAS_VENDOR} MATCHES "Generic" OR ${LLAMA_BLAS_VENDOR} MATCHES "Intel")) - add_compile_definitions(GGML_BLAS_USE_MKL) - endif() - - set(GGML_HEADERS_BLAS ggml-blas.h) - set(GGML_SOURCES_BLAS ggml-blas.cpp) - - set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} ${BLAS_LIBRARIES}) - set(LLAMA_EXTRA_INCLUDES ${LLAMA_EXTRA_INCLUDES} ${BLAS_INCLUDE_DIRS}) - else() - message(WARNING "BLAS not found, please refer to " - "https://cmake.org/cmake/help/latest/module/FindBLAS.html#blas-lapack-vendors" - " to set correct LLAMA_BLAS_VENDOR") - endif() -endif() - -if (LLAMA_LLAMAFILE) - add_compile_definitions(GGML_USE_LLAMAFILE) - - set(GGML_HEADERS_LLAMAFILE sgemm.h) - set(GGML_SOURCES_LLAMAFILE sgemm.cpp) -endif() - -if (LLAMA_CUBLAS) - message(WARNING "LLAMA_CUBLAS is deprecated and will be removed in the future.\nUse LLAMA_CUDA instead") - set(LLAMA_CUDA ON) -endif() - -if (LLAMA_CUDA) - cmake_minimum_required(VERSION 3.18) # for CMAKE_CUDA_ARCHITECTURES - - find_package(CUDAToolkit) - if (CUDAToolkit_FOUND) - message(STATUS "CUDA found") - - if (NOT DEFINED CMAKE_CUDA_ARCHITECTURES) - # 52 == lowest CUDA 12 standard - # 60 == FP16 CUDA intrinsics - # 61 == integer CUDA intrinsics - # 70 == FP16 tensor cores - # 75 == int8 tensor cores - if (LLAMA_CUDA_F16 OR LLAMA_CUDA_DMMV_F16) - set(CMAKE_CUDA_ARCHITECTURES "60;61;70;75") - else() - set(CMAKE_CUDA_ARCHITECTURES "52;61;70;75") - #set(CMAKE_CUDA_ARCHITECTURES "OFF") # use this to compile much faster, but only F16 models work - endif() - endif() - message(STATUS "Using CUDA architectures: ${CMAKE_CUDA_ARCHITECTURES}") - - enable_language(CUDA) - - set(GGML_HEADERS_CUDA ggml-cuda.h) - - file(GLOB GGML_SOURCES_CUDA "ggml-cuda/*.cu") - list(APPEND GGML_SOURCES_CUDA "ggml-cuda.cu") - file(GLOB SRCS "ggml-cuda/template-instances/fattn-wmma*.cu") - list(APPEND GGML_SOURCES_CUDA ${SRCS}) - file(GLOB SRCS "ggml-cuda/template-instances/mmq*.cu") - list(APPEND GGML_SOURCES_CUDA ${SRCS}) - - add_compile_definitions(GGML_USE_CUDA) - add_compile_definitions(GGML_CUDA_USE_GRAPHS) - if (LLAMA_CUDA_FORCE_DMMV) - add_compile_definitions(GGML_CUDA_FORCE_DMMV) - endif() - if (LLAMA_CUDA_FORCE_MMQ) - add_compile_definitions(GGML_CUDA_FORCE_MMQ) - endif() - if (LLAMA_CUDA_FORCE_CUBLAS) - add_compile_definitions(GGML_CUDA_FORCE_CUBLAS) - endif() - if (LLAMA_CUDA_NO_VMM) - add_compile_definitions(GGML_CUDA_NO_VMM) - endif() - add_compile_definitions(GGML_CUDA_DMMV_X=${LLAMA_CUDA_DMMV_X}) - add_compile_definitions(GGML_CUDA_MMV_Y=${LLAMA_CUDA_MMV_Y}) - if (DEFINED LLAMA_CUDA_DMMV_Y) - add_compile_definitions(GGML_CUDA_MMV_Y=${LLAMA_CUDA_DMMV_Y}) # for backwards compatibility - endif() - if (LLAMA_CUDA_F16 OR LLAMA_CUDA_DMMV_F16) - add_compile_definitions(GGML_CUDA_F16) - endif() - add_compile_definitions(K_QUANTS_PER_ITERATION=${LLAMA_CUDA_KQUANTS_ITER}) - add_compile_definitions(GGML_CUDA_PEER_MAX_BATCH_SIZE=${LLAMA_CUDA_PEER_MAX_BATCH_SIZE}) - if (LLAMA_CUDA_NO_PEER_COPY) - add_compile_definitions(GGML_CUDA_NO_PEER_COPY) - endif() - if (LLAMA_CUDA_FA_ALL_QUANTS) - file(GLOB SRCS "ggml-cuda/template-instances/fattn-vec*.cu") - list(APPEND GGML_SOURCES_CUDA ${SRCS}) - add_compile_definitions(GGML_CUDA_FA_ALL_QUANTS) - else() - file(GLOB SRCS "ggml-cuda/template-instances/fattn-vec*q4_0-q4_0.cu") - list(APPEND GGML_SOURCES_CUDA ${SRCS}) - file(GLOB SRCS "ggml-cuda/template-instances/fattn-vec*q8_0-q8_0.cu") - list(APPEND GGML_SOURCES_CUDA ${SRCS}) - file(GLOB SRCS "ggml-cuda/template-instances/fattn-vec*f16-f16.cu") - list(APPEND GGML_SOURCES_CUDA ${SRCS}) - endif() - - if (LLAMA_STATIC) - if (WIN32) - # As of 12.3.1 CUDA Toolkit for Windows does not offer a static cublas library - set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} CUDA::cudart_static CUDA::cublas CUDA::cublasLt) - else () - set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} CUDA::cudart_static CUDA::cublas_static CUDA::cublasLt_static) - endif() - else() - set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} CUDA::cudart CUDA::cublas CUDA::cublasLt) - endif() - - if (LLAMA_CUDA_NO_VMM) - # No VMM requested, no need to link directly with the cuda driver lib (libcuda.so) - else() - set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} CUDA::cuda_driver) # required by cuDeviceGetAttribute(), cuMemGetAllocationGranularity(...), ... - endif() - else() - message(WARNING "CUDA not found") - endif() -endif() - -if (LLAMA_RPC) - add_compile_definitions(GGML_USE_RPC) - - if (WIN32) - set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} ws2_32) - endif() - - set(GGML_HEADERS_RPC ggml-rpc.h) - set(GGML_SOURCES_RPC ggml-rpc.cpp) -endif() - -if (LLAMA_VULKAN) - find_package(Vulkan) - if (Vulkan_FOUND) - message(STATUS "Vulkan found") - - set(GGML_HEADERS_VULKAN ggml-vulkan.h) - set(GGML_SOURCES_VULKAN ggml-vulkan.cpp) - - add_compile_definitions(GGML_USE_VULKAN) - - # Workaround to the "can't dereference invalidated vector iterator" bug in clang-cl debug build - # Posssibly relevant: https://stackoverflow.com/questions/74748276/visual-studio-no-displays-the-correct-length-of-stdvector - if (MSVC AND CMAKE_CXX_COMPILER_ID STREQUAL "Clang") - add_compile_definitions(_ITERATOR_DEBUG_LEVEL=0) - endif() - - if (LLAMA_VULKAN_CHECK_RESULTS) - add_compile_definitions(GGML_VULKAN_CHECK_RESULTS) - endif() - - if (LLAMA_VULKAN_DEBUG) - add_compile_definitions(GGML_VULKAN_DEBUG) - endif() - - if (LLAMA_VULKAN_MEMORY_DEBUG) - add_compile_definitions(GGML_VULKAN_MEMORY_DEBUG) - endif() - - if (LLAMA_VULKAN_VALIDATE) - add_compile_definitions(GGML_VULKAN_VALIDATE) - endif() - - if (LLAMA_VULKAN_RUN_TESTS) - add_compile_definitions(GGML_VULKAN_RUN_TESTS) - endif() - - set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} Vulkan::Vulkan) - else() - message(WARNING "Vulkan not found") - endif() -endif() - -if (LLAMA_HIPBLAS) - if (NOT EXISTS $ENV{ROCM_PATH}) - if (NOT EXISTS /opt/rocm) - set(ROCM_PATH /usr) - else() - set(ROCM_PATH /opt/rocm) - endif() - else() - set(ROCM_PATH $ENV{ROCM_PATH}) - endif() - list(APPEND CMAKE_PREFIX_PATH ${ROCM_PATH}) - list(APPEND CMAKE_PREFIX_PATH "${ROCM_PATH}/lib64/cmake") - - # CMake on Windows doesn't support the HIP language yet - if(WIN32) - set(CXX_IS_HIPCC TRUE) - else() - string(REGEX MATCH "hipcc(\.bat)?$" CXX_IS_HIPCC "${CMAKE_CXX_COMPILER}") - endif() - - if(CXX_IS_HIPCC) - if(LINUX) - if (NOT ${CMAKE_CXX_COMPILER_ID} MATCHES "Clang") - message(WARNING "Only LLVM is supported for HIP, hint: CXX=/opt/rocm/llvm/bin/clang++") - endif() - - message(WARNING "Setting hipcc as the C++ compiler is legacy behavior." - " Prefer setting the HIP compiler directly. See README for details.") - endif() - else() - # Forward AMDGPU_TARGETS to CMAKE_HIP_ARCHITECTURES. - if(AMDGPU_TARGETS AND NOT CMAKE_HIP_ARCHITECTURES) - set(CMAKE_HIP_ARCHITECTURES ${AMDGPU_TARGETS}) - endif() - cmake_minimum_required(VERSION 3.21) - enable_language(HIP) - endif() - find_package(hip REQUIRED) - find_package(hipblas REQUIRED) - find_package(rocblas REQUIRED) - - message(STATUS "HIP and hipBLAS found") - - set(GGML_HEADERS_ROCM ggml-cuda.h) - - file(GLOB GGML_SOURCES_ROCM "ggml-cuda/*.cu") - list(APPEND GGML_SOURCES_ROCM "ggml-cuda.cu") - file(GLOB SRCS "ggml-cuda/template-instances/fattn-wmma*.cu") - list(APPEND GGML_SOURCES_ROCM ${SRCS}) - file(GLOB SRCS "ggml-cuda/template-instances/mmq*.cu") - list(APPEND GGML_SOURCES_ROCM ${SRCS}) - - add_compile_definitions(GGML_USE_HIPBLAS GGML_USE_CUDA) - - if (LLAMA_HIP_UMA) - add_compile_definitions(GGML_HIP_UMA) - endif() - - if (LLAMA_CUDA_FORCE_DMMV) - add_compile_definitions(GGML_CUDA_FORCE_DMMV) - endif() - - if (LLAMA_CUDA_FORCE_MMQ) - add_compile_definitions(GGML_CUDA_FORCE_MMQ) - endif() - - if (LLAMA_CUDA_NO_PEER_COPY) - add_compile_definitions(GGML_CUDA_NO_PEER_COPY) - endif() - - if (LLAMA_CUDA_FA_ALL_QUANTS) - file(GLOB SRCS "ggml-cuda/template-instances/fattn-vec*.cu") - list(APPEND GGML_SOURCES_ROCM ${SRCS}) - add_compile_definitions(GGML_CUDA_FA_ALL_QUANTS) - else() - file(GLOB SRCS "ggml-cuda/template-instances/fattn-vec*q4_0-q4_0.cu") - list(APPEND GGML_SOURCES_ROCM ${SRCS}) - file(GLOB SRCS "ggml-cuda/template-instances/fattn-vec*q8_0-q8_0.cu") - list(APPEND GGML_SOURCES_ROCM ${SRCS}) - file(GLOB SRCS "ggml-cuda/template-instances/fattn-vec*f16-f16.cu") - list(APPEND GGML_SOURCES_ROCM ${SRCS}) - endif() - - add_compile_definitions(GGML_CUDA_DMMV_X=${LLAMA_CUDA_DMMV_X}) - add_compile_definitions(GGML_CUDA_MMV_Y=${LLAMA_CUDA_MMV_Y}) - add_compile_definitions(K_QUANTS_PER_ITERATION=${LLAMA_CUDA_KQUANTS_ITER}) - - if (CXX_IS_HIPCC) - set_source_files_properties(${GGML_SOURCES_ROCM} PROPERTIES LANGUAGE CXX) - set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} hip::device) - else() - set_source_files_properties(${GGML_SOURCES_ROCM} PROPERTIES LANGUAGE HIP) - endif() - - if (LLAMA_STATIC) - message(FATAL_ERROR "Static linking not supported for HIP/ROCm") - endif() - - set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} PUBLIC hip::host roc::rocblas roc::hipblas) -endif() - -if (LLAMA_SYCL) - if (NOT LLAMA_SYCL_TARGET MATCHES "^(INTEL|NVIDIA)$") - message(FATAL_ERROR "Invalid backend chosen, supported options are INTEL or NVIDIA") - endif() - - if ( NOT DEFINED ENV{ONEAPI_ROOT}) - message(FATAL_ERROR "Not detect ENV {ONEAPI_ROOT}, please install oneAPI & source it, like: source /opt/intel/oneapi/setvars.sh") - endif() - #todo: AOT - - find_package(IntelSYCL REQUIRED) - find_package(MKL REQUIRED) - - message(STATUS "SYCL found") - - add_compile_definitions(GGML_USE_SYCL) - - if (LLAMA_SYCL_F16) - add_compile_definitions(GGML_SYCL_F16) - endif() - - if (LLAMA_CUDA_FORCE_MMQ) - add_compile_definitions(GGML_SYCL_FORCE_MMQ) - endif() - - add_compile_options(-I./) #include DPCT - - set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-narrowing") - set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O3") - if (LLAMA_SYCL_TARGET STREQUAL "NVIDIA") - set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fsycl-targets=nvptx64-nvidia-cuda") - endif() - - set(GGML_HEADERS_SYCL ggml-sycl.h) - file(GLOB GGML_SOURCES_SYCL "ggml-sycl/*.cpp") - list(APPEND GGML_SOURCES_SYCL "ggml-sycl.cpp") - - if (WIN32) - set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} IntelSYCL::SYCL_CXX MKL::MKL MKL::MKL_SYCL) - else() - add_compile_options(-I/${SYCL_INCLUDE_DIR}) - set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fsycl -L${MKLROOT}/lib") - if (LLAMA_SYCL_TARGET STREQUAL "INTEL") - set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} -fsycl OpenCL mkl_core pthread m dl mkl_sycl_blas mkl_intel_ilp64 mkl_tbb_thread) - elseif (LLAMA_SYCL_TARGET STREQUAL "NVIDIA") - set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} -fsycl pthread m dl onemkl) - endif() - endif() -endif() - -if (LLAMA_KOMPUTE) - add_compile_definitions(VULKAN_HPP_DISPATCH_LOADER_DYNAMIC=1) - find_package(Vulkan COMPONENTS glslc REQUIRED) - find_program(glslc_executable NAMES glslc HINTS Vulkan::glslc) - if (NOT glslc_executable) - message(FATAL_ERROR "glslc not found") - endif() - - function(compile_shader) - set(options) - set(oneValueArgs) - set(multiValueArgs SOURCES) - cmake_parse_arguments(compile_shader "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN}) - foreach(source ${compile_shader_SOURCES}) - get_filename_component(filename ${source} NAME) - set(spv_file ${filename}.spv) - add_custom_command( - OUTPUT ${spv_file} - DEPENDS ${CMAKE_CURRENT_SOURCE_DIR}/${source} - ${CMAKE_CURRENT_SOURCE_DIR}/kompute-shaders/common.comp - ${CMAKE_CURRENT_SOURCE_DIR}/kompute-shaders/op_getrows.comp - ${CMAKE_CURRENT_SOURCE_DIR}/kompute-shaders/op_mul_mv_q_n_pre.comp - ${CMAKE_CURRENT_SOURCE_DIR}/kompute-shaders/op_mul_mv_q_n.comp - COMMAND ${glslc_executable} --target-env=vulkan1.2 -o ${spv_file} ${CMAKE_CURRENT_SOURCE_DIR}/${source} - COMMENT "Compiling ${source} to ${spv_file}" - ) - - get_filename_component(RAW_FILE_NAME ${spv_file} NAME) - set(FILE_NAME "shader${RAW_FILE_NAME}") - string(REPLACE ".comp.spv" ".h" HEADER_FILE ${FILE_NAME}) - string(TOUPPER ${HEADER_FILE} HEADER_FILE_DEFINE) - string(REPLACE "." "_" HEADER_FILE_DEFINE "${HEADER_FILE_DEFINE}") - set(OUTPUT_HEADER_FILE "${HEADER_FILE}") - message(STATUS "${HEADER_FILE} generating ${HEADER_FILE_DEFINE}") - if(CMAKE_GENERATOR MATCHES "Visual Studio") - add_custom_command( - OUTPUT ${OUTPUT_HEADER_FILE} - COMMAND ${CMAKE_COMMAND} -E echo "/*THIS FILE HAS BEEN AUTOMATICALLY GENERATED - DO NOT EDIT*/" > ${OUTPUT_HEADER_FILE} - COMMAND ${CMAKE_COMMAND} -E echo \"\#ifndef ${HEADER_FILE_DEFINE}\" >> ${OUTPUT_HEADER_FILE} - COMMAND ${CMAKE_COMMAND} -E echo \"\#define ${HEADER_FILE_DEFINE}\" >> ${OUTPUT_HEADER_FILE} - COMMAND ${CMAKE_COMMAND} -E echo "namespace kp {" >> ${OUTPUT_HEADER_FILE} - COMMAND ${CMAKE_COMMAND} -E echo "namespace shader_data {" >> ${OUTPUT_HEADER_FILE} - COMMAND ${CMAKE_BINARY_DIR}/bin/$/xxd -i ${RAW_FILE_NAME} >> ${OUTPUT_HEADER_FILE} - COMMAND ${CMAKE_COMMAND} -E echo "}}" >> ${OUTPUT_HEADER_FILE} - COMMAND ${CMAKE_COMMAND} -E echo \"\#endif // define ${HEADER_FILE_DEFINE}\" >> ${OUTPUT_HEADER_FILE} - DEPENDS ${spv_file} xxd - COMMENT "Converting to hpp: ${FILE_NAME} ${CMAKE_BINARY_DIR}/bin/$/xxd" - ) - else() - add_custom_command( - OUTPUT ${OUTPUT_HEADER_FILE} - COMMAND ${CMAKE_COMMAND} -E echo "/*THIS FILE HAS BEEN AUTOMATICALLY GENERATED - DO NOT EDIT*/" > ${OUTPUT_HEADER_FILE} - COMMAND ${CMAKE_COMMAND} -E echo \"\#ifndef ${HEADER_FILE_DEFINE}\" >> ${OUTPUT_HEADER_FILE} - COMMAND ${CMAKE_COMMAND} -E echo \"\#define ${HEADER_FILE_DEFINE}\" >> ${OUTPUT_HEADER_FILE} - COMMAND ${CMAKE_COMMAND} -E echo "namespace kp {" >> ${OUTPUT_HEADER_FILE} - COMMAND ${CMAKE_COMMAND} -E echo "namespace shader_data {" >> ${OUTPUT_HEADER_FILE} - COMMAND ${CMAKE_BINARY_DIR}/bin/xxd -i ${RAW_FILE_NAME} >> ${OUTPUT_HEADER_FILE} - COMMAND ${CMAKE_COMMAND} -E echo "}}" >> ${OUTPUT_HEADER_FILE} - COMMAND ${CMAKE_COMMAND} -E echo \"\#endif // define ${HEADER_FILE_DEFINE}\" >> ${OUTPUT_HEADER_FILE} - DEPENDS ${spv_file} xxd - COMMENT "Converting to hpp: ${FILE_NAME} ${CMAKE_BINARY_DIR}/bin/xxd" - ) - endif() - endforeach() - endfunction() - - if (EXISTS "${CMAKE_CURRENT_SOURCE_DIR}/kompute/CMakeLists.txt") - message(STATUS "Kompute found") - set(KOMPUTE_OPT_LOG_LEVEL Error CACHE STRING "Kompute log level") - add_subdirectory(kompute) - - # Compile our shaders - compile_shader(SOURCES - kompute-shaders/op_scale.comp - kompute-shaders/op_scale_8.comp - kompute-shaders/op_add.comp - kompute-shaders/op_addrow.comp - kompute-shaders/op_mul.comp - kompute-shaders/op_silu.comp - kompute-shaders/op_relu.comp - kompute-shaders/op_gelu.comp - kompute-shaders/op_softmax.comp - kompute-shaders/op_norm.comp - kompute-shaders/op_rmsnorm.comp - kompute-shaders/op_diagmask.comp - kompute-shaders/op_mul_mat_mat_f32.comp - kompute-shaders/op_mul_mat_f16.comp - kompute-shaders/op_mul_mat_q8_0.comp - kompute-shaders/op_mul_mat_q4_0.comp - kompute-shaders/op_mul_mat_q4_1.comp - kompute-shaders/op_mul_mat_q6_k.comp - kompute-shaders/op_getrows_f32.comp - kompute-shaders/op_getrows_f16.comp - kompute-shaders/op_getrows_q4_0.comp - kompute-shaders/op_getrows_q4_1.comp - kompute-shaders/op_getrows_q6_k.comp - kompute-shaders/op_rope_f16.comp - kompute-shaders/op_rope_f32.comp - kompute-shaders/op_cpy_f16_f16.comp - kompute-shaders/op_cpy_f16_f32.comp - kompute-shaders/op_cpy_f32_f16.comp - kompute-shaders/op_cpy_f32_f32.comp - ) - - # Create a custom target for our generated shaders - add_custom_target(generated_shaders DEPENDS - shaderop_scale.h - shaderop_scale_8.h - shaderop_add.h - shaderop_addrow.h - shaderop_mul.h - shaderop_silu.h - shaderop_relu.h - shaderop_gelu.h - shaderop_softmax.h - shaderop_norm.h - shaderop_rmsnorm.h - shaderop_diagmask.h - shaderop_mul_mat_mat_f32.h - shaderop_mul_mat_f16.h - shaderop_mul_mat_q8_0.h - shaderop_mul_mat_q4_0.h - shaderop_mul_mat_q4_1.h - shaderop_mul_mat_q6_k.h - shaderop_getrows_f32.h - shaderop_getrows_f16.h - shaderop_getrows_q4_0.h - shaderop_getrows_q4_1.h - shaderop_getrows_q6_k.h - shaderop_rope_f16.h - shaderop_rope_f32.h - shaderop_cpy_f16_f16.h - shaderop_cpy_f16_f32.h - shaderop_cpy_f32_f16.h - shaderop_cpy_f32_f32.h - ) - - # Create a custom command that depends on the generated_shaders - add_custom_command( - OUTPUT ${CMAKE_CURRENT_BINARY_DIR}/ggml-kompute.stamp - COMMAND ${CMAKE_COMMAND} -E touch ${CMAKE_CURRENT_BINARY_DIR}/ggml-kompute.stamp - DEPENDS generated_shaders - COMMENT "Ensuring shaders are generated before compiling ggml-kompute.cpp" - ) - - # Add the stamp to the main sources to ensure dependency tracking - set(GGML_SOURCES_KOMPUTE ggml-kompute.cpp ${CMAKE_CURRENT_BINARY_DIR}/ggml-kompute.stamp) - set(GGML_HEADERS_KOMPUTE ggml-kompute.h ${CMAKE_CURRENT_BINARY_DIR}/ggml-kompute.stamp) - - add_compile_definitions(GGML_USE_KOMPUTE) - - set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} kompute) - set(LLAMA_EXTRA_INCLUDES ${LLAMA_EXTRA_INCLUDES} ${CMAKE_BINARY_DIR}) - else() - message(WARNING "Kompute not found") - endif() -endif() - -if (LLAMA_CPU_HBM) - find_library(memkind memkind REQUIRED) - - add_compile_definitions(GGML_USE_CPU_HBM) - - target_link_libraries(ggml PUBLIC memkind) -endif() - -function(get_flags CCID CCVER) - set(C_FLAGS "") - set(CXX_FLAGS "") - - if (CCID MATCHES "Clang") - set(C_FLAGS -Wunreachable-code-break -Wunreachable-code-return) - set(CXX_FLAGS -Wunreachable-code-break -Wunreachable-code-return -Wmissing-prototypes -Wextra-semi) - - if ( - (CCID STREQUAL "Clang" AND CCVER VERSION_GREATER_EQUAL 3.8.0) OR - (CCID STREQUAL "AppleClang" AND CCVER VERSION_GREATER_EQUAL 7.3.0) - ) - list(APPEND C_FLAGS -Wdouble-promotion) - endif() - elseif (CCID STREQUAL "GNU") - set(C_FLAGS -Wdouble-promotion) - set(CXX_FLAGS -Wno-array-bounds) - - if (CCVER VERSION_GREATER_EQUAL 7.1.0) - list(APPEND CXX_FLAGS -Wno-format-truncation) - endif() - if (CCVER VERSION_GREATER_EQUAL 8.1.0) - list(APPEND CXX_FLAGS -Wextra-semi) - endif() - endif() - - set(GF_C_FLAGS ${C_FLAGS} PARENT_SCOPE) - set(GF_CXX_FLAGS ${CXX_FLAGS} PARENT_SCOPE) endfunction() -if (LLAMA_FATAL_WARNINGS) - if (CMAKE_CXX_COMPILER_ID MATCHES "GNU" OR CMAKE_CXX_COMPILER_ID MATCHES "Clang") - list(APPEND C_FLAGS -Werror) - 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set(NVCC_CMD ${CMAKE_CUDA_COMPILER} .c) - if (NOT CMAKE_CUDA_HOST_COMPILER STREQUAL "") - list(APPEND NVCC_CMD -ccbin ${CMAKE_CUDA_HOST_COMPILER}) - endif() - - execute_process( - COMMAND ${NVCC_CMD} -Xcompiler --version - OUTPUT_VARIABLE CUDA_CCFULLVER - ERROR_QUIET - ) - - if (NOT CUDA_CCFULLVER MATCHES clang) - set(CUDA_CCID "GNU") - execute_process( - COMMAND ${NVCC_CMD} -Xcompiler "-dumpfullversion -dumpversion" - OUTPUT_VARIABLE CUDA_CCVER - ERROR_QUIET - ) - else() - if (CUDA_CCFULLVER MATCHES Apple) - set(CUDA_CCID "AppleClang") - else() - set(CUDA_CCID "Clang") - endif() - string(REGEX REPLACE "^.* version ([0-9.]*).*$" "\\1" CUDA_CCVER ${CUDA_CCFULLVER}) - endif() - - message("-- CUDA host compiler is ${CUDA_CCID} ${CUDA_CCVER}") - - get_flags(${CUDA_CCID} ${CUDA_CCVER}) - list(APPEND CUDA_CXX_FLAGS ${CXX_FLAGS} ${GF_CXX_FLAGS}) # This is passed to -Xcompiler later - endif() - - if (NOT MSVC) - list(APPEND CUDA_CXX_FLAGS -Wno-pedantic) - endif() -endif() - -if (WIN32) - add_compile_definitions(_CRT_SECURE_NO_WARNINGS) - - if (BUILD_SHARED_LIBS) - set(CMAKE_WINDOWS_EXPORT_ALL_SYMBOLS ON) - endif() -endif() - -if (LLAMA_LTO) - include(CheckIPOSupported) - check_ipo_supported(RESULT result OUTPUT output) - if (result) - set(CMAKE_INTERPROCEDURAL_OPTIMIZATION TRUE) - else() - message(WARNING "IPO is not supported: ${output}") - endif() -endif() - -if (LLAMA_CCACHE) - find_program(LLAMA_CCACHE_FOUND ccache) - if (LLAMA_CCACHE_FOUND) - set_property(GLOBAL PROPERTY RULE_LAUNCH_COMPILE ccache) - set(ENV{CCACHE_SLOPPINESS} time_macros) - message(STATUS "ccache found, compilation results will be cached. Disable with LLAMA_CCACHE=OFF.") - else() - message(STATUS "Warning: ccache not found - consider installing it for faster compilation or disable this warning with LLAMA_CCACHE=OFF") - endif () -endif() - -# this version of Apple ld64 is buggy -execute_process( - COMMAND ${CMAKE_C_COMPILER} ${CMAKE_EXE_LINKER_FLAGS} -Wl,-v - ERROR_VARIABLE output - OUTPUT_QUIET -) - -if (output MATCHES "dyld-1015\.7") - add_compile_definitions(HAVE_BUGGY_APPLE_LINKER) -endif() - -# Architecture specific -# TODO: probably these flags need to be tweaked on some architectures -# feel free to update the Makefile for your architecture and send a pull request or issue -message(STATUS "CMAKE_SYSTEM_PROCESSOR: ${CMAKE_SYSTEM_PROCESSOR}") -if (MSVC) - string(TOLOWER "${CMAKE_GENERATOR_PLATFORM}" CMAKE_GENERATOR_PLATFORM_LWR) - message(STATUS "CMAKE_GENERATOR_PLATFORM: ${CMAKE_GENERATOR_PLATFORM}") -else () - set(CMAKE_GENERATOR_PLATFORM_LWR "") -endif () - -if (NOT MSVC) - if (LLAMA_STATIC) - add_link_options(-static) - if (MINGW) - add_link_options(-static-libgcc -static-libstdc++) - endif() - endif() - if (LLAMA_GPROF) - add_compile_options(-pg) - endif() -endif() - -set(ARCH_FLAGS "") - -if (CMAKE_OSX_ARCHITECTURES STREQUAL "arm64" OR CMAKE_GENERATOR_PLATFORM_LWR STREQUAL "arm64" OR - (NOT CMAKE_OSX_ARCHITECTURES AND NOT CMAKE_GENERATOR_PLATFORM_LWR AND - CMAKE_SYSTEM_PROCESSOR MATCHES "^(aarch64|arm.*|ARM64)$")) - message(STATUS "ARM detected") - if (MSVC) - add_compile_definitions(__aarch64__) # MSVC defines _M_ARM64 instead - add_compile_definitions(__ARM_NEON) - add_compile_definitions(__ARM_FEATURE_FMA) - - set(CMAKE_REQUIRED_FLAGS_PREV ${CMAKE_REQUIRED_FLAGS}) - string(JOIN " " CMAKE_REQUIRED_FLAGS ${CMAKE_REQUIRED_FLAGS} "/arch:armv8.2") - check_cxx_source_compiles("#include \nint main() { int8x16_t _a, _b; int32x4_t _s = vdotq_s32(_s, _a, _b); return 0; }" GGML_COMPILER_SUPPORT_DOTPROD) - if (GGML_COMPILER_SUPPORT_DOTPROD) - add_compile_definitions(__ARM_FEATURE_DOTPROD) - endif () - check_cxx_source_compiles("#include \nint main() { int8x16_t _a, _b; int32x4_t _s = vmlaq_f32(_s, _a, _b); return 0; }" GGML_COMPILER_SUPPORT_MATMUL_INT8) - if (GGML_COMPILER_SUPPORT_MATMUL_INT8) - add_compile_definitions(__ARM_FEATURE_MATMUL_INT8) - endif () - - check_cxx_source_compiles("#include \nint main() { float16_t _a; float16x8_t _s = vdupq_n_f16(_a); return 0; }" GGML_COMPILER_SUPPORT_FP16_VECTOR_ARITHMETIC) - if (GGML_COMPILER_SUPPORT_FP16_VECTOR_ARITHMETIC) - add_compile_definitions(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) - endif () - set(CMAKE_REQUIRED_FLAGS ${CMAKE_REQUIRED_FLAGS_PREV}) - else() - check_cxx_compiler_flag(-mfp16-format=ieee COMPILER_SUPPORTS_FP16_FORMAT_I3E) - if (NOT "${COMPILER_SUPPORTS_FP16_FORMAT_I3E}" STREQUAL "") - list(APPEND ARCH_FLAGS -mfp16-format=ieee) - endif() - if (${CMAKE_SYSTEM_PROCESSOR} MATCHES "armv6") - # Raspberry Pi 1, Zero - list(APPEND ARCH_FLAGS -mfpu=neon-fp-armv8 -mno-unaligned-access) - endif() - if (${CMAKE_SYSTEM_PROCESSOR} MATCHES "armv7") - if ("${CMAKE_SYSTEM_NAME}" STREQUAL "Android") - # Android armeabi-v7a - list(APPEND ARCH_FLAGS -mfpu=neon-vfpv4 -mno-unaligned-access -funsafe-math-optimizations) - else() - # Raspberry Pi 2 - list(APPEND ARCH_FLAGS -mfpu=neon-fp-armv8 -mno-unaligned-access -funsafe-math-optimizations) - endif() - endif() - if (${CMAKE_SYSTEM_PROCESSOR} MATCHES "armv8") - # Android arm64-v8a - # Raspberry Pi 3, 4, Zero 2 (32-bit) - list(APPEND ARCH_FLAGS -mno-unaligned-access) - endif() - if (LLAMA_SVE) - list(APPEND ARCH_FLAGS -march=armv8.6-a+sve) - endif() - endif() -elseif (CMAKE_OSX_ARCHITECTURES STREQUAL "x86_64" OR CMAKE_GENERATOR_PLATFORM_LWR MATCHES "^(x86_64|i686|amd64|x64|win32)$" OR - (NOT CMAKE_OSX_ARCHITECTURES AND NOT CMAKE_GENERATOR_PLATFORM_LWR AND - CMAKE_SYSTEM_PROCESSOR MATCHES "^(x86_64|i686|AMD64)$")) - message(STATUS "x86 detected") - if (MSVC) - # instruction set detection for MSVC only - if (LLAMA_NATIVE) - include(cmake/FindSIMD.cmake) - endif () - if (LLAMA_AVX512) - list(APPEND ARCH_FLAGS /arch:AVX512) - # MSVC has no compile-time flags enabling specific - # AVX512 extensions, neither it defines the - # macros corresponding to the extensions. - 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endif() - if (LLAMA_AVX512_VNNI) - list(APPEND ARCH_FLAGS -mavx512vnni) - endif() - if (LLAMA_AVX512_BF16) - list(APPEND ARCH_FLAGS -mavx512bf16) - endif() - endif() -elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "ppc64") - message(STATUS "PowerPC detected") - if (${CMAKE_SYSTEM_PROCESSOR} MATCHES "ppc64le") - list(APPEND ARCH_FLAGS -mcpu=powerpc64le) - else() - list(APPEND ARCH_FLAGS -mcpu=native -mtune=native) - #TODO: Add targets for Power8/Power9 (Altivec/VSX) and Power10(MMA) and query for big endian systems (ppc64/le/be) - endif() -elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "loongarch64") - message(STATUS "loongarch64 detected") - - list(APPEND ARCH_FLAGS -march=loongarch64) - if (LLAMA_LASX) - list(APPEND ARCH_FLAGS -mlasx) - endif() - if (LLAMA_LSX) - list(APPEND ARCH_FLAGS -mlsx) - endif() - -else() - message(STATUS "Unknown architecture") -endif() - -add_compile_options("$<$:${ARCH_FLAGS}>") -add_compile_options("$<$:${ARCH_FLAGS}>") - -if (LLAMA_CUDA) - list(APPEND CUDA_CXX_FLAGS ${ARCH_FLAGS}) - list(JOIN CUDA_CXX_FLAGS " " CUDA_CXX_FLAGS_JOINED) # pass host compiler flags as a single argument - if (NOT CUDA_CXX_FLAGS_JOINED STREQUAL "") - list(APPEND CUDA_FLAGS -Xcompiler ${CUDA_CXX_FLAGS_JOINED}) - endif() - add_compile_options("$<$:${CUDA_FLAGS}>") -endif() - -if (MINGW) - # Target Windows 8 for PrefetchVirtualMemory - add_compile_definitions(_WIN32_WINNT=${LLAMA_WIN_VER}) -endif() +llama_option_depr(FATAL_ERROR LLAMA_CUBLAS GGML_CUDA) +llama_option_depr(WARNING LLAMA_CUDA GGML_CUDA) +llama_option_depr(WARNING LLAMA_KOMPUTE GGML_KOMPUTE) +llama_option_depr(WARNING LLAMA_METAL GGML_METAL) +llama_option_depr(WARNING LLAMA_METAL_EMBED_LIBRARY GGML_METAL_EMBED_LIBRARY) +llama_option_depr(WARNING LLAMA_NATIVE GGML_NATIVE) +llama_option_depr(WARNING LLAMA_OPENMP GGML_OPENMP) +llama_option_depr(WARNING LLAMA_RPC GGML_RPC) +llama_option_depr(WARNING LLAMA_SYCL GGML_SYCL) +llama_option_depr(WARNING LLAMA_SYCL_F16 GGML_SYCL_F16) # -# POSIX conformance +# build the library # -# clock_gettime came in POSIX.1b (1993) -# CLOCK_MONOTONIC came in POSIX.1-2001 / SUSv3 as optional -# posix_memalign came in POSIX.1-2001 / SUSv3 -# M_PI is an XSI extension since POSIX.1-2001 / SUSv3, came in XPG1 (1985) -add_compile_definitions(_XOPEN_SOURCE=600) - -# Somehow in OpenBSD whenever POSIX conformance is specified -# some string functions rely on locale_t availability, -# which was introduced in POSIX.1-2008, forcing us to go higher -if (CMAKE_SYSTEM_NAME MATCHES "OpenBSD") - remove_definitions(-D_XOPEN_SOURCE=600) - add_compile_definitions(_XOPEN_SOURCE=700) -endif() - -# Data types, macros and functions related to controlling CPU affinity and -# some memory allocation are available on Linux through GNU extensions in libc -if (CMAKE_SYSTEM_NAME MATCHES "Linux") - add_compile_definitions(_GNU_SOURCE) -endif() - -# RLIMIT_MEMLOCK came in BSD, is not specified in POSIX.1, -# and on macOS its availability depends on enabling Darwin extensions -# similarly on DragonFly, enabling BSD extensions is necessary -if ( - CMAKE_SYSTEM_NAME MATCHES "Darwin" OR - CMAKE_SYSTEM_NAME MATCHES "iOS" OR - CMAKE_SYSTEM_NAME MATCHES "tvOS" OR - CMAKE_SYSTEM_NAME MATCHES "DragonFly" -) - add_compile_definitions(_DARWIN_C_SOURCE) -endif() - -# alloca is a non-standard interface that is not visible on BSDs when -# POSIX conformance is specified, but not all of them provide a clean way -# to enable it in such cases -if (CMAKE_SYSTEM_NAME MATCHES "FreeBSD") - add_compile_definitions(__BSD_VISIBLE) -endif() -if (CMAKE_SYSTEM_NAME MATCHES "NetBSD") - add_compile_definitions(_NETBSD_SOURCE) -endif() -if (CMAKE_SYSTEM_NAME MATCHES "OpenBSD") - add_compile_definitions(_BSD_SOURCE) -endif() - -# -# libraries -# - -# ggml - -add_library(ggml OBJECT - ggml.c - ggml.h - ggml-alloc.c - ggml-alloc.h - ggml-backend.c - ggml-backend.h - ggml-quants.c - ggml-quants.h - ${GGML_SOURCES_CUDA} ${GGML_HEADERS_CUDA} - ${GGML_SOURCES_METAL} ${GGML_HEADERS_METAL} - ${GGML_SOURCES_RPC} ${GGML_HEADERS_RPC} - ${GGML_SOURCES_EXTRA} ${GGML_HEADERS_EXTRA} - ${GGML_SOURCES_SYCL} ${GGML_HEADERS_SYCL} - ${GGML_SOURCES_KOMPUTE} ${GGML_HEADERS_KOMPUTE} - ${GGML_SOURCES_VULKAN} ${GGML_HEADERS_VULKAN} - ${GGML_SOURCES_ROCM} ${GGML_HEADERS_ROCM} - ${GGML_SOURCES_BLAS} ${GGML_HEADERS_BLAS} - ${GGML_SOURCES_LLAMAFILE} ${GGML_HEADERS_LLAMAFILE} - ) - -target_include_directories(ggml PUBLIC . ${LLAMA_EXTRA_INCLUDES}) -target_compile_features (ggml PUBLIC c_std_11) # don't bump - -target_link_libraries(ggml PUBLIC Threads::Threads ${LLAMA_EXTRA_LIBS}) - -add_library(ggml_static STATIC $) - -if (BUILD_SHARED_LIBS) - set_target_properties(ggml PROPERTIES POSITION_INDEPENDENT_CODE ON) - add_library(ggml_shared SHARED $) - target_link_libraries(ggml_shared PUBLIC Threads::Threads ${LLAMA_EXTRA_LIBS}) - install(TARGETS ggml_shared LIBRARY) -endif() - -# llama - -add_library(llama - llama.cpp - llama.h - unicode.h - unicode.cpp - unicode-data.cpp - ) - -target_include_directories(llama PUBLIC .) -target_compile_features (llama PUBLIC cxx_std_11) # don't bump - -target_link_libraries(llama PRIVATE - ggml - ${LLAMA_EXTRA_LIBS} - ) - -if (BUILD_SHARED_LIBS) - set_target_properties(llama PROPERTIES POSITION_INDEPENDENT_CODE ON) - target_compile_definitions(llama PRIVATE LLAMA_SHARED LLAMA_BUILD) - if (LLAMA_METAL) - set_target_properties(llama PROPERTIES RESOURCE "${CMAKE_CURRENT_SOURCE_DIR}/ggml-metal.metal") - endif() -endif() - +add_subdirectory(ggml) +add_subdirectory(src) # # install @@ -1323,44 +114,35 @@ endif() include(GNUInstallDirs) include(CMakePackageConfigHelpers) -set(LLAMA_INCLUDE_INSTALL_DIR ${CMAKE_INSTALL_INCLUDEDIR} - CACHE PATH "Location of header files") -set(LLAMA_LIB_INSTALL_DIR ${CMAKE_INSTALL_LIBDIR} - CACHE PATH "Location of library files") -set(LLAMA_BIN_INSTALL_DIR ${CMAKE_INSTALL_BINDIR} - CACHE PATH "Location of binary files") -set(LLAMA_BUILD_NUMBER ${BUILD_NUMBER}) -set(LLAMA_BUILD_COMMIT ${BUILD_COMMIT}) +set(LLAMA_BUILD_NUMBER ${BUILD_NUMBER}) +set(LLAMA_BUILD_COMMIT ${BUILD_COMMIT}) set(LLAMA_INSTALL_VERSION 0.0.${BUILD_NUMBER}) + +set(LLAMA_INCLUDE_INSTALL_DIR ${CMAKE_INSTALL_INCLUDEDIR} CACHE PATH "Location of header files") +set(LLAMA_LIB_INSTALL_DIR ${CMAKE_INSTALL_LIBDIR} CACHE PATH "Location of library files") +set(LLAMA_BIN_INSTALL_DIR ${CMAKE_INSTALL_BINDIR} CACHE PATH "Location of binary files") + get_directory_property(LLAMA_TRANSIENT_DEFINES COMPILE_DEFINITIONS) +set_target_properties(llama PROPERTIES PUBLIC_HEADER ${CMAKE_CURRENT_SOURCE_DIR}/include/llama.h) +install(TARGETS llama LIBRARY PUBLIC_HEADER) + configure_package_config_file( - ${CMAKE_CURRENT_SOURCE_DIR}/scripts/LlamaConfig.cmake.in - ${CMAKE_CURRENT_BINARY_DIR}/LlamaConfig.cmake - INSTALL_DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/Llama + ${CMAKE_CURRENT_SOURCE_DIR}/cmake/llama-config.cmake.in + ${CMAKE_CURRENT_BINARY_DIR}/llama-config.cmake + INSTALL_DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/llama PATH_VARS LLAMA_INCLUDE_INSTALL_DIR LLAMA_LIB_INSTALL_DIR LLAMA_BIN_INSTALL_DIR ) write_basic_package_version_file( - ${CMAKE_CURRENT_BINARY_DIR}/LlamaConfigVersion.cmake + ${CMAKE_CURRENT_BINARY_DIR}/llama-version.cmake VERSION ${LLAMA_INSTALL_VERSION} COMPATIBILITY SameMajorVersion) -install(FILES ${CMAKE_CURRENT_BINARY_DIR}/LlamaConfig.cmake - ${CMAKE_CURRENT_BINARY_DIR}/LlamaConfigVersion.cmake - DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/Llama) - -set(GGML_PUBLIC_HEADERS "ggml.h" "ggml-alloc.h" "ggml-backend.h" - "${GGML_HEADERS_CUDA}" - "${GGML_HEADERS_METAL}" - "${GGML_HEADERS_EXTRA}") - -set_target_properties(ggml PROPERTIES PUBLIC_HEADER "${GGML_PUBLIC_HEADERS}") -install(TARGETS ggml PUBLIC_HEADER) - -set_target_properties(llama PROPERTIES PUBLIC_HEADER ${CMAKE_CURRENT_SOURCE_DIR}/llama.h) -install(TARGETS llama LIBRARY PUBLIC_HEADER) +install(FILES ${CMAKE_CURRENT_BINARY_DIR}/llama-config.cmake + ${CMAKE_CURRENT_BINARY_DIR}/llama-version.cmake + DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/llama) install( FILES convert-hf-to-gguf.py @@ -1373,22 +155,6 @@ install( WORLD_READ WORLD_EXECUTE DESTINATION ${CMAKE_INSTALL_BINDIR}) -if (LLAMA_METAL) - install( - FILES ggml-metal.metal - PERMISSIONS - OWNER_READ - OWNER_WRITE - GROUP_READ - WORLD_READ - DESTINATION ${CMAKE_INSTALL_BINDIR}) - if (NOT LLAMA_METAL_EMBED_LIBRARY) - install( - FILES ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib - DESTINATION ${CMAKE_INSTALL_BINDIR} - ) - endif() -endif() configure_file(cmake/llama.pc.in "${CMAKE_CURRENT_BINARY_DIR}/llama.pc" diff --git a/CMakePresets.json b/CMakePresets.json index fba22af9a6bab..d69bc03447ae9 100644 --- a/CMakePresets.json +++ b/CMakePresets.json @@ -19,14 +19,14 @@ "cacheVariables": { "CMAKE_EXPORT_COMPILE_COMMANDS": "ON", "CMAKE_CXX_COMPILER": "icx", - "LLAMA_SYCL": "ON", + "GGML_SYCL": "ON", "CMAKE_INSTALL_RPATH": "$ORIGIN;$ORIGIN/.." } }, { "name": "debug", "hidden": true, "cacheVariables": { "CMAKE_BUILD_TYPE": "Debug" } }, { "name": "release", "hidden": true, "cacheVariables": { "CMAKE_BUILD_TYPE": "Release" } }, - { "name": "reldbg", "hidden": true, "cacheVariables": { "CMAKE_BUILD_TYPE": "RelWithDebInfo" } }, - { "name": "static", "hidden": true, "cacheVariables": { "LLAMA_STATIC": "ON" } }, + { "name": "reldbg", "hidden": true, "cacheVariables": { "CMAKE_BUILD_TYPE": "RelWithDebInfo" } }, + { "name": "static", "hidden": true, "cacheVariables": { "GGML_STATIC": "ON" } }, { "name": "arm64-windows-msvc", "hidden": true, diff --git a/Makefile b/Makefile index f6e8eb73eb9eb..64a6e6ff00e5a 100644 --- a/Makefile +++ b/Makefile @@ -61,8 +61,80 @@ TEST_TARGETS = \ tests/test-tokenizer-1-bpe \ tests/test-tokenizer-1-spm -# Code coverage output files -COV_TARGETS = *.gcno tests/*.gcno *.gcda tests/*.gcda *.gcov tests/*.gcov lcov-report gcovr-report +# Deprecation aliases +ifdef LLAMA_CUBLAS +$(error LLAMA_CUBLAS is removed. Use GGML_CUDA instead.) +endif + +ifdef LLAMA_CUDA +GGML_CUDA := 1 +DEPRECATE_WARNING := 1 +endif + +ifdef LLAMA_KOMPUTE +GGML_KOMPUTE := 1 +DEPRECATE_WARNING := 1 +endif + +ifdef LLAMA_METAL +GGML_METAL := 1 +DEPRECATE_WARNING := 1 +endif + +ifdef LLAMA_OPENMP +GGML_OPENMP := 1 +DEPRECATE_WARNING := 1 +endif + +ifdef LLAMA_RPC +GGML_RPC := 1 +DEPRECATE_WARNING := 1 +endif + +ifdef LLAMA_SYCL +GGML_SYCL := 1 +DEPRECATE_WARNING := 1 +endif + +ifdef LLAMA_SYCL_F16 +GGML_SYCL_F16 := 1 +DEPRECATE_WARNING := 1 +endif + +ifdef LLAMA_OPENBLAS +GGML_OPENBLAS := 1 +DEPRECATE_WARNING := 1 +endif + +ifdef LLAMA_OPENBLAS64 +GGML_OPENBLAS64 := 1 +DEPRECATE_WARNING := 1 +endif + +ifdef LLAMA_BLIS +GGML_BLIS := 1 +DEPRECATE_WARNING := 1 +endif + +ifdef LLAMA_NO_LLAMAFILE +GGML_NO_LLAMAFILE := 1 +DEPRECATE_WARNING := 1 +endif + +ifdef LLAMA_NO_ACCELERATE +GGML_NO_ACCELERATE := 1 +DEPRECATE_WARNING := 1 +endif + +ifdef LLAMA_NO_OPENMP +GGML_NO_OPENMP := 1 +DEPRECATE_WARNING := 1 +endif + +ifdef LLAMA_NO_METAL +GGML_NO_METAL := 1 +DEPRECATE_WARNING := 1 +endif ifndef UNAME_S UNAME_S := $(shell uname -s) @@ -76,6 +148,12 @@ ifndef UNAME_M UNAME_M := $(shell uname -m) endif +MK_CFLAGS += -O3 +MK_CXXFLAGS += -O3 +ifndef LLAMA_DEBUG +MK_NVCCFLAGS += -O3 +endif # LLAMA_DEBUG + # In GNU make default CXX is g++ instead of c++. Let's fix that so that users # of non-gcc compilers don't have to provide g++ alias or wrapper. DEFCC := cc @@ -90,11 +168,11 @@ endif # Mac OS + Arm can report x86_64 # ref: https://github.com/ggerganov/whisper.cpp/issues/66#issuecomment-1282546789 ifeq ($(UNAME_S),Darwin) - ifndef LLAMA_NO_METAL - LLAMA_METAL := 1 + ifndef GGML_NO_METAL + GGML_METAL := 1 endif - LLAMA_NO_OPENMP := 1 + GGML_NO_OPENMP := 1 ifneq ($(UNAME_P),arm) SYSCTL_M := $(shell sysctl -n hw.optional.arm64 2>/dev/null) @@ -106,7 +184,11 @@ ifeq ($(UNAME_S),Darwin) endif endif -ifdef LLAMA_RPC +ifdef GGML_METAL + GGML_METAL_EMBED_LIBRARY := 1 +endif + +ifdef GGML_RPC BUILD_TARGETS += rpc-server endif @@ -147,18 +229,6 @@ test: $(TEST_TARGETS) all: $(BUILD_TARGETS) $(TEST_TARGETS) -coverage: ## Run code coverage - gcov -pb tests/*.cpp - -lcov-report: coverage ## Generate lcov report - mkdir -p lcov-report - lcov --capture --directory . --output-file lcov-report/coverage.info - genhtml lcov-report/coverage.info --output-directory lcov-report - -gcovr-report: coverage ## Generate gcovr report - mkdir -p gcovr-report - gcovr --root . --html --html-details --output gcovr-report/coverage.html - ifdef RISCV_CROSS_COMPILE CC := riscv64-unknown-linux-gnu-gcc CXX := riscv64-unknown-linux-gnu-g++ @@ -169,26 +239,11 @@ endif # # keep standard at C11 and C++11 -MK_CPPFLAGS = -I. -Icommon +MK_CPPFLAGS = -Iggml/include -Iggml/src -Iinclude -Isrc -Icommon MK_CFLAGS = -std=c11 -fPIC MK_CXXFLAGS = -std=c++11 -fPIC MK_NVCCFLAGS = -std=c++11 -# -Ofast tends to produce faster code, but may not be available for some compilers. -ifdef LLAMA_FAST -MK_CFLAGS += -Ofast -HOST_CXXFLAGS += -Ofast -ifndef LLAMA_DEBUG -MK_NVCCFLAGS += -O3 -endif # LLAMA_DEBUG -else -MK_CFLAGS += -O3 -MK_CXXFLAGS += -O3 -ifndef LLAMA_DEBUG -MK_NVCCFLAGS += -O3 -endif # LLAMA_DEBUG -endif # LLAMA_FAST - ifndef LLAMA_NO_CCACHE CCACHE := $(shell which ccache) ifdef CCACHE @@ -243,8 +298,8 @@ ifeq ($(UNAME_S),OpenBSD) MK_CPPFLAGS += -D_BSD_SOURCE endif -ifdef LLAMA_SCHED_MAX_COPIES - MK_CPPFLAGS += -DGGML_SCHED_MAX_COPIES=$(LLAMA_SCHED_MAX_COPIES) +ifdef GGML_SCHED_MAX_COPIES + MK_CPPFLAGS += -DGGML_SCHED_MAX_COPIES=$(GGML_SCHED_MAX_COPIES) endif ifdef LLAMA_DEBUG @@ -287,19 +342,31 @@ ifdef LLAMA_SERVER_SSL MK_LDFLAGS += -lssl -lcrypto endif -ifdef LLAMA_CODE_COVERAGE - MK_CXXFLAGS += -fprofile-arcs -ftest-coverage -dumpbase '' -endif - ifdef LLAMA_DISABLE_LOGS MK_CPPFLAGS += -DLOG_DISABLE_LOGS endif # LLAMA_DISABLE_LOGS # warnings -WARN_FLAGS = -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -MK_CFLAGS += $(WARN_FLAGS) -Wshadow -Wstrict-prototypes -Wpointer-arith -Wmissing-prototypes -Werror=implicit-int \ - -Werror=implicit-function-declaration -MK_CXXFLAGS += $(WARN_FLAGS) -Wmissing-declarations -Wmissing-noreturn +WARN_FLAGS = \ + -Wall \ + -Wextra \ + -Wpedantic \ + -Wcast-qual \ + -Wno-unused-function + +MK_CFLAGS += \ + $(WARN_FLAGS) \ + -Wshadow \ + -Wstrict-prototypes \ + -Wpointer-arith \ + -Wmissing-prototypes \ + -Werror=implicit-int \ + -Werror=implicit-function-declaration + +MK_CXXFLAGS += \ + $(WARN_FLAGS) \ + -Wmissing-declarations \ + -Wmissing-noreturn ifeq ($(LLAMA_FATAL_WARNINGS),1) MK_CFLAGS += -Werror @@ -434,7 +501,7 @@ else MK_CXXFLAGS += -march=rv64gcv -mabi=lp64d endif -ifndef LLAMA_NO_ACCELERATE +ifndef GGML_NO_ACCELERATE # Mac OS - include Accelerate framework. # `-framework Accelerate` works both with Apple Silicon and Mac Intel ifeq ($(UNAME_S),Darwin) @@ -442,141 +509,157 @@ ifndef LLAMA_NO_ACCELERATE MK_CPPFLAGS += -DACCELERATE_NEW_LAPACK MK_CPPFLAGS += -DACCELERATE_LAPACK_ILP64 MK_LDFLAGS += -framework Accelerate - OBJS += ggml-blas.o + OBJ_GGML += ggml/src/ggml-blas.o endif -endif # LLAMA_NO_ACCELERATE +endif # GGML_NO_ACCELERATE -ifndef LLAMA_NO_OPENMP +ifndef GGML_NO_OPENMP MK_CPPFLAGS += -DGGML_USE_OPENMP MK_CFLAGS += -fopenmp MK_CXXFLAGS += -fopenmp -endif # LLAMA_NO_OPENMP +endif # GGML_NO_OPENMP -ifdef LLAMA_OPENBLAS +ifdef GGML_OPENBLAS MK_CPPFLAGS += -DGGML_USE_BLAS $(shell pkg-config --cflags-only-I openblas) MK_CFLAGS += $(shell pkg-config --cflags-only-other openblas) MK_LDFLAGS += $(shell pkg-config --libs openblas) - OBJS += ggml-blas.o -endif # LLAMA_OPENBLAS + OBJ_GGML += ggml/src/ggml-blas.o +endif # GGML_OPENBLAS -ifdef LLAMA_OPENBLAS64 +ifdef GGML_OPENBLAS64 MK_CPPFLAGS += -DGGML_USE_BLAS $(shell pkg-config --cflags-only-I openblas64) MK_CFLAGS += $(shell pkg-config --cflags-only-other openblas64) MK_LDFLAGS += $(shell pkg-config --libs openblas64) - OBJS += ggml-blas.o -endif # LLAMA_OPENBLAS64 + OBJ_GGML += ggml/src/ggml-blas.o +endif # GGML_OPENBLAS64 -ifdef LLAMA_BLIS +ifdef GGML_BLIS MK_CPPFLAGS += -DGGML_USE_BLAS -I/usr/local/include/blis -I/usr/include/blis MK_LDFLAGS += -lblis -L/usr/local/lib - OBJS += ggml-blas.o -endif # LLAMA_BLIS + OBJ_GGML += ggml/src/ggml-blas.o +endif # GGML_BLIS -ifndef LLAMA_NO_LLAMAFILE +ifndef GGML_NO_LLAMAFILE MK_CPPFLAGS += -DGGML_USE_LLAMAFILE - OBJS += sgemm.o + OBJ_GGML += ggml/src/sgemm.o endif -ifdef LLAMA_RPC - MK_CPPFLAGS += -DGGML_USE_RPC - OBJS += ggml-rpc.o -endif # LLAMA_RPC +ifdef GGML_RPC + MK_CPPFLAGS += -DGGML_USE_RPC + OBJ_GGML += ggml/src/ggml-rpc.o +endif # GGML_RPC -ifdef LLAMA_CUBLAS -# LLAMA_CUBLAS is deprecated and will be removed in the future - LLAMA_CUDA := 1 -endif +OBJ_CUDA_TMPL = $(patsubst %.cu,%.o,$(wildcard ggml/src/ggml-cuda/template-instances/fattn-wmma*.cu)) +OBJ_CUDA_TMPL += $(patsubst %.cu,%.o,$(wildcard ggml/src/ggml-cuda/template-instances/mmq*.cu)) -OBJS_CUDA_TEMP_INST = $(patsubst %.cu,%.o,$(wildcard ggml-cuda/template-instances/fattn-wmma*.cu)) -OBJS_CUDA_TEMP_INST += $(patsubst %.cu,%.o,$(wildcard ggml-cuda/template-instances/mmq*.cu)) -ifdef LLAMA_CUDA_FA_ALL_QUANTS - OBJS_CUDA_TEMP_INST += $(patsubst %.cu,%.o,$(wildcard ggml-cuda/template-instances/fattn-vec*.cu)) +ifdef GGML_CUDA_FA_ALL_QUANTS + OBJ_CUDA_TMPL += $(patsubst %.cu,%.o,$(wildcard ggml/src/ggml-cuda/template-instances/fattn-vec*.cu)) else - OBJS_CUDA_TEMP_INST += $(patsubst %.cu,%.o,$(wildcard ggml-cuda/template-instances/fattn-vec*q4_0-q4_0.cu)) - OBJS_CUDA_TEMP_INST += $(patsubst %.cu,%.o,$(wildcard ggml-cuda/template-instances/fattn-vec*q8_0-q8_0.cu)) - OBJS_CUDA_TEMP_INST += $(patsubst %.cu,%.o,$(wildcard ggml-cuda/template-instances/fattn-vec*f16-f16.cu)) -endif # LLAMA_CUDA_FA_ALL_QUANTS + OBJ_CUDA_TMPL += $(patsubst %.cu,%.o,$(wildcard ggml/src/ggml-cuda/template-instances/fattn-vec*q4_0-q4_0.cu)) + OBJ_CUDA_TMPL += $(patsubst %.cu,%.o,$(wildcard ggml/src/ggml-cuda/template-instances/fattn-vec*q8_0-q8_0.cu)) + OBJ_CUDA_TMPL += $(patsubst %.cu,%.o,$(wildcard ggml/src/ggml-cuda/template-instances/fattn-vec*f16-f16.cu)) +endif # GGML_CUDA_FA_ALL_QUANTS -ifdef LLAMA_CUDA +ifdef GGML_CUDA ifneq ('', '$(wildcard /opt/cuda)') CUDA_PATH ?= /opt/cuda else CUDA_PATH ?= /usr/local/cuda endif + MK_CPPFLAGS += -DGGML_USE_CUDA -I$(CUDA_PATH)/include -I$(CUDA_PATH)/targets/$(UNAME_M)-linux/include -DGGML_CUDA_USE_GRAPHS MK_LDFLAGS += -lcuda -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L$(CUDA_PATH)/lib64 -L/usr/lib64 -L$(CUDA_PATH)/targets/$(UNAME_M)-linux/lib -L$(CUDA_PATH)/lib64/stubs -L/usr/lib/wsl/lib - OBJS += ggml-cuda.o - OBJS += $(patsubst %.cu,%.o,$(wildcard ggml-cuda/*.cu)) - OBJS += $(OBJS_CUDA_TEMP_INST) MK_NVCCFLAGS += -use_fast_math + + OBJ_GGML += ggml/src/ggml-cuda.o + OBJ_GGML += $(patsubst %.cu,%.o,$(wildcard ggml/src/ggml-cuda/*.cu)) + OBJ_GGML += $(OBJ_CUDA_TMPL) + ifdef LLAMA_FATAL_WARNINGS MK_NVCCFLAGS += -Werror all-warnings endif # LLAMA_FATAL_WARNINGS + ifndef JETSON_EOL_MODULE_DETECT MK_NVCCFLAGS += --forward-unknown-to-host-compiler endif # JETSON_EOL_MODULE_DETECT + ifdef LLAMA_DEBUG MK_NVCCFLAGS += -lineinfo endif # LLAMA_DEBUG -ifdef LLAMA_CUDA_DEBUG + +ifdef GGML_CUDA_DEBUG MK_NVCCFLAGS += --device-debug -endif # LLAMA_CUDA_DEBUG -ifdef LLAMA_CUDA_NVCC - NVCC = $(CCACHE) $(LLAMA_CUDA_NVCC) +endif # GGML_CUDA_DEBUG + +ifdef GGML_CUDA_NVCC + NVCC = $(CCACHE) $(GGML_CUDA_NVCC) else NVCC = $(CCACHE) nvcc -endif #LLAMA_CUDA_NVCC +endif #GGML_CUDA_NVCC + ifdef CUDA_DOCKER_ARCH MK_NVCCFLAGS += -Wno-deprecated-gpu-targets -arch=$(CUDA_DOCKER_ARCH) else ifndef CUDA_POWER_ARCH MK_NVCCFLAGS += -arch=native endif # CUDA_DOCKER_ARCH -ifdef LLAMA_CUDA_FORCE_DMMV + +ifdef GGML_CUDA_FORCE_DMMV MK_NVCCFLAGS += -DGGML_CUDA_FORCE_DMMV -endif # LLAMA_CUDA_FORCE_DMMV -ifdef LLAMA_CUDA_FORCE_MMQ +endif # GGML_CUDA_FORCE_DMMV + +ifdef GGML_CUDA_FORCE_MMQ MK_NVCCFLAGS += -DGGML_CUDA_FORCE_MMQ -endif # LLAMA_CUDA_FORCE_MMQ -ifdef LLAMA_CUDA_FORCE_CUBLAS +endif # GGML_CUDA_FORCE_MMQ + +ifdef GGML_CUDA_FORCE_CUBLAS MK_NVCCFLAGS += -DGGML_CUDA_FORCE_CUBLAS -endif # LLAMA_CUDA_FORCE_CUBLAS -ifdef LLAMA_CUDA_DMMV_X - MK_NVCCFLAGS += -DGGML_CUDA_DMMV_X=$(LLAMA_CUDA_DMMV_X) +endif # GGML_CUDA_FORCE_CUBLAS + +ifdef GGML_CUDA_DMMV_X + MK_NVCCFLAGS += -DGGML_CUDA_DMMV_X=$(GGML_CUDA_DMMV_X) else MK_NVCCFLAGS += -DGGML_CUDA_DMMV_X=32 -endif # LLAMA_CUDA_DMMV_X -ifdef LLAMA_CUDA_MMV_Y - MK_NVCCFLAGS += -DGGML_CUDA_MMV_Y=$(LLAMA_CUDA_MMV_Y) -else ifdef LLAMA_CUDA_DMMV_Y - MK_NVCCFLAGS += -DGGML_CUDA_MMV_Y=$(LLAMA_CUDA_DMMV_Y) # for backwards compatibility +endif # GGML_CUDA_DMMV_X + +ifdef GGML_CUDA_MMV_Y + MK_NVCCFLAGS += -DGGML_CUDA_MMV_Y=$(GGML_CUDA_MMV_Y) +else ifdef GGML_CUDA_DMMV_Y + MK_NVCCFLAGS += -DGGML_CUDA_MMV_Y=$(GGML_CUDA_DMMV_Y) # for backwards compatibility else MK_NVCCFLAGS += -DGGML_CUDA_MMV_Y=1 -endif # LLAMA_CUDA_MMV_Y -ifdef LLAMA_CUDA_F16 +endif # GGML_CUDA_MMV_Y + +ifdef GGML_CUDA_F16 MK_NVCCFLAGS += -DGGML_CUDA_F16 -endif # LLAMA_CUDA_F16 -ifdef LLAMA_CUDA_DMMV_F16 +endif # GGML_CUDA_F16 + +ifdef GGML_CUDA_DMMV_F16 MK_NVCCFLAGS += -DGGML_CUDA_F16 -endif # LLAMA_CUDA_DMMV_F16 -ifdef LLAMA_CUDA_KQUANTS_ITER - MK_NVCCFLAGS += -DK_QUANTS_PER_ITERATION=$(LLAMA_CUDA_KQUANTS_ITER) +endif # GGML_CUDA_DMMV_F16 + +ifdef GGML_CUDA_KQUANTS_ITER + MK_NVCCFLAGS += -DK_QUANTS_PER_ITERATION=$(GGML_CUDA_KQUANTS_ITER) else MK_NVCCFLAGS += -DK_QUANTS_PER_ITERATION=2 endif -ifdef LLAMA_CUDA_PEER_MAX_BATCH_SIZE - MK_NVCCFLAGS += -DGGML_CUDA_PEER_MAX_BATCH_SIZE=$(LLAMA_CUDA_PEER_MAX_BATCH_SIZE) + +ifdef GGML_CUDA_PEER_MAX_BATCH_SIZE + MK_NVCCFLAGS += -DGGML_CUDA_PEER_MAX_BATCH_SIZE=$(GGML_CUDA_PEER_MAX_BATCH_SIZE) else MK_NVCCFLAGS += -DGGML_CUDA_PEER_MAX_BATCH_SIZE=128 -endif # LLAMA_CUDA_PEER_MAX_BATCH_SIZE -ifdef LLAMA_CUDA_NO_PEER_COPY +endif # GGML_CUDA_PEER_MAX_BATCH_SIZE + +ifdef GGML_CUDA_NO_PEER_COPY MK_NVCCFLAGS += -DGGML_CUDA_NO_PEER_COPY -endif # LLAMA_CUDA_NO_PEER_COPY -ifdef LLAMA_CUDA_CCBIN - MK_NVCCFLAGS += -ccbin $(LLAMA_CUDA_CCBIN) -endif # LLAMA_CUDA_CCBIN -ifdef LLAMA_CUDA_FA_ALL_QUANTS +endif # GGML_CUDA_NO_PEER_COPY + +ifdef GGML_CUDA_CCBIN + MK_NVCCFLAGS += -ccbin $(GGML_CUDA_CCBIN) +endif # GGML_CUDA_CCBIN + +ifdef GGML_CUDA_FA_ALL_QUANTS MK_NVCCFLAGS += -DGGML_CUDA_FA_ALL_QUANTS -endif # LLAMA_CUDA_FA_ALL_QUANTS +endif # GGML_CUDA_FA_ALL_QUANTS ifdef JETSON_EOL_MODULE_DETECT define NVCC_COMPILE @@ -588,135 +671,187 @@ define NVCC_COMPILE endef # NVCC_COMPILE endif # JETSON_EOL_MODULE_DETECT -ggml-cuda/%.o: ggml-cuda/%.cu ggml.h ggml-common.h ggml-cuda/common.cuh +ggml/src/ggml-cuda/%.o: \ + ggml/src/ggml-cuda/%.cu \ + ggml/include/ggml.h \ + ggml/src/ggml-common.h \ + ggml/src/ggml-cuda/common.cuh $(NVCC_COMPILE) -ggml-cuda.o: ggml-cuda.cu ggml-cuda.h ggml.h ggml-backend.h ggml-backend-impl.h ggml-common.h $(wildcard ggml-cuda/*.cuh) +ggml/src/ggml-cuda.o: \ + ggml/src/ggml-cuda.cu \ + ggml/include/ggml-cuda.h \ + ggml/include/ggml.h \ + ggml/include/ggml-backend.h \ + ggml/src/ggml-backend-impl.h \ + ggml/src/ggml-common.h \ + $(wildcard ggml/src/ggml-cuda/*.cuh) $(NVCC_COMPILE) -endif # LLAMA_CUDA +endif # GGML_CUDA -ifdef LLAMA_VULKAN - MK_CPPFLAGS += -DGGML_USE_VULKAN - MK_LDFLAGS += -lvulkan - OBJS += ggml-vulkan.o +ifdef GGML_VULKAN + MK_CPPFLAGS += -DGGML_USE_VULKAN + MK_LDFLAGS += -lvulkan + OBJ_GGML += ggml/src/ggml-vulkan.o -ifdef LLAMA_VULKAN_CHECK_RESULTS +ifdef GGML_VULKAN_CHECK_RESULTS MK_CPPFLAGS += -DGGML_VULKAN_CHECK_RESULTS endif -ifdef LLAMA_VULKAN_DEBUG +ifdef GGML_VULKAN_DEBUG MK_CPPFLAGS += -DGGML_VULKAN_DEBUG endif -ifdef LLAMA_VULKAN_MEMORY_DEBUG +ifdef GGML_VULKAN_MEMORY_DEBUG MK_CPPFLAGS += -DGGML_VULKAN_MEMORY_DEBUG endif -ifdef LLAMA_VULKAN_VALIDATE +ifdef GGML_VULKAN_VALIDATE MK_CPPFLAGS += -DGGML_VULKAN_VALIDATE endif -ifdef LLAMA_VULKAN_RUN_TESTS +ifdef GGML_VULKAN_RUN_TESTS MK_CPPFLAGS += -DGGML_VULKAN_RUN_TESTS endif -ggml-vulkan.o: ggml-vulkan.cpp ggml-vulkan.h +ggml/src/ggml-vulkan.o: \ + ggml/src/ggml-vulkan.cpp \ + ggml/include/ggml-vulkan.h $(CXX) $(CXXFLAGS) -c $< -o $@ -endif # LLAMA_VULKAN +endif # GGML_VULKAN -ifdef LLAMA_HIPBLAS +ifdef GGML_HIPBLAS ifeq ($(wildcard /opt/rocm),) - ROCM_PATH ?= /usr + ROCM_PATH ?= /usr AMDGPU_TARGETS ?= $(shell $(shell which amdgpu-arch)) else ROCM_PATH ?= /opt/rocm AMDGPU_TARGETS ?= $(shell $(ROCM_PATH)/llvm/bin/amdgpu-arch) endif - HIPCC ?= $(CCACHE) $(ROCM_PATH)/bin/hipcc - LLAMA_CUDA_DMMV_X ?= 32 - LLAMA_CUDA_MMV_Y ?= 1 - LLAMA_CUDA_KQUANTS_ITER ?= 2 + + GGML_CUDA_DMMV_X ?= 32 + GGML_CUDA_MMV_Y ?= 1 + GGML_CUDA_KQUANTS_ITER ?= 2 + MK_CPPFLAGS += -DGGML_USE_HIPBLAS -DGGML_USE_CUDA -ifdef LLAMA_HIP_UMA + +ifdef GGML_HIP_UMA MK_CPPFLAGS += -DGGML_HIP_UMA -endif # LLAMA_HIP_UMA - MK_LDFLAGS += -L$(ROCM_PATH)/lib -Wl,-rpath=$(ROCM_PATH)/lib - MK_LDFLAGS += -L$(ROCM_PATH)/lib64 -Wl,-rpath=$(ROCM_PATH)/lib64 - MK_LDFLAGS += -lhipblas -lamdhip64 -lrocblas - HIPFLAGS += $(addprefix --offload-arch=,$(AMDGPU_TARGETS)) - HIPFLAGS += -DGGML_CUDA_DMMV_X=$(LLAMA_CUDA_DMMV_X) - HIPFLAGS += -DGGML_CUDA_MMV_Y=$(LLAMA_CUDA_MMV_Y) - HIPFLAGS += -DK_QUANTS_PER_ITERATION=$(LLAMA_CUDA_KQUANTS_ITER) -ifdef LLAMA_CUDA_FORCE_DMMV - HIPFLAGS += -DGGML_CUDA_FORCE_DMMV -endif # LLAMA_CUDA_FORCE_DMMV -ifdef LLAMA_CUDA_NO_PEER_COPY - HIPFLAGS += -DGGML_CUDA_NO_PEER_COPY -endif # LLAMA_CUDA_NO_PEER_COPY - OBJS += ggml-cuda.o - OBJS += $(patsubst %.cu,%.o,$(wildcard ggml-cuda/*.cu)) - OBJS += $(OBJS_CUDA_TEMP_INST) - -ggml-cuda.o: ggml-cuda.cu ggml-cuda.h ggml.h ggml-backend.h ggml-backend-impl.h ggml-common.h $(wildcard ggml-cuda/*.cuh) +endif # GGML_HIP_UMA + + MK_LDFLAGS += -L$(ROCM_PATH)/lib -Wl,-rpath=$(ROCM_PATH)/lib + MK_LDFLAGS += -L$(ROCM_PATH)/lib64 -Wl,-rpath=$(ROCM_PATH)/lib64 + MK_LDFLAGS += -lhipblas -lamdhip64 -lrocblas + + HIPCC ?= $(CCACHE) $(ROCM_PATH)/bin/hipcc + + HIPFLAGS += $(addprefix --offload-arch=,$(AMDGPU_TARGETS)) + HIPFLAGS += -DGGML_CUDA_DMMV_X=$(GGML_CUDA_DMMV_X) + HIPFLAGS += -DGGML_CUDA_MMV_Y=$(GGML_CUDA_MMV_Y) + HIPFLAGS += -DK_QUANTS_PER_ITERATION=$(GGML_CUDA_KQUANTS_ITER) + +ifdef GGML_CUDA_FORCE_DMMV + HIPFLAGS += -DGGML_CUDA_FORCE_DMMV +endif # GGML_CUDA_FORCE_DMMV + +ifdef GGML_CUDA_NO_PEER_COPY + HIPFLAGS += -DGGML_CUDA_NO_PEER_COPY +endif # GGML_CUDA_NO_PEER_COPY + + OBJ_GGML += ggml/src/ggml-cuda.o + OBJ_GGML += $(patsubst %.cu,%.o,$(wildcard ggml/src/ggml-cuda/*.cu)) + OBJ_GGML += $(OBJ_CUDA_TMPL) + +ggml/src/ggml-cuda.o: \ + ggml/src/ggml-cuda.cu \ + ggml/include/ggml-cuda.h \ + ggml/include/ggml.h \ + ggml/include/ggml-backend.h \ + ggml/src/ggml-backend-impl.h \ + ggml/src/ggml-common.h \ + $(wildcard ggml/src/ggml-cuda/*.cuh) $(HIPCC) $(CXXFLAGS) $(HIPFLAGS) -x hip -c -o $@ $< -ggml-cuda/%.o: ggml-cuda/%.cu ggml.h ggml-common.h ggml-cuda/common.cuh +ggml/src/ggml-cuda/%.o: \ + ggml/src/ggml-cuda/%.cu \ + ggml/include/ggml.h \ + ggml/src/ggml-common.h \ + ggml/src/ggml-cuda/common.cuh $(HIPCC) $(CXXFLAGS) $(HIPFLAGS) -x hip -c -o $@ $< +endif # GGML_HIPBLAS -endif # LLAMA_HIPBLAS - -ifdef LLAMA_METAL +ifdef GGML_METAL MK_CPPFLAGS += -DGGML_USE_METAL MK_LDFLAGS += -framework Foundation -framework Metal -framework MetalKit - OBJS += ggml-metal.o -ifdef LLAMA_METAL_NDEBUG + OBJ_GGML += ggml/src/ggml-metal.o +ifdef GGML_METAL_NDEBUG MK_CPPFLAGS += -DGGML_METAL_NDEBUG endif -ifdef LLAMA_METAL_EMBED_LIBRARY +ifdef GGML_METAL_EMBED_LIBRARY MK_CPPFLAGS += -DGGML_METAL_EMBED_LIBRARY - OBJS += ggml-metal-embed.o + OBJ_GGML += ggml/src/ggml-metal-embed.o endif -endif # LLAMA_METAL +endif # GGML_METAL -ifdef LLAMA_METAL -ggml-metal.o: ggml-metal.m ggml-metal.h ggml.h +ifdef GGML_METAL +ggml/src/ggml-metal.o: \ + ggml/src/ggml-metal.m \ + ggml/include/ggml-metal.h \ + ggml/include/ggml.h $(CC) $(CFLAGS) -c $< -o $@ -ifdef LLAMA_METAL_EMBED_LIBRARY -ggml-metal-embed.o: ggml-metal.metal ggml-common.h +ifdef GGML_METAL_EMBED_LIBRARY +ggml/src/ggml-metal-embed.o: \ + ggml/src/ggml-metal.metal \ + ggml/src/ggml-common.h @echo "Embedding Metal library" - @sed -e '/#include "ggml-common.h"/r ggml-common.h' -e '/#include "ggml-common.h"/d' < ggml-metal.metal > ggml-metal-embed.metal + @sed -e '/#include "ggml-common.h"/r ggml/src/ggml-common.h' -e '/#include "ggml-common.h"/d' < ggml/src/ggml-metal.metal > ggml/src/ggml-metal-embed.metal $(eval TEMP_ASSEMBLY=$(shell mktemp)) - @echo ".section __DATA, __ggml_metallib" > $(TEMP_ASSEMBLY) - @echo ".globl _ggml_metallib_start" >> $(TEMP_ASSEMBLY) - @echo "_ggml_metallib_start:" >> $(TEMP_ASSEMBLY) - @echo ".incbin \"ggml-metal-embed.metal\"" >> $(TEMP_ASSEMBLY) - @echo ".globl _ggml_metallib_end" >> $(TEMP_ASSEMBLY) - @echo "_ggml_metallib_end:" >> $(TEMP_ASSEMBLY) + @echo ".section __DATA, __ggml_metallib" > $(TEMP_ASSEMBLY) + @echo ".globl _ggml_metallib_start" >> $(TEMP_ASSEMBLY) + @echo "_ggml_metallib_start:" >> $(TEMP_ASSEMBLY) + @echo ".incbin \"ggml/src/ggml-metal-embed.metal\"" >> $(TEMP_ASSEMBLY) + @echo ".globl _ggml_metallib_end" >> $(TEMP_ASSEMBLY) + @echo "_ggml_metallib_end:" >> $(TEMP_ASSEMBLY) @$(AS) $(TEMP_ASSEMBLY) -o $@ @rm -f ${TEMP_ASSEMBLY} endif -endif # LLAMA_METAL +endif # GGML_METAL -OBJS += ggml-alloc.o ggml-backend.o ggml-quants.o unicode.o unicode-data.o -COMMON_H_DEPS = common/common.h common/sampling.h common/log.h llama.h -COMMON_DEPS = common.o sampling.o grammar-parser.o build-info.o json-schema-to-grammar.o +OBJ_GGML += \ + ggml/src/ggml.o \ + ggml/src/ggml-alloc.o \ + ggml/src/ggml-backend.o \ + ggml/src/ggml-quants.o -ifndef LLAMA_NO_LLAMAFILE -sgemm.o: sgemm.cpp sgemm.h ggml.h - $(CXX) $(CXXFLAGS) -c $< -o $@ -endif +OBJ_LLAMA = \ + src/llama.o \ + src/unicode.o \ + src/unicode-data.o -ifdef LLAMA_RPC -ggml-rpc.o: ggml-rpc.cpp ggml-rpc.h - $(CXX) $(CXXFLAGS) -c $< -o $@ +OBJ_COMMON = \ + common/common.o \ + common/console.o \ + common/ngram-cache.o \ + common/sampling.o \ + common/train.o \ + common/grammar-parser.o \ + common/build-info.o \ + common/json-schema-to-grammar.o -rpc-server.o: examples/rpc/rpc-server.cpp ggml-rpc.h - $(CXX) $(CXXFLAGS) -c $< -o $@ +OBJ_ALL = $(OBJ_GGML) $(OBJ_LLAMA) $(OBJ_COMMON) -rpc-server: rpc-server.o ggml.o llama.o $(COMMON_DEPS) $(OBJS) - $(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS) -endif # LLAMA_RPC +LIB_GGML = $(LIB_PRE)ggml$(DSO_EXT) +LIB_GGML_S = $(LIB_PRE)ggml.a + +LIB_LLAMA = $(LIB_PRE)llama$(DSO_EXT) +LIB_LLAMA_S = $(LIB_PRE)llama.a + +LIB_COMMON = $(LIB_PRE)common$(DSO_EXT) +LIB_COMMON_S = $(LIB_PRE)common.a + +LIB_ALL = $(LIB_GGML) $(LIB_LLAMA) $(LIB_COMMON) +LIB_ALL_S = $(LIB_GGML_S) $(LIB_LLAMA_S) $(LIB_COMMON_S) GF_CC := $(CC) include scripts/get-flags.mk @@ -730,7 +865,7 @@ override NVCCFLAGS := $(MK_NVCCFLAGS) $(NVCCFLAGS) override LDFLAGS := $(MK_LDFLAGS) $(LDFLAGS) # identify CUDA host compiler -ifdef LLAMA_CUDA +ifdef GGML_CUDA GF_CC := $(NVCC) $(NVCCFLAGS) 2>/dev/null .c -Xcompiler include scripts/get-flags.mk CUDA_CXXFLAGS := $(BASE_CXXFLAGS) $(GF_CXXFLAGS) -Wno-pedantic @@ -755,85 +890,203 @@ $(info I NVCCFLAGS: $(NVCCFLAGS)) $(info I LDFLAGS: $(LDFLAGS)) $(info I CC: $(shell $(CC) --version | head -n 1)) $(info I CXX: $(shell $(CXX) --version | head -n 1)) -ifdef LLAMA_CUDA +ifdef GGML_CUDA $(info I NVCC: $(shell $(NVCC) --version | tail -n 1)) CUDA_VERSION := $(shell $(NVCC) --version | grep -oP 'release (\K[0-9]+\.[0-9])') ifeq ($(shell awk -v "v=$(CUDA_VERSION)" 'BEGIN { print (v < 11.7) }'),1) + ifndef CUDA_DOCKER_ARCH ifndef CUDA_POWER_ARCH $(error I ERROR: For CUDA versions < 11.7 a target CUDA architecture must be explicitly provided via environment variable CUDA_DOCKER_ARCH, e.g. by running "export CUDA_DOCKER_ARCH=compute_XX" on Unix-like systems, where XX is the minimum compute capability that the code needs to run on. A list with compute capabilities can be found here: https://developer.nvidia.com/cuda-gpus ) endif # CUDA_POWER_ARCH endif # CUDA_DOCKER_ARCH + endif # eq ($(shell echo "$(CUDA_VERSION) < 11.7" | bc),1) -endif # LLAMA_CUDA +endif # GGML_CUDA $(info ) -ifdef LLAMA_CUBLAS -$(info !!!!) -$(info LLAMA_CUBLAS is deprecated and will be removed in the future. Use LLAMA_CUDA instead.) -$(info !!!!) +ifdef DEPRECATE_WARNING +$(info !!! DEPRECATION WARNING !!!) +$(info The following LLAMA_ options are deprecated and will be removed in the future. Use the GGML_ prefix instead) +$(info - LLAMA_CUDA) +$(info - LLAMA_METAL) +$(info - LLAMA_METAL_EMBED_LIBRARY) +$(info - LLAMA_OPENMP) +$(info - LLAMA_RPC) +$(info - LLAMA_SYCL) +$(info - LLAMA_SYCL_F16) +$(info - LLAMA_OPENBLAS) +$(info - LLAMA_OPENBLAS64) +$(info - LLAMA_BLIS) +$(info - LLAMA_NO_LLAMAFILE) +$(info - LLAMA_NO_ACCELERATE) +$(info - LLAMA_NO_OPENMP) +$(info - LLAMA_NO_METAL) $(info ) endif # -# Build library +# Build libraries # -ggml.o: ggml.c ggml.h ggml-cuda.h +# ggml + +ggml/src/ggml.o: \ + ggml/src/ggml.c \ + ggml/include/ggml.h $(CC) $(CFLAGS) -c $< -o $@ -ggml-alloc.o: ggml-alloc.c ggml.h ggml-alloc.h +ggml/src/ggml-alloc.o: \ + ggml/src/ggml-alloc.c \ + ggml/include/ggml.h \ + ggml/include/ggml-alloc.h $(CC) $(CFLAGS) -c $< -o $@ -ggml-backend.o: ggml-backend.c ggml.h ggml-backend.h +ggml/src/ggml-backend.o: \ + ggml/src/ggml-backend.c \ + ggml/include/ggml.h \ + ggml/include/ggml-backend.h $(CC) $(CFLAGS) -c $< -o $@ -ggml-quants.o: ggml-quants.c ggml.h ggml-quants.h ggml-common.h +ggml/src/ggml-quants.o: \ + ggml/src/ggml-quants.c \ + ggml/include/ggml.h \ + ggml/src/ggml-quants.h \ + ggml/src/ggml-common.h $(CC) $(CFLAGS) -c $< -o $@ -ggml-blas.o: ggml-blas.cpp ggml-blas.h +ggml/src/ggml-blas.o: \ + ggml/src/ggml-blas.cpp \ + ggml/include/ggml-blas.h $(CXX) $(CXXFLAGS) -c $< -o $@ -unicode.o: unicode.cpp unicode.h +ifndef GGML_NO_LLAMAFILE +ggml/src/sgemm.o: \ + ggml/src/sgemm.cpp \ + ggml/src/sgemm.h \ + ggml/include/ggml.h $(CXX) $(CXXFLAGS) -c $< -o $@ +endif # GGML_NO_LLAMAFILE -unicode-data.o: unicode-data.cpp unicode-data.h +ifdef GGML_RPC +ggml/src/ggml-rpc.o: \ + ggml/src/ggml-rpc.cpp \ + ggml/include/ggml-rpc.h $(CXX) $(CXXFLAGS) -c $< -o $@ +endif # GGML_RPC + +$(LIB_GGML): \ + $(OBJ_GGML) + $(CXX) $(CXXFLAGS) -shared -fPIC -o $@ $^ $(LDFLAGS) -llama.o: llama.cpp unicode.h ggml.h ggml-alloc.h ggml-backend.h ggml-cuda.h ggml-metal.h llama.h +$(LIB_GGML_S): \ + $(OBJ_GGML) + ar rcs $(LIB_GGML_S) $^ + +# llama + +src/unicode.o: \ + src/unicode.cpp \ + src/unicode.h $(CXX) $(CXXFLAGS) -c $< -o $@ -common.o: common/common.cpp $(COMMON_H_DEPS) +src/unicode-data.o: \ + src/unicode-data.cpp \ + src/unicode-data.h $(CXX) $(CXXFLAGS) -c $< -o $@ -sampling.o: common/sampling.cpp $(COMMON_H_DEPS) +src/llama.o: \ + src/llama.cpp \ + src/unicode.h \ + include/llama.h \ + ggml/include/ggml-cuda.h \ + ggml/include/ggml-metal.h \ + ggml/include/ggml.h \ + ggml/include/ggml-alloc.h \ + ggml/include/ggml-backend.h + $(CXX) $(CXXFLAGS) -c $< -o $@ + +$(LIB_LLAMA): \ + $(OBJ_LLAMA) \ + $(LIB_GGML) + $(CXX) $(CXXFLAGS) -shared -fPIC -o $@ $^ $(LDFLAGS) + +$(LIB_LLAMA_S): \ + $(OBJ_LLAMA) + ar rcs $(LIB_LLAMA_S) $^ + +# common + +common/common.o: \ + common/common.cpp \ + common/common.h \ + common/console.h \ + common/sampling.h \ + common/json.hpp \ + common/json-schema-to-grammar.h \ + include/llama.h $(CXX) $(CXXFLAGS) -c $< -o $@ -console.o: common/console.cpp common/console.h +common/sampling.o: \ + common/sampling.cpp \ + common/sampling.h \ + include/llama.h $(CXX) $(CXXFLAGS) -c $< -o $@ -grammar-parser.o: common/grammar-parser.cpp common/grammar-parser.h +common/console.o: \ + common/console.cpp \ + common/console.h $(CXX) $(CXXFLAGS) -c $< -o $@ -json-schema-to-grammar.o: common/json-schema-to-grammar.cpp common/json-schema-to-grammar.h +common/grammar-parser.o: \ + common/grammar-parser.cpp \ + common/grammar-parser.h $(CXX) $(CXXFLAGS) -c $< -o $@ -train.o: common/train.cpp common/train.h +common/json-schema-to-grammar.o: \ + common/json-schema-to-grammar.cpp \ + common/json-schema-to-grammar.h $(CXX) $(CXXFLAGS) -c $< -o $@ -ngram-cache.o: common/ngram-cache.cpp common/ngram-cache.h +common/train.o: \ + common/train.cpp \ + common/train.h $(CXX) $(CXXFLAGS) -c $< -o $@ -libllama.so: llama.o ggml.o $(OBJS) +common/ngram-cache.o: \ + common/ngram-cache.cpp \ + common/ngram-cache.h + $(CXX) $(CXXFLAGS) -c $< -o $@ + +$(LIB_COMMON): \ + $(OBJ_COMMON) \ + $(LIB_LLAMA) \ + $(LIB_GGML) $(CXX) $(CXXFLAGS) -shared -fPIC -o $@ $^ $(LDFLAGS) -libllama.a: llama.o ggml.o $(OBJS) $(COMMON_DEPS) - ar rcs libllama.a llama.o ggml.o $(OBJS) $(COMMON_DEPS) +$(LIB_COMMON_S): \ + $(OBJ_COMMON) + ar rcs $(LIB_COMMON_S) $^ clean: - rm -vrf *.o tests/*.o *.so *.a *.dll common/build-info.cpp *.dot $(COV_TARGETS) $(BUILD_TARGETS) $(TEST_TARGETS) - rm -vrf ggml-cuda/*.o - rm -vrf ggml-cuda/template-instances/*.o + rm -vrf *.dot $(BUILD_TARGETS) $(TEST_TARGETS) + rm -rvf src/*.o + rm -rvf tests/*.o + rm -rvf examples/*.o + rm -rvf *.a + rm -rvf *.dll + rm -rvf *.so + rm -rvf *.dot + rm -rvf ggml/*.a + rm -rvf ggml/*.dll + rm -rvf ggml/*.so + rm -vrf ggml/src/*.o + rm -rvf common/build-info.cpp + rm -vrf ggml/src/ggml-metal-embed.metal + rm -vrf ggml/src/ggml-cuda/*.o + rm -vrf ggml/src/ggml-cuda/template-instances/*.o + rm -rvf $(BUILD_TARGETS) + rm -rvf $(TEST_TARGETS) find examples pocs -type f -name "*.o" -delete # @@ -847,162 +1100,233 @@ clean: # Helper function that replaces .c, .cpp, and .cu file endings with .o: GET_OBJ_FILE = $(patsubst %.c,%.o,$(patsubst %.cpp,%.o,$(patsubst %.cu,%.o,$(1)))) -llama-cli: examples/main/main.cpp ggml.o llama.o $(COMMON_DEPS) console.o grammar-parser.o $(OBJS) +llama-cli: examples/main/main.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) @echo @echo '==== Run ./llama-cli -h for help. ====' @echo -llama-infill: examples/infill/infill.cpp ggml.o llama.o $(COMMON_DEPS) console.o grammar-parser.o $(OBJS) +llama-infill: examples/infill/infill.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-simple: examples/simple/simple.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-simple: examples/simple/simple.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-tokenize: examples/tokenize/tokenize.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-tokenize: examples/tokenize/tokenize.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-batched: examples/batched/batched.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-batched: examples/batched/batched.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-batched-bench: examples/batched-bench/batched-bench.cpp build-info.o ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-batched-bench: examples/batched-bench/batched-bench.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-quantize: examples/quantize/quantize.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-quantize: examples/quantize/quantize.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-quantize-stats: examples/quantize-stats/quantize-stats.cpp build-info.o ggml.o llama.o $(OBJS) +llama-quantize-stats: examples/quantize-stats/quantize-stats.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-perplexity: examples/perplexity/perplexity.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-perplexity: examples/perplexity/perplexity.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-imatrix: examples/imatrix/imatrix.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-imatrix: examples/imatrix/imatrix.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-embedding: examples/embedding/embedding.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-embedding: examples/embedding/embedding.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-gritlm: examples/gritlm/gritlm.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-gritlm: examples/gritlm/gritlm.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-save-load-state: examples/save-load-state/save-load-state.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-save-load-state: examples/save-load-state/save-load-state.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-server: examples/server/server.cpp examples/server/utils.hpp examples/server/httplib.h common/json.hpp examples/server/colorthemes.css.hpp examples/server/style.css.hpp examples/server/theme-beeninorder.css.hpp examples/server/theme-ketivah.css.hpp examples/server/theme-mangotango.css.hpp examples/server/theme-playground.css.hpp examples/server/theme-polarnight.css.hpp examples/server/theme-snowstorm.css.hpp examples/server/index.html.hpp examples/server/index-new.html.hpp examples/server/index.js.hpp examples/server/completion.js.hpp examples/server/system-prompts.js.hpp examples/server/prompt-formats.js.hpp examples/server/json-schema-to-grammar.mjs.hpp common/stb_image.h ggml.o llama.o $(COMMON_DEPS) grammar-parser.o $(OBJS) +llama-gguf: examples/gguf/gguf.cpp \ + $(OBJ_GGML) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) - $(CXX) $(CXXFLAGS) $(filter-out %.h %.hpp $<,$^) -Iexamples/server $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(LWINSOCK2) - -# Portable equivalent of `cd examples/server/public && xxd -i $(notdir $<) ../$(notdir $<).hpp`: -examples/server/%.hpp: examples/server/public/% Makefile - @( export NAME=$(subst .,_,$(subst -,_,$(notdir $<))) && \ - echo "unsigned char $${NAME}[] = {" && \ - cat $< | od -v -t x1 -An | sed -E 's/([0-9a-fA-F]+)/0x\1, /g' && \ - echo "};" && \ - echo "unsigned int $${NAME}_len = $(shell cat $< | wc -c );" \ - ) > $@ + $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-gguf: examples/gguf/gguf.cpp ggml.o $(OBJS) +llama-gguf-split: examples/gguf-split/gguf-split.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-gguf-split: examples/gguf-split/gguf-split.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-eval-callback: examples/eval-callback/eval-callback.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-eval-callback: examples/eval-callback/eval-callback.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-cvector-generator: examples/cvector-generator/cvector-generator.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-cvector-generator: examples/cvector-generator/cvector-generator.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-train-text-from-scratch: examples/train-text-from-scratch/train-text-from-scratch.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-train-text-from-scratch: examples/train-text-from-scratch/train-text-from-scratch.cpp ggml.o llama.o $(COMMON_DEPS) train.o $(OBJS) +llama-convert-llama2c-to-ggml: examples/convert-llama2c-to-ggml/convert-llama2c-to-ggml.cpp \ + $(OBJ_GGML) $(OBJ_LLAMA) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-convert-llama2c-to-ggml: examples/convert-llama2c-to-ggml/convert-llama2c-to-ggml.cpp ggml.o llama.o $(OBJS) +llama-bench: examples/llama-bench/llama-bench.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-bench: examples/llama-bench/llama-bench.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-baby-llama: examples/baby-llama/baby-llama.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -libllava.a: examples/llava/llava.cpp examples/llava/llava.h examples/llava/clip.cpp examples/llava/clip.h common/stb_image.h common/base64.hpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) - $(CXX) $(CXXFLAGS) -static -fPIC -c $< -o $@ -Wno-cast-qual - -llama-llava-cli: examples/llava/llava-cli.cpp examples/llava/clip.h examples/llava/clip.cpp examples/llava/llava.h examples/llava/llava.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-finetune: examples/finetune/finetune.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) - $(CXX) $(CXXFLAGS) -c examples/llava/clip.cpp -o $(call GET_OBJ_FILE, examples/llava/clip.cpp) -Wno-cast-qual - $(CXX) $(CXXFLAGS) -c examples/llava/llava.cpp -o $(call GET_OBJ_FILE, examples/llava/llava.cpp) - $(CXX) $(CXXFLAGS) $(filter-out %.h $< examples/llava/clip.cpp examples/llava/llava.cpp,$^) $(call GET_OBJ_FILE, $<) $(call GET_OBJ_FILE, examples/llava/clip.cpp) $(call GET_OBJ_FILE, examples/llava/llava.cpp) -o $@ $(LDFLAGS) + $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-baby-llama: examples/baby-llama/baby-llama.cpp ggml.o llama.o $(COMMON_DEPS) train.o $(OBJS) +llama-export-lora: examples/export-lora/export-lora.cpp \ + $(OBJ_GGML) common/log.h $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-finetune: examples/finetune/finetune.cpp ggml.o llama.o $(COMMON_DEPS) train.o $(OBJS) +llama-retrieval: examples/retrieval/retrieval.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-export-lora: examples/export-lora/export-lora.cpp ggml.o common/common.h $(OBJS) +llama-speculative: examples/speculative/speculative.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-retrieval: examples/retrieval/retrieval.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-parallel: examples/parallel/parallel.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-speculative: examples/speculative/speculative.cpp ggml.o llama.o $(COMMON_DEPS) grammar-parser.o $(OBJS) +llama-lookahead: examples/lookahead/lookahead.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-parallel: examples/parallel/parallel.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-lookup: examples/lookup/lookup.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-lookahead: examples/lookahead/lookahead.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +llama-lookup-create: examples/lookup/lookup-create.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-lookup: examples/lookup/lookup.cpp ggml.o llama.o ngram-cache.o $(COMMON_DEPS) $(OBJS) +llama-lookup-merge: examples/lookup/lookup-merge.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-lookup-create: examples/lookup/lookup-create.cpp ggml.o llama.o ngram-cache.o $(COMMON_DEPS) $(OBJS) +llama-lookup-stats: examples/lookup/lookup-stats.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-lookup-merge: examples/lookup/lookup-merge.cpp ggml.o llama.o ngram-cache.o $(COMMON_DEPS) $(OBJS) +llama-passkey: examples/passkey/passkey.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-lookup-stats: examples/lookup/lookup-stats.cpp ggml.o llama.o ngram-cache.o $(COMMON_DEPS) $(OBJS) +llama-gbnf-validator: examples/gbnf-validator/gbnf-validator.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -llama-passkey: examples/passkey/passkey.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +ifdef GGML_RPC +rpc-server: examples/rpc/rpc-server.cpp \ + $(OBJ_GGML) + $(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS) +endif # GGML_RPC + +llama-server: \ + examples/server/server.cpp \ + examples/server/utils.hpp \ + examples/server/httplib.h \ + examples/server/colorthemes.css.hpp \ + examples/server/style.css.hpp \ + examples/server/theme-beeninorder.css.hpp \ + examples/server/theme-ketivah.css.hpp \ + examples/server/theme-mangotango.css.hpp \ + examples/server/theme-playground.css.hpp \ + examples/server/theme-polarnight.css.hpp \ + examples/server/theme-snowstorm.css.hpp \ + examples/server/index.html.hpp \ + examples/server/index-new.html.hpp \ + examples/server/index.js.hpp \ + examples/server/completion.js.hpp \ + examples/server/system-prompts.js.hpp \ + examples/server/prompt-formats.js.hpp \ + examples/server/json-schema-to-grammar.mjs.hpp \ + common/json.hpp \ + common/stb_image.h \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) - $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) + $(CXX) $(CXXFLAGS) $(filter-out %.h %.hpp $<,$^) -Iexamples/server $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(LWINSOCK2) + +# Portable equivalent of `cd examples/server/public && xxd -i $(notdir $<) ../$(notdir $<).hpp`: +examples/server/%.hpp: examples/server/public/% Makefile + @( export NAME=$(subst .,_,$(subst -,_,$(notdir $<))) && \ + echo "unsigned char $${NAME}[] = {" && \ + cat $< | od -v -t x1 -An | sed -E 's/([0-9a-fA-F]+)/0x\1, /g' && \ + echo "};" && \ + echo "unsigned int $${NAME}_len = $(shell cat $< | wc -c );" \ + ) > $@ -llama-gbnf-validator: examples/gbnf-validator/gbnf-validator.cpp ggml.o llama.o $(COMMON_DEPS) grammar-parser.o $(OBJS) +libllava.a: examples/llava/llava.cpp \ + examples/llava/llava.h \ + examples/llava/clip.cpp \ + examples/llava/clip.h \ + common/stb_image.h \ + common/base64.hpp \ + $(OBJ_ALL) + $(CXX) $(CXXFLAGS) -static -fPIC -c $< -o $@ -Wno-cast-qual + +llama-llava-cli: examples/llava/llava-cli.cpp \ + examples/llava/clip.h \ + examples/llava/clip.cpp \ + examples/llava/llava.h \ + examples/llava/llava.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) - $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) + $(CXX) $(CXXFLAGS) -c examples/llava/clip.cpp -o $(call GET_OBJ_FILE, examples/llava/clip.cpp) -Wno-cast-qual + $(CXX) $(CXXFLAGS) -c examples/llava/llava.cpp -o $(call GET_OBJ_FILE, examples/llava/llava.cpp) + $(CXX) $(CXXFLAGS) $(filter-out %.h $< examples/llava/clip.cpp examples/llava/llava.cpp,$^) $(call GET_OBJ_FILE, $<) $(call GET_OBJ_FILE, examples/llava/clip.cpp) $(call GET_OBJ_FILE, examples/llava/llava.cpp) -o $@ $(LDFLAGS) ifeq ($(UNAME_S),Darwin) swift: examples/batched.swift @@ -1017,7 +1341,7 @@ common/build-info.cpp: $(wildcard .git/index) scripts/build-info.sh rm $@.tmp; \ fi -build-info.o: common/build-info.cpp +common/build-info.o: common/build-info.cpp $(CXX) $(CXXFLAGS) -c $(filter-out %.h,$^) -o $@ # @@ -1026,7 +1350,8 @@ build-info.o: common/build-info.cpp tests: $(TEST_TARGETS) -llama-benchmark-matmult: examples/benchmark/benchmark-matmult.cpp build-info.o ggml.o $(OBJS) +llama-benchmark-matmult: examples/benchmark/benchmark-matmult.cpp \ + $(OBJ_GGML) common/build-info.o $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) @@ -1035,85 +1360,108 @@ run-benchmark-matmult: llama-benchmark-matmult .PHONY: run-benchmark-matmult swift -llama-vdot: pocs/vdot/vdot.cpp ggml.o $(OBJS) - $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) - $(CXX) $(CXXFLAGS) $(filter-out $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) - -llama-q8dot: pocs/vdot/q8dot.cpp ggml.o $(OBJS) - $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) - $(CXX) $(CXXFLAGS) $(filter-out $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) - -tests/test-llama-grammar: tests/test-llama-grammar.cpp ggml.o grammar-parser.o $(OBJS) +tests/test-llama-grammar: tests/test-llama-grammar.cpp \ + $(OBJ_GGML) $(OBJ_COMMON) src/unicode.o src/unicode-data.o $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -tests/test-grammar-parser: tests/test-grammar-parser.cpp ggml.o llama.o grammar-parser.o $(OBJS) +tests/test-grammar-parser: tests/test-grammar-parser.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -tests/test-grammar-integration: tests/test-grammar-integration.cpp json-schema-to-grammar.o ggml.o llama.o grammar-parser.o $(OBJS) +tests/test-grammar-integration: tests/test-grammar-integration.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -tests/test-double-float: tests/test-double-float.cpp ggml.o $(OBJS) +tests/test-double-float: tests/test-double-float.cpp $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -tests/test-json-schema-to-grammar: tests/test-json-schema-to-grammar.cpp json-schema-to-grammar.o ggml.o llama.o grammar-parser.o $(OBJS) +tests/test-json-schema-to-grammar: tests/test-json-schema-to-grammar.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -Iexamples/server -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -tests/test-grad0: tests/test-grad0.cpp ggml.o $(OBJS) +tests/test-grad0: tests/test-grad0.cpp \ + $(OBJ_GGML) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -tests/test-opt: tests/test-opt.cpp ggml.o $(OBJS) +tests/test-opt: tests/test-opt.cpp \ + $(OBJ_GGML) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -tests/test-quantize-fns: tests/test-quantize-fns.cpp ggml.o $(OBJS) +tests/test-quantize-fns: tests/test-quantize-fns.cpp \ + $(OBJ_GGML) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -tests/test-quantize-perf: tests/test-quantize-perf.cpp ggml.o $(OBJS) +tests/test-quantize-perf: tests/test-quantize-perf.cpp \ + $(OBJ_GGML) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -tests/test-sampling: tests/test-sampling.cpp ggml.o llama.o $(OBJS) +tests/test-sampling: tests/test-sampling.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -tests/test-tokenizer-0: tests/test-tokenizer-0.cpp ggml.o llama.o $(COMMON_DEPS) console.o $(OBJS) +tests/test-tokenizer-0: tests/test-tokenizer-0.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -tests/test-tokenizer-1-bpe: tests/test-tokenizer-1-bpe.cpp ggml.o llama.o $(COMMON_DEPS) console.o $(OBJS) +tests/test-tokenizer-1-bpe: tests/test-tokenizer-1-bpe.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -tests/test-tokenizer-1-spm: tests/test-tokenizer-1-spm.cpp ggml.o llama.o $(COMMON_DEPS) console.o $(OBJS) +tests/test-tokenizer-1-spm: tests/test-tokenizer-1-spm.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -tests/test-rope: tests/test-rope.cpp ggml.o $(OBJS) +tests/test-rope: tests/test-rope.cpp ggml/src/ggml.o \ + $(OBJ_GGML) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -tests/test-c.o: tests/test-c.c llama.h +tests/test-c.o: tests/test-c.c include/llama.h $(CC) $(CFLAGS) -c $(filter-out %.h,$^) -o $@ -tests/test-backend-ops: tests/test-backend-ops.cpp ggml.o $(OBJS) +tests/test-backend-ops: tests/test-backend-ops.cpp \ + $(OBJ_GGML) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -tests/test-model-load-cancel: tests/test-model-load-cancel.cpp ggml.o llama.o tests/get-model.cpp $(COMMON_DEPS) $(OBJS) +tests/test-model-load-cancel: tests/test-model-load-cancel.cpp tests/get-model.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -tests/test-autorelease: tests/test-autorelease.cpp ggml.o llama.o tests/get-model.cpp $(COMMON_DEPS) $(OBJS) +tests/test-autorelease: tests/test-autorelease.cpp tests/get-model.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) -tests/test-chat-template: tests/test-chat-template.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) +tests/test-chat-template: tests/test-chat-template.cpp \ + $(OBJ_ALL) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) + +# +# PoCs +# + +llama-vdot: pocs/vdot/vdot.cpp ggml/src/ggml.o \ + $(OBJ_GGML) + $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) + $(CXX) $(CXXFLAGS) $(filter-out $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) + +llama-q8dot: pocs/vdot/q8dot.cpp ggml/src/ggml.o \ + $(OBJ_GGML) + $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) + $(CXX) $(CXXFLAGS) $(filter-out $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) diff --git a/Package.swift b/Package.swift index 183e647575b42..77fed86df3105 100644 --- a/Package.swift +++ b/Package.swift @@ -3,14 +3,13 @@ import PackageDescription var sources = [ - "ggml.c", - "sgemm.cpp", - "llama.cpp", - "unicode.cpp", - "unicode-data.cpp", - "ggml-alloc.c", - "ggml-backend.c", - "ggml-quants.c", + "src/llama.cpp", + "src/unicode.cpp", + "src/unicode-data.cpp", + "ggml/src/ggml.c", + "ggml/src/ggml-alloc.c", + "ggml/src/ggml-backend.c", + "ggml/src/ggml-quants.c", ] var resources: [Resource] = [] @@ -26,8 +25,8 @@ var cSettings: [CSetting] = [ ] #if canImport(Darwin) -sources.append("ggml-metal.m") -resources.append(.process("ggml-metal.metal")) +sources.append("ggml/src/ggml-metal.m") +resources.append(.process("ggml/src/ggml-metal.metal")) linkerSettings.append(.linkedFramework("Accelerate")) cSettings.append( contentsOf: [ @@ -63,8 +62,6 @@ let package = Package( "models", "tests", "CMakeLists.txt", - "ggml-cuda.cu", - "ggml-cuda.h", "Makefile" ], sources: sources, diff --git a/README-sycl.md b/README-sycl.md index b7e2bb12a68e8..885983e92277e 100644 --- a/README-sycl.md +++ b/README-sycl.md @@ -115,12 +115,12 @@ The docker build option is currently limited to *intel GPU* targets. ### Build image ```sh # Using FP16 -docker build -t llama-cpp-sycl --build-arg="LLAMA_SYCL_F16=ON" -f .devops/llama-cli-intel.Dockerfile . +docker build -t llama-cpp-sycl --build-arg="GGML_SYCL_F16=ON" -f .devops/llama-cli-intel.Dockerfile . ``` *Notes*: -To build in default FP32 *(Slower than FP16 alternative)*, you can remove the `--build-arg="LLAMA_SYCL_F16=ON"` argument from the previous command. +To build in default FP32 *(Slower than FP16 alternative)*, you can remove the `--build-arg="GGML_SYCL_F16=ON"` argument from the previous command. You can also use the `.devops/llama-server-intel.Dockerfile`, which builds the *"server"* alternative. @@ -244,10 +244,10 @@ source /opt/intel/oneapi/setvars.sh # Build LLAMA with MKL BLAS acceleration for intel GPU # Option 1: Use FP32 (recommended for better performance in most cases) -cmake -B build -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx +cmake -B build -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx # Option 2: Use FP16 -cmake -B build -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL_F16=ON +cmake -B build -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL_F16=ON # build all binary cmake --build build --config Release -j -v @@ -264,10 +264,10 @@ export CPLUS_INCLUDE_DIR=/path/to/oneMKL/include:$CPLUS_INCLUDE_DIR # Build LLAMA with Nvidia BLAS acceleration through SYCL # Option 1: Use FP32 (recommended for better performance in most cases) -cmake -B build -DLLAMA_SYCL=ON -DLLAMA_SYCL_TARGET=NVIDIA -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx +cmake -B build -DGGML_SYCL=ON -DGGML_SYCL_TARGET=NVIDIA -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx # Option 2: Use FP16 -cmake -B build -DLLAMA_SYCL=ON -DLLAMA_SYCL_TARGET=NVIDIA -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL_F16=ON +cmake -B build -DGGML_SYCL=ON -DGGML_SYCL_TARGET=NVIDIA -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL_F16=ON # build all binary cmake --build build --config Release -j -v @@ -422,10 +422,10 @@ On the oneAPI command line window, step into the llama.cpp main directory and ru @call "C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64 --force # Option 1: Use FP32 (recommended for better performance in most cases) -cmake -B build -G "Ninja" -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=cl -DCMAKE_CXX_COMPILER=icx -DCMAKE_BUILD_TYPE=Release +cmake -B build -G "Ninja" -DGGML_SYCL=ON -DCMAKE_C_COMPILER=cl -DCMAKE_CXX_COMPILER=icx -DCMAKE_BUILD_TYPE=Release # Option 2: Or FP16 -cmake -B build -G "Ninja" -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=cl -DCMAKE_CXX_COMPILER=icx -DCMAKE_BUILD_TYPE=Release -DLLAMA_SYCL_F16=ON +cmake -B build -G "Ninja" -DGGML_SYCL=ON -DCMAKE_C_COMPILER=cl -DCMAKE_CXX_COMPILER=icx -DCMAKE_BUILD_TYPE=Release -DGGML_SYCL_F16=ON cmake --build build --config Release -j ``` @@ -440,7 +440,7 @@ Or, use CMake presets to build: cmake --preset x64-windows-sycl-release cmake --build build-x64-windows-sycl-release -j --target llama-cli -cmake -DLLAMA_SYCL_F16=ON --preset x64-windows-sycl-release +cmake -DGGML_SYCL_F16=ON --preset x64-windows-sycl-release cmake --build build-x64-windows-sycl-release -j --target llama-cli cmake --preset x64-windows-sycl-debug @@ -544,9 +544,9 @@ use 1 SYCL GPUs: [0] with Max compute units:512 | Name | Value | Function | |--------------------|-----------------------------------|---------------------------------------------| -| LLAMA_SYCL | ON (mandatory) | Enable build with SYCL code path. | -| LLAMA_SYCL_TARGET | INTEL *(default)* \| NVIDIA | Set the SYCL target device type. | -| LLAMA_SYCL_F16 | OFF *(default)* \|ON *(optional)* | Enable FP16 build with SYCL code path. | +| GGML_SYCL | ON (mandatory) | Enable build with SYCL code path. | +| GGML_SYCL_TARGET | INTEL *(default)* \| NVIDIA | Set the SYCL target device type. | +| GGML_SYCL_F16 | OFF *(default)* \|ON *(optional)* | Enable FP16 build with SYCL code path. | | CMAKE_C_COMPILER | icx | Set *icx* compiler for SYCL code path. | | CMAKE_CXX_COMPILER | icpx *(Linux)*, icx *(Windows)* | Set `icpx/icx` compiler for SYCL code path. | diff --git a/README.md b/README.md index 95d970d8382b3..6ca5ba43ea427 100644 --- a/README.md +++ b/README.md @@ -415,7 +415,7 @@ Flox follows the nixpkgs build of llama.cpp. ### Metal Build On MacOS, Metal is enabled by default. Using Metal makes the computation run on the GPU. -To disable the Metal build at compile time use the `LLAMA_NO_METAL=1` flag or the `LLAMA_METAL=OFF` cmake option. +To disable the Metal build at compile time use the `GGML_NO_METAL=1` flag or the `GGML_METAL=OFF` cmake option. When built with Metal support, you can explicitly disable GPU inference with the `--n-gpu-layers|-ngl 0` command-line argument. @@ -435,7 +435,7 @@ Building the program with BLAS support may lead to some performance improvements - Using `make`: - On Linux: ```bash - make LLAMA_OPENBLAS=1 + make GGML_OPENBLAS=1 ``` - On Windows: @@ -450,13 +450,13 @@ Building the program with BLAS support may lead to some performance improvements 8. From here you can run: ```bash - make LLAMA_OPENBLAS=1 + make GGML_OPENBLAS=1 ``` - Using `CMake` on Linux: ```bash - cmake -B build -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS + cmake -B build -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS cmake --build build --config Release ``` @@ -475,10 +475,10 @@ Building the program with BLAS support may lead to some performance improvements Building through oneAPI compilers will make avx_vnni instruction set available for intel processors that do not support avx512 and avx512_vnni. Please note that this build config **does not support Intel GPU**. For Intel GPU support, please refer to [llama.cpp for SYCL](./README-sycl.md). - Using manual oneAPI installation: - By default, `LLAMA_BLAS_VENDOR` is set to `Generic`, so if you already sourced intel environment script and assign `-DLLAMA_BLAS=ON` in cmake, the mkl version of Blas will automatically been selected. Otherwise please install oneAPI and follow the below steps: + By default, `GGML_BLAS_VENDOR` is set to `Generic`, so if you already sourced intel environment script and assign `-DGGML_BLAS=ON` in cmake, the mkl version of Blas will automatically been selected. Otherwise please install oneAPI and follow the below steps: ```bash source /opt/intel/oneapi/setvars.sh # You can skip this step if in oneapi-basekit docker image, only required for manual installation - cmake -B build -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=Intel10_64lp -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_NATIVE=ON + cmake -B build -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=Intel10_64lp -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_NATIVE=ON cmake --build build --config Release ``` @@ -495,28 +495,28 @@ Building the program with BLAS support may lead to some performance improvements - Using `make`: ```bash - make LLAMA_CUDA=1 + make GGML_CUDA=1 ``` - Using `CMake`: ```bash - cmake -B build -DLLAMA_CUDA=ON + cmake -B build -DGGML_CUDA=ON cmake --build build --config Release ``` The environment variable [`CUDA_VISIBLE_DEVICES`](https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#env-vars) can be used to specify which GPU(s) will be used. The following compilation options are also available to tweak performance: - | Option | Legal values | Default | Description | - |--------------------------------|------------------------|---------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| - | LLAMA_CUDA_FORCE_DMMV | Boolean | false | Force the use of dequantization + matrix vector multiplication kernels instead of using kernels that do matrix vector multiplication on quantized data. By default the decision is made based on compute capability (MMVQ for 6.1/Pascal/GTX 1000 or higher). Does not affect k-quants. | - | LLAMA_CUDA_DMMV_X | Positive integer >= 32 | 32 | Number of values in x direction processed by the CUDA dequantization + matrix vector multiplication kernel per iteration. Increasing this value can improve performance on fast GPUs. Power of 2 heavily recommended. Does not affect k-quants. | - | LLAMA_CUDA_MMV_Y | Positive integer | 1 | Block size in y direction for the CUDA mul mat vec kernels. Increasing this value can improve performance on fast GPUs. Power of 2 recommended. | - | LLAMA_CUDA_FORCE_MMQ | Boolean | false | Force the use of custom matrix multiplication kernels for quantized models instead of FP16 cuBLAS even if there is no int8 tensor core implementation available (affects V100, RDNA3). MMQ kernels are enabled by default on GPUs with int8 tensor core support. With MMQ force enabled, speed for large batch sizes will be worse but VRAM consumption will be lower. | - | LLAMA_CUDA_FORCE_CUBLAS | Boolean | false | Force the use of FP16 cuBLAS instead of custom matrix multiplication kernels for quantized models | - | LLAMA_CUDA_F16 | Boolean | false | If enabled, use half-precision floating point arithmetic for the CUDA dequantization + mul mat vec kernels and for the q4_1 and q5_1 matrix matrix multiplication kernels. Can improve performance on relatively recent GPUs. | - | LLAMA_CUDA_KQUANTS_ITER | 1 or 2 | 2 | Number of values processed per iteration and per CUDA thread for Q2_K and Q6_K quantization formats. Setting this value to 1 can improve performance for slow GPUs. | - | LLAMA_CUDA_PEER_MAX_BATCH_SIZE | Positive integer | 128 | Maximum batch size for which to enable peer access between multiple GPUs. Peer access requires either Linux or NVLink. When using NVLink enabling peer access for larger batch sizes is potentially beneficial. | - | LLAMA_CUDA_FA_ALL_QUANTS | Boolean | false | Compile support for all KV cache quantization type (combinations) for the FlashAttention CUDA kernels. More fine-grained control over KV cache size but compilation takes much longer. | + | Option | Legal values | Default | Description | + |-------------------------------|------------------------|---------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| + | GGML_CUDA_FORCE_DMMV | Boolean | false | Force the use of dequantization + matrix vector multiplication kernels instead of using kernels that do matrix vector multiplication on quantized data. By default the decision is made based on compute capability (MMVQ for 6.1/Pascal/GTX 1000 or higher). Does not affect k-quants. | + | GGML_CUDA_DMMV_X | Positive integer >= 32 | 32 | Number of values in x direction processed by the CUDA dequantization + matrix vector multiplication kernel per iteration. Increasing this value can improve performance on fast GPUs. Power of 2 heavily recommended. Does not affect k-quants. | + | GGML_CUDA_MMV_Y | Positive integer | 1 | Block size in y direction for the CUDA mul mat vec kernels. Increasing this value can improve performance on fast GPUs. Power of 2 recommended. | + | GGML_CUDA_FORCE_MMQ | Boolean | false | Force the use of custom matrix multiplication kernels for quantized models instead of FP16 cuBLAS even if there is no int8 tensor core implementation available (affects V100, RDNA3). MMQ kernels are enabled by default on GPUs with int8 tensor core support. With MMQ force enabled, speed for large batch sizes will be worse but VRAM consumption will be lower. | + | GGML_CUDA_FORCE_CUBLAS | Boolean | false | Force the use of FP16 cuBLAS instead of custom matrix multiplication kernels for quantized models | + | GGML_CUDA_F16 | Boolean | false | If enabled, use half-precision floating point arithmetic for the CUDA dequantization + mul mat vec kernels and for the q4_1 and q5_1 matrix matrix multiplication kernels. Can improve performance on relatively recent GPUs. | + | GGML_CUDA_KQUANTS_ITER | 1 or 2 | 2 | Number of values processed per iteration and per CUDA thread for Q2_K and Q6_K quantization formats. Setting this value to 1 can improve performance for slow GPUs. | + | GGML_CUDA_PEER_MAX_BATCH_SIZE | Positive integer | 128 | Maximum batch size for which to enable peer access between multiple GPUs. Peer access requires either Linux or NVLink. When using NVLink enabling peer access for larger batch sizes is potentially beneficial. | + | GGML_CUDA_FA_ALL_QUANTS | Boolean | false | Compile support for all KV cache quantization type (combinations) for the FlashAttention CUDA kernels. More fine-grained control over KV cache size but compilation takes much longer. | - #### hipBLAS @@ -526,15 +526,15 @@ Building the program with BLAS support may lead to some performance improvements - Using `make`: ```bash - make LLAMA_HIPBLAS=1 + make GGML_HIPBLAS=1 ``` - Using `CMake` for Linux (assuming a gfx1030-compatible AMD GPU): ```bash HIPCXX="$(hipconfig -l)/clang" HIP_PATH="$(hipconfig -R)" \ - cmake -S . -B build -DLLAMA_HIPBLAS=ON -DAMDGPU_TARGETS=gfx1030 -DCMAKE_BUILD_TYPE=Release \ + cmake -S . -B build -DGGML_HIPBLAS=ON -DAMDGPU_TARGETS=gfx1030 -DCMAKE_BUILD_TYPE=Release \ && cmake --build build --config Release -- -j 16 ``` - On Linux it is also possible to use unified memory architecture (UMA) to share main memory between the CPU and integrated GPU by setting `-DLLAMA_HIP_UMA=ON`. + On Linux it is also possible to use unified memory architecture (UMA) to share main memory between the CPU and integrated GPU by setting `-DGGML_HIP_UMA=ON`. However, this hurts performance for non-integrated GPUs (but enables working with integrated GPUs). Note that if you get the following error: @@ -548,19 +548,19 @@ Building the program with BLAS support may lead to some performance improvements ```bash HIPCXX="$(hipconfig -l)/clang" HIP_PATH="$(hipconfig -p)" \ HIP_DEVICE_LIB_PATH= \ - cmake -S . -B build -DLLAMA_HIPBLAS=ON -DAMDGPU_TARGETS=gfx1030 -DCMAKE_BUILD_TYPE=Release \ + cmake -S . -B build -DGGML_HIPBLAS=ON -DAMDGPU_TARGETS=gfx1030 -DCMAKE_BUILD_TYPE=Release \ && cmake --build build -- -j 16 ``` - Using `make` (example for target gfx1030, build with 16 CPU threads): ```bash - make -j16 LLAMA_HIPBLAS=1 LLAMA_HIP_UMA=1 AMDGPU_TARGETS=gfx1030 + make -j16 GGML_HIPBLAS=1 GGML_HIP_UMA=1 AMDGPU_TARGETS=gfx1030 ``` - Using `CMake` for Windows (using x64 Native Tools Command Prompt for VS, and assuming a gfx1100-compatible AMD GPU): ```bash set PATH=%HIP_PATH%\bin;%PATH% - cmake -S . -B build -G Ninja -DAMDGPU_TARGETS=gfx1100 -DLLAMA_HIPBLAS=ON -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_BUILD_TYPE=Release + cmake -S . -B build -G Ninja -DAMDGPU_TARGETS=gfx1100 -DGGML_HIPBLAS=ON -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_BUILD_TYPE=Release cmake --build build ``` Make sure that `AMDGPU_TARGETS` is set to the GPU arch you want to compile for. The above example uses `gfx1100` that corresponds to Radeon RX 7900XTX/XT/GRE. You can find a list of targets [here](https://llvm.org/docs/AMDGPUUsage.html#processors) @@ -571,11 +571,11 @@ Building the program with BLAS support may lead to some performance improvements If your GPU is not officially supported you can use the environment variable [`HSA_OVERRIDE_GFX_VERSION`] set to a similar GPU, for example 10.3.0 on RDNA2 (e.g. gfx1030, gfx1031, or gfx1035) or 11.0.0 on RDNA3. The following compilation options are also available to tweak performance (yes, they refer to CUDA, not HIP, because it uses the same code as the cuBLAS version above): - | Option | Legal values | Default | Description | - |-------------------------|------------------------|---------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| - | LLAMA_CUDA_DMMV_X | Positive integer >= 32 | 32 | Number of values in x direction processed by the HIP dequantization + matrix vector multiplication kernel per iteration. Increasing this value can improve performance on fast GPUs. Power of 2 heavily recommended. Does not affect k-quants. | - | LLAMA_CUDA_MMV_Y | Positive integer | 1 | Block size in y direction for the HIP mul mat vec kernels. Increasing this value can improve performance on fast GPUs. Power of 2 recommended. Does not affect k-quants. | - | LLAMA_CUDA_KQUANTS_ITER | 1 or 2 | 2 | Number of values processed per iteration and per HIP thread for Q2_K and Q6_K quantization formats. Setting this value to 1 can improve performance for slow GPUs. | + | Option | Legal values | Default | Description | + |------------------------|------------------------|---------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| + | GGML_CUDA_DMMV_X | Positive integer >= 32 | 32 | Number of values in x direction processed by the HIP dequantization + matrix vector multiplication kernel per iteration. Increasing this value can improve performance on fast GPUs. Power of 2 heavily recommended. Does not affect k-quants. | + | GGML_CUDA_MMV_Y | Positive integer | 1 | Block size in y direction for the HIP mul mat vec kernels. Increasing this value can improve performance on fast GPUs. Power of 2 recommended. Does not affect k-quants. | + | GGML_CUDA_KQUANTS_ITER | 1 or 2 | 2 | Number of values processed per iteration and per HIP thread for Q2_K and Q6_K quantization formats. Setting this value to 1 can improve performance for slow GPUs. | - #### Vulkan @@ -613,7 +613,7 @@ Building the program with BLAS support may lead to some performance improvements Then, build llama.cpp using the cmake command below: ```bash - cmake -B build -DLLAMA_VULKAN=1 + cmake -B build -DGGML_VULKAN=1 cmake --build build --config Release # Test the output binary (with "-ngl 33" to offload all layers to GPU) ./bin/llama-cli -m "PATH_TO_MODEL" -p "Hi you how are you" -n 50 -e -ngl 33 -t 4 diff --git a/ci/run.sh b/ci/run.sh index 291c44f47b86d..e0cedb24f5a58 100755 --- a/ci/run.sh +++ b/ci/run.sh @@ -36,11 +36,11 @@ SRC=`pwd` CMAKE_EXTRA="-DLLAMA_FATAL_WARNINGS=ON" if [ ! -z ${GG_BUILD_METAL} ]; then - CMAKE_EXTRA="${CMAKE_EXTRA} -DLLAMA_METAL_SHADER_DEBUG=ON" + CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_METAL=ON" fi if [ ! -z ${GG_BUILD_CUDA} ]; then - CMAKE_EXTRA="${CMAKE_EXTRA} -DLLAMA_CUDA=1" + CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_CUDA=1" fi if [ ! -z ${GG_BUILD_SYCL} ]; then @@ -50,7 +50,7 @@ if [ ! -z ${GG_BUILD_SYCL} ]; then exit 1 fi - CMAKE_EXTRA="${CMAKE_EXTRA} -DLLAMA_SYCL=1 DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL_F16=ON" + CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_SYCL=1 DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL_F16=ON" fi ## helpers @@ -284,7 +284,7 @@ function gg_run_open_llama_7b_v2 { set -e - (time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} -DLLAMA_CUDA=1 .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log + (time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} -DGGML_CUDA=1 .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log (time make -j ) 2>&1 | tee -a $OUT/${ci}-make.log python3 ../examples/convert-legacy-llama.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf @@ -550,7 +550,7 @@ function gg_run_pythia_2_8b { set -e - (time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} -DLLAMA_CUDA=1 .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log + (time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} -DGGML_CUDA=1 .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log (time make -j ) 2>&1 | tee -a $OUT/${ci}-make.log python3 ../convert-hf-to-gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf diff --git a/scripts/build-info.cmake b/cmake/build-info.cmake similarity index 100% rename from scripts/build-info.cmake rename to cmake/build-info.cmake diff --git a/cmake/git-vars.cmake b/cmake/git-vars.cmake new file mode 100644 index 0000000000000..1a4c24ebf6ade --- /dev/null +++ b/cmake/git-vars.cmake @@ -0,0 +1,22 @@ +find_package(Git) + +# the commit's SHA1 +execute_process(COMMAND + "${GIT_EXECUTABLE}" describe --match=NeVeRmAtCh --always --abbrev=8 + WORKING_DIRECTORY "${CMAKE_SOURCE_DIR}" + OUTPUT_VARIABLE GIT_SHA1 + ERROR_QUIET OUTPUT_STRIP_TRAILING_WHITESPACE) + +# the date of the commit +execute_process(COMMAND + "${GIT_EXECUTABLE}" log -1 --format=%ad --date=local + WORKING_DIRECTORY "${CMAKE_SOURCE_DIR}" + OUTPUT_VARIABLE GIT_DATE + ERROR_QUIET OUTPUT_STRIP_TRAILING_WHITESPACE) + +# the subject of the commit +execute_process(COMMAND + "${GIT_EXECUTABLE}" log -1 --format=%s + WORKING_DIRECTORY "${CMAKE_SOURCE_DIR}" + OUTPUT_VARIABLE GIT_COMMIT_SUBJECT + ERROR_QUIET OUTPUT_STRIP_TRAILING_WHITESPACE) diff --git a/scripts/LlamaConfig.cmake.in b/cmake/llama-config.cmake.in similarity index 73% rename from scripts/LlamaConfig.cmake.in rename to cmake/llama-config.cmake.in index 9311055d925d4..2e7da2f8ebd69 100644 --- a/scripts/LlamaConfig.cmake.in +++ b/cmake/llama-config.cmake.in @@ -1,41 +1,43 @@ -set(LLAMA_VERSION @LLAMA_INSTALL_VERSION@) +set(LLAMA_VERSION @LLAMA_INSTALL_VERSION@) set(LLAMA_BUILD_COMMIT @LLAMA_BUILD_COMMIT@) set(LLAMA_BUILD_NUMBER @LLAMA_BUILD_NUMBER@) -set(LLAMA_SHARED_LIB @BUILD_SHARED_LIBS@) -set(LLAMA_BLAS @LLAMA_BLAS@) -set(LLAMA_CUDA @LLAMA_CUDA@) -set(LLAMA_METAL @LLAMA_METAL@) -set(LLAMA_HIPBLAS @LLAMA_HIPBLAS@) -set(LLAMA_ACCELERATE @LLAMA_ACCELERATE@) +set(LLAMA_SHARED_LIB @BUILD_SHARED_LIBS@) + +set(GGML_BLAS @GGML_BLAS@) +set(GGML_CUDA @GGML_CUDA@) +set(GGML_METAL @GGML_METAL@) +set(GGML_HIPBLAS @GGML_HIPBLAS@) +set(GGML_ACCELERATE @GGML_ACCELERATE@) @PACKAGE_INIT@ set_and_check(LLAMA_INCLUDE_DIR "@PACKAGE_LLAMA_INCLUDE_INSTALL_DIR@") -set_and_check(LLAMA_LIB_DIR "@PACKAGE_LLAMA_LIB_INSTALL_DIR@") -set_and_check(LLAMA_BIN_DIR "@PACKAGE_LLAMA_BIN_INSTALL_DIR@") +set_and_check(LLAMA_LIB_DIR "@PACKAGE_LLAMA_LIB_INSTALL_DIR@") +set_and_check(LLAMA_BIN_DIR "@PACKAGE_LLAMA_BIN_INSTALL_DIR@") # Ensure transient dependencies satisfied find_package(Threads REQUIRED) -if (APPLE AND LLAMA_ACCELERATE) + +if (APPLE AND GGML_ACCELERATE) find_library(ACCELERATE_FRAMEWORK Accelerate REQUIRED) endif() -if (LLAMA_BLAS) +if (GGML_BLAS) find_package(BLAS REQUIRED) endif() -if (LLAMA_CUDA) +if (GGML_CUDA) find_package(CUDAToolkit REQUIRED) endif() -if (LLAMA_METAL) +if (GGML_METAL) find_library(FOUNDATION_LIBRARY Foundation REQUIRED) find_library(METAL_FRAMEWORK Metal REQUIRED) find_library(METALKIT_FRAMEWORK MetalKit REQUIRED) endif() -if (LLAMA_HIPBLAS) +if (GGML_HIPBLAS) find_package(hip REQUIRED) find_package(hipblas REQUIRED) find_package(rocblas REQUIRED) @@ -47,7 +49,9 @@ find_library(llama_LIBRARY llama set(_llama_link_deps "Threads::Threads" "@LLAMA_EXTRA_LIBS@") set(_llama_transient_defines "@LLAMA_TRANSIENT_DEFINES@") + add_library(llama UNKNOWN IMPORTED) + set_target_properties(llama PROPERTIES INTERFACE_INCLUDE_DIRECTORIES "${LLAMA_INCLUDE_DIR}" diff --git a/common/CMakeLists.txt b/common/CMakeLists.txt index 171530c915332..761971d6881f3 100644 --- a/common/CMakeLists.txt +++ b/common/CMakeLists.txt @@ -1,5 +1,6 @@ # common +find_package(Threads REQUIRED) # Build info header # @@ -36,7 +37,7 @@ add_custom_command( COMMENT "Generating build details from Git" COMMAND ${CMAKE_COMMAND} -DMSVC=${MSVC} -DCMAKE_C_COMPILER_VERSION=${CMAKE_C_COMPILER_VERSION} -DCMAKE_C_COMPILER_ID=${CMAKE_C_COMPILER_ID} -DCMAKE_VS_PLATFORM_NAME=${CMAKE_VS_PLATFORM_NAME} - -DCMAKE_C_COMPILER=${CMAKE_C_COMPILER} -P "${CMAKE_CURRENT_SOURCE_DIR}/../scripts/gen-build-info-cpp.cmake" + -DCMAKE_C_COMPILER=${CMAKE_C_COMPILER} -P "${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info-gen-cpp.cmake" WORKING_DIRECTORY "${CMAKE_CURRENT_SOURCE_DIR}/.." DEPENDS "${CMAKE_CURRENT_SOURCE_DIR}/build-info.cpp.in" ${GIT_INDEX} VERBATIM @@ -83,5 +84,5 @@ if (LLAMA_CURL) endif () target_include_directories(${TARGET} PUBLIC .) -target_compile_features(${TARGET} PUBLIC cxx_std_11) -target_link_libraries(${TARGET} PRIVATE ${LLAMA_COMMON_EXTRA_LIBS} PUBLIC llama Threads::Threads) +target_compile_features (${TARGET} PUBLIC cxx_std_11) +target_link_libraries (${TARGET} PRIVATE ${LLAMA_COMMON_EXTRA_LIBS} PUBLIC llama Threads::Threads) diff --git a/scripts/gen-build-info-cpp.cmake b/common/cmake/build-info-gen-cpp.cmake similarity index 86% rename from scripts/gen-build-info-cpp.cmake rename to common/cmake/build-info-gen-cpp.cmake index d8933892011b3..fbc92b52cc4fe 100644 --- a/scripts/gen-build-info-cpp.cmake +++ b/common/cmake/build-info-gen-cpp.cmake @@ -1,7 +1,7 @@ -include(${CMAKE_CURRENT_SOURCE_DIR}/scripts/build-info.cmake) +include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info.cmake) set(TEMPLATE_FILE "${CMAKE_CURRENT_SOURCE_DIR}/common/build-info.cpp.in") -set(OUTPUT_FILE "${CMAKE_CURRENT_SOURCE_DIR}/common/build-info.cpp") +set(OUTPUT_FILE "${CMAKE_CURRENT_SOURCE_DIR}/common/build-info.cpp") # Only write the build info if it changed if(EXISTS ${OUTPUT_FILE}) diff --git a/docs/BLIS.md b/docs/BLIS.md index c933766b7f4ec..35d06bd0f303d 100644 --- a/docs/BLIS.md +++ b/docs/BLIS.md @@ -30,8 +30,8 @@ We recommend using openmp since it's easier to modify the cores being used. Makefile: ```bash -make LLAMA_BLIS=1 -j -# make LLAMA_BLIS=1 benchmark-matmult +make GGML_BLIS=1 -j +# make GGML_BLIS=1 llama-benchmark-matmult ``` CMake: @@ -39,7 +39,7 @@ CMake: ```bash mkdir build cd build -cmake -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=FLAME .. +cmake -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=FLAME .. make -j ``` diff --git a/examples/CMakeLists.txt b/examples/CMakeLists.txt index 0b51c44c05e4e..7d9ab34572b74 100644 --- a/examples/CMakeLists.txt +++ b/examples/CMakeLists.txt @@ -39,13 +39,13 @@ else() add_subdirectory(quantize-stats) add_subdirectory(quantize) add_subdirectory(retrieval) - if (LLAMA_RPC) + if (GGML_RPC) add_subdirectory(rpc) endif() if (LLAMA_BUILD_SERVER) add_subdirectory(server) endif() - if (LLAMA_SYCL) + if (GGML_SYCL) add_subdirectory(sycl) endif() add_subdirectory(save-load-state) diff --git a/examples/imatrix/README.md b/examples/imatrix/README.md index 38b36ee5a26fd..29602881a0d21 100644 --- a/examples/imatrix/README.md +++ b/examples/imatrix/README.md @@ -25,7 +25,7 @@ For faster computation, make sure to use GPU offloading via the `-ngl` argument ## Example ```bash -LLAMA_CUDA=1 make -j +GGML_CUDA=1 make -j # generate importance matrix (imatrix.dat) ./llama-imatrix -m ggml-model-f16.gguf -f train-data.txt -ngl 99 diff --git a/examples/llava/MobileVLM-README.md b/examples/llava/MobileVLM-README.md index 05a8207e67b88..f6c619c87df55 100644 --- a/examples/llava/MobileVLM-README.md +++ b/examples/llava/MobileVLM-README.md @@ -194,7 +194,7 @@ llama_print_timings: total time = 44411.01 ms / 377 tokens ## Orin compile and run ### compile ```sh -make LLAMA_CUDA=1 CUDA_DOCKER_ARCH=sm_87 LLAMA_CUDA_F16=1 -j 32 +make GGML_CUDA=1 CUDA_DOCKER_ARCH=sm_87 GGML_CUDA_F16=1 -j 32 ``` ### run on Orin ### case 1 diff --git a/examples/rpc/README.md b/examples/rpc/README.md index 86544e3fea2c3..e1da801f285c6 100644 --- a/examples/rpc/README.md +++ b/examples/rpc/README.md @@ -29,13 +29,13 @@ You can also run multiple `rpc-server` instances on the same host, each with a d ## Usage -On each host, build the corresponding backend with `cmake` and add `-DLLAMA_RPC=ON` to the build options. +On each host, build the corresponding backend with `cmake` and add `-DGGML_RPC=ON` to the build options. For example, to build the CUDA backend with RPC support: ```bash mkdir build-rpc-cuda cd build-rpc-cuda -cmake .. -DLLAMA_CUDA=ON -DLLAMA_RPC=ON +cmake .. -DGGML_CUDA=ON -DGGML_RPC=ON cmake --build . --config Release ``` @@ -58,12 +58,12 @@ $ CUDA_VISIBLE_DEVICES=0 bin/rpc-server -p 50052 This way you can run multiple `rpc-server` instances on the same host, each with a different CUDA device. -On the main host build `llama.cpp` only with `-DLLAMA_RPC=ON`: +On the main host build `llama.cpp` only with `-DGGML_RPC=ON`: ```bash mkdir build-rpc cd build-rpc -cmake .. -DLLAMA_RPC=ON +cmake .. -DGGML_RPC=ON cmake --build . --config Release ``` diff --git a/examples/server/CMakeLists.txt b/examples/server/CMakeLists.txt index 8365f9510ceae..dbe41f1fd1120 100644 --- a/examples/server/CMakeLists.txt +++ b/examples/server/CMakeLists.txt @@ -1,7 +1,14 @@ set(TARGET llama-server) option(LLAMA_SERVER_VERBOSE "Build verbose logging option for Server" ON) -option(LLAMA_SERVER_SSL "Build SSL support for the server" OFF) +option(LLAMA_SERVER_SSL "Build SSL support for the server" OFF) + include_directories(${CMAKE_CURRENT_SOURCE_DIR} ${CMAKE_CURRENT_BINARY_DIR}) + +if (MINGW) + # fix: https://github.com/ggerganov/llama.cpp/actions/runs/9651004652/job/26617901362?pr=8006 + add_compile_definitions(_WIN32_WINNT=${GGML_WIN_VER}) +endif() + set(TARGET_SRCS server.cpp utils.hpp @@ -24,6 +31,7 @@ set(PUBLIC_ASSETS prompt-formats.js json-schema-to-grammar.mjs ) + foreach(asset ${PUBLIC_ASSETS}) set(input "${CMAKE_CURRENT_SOURCE_DIR}/public/${asset}") set(output "${CMAKE_CURRENT_BINARY_DIR}/${asset}.hpp") @@ -34,18 +42,23 @@ foreach(asset ${PUBLIC_ASSETS}) COMMAND "${CMAKE_COMMAND}" "-DINPUT=${input}" "-DOUTPUT=${output}" -P "${PROJECT_SOURCE_DIR}/scripts/xxd.cmake" ) endforeach() + add_executable(${TARGET} ${TARGET_SRCS}) install(TARGETS ${TARGET} RUNTIME) target_compile_definitions(${TARGET} PRIVATE SERVER_VERBOSE=$ ) + target_link_libraries(${TARGET} PRIVATE common ${CMAKE_THREAD_LIBS_INIT}) + if (LLAMA_SERVER_SSL) find_package(OpenSSL REQUIRED) target_link_libraries(${TARGET} PRIVATE OpenSSL::SSL OpenSSL::Crypto) target_compile_definitions(${TARGET} PRIVATE CPPHTTPLIB_OPENSSL_SUPPORT) endif() + if (WIN32) TARGET_LINK_LIBRARIES(${TARGET} PRIVATE ws2_32) endif() + target_compile_features(${TARGET} PRIVATE cxx_std_11) diff --git a/examples/sycl/build.sh b/examples/sycl/build.sh index db46d57cabe0b..8fe0a67902cbd 100755 --- a/examples/sycl/build.sh +++ b/examples/sycl/build.sh @@ -8,10 +8,10 @@ cd build source /opt/intel/oneapi/setvars.sh #for FP16 -#cmake .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL_F16=ON # faster for long-prompt inference +#cmake .. -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL_F16=ON # faster for long-prompt inference #for FP32 -cmake .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx +cmake .. -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx #build example/main #cmake --build . --config Release --target main diff --git a/examples/sycl/win-build-sycl.bat b/examples/sycl/win-build-sycl.bat index 027173b0a974b..cdae5a52855a2 100644 --- a/examples/sycl/win-build-sycl.bat +++ b/examples/sycl/win-build-sycl.bat @@ -13,10 +13,10 @@ if %errorlevel% neq 0 goto ERROR :: for FP16 :: faster for long-prompt inference -:: cmake -G "MinGW Makefiles" .. -DLLAMA_SYCL=ON -DCMAKE_CXX_COMPILER=icx -DBUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release -DLLAMA_SYCL_F16=ON +:: cmake -G "MinGW Makefiles" .. -DGGML_SYCL=ON -DCMAKE_CXX_COMPILER=icx -DBUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release -DGGML_SYCL_F16=ON :: for FP32 -cmake -G "Ninja" .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=cl -DCMAKE_CXX_COMPILER=icx -DBUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release +cmake -G "Ninja" .. -DGGML_SYCL=ON -DCMAKE_C_COMPILER=cl -DCMAKE_CXX_COMPILER=icx -DBUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release if %errorlevel% neq 0 goto ERROR :: build example/main only :: make main diff --git a/ggml/CMakeLists.txt b/ggml/CMakeLists.txt new file mode 100644 index 0000000000000..f3763f7eb9fef --- /dev/null +++ b/ggml/CMakeLists.txt @@ -0,0 +1,238 @@ +cmake_minimum_required(VERSION 3.14) # for add_link_options and implicit target directories. +project("ggml" C CXX) +include(CheckIncludeFileCXX) + +set(CMAKE_EXPORT_COMPILE_COMMANDS ON) + +if (NOT XCODE AND NOT MSVC AND NOT CMAKE_BUILD_TYPE) + set(CMAKE_BUILD_TYPE Release CACHE STRING "Build type" FORCE) + set_property(CACHE CMAKE_BUILD_TYPE PROPERTY STRINGS "Debug" "Release" "MinSizeRel" "RelWithDebInfo") +endif() + +if (CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR) + set(GGML_STANDALONE ON) + + set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin) + + # configure project version + # TODO +else() + set(GGML_STANDALONE OFF) +endif() + +if (EMSCRIPTEN) + set(BUILD_SHARED_LIBS_DEFAULT OFF) + + option(GGML_WASM_SINGLE_FILE "ggml: embed WASM inside the generated ggml.js" ON) +else() + if (MINGW) + set(BUILD_SHARED_LIBS_DEFAULT OFF) + else() + set(BUILD_SHARED_LIBS_DEFAULT ON) + endif() +endif() + +option(BUILD_SHARED_LIBS "ggml: build shared libraries" ${BUILD_SHARED_LIBS_DEFAULT}) + +# +# option list +# + +# TODO: mark all options as advanced when not GGML_STANDALONE + +if (APPLE) + set(GGML_METAL_DEFAULT ON) + set(GGML_BLAS_DEFAULT ON) + set(GGML_BLAS_VENDOR_DEFAULT "Apple") +else() + set(GGML_METAL_DEFAULT OFF) + set(GGML_BLAS_DEFAULT OFF) + set(GGML_BLAS_VENDOR_DEFAULT "Generic") +endif() + +# general +option(GGML_STATIC "ggml: static link libraries" OFF) +option(GGML_NATIVE "ggml: enable -march=native flag" ON) +option(GGML_LTO "ggml: enable link time optimization" OFF) +option(GGML_CCACHE "ggml: use ccache if available" ON) + +# debug +option(GGML_ALL_WARNINGS "ggml: enable all compiler warnings" ON) +option(GGML_ALL_WARNINGS_3RD_PARTY "ggml: enable all compiler warnings in 3rd party libs" OFF) +option(GGML_GPROF "ggml: enable gprof" OFF) + +# build +option(GGML_FATAL_WARNINGS "ggml: enable -Werror flag" OFF) + +# sanitizers +option(GGML_SANITIZE_THREAD "ggml: enable thread sanitizer" OFF) +option(GGML_SANITIZE_ADDRESS "ggml: enable address sanitizer" OFF) +option(GGML_SANITIZE_UNDEFINED "ggml: enable undefined sanitizer" OFF) + +# instruction set specific +if (GGML_NATIVE) + set(INS_ENB OFF) +else() + set(INS_ENB ON) +endif() + +option(GGML_CPU_HBM "ggml: use memkind for CPU HBM" OFF) + +option(GGML_AVX "ggml: enable AVX" ${INS_ENB}) +option(GGML_AVX2 "ggml: enable AVX2" ${INS_ENB}) +option(GGML_AVX512 "ggml: enable AVX512" OFF) +option(GGML_AVX512_VBMI "ggml: enable AVX512-VBMI" OFF) +option(GGML_AVX512_VNNI "ggml: enable AVX512-VNNI" OFF) +option(GGML_AVX512_BF16 "ggml: enable AVX512-BF16" OFF) +option(GGML_FMA "ggml: enable FMA" ${INS_ENB}) +if (NOT MSVC) + option(GGML_F16C "ggml: enable F16C" ${INS_ENB}) # in MSVC F16C is implied with AVX2/AVX512 +endif() +option(GGML_LASX "ggml: enable lasx" ON) +option(GGML_LSX "ggml: enable lsx" ON) +option(GGML_SVE "ggml: enable SVE" OFF) + +if (WIN32) + set(GGML_WIN_VER "0x602" CACHE STRING "ggml: Windows Version") +endif() + +# ggml core +set(GGML_SCHED_MAX_COPIES "4" CACHE STRING "ggml: max input copies for pipeline parallelism") + +# 3rd party libs / backends +option(GGML_ACCELERATE "ggml: enable Accelerate framework" ON) +option(GGML_BLAS "ggml: use BLAS" ${GGML_BLAS_DEFAULT}) +set(GGML_BLAS_VENDOR ${GGML_BLAS_VENDOR_DEFAULT} CACHE STRING + "ggml: BLAS library vendor") +option(GGML_LLAMAFILE "ggml: use ggml SGEMM" OFF) + +option(GGML_CUDA "ggml: use CUDA" OFF) +option(GGML_CUDA_FORCE_DMMV "ggml: use dmmv instead of mmvq CUDA kernels" OFF) +option(GGML_CUDA_FORCE_MMQ "ggml: use mmq kernels instead of cuBLAS" OFF) +set (GGML_CUDA_DMMV_X "32" CACHE STRING "ggml: x stride for dmmv CUDA kernels") +set (GGML_CUDA_MMV_Y "1" CACHE STRING "ggml: y block size for mmv CUDA kernels") +option(GGML_CUDA_F16 "ggml: use 16 bit floats for some calculations" OFF) +set (GGML_CUDA_KQUANTS_ITER "2" CACHE STRING + "ggml: iters./thread per block for Q2_K/Q6_K") +set (GGML_CUDA_PEER_MAX_BATCH_SIZE "128" CACHE STRING + "ggml: max. batch size for using peer access") +option(GGML_CUDA_NO_PEER_COPY "ggml: do not use peer to peer copies" OFF) +option(GGML_CUDA_NO_VMM "ggml: do not try to use CUDA VMM" OFF) +option(GGML_CUDA_FA_ALL_QUANTS "ggml: compile all quants for FlashAttention" OFF) + +option(GGML_CURL "ggml: use libcurl to download model from an URL" OFF) +option(GGML_HIPBLAS "ggml: use hipBLAS" OFF) +option(GGML_HIP_UMA "ggml: use HIP unified memory architecture" OFF) +option(GGML_VULKAN "ggml: use Vulkan" OFF) +option(GGML_VULKAN_CHECK_RESULTS "ggml: run Vulkan op checks" OFF) +option(GGML_VULKAN_DEBUG "ggml: enable Vulkan debug output" OFF) +option(GGML_VULKAN_MEMORY_DEBUG "ggml: enable Vulkan memory debug output" OFF) +option(GGML_VULKAN_VALIDATE "ggml: enable Vulkan validation" OFF) +option(GGML_VULKAN_RUN_TESTS "ggml: run Vulkan tests" OFF) +option(GGML_KOMPUTE "ggml: use Kompute" OFF) +option(GGML_METAL "ggml: use Metal" ${GGML_METAL_DEFAULT}) +option(GGML_METAL_NDEBUG "ggml: disable Metal debugging" OFF) +option(GGML_METAL_SHADER_DEBUG "ggml: compile Metal with -fno-fast-math" OFF) +option(GGML_METAL_EMBED_LIBRARY "ggml: embed Metal library" ${GGML_METAL}) +set (GGML_METAL_MACOSX_VERSION_MIN "" CACHE STRING + "ggml: metal minimum macOS version") +set (GGML_METAL_STD "" CACHE STRING "ggml: metal standard version (-std flag)") +option(GGML_OPENMP "ggml: use OpenMP" ON) +option(GGML_RPC "ggml: use RPC" OFF) +option(GGML_SYCL "ggml: use SYCL" OFF) +option(GGML_SYCL_F16 "ggml: use 16 bit floats for sycl calculations" OFF) +set (GGML_SYCL_TARGET "INTEL" CACHE STRING + "ggml: sycl target device") + +# extra artifacts +option(GGML_BUILD_TESTS "ggml: build tests" ${GGML_STANDALONE}) +option(GGML_BUILD_EXAMPLES "ggml: build examples" ${GGML_STANDALONE}) + +# +# dependencies +# + +set(CMAKE_C_STANDARD 11) +set(CMAKE_C_STANDARD_REQUIRED true) + +if (GGML_SYCL) + set(CMAKE_CXX_STANDARD 17) +else() + set(CMAKE_CXX_STANDARD 11) +endif() +set(CMAKE_CXX_STANDARD_REQUIRED true) + +set(THREADS_PREFER_PTHREAD_FLAG ON) + +find_package(Threads REQUIRED) + +# +# build the library +# + +add_subdirectory(src) + +# +# tests and examples +# + +if (GGML_BUILD_TESTS) + enable_testing() + add_subdirectory(tests) +endif () + +if (GGML_BUILD_EXAMPLES) + add_subdirectory(examples) +endif () + +# +# install +# + +include(GNUInstallDirs) +include(CMakePackageConfigHelpers) + +set(GGML_PUBLIC_HEADERS + include/ggml.h + include/ggml-alloc.h + include/ggml-backend.h + "${GGML_HEADERS_CUDA}" + "${GGML_HEADERS_METAL}" + "${GGML_HEADERS_EXTRA}") + +set_target_properties(ggml PROPERTIES PUBLIC_HEADER "${GGML_PUBLIC_HEADERS}") +#if (GGML_METAL) +# set_target_properties(ggml PROPERTIES RESOURCE "${CMAKE_CURRENT_SOURCE_DIR}/src/ggml-metal.metal") +#endif() +install(TARGETS ggml PUBLIC_HEADER) + +if (BUILD_SHARED_LIBS) + install(TARGETS ggml LIBRARY) +endif() + +if (GGML_METAL) + install( + FILES src/ggml-metal.metal + PERMISSIONS + OWNER_READ + OWNER_WRITE + GROUP_READ + WORLD_READ + DESTINATION ${CMAKE_INSTALL_BINDIR}) + + if (NOT GGML_METAL_EMBED_LIBRARY) + install( + FILES ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib + DESTINATION ${CMAKE_INSTALL_BINDIR} + ) + endif() +endif() + +if (GGML_STANDALONE) + configure_file(${CMAKE_CURRENT_SOURCE_DIR}/ggml.pc.in + ${CMAKE_CURRENT_BINARY_DIR}/ggml.pc + @ONLY) + + install(FILES ${CMAKE_CURRENT_BINARY_DIR}/ggml.pc + DESTINATION share/pkgconfig) +endif() diff --git a/cmake/FindSIMD.cmake b/ggml/cmake/FindSIMD.cmake similarity index 94% rename from cmake/FindSIMD.cmake rename to ggml/cmake/FindSIMD.cmake index 33377ec44de12..5533668ec4ab1 100644 --- a/cmake/FindSIMD.cmake +++ b/ggml/cmake/FindSIMD.cmake @@ -79,22 +79,22 @@ endmacro() # flags are for MSVC only! check_sse("AVX" " ;/arch:AVX") if (NOT ${AVX_FOUND}) - set(LLAMA_AVX OFF) + set(GGML_AVX OFF) else() - set(LLAMA_AVX ON) + set(GGML_AVX ON) endif() check_sse("AVX2" " ;/arch:AVX2") check_sse("FMA" " ;/arch:AVX2") if ((NOT ${AVX2_FOUND}) OR (NOT ${FMA_FOUND})) - set(LLAMA_AVX2 OFF) + set(GGML_AVX2 OFF) else() - set(LLAMA_AVX2 ON) + set(GGML_AVX2 ON) endif() check_sse("AVX512" " ;/arch:AVX512") if (NOT ${AVX512_FOUND}) - set(LLAMA_AVX512 OFF) + set(GGML_AVX512 OFF) else() - set(LLAMA_AVX512 ON) + set(GGML_AVX512 ON) endif() diff --git a/ggml_vk_generate_shaders.py b/ggml/ggml_vk_generate_shaders.py similarity index 100% rename from ggml_vk_generate_shaders.py rename to ggml/ggml_vk_generate_shaders.py diff --git a/ggml-alloc.h b/ggml/include/ggml-alloc.h similarity index 100% rename from ggml-alloc.h rename to ggml/include/ggml-alloc.h diff --git a/ggml-backend.h b/ggml/include/ggml-backend.h similarity index 100% rename from ggml-backend.h rename to ggml/include/ggml-backend.h diff --git a/ggml-blas.h b/ggml/include/ggml-blas.h similarity index 100% rename from ggml-blas.h rename to ggml/include/ggml-blas.h diff --git a/ggml-cuda.h b/ggml/include/ggml-cuda.h similarity index 100% rename from ggml-cuda.h rename to ggml/include/ggml-cuda.h diff --git a/ggml-kompute.h b/ggml/include/ggml-kompute.h similarity index 100% rename from ggml-kompute.h rename to ggml/include/ggml-kompute.h diff --git a/ggml-metal.h b/ggml/include/ggml-metal.h similarity index 100% rename from ggml-metal.h rename to ggml/include/ggml-metal.h diff --git a/ggml-rpc.h b/ggml/include/ggml-rpc.h similarity index 100% rename from ggml-rpc.h rename to ggml/include/ggml-rpc.h diff --git a/ggml-sycl.h b/ggml/include/ggml-sycl.h similarity index 95% rename from ggml-sycl.h rename to ggml/include/ggml-sycl.h index 451938fc4151d..43ab1519cd05d 100644 --- a/ggml-sycl.h +++ b/ggml/include/ggml-sycl.h @@ -8,7 +8,9 @@ #include "ggml.h" #include "ggml-backend.h" -#include "ggml-sycl/presets.hpp" + +#define GGML_SYCL_NAME "SYCL" +#define GGML_SYCL_MAX_DEVICES 48 #ifdef __cplusplus extern "C" { diff --git a/ggml-vulkan.h b/ggml/include/ggml-vulkan.h similarity index 100% rename from ggml-vulkan.h rename to ggml/include/ggml-vulkan.h diff --git a/ggml.h b/ggml/include/ggml.h similarity index 100% rename from ggml.h rename to ggml/include/ggml.h diff --git a/ggml/src/CMakeLists.txt b/ggml/src/CMakeLists.txt new file mode 100644 index 0000000000000..ba341d3749050 --- /dev/null +++ b/ggml/src/CMakeLists.txt @@ -0,0 +1,1171 @@ +include(CheckCXXCompilerFlag) + +unset(GGML_CDEF_PUBLIC) + +add_compile_definitions(GGML_SCHED_MAX_COPIES=${GGML_SCHED_MAX_COPIES}) + +# enable libstdc++ assertions for debug builds +if (CMAKE_SYSTEM_NAME MATCHES "Linux") + add_compile_definitions($<$:_GLIBCXX_ASSERTIONS>) +endif() + +if (NOT MSVC) + if (GGML_SANITIZE_THREAD) + add_compile_options(-fsanitize=thread) + link_libraries (-fsanitize=thread) + endif() + + if (GGML_SANITIZE_ADDRESS) + add_compile_options(-fsanitize=address -fno-omit-frame-pointer) + link_libraries (-fsanitize=address) + endif() + + if (GGML_SANITIZE_UNDEFINED) + add_compile_options(-fsanitize=undefined) + link_libraries (-fsanitize=undefined) + endif() +endif() + +if (APPLE AND GGML_ACCELERATE) + find_library(ACCELERATE_FRAMEWORK Accelerate) + if (ACCELERATE_FRAMEWORK) + message(STATUS "Accelerate framework found") + + add_compile_definitions(GGML_USE_ACCELERATE) + add_compile_definitions(ACCELERATE_NEW_LAPACK) + add_compile_definitions(ACCELERATE_LAPACK_ILP64) + + set(GGML_EXTRA_LIBS ${GGML_EXTRA_LIBS} ${ACCELERATE_FRAMEWORK}) + else() + message(WARNING "Accelerate framework not found") + endif() +endif() + +if (GGML_METAL) + find_library(FOUNDATION_LIBRARY Foundation REQUIRED) + find_library(METAL_FRAMEWORK Metal REQUIRED) + find_library(METALKIT_FRAMEWORK MetalKit REQUIRED) + + message(STATUS "Metal framework found") + set(GGML_HEADERS_METAL ../include/ggml-metal.h) + set(GGML_SOURCES_METAL ggml-metal.m) + + list(APPEND GGML_CDEF_PUBLIC GGML_USE_METAL) + if (GGML_METAL_NDEBUG) + add_compile_definitions(GGML_METAL_NDEBUG) + endif() + + # copy ggml-common.h and ggml-metal.metal to bin directory + configure_file(ggml-common.h ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-common.h COPYONLY) + configure_file(ggml-metal.metal ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.metal COPYONLY) + + if (GGML_METAL_EMBED_LIBRARY) + enable_language(ASM) + + add_compile_definitions(GGML_METAL_EMBED_LIBRARY) + + set(METALLIB_COMMON "${CMAKE_CURRENT_SOURCE_DIR}/ggml-common.h") + set(METALLIB_SOURCE "${CMAKE_CURRENT_SOURCE_DIR}/ggml-metal.metal") + + file(MAKE_DIRECTORY "${CMAKE_BINARY_DIR}/autogenerated") + + # merge ggml-common.h and ggml-metal.metal into a single file + set(METALLIB_EMBED_ASM "${CMAKE_BINARY_DIR}/autogenerated/ggml-metal-embed.s") + set(METALLIB_SOURCE_EMBED "${CMAKE_BINARY_DIR}/autogenerated/ggml-metal-embed.metal") + + add_custom_command( + OUTPUT ${METALLIB_EMBED_ASM} + COMMAND echo "Embedding Metal library" + COMMAND sed -e '/\#include \"ggml-common.h\"/r ${METALLIB_COMMON}' -e '/\#include \"ggml-common.h\"/d' < ${METALLIB_SOURCE} > ${METALLIB_SOURCE_EMBED} + COMMAND echo ".section __DATA,__ggml_metallib" > ${METALLIB_EMBED_ASM} + COMMAND echo ".globl _ggml_metallib_start" >> ${METALLIB_EMBED_ASM} + COMMAND echo "_ggml_metallib_start:" >> ${METALLIB_EMBED_ASM} + COMMAND echo ".incbin \\\"${METALLIB_SOURCE_EMBED}\\\"" >> ${METALLIB_EMBED_ASM} + COMMAND echo ".globl _ggml_metallib_end" >> ${METALLIB_EMBED_ASM} + COMMAND echo "_ggml_metallib_end:" >> ${METALLIB_EMBED_ASM} + DEPENDS ggml-metal.metal ggml-common.h + COMMENT "Generate assembly for embedded Metal library" + ) + + set(GGML_SOURCES_METAL ${GGML_SOURCES_METAL} ${METALLIB_EMBED_ASM}) + else() + if (GGML_METAL_SHADER_DEBUG) + # custom command to do the following: + # xcrun -sdk macosx metal -fno-fast-math -c ggml-metal.metal -o ggml-metal.air + # xcrun -sdk macosx metallib ggml-metal.air -o default.metallib + # + # note: this is the only way I found to disable fast-math in Metal. it's ugly, but at least it works + # disabling fast math is needed in order to pass tests/test-backend-ops + # note: adding -fno-inline fixes the tests when using MTL_SHADER_VALIDATION=1 + # note: unfortunately, we have to call it default.metallib instead of ggml.metallib + # ref: https://github.com/ggerganov/whisper.cpp/issues/1720 + set(XC_FLAGS -fno-fast-math -fno-inline -g) + else() + set(XC_FLAGS -O3) + endif() + + # Append macOS metal versioning flags + if (GGML_METAL_MACOSX_VERSION_MIN) + message(STATUS "Adding -mmacosx-version-min=${GGML_METAL_MACOSX_VERSION_MIN} flag to metal compilation") + list (APPEND XC_FLAGS -mmacosx-version-min=${GGML_METAL_MACOSX_VERSION_MIN}) + endif() + + if (GGML_METAL_STD) + message(STATUS "Adding -std=${GGML_METAL_STD} flag to metal compilation") + list (APPEND XC_FLAGS -std=${GGML_METAL_STD}) + endif() + + add_custom_command( + OUTPUT ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib + COMMAND xcrun -sdk macosx metal ${XC_FLAGS} -c ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.metal -o ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.air + COMMAND xcrun -sdk macosx metallib ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.air -o ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib + COMMAND rm -f ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.air + COMMAND rm -f ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-common.h + COMMAND rm -f ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.metal + DEPENDS ggml-metal.metal ggml-common.h + COMMENT "Compiling Metal kernels" + ) + + add_custom_target( + ggml-metal ALL + DEPENDS ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib + ) + endif() # GGML_METAL_EMBED_LIBRARY + + set(GGML_EXTRA_LIBS ${GGML_EXTRA_LIBS} + ${FOUNDATION_LIBRARY} + ${METAL_FRAMEWORK} + ${METALKIT_FRAMEWORK} + ) +endif() + +if (GGML_OPENMP) + find_package(OpenMP) + if (OpenMP_FOUND) + message(STATUS "OpenMP found") + + add_compile_definitions(GGML_USE_OPENMP) + + set(GGML_EXTRA_LIBS ${GGML_EXTRA_LIBS} OpenMP::OpenMP_C OpenMP::OpenMP_CXX) + else() + message(WARNING "OpenMP not found") + endif() +endif() + +if (GGML_BLAS) + if (GGML_STATIC) + set(BLA_STATIC ON) + endif() + #if (CMAKE_VERSION VERSION_GREATER_EQUAL 3.22) + # set(BLA_SIZEOF_INTEGER 8) + #endif() + + set(BLA_VENDOR ${GGML_BLAS_VENDOR}) + find_package(BLAS) + + if (BLAS_FOUND) + message(STATUS "BLAS found, Libraries: ${BLAS_LIBRARIES}") + + if (("${BLAS_INCLUDE_DIRS}" STREQUAL "") AND NOT (${GGML_BLAS_VENDOR} MATCHES "Apple")) + # BLAS_INCLUDE_DIRS is missing in FindBLAS.cmake. + # see https://gitlab.kitware.com/cmake/cmake/-/issues/20268 + find_package(PkgConfig REQUIRED) + if (${GGML_BLAS_VENDOR} MATCHES "Generic") + pkg_check_modules(DepBLAS REQUIRED blas) + elseif (${GGML_BLAS_VENDOR} MATCHES "OpenBLAS") + # As of openblas v0.3.22, the 64-bit is named openblas64.pc + pkg_check_modules(DepBLAS openblas64) + if (NOT DepBLAS_FOUND) + pkg_check_modules(DepBLAS REQUIRED openblas) + endif() + elseif (${GGML_BLAS_VENDOR} MATCHES "FLAME") + pkg_check_modules(DepBLAS REQUIRED blis) + elseif (${GGML_BLAS_VENDOR} MATCHES "ATLAS") + pkg_check_modules(DepBLAS REQUIRED blas-atlas) + elseif (${GGML_BLAS_VENDOR} MATCHES "FlexiBLAS") + pkg_check_modules(DepBLAS REQUIRED flexiblas_api) + elseif (${GGML_BLAS_VENDOR} MATCHES "Intel") + # all Intel* libraries share the same include path + pkg_check_modules(DepBLAS REQUIRED mkl-sdl) + elseif (${GGML_BLAS_VENDOR} MATCHES "NVHPC") + # this doesn't provide pkg-config + # suggest to assign BLAS_INCLUDE_DIRS on your own + if ("${NVHPC_VERSION}" STREQUAL "") + message(WARNING "Better to set NVHPC_VERSION") + else() + set(DepBLAS_FOUND ON) + set(DepBLAS_INCLUDE_DIRS "/opt/nvidia/hpc_sdk/${CMAKE_SYSTEM_NAME}_${CMAKE_SYSTEM_PROCESSOR}/${NVHPC_VERSION}/math_libs/include") + endif() + endif() + if (DepBLAS_FOUND) + set(BLAS_INCLUDE_DIRS ${DepBLAS_INCLUDE_DIRS}) + else() + message(WARNING "BLAS_INCLUDE_DIRS neither been provided nor been automatically" + " detected by pkgconfig, trying to find cblas.h from possible paths...") + find_path(BLAS_INCLUDE_DIRS + NAMES cblas.h + HINTS + /usr/include + /usr/local/include + /usr/include/openblas + /opt/homebrew/opt/openblas/include + /usr/local/opt/openblas/include + /usr/include/x86_64-linux-gnu/openblas/include + ) + endif() + endif() + + message(STATUS "BLAS found, Includes: ${BLAS_INCLUDE_DIRS}") + + add_compile_options(${BLAS_LINKER_FLAGS}) + + list(APPEND GGML_CDEF_PUBLIC GGML_USE_BLAS) + + if (${BLAS_INCLUDE_DIRS} MATCHES "mkl" AND (${GGML_BLAS_VENDOR} MATCHES "Generic" OR ${GGML_BLAS_VENDOR} MATCHES "Intel")) + add_compile_definitions(GGML_BLAS_USE_MKL) + endif() + + set(GGML_HEADERS_BLAS ../include/ggml-blas.h) + set(GGML_SOURCES_BLAS ggml-blas.cpp) + + set(GGML_EXTRA_LIBS ${GGML_EXTRA_LIBS} ${BLAS_LIBRARIES}) + set(GGML_EXTRA_INCLUDES ${GGML_EXTRA_INCLUDES} ${BLAS_INCLUDE_DIRS}) + else() + message(WARNING "BLAS not found, please refer to " + "https://cmake.org/cmake/help/latest/module/FindBLAS.html#blas-lapack-vendors" + " to set correct GGML_BLAS_VENDOR") + endif() +endif() + +if (GGML_LLAMAFILE) + message(STATUS "Using ggml SGEMM") + + add_compile_definitions(GGML_USE_LLAMAFILE) + + set(GGML_HEADERS_LLAMAFILE sgemm.h) + set(GGML_SOURCES_LLAMAFILE sgemm.cpp) +endif() + +if (GGML_CUDA) + cmake_minimum_required(VERSION 3.18) # for CMAKE_CUDA_ARCHITECTURES + + find_package(CUDAToolkit) + + if (CUDAToolkit_FOUND) + message(STATUS "CUDA found") + + if (NOT DEFINED CMAKE_CUDA_ARCHITECTURES) + # 52 == lowest CUDA 12 standard + # 60 == FP16 CUDA intrinsics + # 61 == integer CUDA intrinsics + # 70 == compute capability at which unrolling a loop in mul_mat_q kernels is faster + if (GGML_CUDA_F16 OR GGML_CUDA_DMMV_F16) + set(CMAKE_CUDA_ARCHITECTURES "60;61;70;75") + else() + set(CMAKE_CUDA_ARCHITECTURES "52;61;70;75") + #set(CMAKE_CUDA_ARCHITECTURES "OFF") # use this to compile much faster, but only F16 models work + endif() + endif() + message(STATUS "Using CUDA architectures: ${CMAKE_CUDA_ARCHITECTURES}") + + enable_language(CUDA) + + file(GLOB GGML_HEADERS_CUDA "ggml-cuda/*.cuh") + list(APPEND GGML_HEADERS_CUDA "../include/ggml-cuda.h") + + file(GLOB GGML_SOURCES_CUDA "ggml-cuda/*.cu") + list(APPEND GGML_SOURCES_CUDA "ggml-cuda.cu") + file(GLOB SRCS "ggml-cuda/template-instances/fattn-wmma*.cu") + list(APPEND GGML_SOURCES_CUDA ${SRCS}) + file(GLOB SRCS "ggml-cuda/template-instances/mmq*.cu") + list(APPEND GGML_SOURCES_CUDA ${SRCS}) + + if (GGML_CUDA_FA_ALL_QUANTS) + file(GLOB SRCS "ggml-cuda/template-instances/fattn-vec*.cu") + list(APPEND GGML_SOURCES_CUDA ${SRCS}) + add_compile_definitions(GGML_CUDA_FA_ALL_QUANTS) + else() + file(GLOB SRCS "ggml-cuda/template-instances/fattn-vec*q4_0-q4_0.cu") + list(APPEND GGML_SOURCES_CUDA ${SRCS}) + file(GLOB SRCS "ggml-cuda/template-instances/fattn-vec*q8_0-q8_0.cu") + list(APPEND GGML_SOURCES_CUDA ${SRCS}) + file(GLOB SRCS "ggml-cuda/template-instances/fattn-vec*f16-f16.cu") + list(APPEND GGML_SOURCES_CUDA ${SRCS}) + endif() + + list(APPEND GGML_CDEF_PUBLIC GGML_USE_CUDA) + + add_compile_definitions(GGML_CUDA_USE_GRAPHS) + add_compile_definitions(GGML_CUDA_DMMV_X=${GGML_CUDA_DMMV_X}) + add_compile_definitions(GGML_CUDA_MMV_Y=${GGML_CUDA_MMV_Y}) + add_compile_definitions(K_QUANTS_PER_ITERATION=${GGML_CUDA_KQUANTS_ITER}) + add_compile_definitions(GGML_CUDA_PEER_MAX_BATCH_SIZE=${GGML_CUDA_PEER_MAX_BATCH_SIZE}) + + if (GGML_CUDA_FORCE_DMMV) + add_compile_definitions(GGML_CUDA_FORCE_DMMV) + endif() + + if (GGML_CUDA_FORCE_MMQ) + add_compile_definitions(GGML_CUDA_FORCE_MMQ) + endif() + + if (GGML_CUDA_FORCE_CUBLAS) + add_compile_definitions(GGML_CUDA_FORCE_CUBLAS) + endif() + + if (GGML_CUDA_NO_VMM) + add_compile_definitions(GGML_CUDA_NO_VMM) + endif() + + if (DEFINED GGML_CUDA_DMMV_Y) + add_compile_definitions(GGML_CUDA_MMV_Y=${GGML_CUDA_DMMV_Y}) # for backwards compatibility + endif() + + if (GGML_CUDA_F16 OR GGML_CUDA_DMMV_F16) + add_compile_definitions(GGML_CUDA_F16) + endif() + + if (GGML_CUDA_NO_PEER_COPY) + add_compile_definitions(GGML_CUDA_NO_PEER_COPY) + endif() + + if (GGML_STATIC) + if (WIN32) + # As of 12.3.1 CUDA Toolkit for Windows does not offer a static cublas library + set(GGML_EXTRA_LIBS ${GGML_EXTRA_LIBS} CUDA::cudart_static CUDA::cublas CUDA::cublasLt) + else () + set(GGML_EXTRA_LIBS ${GGML_EXTRA_LIBS} CUDA::cudart_static CUDA::cublas_static CUDA::cublasLt_static) + endif() + else() + set(GGML_EXTRA_LIBS ${GGML_EXTRA_LIBS} CUDA::cudart CUDA::cublas CUDA::cublasLt) + endif() + + if (GGML_CUDA_NO_VMM) + # No VMM requested, no need to link directly with the cuda driver lib (libcuda.so) + else() + set(GGML_EXTRA_LIBS ${GGML_EXTRA_LIBS} CUDA::cuda_driver) # required by cuDeviceGetAttribute(), cuMemGetAllocationGranularity(...), ... + endif() + else() + message(WARNING "CUDA not found") + endif() +endif() + +if (GGML_HIPBLAS) + if (NOT EXISTS $ENV{ROCM_PATH}) + if (NOT EXISTS /opt/rocm) + set(ROCM_PATH /usr) + else() + set(ROCM_PATH /opt/rocm) + endif() + else() + set(ROCM_PATH $ENV{ROCM_PATH}) + endif() + + list(APPEND CMAKE_PREFIX_PATH ${ROCM_PATH}) + list(APPEND CMAKE_PREFIX_PATH "${ROCM_PATH}/lib64/cmake") + + # CMake on Windows doesn't support the HIP language yet + if (WIN32) + set(CXX_IS_HIPCC TRUE) + else() + string(REGEX MATCH "hipcc(\.bat)?$" CXX_IS_HIPCC "${CMAKE_CXX_COMPILER}") + endif() + + if (CXX_IS_HIPCC) + if (LINUX) + if (NOT ${CMAKE_CXX_COMPILER_ID} MATCHES "Clang") + message(WARNING "Only LLVM is supported for HIP, hint: CXX=/opt/rocm/llvm/bin/clang++") + endif() + + message(WARNING "Setting hipcc as the C++ compiler is legacy behavior." + " Prefer setting the HIP compiler directly. See README for details.") + endif() + else() + # Forward AMDGPU_TARGETS to CMAKE_HIP_ARCHITECTURES. + if (AMDGPU_TARGETS AND NOT CMAKE_HIP_ARCHITECTURES) + set(CMAKE_HIP_ARCHITECTURES ${AMDGPU_TARGETS}) + endif() + cmake_minimum_required(VERSION 3.21) + enable_language(HIP) + endif() + + find_package(hip REQUIRED) + find_package(hipblas REQUIRED) + find_package(rocblas REQUIRED) + + message(STATUS "HIP and hipBLAS found") + + file(GLOB GGML_HEADERS_ROCM "ggml-cuda/*.cuh") + list(APPEND GGML_HEADERS_ROCM "../include/ggml-cuda.h") + + file(GLOB GGML_SOURCES_ROCM "ggml-cuda/*.cu") + list(APPEND GGML_SOURCES_ROCM "ggml-cuda.cu") + file(GLOB SRCS "ggml-cuda/template-instances/fattn-wmma*.cu") + list(APPEND GGML_SOURCES_ROCM ${SRCS}) + file(GLOB SRCS "ggml-cuda/template-instances/mmq*.cu") + list(APPEND GGML_SOURCES_ROCM ${SRCS}) + + if (GGML_CUDA_FA_ALL_QUANTS) + file(GLOB SRCS "ggml-cuda/template-instances/fattn-vec*.cu") + list(APPEND GGML_SOURCES_ROCM ${SRCS}) + add_compile_definitions(GGML_CUDA_FA_ALL_QUANTS) + else() + file(GLOB SRCS "ggml-cuda/template-instances/fattn-vec*q4_0-q4_0.cu") + list(APPEND GGML_SOURCES_ROCM ${SRCS}) + file(GLOB SRCS "ggml-cuda/template-instances/fattn-vec*q8_0-q8_0.cu") + list(APPEND GGML_SOURCES_ROCM ${SRCS}) + file(GLOB SRCS "ggml-cuda/template-instances/fattn-vec*f16-f16.cu") + list(APPEND GGML_SOURCES_ROCM ${SRCS}) + endif() + + list(APPEND GGML_CDEF_PUBLIC GGML_USE_CUDA) + + add_compile_definitions(GGML_USE_HIPBLAS) + add_compile_definitions(GGML_CUDA_DMMV_X=${GGML_CUDA_DMMV_X}) + add_compile_definitions(GGML_CUDA_MMV_Y=${GGML_CUDA_MMV_Y}) + add_compile_definitions(K_QUANTS_PER_ITERATION=${GGML_CUDA_KQUANTS_ITER}) + + if (GGML_HIP_UMA) + add_compile_definitions(GGML_HIP_UMA) + endif() + + if (GGML_CUDA_FORCE_DMMV) + add_compile_definitions(GGML_CUDA_FORCE_DMMV) + endif() + + if (GGML_CUDA_FORCE_MMQ) + add_compile_definitions(GGML_CUDA_FORCE_MMQ) + endif() + + if (GGML_CUDA_NO_PEER_COPY) + add_compile_definitions(GGML_CUDA_NO_PEER_COPY) + endif() + + if (CXX_IS_HIPCC) + set_source_files_properties(${GGML_SOURCES_ROCM} PROPERTIES LANGUAGE CXX) + set(GGML_EXTRA_LIBS ${GGML_EXTRA_LIBS} hip::device) + else() + set_source_files_properties(${GGML_SOURCES_ROCM} PROPERTIES LANGUAGE HIP) + endif() + + if (GGML_STATIC) + message(FATAL_ERROR "Static linking not supported for HIP/ROCm") + endif() + + set(GGML_EXTRA_LIBS ${GGML_EXTRA_LIBS} PUBLIC hip::host roc::rocblas roc::hipblas) +endif() + +if (GGML_SYCL) + if (NOT GGML_SYCL_TARGET MATCHES "^(INTEL|NVIDIA)$") + message(FATAL_ERROR "Invalid backend chosen, supported options are INTEL or NVIDIA") + endif() + + if ( NOT DEFINED ENV{ONEAPI_ROOT}) + message(FATAL_ERROR "Not detect ENV {ONEAPI_ROOT}, please install oneAPI & source it, like: source /opt/intel/oneapi/setvars.sh") + endif() + #todo: AOT + + find_package(IntelSYCL REQUIRED) + find_package(MKL REQUIRED) + + message(STATUS "SYCL found") + + list(APPEND GGML_CDEF_PUBLIC GGML_USE_SYCL) + + if (GGML_SYCL_F16) + add_compile_definitions(GGML_SYCL_F16) + endif() + + if (GGML_CUDA_FORCE_MMQ) + add_compile_definitions(GGML_SYCL_FORCE_MMQ) + endif() + + add_compile_options(-I./) #include DPCT + + set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-narrowing") + set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O3") + if (GGML_SYCL_TARGET STREQUAL "NVIDIA") + set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fsycl-targets=nvptx64-nvidia-cuda") + endif() + + file(GLOB GGML_HEADERS_SYCL "ggml-sycl/*.hpp") + list(APPEND GGML_HEADERS_SYCL "../include/ggml-sycl.h") + + file(GLOB GGML_SOURCES_SYCL "ggml-sycl/*.cpp") + list(APPEND GGML_SOURCES_SYCL "ggml-sycl.cpp") + + if (WIN32) + set(GGML_EXTRA_LIBS ${GGML_EXTRA_LIBS} IntelSYCL::SYCL_CXX MKL::MKL MKL::MKL_SYCL) + else() + add_compile_options(-I/${SYCL_INCLUDE_DIR}) + set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fsycl -L${MKLROOT}/lib") + + if (GGML_SYCL_TARGET STREQUAL "INTEL") + set(GGML_EXTRA_LIBS ${GGML_EXTRA_LIBS} -fsycl OpenCL mkl_core pthread m dl mkl_sycl_blas mkl_intel_ilp64 mkl_tbb_thread) + elseif (GGML_SYCL_TARGET STREQUAL "NVIDIA") + set(GGML_EXTRA_LIBS ${GGML_EXTRA_LIBS} -fsycl pthread m dl onemkl) + endif() + endif() +endif() + +if (GGML_RPC) + message(STATUS "RPC found") + + list(APPEND GGML_CDEF_PUBLIC GGML_USE_RPC) + + if (WIN32) + set(GGML_EXTRA_LIBS ${GGML_EXTRA_LIBS} ws2_32) + endif() + + set(GGML_HEADERS_RPC ../include/ggml-rpc.h) + set(GGML_SOURCES_RPC ggml-rpc.cpp) +endif() + +if (GGML_VULKAN) + find_package(Vulkan) + + if (Vulkan_FOUND) + message(STATUS "Vulkan found") + + set(GGML_HEADERS_VULKAN ../include/ggml-vulkan.h) + set(GGML_SOURCES_VULKAN ggml-vulkan.cpp) + + list(APPEND GGML_CDEF_PUBLIC GGML_USE_VULKAN) + + # Workaround to the "can't dereference invalidated vector iterator" bug in clang-cl debug build + # Posssibly relevant: https://stackoverflow.com/questions/74748276/visual-studio-no-displays-the-correct-length-of-stdvector + if (MSVC AND CMAKE_CXX_COMPILER_ID STREQUAL "Clang") + add_compile_definitions(_ITERATOR_DEBUG_LEVEL=0) + endif() + + if (GGML_VULKAN_CHECK_RESULTS) + add_compile_definitions(GGML_VULKAN_CHECK_RESULTS) + endif() + + if (GGML_VULKAN_DEBUG) + add_compile_definitions(GGML_VULKAN_DEBUG) + endif() + + if (GGML_VULKAN_MEMORY_DEBUG) + add_compile_definitions(GGML_VULKAN_MEMORY_DEBUG) + endif() + + if (GGML_VULKAN_VALIDATE) + add_compile_definitions(GGML_VULKAN_VALIDATE) + endif() + + if (GGML_VULKAN_RUN_TESTS) + add_compile_definitions(GGML_VULKAN_RUN_TESTS) + endif() + + set(GGML_EXTRA_LIBS ${GGML_EXTRA_LIBS} Vulkan::Vulkan) + else() + message(WARNING "Vulkan not found") + endif() +endif() + +if (GGML_KOMPUTE) + add_compile_definitions(VULKAN_HPP_DISPATCH_LOADER_DYNAMIC=1) + + find_package(Vulkan COMPONENTS glslc REQUIRED) + find_program(glslc_executable NAMES glslc HINTS Vulkan::glslc) + + if (NOT glslc_executable) + message(FATAL_ERROR "glslc not found") + endif() + + function(compile_shader) + set(options) + set(oneValueArgs) + set(multiValueArgs SOURCES) + cmake_parse_arguments(compile_shader "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN}) + foreach(source ${compile_shader_SOURCES}) + get_filename_component(filename ${source} NAME) + set(spv_file ${filename}.spv) + add_custom_command( + OUTPUT ${spv_file} + DEPENDS ${CMAKE_CURRENT_SOURCE_DIR}/${source} + ${CMAKE_CURRENT_SOURCE_DIR}/kompute-shaders/common.comp + ${CMAKE_CURRENT_SOURCE_DIR}/kompute-shaders/op_getrows.comp + ${CMAKE_CURRENT_SOURCE_DIR}/kompute-shaders/op_mul_mv_q_n_pre.comp + ${CMAKE_CURRENT_SOURCE_DIR}/kompute-shaders/op_mul_mv_q_n.comp + COMMAND ${glslc_executable} --target-env=vulkan1.2 -o ${spv_file} ${CMAKE_CURRENT_SOURCE_DIR}/${source} + COMMENT "Compiling ${source} to ${spv_file}" + ) + + get_filename_component(RAW_FILE_NAME ${spv_file} NAME) + set(FILE_NAME "shader${RAW_FILE_NAME}") + string(REPLACE ".comp.spv" ".h" HEADER_FILE ${FILE_NAME}) + string(TOUPPER ${HEADER_FILE} HEADER_FILE_DEFINE) + string(REPLACE "." "_" HEADER_FILE_DEFINE "${HEADER_FILE_DEFINE}") + set(OUTPUT_HEADER_FILE "${HEADER_FILE}") + message(STATUS "${HEADER_FILE} generating ${HEADER_FILE_DEFINE}") + if(CMAKE_GENERATOR MATCHES "Visual Studio") + add_custom_command( + OUTPUT ${OUTPUT_HEADER_FILE} + COMMAND ${CMAKE_COMMAND} -E echo "/*THIS FILE HAS BEEN AUTOMATICALLY GENERATED - DO NOT EDIT*/" > ${OUTPUT_HEADER_FILE} + COMMAND ${CMAKE_COMMAND} -E echo \"\#ifndef ${HEADER_FILE_DEFINE}\" >> ${OUTPUT_HEADER_FILE} + COMMAND ${CMAKE_COMMAND} -E echo \"\#define ${HEADER_FILE_DEFINE}\" >> ${OUTPUT_HEADER_FILE} + COMMAND ${CMAKE_COMMAND} -E echo "namespace kp {" >> ${OUTPUT_HEADER_FILE} + COMMAND ${CMAKE_COMMAND} -E echo "namespace shader_data {" >> ${OUTPUT_HEADER_FILE} + COMMAND ${CMAKE_BINARY_DIR}/bin/$/xxd -i ${RAW_FILE_NAME} >> ${OUTPUT_HEADER_FILE} + COMMAND ${CMAKE_COMMAND} -E echo "}}" >> ${OUTPUT_HEADER_FILE} + COMMAND ${CMAKE_COMMAND} -E echo \"\#endif // define ${HEADER_FILE_DEFINE}\" >> ${OUTPUT_HEADER_FILE} + DEPENDS ${spv_file} xxd + COMMENT "Converting to hpp: ${FILE_NAME} ${CMAKE_BINARY_DIR}/bin/$/xxd" + ) + else() + add_custom_command( + OUTPUT ${OUTPUT_HEADER_FILE} + COMMAND ${CMAKE_COMMAND} -E echo "/*THIS FILE HAS BEEN AUTOMATICALLY GENERATED - DO NOT EDIT*/" > ${OUTPUT_HEADER_FILE} + COMMAND ${CMAKE_COMMAND} -E echo \"\#ifndef ${HEADER_FILE_DEFINE}\" >> ${OUTPUT_HEADER_FILE} + COMMAND ${CMAKE_COMMAND} -E echo \"\#define ${HEADER_FILE_DEFINE}\" >> ${OUTPUT_HEADER_FILE} + COMMAND ${CMAKE_COMMAND} -E echo "namespace kp {" >> ${OUTPUT_HEADER_FILE} + COMMAND ${CMAKE_COMMAND} -E echo "namespace shader_data {" >> ${OUTPUT_HEADER_FILE} + COMMAND ${CMAKE_BINARY_DIR}/bin/xxd -i ${RAW_FILE_NAME} >> ${OUTPUT_HEADER_FILE} + COMMAND ${CMAKE_COMMAND} -E echo "}}" >> ${OUTPUT_HEADER_FILE} + COMMAND ${CMAKE_COMMAND} -E echo \"\#endif // define ${HEADER_FILE_DEFINE}\" >> ${OUTPUT_HEADER_FILE} + DEPENDS ${spv_file} xxd + COMMENT "Converting to hpp: ${FILE_NAME} ${CMAKE_BINARY_DIR}/bin/xxd" + ) + endif() + endforeach() + endfunction() + + if (EXISTS "${CMAKE_CURRENT_SOURCE_DIR}/kompute/CMakeLists.txt") + message(STATUS "Kompute found") + set(KOMPUTE_OPT_LOG_LEVEL Error CACHE STRING "Kompute log level") + add_subdirectory(kompute) + + # Compile our shaders + compile_shader(SOURCES + kompute-shaders/op_scale.comp + kompute-shaders/op_scale_8.comp + kompute-shaders/op_add.comp + kompute-shaders/op_addrow.comp + kompute-shaders/op_mul.comp + kompute-shaders/op_silu.comp + kompute-shaders/op_relu.comp + kompute-shaders/op_gelu.comp + kompute-shaders/op_softmax.comp + kompute-shaders/op_norm.comp + kompute-shaders/op_rmsnorm.comp + kompute-shaders/op_diagmask.comp + kompute-shaders/op_mul_mat_mat_f32.comp + kompute-shaders/op_mul_mat_f16.comp + kompute-shaders/op_mul_mat_q8_0.comp + kompute-shaders/op_mul_mat_q4_0.comp + kompute-shaders/op_mul_mat_q4_1.comp + kompute-shaders/op_mul_mat_q6_k.comp + kompute-shaders/op_getrows_f32.comp + kompute-shaders/op_getrows_f16.comp + kompute-shaders/op_getrows_q4_0.comp + kompute-shaders/op_getrows_q4_1.comp + kompute-shaders/op_getrows_q6_k.comp + kompute-shaders/op_rope_f16.comp + kompute-shaders/op_rope_f32.comp + kompute-shaders/op_cpy_f16_f16.comp + kompute-shaders/op_cpy_f16_f32.comp + kompute-shaders/op_cpy_f32_f16.comp + kompute-shaders/op_cpy_f32_f32.comp + ) + + # Create a custom target for our generated shaders + add_custom_target(generated_shaders DEPENDS + shaderop_scale.h + shaderop_scale_8.h + shaderop_add.h + shaderop_addrow.h + shaderop_mul.h + shaderop_silu.h + shaderop_relu.h + shaderop_gelu.h + shaderop_softmax.h + shaderop_norm.h + shaderop_rmsnorm.h + shaderop_diagmask.h + shaderop_mul_mat_mat_f32.h + shaderop_mul_mat_f16.h + shaderop_mul_mat_q8_0.h + shaderop_mul_mat_q4_0.h + shaderop_mul_mat_q4_1.h + shaderop_mul_mat_q6_k.h + shaderop_getrows_f32.h + shaderop_getrows_f16.h + shaderop_getrows_q4_0.h + shaderop_getrows_q4_1.h + shaderop_getrows_q6_k.h + shaderop_rope_f16.h + shaderop_rope_f32.h + shaderop_cpy_f16_f16.h + shaderop_cpy_f16_f32.h + shaderop_cpy_f32_f16.h + shaderop_cpy_f32_f32.h + ) + + # Create a custom command that depends on the generated_shaders + add_custom_command( + OUTPUT ${CMAKE_CURRENT_BINARY_DIR}/ggml-kompute.stamp + COMMAND ${CMAKE_COMMAND} -E touch ${CMAKE_CURRENT_BINARY_DIR}/ggml-kompute.stamp + DEPENDS generated_shaders + COMMENT "Ensuring shaders are generated before compiling ggml-kompute.cpp" + ) + + # Add the stamp to the main sources to ensure dependency tracking + set(GGML_SOURCES_KOMPUTE ggml-kompute.cpp ${CMAKE_CURRENT_BINARY_DIR}/ggml-kompute.stamp) + set(GGML_HEADERS_KOMPUTE ../include/ggml-kompute.h ${CMAKE_CURRENT_BINARY_DIR}/ggml-kompute.stamp) + + list(APPEND GGML_CDEF_PUBLIC GGML_USE_KOMPUTE) + + set(GGML_EXTRA_LIBS ${GGML_EXTRA_LIBS} kompute) + set(GGML_EXTRA_INCLUDES ${GGML_EXTRA_INCLUDES} ${CMAKE_CURRENT_BINARY_DIR}) + else() + message(WARNING "Kompute not found") + endif() +endif() + +if (GGML_CPU_HBM) + find_library(memkind memkind REQUIRED) + + message(STATUS "Using memkind for CPU HBM") + + add_compile_definitions(GGML_USE_CPU_HBM) + + target_link_libraries(ggml PUBLIC memkind) +endif() + +function(get_flags CCID CCVER) + set(C_FLAGS "") + set(CXX_FLAGS "") + + if (CCID MATCHES "Clang") + set(C_FLAGS -Wunreachable-code-break -Wunreachable-code-return) + set(CXX_FLAGS -Wunreachable-code-break -Wunreachable-code-return -Wmissing-prototypes -Wextra-semi) + + if ( + (CCID STREQUAL "Clang" AND CCVER VERSION_GREATER_EQUAL 3.8.0) OR + (CCID STREQUAL "AppleClang" AND CCVER VERSION_GREATER_EQUAL 7.3.0) + ) + list(APPEND C_FLAGS -Wdouble-promotion) + endif() + elseif (CCID STREQUAL "GNU") + set(C_FLAGS -Wdouble-promotion) + set(CXX_FLAGS -Wno-array-bounds) + + if (CCVER VERSION_GREATER_EQUAL 7.1.0) + list(APPEND CXX_FLAGS -Wno-format-truncation) + endif() + if (CCVER VERSION_GREATER_EQUAL 8.1.0) + list(APPEND CXX_FLAGS -Wextra-semi) + endif() + endif() + + set(GF_C_FLAGS ${C_FLAGS} PARENT_SCOPE) + set(GF_CXX_FLAGS ${CXX_FLAGS} PARENT_SCOPE) +endfunction() + +if (GGML_FATAL_WARNINGS) + if (CMAKE_CXX_COMPILER_ID MATCHES "GNU" OR CMAKE_CXX_COMPILER_ID MATCHES "Clang") + list(APPEND C_FLAGS -Werror) + list(APPEND CXX_FLAGS -Werror) + elseif (CMAKE_CXX_COMPILER_ID STREQUAL "MSVC") + add_compile_options(/WX) + endif() +endif() + +if (GGML_ALL_WARNINGS) + if (NOT MSVC) + list(APPEND WARNING_FLAGS -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function) + list(APPEND C_FLAGS -Wshadow -Wstrict-prototypes -Wpointer-arith -Wmissing-prototypes + -Werror=implicit-int -Werror=implicit-function-declaration) + list(APPEND CXX_FLAGS -Wmissing-declarations -Wmissing-noreturn) + + list(APPEND C_FLAGS ${WARNING_FLAGS}) + list(APPEND CXX_FLAGS ${WARNING_FLAGS}) + + get_flags(${CMAKE_CXX_COMPILER_ID} ${CMAKE_CXX_COMPILER_VERSION}) + + add_compile_options("$<$:${C_FLAGS};${GF_C_FLAGS}>" + "$<$:${CXX_FLAGS};${GF_CXX_FLAGS}>") + else() + # todo : msvc + set(C_FLAGS "") + set(CXX_FLAGS "") + endif() +endif() + +set(CUDA_CXX_FLAGS "") + +if (GGML_CUDA) + set(CUDA_FLAGS -use_fast_math) + + if (GGML_FATAL_WARNINGS) + list(APPEND CUDA_FLAGS -Werror all-warnings) + endif() + + if (GGML_ALL_WARNINGS AND NOT MSVC) + set(NVCC_CMD ${CMAKE_CUDA_COMPILER} .c) + if (NOT CMAKE_CUDA_HOST_COMPILER STREQUAL "") + list(APPEND NVCC_CMD -ccbin ${CMAKE_CUDA_HOST_COMPILER}) + endif() + + execute_process( + COMMAND ${NVCC_CMD} -Xcompiler --version + OUTPUT_VARIABLE CUDA_CCFULLVER + ERROR_QUIET + ) + + if (NOT CUDA_CCFULLVER MATCHES clang) + set(CUDA_CCID "GNU") + execute_process( + COMMAND ${NVCC_CMD} -Xcompiler "-dumpfullversion -dumpversion" + OUTPUT_VARIABLE CUDA_CCVER + ERROR_QUIET + ) + else() + if (CUDA_CCFULLVER MATCHES Apple) + set(CUDA_CCID "AppleClang") + else() + set(CUDA_CCID "Clang") + endif() + string(REGEX REPLACE "^.* version ([0-9.]*).*$" "\\1" CUDA_CCVER ${CUDA_CCFULLVER}) + endif() + + message("-- CUDA host compiler is ${CUDA_CCID} ${CUDA_CCVER}") + + get_flags(${CUDA_CCID} ${CUDA_CCVER}) + list(APPEND CUDA_CXX_FLAGS ${CXX_FLAGS} ${GF_CXX_FLAGS}) # This is passed to -Xcompiler later + endif() + + if (NOT MSVC) + list(APPEND CUDA_CXX_FLAGS -Wno-pedantic) + endif() +endif() + +if (GGML_LTO) + include(CheckIPOSupported) + check_ipo_supported(RESULT result OUTPUT output) + if (result) + set(CMAKE_INTERPROCEDURAL_OPTIMIZATION TRUE) + else() + message(WARNING "IPO is not supported: ${output}") + endif() +endif() + +if (GGML_CCACHE) + find_program(GGML_CCACHE_FOUND ccache) + + if (GGML_CCACHE_FOUND) + # TODO: should not be set globally + set_property(GLOBAL PROPERTY RULE_LAUNCH_COMPILE ccache) + set(ENV{CCACHE_SLOPPINESS} time_macros) + message(STATUS "ccache found, compilation results will be cached. Disable with GGML_CCACHE=OFF.") + else() + message(STATUS "Warning: ccache not found - consider installing it for faster compilation or disable this warning with GGML_CCACHE=OFF") + endif () +endif() + +# this version of Apple ld64 is buggy +execute_process( + COMMAND ${CMAKE_C_COMPILER} ${CMAKE_EXE_LINKER_FLAGS} -Wl,-v + ERROR_VARIABLE output + OUTPUT_QUIET +) + +if (output MATCHES "dyld-1015\.7") + add_compile_definitions(HAVE_BUGGY_APPLE_LINKER) +endif() + +# architecture specific +# TODO: probably these flags need to be tweaked on some architectures +# feel free to update the Makefile for your architecture and send a pull request or issue +message(STATUS "CMAKE_SYSTEM_PROCESSOR: ${CMAKE_SYSTEM_PROCESSOR}") +if (MSVC) + string(TOLOWER "${CMAKE_GENERATOR_PLATFORM}" CMAKE_GENERATOR_PLATFORM_LWR) + message(STATUS "CMAKE_GENERATOR_PLATFORM: ${CMAKE_GENERATOR_PLATFORM}") +else () + set(CMAKE_GENERATOR_PLATFORM_LWR "") +endif () + +if (NOT MSVC) + if (GGML_STATIC) + add_link_options(-static) + if (MINGW) + add_link_options(-static-libgcc -static-libstdc++) + endif() + endif() + if (GGML_GPROF) + add_compile_options(-pg) + endif() +endif() + +set(ARCH_FLAGS "") + +if (CMAKE_OSX_ARCHITECTURES STREQUAL "arm64" OR + CMAKE_GENERATOR_PLATFORM_LWR STREQUAL "arm64" OR + (NOT CMAKE_OSX_ARCHITECTURES AND + NOT CMAKE_GENERATOR_PLATFORM_LWR AND + CMAKE_SYSTEM_PROCESSOR MATCHES "^(aarch64|arm.*|ARM64)$")) + + message(STATUS "ARM detected") + + if (MSVC) + add_compile_definitions(__aarch64__) # MSVC defines _M_ARM64 instead + add_compile_definitions(__ARM_NEON) + add_compile_definitions(__ARM_FEATURE_FMA) + + set(CMAKE_REQUIRED_FLAGS_PREV ${CMAKE_REQUIRED_FLAGS}) + string(JOIN " " CMAKE_REQUIRED_FLAGS ${CMAKE_REQUIRED_FLAGS} "/arch:armv8.2") + + check_cxx_source_compiles("#include \nint main() { int8x16_t _a, _b; int32x4_t _s = vdotq_s32(_s, _a, _b); return 0; }" GGML_COMPILER_SUPPORT_DOTPROD) + if (GGML_COMPILER_SUPPORT_DOTPROD) + add_compile_definitions(__ARM_FEATURE_DOTPROD) + endif () + + check_cxx_source_compiles("#include \nint main() { int8x16_t _a, _b; int32x4_t _s = vmlaq_f32(_s, _a, _b); return 0; }" GGML_COMPILER_SUPPORT_MATMUL_INT8) + + if (GGML_COMPILER_SUPPORT_MATMUL_INT8) + add_compile_definitions(__ARM_FEATURE_MATMUL_INT8) + endif () + + check_cxx_source_compiles("#include \nint main() { float16_t _a; float16x8_t _s = vdupq_n_f16(_a); return 0; }" GGML_COMPILER_SUPPORT_FP16_VECTOR_ARITHMETIC) + if (GGML_COMPILER_SUPPORT_FP16_VECTOR_ARITHMETIC) + add_compile_definitions(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) + endif () + + set(CMAKE_REQUIRED_FLAGS ${CMAKE_REQUIRED_FLAGS_PREV}) + else() + check_cxx_compiler_flag(-mfp16-format=ieee COMPILER_SUPPORTS_FP16_FORMAT_I3E) + if (NOT "${COMPILER_SUPPORTS_FP16_FORMAT_I3E}" STREQUAL "") + list(APPEND ARCH_FLAGS -mfp16-format=ieee) + endif() + if (${CMAKE_SYSTEM_PROCESSOR} MATCHES "armv6") + # Raspberry Pi 1, Zero + list(APPEND ARCH_FLAGS -mfpu=neon-fp-armv8 -mno-unaligned-access) + endif() + if (${CMAKE_SYSTEM_PROCESSOR} MATCHES "armv7") + if ("${CMAKE_SYSTEM_NAME}" STREQUAL "Android") + # Android armeabi-v7a + list(APPEND ARCH_FLAGS -mfpu=neon-vfpv4 -mno-unaligned-access -funsafe-math-optimizations) + else() + # Raspberry Pi 2 + list(APPEND ARCH_FLAGS -mfpu=neon-fp-armv8 -mno-unaligned-access -funsafe-math-optimizations) + endif() + endif() + if (${CMAKE_SYSTEM_PROCESSOR} MATCHES "armv8") + # Android arm64-v8a + # Raspberry Pi 3, 4, Zero 2 (32-bit) + list(APPEND ARCH_FLAGS -mno-unaligned-access) + endif() + if (GGML_SVE) + list(APPEND ARCH_FLAGS -march=armv8.6-a+sve) + endif() + endif() +elseif (CMAKE_OSX_ARCHITECTURES STREQUAL "x86_64" OR CMAKE_GENERATOR_PLATFORM_LWR MATCHES "^(x86_64|i686|amd64|x64|win32)$" OR + (NOT CMAKE_OSX_ARCHITECTURES AND NOT CMAKE_GENERATOR_PLATFORM_LWR AND + CMAKE_SYSTEM_PROCESSOR MATCHES "^(x86_64|i686|AMD64)$")) + message(STATUS "x86 detected") + if (MSVC) + # instruction set detection for MSVC only + if (GGML_NATIVE) + # TODO: improve, should not reference files from the parent folder + include(../cmake/FindSIMD.cmake) + endif () + if (GGML_AVX512) + list(APPEND ARCH_FLAGS /arch:AVX512) + # MSVC has no compile-time flags enabling specific + # AVX512 extensions, neither it defines the + # macros corresponding to the extensions. + # Do it manually. + if (GGML_AVX512_VBMI) + add_compile_definitions($<$:__AVX512VBMI__>) + add_compile_definitions($<$:__AVX512VBMI__>) + endif() + if (GGML_AVX512_VNNI) + add_compile_definitions($<$:__AVX512VNNI__>) + add_compile_definitions($<$:__AVX512VNNI__>) + endif() + if (GGML_AVX512_BF16) + add_compile_definitions($<$:__AVX512BF16__>) + add_compile_definitions($<$:__AVX512BF16__>) + endif() + elseif (GGML_AVX2) + list(APPEND ARCH_FLAGS /arch:AVX2) + elseif (GGML_AVX) + list(APPEND ARCH_FLAGS /arch:AVX) + endif() + else() + if (GGML_NATIVE) + list(APPEND ARCH_FLAGS -march=native) + endif() + if (GGML_F16C) + list(APPEND ARCH_FLAGS -mf16c) + endif() + if (GGML_FMA) + list(APPEND ARCH_FLAGS -mfma) + endif() + if (GGML_AVX) + list(APPEND ARCH_FLAGS -mavx) + endif() + if (GGML_AVX2) + list(APPEND ARCH_FLAGS -mavx2) + endif() + if (GGML_AVX512) + list(APPEND ARCH_FLAGS -mavx512f) + list(APPEND ARCH_FLAGS -mavx512bw) + endif() + if (GGML_AVX512_VBMI) + list(APPEND ARCH_FLAGS -mavx512vbmi) + endif() + if (GGML_AVX512_VNNI) + list(APPEND ARCH_FLAGS -mavx512vnni) + endif() + if (GGML_AVX512_BF16) + list(APPEND ARCH_FLAGS -mavx512bf16) + endif() + endif() +elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "ppc64") + message(STATUS "PowerPC detected") + if (${CMAKE_SYSTEM_PROCESSOR} MATCHES "ppc64le") + list(APPEND ARCH_FLAGS -mcpu=powerpc64le) + else() + list(APPEND ARCH_FLAGS -mcpu=native -mtune=native) + #TODO: Add targets for Power8/Power9 (Altivec/VSX) and Power10(MMA) and query for big endian systems (ppc64/le/be) + endif() +elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "loongarch64") + message(STATUS "loongarch64 detected") + + list(APPEND ARCH_FLAGS -march=loongarch64) + if (GGML_LASX) + list(APPEND ARCH_FLAGS -mlasx) + endif() + if (GGML_LSX) + list(APPEND ARCH_FLAGS -mlsx) + endif() +else() + message(STATUS "Unknown architecture") +endif() + +add_compile_options("$<$:${ARCH_FLAGS}>") +add_compile_options("$<$:${ARCH_FLAGS}>") + +if (GGML_CUDA) + list(APPEND CUDA_CXX_FLAGS ${ARCH_FLAGS}) + list(JOIN CUDA_CXX_FLAGS " " CUDA_CXX_FLAGS_JOINED) # pass host compiler flags as a single argument + + if (NOT CUDA_CXX_FLAGS_JOINED STREQUAL "") + list(APPEND CUDA_FLAGS -Xcompiler ${CUDA_CXX_FLAGS_JOINED}) + endif() + + add_compile_options("$<$:${CUDA_FLAGS}>") +endif() + +if (MINGW) + # Target Windows 8 for PrefetchVirtualMemory + add_compile_definitions(_WIN32_WINNT=${GGML_WIN_VER}) +endif() + +# +# POSIX conformance +# + +# clock_gettime came in POSIX.1b (1993) +# CLOCK_MONOTONIC came in POSIX.1-2001 / SUSv3 as optional +# posix_memalign came in POSIX.1-2001 / SUSv3 +# M_PI is an XSI extension since POSIX.1-2001 / SUSv3, came in XPG1 (1985) +add_compile_definitions(_XOPEN_SOURCE=600) + +# Somehow in OpenBSD whenever POSIX conformance is specified +# some string functions rely on locale_t availability, +# which was introduced in POSIX.1-2008, forcing us to go higher +if (CMAKE_SYSTEM_NAME MATCHES "OpenBSD") + remove_definitions(-D_XOPEN_SOURCE=600) + add_compile_definitions(_XOPEN_SOURCE=700) +endif() + +# Data types, macros and functions related to controlling CPU affinity and +# some memory allocation are available on Linux through GNU extensions in libc +if (CMAKE_SYSTEM_NAME MATCHES "Linux") + add_compile_definitions(_GNU_SOURCE) +endif() + +# RLIMIT_MEMLOCK came in BSD, is not specified in POSIX.1, +# and on macOS its availability depends on enabling Darwin extensions +# similarly on DragonFly, enabling BSD extensions is necessary +if ( + CMAKE_SYSTEM_NAME MATCHES "Darwin" OR + CMAKE_SYSTEM_NAME MATCHES "iOS" OR + CMAKE_SYSTEM_NAME MATCHES "tvOS" OR + CMAKE_SYSTEM_NAME MATCHES "DragonFly" +) + add_compile_definitions(_DARWIN_C_SOURCE) +endif() + +# alloca is a non-standard interface that is not visible on BSDs when +# POSIX conformance is specified, but not all of them provide a clean way +# to enable it in such cases +if (CMAKE_SYSTEM_NAME MATCHES "FreeBSD") + add_compile_definitions(__BSD_VISIBLE) +endif() +if (CMAKE_SYSTEM_NAME MATCHES "NetBSD") + add_compile_definitions(_NETBSD_SOURCE) +endif() +if (CMAKE_SYSTEM_NAME MATCHES "OpenBSD") + add_compile_definitions(_BSD_SOURCE) +endif() + +if (WIN32) + add_compile_definitions(_CRT_SECURE_NO_WARNINGS) + + if (BUILD_SHARED_LIBS) + # TODO: should not use this + set(CMAKE_WINDOWS_EXPORT_ALL_SYMBOLS ON) + endif() +endif() + +# +# libraries +# + +# ggml + +add_library(ggml + ../include/ggml.h + ../include/ggml-alloc.h + ../include/ggml-backend.h + ggml.c + ggml-alloc.c + ggml-backend.c + ggml-quants.c + ggml-quants.h + ${GGML_SOURCES_CUDA} ${GGML_HEADERS_CUDA} + ${GGML_SOURCES_METAL} ${GGML_HEADERS_METAL} + ${GGML_SOURCES_RPC} ${GGML_HEADERS_RPC} + ${GGML_SOURCES_EXTRA} ${GGML_HEADERS_EXTRA} + ${GGML_SOURCES_SYCL} ${GGML_HEADERS_SYCL} + ${GGML_SOURCES_KOMPUTE} ${GGML_HEADERS_KOMPUTE} + ${GGML_SOURCES_VULKAN} ${GGML_HEADERS_VULKAN} + ${GGML_SOURCES_ROCM} ${GGML_HEADERS_ROCM} + ${GGML_SOURCES_BLAS} ${GGML_HEADERS_BLAS} + ${GGML_SOURCES_LLAMAFILE} ${GGML_HEADERS_LLAMAFILE} + ) + +if (EMSCRIPTEN) + set_target_properties(ggml PROPERTIES COMPILE_FLAGS "-msimd128") +endif() + +target_compile_definitions(ggml PUBLIC ${GGML_CDEF_PUBLIC}) +target_include_directories(ggml PUBLIC ../include) +target_include_directories(ggml PRIVATE . ${GGML_EXTRA_INCLUDES}) +target_compile_features (ggml PRIVATE c_std_11) # don't bump + +target_link_libraries(ggml PRIVATE Threads::Threads ${GGML_EXTRA_LIBS}) + +find_library(MATH_LIBRARY m) +if (MATH_LIBRARY) + target_link_libraries(ggml PRIVATE ${MATH_LIBRARY}) +endif() + +if (BUILD_SHARED_LIBS) + set_target_properties(ggml PROPERTIES POSITION_INDEPENDENT_CODE ON) +endif() diff --git a/ggml-alloc.c b/ggml/src/ggml-alloc.c similarity index 100% rename from ggml-alloc.c rename to ggml/src/ggml-alloc.c diff --git a/ggml-backend-impl.h b/ggml/src/ggml-backend-impl.h similarity index 100% rename from ggml-backend-impl.h rename to ggml/src/ggml-backend-impl.h diff --git a/ggml-backend.c b/ggml/src/ggml-backend.c similarity index 100% rename from ggml-backend.c rename to ggml/src/ggml-backend.c diff --git a/ggml-blas.cpp b/ggml/src/ggml-blas.cpp similarity index 100% rename from ggml-blas.cpp rename to ggml/src/ggml-blas.cpp diff --git a/ggml-common.h b/ggml/src/ggml-common.h similarity index 100% rename from ggml-common.h rename to ggml/src/ggml-common.h diff --git a/ggml-cuda.cu b/ggml/src/ggml-cuda.cu similarity index 100% rename from ggml-cuda.cu rename to ggml/src/ggml-cuda.cu diff --git a/ggml-cuda/acc.cu b/ggml/src/ggml-cuda/acc.cu similarity index 100% rename from ggml-cuda/acc.cu rename to ggml/src/ggml-cuda/acc.cu diff --git a/ggml-cuda/acc.cuh b/ggml/src/ggml-cuda/acc.cuh similarity index 100% rename from ggml-cuda/acc.cuh rename to ggml/src/ggml-cuda/acc.cuh diff --git a/ggml-cuda/arange.cu b/ggml/src/ggml-cuda/arange.cu similarity index 100% rename from ggml-cuda/arange.cu rename to ggml/src/ggml-cuda/arange.cu diff --git a/ggml-cuda/arange.cuh b/ggml/src/ggml-cuda/arange.cuh similarity index 100% rename from ggml-cuda/arange.cuh rename to ggml/src/ggml-cuda/arange.cuh diff --git a/ggml-cuda/argsort.cu b/ggml/src/ggml-cuda/argsort.cu similarity index 100% rename from ggml-cuda/argsort.cu rename to ggml/src/ggml-cuda/argsort.cu diff --git a/ggml-cuda/argsort.cuh b/ggml/src/ggml-cuda/argsort.cuh similarity index 100% rename from ggml-cuda/argsort.cuh rename to ggml/src/ggml-cuda/argsort.cuh diff --git a/ggml-cuda/binbcast.cu b/ggml/src/ggml-cuda/binbcast.cu similarity index 100% rename from ggml-cuda/binbcast.cu rename to ggml/src/ggml-cuda/binbcast.cu diff --git a/ggml-cuda/binbcast.cuh b/ggml/src/ggml-cuda/binbcast.cuh similarity index 100% rename from ggml-cuda/binbcast.cuh rename to ggml/src/ggml-cuda/binbcast.cuh diff --git a/ggml-cuda/clamp.cu b/ggml/src/ggml-cuda/clamp.cu similarity index 100% rename from ggml-cuda/clamp.cu rename to ggml/src/ggml-cuda/clamp.cu diff --git a/ggml-cuda/clamp.cuh b/ggml/src/ggml-cuda/clamp.cuh similarity index 100% rename from ggml-cuda/clamp.cuh rename to ggml/src/ggml-cuda/clamp.cuh diff --git a/ggml-cuda/common.cuh b/ggml/src/ggml-cuda/common.cuh similarity index 100% rename from ggml-cuda/common.cuh rename to ggml/src/ggml-cuda/common.cuh diff --git a/ggml-cuda/concat.cu b/ggml/src/ggml-cuda/concat.cu similarity index 100% rename from ggml-cuda/concat.cu rename to ggml/src/ggml-cuda/concat.cu diff --git a/ggml-cuda/concat.cuh b/ggml/src/ggml-cuda/concat.cuh similarity index 100% rename from ggml-cuda/concat.cuh rename to ggml/src/ggml-cuda/concat.cuh diff --git a/ggml-cuda/convert.cu b/ggml/src/ggml-cuda/convert.cu similarity index 100% rename from ggml-cuda/convert.cu rename to ggml/src/ggml-cuda/convert.cu diff --git a/ggml-cuda/convert.cuh b/ggml/src/ggml-cuda/convert.cuh similarity index 100% rename from ggml-cuda/convert.cuh rename to ggml/src/ggml-cuda/convert.cuh diff --git a/ggml-cuda/cpy.cu b/ggml/src/ggml-cuda/cpy.cu similarity index 100% rename from ggml-cuda/cpy.cu rename to ggml/src/ggml-cuda/cpy.cu diff --git a/ggml-cuda/cpy.cuh b/ggml/src/ggml-cuda/cpy.cuh similarity index 100% rename from ggml-cuda/cpy.cuh rename to ggml/src/ggml-cuda/cpy.cuh diff --git a/ggml-cuda/dequantize.cuh b/ggml/src/ggml-cuda/dequantize.cuh similarity index 100% rename from ggml-cuda/dequantize.cuh rename to ggml/src/ggml-cuda/dequantize.cuh diff --git a/ggml-cuda/diagmask.cu b/ggml/src/ggml-cuda/diagmask.cu similarity index 100% rename from ggml-cuda/diagmask.cu rename to ggml/src/ggml-cuda/diagmask.cu diff --git a/ggml-cuda/diagmask.cuh b/ggml/src/ggml-cuda/diagmask.cuh similarity index 100% rename from ggml-cuda/diagmask.cuh rename to ggml/src/ggml-cuda/diagmask.cuh diff --git a/ggml-cuda/dmmv.cu b/ggml/src/ggml-cuda/dmmv.cu similarity index 100% rename from ggml-cuda/dmmv.cu rename to ggml/src/ggml-cuda/dmmv.cu diff --git a/ggml-cuda/dmmv.cuh b/ggml/src/ggml-cuda/dmmv.cuh similarity index 100% rename from ggml-cuda/dmmv.cuh rename to ggml/src/ggml-cuda/dmmv.cuh diff --git a/ggml-cuda/fattn-common.cuh b/ggml/src/ggml-cuda/fattn-common.cuh similarity index 99% rename from ggml-cuda/fattn-common.cuh rename to ggml/src/ggml-cuda/fattn-common.cuh index 37b3b99323b20..bd7993595467c 100644 --- a/ggml-cuda/fattn-common.cuh +++ b/ggml/src/ggml-cuda/fattn-common.cuh @@ -603,7 +603,7 @@ static void on_no_fattn_vec_case(const int D) { if (D == 64) { fprintf(stderr, "Unsupported KV type combination for head_size 64.\n"); fprintf(stderr, "By default only f16 KV cache is supported.\n"); - fprintf(stderr, "Compile with LLAMA_CUDA_FA_ALL_QUANTS for V cache quantization support.\n"); + fprintf(stderr, "Compile with GGML_CUDA_FA_ALL_QUANTS for V cache quantization support.\n"); GGML_ASSERT(false); } else if (D == 128) { fprintf(stderr, "Unsupported KV type combination for head_size 128.\n"); @@ -611,7 +611,7 @@ static void on_no_fattn_vec_case(const int D) { fprintf(stderr, " - K == q4_0, V == q4_0, 4.50 BPV\n"); fprintf(stderr, " - K == q8_0, V == q8_0, 8.50 BPV\n"); fprintf(stderr, " - K == f16, V == f16, 16.00 BPV\n"); - fprintf(stderr, "Compile with LLAMA_CUDA_FA_ALL_QUANTS for all combinations of q4_0, q4_1, q5_0, q5_1, q8_0, and f16.\n"); + fprintf(stderr, "Compile with GGML_CUDA_FA_ALL_QUANTS for all combinations of q4_0, q4_1, q5_0, q5_1, q8_0, and f16.\n"); GGML_ASSERT(false); } else { fprintf(stderr, "Unsupported KV type combination for head_size 256.\n"); diff --git a/ggml-cuda/fattn-tile-f16.cu b/ggml/src/ggml-cuda/fattn-tile-f16.cu similarity index 100% rename from ggml-cuda/fattn-tile-f16.cu rename to ggml/src/ggml-cuda/fattn-tile-f16.cu diff --git a/ggml-cuda/fattn-tile-f16.cuh b/ggml/src/ggml-cuda/fattn-tile-f16.cuh similarity index 100% rename from ggml-cuda/fattn-tile-f16.cuh rename to ggml/src/ggml-cuda/fattn-tile-f16.cuh diff --git a/ggml-cuda/fattn-tile-f32.cu b/ggml/src/ggml-cuda/fattn-tile-f32.cu similarity index 100% rename from ggml-cuda/fattn-tile-f32.cu rename to ggml/src/ggml-cuda/fattn-tile-f32.cu diff --git a/ggml-cuda/fattn-tile-f32.cuh b/ggml/src/ggml-cuda/fattn-tile-f32.cuh similarity index 100% rename from ggml-cuda/fattn-tile-f32.cuh rename to ggml/src/ggml-cuda/fattn-tile-f32.cuh diff --git a/ggml-cuda/fattn-vec-f16.cuh b/ggml/src/ggml-cuda/fattn-vec-f16.cuh similarity index 100% rename from ggml-cuda/fattn-vec-f16.cuh rename to ggml/src/ggml-cuda/fattn-vec-f16.cuh diff --git a/ggml-cuda/fattn-vec-f32.cuh b/ggml/src/ggml-cuda/fattn-vec-f32.cuh similarity index 100% rename from ggml-cuda/fattn-vec-f32.cuh rename to ggml/src/ggml-cuda/fattn-vec-f32.cuh diff --git a/ggml-cuda/fattn-wmma-f16.cuh b/ggml/src/ggml-cuda/fattn-wmma-f16.cuh similarity index 100% rename from ggml-cuda/fattn-wmma-f16.cuh rename to ggml/src/ggml-cuda/fattn-wmma-f16.cuh diff --git a/ggml-cuda/fattn.cu b/ggml/src/ggml-cuda/fattn.cu similarity index 100% rename from ggml-cuda/fattn.cu rename to ggml/src/ggml-cuda/fattn.cu diff --git a/ggml-cuda/fattn.cuh b/ggml/src/ggml-cuda/fattn.cuh similarity index 100% rename from ggml-cuda/fattn.cuh rename to ggml/src/ggml-cuda/fattn.cuh diff --git a/ggml-cuda/getrows.cu b/ggml/src/ggml-cuda/getrows.cu similarity index 100% rename from ggml-cuda/getrows.cu rename to ggml/src/ggml-cuda/getrows.cu diff --git a/ggml-cuda/getrows.cuh b/ggml/src/ggml-cuda/getrows.cuh similarity index 100% rename from ggml-cuda/getrows.cuh rename to ggml/src/ggml-cuda/getrows.cuh diff --git a/ggml-cuda/im2col.cu b/ggml/src/ggml-cuda/im2col.cu similarity index 100% rename from ggml-cuda/im2col.cu rename to ggml/src/ggml-cuda/im2col.cu diff --git a/ggml-cuda/im2col.cuh b/ggml/src/ggml-cuda/im2col.cuh similarity index 100% rename from ggml-cuda/im2col.cuh rename to ggml/src/ggml-cuda/im2col.cuh diff --git a/ggml-cuda/mma.cuh b/ggml/src/ggml-cuda/mma.cuh similarity index 100% rename from ggml-cuda/mma.cuh rename to ggml/src/ggml-cuda/mma.cuh diff --git a/ggml-cuda/mmq.cu b/ggml/src/ggml-cuda/mmq.cu similarity index 100% rename from ggml-cuda/mmq.cu rename to ggml/src/ggml-cuda/mmq.cu diff --git a/ggml-cuda/mmq.cuh b/ggml/src/ggml-cuda/mmq.cuh similarity index 100% rename from ggml-cuda/mmq.cuh rename to ggml/src/ggml-cuda/mmq.cuh diff --git a/ggml-cuda/mmvq.cu b/ggml/src/ggml-cuda/mmvq.cu similarity index 100% rename from ggml-cuda/mmvq.cu rename to ggml/src/ggml-cuda/mmvq.cu diff --git a/ggml-cuda/mmvq.cuh b/ggml/src/ggml-cuda/mmvq.cuh similarity index 100% rename from ggml-cuda/mmvq.cuh rename to ggml/src/ggml-cuda/mmvq.cuh diff --git a/ggml-cuda/norm.cu b/ggml/src/ggml-cuda/norm.cu similarity index 100% rename from ggml-cuda/norm.cu rename to ggml/src/ggml-cuda/norm.cu diff --git a/ggml-cuda/norm.cuh 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from ggml-cuda/quantize.cuh rename to ggml/src/ggml-cuda/quantize.cuh diff --git a/ggml-cuda/rope.cu b/ggml/src/ggml-cuda/rope.cu similarity index 100% rename from ggml-cuda/rope.cu rename to ggml/src/ggml-cuda/rope.cu diff --git a/ggml-cuda/rope.cuh b/ggml/src/ggml-cuda/rope.cuh similarity index 100% rename from ggml-cuda/rope.cuh rename to ggml/src/ggml-cuda/rope.cuh diff --git a/ggml-cuda/scale.cu b/ggml/src/ggml-cuda/scale.cu similarity index 100% rename from ggml-cuda/scale.cu rename to ggml/src/ggml-cuda/scale.cu diff --git a/ggml-cuda/scale.cuh b/ggml/src/ggml-cuda/scale.cuh similarity index 100% rename from ggml-cuda/scale.cuh rename to ggml/src/ggml-cuda/scale.cuh diff --git a/ggml-cuda/softmax.cu b/ggml/src/ggml-cuda/softmax.cu similarity index 100% rename from ggml-cuda/softmax.cu rename to ggml/src/ggml-cuda/softmax.cu diff --git a/ggml-cuda/softmax.cuh b/ggml/src/ggml-cuda/softmax.cuh similarity index 100% rename from ggml-cuda/softmax.cuh rename to 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ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-f16-q5_1.cu rename to ggml/src/ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-f16-q5_1.cu diff --git a/ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-f16-q8_0.cu b/ggml/src/ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-f16-q8_0.cu similarity index 100% rename from ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-f16-q8_0.cu rename to ggml/src/ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-f16-q8_0.cu diff --git a/ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-q4_0-f16.cu b/ggml/src/ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-q4_0-f16.cu similarity index 100% rename from ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-q4_0-f16.cu rename to ggml/src/ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-q4_0-f16.cu diff --git a/ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-q4_0-q4_0.cu 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diff --git a/ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-q4_0-q5_1.cu b/ggml/src/ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-q4_0-q5_1.cu similarity index 100% rename from ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-q4_0-q5_1.cu rename to ggml/src/ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-q4_0-q5_1.cu diff --git a/ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-q4_0-q8_0.cu b/ggml/src/ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-q4_0-q8_0.cu similarity index 100% rename from ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-q4_0-q8_0.cu rename to ggml/src/ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-q4_0-q8_0.cu diff --git a/ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-q4_1-f16.cu b/ggml/src/ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-q4_1-f16.cu similarity index 100% rename from ggml-cuda/template-instances/fattn-vec-f16-instance-hs128-q4_1-f16.cu rename to 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diff --git a/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_0-q5_1.cu b/ggml/src/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_0-q5_1.cu similarity index 100% rename from ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_0-q5_1.cu rename to ggml/src/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_0-q5_1.cu diff --git a/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_0-q8_0.cu b/ggml/src/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_0-q8_0.cu similarity index 100% rename from ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_0-q8_0.cu rename to ggml/src/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_0-q8_0.cu diff --git a/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-f16.cu b/ggml/src/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-f16.cu similarity index 100% rename from ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-f16.cu rename to ggml/src/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-f16.cu diff --git a/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q4_0.cu b/ggml/src/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q4_0.cu similarity index 100% rename from ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q4_0.cu rename to ggml/src/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q4_0.cu diff --git a/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q4_1.cu b/ggml/src/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q4_1.cu similarity index 100% rename from ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q4_1.cu rename to ggml/src/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q4_1.cu diff --git a/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q5_0.cu b/ggml/src/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q5_0.cu similarity index 100% rename from ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q5_0.cu rename to ggml/src/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q5_0.cu diff --git a/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q5_1.cu b/ggml/src/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q5_1.cu similarity index 100% rename from ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q5_1.cu rename to ggml/src/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q5_1.cu diff --git a/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q8_0.cu b/ggml/src/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q8_0.cu similarity index 100% rename from ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q8_0.cu rename to ggml/src/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q5_1-q8_0.cu diff --git a/ggml-cuda/template-instances/fattn-vec-f32-instance-hs128-q8_0-f16.cu 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a/ggml-cuda/template-instances/mmq-instance-q3_k.cu b/ggml/src/ggml-cuda/template-instances/mmq-instance-q3_k.cu similarity index 100% rename from ggml-cuda/template-instances/mmq-instance-q3_k.cu rename to ggml/src/ggml-cuda/template-instances/mmq-instance-q3_k.cu diff --git a/ggml-cuda/template-instances/mmq-instance-q4_0.cu b/ggml/src/ggml-cuda/template-instances/mmq-instance-q4_0.cu similarity index 100% rename from ggml-cuda/template-instances/mmq-instance-q4_0.cu rename to ggml/src/ggml-cuda/template-instances/mmq-instance-q4_0.cu diff --git a/ggml-cuda/template-instances/mmq-instance-q4_1.cu b/ggml/src/ggml-cuda/template-instances/mmq-instance-q4_1.cu similarity index 100% rename from ggml-cuda/template-instances/mmq-instance-q4_1.cu rename to ggml/src/ggml-cuda/template-instances/mmq-instance-q4_1.cu diff --git a/ggml-cuda/template-instances/mmq-instance-q4_k.cu b/ggml/src/ggml-cuda/template-instances/mmq-instance-q4_k.cu similarity index 100% rename from ggml-cuda/template-instances/mmq-instance-q4_k.cu rename to ggml/src/ggml-cuda/template-instances/mmq-instance-q4_k.cu diff --git a/ggml-cuda/template-instances/mmq-instance-q5_0.cu b/ggml/src/ggml-cuda/template-instances/mmq-instance-q5_0.cu similarity index 100% rename from ggml-cuda/template-instances/mmq-instance-q5_0.cu rename to ggml/src/ggml-cuda/template-instances/mmq-instance-q5_0.cu diff --git a/ggml-cuda/template-instances/mmq-instance-q5_1.cu b/ggml/src/ggml-cuda/template-instances/mmq-instance-q5_1.cu similarity index 100% rename from ggml-cuda/template-instances/mmq-instance-q5_1.cu rename to ggml/src/ggml-cuda/template-instances/mmq-instance-q5_1.cu diff --git a/ggml-cuda/template-instances/mmq-instance-q5_k.cu b/ggml/src/ggml-cuda/template-instances/mmq-instance-q5_k.cu similarity index 100% rename from ggml-cuda/template-instances/mmq-instance-q5_k.cu rename to ggml/src/ggml-cuda/template-instances/mmq-instance-q5_k.cu diff --git a/ggml-cuda/template-instances/mmq-instance-q6_k.cu b/ggml/src/ggml-cuda/template-instances/mmq-instance-q6_k.cu similarity index 100% rename from ggml-cuda/template-instances/mmq-instance-q6_k.cu rename to ggml/src/ggml-cuda/template-instances/mmq-instance-q6_k.cu diff --git a/ggml-cuda/template-instances/mmq-instance-q8_0.cu b/ggml/src/ggml-cuda/template-instances/mmq-instance-q8_0.cu similarity index 100% rename from ggml-cuda/template-instances/mmq-instance-q8_0.cu rename to ggml/src/ggml-cuda/template-instances/mmq-instance-q8_0.cu diff --git a/ggml-cuda/tsembd.cu b/ggml/src/ggml-cuda/tsembd.cu similarity index 100% rename from ggml-cuda/tsembd.cu rename to ggml/src/ggml-cuda/tsembd.cu diff --git a/ggml-cuda/tsembd.cuh b/ggml/src/ggml-cuda/tsembd.cuh similarity index 100% rename from ggml-cuda/tsembd.cuh rename to ggml/src/ggml-cuda/tsembd.cuh diff --git a/ggml-cuda/unary.cu b/ggml/src/ggml-cuda/unary.cu similarity index 100% rename from ggml-cuda/unary.cu rename to ggml/src/ggml-cuda/unary.cu diff --git a/ggml-cuda/unary.cuh b/ggml/src/ggml-cuda/unary.cuh similarity index 100% rename from ggml-cuda/unary.cuh rename to ggml/src/ggml-cuda/unary.cuh diff --git a/ggml-cuda/upscale.cu b/ggml/src/ggml-cuda/upscale.cu similarity index 100% rename from ggml-cuda/upscale.cu rename to ggml/src/ggml-cuda/upscale.cu diff --git a/ggml-cuda/upscale.cuh b/ggml/src/ggml-cuda/upscale.cuh similarity index 100% rename from ggml-cuda/upscale.cuh rename to ggml/src/ggml-cuda/upscale.cuh diff --git a/ggml-cuda/vecdotq.cuh b/ggml/src/ggml-cuda/vecdotq.cuh similarity index 100% rename from ggml-cuda/vecdotq.cuh rename to ggml/src/ggml-cuda/vecdotq.cuh diff --git a/ggml-impl.h b/ggml/src/ggml-impl.h similarity index 100% rename from ggml-impl.h rename to ggml/src/ggml-impl.h diff --git a/ggml-kompute.cpp b/ggml/src/ggml-kompute.cpp similarity index 100% rename from ggml-kompute.cpp rename to ggml/src/ggml-kompute.cpp diff --git a/ggml-metal.m b/ggml/src/ggml-metal.m similarity index 100% rename from ggml-metal.m rename to ggml/src/ggml-metal.m diff --git a/ggml-metal.metal b/ggml/src/ggml-metal.metal similarity index 100% rename from ggml-metal.metal rename to ggml/src/ggml-metal.metal diff --git a/ggml-quants.c b/ggml/src/ggml-quants.c similarity index 100% rename from ggml-quants.c rename to ggml/src/ggml-quants.c diff --git a/ggml-quants.h b/ggml/src/ggml-quants.h similarity index 100% rename from ggml-quants.h rename to ggml/src/ggml-quants.h diff --git a/ggml-rpc.cpp b/ggml/src/ggml-rpc.cpp similarity index 100% rename from ggml-rpc.cpp rename to ggml/src/ggml-rpc.cpp diff --git a/ggml-sycl.cpp b/ggml/src/ggml-sycl.cpp similarity index 99% rename from ggml-sycl.cpp rename to ggml/src/ggml-sycl.cpp index db045336f1edb..4a668a2c34d3e 100644 --- a/ggml-sycl.cpp +++ b/ggml/src/ggml-sycl.cpp @@ -37,6 +37,7 @@ #include "ggml-backend-impl.h" #include "ggml-sycl/backend.hpp" +#include "ggml-sycl/presets.hpp" bool ggml_sycl_loaded(void); void ggml_sycl_free_data(struct ggml_tensor * tensor); diff --git a/ggml-sycl/backend.hpp b/ggml/src/ggml-sycl/backend.hpp similarity index 100% rename from ggml-sycl/backend.hpp rename to ggml/src/ggml-sycl/backend.hpp diff --git a/ggml-sycl/common.cpp b/ggml/src/ggml-sycl/common.cpp similarity index 100% rename from ggml-sycl/common.cpp rename to ggml/src/ggml-sycl/common.cpp diff --git a/ggml-sycl/common.hpp b/ggml/src/ggml-sycl/common.hpp similarity index 99% rename from ggml-sycl/common.hpp rename to ggml/src/ggml-sycl/common.hpp index 414c37eed0d5d..e01f91633a4bf 100644 --- a/ggml-sycl/common.hpp +++ b/ggml/src/ggml-sycl/common.hpp @@ -17,6 +17,7 @@ #include #include "dpct/helper.hpp" +#include "ggml-sycl.h" #include "presets.hpp" #define GGML_COMMON_DECL_SYCL diff --git a/ggml-sycl/convert.cpp b/ggml/src/ggml-sycl/convert.cpp similarity index 100% rename from ggml-sycl/convert.cpp rename to ggml/src/ggml-sycl/convert.cpp diff --git a/ggml-sycl/convert.hpp b/ggml/src/ggml-sycl/convert.hpp similarity index 100% rename from ggml-sycl/convert.hpp rename to ggml/src/ggml-sycl/convert.hpp diff --git a/ggml-sycl/dequantize.hpp b/ggml/src/ggml-sycl/dequantize.hpp similarity index 100% rename from ggml-sycl/dequantize.hpp rename to ggml/src/ggml-sycl/dequantize.hpp diff --git a/ggml-sycl/dmmv.cpp b/ggml/src/ggml-sycl/dmmv.cpp similarity index 100% rename from ggml-sycl/dmmv.cpp rename to ggml/src/ggml-sycl/dmmv.cpp diff --git a/ggml-sycl/dmmv.hpp b/ggml/src/ggml-sycl/dmmv.hpp similarity index 100% rename from ggml-sycl/dmmv.hpp rename to ggml/src/ggml-sycl/dmmv.hpp diff --git a/ggml-sycl/dpct/helper.hpp b/ggml/src/ggml-sycl/dpct/helper.hpp similarity index 100% rename from ggml-sycl/dpct/helper.hpp rename to ggml/src/ggml-sycl/dpct/helper.hpp diff --git a/ggml-sycl/mmq.cpp b/ggml/src/ggml-sycl/mmq.cpp similarity index 100% rename from ggml-sycl/mmq.cpp rename to ggml/src/ggml-sycl/mmq.cpp diff --git a/ggml-sycl/mmq.hpp b/ggml/src/ggml-sycl/mmq.hpp similarity index 100% rename from ggml-sycl/mmq.hpp rename to ggml/src/ggml-sycl/mmq.hpp diff --git a/ggml-sycl/mmvq.cpp b/ggml/src/ggml-sycl/mmvq.cpp similarity index 100% rename from ggml-sycl/mmvq.cpp rename to ggml/src/ggml-sycl/mmvq.cpp diff --git a/ggml-sycl/mmvq.hpp b/ggml/src/ggml-sycl/mmvq.hpp similarity index 100% rename from ggml-sycl/mmvq.hpp rename to ggml/src/ggml-sycl/mmvq.hpp diff --git a/ggml-sycl/presets.hpp b/ggml/src/ggml-sycl/presets.hpp similarity index 96% rename from ggml-sycl/presets.hpp rename to ggml/src/ggml-sycl/presets.hpp index 5e6b61813ab49..fe9d41770b76a 100644 --- a/ggml-sycl/presets.hpp +++ b/ggml/src/ggml-sycl/presets.hpp @@ -15,8 +15,6 @@ #define GGML_SYCL_MAX_STREAMS 8 #define GGML_SYCL_MAX_BUFFERS 256 -#define GGML_SYCL_MAX_DEVICES 48 -#define GGML_SYCL_NAME "SYCL" #define WARP_SIZE 32 #define MATRIX_ROW_PADDING 512 // last row of quant. matrices is a multiple of this to avoid out-of-bounds memory accesses diff --git a/ggml-sycl/vecdotq.hpp b/ggml/src/ggml-sycl/vecdotq.hpp similarity index 100% rename from ggml-sycl/vecdotq.hpp rename to ggml/src/ggml-sycl/vecdotq.hpp diff --git a/ggml-vulkan-shaders.hpp b/ggml/src/ggml-vulkan-shaders.hpp similarity index 100% rename from ggml-vulkan-shaders.hpp rename to ggml/src/ggml-vulkan-shaders.hpp diff --git a/ggml-vulkan.cpp b/ggml/src/ggml-vulkan.cpp similarity index 100% rename from ggml-vulkan.cpp rename to ggml/src/ggml-vulkan.cpp diff --git a/ggml.c b/ggml/src/ggml.c similarity index 100% rename from ggml.c rename to ggml/src/ggml.c diff --git a/kompute b/ggml/src/kompute similarity index 100% rename from kompute rename to ggml/src/kompute diff --git a/kompute-shaders/common.comp b/ggml/src/kompute-shaders/common.comp similarity index 100% rename from kompute-shaders/common.comp rename to ggml/src/kompute-shaders/common.comp diff --git a/kompute-shaders/op_add.comp b/ggml/src/kompute-shaders/op_add.comp similarity index 100% rename from kompute-shaders/op_add.comp rename to ggml/src/kompute-shaders/op_add.comp diff --git a/kompute-shaders/op_addrow.comp b/ggml/src/kompute-shaders/op_addrow.comp similarity index 100% rename from kompute-shaders/op_addrow.comp rename to ggml/src/kompute-shaders/op_addrow.comp diff --git a/kompute-shaders/op_cpy_f16_f16.comp b/ggml/src/kompute-shaders/op_cpy_f16_f16.comp similarity index 100% rename from kompute-shaders/op_cpy_f16_f16.comp rename to ggml/src/kompute-shaders/op_cpy_f16_f16.comp diff --git a/kompute-shaders/op_cpy_f16_f32.comp b/ggml/src/kompute-shaders/op_cpy_f16_f32.comp similarity index 100% rename from kompute-shaders/op_cpy_f16_f32.comp rename to ggml/src/kompute-shaders/op_cpy_f16_f32.comp diff --git a/kompute-shaders/op_cpy_f32_f16.comp b/ggml/src/kompute-shaders/op_cpy_f32_f16.comp similarity index 100% rename from kompute-shaders/op_cpy_f32_f16.comp rename to ggml/src/kompute-shaders/op_cpy_f32_f16.comp diff --git a/kompute-shaders/op_cpy_f32_f32.comp b/ggml/src/kompute-shaders/op_cpy_f32_f32.comp similarity index 100% rename from kompute-shaders/op_cpy_f32_f32.comp rename to ggml/src/kompute-shaders/op_cpy_f32_f32.comp diff --git a/kompute-shaders/op_diagmask.comp b/ggml/src/kompute-shaders/op_diagmask.comp similarity index 100% rename from kompute-shaders/op_diagmask.comp rename to ggml/src/kompute-shaders/op_diagmask.comp diff --git a/kompute-shaders/op_gelu.comp b/ggml/src/kompute-shaders/op_gelu.comp similarity index 100% rename from kompute-shaders/op_gelu.comp rename to ggml/src/kompute-shaders/op_gelu.comp diff --git a/kompute-shaders/op_getrows.comp b/ggml/src/kompute-shaders/op_getrows.comp similarity index 100% rename from kompute-shaders/op_getrows.comp rename to ggml/src/kompute-shaders/op_getrows.comp diff --git a/kompute-shaders/op_getrows_f16.comp b/ggml/src/kompute-shaders/op_getrows_f16.comp similarity index 100% rename from kompute-shaders/op_getrows_f16.comp rename to ggml/src/kompute-shaders/op_getrows_f16.comp diff --git a/kompute-shaders/op_getrows_f32.comp b/ggml/src/kompute-shaders/op_getrows_f32.comp similarity index 100% rename from kompute-shaders/op_getrows_f32.comp rename to ggml/src/kompute-shaders/op_getrows_f32.comp diff --git a/kompute-shaders/op_getrows_q4_0.comp b/ggml/src/kompute-shaders/op_getrows_q4_0.comp similarity index 100% rename from kompute-shaders/op_getrows_q4_0.comp rename to ggml/src/kompute-shaders/op_getrows_q4_0.comp diff --git a/kompute-shaders/op_getrows_q4_1.comp b/ggml/src/kompute-shaders/op_getrows_q4_1.comp similarity index 100% rename from kompute-shaders/op_getrows_q4_1.comp rename to ggml/src/kompute-shaders/op_getrows_q4_1.comp diff --git a/kompute-shaders/op_getrows_q6_k.comp b/ggml/src/kompute-shaders/op_getrows_q6_k.comp similarity index 100% rename from kompute-shaders/op_getrows_q6_k.comp rename to ggml/src/kompute-shaders/op_getrows_q6_k.comp diff --git a/kompute-shaders/op_mul.comp b/ggml/src/kompute-shaders/op_mul.comp similarity index 100% rename from kompute-shaders/op_mul.comp rename to ggml/src/kompute-shaders/op_mul.comp diff --git a/kompute-shaders/op_mul_mat_f16.comp b/ggml/src/kompute-shaders/op_mul_mat_f16.comp similarity index 100% rename from kompute-shaders/op_mul_mat_f16.comp rename to ggml/src/kompute-shaders/op_mul_mat_f16.comp diff --git a/kompute-shaders/op_mul_mat_mat_f32.comp b/ggml/src/kompute-shaders/op_mul_mat_mat_f32.comp similarity index 100% rename from kompute-shaders/op_mul_mat_mat_f32.comp rename to ggml/src/kompute-shaders/op_mul_mat_mat_f32.comp diff --git a/kompute-shaders/op_mul_mat_q4_0.comp b/ggml/src/kompute-shaders/op_mul_mat_q4_0.comp similarity index 100% rename from kompute-shaders/op_mul_mat_q4_0.comp rename to ggml/src/kompute-shaders/op_mul_mat_q4_0.comp diff --git a/kompute-shaders/op_mul_mat_q4_1.comp b/ggml/src/kompute-shaders/op_mul_mat_q4_1.comp similarity index 100% rename from kompute-shaders/op_mul_mat_q4_1.comp rename to ggml/src/kompute-shaders/op_mul_mat_q4_1.comp diff --git a/kompute-shaders/op_mul_mat_q6_k.comp b/ggml/src/kompute-shaders/op_mul_mat_q6_k.comp similarity index 100% rename from kompute-shaders/op_mul_mat_q6_k.comp rename to ggml/src/kompute-shaders/op_mul_mat_q6_k.comp diff --git a/kompute-shaders/op_mul_mat_q8_0.comp b/ggml/src/kompute-shaders/op_mul_mat_q8_0.comp similarity index 100% rename from kompute-shaders/op_mul_mat_q8_0.comp rename to ggml/src/kompute-shaders/op_mul_mat_q8_0.comp diff --git a/kompute-shaders/op_mul_mv_q_n.comp b/ggml/src/kompute-shaders/op_mul_mv_q_n.comp similarity index 100% rename from kompute-shaders/op_mul_mv_q_n.comp rename to ggml/src/kompute-shaders/op_mul_mv_q_n.comp diff --git a/kompute-shaders/op_mul_mv_q_n_pre.comp b/ggml/src/kompute-shaders/op_mul_mv_q_n_pre.comp similarity index 100% rename from kompute-shaders/op_mul_mv_q_n_pre.comp rename to ggml/src/kompute-shaders/op_mul_mv_q_n_pre.comp diff --git a/kompute-shaders/op_norm.comp b/ggml/src/kompute-shaders/op_norm.comp similarity index 100% rename from kompute-shaders/op_norm.comp rename to ggml/src/kompute-shaders/op_norm.comp diff --git a/kompute-shaders/op_relu.comp b/ggml/src/kompute-shaders/op_relu.comp similarity index 100% rename from kompute-shaders/op_relu.comp rename to ggml/src/kompute-shaders/op_relu.comp diff --git a/kompute-shaders/op_rmsnorm.comp b/ggml/src/kompute-shaders/op_rmsnorm.comp similarity index 100% rename from kompute-shaders/op_rmsnorm.comp rename to ggml/src/kompute-shaders/op_rmsnorm.comp diff --git a/kompute-shaders/op_rope_f16.comp b/ggml/src/kompute-shaders/op_rope_f16.comp similarity index 100% rename from kompute-shaders/op_rope_f16.comp rename to ggml/src/kompute-shaders/op_rope_f16.comp diff --git a/kompute-shaders/op_rope_f32.comp b/ggml/src/kompute-shaders/op_rope_f32.comp similarity index 100% rename from kompute-shaders/op_rope_f32.comp rename to ggml/src/kompute-shaders/op_rope_f32.comp diff --git a/kompute-shaders/op_scale.comp b/ggml/src/kompute-shaders/op_scale.comp similarity index 100% rename from kompute-shaders/op_scale.comp rename to ggml/src/kompute-shaders/op_scale.comp diff --git a/kompute-shaders/op_scale_8.comp b/ggml/src/kompute-shaders/op_scale_8.comp similarity index 100% rename from kompute-shaders/op_scale_8.comp rename to ggml/src/kompute-shaders/op_scale_8.comp diff --git a/kompute-shaders/op_silu.comp b/ggml/src/kompute-shaders/op_silu.comp similarity index 100% rename from kompute-shaders/op_silu.comp rename to ggml/src/kompute-shaders/op_silu.comp diff --git a/kompute-shaders/op_softmax.comp b/ggml/src/kompute-shaders/op_softmax.comp similarity index 100% rename from kompute-shaders/op_softmax.comp rename to ggml/src/kompute-shaders/op_softmax.comp diff --git a/kompute-shaders/rope_common.comp b/ggml/src/kompute-shaders/rope_common.comp similarity index 100% rename from kompute-shaders/rope_common.comp rename to ggml/src/kompute-shaders/rope_common.comp diff --git a/sgemm.cpp b/ggml/src/sgemm.cpp similarity index 100% rename from sgemm.cpp rename to ggml/src/sgemm.cpp diff --git a/sgemm.h b/ggml/src/sgemm.h similarity index 100% rename from sgemm.h rename to ggml/src/sgemm.h diff --git a/vulkan-shaders/add.comp b/ggml/src/vulkan-shaders/add.comp similarity index 100% rename from vulkan-shaders/add.comp rename to ggml/src/vulkan-shaders/add.comp diff --git a/vulkan-shaders/argsort.comp b/ggml/src/vulkan-shaders/argsort.comp similarity index 100% rename from vulkan-shaders/argsort.comp rename to ggml/src/vulkan-shaders/argsort.comp diff --git a/vulkan-shaders/clamp.comp b/ggml/src/vulkan-shaders/clamp.comp similarity index 100% rename from vulkan-shaders/clamp.comp rename to ggml/src/vulkan-shaders/clamp.comp diff --git a/vulkan-shaders/copy.comp b/ggml/src/vulkan-shaders/copy.comp similarity index 100% rename from vulkan-shaders/copy.comp rename to ggml/src/vulkan-shaders/copy.comp diff --git a/vulkan-shaders/dequant_f32.comp b/ggml/src/vulkan-shaders/dequant_f32.comp similarity index 100% rename from vulkan-shaders/dequant_f32.comp rename to ggml/src/vulkan-shaders/dequant_f32.comp diff --git a/vulkan-shaders/dequant_funcs.comp b/ggml/src/vulkan-shaders/dequant_funcs.comp similarity index 100% rename from vulkan-shaders/dequant_funcs.comp rename to ggml/src/vulkan-shaders/dequant_funcs.comp diff --git a/vulkan-shaders/dequant_head.comp b/ggml/src/vulkan-shaders/dequant_head.comp similarity index 100% rename from vulkan-shaders/dequant_head.comp rename to ggml/src/vulkan-shaders/dequant_head.comp diff --git a/vulkan-shaders/dequant_q2_k.comp b/ggml/src/vulkan-shaders/dequant_q2_k.comp similarity index 100% rename from vulkan-shaders/dequant_q2_k.comp rename to ggml/src/vulkan-shaders/dequant_q2_k.comp diff --git a/vulkan-shaders/dequant_q3_k.comp b/ggml/src/vulkan-shaders/dequant_q3_k.comp similarity index 100% rename from vulkan-shaders/dequant_q3_k.comp rename to ggml/src/vulkan-shaders/dequant_q3_k.comp diff --git a/vulkan-shaders/dequant_q4_0.comp b/ggml/src/vulkan-shaders/dequant_q4_0.comp similarity index 100% rename from vulkan-shaders/dequant_q4_0.comp rename to ggml/src/vulkan-shaders/dequant_q4_0.comp diff --git a/vulkan-shaders/dequant_q4_1.comp b/ggml/src/vulkan-shaders/dequant_q4_1.comp similarity index 100% rename from vulkan-shaders/dequant_q4_1.comp rename to ggml/src/vulkan-shaders/dequant_q4_1.comp diff --git a/vulkan-shaders/dequant_q4_k.comp b/ggml/src/vulkan-shaders/dequant_q4_k.comp similarity index 100% rename from vulkan-shaders/dequant_q4_k.comp rename to ggml/src/vulkan-shaders/dequant_q4_k.comp diff --git a/vulkan-shaders/dequant_q5_0.comp b/ggml/src/vulkan-shaders/dequant_q5_0.comp similarity index 100% rename from vulkan-shaders/dequant_q5_0.comp rename to ggml/src/vulkan-shaders/dequant_q5_0.comp diff --git a/vulkan-shaders/dequant_q5_1.comp b/ggml/src/vulkan-shaders/dequant_q5_1.comp similarity index 100% rename from vulkan-shaders/dequant_q5_1.comp rename to ggml/src/vulkan-shaders/dequant_q5_1.comp diff --git a/vulkan-shaders/dequant_q5_k.comp b/ggml/src/vulkan-shaders/dequant_q5_k.comp similarity index 100% rename from vulkan-shaders/dequant_q5_k.comp rename to ggml/src/vulkan-shaders/dequant_q5_k.comp diff --git a/vulkan-shaders/dequant_q6_k.comp b/ggml/src/vulkan-shaders/dequant_q6_k.comp similarity index 100% rename from vulkan-shaders/dequant_q6_k.comp rename to ggml/src/vulkan-shaders/dequant_q6_k.comp diff --git a/vulkan-shaders/dequant_q8_0.comp b/ggml/src/vulkan-shaders/dequant_q8_0.comp similarity index 100% rename from vulkan-shaders/dequant_q8_0.comp rename to ggml/src/vulkan-shaders/dequant_q8_0.comp diff --git a/vulkan-shaders/diag_mask_inf.comp b/ggml/src/vulkan-shaders/diag_mask_inf.comp similarity index 100% rename from vulkan-shaders/diag_mask_inf.comp rename to ggml/src/vulkan-shaders/diag_mask_inf.comp diff --git a/vulkan-shaders/div.comp b/ggml/src/vulkan-shaders/div.comp similarity index 100% rename from vulkan-shaders/div.comp rename to ggml/src/vulkan-shaders/div.comp diff --git a/vulkan-shaders/gelu.comp b/ggml/src/vulkan-shaders/gelu.comp similarity index 100% rename from vulkan-shaders/gelu.comp rename to ggml/src/vulkan-shaders/gelu.comp diff --git a/vulkan-shaders/generic_binary_head.comp b/ggml/src/vulkan-shaders/generic_binary_head.comp similarity index 100% rename from vulkan-shaders/generic_binary_head.comp rename to ggml/src/vulkan-shaders/generic_binary_head.comp diff --git a/vulkan-shaders/generic_head.comp b/ggml/src/vulkan-shaders/generic_head.comp similarity index 100% rename from vulkan-shaders/generic_head.comp rename to ggml/src/vulkan-shaders/generic_head.comp diff --git a/vulkan-shaders/generic_unary_head.comp b/ggml/src/vulkan-shaders/generic_unary_head.comp similarity index 100% rename from vulkan-shaders/generic_unary_head.comp rename to ggml/src/vulkan-shaders/generic_unary_head.comp diff --git a/vulkan-shaders/get_rows.comp b/ggml/src/vulkan-shaders/get_rows.comp similarity index 100% rename from vulkan-shaders/get_rows.comp rename to ggml/src/vulkan-shaders/get_rows.comp diff --git a/vulkan-shaders/get_rows_quant.comp b/ggml/src/vulkan-shaders/get_rows_quant.comp similarity index 100% rename from vulkan-shaders/get_rows_quant.comp rename to ggml/src/vulkan-shaders/get_rows_quant.comp diff --git a/vulkan-shaders/mul.comp b/ggml/src/vulkan-shaders/mul.comp similarity index 100% rename from vulkan-shaders/mul.comp rename to ggml/src/vulkan-shaders/mul.comp diff --git a/vulkan-shaders/mul_mat_split_k_reduce.comp b/ggml/src/vulkan-shaders/mul_mat_split_k_reduce.comp similarity index 100% rename from vulkan-shaders/mul_mat_split_k_reduce.comp rename to ggml/src/vulkan-shaders/mul_mat_split_k_reduce.comp diff --git a/vulkan-shaders/mul_mat_vec.comp b/ggml/src/vulkan-shaders/mul_mat_vec.comp similarity index 100% rename from vulkan-shaders/mul_mat_vec.comp rename to ggml/src/vulkan-shaders/mul_mat_vec.comp diff --git a/vulkan-shaders/mul_mat_vec_base.comp b/ggml/src/vulkan-shaders/mul_mat_vec_base.comp similarity index 100% rename from vulkan-shaders/mul_mat_vec_base.comp rename to ggml/src/vulkan-shaders/mul_mat_vec_base.comp diff --git a/vulkan-shaders/mul_mat_vec_nc.comp b/ggml/src/vulkan-shaders/mul_mat_vec_nc.comp similarity index 100% rename from vulkan-shaders/mul_mat_vec_nc.comp rename to ggml/src/vulkan-shaders/mul_mat_vec_nc.comp diff --git a/vulkan-shaders/mul_mat_vec_p021.comp b/ggml/src/vulkan-shaders/mul_mat_vec_p021.comp similarity index 100% rename from vulkan-shaders/mul_mat_vec_p021.comp rename to ggml/src/vulkan-shaders/mul_mat_vec_p021.comp diff --git a/vulkan-shaders/mul_mat_vec_q2_k.comp b/ggml/src/vulkan-shaders/mul_mat_vec_q2_k.comp similarity index 100% rename from vulkan-shaders/mul_mat_vec_q2_k.comp rename to ggml/src/vulkan-shaders/mul_mat_vec_q2_k.comp diff --git a/vulkan-shaders/mul_mat_vec_q3_k.comp b/ggml/src/vulkan-shaders/mul_mat_vec_q3_k.comp similarity index 100% rename from vulkan-shaders/mul_mat_vec_q3_k.comp rename to ggml/src/vulkan-shaders/mul_mat_vec_q3_k.comp diff --git a/vulkan-shaders/mul_mat_vec_q4_k.comp b/ggml/src/vulkan-shaders/mul_mat_vec_q4_k.comp similarity index 100% rename from vulkan-shaders/mul_mat_vec_q4_k.comp rename to ggml/src/vulkan-shaders/mul_mat_vec_q4_k.comp diff --git a/vulkan-shaders/mul_mat_vec_q5_k.comp b/ggml/src/vulkan-shaders/mul_mat_vec_q5_k.comp similarity index 100% rename from vulkan-shaders/mul_mat_vec_q5_k.comp rename to ggml/src/vulkan-shaders/mul_mat_vec_q5_k.comp diff --git a/vulkan-shaders/mul_mat_vec_q6_k.comp b/ggml/src/vulkan-shaders/mul_mat_vec_q6_k.comp similarity index 100% rename from vulkan-shaders/mul_mat_vec_q6_k.comp rename to ggml/src/vulkan-shaders/mul_mat_vec_q6_k.comp diff --git a/vulkan-shaders/mul_mm.comp b/ggml/src/vulkan-shaders/mul_mm.comp similarity index 100% rename from vulkan-shaders/mul_mm.comp rename to ggml/src/vulkan-shaders/mul_mm.comp diff --git a/vulkan-shaders/norm.comp b/ggml/src/vulkan-shaders/norm.comp similarity index 100% rename from vulkan-shaders/norm.comp rename to ggml/src/vulkan-shaders/norm.comp diff --git a/vulkan-shaders/relu.comp b/ggml/src/vulkan-shaders/relu.comp similarity index 100% rename from vulkan-shaders/relu.comp rename to ggml/src/vulkan-shaders/relu.comp diff --git a/vulkan-shaders/rms_norm.comp b/ggml/src/vulkan-shaders/rms_norm.comp similarity index 100% rename from vulkan-shaders/rms_norm.comp rename to ggml/src/vulkan-shaders/rms_norm.comp diff --git a/vulkan-shaders/rope_head.comp b/ggml/src/vulkan-shaders/rope_head.comp similarity index 100% rename from vulkan-shaders/rope_head.comp rename to ggml/src/vulkan-shaders/rope_head.comp diff --git a/vulkan-shaders/rope_neox.comp b/ggml/src/vulkan-shaders/rope_neox.comp similarity index 100% rename from vulkan-shaders/rope_neox.comp rename to ggml/src/vulkan-shaders/rope_neox.comp diff --git a/vulkan-shaders/rope_norm.comp b/ggml/src/vulkan-shaders/rope_norm.comp similarity index 100% rename from vulkan-shaders/rope_norm.comp rename to ggml/src/vulkan-shaders/rope_norm.comp diff --git a/vulkan-shaders/scale.comp b/ggml/src/vulkan-shaders/scale.comp similarity index 100% rename from vulkan-shaders/scale.comp rename to ggml/src/vulkan-shaders/scale.comp diff --git a/vulkan-shaders/silu.comp b/ggml/src/vulkan-shaders/silu.comp similarity index 100% rename from vulkan-shaders/silu.comp rename to ggml/src/vulkan-shaders/silu.comp diff --git a/vulkan-shaders/soft_max.comp b/ggml/src/vulkan-shaders/soft_max.comp similarity index 100% rename from vulkan-shaders/soft_max.comp rename to ggml/src/vulkan-shaders/soft_max.comp diff --git a/vulkan-shaders/square.comp b/ggml/src/vulkan-shaders/square.comp similarity index 100% rename from vulkan-shaders/square.comp rename to ggml/src/vulkan-shaders/square.comp diff --git a/vulkan-shaders/sum_rows.comp b/ggml/src/vulkan-shaders/sum_rows.comp similarity index 100% rename from vulkan-shaders/sum_rows.comp rename to ggml/src/vulkan-shaders/sum_rows.comp diff --git a/vulkan-shaders/types.comp b/ggml/src/vulkan-shaders/types.comp similarity index 100% rename from vulkan-shaders/types.comp rename to ggml/src/vulkan-shaders/types.comp diff --git a/llama.h b/include/llama.h similarity index 100% rename from llama.h rename to include/llama.h diff --git a/scripts/build-info.sh b/scripts/build-info.sh index 32682afbdbd52..fa9e7bacdb8cf 100755 --- a/scripts/build-info.sh +++ b/scripts/build-info.sh @@ -8,20 +8,20 @@ build_compiler="unknown" build_target="unknown" if out=$(git rev-list --count HEAD); then - # git is broken on WSL so we need to strip extra newlines - build_number=$(printf '%s' "$out" | tr -d '\n') + # git is broken on WSL so we need to strip extra newlines + build_number=$(printf '%s' "$out" | tr -d '\n') fi if out=$(git rev-parse --short HEAD); then - build_commit=$(printf '%s' "$out" | tr -d '\n') + build_commit=$(printf '%s' "$out" | tr -d '\n') fi if out=$($CC --version | head -1); then - build_compiler=$out + build_compiler=$out fi if out=$($CC -dumpmachine); then - build_target=$out + build_target=$out fi echo "int LLAMA_BUILD_NUMBER = ${build_number};" diff --git a/scripts/compare-commits.sh b/scripts/compare-commits.sh index a45cd3962ac0a..70679f4e56470 100755 --- a/scripts/compare-commits.sh +++ b/scripts/compare-commits.sh @@ -12,7 +12,7 @@ bench_args="${@:3}" rm -f llama-bench.sqlite > /dev/null -# to test a backend, call the script with the corresponding environment variable (e.g. LLAMA_CUDA=1 ./scripts/compare-commits.sh ...) +# to test a backend, call the script with the corresponding environment variable (e.g. GGML_CUDA=1 ./scripts/compare-commits.sh ...) git checkout $1 > /dev/null make clean > /dev/null diff --git a/scripts/debug-test.sh b/scripts/debug-test.sh index 7b2b601a96477..91946c514e6b2 100755 --- a/scripts/debug-test.sh +++ b/scripts/debug-test.sh @@ -110,7 +110,7 @@ rm -rf "$build_dir" && mkdir "$build_dir" || abort "Failed to make $build_dir" ########################################################### # Note: test-eval-callback requires -DLLAMA_CURL -cmake -B "./$build_dir" -DCMAKE_BUILD_TYPE=Debug -DLLAMA_CUDA=1 -DLLAMA_CURL=1 || abort "Failed to build enviroment" +cmake -B "./$build_dir" -DCMAKE_BUILD_TYPE=Debug -DGGML_CUDA=1 -DLLAMA_CURL=1 || abort "Failed to build enviroment" pushd "$build_dir" make -j || abort "Failed to compile" popd > /dev/null || exit 1 diff --git a/scripts/pod-llama.sh b/scripts/pod-llama.sh index 6ba499a2a2521..586d6ea18af01 100644 --- a/scripts/pod-llama.sh +++ b/scripts/pod-llama.sh @@ -42,7 +42,7 @@ git clone https://github.com/ggerganov/llama.cpp cd llama.cpp -LLAMA_CUDA=1 make -j +GGML_CUDA=1 make -j ln -sfn /workspace/TinyLlama-1.1B-Chat-v0.3 ./models/tinyllama-1b ln -sfn /workspace/CodeLlama-7b-hf ./models/codellama-7b @@ -60,7 +60,7 @@ cd /workspace/llama.cpp mkdir build-cublas cd build-cublas -cmake -DLLAMA_CUDA=1 ../ +cmake -DGGML_CUDA=1 ../ make -j if [ "$1" -eq "0" ]; then @@ -186,17 +186,17 @@ if [ "$1" -eq "1" ]; then # batched cd /workspace/llama.cpp - LLAMA_CUDA=1 make -j && ./llama-batched ./models/tinyllama-1b/ggml-model-f16.gguf "Hello, my name is" 8 128 999 + GGML_CUDA=1 make -j && ./llama-batched ./models/tinyllama-1b/ggml-model-f16.gguf "Hello, my name is" 8 128 999 # batched-bench cd /workspace/llama.cpp - LLAMA_CUDA=1 make -j && ./llama-batched-bench ./models/tinyllama-1b/ggml-model-f16.gguf 4608 1 99 0 512 128 1,2,3,4,5,6,7,8,16,32 + GGML_CUDA=1 make -j && ./llama-batched-bench ./models/tinyllama-1b/ggml-model-f16.gguf 4608 1 99 0 512 128 1,2,3,4,5,6,7,8,16,32 # parallel cd /workspace/llama.cpp - LLAMA_CUDA=1 make -j && ./llama-parallel -m ./models/tinyllama-1b/ggml-model-f16.gguf -t 1 -ngl 100 -c 4096 -b 512 -s 1 -np 8 -ns 128 -n 100 -cb + GGML_CUDA=1 make -j && ./llama-parallel -m ./models/tinyllama-1b/ggml-model-f16.gguf -t 1 -ngl 100 -c 4096 -b 512 -s 1 -np 8 -ns 128 -n 100 -cb fi @@ -204,10 +204,10 @@ fi #if [ "$1" -eq "7" ]; then # cd /workspace/llama.cpp # -# LLAMA_CUDA=1 make -j && ./llama-speculative -m ./models/codellama-34b-instruct/ggml-model-f16.gguf -md ./models/codellama-7b-instruct/ggml-model-q4_0.gguf -p "# Dijkstra's shortest path algorithm in Python (4 spaces indentation) + complexity analysis:\n\n" -e -ngl 999 -ngld 999 -t 4 -n 512 -c 4096 -s 21 --draft 16 -np 1 --temp 0.0 +# GGML_CUDA=1 make -j && ./llama-speculative -m ./models/codellama-34b-instruct/ggml-model-f16.gguf -md ./models/codellama-7b-instruct/ggml-model-q4_0.gguf -p "# Dijkstra's shortest path algorithm in Python (4 spaces indentation) + complexity analysis:\n\n" -e -ngl 999 -ngld 999 -t 4 -n 512 -c 4096 -s 21 --draft 16 -np 1 --temp 0.0 #fi # more benches -#LLAMA_CUDA=1 make -j && ./llama-batched-bench ./models/codellama-7b/ggml-model-q4_k.gguf 4096 1 99 1 512,3200 128,128,800 1 -#LLAMA_CUDA=1 make -j && ./llama-batched-bench ./models/codellama-13b/ggml-model-q4_k.gguf 4096 1 99 1 512,3200 128,128,800 1 +#GGML_CUDA=1 make -j && ./llama-batched-bench ./models/codellama-7b/ggml-model-q4_k.gguf 4096 1 99 1 512,3200 128,128,800 1 +#GGML_CUDA=1 make -j && ./llama-batched-bench ./models/codellama-13b/ggml-model-q4_k.gguf 4096 1 99 1 512,3200 128,128,800 1 diff --git a/scripts/server-llm.sh b/scripts/server-llm.sh index 199232440449b..802592a3e0d3b 100644 --- a/scripts/server-llm.sh +++ b/scripts/server-llm.sh @@ -380,7 +380,7 @@ fi if [[ "$backend" == "cuda" ]]; then printf "[+] Building with CUDA backend\n" - LLAMA_CUDA=1 make -j llama-server $log + GGML_CUDA=1 make -j llama-server $log elif [[ "$backend" == "cpu" ]]; then printf "[+] Building with CPU backend\n" make -j llama-server $log diff --git a/scripts/sync-ggml-am.sh b/scripts/sync-ggml-am.sh index 9e34dc8b9a590..9e654180b93fb 100755 --- a/scripts/sync-ggml-am.sh +++ b/scripts/sync-ggml-am.sh @@ -53,7 +53,9 @@ while read c; do fi git format-patch -k $c~1..$c --stdout -- \ - include/ggml/ggml*.h \ + CMakeLists.txt \ + src/CMakeLists.txt \ + cmake/FindSIMD.cmake \ src/ggml*.h \ src/ggml*.c \ src/ggml*.cpp \ @@ -61,6 +63,7 @@ while read c; do src/ggml*.metal \ src/ggml*.cu \ src/ggml-cuda/* \ + include/ggml*.h \ tests/test-opt.cpp \ tests/test-grad0.cpp \ tests/test-quantize-fns.cpp \ @@ -93,30 +96,36 @@ if [ -f $SRC_LLAMA/ggml-src.patch ]; then # replace filenames: # - # src/ggml.c -> ggml.c - # src/ggml-alloc.c -> ggml-alloc.c - # src/ggml-backend-impl.h -> ggml-backend-impl.h - # src/ggml-backend.c -> ggml-backend.c - # src/ggml-common.h -> ggml-common.h - # src/ggml-cuda/* -> ggml-cuda/ - # src/ggml-cuda.cu -> ggml-cuda.cu - # src/ggml-cuda.h -> ggml-cuda.h - # src/ggml-impl.h -> ggml-impl.h - # src/ggml-kompute.cpp -> ggml-kompute.cpp - # src/ggml-kompute.h -> ggml-kompute.h - # src/ggml-metal.h -> ggml-metal.h - # src/ggml-metal.m -> ggml-metal.m - # src/ggml-quants.c -> ggml-quants.c - # src/ggml-quants.h -> ggml-quants.h - # src/ggml-rpc.cpp -> ggml-rpc.cpp - # src/ggml-rpc.h -> ggml-rpc.h - # src/ggml-sycl.cpp -> ggml-sycl.cpp - # src/ggml-sycl.h -> ggml-sycl.h - # src/ggml-vulkan.cpp -> ggml-vulkan.cpp - # src/ggml-vulkan.h -> ggml-vulkan.h - # include/ggml/ggml.h -> ggml.h - # include/ggml/ggml-alloc.h -> ggml-alloc.h - # include/ggml/ggml-backend.h -> ggml-backend.h + # CMakelists.txt -> ggml/CMakeLists.txt + # src/CMakeLists.txt -> ggml/src/CMakeLists.txt + # cmake/FindSIMD.cmake -> ggml/cmake/FindSIMD.cmake + # + # src/ggml.c -> ggml/src/ggml.c + # src/ggml-alloc.c -> ggml/src/ggml-alloc.c + # src/ggml-backend-impl.h -> ggml/src/ggml-backend-impl.h + # src/ggml-backend.c -> ggml/src/ggml-backend.c + # src/ggml-common.h -> ggml/src/ggml-common.h + # src/ggml-cuda/* -> ggml/src/ggml-cuda/ + # src/ggml-cuda.cu -> ggml/src/ggml-cuda.cu + # src/ggml-impl.h -> ggml/src/ggml-impl.h + # src/ggml-kompute.cpp -> ggml/src/ggml-kompute.cpp + # src/ggml-metal.m -> ggml/src/ggml-metal.m + # src/ggml-quants.c -> ggml/src/ggml-quants.c + # src/ggml-quants.h -> ggml/src/ggml-quants.h + # src/ggml-rpc.cpp -> ggml/src/ggml-rpc.cpp + # src/ggml-sycl.cpp -> ggml/src/ggml-sycl.cpp + # src/ggml-vulkan.cpp -> ggml/src/ggml-vulkan.cpp + # + # include/ggml.h -> ggml/include/ggml.h + # include/ggml-alloc.h -> ggml/include/ggml-alloc.h + # include/ggml-backend.h -> ggml/include/ggml-backend.h + # include/ggml-blas.h -> ggml/include/ggml-blas.h + # include/ggml-cuda.h -> ggml/include/ggml-cuda.h + # include/ggml-kompute.h -> ggml/include/ggml-kompute.h + # include/ggml-metal.h -> ggml/include/ggml-metal.h + # include/ggml-rpc.h -> ggml/include/ggml-rpc.h + # include/ggml-sycl.h -> ggml/include/ggml-sycl.h + # include/ggml-vulkan.h -> ggml/include/ggml-vulkan.h # # tests/test-opt.cpp -> tests/test-opt.cpp # tests/test-grad0.cpp -> tests/test-grad0.cpp @@ -124,34 +133,38 @@ if [ -f $SRC_LLAMA/ggml-src.patch ]; then # tests/test-quantize-perf.cpp -> tests/test-quantize-perf.cpp # tests/test-backend-ops.cpp -> tests/test-backend-ops.cpp # - # LICENSE -> LICENSE - # scripts/gen-authors.sh -> scripts/gen-authors.sh + # LICENSE -> LICENSE + # scripts/gen-authors.sh -> scripts/gen-authors.sh cat ggml-src.patch | sed \ - -e 's/src\/ggml\.c/ggml.c/g' \ - -e 's/src\/ggml-alloc\.c/ggml-alloc.c/g' \ - -e 's/src\/ggml-backend-impl\.h/ggml-backend-impl.h/g' \ - -e 's/src\/ggml-backend\.c/ggml-backend.c/g' \ - -e 's/src\/ggml-common\.h/ggml-common.h/g' \ + -e 's/CMakeLists.txt/ggml\/CMakeLists.txt/g' \ + -e 's/src\/CMakeLists.txt/ggml\/src\/CMakeLists.txt/g' \ + -e 's/cmake\/FindSIMD.cmake/ggml\/cmake\/FindSIMD.cmake/g' \ + -e 's/src\/ggml\.c/ggml/src/ggml.c/g' \ + -e 's/src\/ggml-alloc\.c/ggml/src/ggml-alloc.c/g' \ + -e 's/src\/ggml-backend-impl\.h/ggml/src/ggml-backend-impl.h/g' \ + -e 's/src\/ggml-backend\.c/ggml/src/ggml-backend.c/g' \ + -e 's/src\/ggml-common\.h/ggml/src/ggml-common.h/g' \ -e 's/src\/ggml-cuda\//ggml-cuda\//g' \ - -e 's/src\/ggml-cuda\.cu/ggml-cuda.cu/g' \ - -e 's/src\/ggml-cuda\.h/ggml-cuda.h/g' \ - -e 's/src\/ggml-impl\.h/ggml-impl.h/g' \ - -e 's/src\/ggml-kompute\.cpp/ggml-kompute.cpp/g' \ - -e 's/src\/ggml-kompute\.h/ggml-kompute.h/g' \ - -e 's/src\/ggml-metal\.h/ggml-metal.h/g' \ - -e 's/src\/ggml-metal\.m/ggml-metal.m/g' \ - -e 's/src\/ggml-quants\.c/ggml-quants.c/g' \ - -e 's/src\/ggml-quants\.h/ggml-quants.h/g' \ - -e 's/src\/ggml-rpc\.cpp/ggml-rpc.cpp/g' \ - -e 's/src\/ggml-rpc\.h/ggml-rpc.h/g' \ - -e 's/src\/ggml-sycl\.cpp/ggml-sycl.cpp/g' \ - -e 's/src\/ggml-sycl\.h/ggml-sycl.h/g' \ - -e 's/src\/ggml-vulkan\.cpp/ggml-vulkan.cpp/g' \ - -e 's/src\/ggml-vulkan\.h/ggml-vulkan.h/g' \ - -e 's/include\/ggml\/ggml\.h/ggml.h/g' \ - -e 's/include\/ggml\/ggml-alloc\.h/ggml-alloc.h/g' \ - -e 's/include\/ggml\/ggml-backend\.h/ggml-backend.h/g' \ + -e 's/src\/ggml-cuda\.cu/ggml/src/ggml-cuda.cu/g' \ + -e 's/src\/ggml-impl\.h/ggml/src/ggml-impl.h/g' \ + -e 's/src\/ggml-kompute\.cpp/ggml/src/ggml-kompute.cpp/g' \ + -e 's/src\/ggml-metal\.m/ggml/src/ggml-metal.m/g' \ + -e 's/src\/ggml-quants\.c/ggml/src/ggml-quants.c/g' \ + -e 's/src\/ggml-quants\.h/ggml/src/ggml-quants.h/g' \ + -e 's/src\/ggml-rpc\.cpp/ggml/src/ggml-rpc.cpp/g' \ + -e 's/src\/ggml-sycl\.cpp/ggml/src/ggml-sycl.cpp/g' \ + -e 's/src\/ggml-vulkan\.cpp/ggml/src/ggml-vulkan.cpp/g' \ + -e 's/include\/ggml\.h/ggml/include/ggml.h/g' \ + -e 's/include\/ggml-alloc\.h/ggml/include/ggml-alloc.h/g' \ + -e 's/include\/ggml-backend\.h/ggml/include/ggml-backend.h/g' \ + -e 's/include\/ggml-blas\.h/ggml/include/ggml-blas.h/g' \ + -e 's/include\/ggml-cuda\.h/ggml/include/ggml-cuda.h/g' \ + -e 's/include\/ggml-kompute\.h/ggml/include/ggml-kompute.h/g' \ + -e 's/include\/ggml-metal\.h/ggml/include/ggml-metal.h/g' \ + -e 's/include\/ggml-rpc\.h/ggml/include/ggml-rpc.h/g' \ + -e 's/include\/ggml-sycl\.h/ggml/include/ggml-sycl.h/g' \ + -e 's/include\/ggml-vulkan\.h/ggml/include/ggml-vulkan.h/g' \ -e 's/tests\/test-opt\.cpp/tests\/test-opt.cpp/g' \ -e 's/tests\/test-grad0\.cpp/tests\/test-grad0.cpp/g' \ -e 's/tests\/test-quantize-fns\.cpp/tests\/test-quantize-fns.cpp/g' \ diff --git a/scripts/sync-ggml.sh b/scripts/sync-ggml.sh index 4843f8a4ae05e..2f32c1ce84cc7 100755 --- a/scripts/sync-ggml.sh +++ b/scripts/sync-ggml.sh @@ -1,34 +1,42 @@ #!/bin/bash -cp -rpv ../ggml/src/ggml.c ./ggml.c -cp -rpv ../ggml/src/ggml-alloc.c ./ggml-alloc.c -cp -rpv ../ggml/src/ggml-backend-impl.h ./ggml-backend-impl.h -cp -rpv ../ggml/src/ggml-backend.c ./ggml-backend.c -cp -rpv ../ggml/src/ggml-common.h ./ggml-common.h -cp -rpv ../ggml/src/ggml-cuda/* ./ggml-cuda/ -cp -rpv ../ggml/src/ggml-cuda.cu ./ggml-cuda.cu -cp -rpv ../ggml/src/ggml-cuda.h ./ggml-cuda.h -cp -rpv ../ggml/src/ggml-impl.h ./ggml-impl.h -cp -rpv ../ggml/src/ggml-kompute.cpp ./ggml-kompute.cpp -cp -rpv ../ggml/src/ggml-kompute.h ./ggml-kompute.h -cp -rpv ../ggml/src/ggml-metal.h ./ggml-metal.h -cp -rpv ../ggml/src/ggml-metal.m ./ggml-metal.m -cp -rpv ../ggml/src/ggml-metal.metal ./ggml-metal.metal -cp -rpv ../ggml/src/ggml-quants.c ./ggml-quants.c -cp -rpv ../ggml/src/ggml-quants.h ./ggml-quants.h -cp -rpv ../ggml/src/ggml-rpc.cpp ./ggml-rpc.cpp -cp -rpv ../ggml/src/ggml-rpc.h ./ggml-rpc.h -cp -rpv ../ggml/src/ggml-sycl.cpp ./ggml-sycl.cpp -cp -rpv ../ggml/src/ggml-sycl.h ./ggml-sycl.h -cp -rpv ../ggml/src/ggml-vulkan.cpp ./ggml-vulkan.cpp -cp -rpv ../ggml/src/ggml-vulkan.h ./ggml-vulkan.h -cp -rpv ../ggml/include/ggml/ggml.h ./ggml.h -cp -rpv ../ggml/include/ggml/ggml-alloc.h ./ggml-alloc.h -cp -rpv ../ggml/include/ggml/ggml-backend.h ./ggml-backend.h +cp -rpv ../ggml/CMakeLists.txt ./ggml/CMakeLists.txt +cp -rpv ../ggml/src/CMakeLists.txt ./ggml/src/CMakeLists.txt +cp -rpv ../ggml/cmake/FindSIMD.cmake ./ggml/cmake/FindSIMD.cmake -cp -rpv ../ggml/tests/test-opt.cpp ./tests/test-opt.cpp -cp -rpv ../ggml/tests/test-grad0.cpp ./tests/test-grad0.cpp -cp -rpv ../ggml/tests/test-backend-ops.cpp ./tests/test-backend-ops.cpp +cp -rpv ../ggml/src/ggml.c ./ggml/src/ggml.c +cp -rpv ../ggml/src/ggml-alloc.c ./ggml/src/ggml-alloc.c +cp -rpv ../ggml/src/ggml-backend-impl.h ./ggml/src/ggml-backend-impl.h +cp -rpv ../ggml/src/ggml-backend.c ./ggml/src/ggml-backend.c +cp -rpv ../ggml/src/ggml-common.h ./ggml/src/ggml-common.h +cp -rpv ../ggml/src/ggml-cuda/* ./ggml/src/ggml-cuda/ +cp -rpv ../ggml/src/ggml-cuda.cu ./ggml/src/ggml-cuda.cu +cp -rpv ../ggml/src/ggml-impl.h ./ggml/src/ggml-impl.h +cp -rpv ../ggml/src/ggml-kompute.cpp ./ggml/src/ggml-kompute.cpp +cp -rpv ../ggml/src/ggml-metal.m ./ggml/src/ggml-metal.m +cp -rpv ../ggml/src/ggml-metal.metal ./ggml/src/ggml-metal.metal +cp -rpv ../ggml/src/ggml-quants.c ./ggml/src/ggml-quants.c +cp -rpv ../ggml/src/ggml-quants.h ./ggml/src/ggml-quants.h +cp -rpv ../ggml/src/ggml-rpc.cpp ./ggml/src/ggml-rpc.cpp +cp -rpv ../ggml/src/ggml-sycl.cpp ./ggml/src/ggml-sycl.cpp +cp -rpv ../ggml/src/ggml-vulkan.cpp ./ggml/src/ggml-vulkan.cpp -cp -rpv ../LICENSE ./LICENSE -cp -rpv ../ggml/scripts/gen-authors.sh ./scripts/gen-authors.sh +cp -rpv ../ggml/include/ggml.h ./ggml/include/ggml.h +cp -rpv ../ggml/include/ggml-alloc.h ./ggml/include/ggml-alloc.h +cp -rpv ../ggml/include/ggml-backend.h ./ggml/include/ggml-backend.h +cp -rpv ../ggml/include/ggml-blas.h ./ggml/include/ggml-blas.h +cp -rpv ../ggml/include/ggml-cuda.h ./ggml/include/ggml-cuda.h +cp -rpv ../ggml/include/ggml-kompute.h ./ggml/include/ggml-kompute.h +cp -rpv ../ggml/include/ggml-metal.h ./ggml/include/ggml-metal.h +cp -rpv ../ggml/include/ggml-rpc.h ./ggml/include/ggml-rpc.h +cp -rpv ../ggml/include/ggml-sycl.h ./ggml/include/ggml-sycl.h +cp -rpv ../ggml/include/ggml-vulkan.h ./ggml/include/ggml-vulkan.h + +cp -rpv ../ggml/tests/test-opt.cpp ./tests/test-opt.cpp +cp -rpv ../ggml/tests/test-grad0.cpp ./tests/test-grad0.cpp +cp -rpv ../ggml/tests/test-quantize-fns.cpp ./tests/test-quantize-fns.cpp +cp -rpv ../ggml/tests/test-quantize-perf.cpp ./tests/test-quantize-perf.cpp +cp -rpv ../ggml/tests/test-backend-ops.cpp ./tests/test-backend-ops.cpp + +cp -rpv ../LICENSE ./LICENSE +cp -rpv ../ggml/scripts/gen-authors.sh ./scripts/gen-authors.sh diff --git a/spm-headers/ggml-alloc.h b/spm-headers/ggml-alloc.h index a49d385a1b864..0361ffc386a1f 120000 --- a/spm-headers/ggml-alloc.h +++ b/spm-headers/ggml-alloc.h @@ -1 +1 @@ -../ggml-alloc.h \ No newline at end of file +../ggml/include/ggml-alloc.h \ No newline at end of file diff --git a/spm-headers/ggml-backend.h b/spm-headers/ggml-backend.h index 17c2cf14fe02b..7295f0f0da742 120000 --- a/spm-headers/ggml-backend.h +++ b/spm-headers/ggml-backend.h @@ -1 +1 @@ -../ggml-backend.h \ No newline at end of file +../ggml/include/ggml-backend.h \ No newline at end of file diff --git a/spm-headers/ggml-metal.h b/spm-headers/ggml-metal.h new file mode 120000 index 0000000000000..aefad5fa04ced --- /dev/null +++ b/spm-headers/ggml-metal.h @@ -0,0 +1 @@ +../ggml/include/ggml-metal.h \ No newline at end of file diff --git a/spm-headers/ggml.h b/spm-headers/ggml.h index 39215298f981b..0bdfeacbdbead 120000 --- a/spm-headers/ggml.h +++ b/spm-headers/ggml.h @@ -1 +1 @@ -../ggml.h \ No newline at end of file +../ggml/include/ggml.h \ No newline at end of file diff --git a/spm-headers/llama.h b/spm-headers/llama.h index 9acceb980c264..b31388f0dd652 120000 --- a/spm-headers/llama.h +++ b/spm-headers/llama.h @@ -1 +1 @@ -../llama.h \ No newline at end of file +../include/llama.h \ No newline at end of file diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt new file mode 100644 index 0000000000000..ccb607e56d336 --- /dev/null +++ b/src/CMakeLists.txt @@ -0,0 +1,32 @@ +# TODO: should not use this +if (WIN32) + add_compile_definitions(_CRT_SECURE_NO_WARNINGS) + + if (BUILD_SHARED_LIBS) + set(CMAKE_WINDOWS_EXPORT_ALL_SYMBOLS ON) + endif() +endif() + +# +# libraries +# + +# llama + +add_library(llama + ../include/llama.h + llama.cpp + unicode.h + unicode.cpp + unicode-data.cpp + ) + +target_include_directories(llama PUBLIC . ../include) +target_compile_features (llama PUBLIC cxx_std_11) # don't bump + +target_link_libraries(llama PUBLIC ggml) + +if (BUILD_SHARED_LIBS) + set_target_properties(llama PROPERTIES POSITION_INDEPENDENT_CODE ON) + target_compile_definitions(llama PRIVATE LLAMA_SHARED LLAMA_BUILD) +endif() diff --git a/llama.cpp b/src/llama.cpp similarity index 100% rename from llama.cpp rename to src/llama.cpp diff --git a/unicode-data.cpp b/src/unicode-data.cpp similarity index 100% rename from unicode-data.cpp rename to src/unicode-data.cpp diff --git a/unicode-data.h b/src/unicode-data.h similarity index 100% rename from unicode-data.h rename to src/unicode-data.h diff --git a/unicode.cpp b/src/unicode.cpp similarity index 100% rename from unicode.cpp rename to src/unicode.cpp diff --git a/unicode.h b/src/unicode.h similarity index 100% rename from unicode.h rename to src/unicode.h diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp index 1ed74e543dd9f..f74c0db475e2e 100644 --- a/tests/test-backend-ops.cpp +++ b/tests/test-backend-ops.cpp @@ -1,7 +1,6 @@ #include #include #include -#include #include #include From a95631ee97bb24861af6bdeec380270459631e8e Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Wed, 26 Jun 2024 19:26:13 +0300 Subject: [PATCH 028/326] readme : update API notes --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index 6ca5ba43ea427..99b16f6e29e32 100644 --- a/README.md +++ b/README.md @@ -15,6 +15,7 @@ Inference of Meta's [LLaMA](https://arxiv.org/abs/2302.13971) model (and others) ### Recent API changes +- [2024 Jun 26] The source code and CMake build scripts have been restructured https://github.com/ggerganov/llama.cpp/pull/8006 - [2024 Apr 21] `llama_token_to_piece` can now optionally render special tokens https://github.com/ggerganov/llama.cpp/pull/6807 - [2024 Apr 4] State and session file functions reorganized under `llama_state_*` https://github.com/ggerganov/llama.cpp/pull/6341 - [2024 Mar 26] Logits and embeddings API updated for compactness https://github.com/ggerganov/llama.cpp/pull/6122 From 0e814dfc42b4b57ad19598d239557b6a977ca16c Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Wed, 26 Jun 2024 19:32:07 +0300 Subject: [PATCH 029/326] devops : remove clblast + LLAMA_CUDA -> GGML_CUDA (#8139) ggml-ci --- .devops/full-cuda.Dockerfile | 2 +- .devops/full-rocm.Dockerfile | 2 +- .devops/llama-cli-cuda.Dockerfile | 2 +- .devops/llama-cli-intel.Dockerfile | 10 +-- .devops/llama-cli-rocm.Dockerfile | 2 +- .devops/llama-cli-vulkan.Dockerfile | 2 +- .devops/llama-cpp-clblast.srpm.spec | 84 -------------------------- .devops/llama-cpp-cuda.srpm.spec | 2 +- .devops/llama-server-cuda.Dockerfile | 2 +- .devops/llama-server-intel.Dockerfile | 10 +-- .devops/llama-server-rocm.Dockerfile | 2 +- .devops/llama-server-vulkan.Dockerfile | 2 +- 12 files changed, 19 insertions(+), 103 deletions(-) delete mode 100644 .devops/llama-cpp-clblast.srpm.spec diff --git a/.devops/full-cuda.Dockerfile b/.devops/full-cuda.Dockerfile index f6073f6622b5a..2a7da586a7086 100644 --- a/.devops/full-cuda.Dockerfile +++ b/.devops/full-cuda.Dockerfile @@ -27,7 +27,7 @@ COPY . . # Set nvcc architecture ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH} # Enable CUDA -ENV LLAMA_CUDA=1 +ENV GGML_CUDA=1 # Enable cURL ENV LLAMA_CURL=1 diff --git a/.devops/full-rocm.Dockerfile b/.devops/full-rocm.Dockerfile index 0314d469bc353..5cbd2e7a131aa 100644 --- a/.devops/full-rocm.Dockerfile +++ b/.devops/full-rocm.Dockerfile @@ -36,7 +36,7 @@ COPY . . # Set nvcc architecture ENV GPU_TARGETS=${ROCM_DOCKER_ARCH} # Enable ROCm -ENV LLAMA_HIPBLAS=1 +ENV GGML_HIPBLAS=1 ENV CC=/opt/rocm/llvm/bin/clang ENV CXX=/opt/rocm/llvm/bin/clang++ diff --git a/.devops/llama-cli-cuda.Dockerfile b/.devops/llama-cli-cuda.Dockerfile index d5ce538f61554..bff946cbc2405 100644 --- a/.devops/llama-cli-cuda.Dockerfile +++ b/.devops/llama-cli-cuda.Dockerfile @@ -21,7 +21,7 @@ COPY . . # Set nvcc architecture ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH} # Enable CUDA -ENV LLAMA_CUDA=1 +ENV GGML_CUDA=1 RUN make -j$(nproc) llama-cli diff --git a/.devops/llama-cli-intel.Dockerfile b/.devops/llama-cli-intel.Dockerfile index 6789e17afcc6e..bd816f9f5a1e6 100644 --- a/.devops/llama-cli-intel.Dockerfile +++ b/.devops/llama-cli-intel.Dockerfile @@ -2,7 +2,7 @@ ARG ONEAPI_VERSION=2024.1.1-devel-ubuntu22.04 FROM intel/oneapi-basekit:$ONEAPI_VERSION as build -ARG LLAMA_SYCL_F16=OFF +ARG GGML_SYCL_F16=OFF RUN apt-get update && \ apt-get install -y git @@ -10,11 +10,11 @@ WORKDIR /app COPY . . -RUN if [ "${LLAMA_SYCL_F16}" = "ON" ]; then \ - echo "LLAMA_SYCL_F16 is set" && \ - export OPT_SYCL_F16="-DLLAMA_SYCL_F16=ON"; \ +RUN if [ "${GGML_SYCL_F16}" = "ON" ]; then \ + echo "GGML_SYCL_F16 is set" && \ + export OPT_SYCL_F16="-DGGML_SYCL_F16=ON"; \ fi && \ - cmake -B build -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx ${OPT_SYCL_F16} && \ + cmake -B build -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx ${OPT_SYCL_F16} && \ cmake --build build --config Release --target llama-cli FROM intel/oneapi-basekit:$ONEAPI_VERSION as runtime diff --git a/.devops/llama-cli-rocm.Dockerfile b/.devops/llama-cli-rocm.Dockerfile index 7e8a6f0fa208c..caa507b081885 100644 --- a/.devops/llama-cli-rocm.Dockerfile +++ b/.devops/llama-cli-rocm.Dockerfile @@ -36,7 +36,7 @@ COPY . . # Set nvcc architecture ENV GPU_TARGETS=${ROCM_DOCKER_ARCH} # Enable ROCm -ENV LLAMA_HIPBLAS=1 +ENV GGML_HIPBLAS=1 ENV CC=/opt/rocm/llvm/bin/clang ENV CXX=/opt/rocm/llvm/bin/clang++ diff --git a/.devops/llama-cli-vulkan.Dockerfile b/.devops/llama-cli-vulkan.Dockerfile index 7a0abe71f1587..6155d588147c9 100644 --- a/.devops/llama-cli-vulkan.Dockerfile +++ b/.devops/llama-cli-vulkan.Dockerfile @@ -14,7 +14,7 @@ RUN wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key # Build it WORKDIR /app COPY . . -RUN cmake -B build -DLLAMA_VULKAN=1 && \ +RUN cmake -B build -DGGML_VULKAN=1 && \ cmake --build build --config Release --target llama-cli # Clean up diff --git a/.devops/llama-cpp-clblast.srpm.spec b/.devops/llama-cpp-clblast.srpm.spec deleted file mode 100644 index 013952191127f..0000000000000 --- a/.devops/llama-cpp-clblast.srpm.spec +++ /dev/null @@ -1,84 +0,0 @@ -# SRPM for building from source and packaging an RPM for RPM-based distros. -# https://docs.fedoraproject.org/en-US/quick-docs/creating-rpm-packages -# Built and maintained by John Boero - boeroboy@gmail.com -# In honor of Seth Vidal https://www.redhat.com/it/blog/thank-you-seth-vidal - -# Notes for llama.cpp: -# 1. Tags are currently based on hash - which will not sort asciibetically. -# We need to declare standard versioning if people want to sort latest releases. -# 2. Builds for CUDA/OpenCL support are separate, with different depenedencies. -# 3. NVidia's developer repo must be enabled with nvcc, cublas, clblas, etc installed. -# Example: https://developer.download.nvidia.com/compute/cuda/repos/fedora37/x86_64/cuda-fedora37.repo -# 4. OpenCL/CLBLAST support simply requires the ICD loader and basic opencl libraries. -# It is up to the user to install the correct vendor-specific support. - -Name: llama.cpp-clblast -Version: %( date "+%%Y%%m%%d" ) -Release: 1%{?dist} -Summary: OpenCL Inference of LLaMA model in C/C++ -License: MIT -Source0: https://github.com/ggerganov/llama.cpp/archive/refs/heads/master.tar.gz -BuildRequires: coreutils make gcc-c++ git mesa-libOpenCL-devel clblast-devel -Requires: clblast -URL: https://github.com/ggerganov/llama.cpp - -%define debug_package %{nil} -%define source_date_epoch_from_changelog 0 - -%description -CPU inference for Meta's Lllama2 models using default options. - -%prep -%setup -n llama.cpp-master - -%build -make -j LLAMA_CLBLAST=1 - -%install -mkdir -p %{buildroot}%{_bindir}/ -cp -p llama-cli %{buildroot}%{_bindir}/llama-clblast-cli -cp -p llama-server %{buildroot}%{_bindir}/llama-clblast-server -cp -p llama-simple %{buildroot}%{_bindir}/llama-clblast-simple - -mkdir -p %{buildroot}/usr/lib/systemd/system -%{__cat} < %{buildroot}/usr/lib/systemd/system/llamaclblast.service -[Unit] -Description=Llama.cpp server, CPU only (no GPU support in this build). -After=syslog.target network.target local-fs.target remote-fs.target nss-lookup.target - -[Service] -Type=simple -EnvironmentFile=/etc/sysconfig/llama -ExecStart=/usr/bin/llama-clblast-server $LLAMA_ARGS -ExecReload=/bin/kill -s HUP $MAINPID -Restart=never - -[Install] -WantedBy=default.target -EOF - -mkdir -p %{buildroot}/etc/sysconfig -%{__cat} < %{buildroot}/etc/sysconfig/llama -LLAMA_ARGS="-m /opt/llama2/ggml-model-f32.bin" -EOF - -%clean -rm -rf %{buildroot} -rm -rf %{_builddir}/* - -%files -%{_bindir}/llama-clblast-cli -%{_bindir}/llama-clblast-server -%{_bindir}/llama-clblast-simple -/usr/lib/systemd/system/llamaclblast.service -%config /etc/sysconfig/llama - - -%pre - -%post - -%preun -%postun - -%changelog diff --git a/.devops/llama-cpp-cuda.srpm.spec b/.devops/llama-cpp-cuda.srpm.spec index cbdf4362629d3..7425d3a9d7a40 100644 --- a/.devops/llama-cpp-cuda.srpm.spec +++ b/.devops/llama-cpp-cuda.srpm.spec @@ -32,7 +32,7 @@ CPU inference for Meta's Lllama2 models using default options. %setup -n llama.cpp-master %build -make -j LLAMA_CUDA=1 +make -j GGML_CUDA=1 %install mkdir -p %{buildroot}%{_bindir}/ diff --git a/.devops/llama-server-cuda.Dockerfile b/.devops/llama-server-cuda.Dockerfile index 7bef07a05f062..d7eaa0925a4a5 100644 --- a/.devops/llama-server-cuda.Dockerfile +++ b/.devops/llama-server-cuda.Dockerfile @@ -21,7 +21,7 @@ COPY . . # Set nvcc architecture ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH} # Enable CUDA -ENV LLAMA_CUDA=1 +ENV GGML_CUDA=1 # Enable cURL ENV LLAMA_CURL=1 diff --git a/.devops/llama-server-intel.Dockerfile b/.devops/llama-server-intel.Dockerfile index 3bf1670ec40a4..8f8fef8c09730 100644 --- a/.devops/llama-server-intel.Dockerfile +++ b/.devops/llama-server-intel.Dockerfile @@ -2,7 +2,7 @@ ARG ONEAPI_VERSION=2024.1.1-devel-ubuntu22.04 FROM intel/oneapi-basekit:$ONEAPI_VERSION as build -ARG LLAMA_SYCL_F16=OFF +ARG GGML_SYCL_F16=OFF RUN apt-get update && \ apt-get install -y git libcurl4-openssl-dev @@ -10,11 +10,11 @@ WORKDIR /app COPY . . -RUN if [ "${LLAMA_SYCL_F16}" = "ON" ]; then \ - echo "LLAMA_SYCL_F16 is set" && \ - export OPT_SYCL_F16="-DLLAMA_SYCL_F16=ON"; \ +RUN if [ "${GGML_SYCL_F16}" = "ON" ]; then \ + echo "GGML_SYCL_F16 is set" && \ + export OPT_SYCL_F16="-DGGML_SYCL_F16=ON"; \ fi && \ - cmake -B build -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_CURL=ON ${OPT_SYCL_F16} && \ + cmake -B build -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_CURL=ON ${OPT_SYCL_F16} && \ cmake --build build --config Release --target llama-server FROM intel/oneapi-basekit:$ONEAPI_VERSION as runtime diff --git a/.devops/llama-server-rocm.Dockerfile b/.devops/llama-server-rocm.Dockerfile index 4b1cdc32090e6..af96c332595b1 100644 --- a/.devops/llama-server-rocm.Dockerfile +++ b/.devops/llama-server-rocm.Dockerfile @@ -36,7 +36,7 @@ COPY . . # Set nvcc architecture ENV GPU_TARGETS=${ROCM_DOCKER_ARCH} # Enable ROCm -ENV LLAMA_HIPBLAS=1 +ENV GGML_HIPBLAS=1 ENV CC=/opt/rocm/llvm/bin/clang ENV CXX=/opt/rocm/llvm/bin/clang++ diff --git a/.devops/llama-server-vulkan.Dockerfile b/.devops/llama-server-vulkan.Dockerfile index 2bc2e45d3d676..49062f84bf314 100644 --- a/.devops/llama-server-vulkan.Dockerfile +++ b/.devops/llama-server-vulkan.Dockerfile @@ -14,7 +14,7 @@ RUN wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key # Build it WORKDIR /app COPY . . -RUN cmake -B build -DLLAMA_VULKAN=1 -DLLAMA_CURL=1 && \ +RUN cmake -B build -DGGML_VULKAN=1 -DLLAMA_CURL=1 && \ cmake --build build --config Release --target llama-server # Clean up From 4713bf3093d58a3e12368ab2ab5fc3630f27803e Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Wed, 26 Jun 2024 19:36:44 +0300 Subject: [PATCH 030/326] authors : regen --- AUTHORS | 129 +++++++++++++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 128 insertions(+), 1 deletion(-) diff --git a/AUTHORS b/AUTHORS index b029f13da3b56..1bd36158a72f4 100644 --- a/AUTHORS +++ b/AUTHORS @@ -1,8 +1,9 @@ -# date: Tue Apr 9 09:17:14 EEST 2024 +# date: Wed Jun 26 19:36:34 EEST 2024 # this file is auto-generated by scripts/gen-authors.sh 0cc4m 0xspringtime <110655352+0xspringtime@users.noreply.github.com> +20kdc 2f38b454 3ooabkhxtn <31479382+3ooabkhxtn@users.noreply.github.com> 44670 <44670@users.noreply.github.com> @@ -11,14 +12,18 @@ AT Aarni Koskela Aaron Miller Aaryaman Vasishta +Abheek Gulati Abhilash Majumder <30946547+abhilash1910@users.noreply.github.com> Abhishek Gopinath K <31348521+overtunned@users.noreply.github.com> Adithya Balaji AdithyanI Adrian Adrian Hesketh +Ahmet Zeer AidanBeltonS <87009434+AidanBeltonS@users.noreply.github.com> Aisuko +Akarshan Biswas +Albert Jin Alberto <57916483+albbus-stack@users.noreply.github.com> Alex Alex Azarov @@ -35,19 +40,24 @@ Ali Nehzat Ali Tariq Alon AlpinDale <52078762+AlpinDale@users.noreply.github.com> +Amir AmirAli Mirian <37371367+amiralimi@users.noreply.github.com> Ananta Bastola Anas Ahouzi <112881240+aahouzi@users.noreply.github.com> András Salamon Andrei Andrew Canis +Andrew Downing Andrew Duffy Andrew Godfrey +Andy Tai Arik Poznanski Artem +Artem Zinnatullin Artyom Lebedev Asbjørn Olling Ásgeir Bjarni Ingvarsson +Ashish <1856117+ashishdatta@users.noreply.github.com> Ashok Gelal <401055+ashokgelal@users.noreply.github.com> Ashraful Islam Atsushi Tatsuma @@ -57,35 +67,46 @@ BADR Bach Le Bailey Chittle <39804642+bachittle@users.noreply.github.com> BarfingLemurs <128182951+BarfingLemurs@users.noreply.github.com> +Bartowski Behnam M <58621210+ibehnam@users.noreply.github.com> +Ben Ashbaugh Ben Garney Ben Siraphob Ben Williams +Benjamin Findley <39356821+Kartoffelsaft@users.noreply.github.com> Benjamin Lecaillon <84293038+blecaillon@users.noreply.github.com> Bernat Vadell +Bingan <70050083+binganao@users.noreply.github.com> Bodo Graumann Bono Lv Borislav Stanimirov Branden Butler Brian Bruce MacDonald +Bryan Honof CJ Pais CRD716 +Calvin Laurenson Cameron Cameron Kaiser +Carolinabanana <140120812+Carolinabanana@users.noreply.github.com> Casey Primozic Casey Primozic CausalLM <148736309+CausalLM@users.noreply.github.com> Cebtenzzre Chad Brewbaker +Chao Jiang Cheng Shao +Chris Elrod Chris Kuehl Christian Demsar Christian Demsar Christian Falch <875252+chrfalch@users.noreply.github.com> Christian Kögler +Christian Zhou-Zheng <59622928+christianazinn@users.noreply.github.com> Clark Saben <76020733+csaben@users.noreply.github.com> Clint Herron +CrispStrobe <154636388+CrispStrobe@users.noreply.github.com> Cuong Trinh Manh DAN™ Damian Stewart @@ -95,8 +116,12 @@ Daniel Bevenius Daniel Drake Daniel Hiltgen Daniel Illescas Romero +Daniele <57776841+daniandtheweb@users.noreply.github.com> DannyDaemonic Dat Quoc Nguyen <2412555+datquocnguyen@users.noreply.github.com> +Dave +Dave Airlie +Dave Airlie Dave Della Costa David Friehs David Kennedy @@ -104,10 +129,13 @@ David Pflug David Renshaw David Sommers <12738+databyte@users.noreply.github.com> David Yang +Dawid Potocki Dawid Wysocki <62249621+TortillaZHawaii@users.noreply.github.com> Dean Deins +Deven Mistry <31466137+deven367@users.noreply.github.com> Didzis Gosko +Djip007 Don Mahurin DooWoong Lee (David) Doomsdayrs <38189170+Doomsdayrs@users.noreply.github.com> @@ -116,8 +144,11 @@ Dr. Tom Murphy VII Ph.D <499244+tom7@users.noreply.github.com> Ebey Abraham Ed Lee Ed Lepedus +Eddie-Wang Edward Taylor +Elaine Elbios <141279586+Elbios@users.noreply.github.com> +Elton Kola Engininja2 <139037756+Engininja2@users.noreply.github.com> Equim Eric Sommerlade @@ -143,37 +174,47 @@ Firat Folko-Ven <71110216+Folko-Ven@users.noreply.github.com> Foul-Tarnished <107711110+Foul-Tarnished@users.noreply.github.com> Francisco Melo <43780565+francis2tm@users.noreply.github.com> +Frank Mai FrankHB +Fred Douglas <43351173+fredlas@users.noreply.github.com> Frederik Vogel Gabe Goodhart GainLee Galunid Gary Linscott Gary Mulder +Gavin Zhao Genkagaku.GPT Georgi Gerganov Gilad S +Giuseppe Scrivano GiviMAD Govlzkoy Guillaume "Vermeille" Sanchez Guillaume Wenzek Guoteng <32697156+SolenoidWGT@users.noreply.github.com> Gustavo Rocha Dias <91472747+gustrd@users.noreply.github.com> +Haggai Nuchi Halalaluyafail3 <55773281+Halalaluyafail3@users.noreply.github.com> +Hamdoud Hakem <90524568+hamdoudhakem@users.noreply.github.com> +HanishKVC Haohui Mai Haoxiang Fei Harald Fernengel Hatsune Miku <129688334+at8u@users.noreply.github.com> +HatsuneMikuUwU33 <173229399+HatsuneMikuUwU33@users.noreply.github.com> Henk Poley Henri Vasserman Henrik Forstén Herman Semenov Hesen Peng Hoang Nguyen +Hong Bo PENG Hongyu Ouyang <96765450+casavaca@users.noreply.github.com> Howard Su Hua Jiang Huawei Lin +Hugo Roussel Ian Bull Ian Bull Ian Scrivener @@ -190,8 +231,10 @@ Ivan Stepanov JH23X <165871467+JH23X@users.noreply.github.com> Jack Mousseau JackJollimore <130917767+JackJollimore@users.noreply.github.com> +Jaemin Son Jag Chadha Jakub N +James A Capozzoli <157492257+jac-jim@users.noreply.github.com> James Reynolds Jan Boon Jan Boon @@ -205,12 +248,17 @@ Jean-Michaël Celerier Jed Fox Jeffrey Quesnelle Jesse Jojo Johnson +Jeximo Jhen-Jie Hong Jiahao Li Jian Liao JidongZhang-THU <1119708529@qq.com> Jinwoo Jeong <33892306+williamjeong2@users.noreply.github.com> Jiří Podivín <66251151+jpodivin@users.noreply.github.com> +Jiří Sejkora +Joan Fontanals +Joan Fontanals +Johan Johannes Gäßler Johannes Rudolph John <78893154+cmp-nct@users.noreply.github.com> @@ -221,15 +269,19 @@ Jonas Wunderlich <32615971+jonas-w@users.noreply.github.com> Jorge A <161275481+jorgealias@users.noreply.github.com> Jose Maldonado <63384398+yukiteruamano@users.noreply.github.com> Joseph Stahl <1269177+josephst@users.noreply.github.com> +Josh Ramer Joyce Juan Calderon-Perez <835733+gaby@users.noreply.github.com> Judd Julius Arkenberg Jun Jie <71215065+junnjiee16@users.noreply.github.com> +Junyang Lin Juraj Bednar Justin Parker Justin Suess +Justina Cho Justine Tunney +Justine Tunney Juuso Alasuutari KASR Kamil Tomšík @@ -242,6 +294,7 @@ Kawrakow <48489457+ikawrakow@users.noreply.github.com> Keiichi Tabata Kenvix ⭐ Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com> +Kevin Gibbons Kevin Ji <1146876+kevinji@users.noreply.github.com> Kevin Kwok Kevin Lo @@ -257,6 +310,7 @@ Laura Lee <44310445+lx200916@users.noreply.github.com> Lee Drake Leng Yue +Leon Knauer LeonEricsson <70749762+LeonEricsson@users.noreply.github.com> Leonardo Neumann Li Tan @@ -265,20 +319,26 @@ LoganDark LostRuins <39025047+LostRuins@users.noreply.github.com> Luciano Luo Tian +Lyle Dean M. Yusuf Sarıgöz Maarten ter Huurne Mack Straight Maël Kerbiriou MaggotHATE +Manuel <44313466+makuche@users.noreply.github.com> Marc Köhlbrugge Marco Matthies <71844+marcom@users.noreply.github.com> Marcus Dunn <51931484+MarcusDunn@users.noreply.github.com> Marian Cepok Mark Fairbairn Marko Tasic +Markus Tavenrath +Martin Delille Martin Krasser Martin Schwaighofer Marvin Gießing +Masaya, Kato <62578291+msy-kato@users.noreply.github.com> +MasterYi1024 <39848311+MasterYi1024@users.noreply.github.com> Mateusz Charytoniuk Matheus C. França Matheus Gabriel Alves Silva @@ -287,8 +347,11 @@ Mathijs de Bruin Matt Clayton <156335168+mattjcly@users.noreply.github.com> Matt Pulver Matteo Boschini <12133566+mbosc@users.noreply.github.com> +Mattheus Chediak Matthew Tejo Matvey Soloviev +Max Krasnyansky +Max Krasnyansky Maxime <672982+maximegmd@users.noreply.github.com> Maximilian Winter Meng Zhang @@ -300,32 +363,41 @@ Michael Kesper Michael Klimenko Michael Podvitskiy Michael Potter +Michael de Gans Michaël de Vries Mihai Mike +Mikko Juola Minsoo Cheong <54794500+mscheong01@users.noreply.github.com> Mirko185 Mirror Azure <54669636+MirrorAzure@users.noreply.github.com> Miwa / Ensan <63481257+ensan-hcl@users.noreply.github.com> Mohammadreza Hendiani +Mohammadreza Hendiani Murilo Santana Musab Gultekin Nam D. Tran <42194884+namtranase@users.noreply.github.com> +Nathan Epstein NawafAlansari <72708095+NawafAlansari@users.noreply.github.com> Nebula +Neo Zhang <14088817+arthw@users.noreply.github.com> +Neo Zhang Neo Zhang Jianyu Neuman Vong Nexesenex <124105151+Nexesenex@users.noreply.github.com> Niall Coates <1349685+Niall-@users.noreply.github.com> Nicolai Weitkemper +Nicolás Pérez Nigel Bosch Niklas Korz +Nikolas <127742645+nneubacher@users.noreply.github.com> Nindaleth Oleksandr Nikitin Oleksii Maryshchenko Olivier Chafik Ondřej Čertík Ouadie EL FAROUKI +Patrice Ferlet Paul Tsochantaris Pavol Rusnak Pedro Cuenca @@ -343,9 +415,14 @@ RJ Adriaansen Radoslav Gerganov Radosław Gryta Rahul Vivek Nair <68507071+RahulVivekNair@users.noreply.github.com> +Raj Hammeer Singh Hada +Ralph Soika Rand Xie Randall Fitzgerald Reinforce-II +Ren Xuancheng +Rene Leonhardt <65483435+reneleonhardt@users.noreply.github.com> +RhinoDevel Riceball LEE Richard Kiss Richard Roberson @@ -373,6 +450,7 @@ Rowan Hart Rune <43761327+Rune-AI@users.noreply.github.com> Ryan Landay Ryder Wishart +Ryuei Rőczey Barnabás <31726601+An0nie@users.noreply.github.com> SakuraUmi Salvador E. Tropea @@ -386,6 +464,7 @@ SebastianApel <13675545+SebastianApel@users.noreply.github.com> Senemu <10880819+Senemu@users.noreply.github.com> Sergey Alirzaev Sergio López +Sertaç Özercan <852750+sozercan@users.noreply.github.com> SeungWon Jeong <65549245+redlion0929@users.noreply.github.com> ShadovvBeast Shakhar Dasgupta @@ -394,6 +473,7 @@ Shijie <821898965@qq.com> Shintarou Okada Shouzheng Liu <61452103+lshzh-ww@users.noreply.github.com> Shouzheng Liu +Shuichi Tsutsumi Sigbjørn Skjæret Simon Willison Siwen Yu @@ -405,11 +485,14 @@ Someone Someone Serge Sourab Mangrulkar <13534540+pacman100@users.noreply.github.com> Spencer Sutton +Srihari-mcw <96763064+Srihari-mcw@users.noreply.github.com> Srinivas Billa Stefan Sydow +Steffen Röcker Stephan Walter Stephen Nichols Steve Grubb +Steven Prichard Steven Roussey Steward Garcia <57494570+FSSRepo@users.noreply.github.com> Suaj Carrot <72162667+SuajCarrot@users.noreply.github.com> @@ -434,16 +517,19 @@ Tom C Tom Jobbins <784313+TheBloke@users.noreply.github.com> Tomas Tomáš Pazdiora +Tristan Druyen Tristan Ross Tungsten842 <886724vf@anonaddy.me> Tungsten842 Tushar UEXTM.com <84163508+uextm@users.noreply.github.com> +Ulrich Drepper Uzo Nweke Vaibhav Srivastav Val Kharitonov Valentin Konovalov Valentyn Bezshapkin <61702053+valentynbez@users.noreply.github.com> +Victor Nogueira Victor Z. Peng Vlad Vladimir @@ -455,7 +541,9 @@ Weird Constructor Welby Seely Wentai Zhang WillCorticesAI <150854901+WillCorticesAI@users.noreply.github.com> +William Tambellini Willy Tarreau +Wouter <9594229+DifferentialityDevelopment@users.noreply.github.com> Wu Jian Ping Wu Jian Ping Xiake Sun @@ -466,6 +554,8 @@ Xiaoyi Chen Xingchen Song(宋星辰) Xuan Son Nguyen Yann Follet <131855179+YannFollet@users.noreply.github.com> +Yaroslav +Yazan Agha-Schrader Yiming Cui Yishuo Wang Yueh-Po Peng <94939112+y10ab1@users.noreply.github.com> @@ -477,6 +567,7 @@ Zane Shannon Zay <95888118+isaiahbjork@users.noreply.github.com> Zenix Zhang Peiyuan +Zheng.Deng <32841220+dengzheng-cloud@users.noreply.github.com> ZhouYuChen Ziad Ben Hadj-Alouane Ziang Wu <97337387+ZiangWu-77@users.noreply.github.com> @@ -484,14 +575,18 @@ Zsapi a-n-n-a-l-e-e <150648636+a-n-n-a-l-e-e@users.noreply.github.com> adel boussaken afrideva <95653597+afrideva@users.noreply.github.com> +agray3 akawrykow <142945436+akawrykow@users.noreply.github.com> alexpinel <93524949+alexpinel@users.noreply.github.com> alonfaraj +alwqx +amd-lalithnc andrijdavid anon998 <131767832+anon998@users.noreply.github.com> anzz1 apaz apcameron <37645737+apcameron@users.noreply.github.com> +arch-btw <57669023+arch-btw@users.noreply.github.com> arcrank arlo-phoenix <140345165+arlo-phoenix@users.noreply.github.com> at8u <129688334+at8u@users.noreply.github.com> @@ -514,13 +609,17 @@ cocktailpeanut <121128867+cocktailpeanut@users.noreply.github.com> coezbek comex compilade <113953597+compilade@users.noreply.github.com> +compilade +cpumaxx <163466046+cpumaxx@users.noreply.github.com> crasm crasm daboe01 david raistrick +ddh0 ddpasa <112642920+ddpasa@users.noreply.github.com> deepdiffuser <112834445+deepdiffuser@users.noreply.github.com> divinity76 +dm4 dotpy314 <33351922+dotpy314@users.noreply.github.com> drbh ds5t5 <145942675+ds5t5@users.noreply.github.com> @@ -529,6 +628,7 @@ eastriver ebraminio eiery <19350831+eiery@users.noreply.github.com> eric8607242 +fairydreaming <166155368+fairydreaming@users.noreply.github.com> fraxy-v <65565042+fraxy-v@users.noreply.github.com> github-actions[bot] gliptic @@ -539,6 +639,7 @@ h-h-h-h <13482553+h-h-h-h@users.noreply.github.com> hankcs hoangmit hongbo.mo <352280764@qq.com> +hopkins385 <98618192+hopkins385@users.noreply.github.com> howlger howlger hutli <6594598+hutli@users.noreply.github.com> @@ -549,14 +650,22 @@ hydai iSma iacore <74560659+iacore@users.noreply.github.com> igarnier +intelmatt <61025942+intelmatt@users.noreply.github.com> iohub jacobi petrucciani <8117202+jpetrucciani@users.noreply.github.com> +jaime-m-p <167997752+jaime-m-p@users.noreply.github.com> jameswu2014 <545426914@qq.com> +jiez <373447296@qq.com> jneem +joecryptotoo <80373433+joecryptotoo@users.noreply.github.com> johnson442 <56517414+johnson442@users.noreply.github.com> +jojorne jon-chuang <9093549+jon-chuang@users.noreply.github.com> jp-x-g +jukofyork <69222624+jukofyork@users.noreply.github.com> +junchao-loongson <68935141+junchao-loongson@users.noreply.github.com> jwj7140 <32943891+jwj7140@users.noreply.github.com> +k.h.lai kaizau kalomaze <66376113+kalomaze@users.noreply.github.com> kang @@ -575,11 +684,15 @@ ldwang le.chang leejet limitedAtonement +liuwei-git <14815172+liuwei-git@users.noreply.github.com> lon <114724657+longregen@users.noreply.github.com> +loonerin <132926317+loonerin@users.noreply.github.com> +luoyu-intel m3ndax maddes8cht <55592906+maddes8cht@users.noreply.github.com> makomk manikbhandari +maor-ps <154728172+maor-ps@users.noreply.github.com> mdrokz mgroeber9110 <45620825+mgroeber9110@users.noreply.github.com> minarchist @@ -593,15 +706,19 @@ ngc92 <7938269+ngc92@users.noreply.github.com> nhamanasu <45545786+nhamanasu@users.noreply.github.com> niansa/tuxifan niansa/tuxifan +nickp27 ningshanwutuobang nold nopperl <54780682+nopperl@users.noreply.github.com> nusu-github <29514220+nusu-github@users.noreply.github.com> olexiyb +omahs <73983677+omahs@users.noreply.github.com> oobabooga <112222186+oobabooga@users.noreply.github.com> opparco ostix360 <55257054+ostix360@users.noreply.github.com> +pengxin99 perserk +pmysl postmasters pudepiedj qingfengfenga <41416092+qingfengfenga@users.noreply.github.com> @@ -614,16 +731,19 @@ rhuddleston rimoliga <53384203+rimoliga@users.noreply.github.com> runfuture sandyiscool +sasha0552 semidark sharpHL <132747147+sharpHL@users.noreply.github.com> shibe2 singularity <12184989+singularity-s0@users.noreply.github.com> sjinzh +sjxx <63994076+ylsdamxssjxxdd@users.noreply.github.com> slaren <2141330+slaren@users.noreply.github.com> slaren snadampal <87143774+snadampal@users.noreply.github.com> staviq stduhpf +strawberrymelonpanda <152940198+strawberrymelonpanda@users.noreply.github.com> swittk takov751 <40316768+takov751@users.noreply.github.com> tarcey @@ -636,12 +756,16 @@ uint256_t uint256_t unbounded valiray <133289098+valiray@users.noreply.github.com> +vik +viric vodkaslime <646329483@qq.com> vvhg1 <94630311+vvhg1@users.noreply.github.com> vxiiduu <73044267+vxiiduu@users.noreply.github.com> wbpxre150 <100937007+wbpxre150@users.noreply.github.com> whoreson <139810751+whoreson@users.noreply.github.com> +woachk <24752637+woachk@users.noreply.github.com> wonjun Jang +woodx <124784234+woodx9@users.noreply.github.com> wzy <32936898+Freed-Wu@users.noreply.github.com> xaedes xaedes @@ -649,7 +773,10 @@ xloem <0xloem@gmail.com> yangli2 yuiseki zakkor +zhangkaihuo zhouwg <6889919+zhouwg@users.noreply.github.com> +zhouwg zrm +Ștefan-Gabriel Muscalu 源文雨 <41315874+fumiama@users.noreply.github.com> Нияз Гарифзянов <112617865+garrnizon@users.noreply.github.com> From f2d48fffde76d959fdb0da37316bdc09e5518eb1 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Wed, 26 Jun 2024 19:39:19 +0300 Subject: [PATCH 031/326] sync : ggml --- scripts/sync-ggml.last | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/sync-ggml.last b/scripts/sync-ggml.last index b6c57ec5e4f14..2da33e913bc8f 100644 --- a/scripts/sync-ggml.last +++ b/scripts/sync-ggml.last @@ -1 +1 @@ -5653a195935ea3ac54652644c9daf154dbc1571b +5378ea0d3c2f25bcd330ecb226ad2db454be86d0 From c7ab7b612cbdce04499575e713076a026af4b9c5 Mon Sep 17 00:00:00 2001 From: slaren Date: Wed, 26 Jun 2024 20:20:22 +0200 Subject: [PATCH 032/326] make : fix missing -O3 (#8143) --- Makefile | 11 ++++------- 1 file changed, 4 insertions(+), 7 deletions(-) diff --git a/Makefile b/Makefile index 64a6e6ff00e5a..bbfe0f12b228f 100644 --- a/Makefile +++ b/Makefile @@ -148,12 +148,6 @@ ifndef UNAME_M UNAME_M := $(shell uname -m) endif -MK_CFLAGS += -O3 -MK_CXXFLAGS += -O3 -ifndef LLAMA_DEBUG -MK_NVCCFLAGS += -O3 -endif # LLAMA_DEBUG - # In GNU make default CXX is g++ instead of c++. Let's fix that so that users # of non-gcc compilers don't have to provide g++ alias or wrapper. DEFCC := cc @@ -312,7 +306,10 @@ ifdef LLAMA_DEBUG MK_CPPFLAGS += -D_GLIBCXX_ASSERTIONS endif else - MK_CPPFLAGS += -DNDEBUG + MK_CPPFLAGS += -DNDEBUG + MK_CFLAGS += -O3 + MK_CXXFLAGS += -O3 + MK_NVCCFLAGS += -O3 endif ifdef LLAMA_SANITIZE_THREAD From 31ec3993f6e050322a249c07af79dbde66ea6ddc Mon Sep 17 00:00:00 2001 From: slaren Date: Wed, 26 Jun 2024 21:34:14 +0200 Subject: [PATCH 033/326] ggml : add GGML_CUDA_USE_GRAPHS option, restore GGML_CUDA_FORCE_CUBLAS (cmake) (#8140) --- CMakeLists.txt | 1 + ggml/CMakeLists.txt | 2 ++ ggml/src/CMakeLists.txt | 5 ++++- 3 files changed, 7 insertions(+), 1 deletion(-) diff --git a/CMakeLists.txt b/CMakeLists.txt index 18297834e9225..7a7197282f946 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -80,6 +80,7 @@ set(GGML_SANITIZE_UNDEFINED ${LLAMA_SANITIZE_UNDEFINED}) set(GGML_ALL_WARNINGS ${LLAMA_ALL_WARNINGS}) set(GGML_FATAL_WARNINGS ${LLAMA_FATAL_WARNINGS}) set(GGML_LLAMAFILE ON) +set(GGML_CUDA_USE_GRAPHS ON) # transition helpers function (llama_option_depr TYPE OLD NEW) diff --git a/ggml/CMakeLists.txt b/ggml/CMakeLists.txt index f3763f7eb9fef..0d0d52d575971 100644 --- a/ggml/CMakeLists.txt +++ b/ggml/CMakeLists.txt @@ -109,6 +109,7 @@ option(GGML_LLAMAFILE "ggml: use ggml SGEMM" option(GGML_CUDA "ggml: use CUDA" OFF) option(GGML_CUDA_FORCE_DMMV "ggml: use dmmv instead of mmvq CUDA kernels" OFF) option(GGML_CUDA_FORCE_MMQ "ggml: use mmq kernels instead of cuBLAS" OFF) +option(GGML_CUDA_FORCE_CUBLAS "ggml: always use cuBLAS instead of mmq kernels" OFF) set (GGML_CUDA_DMMV_X "32" CACHE STRING "ggml: x stride for dmmv CUDA kernels") set (GGML_CUDA_MMV_Y "1" CACHE STRING "ggml: y block size for mmv CUDA kernels") option(GGML_CUDA_F16 "ggml: use 16 bit floats for some calculations" OFF) @@ -119,6 +120,7 @@ set (GGML_CUDA_PEER_MAX_BATCH_SIZE "128" CACHE STRING option(GGML_CUDA_NO_PEER_COPY "ggml: do not use peer to peer copies" OFF) option(GGML_CUDA_NO_VMM "ggml: do not try to use CUDA VMM" OFF) option(GGML_CUDA_FA_ALL_QUANTS "ggml: compile all quants for FlashAttention" OFF) +option(GGML_CUDA_USE_GRAPHS "ggml: use CUDA graphs (llama.cpp only)" OFF) option(GGML_CURL "ggml: use libcurl to download model from an URL" OFF) option(GGML_HIPBLAS "ggml: use hipBLAS" OFF) diff --git a/ggml/src/CMakeLists.txt b/ggml/src/CMakeLists.txt index ba341d3749050..d0f4097d8cd0c 100644 --- a/ggml/src/CMakeLists.txt +++ b/ggml/src/CMakeLists.txt @@ -295,12 +295,15 @@ if (GGML_CUDA) list(APPEND GGML_CDEF_PUBLIC GGML_USE_CUDA) - add_compile_definitions(GGML_CUDA_USE_GRAPHS) add_compile_definitions(GGML_CUDA_DMMV_X=${GGML_CUDA_DMMV_X}) add_compile_definitions(GGML_CUDA_MMV_Y=${GGML_CUDA_MMV_Y}) add_compile_definitions(K_QUANTS_PER_ITERATION=${GGML_CUDA_KQUANTS_ITER}) add_compile_definitions(GGML_CUDA_PEER_MAX_BATCH_SIZE=${GGML_CUDA_PEER_MAX_BATCH_SIZE}) + if (GGML_CUDA_USE_GRAPHS) + add_compile_definitions(GGML_CUDA_USE_GRAPHS) + endif() + if (GGML_CUDA_FORCE_DMMV) add_compile_definitions(GGML_CUDA_FORCE_DMMV) endif() From ae5d0f4b899ff2842bfca561370c945ad8d4368b Mon Sep 17 00:00:00 2001 From: slaren Date: Wed, 26 Jun 2024 21:59:28 +0200 Subject: [PATCH 034/326] ci : publish new docker images only when the files change (#8142) --- .github/workflows/build.yml | 4 ++-- .github/workflows/docker.yml | 1 + 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 0d91fc4e4e965..20851528726aa 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -10,10 +10,10 @@ on: push: branches: - master - paths: ['.github/workflows/**', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.swift', '**/*.m'] + paths: ['.github/workflows/build.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.cuh', '**/*.swift', '**/*.m', '**/*.metal'] pull_request: types: [opened, synchronize, reopened] - paths: ['.github/workflows/build.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.cuh', '**/*.swift', '**/*.m'] + paths: ['.github/workflows/build.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.cuh', '**/*.swift', '**/*.m', '**/*.metal'] concurrency: group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }} diff --git a/.github/workflows/docker.yml b/.github/workflows/docker.yml index 01f1a45227527..bf94b2024e814 100644 --- a/.github/workflows/docker.yml +++ b/.github/workflows/docker.yml @@ -14,6 +14,7 @@ on: push: branches: - master + paths: ['.github/workflows/docker.yml', '.devops/*.Dockerfile', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.cuh', '**/*.swift', '**/*.m', '**/*.metal'] concurrency: group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }} From c70d117c37cc7876e775d1e2722208a50c52edb3 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Wed, 26 Jun 2024 23:25:22 +0300 Subject: [PATCH 035/326] scripts : fix filename sync --- scripts/sync-ggml-am.sh | 71 ++++++++++++++++++++--------------------- 1 file changed, 35 insertions(+), 36 deletions(-) diff --git a/scripts/sync-ggml-am.sh b/scripts/sync-ggml-am.sh index 9e654180b93fb..b05a33747f831 100755 --- a/scripts/sync-ggml-am.sh +++ b/scripts/sync-ggml-am.sh @@ -136,42 +136,41 @@ if [ -f $SRC_LLAMA/ggml-src.patch ]; then # LICENSE -> LICENSE # scripts/gen-authors.sh -> scripts/gen-authors.sh - cat ggml-src.patch | sed \ - -e 's/CMakeLists.txt/ggml\/CMakeLists.txt/g' \ - -e 's/src\/CMakeLists.txt/ggml\/src\/CMakeLists.txt/g' \ - -e 's/cmake\/FindSIMD.cmake/ggml\/cmake\/FindSIMD.cmake/g' \ - -e 's/src\/ggml\.c/ggml/src/ggml.c/g' \ - -e 's/src\/ggml-alloc\.c/ggml/src/ggml-alloc.c/g' \ - -e 's/src\/ggml-backend-impl\.h/ggml/src/ggml-backend-impl.h/g' \ - -e 's/src\/ggml-backend\.c/ggml/src/ggml-backend.c/g' \ - -e 's/src\/ggml-common\.h/ggml/src/ggml-common.h/g' \ - -e 's/src\/ggml-cuda\//ggml-cuda\//g' \ - -e 's/src\/ggml-cuda\.cu/ggml/src/ggml-cuda.cu/g' \ - -e 's/src\/ggml-impl\.h/ggml/src/ggml-impl.h/g' \ - -e 's/src\/ggml-kompute\.cpp/ggml/src/ggml-kompute.cpp/g' \ - -e 's/src\/ggml-metal\.m/ggml/src/ggml-metal.m/g' \ - -e 's/src\/ggml-quants\.c/ggml/src/ggml-quants.c/g' \ - -e 's/src\/ggml-quants\.h/ggml/src/ggml-quants.h/g' \ - -e 's/src\/ggml-rpc\.cpp/ggml/src/ggml-rpc.cpp/g' \ - -e 's/src\/ggml-sycl\.cpp/ggml/src/ggml-sycl.cpp/g' \ - -e 's/src\/ggml-vulkan\.cpp/ggml/src/ggml-vulkan.cpp/g' \ - -e 's/include\/ggml\.h/ggml/include/ggml.h/g' \ - -e 's/include\/ggml-alloc\.h/ggml/include/ggml-alloc.h/g' \ - -e 's/include\/ggml-backend\.h/ggml/include/ggml-backend.h/g' \ - -e 's/include\/ggml-blas\.h/ggml/include/ggml-blas.h/g' \ - -e 's/include\/ggml-cuda\.h/ggml/include/ggml-cuda.h/g' \ - -e 's/include\/ggml-kompute\.h/ggml/include/ggml-kompute.h/g' \ - -e 's/include\/ggml-metal\.h/ggml/include/ggml-metal.h/g' \ - -e 's/include\/ggml-rpc\.h/ggml/include/ggml-rpc.h/g' \ - -e 's/include\/ggml-sycl\.h/ggml/include/ggml-sycl.h/g' \ - -e 's/include\/ggml-vulkan\.h/ggml/include/ggml-vulkan.h/g' \ - -e 's/tests\/test-opt\.cpp/tests\/test-opt.cpp/g' \ - -e 's/tests\/test-grad0\.cpp/tests\/test-grad0.cpp/g' \ - -e 's/tests\/test-quantize-fns\.cpp/tests\/test-quantize-fns.cpp/g' \ - -e 's/tests\/test-quantize-perf\.cpp/tests\/test-quantize-perf.cpp/g' \ - -e 's/tests\/test-backend-ops\.cpp/tests\/test-backend-ops.cpp/g' \ - -e 's/LICENSE/LICENSE/g' \ - -e 's/scripts\/gen-authors\.sh/scripts\/gen-authors.sh/g' \ + cat ggml-src.patch | sed -E \ + -e 's/([[:space:]]|[ab]\/)CMakeLists.txt/\1ggml\/CMakeLists.txt/g' \ + -e 's/([[:space:]]|[ab]\/)src\/CMakeLists.txt/\1ggml\/src\/CMakeLists.txt/g' \ + -e 's/([[:space:]]|[ab]\/)cmake\/FindSIMD.cmake/\1ggml\/cmake\/FindSIMD.cmake/g' \ + -e 's/([[:space:]]|[ab]\/)src\/ggml\.c/\1ggml\/src\/ggml.c/g' \ + -e 's/([[:space:]]|[ab]\/)src\/ggml-alloc\.c/\1ggml\/src\/ggml-alloc.c/g' \ + -e 's/([[:space:]]|[ab]\/)src\/ggml-backend-impl\.h/\1ggml\/src\/ggml-backend-impl.h/g' \ + -e 's/([[:space:]]|[ab]\/)src\/ggml-backend\.c/\1ggml\/src\/ggml-backend.c/g' \ + -e 's/([[:space:]]|[ab]\/)src\/ggml-common\.h/\1ggml\/src\/ggml-common.h/g' \ + -e 's/([[:space:]]|[ab]\/)src\/ggml-cuda\//\1ggml\/src\/ggml-cuda\//g' \ + -e 's/([[:space:]]|[ab]\/)src\/ggml-cuda\.cu/\1ggml\/src\/ggml-cuda.cu/g' \ + -e 's/([[:space:]]|[ab]\/)src\/ggml-impl\.h/\1ggml\/src\/ggml-impl.h/g' \ + -e 's/([[:space:]]|[ab]\/)src\/ggml-kompute\.cpp/\1ggml\/src\/ggml-kompute.cpp/g' \ + -e 's/([[:space:]]|[ab]\/)src\/ggml-metal\.m/\1ggml\/src\/ggml-metal.m/g' \ + -e 's/([[:space:]]|[ab]\/)src\/ggml-quants\.c/\1ggml\/src\/ggml-quants.c/g' \ + -e 's/([[:space:]]|[ab]\/)src\/ggml-quants\.h/\1ggml\/src\/ggml-quants.h/g' \ + -e 's/([[:space:]]|[ab]\/)src\/ggml-rpc\.cpp/\1ggml\/src\/ggml-rpc.cpp/g' \ + -e 's/([[:space:]]|[ab]\/)src\/ggml-sycl\.cpp/\1ggml\/src\/ggml-sycl.cpp/g' \ + -e 's/([[:space:]]|[ab]\/)src\/ggml-vulkan\.cpp/\1ggml\/src\/ggml-vulkan.cpp/g' \ + -e 's/([[:space:]]|[ab]\/)include\/ggml\.h/\1ggml\/include\/ggml.h/g' \ + -e 's/([[:space:]]|[ab]\/)include\/ggml-alloc\.h/\1ggml\/include\/ggml-alloc.h/g' \ + -e 's/([[:space:]]|[ab]\/)include\/ggml-backend\.h/\1ggml\/include\/ggml-backend.h/g' \ + -e 's/([[:space:]]|[ab]\/)include\/ggml-blas\.h/\1ggml\/include\/ggml-blas.h/g' \ + -e 's/([[:space:]]|[ab]\/)include\/ggml-cuda\.h/\1ggml\/include\/ggml-cuda.h/g' \ + -e 's/([[:space:]]|[ab]\/)include\/ggml-kompute\.h/\1ggml\/include\/ggml-kompute.h/g' \ + -e 's/([[:space:]]|[ab]\/)include\/ggml-metal\.h/\1ggml\/include\/ggml-metal.h/g' \ + -e 's/([[:space:]]|[ab]\/)include\/ggml-rpc\.h/\1ggml\/include\/ggml-rpc.h/g' \ + -e 's/([[:space:]]|[ab]\/)include\/ggml-sycl\.h/\1ggml\/include\/ggml-sycl.h/g' \ + -e 's/([[:space:]]|[ab]\/)include\/ggml-vulkan\.h/\1ggml\/include\/ggml-vulkan.h/g' \ + -e 's/([[:space:]]|[ab]\/)examples\/common\.h/examples\/common.h/g' \ + -e 's/([[:space:]]|[ab]\/)examples\/common\.cpp/examples\/common.cpp/g' \ + -e 's/([[:space:]]|[ab]\/)examples\/common-ggml\.h/examples\/common-ggml.h/g' \ + -e 's/([[:space:]]|[ab]\/)examples\/common-ggml\.cpp/examples\/common-ggml.cpp/g' \ + -e 's/([[:space:]]|[ab]\/)LICENSE/LICENSE/g' \ + -e 's/([[:space:]]|[ab]\/)scripts\/gen-authors\.sh/scripts\/gen-authors.sh/g' \ > ggml-src.patch.tmp mv ggml-src.patch.tmp ggml-src.patch From 9b31a40c6ddabe552875b811d7127aa039ca9703 Mon Sep 17 00:00:00 2001 From: Daniel Bevenius Date: Thu, 27 Jun 2024 01:50:09 +0200 Subject: [PATCH 036/326] clip : suppress unused variable warnings (#8105) * clip : suppress unused variable warnings This commit suppresses unused variable warnings for the variables e in the catch blocks. The motivation for this change is to suppress the warnings that are generated on Windows when using the MSVC compiler. The warnings are not displayed when using GCC because GCC will mark all catch parameters as used. Signed-off-by: Daniel Bevenius * squash! clip : suppress unused variable warnings Remove e (/*e*/) instead instead of using GGML_UNUSED. --------- Signed-off-by: Daniel Bevenius --- examples/llava/clip.cpp | 26 +++++++++++++------------- 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/examples/llava/clip.cpp b/examples/llava/clip.cpp index 95fbe3d0216c4..d6882eec31e1a 100644 --- a/examples/llava/clip.cpp +++ b/examples/llava/clip.cpp @@ -1121,20 +1121,20 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) { } if (n < 32) hparams.image_grid_pinpoints[n] = 0; - } catch (std::runtime_error & e) { + } catch (std::runtime_error & /*e*/) { hparams.image_grid_pinpoints[0]=0; } try { int idx = get_key_idx(ctx, KEY_MM_PATCH_MERGE_TYPE); strcpy(hparams.mm_patch_merge_type, gguf_get_val_str(ctx, idx)); - } catch (std::runtime_error & e) { + } catch (std::runtime_error & /*e*/) { strcpy(hparams.mm_patch_merge_type, "flat"); } try { hparams.image_crop_resolution = get_u32(ctx, KEY_IMAGE_CROP_RESOLUTION); // llava-1.6 - } catch(const std::exception& e) { + } catch(const std::exception& /*e*/) { hparams.image_crop_resolution = hparams.image_size; } @@ -1173,7 +1173,7 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) { try { vision_model.class_embedding = get_tensor(new_clip->ctx_data, TN_CLASS_EMBD); new_clip->has_class_embedding = true; - } catch (const std::exception& e) { + } catch (const std::exception& /*e*/) { new_clip->has_class_embedding = false; } @@ -1181,7 +1181,7 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) { vision_model.pre_ln_w = get_tensor(new_clip->ctx_data, format(TN_LN_PRE, "v", "weight")); vision_model.pre_ln_b = get_tensor(new_clip->ctx_data, format(TN_LN_PRE, "v", "bias")); new_clip->has_pre_norm = true; - } catch (std::exception & e) { + } catch (std::exception & /*e*/) { new_clip->has_pre_norm = false; } @@ -1189,21 +1189,21 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) { vision_model.post_ln_w = get_tensor(new_clip->ctx_data, format(TN_LN_POST, "v", "weight")); vision_model.post_ln_b = get_tensor(new_clip->ctx_data, format(TN_LN_POST, "v", "bias")); new_clip->has_post_norm = true; - } catch (std::exception & e) { + } catch (std::exception & /*e*/) { new_clip->has_post_norm = false; } try { vision_model.patch_bias = get_tensor(new_clip->ctx_data, TN_PATCH_BIAS); new_clip->has_patch_bias = true; - } catch (std::exception & e) { + } catch (std::exception & /*e*/) { new_clip->has_patch_bias = false; } try { vision_model.patch_embeddings = get_tensor(new_clip->ctx_data, TN_PATCH_EMBD); vision_model.position_embeddings = get_tensor(new_clip->ctx_data, format(TN_POS_EMBD, "v")); - } catch(const std::exception& e) { + } catch(const std::exception& /*e*/) { LOG_TEE("%s: failed to load vision model tensors\n", __func__); } @@ -1215,26 +1215,26 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) { // Yi-type llava vision_model.mm_1_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 1, "weight")); vision_model.mm_1_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 1, "bias")); - } catch (std::runtime_error & e) { } + } catch (std::runtime_error & /*e*/) { } try { // missing in Yi-type llava vision_model.mm_2_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 2, "weight")); vision_model.mm_2_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 2, "bias")); - } catch (std::runtime_error & e) { } + } catch (std::runtime_error & /*e*/) { } try { // Yi-type llava vision_model.mm_3_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 3, "weight")); vision_model.mm_3_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 3, "bias")); - } catch (std::runtime_error & e) { } + } catch (std::runtime_error & /*e*/) { } try { // Yi-type llava vision_model.mm_4_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 4, "weight")); vision_model.mm_4_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 4, "bias")); - } catch (std::runtime_error & e) { } + } catch (std::runtime_error & /*e*/) { } try { vision_model.image_newline = get_tensor(new_clip->ctx_data, TN_IMAGE_NEWLINE); // LOG_TEE("%s: image_newline tensor (llava-1.6) found\n", __func__); - } catch (std::runtime_error & e) { } + } catch (std::runtime_error & /*e*/) { } } else if (new_clip->proj_type == PROJECTOR_TYPE_LDP) { // MobileVLM projection vision_model.mm_model_mlp_1_w = get_tensor(new_clip->ctx_data, format(TN_MVLM_PROJ_MLP, 1, "weight")); From ac146628e47451c531a3c7e62e6a973a2bb467a0 Mon Sep 17 00:00:00 2001 From: Raj Hammeer Singh Hada Date: Thu, 27 Jun 2024 07:27:57 +0530 Subject: [PATCH 037/326] Fix llama-android.cpp for error - "common/common.h not found" (#8145) - Path seems to be wrong for the common.h header file in llama-android.cpp file. Fixing the path so the Android Build doesn't fail with the error "There is no file common/common.h" --- examples/llama.android/llama/src/main/cpp/llama-android.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/llama.android/llama/src/main/cpp/llama-android.cpp b/examples/llama.android/llama/src/main/cpp/llama-android.cpp index 874158ef0f98f..92a6b16b1a00c 100644 --- a/examples/llama.android/llama/src/main/cpp/llama-android.cpp +++ b/examples/llama.android/llama/src/main/cpp/llama-android.cpp @@ -5,7 +5,7 @@ #include #include #include "llama.h" -#include "common/common.h" +#include "common.h" // Write C++ code here. // From 911e35bb8bb2fd1c7d3f40f27e96ff432eae7e14 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Sigbj=C3=B8rn=20Skj=C3=A6ret?= Date: Thu, 27 Jun 2024 09:46:41 +0200 Subject: [PATCH 038/326] llama : fix CodeLlama FIM token checks (#8144) * account for space prefix character * use find instead --- src/llama.cpp | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/llama.cpp b/src/llama.cpp index f78594a6f7c49..080057332b4dc 100644 --- a/src/llama.cpp +++ b/src/llama.cpp @@ -5152,10 +5152,10 @@ static void llm_load_vocab( if (gen_name.find("code") != std::string::npos) { if (model.arch == LLM_ARCH_LLAMA && 32010 < vocab.id_to_token.size() - && vocab.id_to_token[32007].text == "
"
-              && vocab.id_to_token[32008].text == ""
-              && vocab.id_to_token[32009].text == ""
-              && vocab.id_to_token[32010].text == "") {
+              && vocab.id_to_token[32007].text.find("
") != std::string::npos
+              && vocab.id_to_token[32008].text.find("") != std::string::npos
+              && vocab.id_to_token[32009].text.find("") != std::string::npos
+              && vocab.id_to_token[32010].text.find("") != std::string::npos) {
                 vocab.special_prefix_id = 32007;
                 vocab.special_suffix_id = 32008;
                 vocab.special_middle_id = 32009;

From f675b20a3b7f878bf3be766b9a737e2c8321ff0d Mon Sep 17 00:00:00 2001
From: kustaaya <58045274+kustaaya@users.noreply.github.com>
Date: Thu, 27 Jun 2024 11:58:54 +0300
Subject: [PATCH 039/326] Added support for Viking pre-tokenizer (#8135)

Co-authored-by: kustaaya 
---
 convert-hf-to-gguf-update.py | 1 +
 convert-hf-to-gguf.py        | 3 +++
 include/llama.h              | 1 +
 src/llama.cpp                | 9 +++++++++
 4 files changed, 14 insertions(+)

diff --git a/convert-hf-to-gguf-update.py b/convert-hf-to-gguf-update.py
index 67598b561e6cb..2758214fa8730 100755
--- a/convert-hf-to-gguf-update.py
+++ b/convert-hf-to-gguf-update.py
@@ -85,6 +85,7 @@ class TOKENIZER_TYPE(IntEnum):
     {"name": "smaug-bpe",      "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/abacusai/Smaug-Llama-3-70B-Instruct", },
     {"name": "poro-chat",      "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/LumiOpen/Poro-34B-chat", },
     {"name": "jina-v2-code",   "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-code", },
+    {"name": "viking",         "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/LumiOpen/Viking-7B", }, # Also used for Viking 13B and 33B
 ]
 
 
diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py
index c26fad9307f15..5bf69ef9fa060 100755
--- a/convert-hf-to-gguf.py
+++ b/convert-hf-to-gguf.py
@@ -487,6 +487,9 @@ def get_vocab_base_pre(self, tokenizer) -> str:
         if chkhsh == "7967bfa498ade6b757b064f31e964dddbb80f8f9a4d68d4ba7998fcf281c531a":
             # ref: https://huggingface.co/jinaai/jina-embeddings-v2-base-code
             res = "jina-v2-code"
+        if chkhsh == "7fc505bd3104ca1083b150b17d088b59534ede9bde81f0dd2090967d7fe52cee":
+            # ref: https://huggingface.co/LumiOpen/Viking-7B
+            res = "viking"
 
         if res is None:
             logger.warning("\n")
diff --git a/include/llama.h b/include/llama.h
index 88eecb0edb17e..cafeafb85dbc7 100644
--- a/include/llama.h
+++ b/include/llama.h
@@ -88,6 +88,7 @@ extern "C" {
         LLAMA_VOCAB_PRE_TYPE_DBRX           = 13,
         LLAMA_VOCAB_PRE_TYPE_SMAUG          = 14,
         LLAMA_VOCAB_PRE_TYPE_PORO           = 15,
+        LLAMA_VOCAB_PRE_TYPE_VIKING         = 16,
     };
 
     // note: these values should be synchronized with ggml_rope
diff --git a/src/llama.cpp b/src/llama.cpp
index 080057332b4dc..b97b5e2795c0d 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -5067,6 +5067,9 @@ static void llm_load_vocab(
             } else if (
                 tokenizer_pre == "poro-chat") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_PORO;
+            } else if (
+                tokenizer_pre == "viking") {
+                vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_VIKING;
             } else {
                 throw std::runtime_error(format("unknown pre-tokenizer type: '%s'", tokenizer_pre.c_str()));
             }
@@ -13703,6 +13706,12 @@ struct llm_tokenizer_bpe {
                     " ?[^(\\s|.,!?…。，、।۔،)]+",
                 };
                 break;
+            case LLAMA_VOCAB_PRE_TYPE_VIKING:
+                regex_exprs = {
+                    "\\p{N}",
+                    " ?[^(\\s|.,!?…。，、।۔،)]+",
+                };
+                break;
             default:
                 // default regex for BPE tokenization pre-processing
                 regex_exprs = {

From 85a267daaa1c6f8fd69160445bcb88717031d10c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= 
Date: Thu, 27 Jun 2024 16:26:05 +0200
Subject: [PATCH 040/326] CUDA: fix MMQ stream-k for --split-mode row (#8167)

---
 ggml/src/ggml-cuda/mmq.cuh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ggml/src/ggml-cuda/mmq.cuh b/ggml/src/ggml-cuda/mmq.cuh
index 31fcbf1397b6b..1396e7a753ac3 100644
--- a/ggml/src/ggml-cuda/mmq.cuh
+++ b/ggml/src/ggml-cuda/mmq.cuh
@@ -2475,7 +2475,7 @@ static void launch_mul_mat_q(ggml_backend_cuda_context & ctx, const mmq_args & a
 
     const dim3 block_nums_mmq(nsm, 1, 1);
 
-    ggml_cuda_pool & pool = ctx.pool();
+    ggml_cuda_pool & pool = ctx.pool(id);
     ggml_cuda_pool_alloc tmp_fixup(pool, block_nums_mmq.x * mmq_x*mmq_y);
 
     if (args.ne01 % mmq_y == 0) {

From 6030c61281c8a7eb94eceb7396a608fac8b71555 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Sigbj=C3=B8rn=20Skj=C3=A6ret?= 
Date: Thu, 27 Jun 2024 16:27:41 +0200
Subject: [PATCH 041/326] Add Qwen2MoE 57B-A14B model identifier (#8158)

* Add Qwen2MoE 57B-A14B

* Add Qwen2MoE 57B-A14B
---
 src/llama.cpp | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/src/llama.cpp b/src/llama.cpp
index b97b5e2795c0d..3dc0f85351c50 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -2038,6 +2038,7 @@ enum e_model {
     MODEL_8x22B,
     MODEL_16x12B,
     MODEL_10B_128x3_66B,
+    MODEL_57B_A14B,
 };
 
 static const size_t kiB = 1024;
@@ -4267,6 +4268,7 @@ static const char * llama_model_type_name(e_model type) {
         case MODEL_8x22B:         return "8x22B";
         case MODEL_16x12B:        return "16x12B";
         case MODEL_10B_128x3_66B: return "10B+128x3.66B";
+        case MODEL_57B_A14B:      return "57B.A14B";
         default:                  return "?B";
     }
 }
@@ -4588,6 +4590,7 @@ static void llm_load_hparams(
                 ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
                 switch (hparams.n_layer) {
                     case 24: model.type = e_model::MODEL_A2_7B; break;
+                    case 28: model.type = e_model::MODEL_57B_A14B; break;
                     default: model.type = e_model::MODEL_UNKNOWN;
                 }
             } break;

From 387952651a8fc493f8c85ea4c9774bd4a5694f87 Mon Sep 17 00:00:00 2001
From: Raj Hammeer Singh Hada 
Date: Thu, 27 Jun 2024 20:09:29 +0530
Subject: [PATCH 042/326] Delete examples/llama.android/llama/CMakeLists.txt
 (#8165)

* Delete examples/llama.android/llama/CMakeLists.txt

https://github.com/ggerganov/llama.cpp/pull/8145#issuecomment-2194534244

This file is not being used for building on Android. `llama.cpp/examples/llama.android/llama/src/main/cpp/CMakeLists.txt` is being used instead.

* Update CMakeLists.txt

Pick local llama.cpp files instead of fetching content from git
---
 examples/llama.android/llama/CMakeLists.txt   | 55 -------------------
 .../llama/src/main/cpp/CMakeLists.txt         | 18 +++---
 2 files changed, 11 insertions(+), 62 deletions(-)
 delete mode 100644 examples/llama.android/llama/CMakeLists.txt

diff --git a/examples/llama.android/llama/CMakeLists.txt b/examples/llama.android/llama/CMakeLists.txt
deleted file mode 100644
index a5618cac05849..0000000000000
--- a/examples/llama.android/llama/CMakeLists.txt
+++ /dev/null
@@ -1,55 +0,0 @@
-
-# For more information about using CMake with Android Studio, read the
-# documentation: https://d.android.com/studio/projects/add-native-code.html.
-# For more examples on how to use CMake, see https://github.com/android/ndk-samples.
-
-# Sets the minimum CMake version required for this project.
-cmake_minimum_required(VERSION 3.22.1)
-
-# Declares the project name. The project name can be accessed via ${ PROJECT_NAME},
-# Since this is the top level CMakeLists.txt, the project name is also accessible
-# with ${CMAKE_PROJECT_NAME} (both CMake variables are in-sync within the top level
-# build script scope).
-project("llama-android")
-
-## Fetch latest llama.cpp from GitHub
-#include(FetchContent)
-#FetchContent_Declare(
-#        llama
-#        GIT_REPOSITORY https://github.com/ggerganov/llama.cpp
-#        GIT_TAG        master
-#)
-#
-## Also provides "common"
-#FetchContent_MakeAvailable(llama)
-
-# llama.cpp CI uses the code from the current branch
-# ref: https://github.com/ggerganov/llama.cpp/pull/7341#issuecomment-2117617700
-add_subdirectory(../../../../../../ build-llama)
-
-# Creates and names a library, sets it as either STATIC
-# or SHARED, and provides the relative paths to its source code.
-# You can define multiple libraries, and CMake builds them for you.
-# Gradle automatically packages shared libraries with your APK.
-#
-# In this top level CMakeLists.txt, ${CMAKE_PROJECT_NAME} is used to define
-# the target library name; in the sub-module's CMakeLists.txt, ${PROJECT_NAME}
-# is preferred for the same purpose.
-#
-# In order to load a library into your app from Java/Kotlin, you must call
-# System.loadLibrary() and pass the name of the library defined here;
-# for GameActivity/NativeActivity derived applications, the same library name must be
-# used in the AndroidManifest.xml file.
-add_library(${CMAKE_PROJECT_NAME} SHARED
-    # List C/C++ source files with relative paths to this CMakeLists.txt.
-        llama-android.cpp)
-
-# Specifies libraries CMake should link to your target library. You
-# can link libraries from various origins, such as libraries defined in this
-# build script, prebuilt third-party libraries, or Android system libraries.
-target_link_libraries(${CMAKE_PROJECT_NAME}
-    # List libraries link to the target library
-    llama
-    common
-    android
-    log)
diff --git a/examples/llama.android/llama/src/main/cpp/CMakeLists.txt b/examples/llama.android/llama/src/main/cpp/CMakeLists.txt
index 42ebaad49a560..2de496574f54a 100644
--- a/examples/llama.android/llama/src/main/cpp/CMakeLists.txt
+++ b/examples/llama.android/llama/src/main/cpp/CMakeLists.txt
@@ -11,15 +11,15 @@ cmake_minimum_required(VERSION 3.22.1)
 # build script scope).
 project("llama-android")
 
-include(FetchContent)
-FetchContent_Declare(
-        llama
-        GIT_REPOSITORY https://github.com/ggerganov/llama.cpp
-        GIT_TAG        master
-)
+#include(FetchContent)
+#FetchContent_Declare(
+#        llama
+#        GIT_REPOSITORY https://github.com/ggerganov/llama.cpp
+#        GIT_TAG        master
+#)
 
 # Also provides "common"
-FetchContent_MakeAvailable(llama)
+#FetchContent_MakeAvailable(llama)
 
 # Creates and names a library, sets it as either STATIC
 # or SHARED, and provides the relative paths to its source code.
@@ -30,6 +30,10 @@ FetchContent_MakeAvailable(llama)
 # the target library name; in the sub-module's CMakeLists.txt, ${PROJECT_NAME}
 # is preferred for the same purpose.
 #
+
+#load local llama.cpp
+add_subdirectory(../../../../../../ build-llama)
+
 # In order to load a library into your app from Java/Kotlin, you must call
 # System.loadLibrary() and pass the name of the library defined here;
 # for GameActivity/NativeActivity derived applications, the same library name must be

From 97877eb10bd8e7f8023420b5b5300bcbdadd62dc Mon Sep 17 00:00:00 2001
From: jukofyork <69222624+jukofyork@users.noreply.github.com>
Date: Thu, 27 Jun 2024 15:48:07 +0100
Subject: [PATCH 043/326] Control vector loading fixes (#8137)

* Fixed leak in llama_control_vector_load_one() and allow llama_control_vector_load() to grow

* refactored `llama_control_vector_load_one()`

* allow multiple directions for same layer in same file

* llama_control_vector_load_one() and llama_control_vector_load() now break on error

* removed unnecessary ggml_free() call
---
 common/common.cpp | 182 +++++++++++++++++++---------------------------
 1 file changed, 74 insertions(+), 108 deletions(-)

diff --git a/common/common.cpp b/common/common.cpp
index c76d0e2c33be5..70349ad70891c 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -2804,125 +2804,87 @@ float llama_embd_similarity_cos(const float * embd1, const float * embd2, int n)
 //
 
 static llama_control_vector_data llama_control_vector_load_one(const llama_control_vector_load_info & load_info) {
-    int32_t n_tensors;
-
-    size_t n_bytes = 0;
-
-    uint32_t max_direction_layer = 0;
-
     llama_control_vector_data result = { -1, {} };
 
-    // calculate size of ctx needed for tensors, ensure tensors are f32, and find max layer
-    {
-        struct ggml_init_params meta_params = {
-            /* .mem_size   = */ ggml_tensor_overhead() * 128 + ggml_graph_overhead(),
-            /* .mem_buffer = */ nullptr,
-            /* .no_alloc   = */ true,
-        };
-        ggml_context * meta_ctx = ggml_init(meta_params);
-        struct gguf_init_params meta_gguf_params = {
-            /* .no_alloc = */ true,
-            /* .ctx      = */ &meta_ctx,
-        };
-        struct gguf_context * meta_ctx_gguf = gguf_init_from_file(load_info.fname.c_str(), meta_gguf_params);
-        if (!meta_ctx_gguf) {
-            fprintf(stderr, "%s: failed to load control vector from %s\n", __func__, load_info.fname.c_str());
-            ggml_free(meta_ctx);
-            return result;
-        }
-
-        n_tensors = gguf_get_n_tensors(meta_ctx_gguf);
-        for (int i = 0; i < n_tensors; i++) {
-            std::string name = gguf_get_tensor_name(meta_ctx_gguf, i);
-
-            // split on '.'
-            size_t dotpos = name.find('.');
-            if (dotpos != std::string::npos && name.substr(0, dotpos) == "direction") {
-                try {
-                    uint32_t layer = std::stoi(name.substr(dotpos + 1));
-                    if (layer == 0) {
-                        fprintf(stderr, "%s: direction tensor invalid in %s\n", __func__, load_info.fname.c_str());
-                        ggml_free(meta_ctx);
-                        gguf_free(meta_ctx_gguf);
-                        return result;
-                    }
-                    if (layer > max_direction_layer) {
-                        max_direction_layer = layer;
-                    }
-                } catch (...) {
-                    fprintf(stderr, "%s: direction tensor invalid in %s\n", __func__, load_info.fname.c_str());
-                    ggml_free(meta_ctx);
-                    gguf_free(meta_ctx_gguf);
-                    return result;
-                }
-            }
-
-            struct ggml_tensor * tensor_meta = ggml_get_tensor(meta_ctx, name.c_str());
-            if (tensor_meta->type != GGML_TYPE_F32 || ggml_n_dims(tensor_meta) != 1) {
-                fprintf(stderr, "%s: direction tensor invalid in %s\n", __func__, load_info.fname.c_str());
-                ggml_free(meta_ctx);
-                gguf_free(meta_ctx_gguf);
-                return result;
-            }
-            if (result.n_embd == -1) {
-                result.n_embd = ggml_nelements(tensor_meta);
-            } else if (ggml_nelements(tensor_meta) != result.n_embd) {
-                fprintf(stderr, "%s: direction tensor sizes mismatched in %s\n", __func__, load_info.fname.c_str());
-                ggml_free(meta_ctx);
-                gguf_free(meta_ctx_gguf);
-                return result;
-            }
-            n_bytes += ggml_nbytes(tensor_meta);
-        }
-        ggml_free(meta_ctx);
-        gguf_free(meta_ctx_gguf);
+    ggml_context * ctx = nullptr;
+    struct gguf_init_params meta_gguf_params = {
+        /* .no_alloc = */ false,
+        /* .ctx      = */ &ctx,
+    };
+    struct gguf_context * ctx_gguf = gguf_init_from_file(load_info.fname.c_str(), meta_gguf_params);
+    if (!ctx_gguf) {
+        fprintf(stderr, "%s: failed to load control vector file from %s\n", __func__, load_info.fname.c_str());
+        return result;
     }
 
+    int32_t n_tensors = gguf_get_n_tensors(ctx_gguf);
     if (n_tensors == 0) {
         fprintf(stderr, "%s: no direction tensors found in %s\n", __func__, load_info.fname.c_str());
-        return result;
     }
 
-    // load and scale tensors into final control vector context
-    struct ggml_init_params ggml_params = {
-        /* .mem_size   = */ ggml_tensor_overhead() * n_tensors + n_bytes,
-        /* .mem_buffer = */ nullptr,
-        /* .no_alloc   = */ false,
-    };
-    struct ggml_context * ctx = ggml_init(ggml_params);
+    for (int i = 0; i < n_tensors; i++) {
+        std::string name = gguf_get_tensor_name(ctx_gguf, i);
 
-    struct gguf_init_params params = {
-        /*.no_alloc = */ false,
-        /*.ctx      = */ &ctx,
-    };
-    struct gguf_context * ctx_gguf = gguf_init_from_file(load_info.fname.c_str(), params);
-    if (!ctx_gguf) {
-        fprintf(stderr, "%s: failed to load control vector from %s\n", __func__, load_info.fname.c_str());
-        ggml_free(ctx);
-        return result;
-    }
+        int layer_idx = -1;
 
-    // do not store data for layer 0 (it's not used)
-    result.data.resize(result.n_embd * max_direction_layer);
+        // split on '.'
+        size_t dotpos = name.find('.');
+        if (dotpos != std::string::npos && name.substr(0, dotpos) == "direction") {
+            try {
+                layer_idx = std::stoi(name.substr(dotpos + 1));
+            } catch (...) {
+                layer_idx = -1;
+            }
+        }
+        if (layer_idx < 0) {
+            fprintf(stderr, "%s: invalid/unparsable direction tensor layer index in %s\n", __func__, load_info.fname.c_str());
+            result.n_embd = -1;
+            break;
+        } else if (layer_idx == 0) {
+            fprintf(stderr, "%s: invalid (zero) direction tensor layer index in %s\n", __func__, load_info.fname.c_str());
+            result.n_embd = -1;
+            break;
+        }
 
-    for (uint32_t il = 1; il <= max_direction_layer; il++) {
-        const std::string name = "direction." + std::to_string(il);
-        const ggml_tensor * tensor = ggml_get_tensor(ctx, name.c_str());
+        struct ggml_tensor * tensor = ggml_get_tensor(ctx, name.c_str());
+        if (tensor->type != GGML_TYPE_F32) {
+            fprintf(stderr, "%s: invalid (non-F32) direction tensor type in %s\n", __func__, load_info.fname.c_str());
+            result.n_embd = -1;
+            break;
+        }
+        if (ggml_n_dims(tensor) != 1) {
+            fprintf(stderr, "%s: invalid (non-1D) direction tensor shape in %s\n", __func__, load_info.fname.c_str());
+            result.n_embd = -1;
+            break;
+        }
+
+        if (result.n_embd == -1) {
+            result.n_embd = ggml_nelements(tensor);
+        } else if (ggml_nelements(tensor) != result.n_embd) {
+            fprintf(stderr, "%s: direction tensor in %s does not match previous dimensions\n", __func__, load_info.fname.c_str());
+            result.n_embd = -1;
+            break;
+        }
 
-        float * dst = result.data.data() + result.n_embd * (il - 1);
+        // extend if necessary - do not store data for layer 0 (it's not used)
+        result.data.resize(std::max(result.data.size(), static_cast(result.n_embd * layer_idx)), 0.0f);
 
-        if (tensor) {
-            const float * src = (const float *) tensor->data;
-            for (int j = 0; j < result.n_embd; j++) {
-                dst[j] = src[j] * load_info.strength;
-            }
-        } else {
-            for (int j = 0; j < result.n_embd; j++) {
-                dst[j] = 0.0f;
-            }
+        const float * src = (const float *) tensor->data;
+        float * dst = result.data.data() + result.n_embd * (layer_idx - 1);  // layer 1 at [0]
+        for (int j = 0; j < result.n_embd; j++) {
+            dst[j] += src[j] * load_info.strength;  // allows multiple directions for same layer in same file
         }
+
     }
 
+    if (result.n_embd == -1) {
+        fprintf(stderr, "%s: skipping %s due to invalid direction tensors\n", __func__, load_info.fname.c_str());
+        result.data.clear();
+    }
+
+    gguf_free(ctx_gguf);
+    ggml_free(ctx);
+
     return result;
 }
 
@@ -2933,16 +2895,19 @@ llama_control_vector_data llama_control_vector_load(const std::vector
Date: Thu, 27 Jun 2024 18:37:29 +0300
Subject: [PATCH 044/326] flake.lock: Update (#8071)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Flake lock file updates:

• Updated input 'nixpkgs':
    'github:NixOS/nixpkgs/e9ee548d90ff586a6471b4ae80ae9cfcbceb3420?narHash=sha256-4Zu0RYRcAY/VWuu6awwq4opuiD//ahpc2aFHg2CWqFY%3D' (2024-06-13)
  → 'github:NixOS/nixpkgs/d603719ec6e294f034936c0d0dc06f689d91b6c3?narHash=sha256-k3JqJrkdoYwE3fHE6xGDY676AYmyh4U2Zw%2B0Bwe5DLU%3D' (2024-06-20)

Co-authored-by: github-actions[bot] 
Co-authored-by: Philip Taron 
---
 flake.lock | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/flake.lock b/flake.lock
index 5278fb68a3f98..79bb3f63fdc6d 100644
--- a/flake.lock
+++ b/flake.lock
@@ -20,11 +20,11 @@
     },
     "nixpkgs": {
       "locked": {
-        "lastModified": 1718318537,
-        "narHash": "sha256-4Zu0RYRcAY/VWuu6awwq4opuiD//ahpc2aFHg2CWqFY=",
+        "lastModified": 1718895438,
+        "narHash": "sha256-k3JqJrkdoYwE3fHE6xGDY676AYmyh4U2Zw+0Bwe5DLU=",
         "owner": "NixOS",
         "repo": "nixpkgs",
-        "rev": "e9ee548d90ff586a6471b4ae80ae9cfcbceb3420",
+        "rev": "d603719ec6e294f034936c0d0dc06f689d91b6c3",
         "type": "github"
       },
       "original": {

From 16791b8f0b4526aafbf5d0e5bbbd2e99c2253418 Mon Sep 17 00:00:00 2001
From: Xuan Son Nguyen 
Date: Thu, 27 Jun 2024 18:14:19 +0200
Subject: [PATCH 045/326] Add chatml fallback for cpp
 `llama_chat_apply_template` (#8160)

* add chatml fallback for cpp `llama_chat_apply_template`

* remove redundant code
---
 common/common.cpp | 19 ++++++++++++++++++-
 common/common.h   |  2 ++
 2 files changed, 20 insertions(+), 1 deletion(-)

diff --git a/common/common.cpp b/common/common.cpp
index 70349ad70891c..57d03a5789edd 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -2618,6 +2618,7 @@ std::string llama_chat_apply_template(const struct llama_model * model,
         const std::vector & msgs,
         bool add_ass) {
     int alloc_size = 0;
+    bool fallback = false; // indicate if we must fallback to default chatml
     std::vector chat;
     for (auto & msg : msgs) {
         chat.push_back({msg.role.c_str(), msg.content.c_str()});
@@ -2630,10 +2631,26 @@ std::string llama_chat_apply_template(const struct llama_model * model,
     // run the first time to get the total output length
     int32_t res = llama_chat_apply_template(model, ptr_tmpl, chat.data(), chat.size(), add_ass, buf.data(), buf.size());
 
+    // error: chat template is not supported
+    if (res < 0) {
+        if (ptr_tmpl != nullptr) {
+            // if the custom "tmpl" is not supported, we throw an error
+            // this is a bit redundant (for good), since we're not sure if user validated the custom template with llama_chat_verify_template()
+            throw std::runtime_error("this custom template is not supported");
+        } else {
+            // If the built-in template is not supported, we default to chatml
+            res = llama_chat_apply_template(nullptr, "chatml", chat.data(), chat.size(), add_ass, buf.data(), buf.size());
+            fallback = true;
+        }
+    }
+
     // if it turns out that our buffer is too small, we resize it
     if ((size_t) res > buf.size()) {
         buf.resize(res);
-        res = llama_chat_apply_template(model, ptr_tmpl, chat.data(), chat.size(), add_ass, buf.data(), buf.size());
+        res = llama_chat_apply_template(
+            fallback ? nullptr : model,
+            fallback ? "chatml" : ptr_tmpl,
+            chat.data(), chat.size(), add_ass, buf.data(), buf.size());
     }
 
     std::string formatted_chat(buf.data(), res);
diff --git a/common/common.h b/common/common.h
index c541204f6743b..0486ba3800ed7 100644
--- a/common/common.h
+++ b/common/common.h
@@ -380,6 +380,8 @@ struct llama_chat_msg {
 bool llama_chat_verify_template(const std::string & tmpl);
 
 // CPP wrapper for llama_chat_apply_template
+// If the built-in template is not supported, we default to chatml
+// If the custom "tmpl" is not supported, we throw an error
 std::string llama_chat_apply_template(const struct llama_model * model,
         const std::string & tmpl,
         const std::vector & chat,

From 8172ee9da9921ca53d698c7438c2d792b3f3f2c8 Mon Sep 17 00:00:00 2001
From: slaren 
Date: Thu, 27 Jun 2024 20:04:39 +0200
Subject: [PATCH 046/326] cmake : fix deprecated option names not working
 (#8171)

* cmake : fix deprecated option names not working

* remove LlAMA_OPENMP
---
 CMakeLists.txt | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/CMakeLists.txt b/CMakeLists.txt
index 7a7197282f946..dba08308967b7 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -86,7 +86,7 @@ set(GGML_CUDA_USE_GRAPHS    ON)
 function (llama_option_depr TYPE OLD NEW)
     if (${OLD})
         message(${TYPE} "${OLD} is deprecated and will be removed in the future.\nUse ${NEW} instead\n")
-        set(${NEW} ON)
+        set(${NEW} ON PARENT_SCOPE)
     endif()
 endfunction()
 
@@ -96,7 +96,6 @@ llama_option_depr(WARNING     LLAMA_KOMPUTE             GGML_KOMPUTE)
 llama_option_depr(WARNING     LLAMA_METAL               GGML_METAL)
 llama_option_depr(WARNING     LLAMA_METAL_EMBED_LIBRARY GGML_METAL_EMBED_LIBRARY)
 llama_option_depr(WARNING     LLAMA_NATIVE              GGML_NATIVE)
-llama_option_depr(WARNING     LLAMA_OPENMP              GGML_OPENMP)
 llama_option_depr(WARNING     LLAMA_RPC                 GGML_RPC)
 llama_option_depr(WARNING     LLAMA_SYCL                GGML_SYCL)
 llama_option_depr(WARNING     LLAMA_SYCL_F16            GGML_SYCL_F16)

From 558f44bf83d78242d4e5c4ab98d0be9125cb9780 Mon Sep 17 00:00:00 2001
From: loonerin <132926317+loonerin@users.noreply.github.com>
Date: Thu, 27 Jun 2024 15:01:23 -0400
Subject: [PATCH 047/326] CI: fix release build (Ubuntu+Mac) (#8170)

* CI: fix release build (Ubuntu)

PR #8006 changes defaults to build shared libs. However, CI for releases
expects static builds.

* CI: fix release build (Mac)

---------

Co-authored-by: loonerin 
---
 .github/workflows/build.yml | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 20851528726aa..adf67cecc7b2c 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -47,7 +47,7 @@ jobs:
           sysctl -a
           mkdir build
           cd build
-          cmake -DLLAMA_FATAL_WARNINGS=ON -DGGML_METAL_EMBED_LIBRARY=ON -DLLAMA_CURL=ON ..
+          cmake -DLLAMA_FATAL_WARNINGS=ON -DGGML_METAL_EMBED_LIBRARY=ON -DLLAMA_CURL=ON -DBUILD_SHARED_LIBS=OFF ..
           cmake --build . --config Release -j $(sysctl -n hw.logicalcpu)
 
       - name: Test
@@ -105,7 +105,7 @@ jobs:
           sysctl -a
           # Metal is disabled due to intermittent failures with Github runners not having a GPU:
           # https://github.com/ggerganov/llama.cpp/actions/runs/8635935781/job/23674807267#step:5:2313
-          cmake -B build -DLLAMA_FATAL_WARNINGS=ON -DGGML_METAL=OFF -DLLAMA_CURL=ON
+          cmake -B build -DLLAMA_FATAL_WARNINGS=ON -DGGML_METAL=OFF -DLLAMA_CURL=ON -DBUILD_SHARED_LIBS=OFF
           cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
 
       - name: Test
@@ -222,7 +222,7 @@ jobs:
         run: |
           mkdir build
           cd build
-          cmake .. -DLLAMA_FATAL_WARNINGS=ON -DLLAMA_CURL=ON
+          cmake .. -DLLAMA_FATAL_WARNINGS=ON -DLLAMA_CURL=ON -DBUILD_SHARED_LIBS=OFF
           cmake --build . --config Release -j $(nproc)
 
       - name: Test

From cb0b06a8a613f7a2ccb7253b2a3c00fdd397ba1c Mon Sep 17 00:00:00 2001
From: Olivier Chafik 
Date: Thu, 27 Jun 2024 22:08:42 +0100
Subject: [PATCH 048/326] `json`: update grammars/README w/ examples & note
 about additionalProperties (#8132)

* json: update grammars/README

* mention broken prefixItems

* add mention to llama-gbnf-validator

* json: explicit type: object for nested items object in cli example
---
 grammars/README.md | 245 +++++++++++++++++++++++++++++++++++++++++++--
 1 file changed, 235 insertions(+), 10 deletions(-)

diff --git a/grammars/README.md b/grammars/README.md
index 2f685eb6de004..40f66624021da 100644
--- a/grammars/README.md
+++ b/grammars/README.md
@@ -126,19 +126,244 @@ You can use GBNF grammars:
     - in CLI, with [examples/json_schema_to_grammar.py](../examples/json_schema_to_grammar.py)
     - in JavaScript with [json-schema-to-grammar.mjs](../examples/server/public/json-schema-to-grammar.mjs) (this is used by the [server](../examples/server)'s Web UI)
 
-Take a look at [tests](../../tests/test-json-schema-to-grammar.cpp) to see which features are likely supported (you'll also find usage examples in https://github.com/ggerganov/llama.cpp/pull/5978, https://github.com/ggerganov/llama.cpp/pull/6659 & https://github.com/ggerganov/llama.cpp/pull/6555).
+Take a look at [tests](../tests/test-json-schema-to-grammar.cpp) to see which features are likely supported (you'll also find usage examples in https://github.com/ggerganov/llama.cpp/pull/5978, https://github.com/ggerganov/llama.cpp/pull/6659 & https://github.com/ggerganov/llama.cpp/pull/6555).
+
+```bash
+llama-cli \
+  -hfr bartowski/Phi-3-medium-128k-instruct-GGUF \
+  -hff Phi-3-medium-128k-instruct-Q8_0.gguf \
+  -j '{
+    "type": "array",
+    "items": {
+        "type": "object",
+        "properties": {
+            "name": {
+                "type": "string",
+                "minLength": 1,
+                "maxLength": 100
+            },
+            "age": {
+                "type": "integer",
+                "minimum": 0,
+                "maximum": 150
+            }
+        },
+        "required": ["name", "age"],
+        "additionalProperties": false
+    },
+    "minItems": 10,
+    "maxItems": 100
+  }' \
+  -p 'Generate a {name, age}[] JSON array with famous actors of all ages.'
+```
+
+

+
+Show grammar
+
+You can convert any schema in command-line with:
+
+```bash
+examples/json_schema_to_grammar.py name-age-schema.json
+```
+
+```
+char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
+item ::= "{" space item-name-kv "," space item-age-kv "}" space
+item-age ::= ([0-9] | ([1-8] [0-9] | [9] [0-9]) | "1" ([0-4] [0-9] | [5] "0")) space
+item-age-kv ::= "\"age\"" space ":" space item-age
+item-name ::= "\"" char{1,100} "\"" space
+item-name-kv ::= "\"name\"" space ":" space item-name
+root ::= "[" space item ("," space item){9,99} "]" space
+space ::= | " " | "\n" [ \t]{0,20}
+```
+
+

+
+Here is also a list of known limitations (contributions welcome):
+
+- Unsupported features are skipped silently. It is currently advised to use the command-line Python converter (see above) to see any warnings, and to inspect the resulting grammar / test it w/ [llama-gbnf-validator](../examples/gbnf-validator/gbnf-validator.cpp).
+- Can't mix `properties` w/ `anyOf` / `oneOf` in the same type (https://github.com/ggerganov/llama.cpp/issues/7703)
+- [prefixItems](https://json-schema.org/draft/2020-12/json-schema-core#name-prefixitems) is broken (but [items](https://json-schema.org/draft/2020-12/json-schema-core#name-items) works)
+- `minimum`, `exclusiveMinimum`, `maximum`, `exclusiveMaximum`: only supported for `"type": "integer"` for now, not `number`
+- Nested `$ref`s are broken (https://github.com/ggerganov/llama.cpp/issues/8073)
+- [pattern](https://json-schema.org/draft/2020-12/json-schema-validation#name-pattern)s must start with `^` and end with `$`
+- Remote `$ref`s not supported in the C++ version (Python & JavaScript versions fetch https refs)
+- `string` [formats](https://json-schema.org/draft/2020-12/json-schema-validation#name-defined-formats) lack `uri`, `email`
+- No [`patternProperties`](https://json-schema.org/draft/2020-12/json-schema-core#name-patternproperties)
 
-Here is also a non-exhaustive list of **unsupported** features:
+And a non-exhaustive list of other unsupported features that are unlikely to be implemented (hard and/or too slow to support w/ stateless grammars):
 
-- `additionalProperties`: to be fixed in https://github.com/ggerganov/llama.cpp/pull/7840
-- `minimum`, `exclusiveMinimum`, `maximum`, `exclusiveMaximum`
-    - `integer` constraints to be implemented in https://github.com/ggerganov/llama.cpp/pull/7797
-- Remote `$ref`s in the C++ version (Python & JavaScript versions fetch https refs)
-- Mixing `properties` w/ `anyOf` / `oneOf` in the same type (https://github.com/ggerganov/llama.cpp/issues/7703)
-- `string` formats `uri`, `email`
+- [`uniqueItems`](https://json-schema.org/draft/2020-12/json-schema-validation#name-uniqueitems)
 - [`contains`](https://json-schema.org/draft/2020-12/json-schema-core#name-contains) / `minContains`
-- `uniqueItems`
 - `$anchor` (cf. [dereferencing](https://json-schema.org/draft/2020-12/json-schema-core#name-dereferencing))
 - [`not`](https://json-schema.org/draft/2020-12/json-schema-core#name-not)
 - [Conditionals](https://json-schema.org/draft/2020-12/json-schema-core#name-keywords-for-applying-subsche) `if` / `then` / `else` / `dependentSchemas`
-- [`patternProperties`](https://json-schema.org/draft/2020-12/json-schema-core#name-patternproperties)
+
+### A word about additionalProperties
+
+> [!WARNING]
+> By default, `object`s accept [additional properties](https://json-schema.org/understanding-json-schema/reference/object#additionalproperties), which you might not want / not expect, and which will make sampling slower (not just because of the extra tokens, but also generates a slower grammar).
+> You can set `"additionalProperties": false` on the schema of any object to ensure only properties listed in `properties` are generated (not needed for non-`object` types, e.g. `array` or `string`).
+
+If you're using [Pydantic](https://pydantic.dev/) to generate schemas, you can disable additional properties with the `extra` config on each model class:
+
+```python
+# pip install pydantic
+import json
+from typing import Annotated, List
+from pydantic import BaseModel, Extra, Field
+class QAPair(BaseModel):
+    class Config:
+        extra = 'forbid'  # triggers additionalProperties: false in the JSON schema
+    question: str
+    concise_answer: str
+    justification: str
+
+class Summary(BaseModel):
+    class Config:
+        extra = 'forbid'
+    key_facts: List[Annotated[str, Field(pattern='- .{5,}')]]
+    question_answers: List[Annotated[List[QAPair], Field(min_items=5)]]
+
+print(json.dumps(Summary.model_json_schema(), indent=2))
+```
+
+

+Show JSON schema & grammar
+
+```json
+{
+  "$defs": {
+    "QAPair": {
+      "additionalProperties": false,
+      "properties": {
+        "question": {
+          "title": "Question",
+          "type": "string"
+        },
+        "concise_answer": {
+          "title": "Concise Answer",
+          "type": "string"
+        },
+        "justification": {
+          "title": "Justification",
+          "type": "string"
+        }
+      },
+      "required": [
+        "question",
+        "concise_answer",
+        "justification"
+      ],
+      "title": "QAPair",
+      "type": "object"
+    }
+  },
+  "additionalProperties": false,
+  "properties": {
+    "key_facts": {
+      "items": {
+        "pattern": "^- .{5,}$",
+        "type": "string"
+      },
+      "title": "Key Facts",
+      "type": "array"
+    },
+    "question_answers": {
+      "items": {
+        "items": {
+          "$ref": "#/$defs/QAPair"
+        },
+        "minItems": 5,
+        "type": "array"
+      },
+      "title": "Question Answers",
+      "type": "array"
+    }
+  },
+  "required": [
+    "key_facts",
+    "question_answers"
+  ],
+  "title": "Summary",
+  "type": "object"
+}
+```
+
+```
+QAPair ::= "{" space QAPair-question-kv "," space QAPair-concise-answer-kv "," space QAPair-justification-kv "}" space
+QAPair-concise-answer-kv ::= "\"concise_answer\"" space ":" space string
+QAPair-justification-kv ::= "\"justification\"" space ":" space string
+QAPair-question-kv ::= "\"question\"" space ":" space string
+char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
+dot ::= [^\x0A\x0D]
+key-facts ::= "[" space (key-facts-item ("," space key-facts-item)*)? "]" space
+key-facts-item ::= "\"" "- " key-facts-item-1{5,} "\"" space
+key-facts-item-1 ::= dot
+key-facts-kv ::= "\"key_facts\"" space ":" space key-facts
+question-answers ::= "[" space (question-answers-item ("," space question-answers-item)*)? "]" space
+question-answers-item ::= "[" space question-answers-item-item ("," space question-answers-item-item){4,} "]" space
+question-answers-item-item ::= QAPair
+question-answers-kv ::= "\"question_answers\"" space ":" space question-answers
+root ::= "{" space key-facts-kv "," space question-answers-kv "}" space
+space ::= | " " | "\n" [ \t]{0,20}
+string ::= "\"" char* "\"" space
+```
+
+

+
+If you're using [Zod](https://zod.dev/), you can make your objects explicitly strict w/ `z.object(...).strict()` or `z.strictObject(...)`.
+
+Note however that [zod-to-json-schema](https://github.com/StefanTerdell/zod-to-json-schema) currently always seems to set `"additionalProperties": false` anyway (even w/ zod schemas on which `nonstrict()` / `passthrough()` was called).
+
+```js
+import { z } from 'zod';
+import { zodToJsonSchema } from 'zod-to-json-schema';
+
+const Foo = z.object({
+  age: z.number().positive(),
+  email: z.string().email(),
+}).strict();
+
+console.log(zodToJsonSchema(Foo));
+```
+
+

+Show JSON schema & grammar
+
+```json
+{
+  "type": "object",
+  "properties": {
+    "age": {
+      "type": "number",
+      "exclusiveMinimum": 0
+    },
+    "email": {
+      "type": "string",
+      "format": "email"
+    }
+  },
+  "required": [
+    "age",
+    "email"
+  ],
+  "additionalProperties": false,
+  "$schema": "http://json-schema.org/draft-07/schema#"
+}
+```
+
+```
+age-kv ::= "\"age\"" space ":" space number
+char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
+decimal-part ::= [0-9]{1,16}
+email-kv ::= "\"email\"" space ":" space string
+integral-part ::= [0] | [1-9] [0-9]{0,15}
+number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
+root ::= "{" space age-kv "," space email-kv "}" space
+space ::= | " " | "\n" [ \t]{0,20}
+string ::= "\"" char* "\"" space
+```
+
+


From a27aa50ab7e07fe46aae619076b6e31d5663e914 Mon Sep 17 00:00:00 2001
From: Xuan Son Nguyen 
Date: Fri, 28 Jun 2024 02:19:11 +0200
Subject: [PATCH 049/326] Add missing items in makefile (#8177)

---
 Makefile | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/Makefile b/Makefile
index bbfe0f12b228f..8ae4f1dc4ede3 100644
--- a/Makefile
+++ b/Makefile
@@ -45,6 +45,7 @@ BUILD_TARGETS = \
 TEST_TARGETS = \
 	tests/test-autorelease \
 	tests/test-backend-ops \
+	tests/test-chat-template \
 	tests/test-double-float \
 	tests/test-grad0 \
 	tests/test-grammar-integration \
@@ -1070,6 +1071,7 @@ clean:
 	rm -rvf src/*.o
 	rm -rvf tests/*.o
 	rm -rvf examples/*.o
+	rm -rvf common/*.o
 	rm -rvf *.a
 	rm -rvf *.dll
 	rm -rvf *.so

From e57dc62057d41211ac018056c19c02cd544694df Mon Sep 17 00:00:00 2001
From: pculliton 
Date: Fri, 28 Jun 2024 00:00:43 -0400
Subject: [PATCH 050/326] llama: Add support for Gemma2ForCausalLM (#8156)

* Inference support for Gemma 2 model family

* Update convert-hf-to-gguf.py, constants, and tensor mappings

* cleanup

* format fix

* Fix special token vocab bug

* Don't add space prefix

* fix deleted lines

* Update src/llama.cpp

Co-authored-by: slaren 

* Add model type names

* Add control vector

* Fix model type identification

---------

Co-authored-by: Andrei Betlen 
Co-authored-by: slaren 
---
 convert-hf-to-gguf.py          |  40 +++++++
 gguf-py/gguf/constants.py      |  23 ++++
 gguf-py/gguf/tensor_mapping.py |  14 +++
 src/llama.cpp                  | 198 ++++++++++++++++++++++++++++++++-
 4 files changed, 274 insertions(+), 1 deletion(-)

diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py
index 5bf69ef9fa060..5bcc849db999d 100755
--- a/convert-hf-to-gguf.py
+++ b/convert-hf-to-gguf.py
@@ -2340,6 +2340,46 @@ def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iter
         return [(self.map_tensor_name(name), data_torch)]
 
 
+@Model.register("Gemma2ForCausalLM")
+class Gemma2Model(Model):
+    model_arch = gguf.MODEL_ARCH.GEMMA2
+
+    def set_vocab(self):
+        self._set_vocab_llama_hf()
+        self.gguf_writer.add_add_space_prefix(False)
+
+    def set_gguf_parameters(self):
+        hparams = self.hparams
+        block_count = hparams["num_hidden_layers"]
+
+        self.gguf_writer.add_name(self.dir_model.name if self.model_name is None else self.model_name)
+        self.gguf_writer.add_context_length(hparams["max_position_embeddings"])
+        self.gguf_writer.add_embedding_length(hparams["hidden_size"])
+        self.gguf_writer.add_block_count(block_count)
+        self.gguf_writer.add_feed_forward_length(hparams["intermediate_size"])
+        self.gguf_writer.add_head_count(hparams["num_attention_heads"])
+        self.gguf_writer.add_head_count_kv(self.hparams["num_key_value_heads"] if "num_key_value_heads" in hparams else hparams["num_attention_heads"])
+        self.gguf_writer.add_layer_norm_rms_eps(self.hparams["rms_norm_eps"])
+        self.gguf_writer.add_key_length(hparams["head_dim"])
+        self.gguf_writer.add_value_length(hparams["head_dim"])
+        self.gguf_writer.add_file_type(self.ftype)
+
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        del bid  # unusem
+
+        # lm_head is not used in llama.cpp, while autoawq will include this tensor in model
+        # To prevent errors, skip loading lm_head.weight.
+        if name == "lm_head.weight":
+            logger.debug(f"Skipping get tensor {name!r} in safetensors so that convert can end normally.")
+            return []
+
+        # ref: https://github.com/huggingface/transformers/blob/fc37f38915372c15992b540dfcbbe00a916d4fc6/src/transformers/models/gemma/modeling_gemma.py#L89
+        if name.endswith("norm.weight"):
+            data_torch = data_torch + 1
+
+        return [(self.map_tensor_name(name), data_torch)]
+
+
 @Model.register("Starcoder2ForCausalLM")
 class StarCoder2Model(Model):
     model_arch = gguf.MODEL_ARCH.STARCODER2
diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py
index 222a2d137b08f..cf3d09e70d3e7 100644
--- a/gguf-py/gguf/constants.py
+++ b/gguf-py/gguf/constants.py
@@ -150,6 +150,7 @@ class MODEL_ARCH(IntEnum):
     INTERNLM2    = auto()
     MINICPM      = auto()
     GEMMA        = auto()
+    GEMMA2       = auto()
     STARCODER2   = auto()
     MAMBA        = auto()
     XVERSE       = auto()
@@ -180,10 +181,13 @@ class MODEL_TENSOR(IntEnum):
     ATTN_NORM            = auto()
     ATTN_NORM_2          = auto()
     ATTN_OUT_NORM        = auto()
+    ATTN_POST_NORM       = auto()
     ATTN_ROT_EMBD        = auto()
     FFN_GATE_INP         = auto()
     FFN_GATE_INP_SHEXP   = auto()
     FFN_NORM             = auto()
+    FFN_PRE_NORM         = auto()
+    FFN_POST_NORM        = auto()
     FFN_GATE             = auto()
     FFN_DOWN             = auto()
     FFN_UP               = auto()
@@ -270,6 +274,7 @@ class MODEL_TENSOR(IntEnum):
     MODEL_ARCH.INTERNLM2:      "internlm2",
     MODEL_ARCH.MINICPM:        "minicpm",
     MODEL_ARCH.GEMMA:          "gemma",
+    MODEL_ARCH.GEMMA2:         "gemma2",
     MODEL_ARCH.STARCODER2:     "starcoder2",
     MODEL_ARCH.MAMBA:          "mamba",
     MODEL_ARCH.XVERSE:         "xverse",
@@ -303,9 +308,12 @@ class MODEL_TENSOR(IntEnum):
     MODEL_TENSOR.ATTN_Q_NORM:          "blk.{bid}.attn_q_norm",
     MODEL_TENSOR.ATTN_K_NORM:          "blk.{bid}.attn_k_norm",
     MODEL_TENSOR.ATTN_OUT_NORM:        "blk.{bid}.attn_output_norm",
+    MODEL_TENSOR.ATTN_POST_NORM:       "blk.{bid}.post_attention_norm",
     MODEL_TENSOR.FFN_GATE_INP:         "blk.{bid}.ffn_gate_inp",
     MODEL_TENSOR.FFN_GATE_INP_SHEXP:   "blk.{bid}.ffn_gate_inp_shexp",
     MODEL_TENSOR.FFN_NORM:             "blk.{bid}.ffn_norm",
+    MODEL_TENSOR.FFN_PRE_NORM:         "blk.{bid}.ffn_norm",
+    MODEL_TENSOR.FFN_POST_NORM:        "blk.{bid}.post_ffw_norm",
     MODEL_TENSOR.FFN_GATE:             "blk.{bid}.ffn_gate",
     MODEL_TENSOR.FFN_DOWN:             "blk.{bid}.ffn_down",
     MODEL_TENSOR.FFN_UP:               "blk.{bid}.ffn_up",
@@ -751,6 +759,21 @@ class MODEL_TENSOR(IntEnum):
         MODEL_TENSOR.FFN_UP,
         MODEL_TENSOR.FFN_NORM,
     ],
+    MODEL_ARCH.GEMMA2: [
+        MODEL_TENSOR.TOKEN_EMBD,
+        MODEL_TENSOR.OUTPUT_NORM,
+        MODEL_TENSOR.ATTN_Q,
+        MODEL_TENSOR.ATTN_K,
+        MODEL_TENSOR.ATTN_V,
+        MODEL_TENSOR.ATTN_OUT,
+        MODEL_TENSOR.FFN_GATE,
+        MODEL_TENSOR.FFN_DOWN,
+        MODEL_TENSOR.FFN_UP,
+        MODEL_TENSOR.ATTN_NORM,
+        MODEL_TENSOR.ATTN_POST_NORM,
+        MODEL_TENSOR.FFN_PRE_NORM,
+        MODEL_TENSOR.FFN_POST_NORM,
+    ],
     MODEL_ARCH.STARCODER2: [
         MODEL_TENSOR.TOKEN_EMBD,
         MODEL_TENSOR.OUTPUT_NORM,
diff --git a/gguf-py/gguf/tensor_mapping.py b/gguf-py/gguf/tensor_mapping.py
index 7b047f241e088..0bed439397bcd 100644
--- a/gguf-py/gguf/tensor_mapping.py
+++ b/gguf-py/gguf/tensor_mapping.py
@@ -187,6 +187,10 @@ class TensorNameMap:
             "transformer.blocks.{bid}.norm_attn_norm.norm_2",  # dbrx
         ),
 
+        MODEL_TENSOR.ATTN_POST_NORM: (
+            "model.layers.{bid}.post_attention_layernorm",     # gemma2
+        ),
+
         # Rotary embeddings
         MODEL_TENSOR.ATTN_ROT_EMBD: (
             "model.layers.{bid}.self_attn.rotary_emb.inv_freq",        # llama-hf
@@ -210,6 +214,16 @@ class TensorNameMap:
             "transformer.decoder_layer.{bid}.rms_norm_2",                    # Grok
         ),
 
+        # Post feed-forward norm
+        MODEL_TENSOR.FFN_PRE_NORM: (
+            "model.layers.{bid}.pre_feedforward_layernorm", # gemma2
+        ),
+
+        # Post feed-forward norm
+        MODEL_TENSOR.FFN_POST_NORM: (
+            "model.layers.{bid}.post_feedforward_layernorm", # gemma2
+        ),
+
         MODEL_TENSOR.FFN_GATE_INP: (
             "layers.{bid}.feed_forward.gate",             # mixtral
             "model.layers.{bid}.block_sparse_moe.gate",   # mixtral
diff --git a/src/llama.cpp b/src/llama.cpp
index 3dc0f85351c50..988ed4fdfc55d 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -217,6 +217,7 @@ enum llm_arch {
     LLM_ARCH_INTERNLM2,
     LLM_ARCH_MINICPM,
     LLM_ARCH_GEMMA,
+    LLM_ARCH_GEMMA2,
     LLM_ARCH_STARCODER2,
     LLM_ARCH_MAMBA,
     LLM_ARCH_XVERSE,
@@ -257,6 +258,7 @@ static const std::map LLM_ARCH_NAMES = {
     { LLM_ARCH_INTERNLM2,       "internlm2"    },
     { LLM_ARCH_MINICPM,         "minicpm"      },
     { LLM_ARCH_GEMMA,           "gemma"        },
+    { LLM_ARCH_GEMMA2,          "gemma2"       },
     { LLM_ARCH_STARCODER2,      "starcoder2"   },
     { LLM_ARCH_MAMBA,           "mamba"        },
     { LLM_ARCH_XVERSE,          "xverse"       },
@@ -478,10 +480,12 @@ enum llm_tensor {
     LLM_TENSOR_ATTN_NORM,
     LLM_TENSOR_ATTN_NORM_2,
     LLM_TENSOR_ATTN_OUT_NORM,
+    LLM_TENSOR_ATTN_POST_NORM,
     LLM_TENSOR_ATTN_ROT_EMBD,
     LLM_TENSOR_FFN_GATE_INP,
     LLM_TENSOR_FFN_GATE_INP_SHEXP,
     LLM_TENSOR_FFN_NORM,
+    LLM_TENSOR_FFN_POST_NORM,
     LLM_TENSOR_FFN_GATE,
     LLM_TENSOR_FFN_DOWN,
     LLM_TENSOR_FFN_UP,
@@ -1004,6 +1008,24 @@ static const std::map> LLM_TENSOR_NA
             { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
         },
     },
+    {
+        LLM_ARCH_GEMMA2,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,      "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM,     "output_norm" },
+            { LLM_TENSOR_ATTN_NORM,       "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_Q,          "blk.%d.attn_q" },
+            { LLM_TENSOR_ATTN_K,          "blk.%d.attn_k" },
+            { LLM_TENSOR_ATTN_V,          "blk.%d.attn_v" },
+            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output" },
+            { LLM_TENSOR_ATTN_POST_NORM,  "blk.%d.post_attention_norm" },
+            { LLM_TENSOR_FFN_NORM,        "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_GATE,        "blk.%d.ffn_gate" },
+            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
+            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
+            { LLM_TENSOR_FFN_POST_NORM,   "blk.%d.post_ffw_norm" },
+        },
+    },
     {
         LLM_ARCH_STARCODER2,
         {
@@ -2039,6 +2061,8 @@ enum e_model {
     MODEL_16x12B,
     MODEL_10B_128x3_66B,
     MODEL_57B_A14B,
+    MODEL_9B,
+    MODEL_27B,
 };
 
 static const size_t kiB = 1024;
@@ -2215,6 +2239,7 @@ struct llama_layer {
     struct ggml_tensor * attn_q_a_norm;
     struct ggml_tensor * attn_kv_a_norm;
     struct ggml_tensor * attn_sub_norm;
+    struct ggml_tensor * attn_post_norm;
     struct ggml_tensor * ffn_sub_norm;
 
     // attention
@@ -2238,6 +2263,7 @@ struct llama_layer {
     // normalization
     struct ggml_tensor * ffn_norm;
     struct ggml_tensor * ffn_norm_b;
+    struct ggml_tensor * ffn_post_norm;
     struct ggml_tensor * layer_out_norm;
     struct ggml_tensor * layer_out_norm_b;
     struct ggml_tensor * ffn_norm_exps;
@@ -4269,6 +4295,8 @@ static const char * llama_model_type_name(e_model type) {
         case MODEL_16x12B:        return "16x12B";
         case MODEL_10B_128x3_66B: return "10B+128x3.66B";
         case MODEL_57B_A14B:      return "57B.A14B";
+        case MODEL_9B:            return "9B";
+        case MODEL_27B:           return "27B";
         default:                  return "?B";
     }
 }
@@ -4671,6 +4699,16 @@ static void llm_load_hparams(
                     default: model.type = e_model::MODEL_UNKNOWN;
                }
             } break;
+        case LLM_ARCH_GEMMA2:
+            {
+                ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
+
+                switch (hparams.n_layer) {
+                    case 42: model.type = e_model::MODEL_9B; break;
+                    case 46: model.type = e_model::MODEL_27B; break;
+                    default: model.type = e_model::MODEL_UNKNOWN;
+               }
+            } break;
         case LLM_ARCH_STARCODER2:
             {
                 ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps);
@@ -6512,6 +6550,40 @@ static bool llm_load_tensors(
                         layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {  n_ff, n_embd});
                     }
                 } break;
+            case LLM_ARCH_GEMMA2:
+                {
+                    model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
+
+                    // output
+                    model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
+                    model.output      = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD,  "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED); // same as tok_embd, duplicated to allow offloading
+
+                    const int64_t n_ff          = hparams.n_ff;
+                    const int64_t n_embd_head_k = hparams.n_embd_head_k;
+                    const int64_t n_embd_k_gqa  = hparams.n_embd_k_gqa();
+                    const int64_t n_embd_v_gqa  = hparams.n_embd_v_gqa();
+
+                    for (uint32_t i = 0; i < n_layer; ++i) {
+                        ggml_context * ctx_layer = ctx_for_layer(i);
+                        ggml_context * ctx_split = ctx_for_layer_split(i);
+
+                        auto & layer = model.layers[i];
+
+                        layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
+
+                        layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd_head_k * hparams.n_head});
+                        layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K,   "weight", i), {n_embd, n_embd_k_gqa});
+                        layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V,   "weight", i), {n_embd, n_embd_v_gqa});
+                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd_head_k * hparams.n_head, n_embd});
+                        layer.attn_post_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_POST_NORM, "weight", i), {n_embd});
+
+                        layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
+                        layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd,   n_ff});
+                        layer.ffn_up   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd,   n_ff});
+                        layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {  n_ff, n_embd});
+                        layer.ffn_post_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_POST_NORM, "weight", i), {n_embd});
+                    }
+                } break;
             case LLM_ARCH_STARCODER2:
                 {
                     model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
@@ -10923,6 +10995,125 @@ struct llm_build_context {
         return gf;
     }
 
+    struct ggml_cgraph * build_gemma2() {
+        struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
+
+        const int64_t n_embd_head_k = hparams.n_embd_head_k;
+
+        struct ggml_tensor * cur;
+        struct ggml_tensor * inpL;
+
+        inpL = llm_build_inp_embd(ctx0, lctx, hparams, batch, model.tok_embd, cb);
+
+        inpL = ggml_scale(ctx0, inpL, sqrtf(n_embd));
+        cb(inpL, "inp_scaled", -1);
+
+        // inp_pos - contains the positions
+        struct ggml_tensor * inp_pos = build_inp_pos();
+
+        // KQ_mask (mask for 1 head, it will be broadcasted to all heads)
+        struct ggml_tensor * KQ_mask = build_inp_KQ_mask();
+
+        for (int il = 0; il < n_layer; ++il) {
+            // norm
+            cur = llm_build_norm(ctx0, inpL, hparams,
+                    model.layers[il].attn_norm, NULL,
+                    LLM_NORM_RMS, cb, il);
+            cb(cur, "attn_norm", il);
+
+            // self-attention
+            {
+                // compute Q and K and RoPE them
+                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                cb(Qcur, "Qcur", il);
+
+                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                cb(Kcur, "Kcur", il);
+
+                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                cb(Vcur, "Vcur", il);
+
+                Qcur = ggml_rope_ext(
+                        ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head_k, n_head,    n_tokens), inp_pos, nullptr,
+                        n_embd_head_k, rope_type, n_ctx_orig, freq_base, freq_scale,
+                        ext_factor, attn_factor, beta_fast, beta_slow);
+                cb(Qcur, "Qcur", il);
+
+                Qcur = ggml_scale(ctx0, Qcur, 1.0f / sqrtf(float(n_embd_head_k)));
+                cb(Qcur, "Qcur_scaled", il);
+
+                Kcur = ggml_rope_ext(
+                        ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head_k, n_head_kv, n_tokens), inp_pos, nullptr,
+                        n_embd_head_k, rope_type, n_ctx_orig, freq_base, freq_scale,
+                        ext_factor, attn_factor, beta_fast, beta_slow);
+                cb(Kcur, "Kcur", il);
+
+                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                        model.layers[il].wo, NULL,
+                        Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f, cb, il);
+            }
+
+            cur = llm_build_norm(ctx0, cur, hparams,
+                    model.layers[il].attn_post_norm, NULL,
+                    LLM_NORM_RMS, cb, il);
+            cb(cur, "attn_post_norm", il);
+
+            if (il == n_layer - 1) {
+                // skip computing output for unused tokens
+                struct ggml_tensor * inp_out_ids = build_inp_out_ids();
+                cur  = ggml_get_rows(ctx0,  cur, inp_out_ids);
+                inpL = ggml_get_rows(ctx0, inpL, inp_out_ids);
+            }
+
+            struct ggml_tensor * sa_out = ggml_add(ctx0, cur, inpL);
+            cb(sa_out, "sa_out", il);
+
+            cur = llm_build_norm(ctx0, sa_out, hparams,
+                    model.layers[il].ffn_norm, NULL,
+                    LLM_NORM_RMS, cb, il);
+            cb(cur, "ffn_norm", il);
+
+            // feed-forward network
+            {
+                cur = llm_build_ffn(ctx0, cur,
+                        model.layers[il].ffn_up,   NULL, NULL,
+                        model.layers[il].ffn_gate, NULL, NULL,
+                        model.layers[il].ffn_down, NULL, NULL,
+                        NULL,
+                        LLM_FFN_GELU, LLM_FFN_PAR, cb, il);
+                cb(cur, "ffn_out", il);
+            }
+
+            cur = llm_build_norm(ctx0, cur, hparams,
+                model.layers[il].ffn_post_norm, NULL,
+                LLM_NORM_RMS, cb, -1);
+            cb(cur, "ffn_post_norm", -1);
+
+            cur = ggml_add(ctx0, cur, sa_out);
+            cur = lctx.cvec.apply_to(ctx0, cur, il);
+            cb(cur, "l_out", il);
+
+            // input for next layer
+            inpL = cur;
+        }
+
+        cur = inpL;
+
+        cur = llm_build_norm(ctx0, cur, hparams,
+                model.output_norm, NULL,
+                LLM_NORM_RMS, cb, -1);
+        cb(cur, "result_norm", -1);
+
+        // lm_head
+        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cb(cur, "result_output", -1);
+
+        ggml_build_forward_expand(gf, cur);
+
+        return gf;
+    }
+
+
     struct ggml_cgraph * build_starcoder2() {
         struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
 
@@ -12303,6 +12494,10 @@ static struct ggml_cgraph * llama_build_graph(
             {
                 result = llm.build_gemma();
             } break;
+        case LLM_ARCH_GEMMA2:
+            {
+                result = llm.build_gemma2();
+            } break;
         case LLM_ARCH_STARCODER2:
             {
                 result = llm.build_starcoder2();
@@ -17597,6 +17792,7 @@ enum llama_rope_type llama_rope_type(const struct llama_model * model) {
         case LLM_ARCH_PHI2:
         case LLM_ARCH_PHI3:
         case LLM_ARCH_GEMMA:
+        case LLM_ARCH_GEMMA2:
         case LLM_ARCH_STARCODER2:
         case LLM_ARCH_GPTNEOX:
             return LLAMA_ROPE_TYPE_NEOX;
@@ -19486,7 +19682,7 @@ static int32_t llama_chat_apply_template_internal(
         if (add_ass) {
             ss << "assistant\n";
         }
-    } else if (tmpl == "gemma" || tmpl.find("") != std::string::npos) {
+    } else if (tmpl == "gemma" || tmpl == "gemma2" || tmpl.find("") != std::string::npos) {
         // google/gemma-7b-it
         std::string system_prompt = "";
         for (auto message : chat) {

From 139cc621e90b4f61830515c3c124cf35b3d7a6dc Mon Sep 17 00:00:00 2001
From: Olivier Chafik 
Date: Fri, 28 Jun 2024 09:26:45 +0100
Subject: [PATCH 051/326] `json`: restore default additionalProperties to
 false, fix some pattern escapes (#8180)

* json: expand ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS charset

* json: revert default of additionalProperties to false

* Update README.md
---
 common/json-schema-to-grammar.cpp             |  4 +-
 examples/json_schema_to_grammar.py            |  6 +--
 .../server/public/json-schema-to-grammar.mjs  |  4 +-
 grammars/README.md                            | 37 ++++++++++++------
 tests/test-grammar-integration.cpp            | 39 ++++++++++++++++++-
 tests/test-json-schema-to-grammar.cpp         | 31 ++-------------
 6 files changed, 73 insertions(+), 48 deletions(-)

diff --git a/common/json-schema-to-grammar.cpp b/common/json-schema-to-grammar.cpp
index 2f233e2e7477f..881eb49e3389e 100644
--- a/common/json-schema-to-grammar.cpp
+++ b/common/json-schema-to-grammar.cpp
@@ -316,7 +316,7 @@ std::unordered_map GRAMMAR_LITERAL_ESCAPES = {
 };
 
 std::unordered_set NON_LITERAL_SET = {'|', '.', '(', ')', '[', ']', '{', '}', '*', '+', '?'};
-std::unordered_set ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS = {'[', ']', '(', ')', '|', '{', '}', '*', '+', '?'};
+std::unordered_set ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS = {'^', '$', '.', '[', ']', '(', ')', '|', '{', '}', '*', '+', '?'};
 
 template 
 std::string join(Iterator begin, Iterator end, const std::string & separator) {
@@ -720,7 +720,7 @@ class SchemaConverter {
             }
             prop_names.push_back(prop_name);
         }
-        if (!(additional_properties.is_boolean() && !additional_properties.get())) {
+        if ((additional_properties.is_boolean() && additional_properties.get()) || additional_properties.is_object()) {
             std::string sub_name = name + (name.empty() ? "" : "-") + "additional";
             std::string value_rule =
                 additional_properties.is_object() ? visit(additional_properties, sub_name + "-value")
diff --git a/examples/json_schema_to_grammar.py b/examples/json_schema_to_grammar.py
index 92f6e3d47bae7..072a230f72408 100755
--- a/examples/json_schema_to_grammar.py
+++ b/examples/json_schema_to_grammar.py
@@ -231,7 +231,7 @@ def __init__(self, content: str, deps: list = None):
 GRAMMAR_LITERAL_ESCAPES = {'\r': '\\r', '\n': '\\n', '"': '\\"', '-': '\\-', ']': '\\]'}
 
 NON_LITERAL_SET = set('|.()[]{}*+?')
-ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS = set('[]()|{}*+?')
+ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS = set('^$.[]()|{}*+?')
 
 
 class SchemaConverter:
@@ -602,7 +602,7 @@ def add_component(comp_schema, is_required):
                 else:
                     add_component(t, is_required=True)
 
-            return self._add_rule(rule_name, self._build_object_rule(properties, required, hybrid_name, additional_properties=[]))
+            return self._add_rule(rule_name, self._build_object_rule(properties, required, hybrid_name, additional_properties=None))
 
         elif schema_type in (None, 'array') and ('items' in schema or 'prefixItems' in schema):
             items = schema.get('items') or schema['prefixItems']
@@ -691,7 +691,7 @@ def _build_object_rule(self, properties: List[Tuple[str, Any]], required: Set[st
         required_props = [k for k in sorted_props if k in required]
         optional_props = [k for k in sorted_props if k not in required]
 
-        if additional_properties != False:
+        if additional_properties is not None and additional_properties != False:
             sub_name = f'{name}{"-" if name else ""}additional'
             value_rule = self.visit(additional_properties, f'{sub_name}-value') if isinstance(additional_properties, dict) else \
                 self._add_primitive('value', PRIMITIVE_RULES['value'])
diff --git a/examples/server/public/json-schema-to-grammar.mjs b/examples/server/public/json-schema-to-grammar.mjs
index 06d76edde500a..7267f3f9c7fad 100644
--- a/examples/server/public/json-schema-to-grammar.mjs
+++ b/examples/server/public/json-schema-to-grammar.mjs
@@ -259,7 +259,7 @@ const GRAMMAR_RANGE_LITERAL_ESCAPE_RE = /[\n\r"\]\-\\]/g;
 const GRAMMAR_LITERAL_ESCAPES = { '\r': '\\r', '\n': '\\n', '"': '\\"', '-': '\\-', ']': '\\]' };
 
 const NON_LITERAL_SET = new Set('|.()[]{}*+?');
-const ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS = new Set('[]()|{}*+?');
+const ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS = new Set('^$.[]()|{}*+?');
 
 export class SchemaConverter {
   constructor(options) {
@@ -751,7 +751,7 @@ export class SchemaConverter {
     const requiredProps = sortedProps.filter(k => required.has(k));
     const optionalProps = sortedProps.filter(k => !required.has(k));
 
-    if (additionalProperties !== false) {
+    if (additionalProperties) {
       const subName = `${name ?? ''}${name ? '-' : ''}additional`;
       const valueRule =
         additionalProperties != null && typeof additionalProperties === 'object' ? this.visit(additionalProperties, `${subName}-value`)
diff --git a/grammars/README.md b/grammars/README.md
index 40f66624021da..886023f770218 100644
--- a/grammars/README.md
+++ b/grammars/README.md
@@ -182,6 +182,8 @@ space ::= | " " | "\n" [ \t]{0,20}
 
 Here is also a list of known limitations (contributions welcome):
 
+- `additionalProperties` defaults to `false` (produces faster grammars + reduces hallucinations).
+- `"additionalProperties": true` may produce keys that contain unescaped newlines.
 - Unsupported features are skipped silently. It is currently advised to use the command-line Python converter (see above) to see any warnings, and to inspect the resulting grammar / test it w/ [llama-gbnf-validator](../examples/gbnf-validator/gbnf-validator.cpp).
 - Can't mix `properties` w/ `anyOf` / `oneOf` in the same type (https://github.com/ggerganov/llama.cpp/issues/7703)
 - [prefixItems](https://json-schema.org/draft/2020-12/json-schema-core#name-prefixitems) is broken (but [items](https://json-schema.org/draft/2020-12/json-schema-core#name-items) works)
@@ -203,10 +205,11 @@ And a non-exhaustive list of other unsupported features that are unlikely to be
 ### A word about additionalProperties
 
 > [!WARNING]
-> By default, `object`s accept [additional properties](https://json-schema.org/understanding-json-schema/reference/object#additionalproperties), which you might not want / not expect, and which will make sampling slower (not just because of the extra tokens, but also generates a slower grammar).
-> You can set `"additionalProperties": false` on the schema of any object to ensure only properties listed in `properties` are generated (not needed for non-`object` types, e.g. `array` or `string`).
+> The JSON schemas spec states `object`s accept [additional properties](https://json-schema.org/understanding-json-schema/reference/object#additionalproperties) by default.
+> Since this is slow and seems prone to hallucinations, we default to no additional properties.
+> You can set `"additionalProperties": true` in the the schema of any object to explicitly allow additional properties.
 
-If you're using [Pydantic](https://pydantic.dev/) to generate schemas, you can disable additional properties with the `extra` config on each model class:
+If you're using [Pydantic](https://pydantic.dev/) to generate schemas, you can enable additional properties with the `extra` config on each model class:
 
 ```python
 # pip install pydantic
@@ -215,14 +218,14 @@ from typing import Annotated, List
 from pydantic import BaseModel, Extra, Field
 class QAPair(BaseModel):
     class Config:
-        extra = 'forbid'  # triggers additionalProperties: false in the JSON schema
+        extra = 'allow'  # triggers additionalProperties: true in the JSON schema
     question: str
     concise_answer: str
     justification: str
 
 class Summary(BaseModel):
     class Config:
-        extra = 'forbid'
+        extra = 'allow'
     key_facts: List[Annotated[str, Field(pattern='- .{5,}')]]
     question_answers: List[Annotated[List[QAPair], Field(min_items=5)]]
 
@@ -236,7 +239,7 @@ print(json.dumps(Summary.model_json_schema(), indent=2))
 {
   "$defs": {
     "QAPair": {
-      "additionalProperties": false,
+      "additionalProperties": true,
       "properties": {
         "question": {
           "title": "Question",
@@ -260,7 +263,7 @@ print(json.dumps(Summary.model_json_schema(), indent=2))
       "type": "object"
     }
   },
-  "additionalProperties": false,
+  "additionalProperties": true,
   "properties": {
     "key_facts": {
       "items": {
@@ -292,30 +295,40 @@ print(json.dumps(Summary.model_json_schema(), indent=2))
 ```
 
 ```
-QAPair ::= "{" space QAPair-question-kv "," space QAPair-concise-answer-kv "," space QAPair-justification-kv "}" space
+QAPair ::= "{" space QAPair-question-kv "," space QAPair-concise-answer-kv "," space QAPair-justification-kv ( "," space ( QAPair-additional-kv ( "," space QAPair-additional-kv )* ) )? "}" space
+QAPair-additional-k ::= ["] ( [c] ([o] ([n] ([c] ([i] ([s] ([e] ([_] ([a] ([n] ([s] ([w] ([e] ([r] char+ | [^"r] char*) | [^"e] char*) | [^"w] char*) | [^"s] char*) | [^"n] char*) | [^"a] char*) | [^"_] char*) | [^"e] char*) | [^"s] char*) | [^"i] char*) | [^"c] char*) | [^"n] char*) | [^"o] char*) | [j] ([u] ([s] ([t] ([i] ([f] ([i] ([c] ([a] ([t] ([i] ([o] ([n] char+ | [^"n] char*) | [^"o] char*) | [^"i] char*) | [^"t] char*) | [^"a] char*) | [^"c] char*) | [^"i] char*) | [^"f] char*) | [^"i] char*) | [^"t] char*) | [^"s] char*) | [^"u] char*) | [q] ([u] ([e] ([s] ([t] ([i] ([o] ([n] char+ | [^"n] char*) | [^"o] char*) | [^"i] char*) | [^"t] char*) | [^"s] char*) | [^"e] char*) | [^"u] char*) | [^"cjq] char* )? ["] space
+QAPair-additional-kv ::= QAPair-additional-k ":" space value
 QAPair-concise-answer-kv ::= "\"concise_answer\"" space ":" space string
 QAPair-justification-kv ::= "\"justification\"" space ":" space string
 QAPair-question-kv ::= "\"question\"" space ":" space string
+additional-k ::= ["] ( [k] ([e] ([y] ([_] ([f] ([a] ([c] ([t] ([s] char+ | [^"s] char*) | [^"t] char*) | [^"c] char*) | [^"a] char*) | [^"f] char*) | [^"_] char*) | [^"y] char*) | [^"e] char*) | [q] ([u] ([e] ([s] ([t] ([i] ([o] ([n] ([_] ([a] ([n] ([s] ([w] ([e] ([r] ([s] char+ | [^"s] char*) | [^"r] char*) | [^"e] char*) | [^"w] char*) | [^"s] char*) | [^"n] char*) | [^"a] char*) | [^"_] char*) | [^"n] char*) | [^"o] char*) | [^"i] char*) | [^"t] char*) | [^"s] char*) | [^"e] char*) | [^"u] char*) | [^"kq] char* )? ["] space
+additional-kv ::= additional-k ":" space value
+array ::= "[" space ( value ("," space value)* )? "]" space
+boolean ::= ("true" | "false") space
 char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
+decimal-part ::= [0-9]{1,16}
 dot ::= [^\x0A\x0D]
+integral-part ::= [0] | [1-9] [0-9]{0,15}
 key-facts ::= "[" space (key-facts-item ("," space key-facts-item)*)? "]" space
 key-facts-item ::= "\"" "- " key-facts-item-1{5,} "\"" space
 key-facts-item-1 ::= dot
 key-facts-kv ::= "\"key_facts\"" space ":" space key-facts
+null ::= "null" space
+number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
+object ::= "{" space ( string ":" space value ("," space string ":" space value)* )? "}" space
 question-answers ::= "[" space (question-answers-item ("," space question-answers-item)*)? "]" space
 question-answers-item ::= "[" space question-answers-item-item ("," space question-answers-item-item){4,} "]" space
 question-answers-item-item ::= QAPair
 question-answers-kv ::= "\"question_answers\"" space ":" space question-answers
-root ::= "{" space key-facts-kv "," space question-answers-kv "}" space
+root ::= "{" space key-facts-kv "," space question-answers-kv ( "," space ( additional-kv ( "," space additional-kv )* ) )? "}" space
 space ::= | " " | "\n" [ \t]{0,20}
 string ::= "\"" char* "\"" space
+value ::= object | array | string | number | boolean | null
 ```
 
 
 
-If you're using [Zod](https://zod.dev/), you can make your objects explicitly strict w/ `z.object(...).strict()` or `z.strictObject(...)`.
-
-Note however that [zod-to-json-schema](https://github.com/StefanTerdell/zod-to-json-schema) currently always seems to set `"additionalProperties": false` anyway (even w/ zod schemas on which `nonstrict()` / `passthrough()` was called).
+If you're using [Zod](https://zod.dev/), you can make your objects to explicitly allow extra properties w/ `nonstrict()` / `passthrough()` (or explicitly no extra props w/ `z.object(...).strict()` or `z.strictObject(...)`) but note that [zod-to-json-schema](https://github.com/StefanTerdell/zod-to-json-schema) currently always sets `"additionalProperties": false` anyway.
 
 ```js
 import { z } from 'zod';
diff --git a/tests/test-grammar-integration.cpp b/tests/test-grammar-integration.cpp
index 0e21dc7959943..975658f7953c9 100644
--- a/tests/test-grammar-integration.cpp
+++ b/tests/test-grammar-integration.cpp
@@ -993,6 +993,40 @@ static void test_json_schema() {
         }
     );
 
+    test_schema(
+        "simple pattern",
+        // Schema
+        R"""({
+            "pattern": "^[a-zA-Z0-9_-]*$"
+        })""",
+        // Passing strings
+        {
+            R"""("")""",
+            R"""("He_llo-12")""",
+        },
+        // Failing strings
+        {
+            R"""("!")""",
+            R"""("Hello World")""",
+        }
+    );
+
+    test_schema(
+        "pattern with escapes",
+        // Schema
+        R"""({
+            "pattern": "^a\\^\\$\\.\\[\\]\\(\\)\\|\\{\\}\\*\\+\\?b$"
+        })""",
+        // Passing strings
+        {
+            R"""("a^$.[]()|{}*+?b")""",
+        },
+        // Failing strings
+        {
+            R"""("ab")""",
+        }
+    );
+
     test_schema(
         "",
         // Schema
@@ -1062,8 +1096,6 @@ static void test_json_schema() {
             R"""({ "number": 1600, "street_name": "Pennsylvania" })""",
             // "By extension, even an empty object is valid"
             R"""({})""",
-            // "By default, providing additional properties is valid"
-            R"""({ "number": 1600, "street_name": "Pennsylvania", "street_type":"Avenue", "direction":"NW"})""",
             R"""({ "number": 1600, "street_name": "Pennsylvania", "street_type": "Avenue" })""",
         },
         // Failing strings
@@ -1074,6 +1106,9 @@ static void test_json_schema() {
             R"""({ "street_name": "Pennsylvania", "number": 1600 })""",
             // Reorder properties
             R"""({ "number": "1600", "street_name": "Pennsylvania", "street_type":"Avenue"})""",
+            // "Additional properties default to false for generation, even though the spec says true.
+            R"""({ "number": 1600, "street_name": "Pennsylvania", "street_type":"Avenue", "direction":"NW"})""",
+
         }
     );
 
diff --git a/tests/test-json-schema-to-grammar.cpp b/tests/test-json-schema-to-grammar.cpp
index 3aaa11833de57..720a949c73644 100755
--- a/tests/test-json-schema-to-grammar.cpp
+++ b/tests/test-json-schema-to-grammar.cpp
@@ -1120,28 +1120,15 @@ static void test_all(const std::string & lang, std::function
Date: Fri, 28 Jun 2024 12:37:45 +0200
Subject: [PATCH 052/326] cmake : allow user to override default options
 (#8178)

---
 CMakeLists.txt | 11 +++++++++--
 1 file changed, 9 insertions(+), 2 deletions(-)

diff --git a/CMakeLists.txt b/CMakeLists.txt
index dba08308967b7..e3a0cc369e364 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -79,8 +79,15 @@ set(GGML_SANITIZE_ADDRESS   ${LLAMA_SANITIZE_ADDRESS})
 set(GGML_SANITIZE_UNDEFINED ${LLAMA_SANITIZE_UNDEFINED})
 set(GGML_ALL_WARNINGS       ${LLAMA_ALL_WARNINGS})
 set(GGML_FATAL_WARNINGS     ${LLAMA_FATAL_WARNINGS})
-set(GGML_LLAMAFILE          ON)
-set(GGML_CUDA_USE_GRAPHS    ON)
+
+# change the default for these ggml options
+if (NOT DEFINED GGML_LLAMAFILE)
+    set(GGML_LLAMAFILE ON)
+endif()
+
+if (NOT DEFINED GGML_CUDA_USE_GRAPHS)
+    set(GGML_CUDA_USE_GRAPHS ON)
+endif()
 
 # transition helpers
 function (llama_option_depr TYPE OLD NEW)

From 38373cfbab5397cc2ab5c3694a3dee12a9e58f45 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Sigbj=C3=B8rn=20Skj=C3=A6ret?= 
Date: Fri, 28 Jun 2024 12:53:43 +0200
Subject: [PATCH 053/326] Add SPM infill support (#8016)

* add --spm-infill option

* support --spm-infill

* support --spm-infill
---
 common/common.cpp          |  6 ++++++
 common/common.h            |  2 ++
 examples/infill/README.md  |  1 +
 examples/infill/infill.cpp | 20 +++++++++++---------
 examples/server/README.md  |  1 +
 examples/server/server.cpp | 16 +++++++++++-----
 6 files changed, 32 insertions(+), 14 deletions(-)

diff --git a/common/common.cpp b/common/common.cpp
index 57d03a5789edd..6a00d25be1316 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -1026,6 +1026,10 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
         params.input_suffix = argv[i];
         return true;
     }
+    if (arg == "--spm-infill") {
+        params.spm_infill = true;
+        return true;
+    }
     if (arg == "--grammar") {
         CHECK_ARG
         sparams.grammar = argv[i];
@@ -1409,6 +1413,8 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
     options.push_back({ "main infill", "       --in-prefix-bos",        "prefix BOS to user inputs, preceding the `--in-prefix` string" });
     options.push_back({ "main infill", "       --in-prefix STRING",     "string to prefix user inputs with (default: empty)" });
     options.push_back({ "main infill", "       --in-suffix STRING",     "string to suffix after user inputs with (default: empty)" });
+    options.push_back({ "server infill",
+                                       "       --spm-infill",           "use Suffix/Prefix/Middle pattern for infill (instead of Prefix/Suffix/Middle) as some models prefer this. (default: %s)", params.spm_infill ? "enabled" : "disabled" });
 
     options.push_back({ "sampling" });
     options.push_back({ "*",           "       --samplers SAMPLERS",    "samplers that will be used for generation in the order, separated by \';\'\n"
diff --git a/common/common.h b/common/common.h
index 0486ba3800ed7..d6cb814b990e9 100644
--- a/common/common.h
+++ b/common/common.h
@@ -250,6 +250,8 @@ struct gpt_params {
     std::string cvector_outfile       = "control_vector.gguf";
     std::string cvector_positive_file = "examples/cvector-generator/positive.txt";
     std::string cvector_negative_file = "examples/cvector-generator/negative.txt";
+
+    bool spm_infill = false; // suffix/prefix/middle pattern for infill
 };
 
 void gpt_params_handle_model_default(gpt_params & params);
diff --git a/examples/infill/README.md b/examples/infill/README.md
index 74f42d2fc2696..810a0c5e76697 100644
--- a/examples/infill/README.md
+++ b/examples/infill/README.md
@@ -15,6 +15,7 @@ In this section, we cover the most commonly used options for running the `infill
 -   `-i, --interactive`: Run the program in interactive mode, allowing you to provide input directly and receive real-time responses.
 -   `-n N, --n-predict N`: Set the number of tokens to predict when generating text. Adjusting this value can influence the length of the generated text.
 -   `-c N, --ctx-size N`: Set the size of the prompt context. The default is 512, but LLaMA models were built with a context of 2048, which will provide better results for longer input/inference.
+-   `--spm-infill`: Use Suffix/Prefix/Middle pattern for infill (instead of Prefix/Suffix/Middle) as some models prefer this.
 
 ## Input Prompts
 
diff --git a/examples/infill/infill.cpp b/examples/infill/infill.cpp
index 3e82e4a81a20b..ca71dd687f30e 100644
--- a/examples/infill/infill.cpp
+++ b/examples/infill/infill.cpp
@@ -210,6 +210,7 @@ int main(int argc, char ** argv) {
         suff_rm_leading_spc = false;
     }
     std::vector embd_inp;
+    std::vector embd_end;
     std::vector inp_pfx = ::llama_tokenize(ctx, params.input_prefix, false);
     std::vector inp_sfx = ::llama_tokenize(ctx, params.input_suffix, false);
     const int space_token = 29871;
@@ -217,12 +218,13 @@ int main(int argc, char ** argv) {
         inp_sfx.erase(inp_sfx.begin());
     }
     inp_pfx.insert(inp_pfx.begin(), llama_token_prefix(model));
+    inp_sfx.insert(inp_sfx.begin(), llama_token_suffix(model));
+    embd_inp = params.spm_infill ? inp_sfx : inp_pfx;
+    embd_end = params.spm_infill ? inp_pfx : inp_sfx;
     if (add_bos) {
-        inp_pfx.insert(inp_pfx.begin(), llama_token_bos(model));
+        embd_inp.insert(embd_inp.begin(), llama_token_bos(model));
     }
-    inp_sfx.insert(inp_sfx.begin(), llama_token_suffix(model));
-    embd_inp = inp_pfx;
-    embd_inp.insert(embd_inp.end(), inp_sfx.begin(), inp_sfx.end());
+    embd_inp.insert(embd_inp.end(), embd_end.begin(), embd_end.end());
 
     const llama_token middle_token = llama_token_middle(model);
     if (middle_token >= 0) {
@@ -526,14 +528,14 @@ int main(int argc, char ** argv) {
                     inp_sfx.erase(inp_sfx.begin());
                 }
                 inp_pfx.insert(inp_pfx.begin(), llama_token_prefix(model));
+                inp_sfx.insert(inp_sfx.begin(), llama_token_suffix(model));
+                embd_inp = params.spm_infill ? inp_sfx : inp_pfx;
+                embd_end = params.spm_infill ? inp_pfx : inp_sfx;
                 if (add_bos) {
-                    inp_pfx.insert(inp_pfx.begin(), llama_token_bos(model));
+                    embd_inp.insert(embd_inp.begin(), llama_token_bos(model));
                 }
-                inp_sfx.insert(inp_sfx.begin(), llama_token_suffix(model));
-                embd_inp = inp_pfx;
-                embd_inp.insert(embd_inp.end(), inp_sfx.begin(), inp_sfx.end());
+                embd_inp.insert(embd_inp.end(), embd_end.begin(), embd_end.end());
 
-                const llama_token middle_token = llama_token_middle(model);
                 if (middle_token >= 0) {
                     embd_inp.push_back(middle_token);
                 }
diff --git a/examples/server/README.md b/examples/server/README.md
index e7fb0bf64c0e1..4fab006bb9a43 100644
--- a/examples/server/README.md
+++ b/examples/server/README.md
@@ -73,6 +73,7 @@ The project is under active development, and we are [looking for feedback and co
 - `-fa`, `--flash-attn` : enable flash attention (default: disabled).
 - `-ctk TYPE`, `--cache-type-k TYPE` : KV cache data type for K (default: `f16`, options `f32`, `f16`, `q8_0`, `q4_0`, `q4_1`, `iq4_nl`, `q5_0`, or `q5_1`)
 - `-ctv TYPE`, `--cache-type-v TYPE` : KV cache type for V (default `f16`, see `-ctk` for options)
+- `--spm-infill` : Use Suffix/Prefix/Middle pattern for infill (instead of Prefix/Suffix/Middle) as some models prefer this.
 
 **If compiled with `LLAMA_SERVER_SSL=ON`**
 - `--ssl-key-file FNAME`: path to file a PEM-encoded SSL private key
diff --git a/examples/server/server.cpp b/examples/server/server.cpp
index ae768097baa0e..d7fb61812aa3e 100644
--- a/examples/server/server.cpp
+++ b/examples/server/server.cpp
@@ -2020,6 +2020,7 @@ struct server_context {
                         slot.t_start_generation = 0;
 
                         if (slot.infill) {
+                            const bool add_bos = llama_should_add_bos_token(model);
                             bool suff_rm_leading_spc = true;
                             if (params.input_suffix.find_first_of(' ') == 0 && params.input_suffix.size() > 1) {
                                 params.input_suffix.erase(0, 1);
@@ -2035,16 +2036,21 @@ struct server_context {
                             }
 
                             prefix_tokens.insert(prefix_tokens.begin(), llama_token_prefix(model));
-                            prefix_tokens.insert(prefix_tokens.begin(), llama_token_bos(model)); // always add BOS
-                            prefix_tokens.insert(prefix_tokens.end(),   llama_token_suffix(model));
-                            prefix_tokens.insert(prefix_tokens.end(),   suffix_tokens.begin(), suffix_tokens.end());
+                            suffix_tokens.insert(suffix_tokens.begin(), llama_token_suffix(model));
+
+                            auto embd_inp = params.spm_infill ? suffix_tokens : prefix_tokens;
+                            auto embd_end = params.spm_infill ? prefix_tokens : suffix_tokens;
+                            if (add_bos) {
+                                embd_inp.insert(embd_inp.begin(), llama_token_bos(model));
+                            }
+                            embd_inp.insert(embd_inp.end(), embd_end.begin(), embd_end.end());
 
                             const llama_token middle_token = llama_token_middle(model);
                             if (middle_token >= 0) {
-                                prefix_tokens.push_back(middle_token);
+                                embd_inp.push_back(middle_token);
                             }
 
-                            prompt_tokens = prefix_tokens;
+                            prompt_tokens = embd_inp;
                         } else {
                             prompt_tokens = tokenize(slot.prompt, system_prompt.empty()); // add BOS if there isn't system prompt
                         }

From 26a39bbd6b0bbd66118bb68569f0276d7fe7df6c Mon Sep 17 00:00:00 2001
From: Xuan Son Nguyen 
Date: Fri, 28 Jun 2024 15:11:44 +0200
Subject: [PATCH 054/326] Add MiniCPM, Deepseek V2 chat template + clean up
 `llama_chat_apply_template_internal` (#8172)

* tmp_contains

* minicpm chat template

* add DeepSeek Lite template

* change deepseek-lite to deepseek2

* correct code comment

* correct code from master branch
---
 src/llama.cpp                | 64 ++++++++++++++++++++++++++----------
 tests/test-chat-template.cpp | 10 +++++-
 2 files changed, 56 insertions(+), 18 deletions(-)

diff --git a/src/llama.cpp b/src/llama.cpp
index 988ed4fdfc55d..3edaa98e8d01b 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -19613,7 +19613,10 @@ static int32_t llama_chat_apply_template_internal(
     std::string & dest, bool add_ass) {
     // Taken from the research: https://github.com/ggerganov/llama.cpp/issues/5527
     std::stringstream ss;
-    if (tmpl == "chatml" || tmpl.find("<|im_start|>") != std::string::npos) {
+    auto tmpl_contains = [&tmpl](std::string haystack) -> bool {
+        return tmpl.find(haystack) != std::string::npos;
+    };
+    if (tmpl == "chatml" || tmpl_contains("<|im_start|>")) {
         // chatml template
         for (auto message : chat) {
             ss << "<|im_start|>" << message->role << "\n" << message->content << "<|im_end|>\n";
@@ -19621,16 +19624,16 @@ static int32_t llama_chat_apply_template_internal(
         if (add_ass) {
             ss << "<|im_start|>assistant\n";
         }
-    } else if (tmpl == "llama2" || tmpl == "mistral" || tmpl.find("[INST]") != std::string::npos) {
+    } else if (tmpl == "llama2" || tmpl == "mistral" || tmpl_contains("[INST]")) {
         // llama2 template and its variants
         // [variant] support system message
-        bool support_system_message = tmpl.find("<>") != std::string::npos || tmpl == "mistral";
+        bool support_system_message = tmpl_contains("<>") || tmpl == "mistral";
         // [variant] space before + after response
-        bool space_around_response = tmpl.find("' ' + eos_token") != std::string::npos;
+        bool space_around_response = tmpl_contains("' ' + eos_token");
         // [variant] add BOS inside history
-        bool add_bos_inside_history = tmpl.find("bos_token + '[INST]") != std::string::npos;
+        bool add_bos_inside_history = tmpl_contains("bos_token + '[INST]");
         // [variant] trim spaces from the input message
-        bool strip_message = tmpl.find("content.strip()") != std::string::npos;
+        bool strip_message = tmpl_contains("content.strip()");
         // construct the prompt
         bool is_inside_turn = true; // skip BOS at the beginning
         ss << "[INST] ";
@@ -19656,7 +19659,7 @@ static int32_t llama_chat_apply_template_internal(
             }
         }
         // llama2 templates seem to not care about "add_generation_prompt"
-    } else if (tmpl == "phi3" || (tmpl.find("<|assistant|>") != std::string::npos && tmpl.find("<|end|>") != std::string::npos)) {
+    } else if (tmpl == "phi3" || (tmpl_contains("<|assistant|>") && tmpl_contains("<|end|>"))) {
         // Phi 3
         for (auto message : chat) {
             std::string role(message->role);
@@ -19665,7 +19668,7 @@ static int32_t llama_chat_apply_template_internal(
         if (add_ass) {
             ss << "<|assistant|>\n";
         }
-    } else if (tmpl == "zephyr" || tmpl.find("<|user|>") != std::string::npos) {
+    } else if (tmpl == "zephyr" || tmpl_contains("<|user|>")) {
         // zephyr template
         for (auto message : chat) {
             ss << "<|" << message->role << "|>" << "\n" << message->content << "<|endoftext|>\n";
@@ -19673,7 +19676,7 @@ static int32_t llama_chat_apply_template_internal(
         if (add_ass) {
             ss << "<|assistant|>\n";
         }
-    } else if (tmpl == "monarch" || tmpl.find("bos_token + message['role']") != std::string::npos) {
+    } else if (tmpl == "monarch" || tmpl_contains("bos_token + message['role']")) {
         // mlabonne/AlphaMonarch-7B template (the  is included inside history)
         for (auto message : chat) {
             std::string bos = (message == chat.front()) ? "" : ""; // skip BOS for first message
@@ -19682,7 +19685,7 @@ static int32_t llama_chat_apply_template_internal(
         if (add_ass) {
             ss << "assistant\n";
         }
-    } else if (tmpl == "gemma" || tmpl == "gemma2" || tmpl.find("") != std::string::npos) {
+    } else if (tmpl == "gemma" || tmpl == "gemma2" || tmpl_contains("")) {
         // google/gemma-7b-it
         std::string system_prompt = "";
         for (auto message : chat) {
@@ -19704,7 +19707,7 @@ static int32_t llama_chat_apply_template_internal(
         if (add_ass) {
             ss << "model\n";
         }
-    } else if (tmpl == "orion" || tmpl.find("'\\n\\nAssistant: ' + eos_token") != std::string::npos) {
+    } else if (tmpl == "orion" || tmpl_contains("'\\n\\nAssistant: ' + eos_token")) {
         // OrionStarAI/Orion-14B-Chat
         std::string system_prompt = "";
         for (auto message : chat) {
@@ -19724,7 +19727,7 @@ static int32_t llama_chat_apply_template_internal(
                 ss << message->content << "";
             }
         }
-    } else if (tmpl == "openchat" || tmpl.find("GPT4 Correct ") != std::string::npos) {
+    } else if (tmpl == "openchat" || tmpl_contains("GPT4 Correct ")) {
         // openchat/openchat-3.5-0106,
         for (auto message : chat) {
             std::string role(message->role);
@@ -19738,13 +19741,13 @@ static int32_t llama_chat_apply_template_internal(
         if (add_ass) {
             ss << "GPT4 Correct Assistant:";
         }
-    } else if (tmpl == "vicuna" || tmpl == "vicuna-orca" || (tmpl.find("USER: ") != std::string::npos && tmpl.find("ASSISTANT: ") != std::string::npos)) {
+    } else if (tmpl == "vicuna" || tmpl == "vicuna-orca" || (tmpl_contains("USER: ") && tmpl_contains("ASSISTANT: "))) {
         // eachadea/vicuna-13b-1.1 (and Orca variant)
         for (auto message : chat) {
             std::string role(message->role);
             if (role == "system") {
                 // Orca-Vicuna variant uses a system prefix
-                if (tmpl == "vicuna-orca" || tmpl.find("SYSTEM: ") != std::string::npos) {
+                if (tmpl == "vicuna-orca" || tmpl_contains("SYSTEM: ")) {
                     ss << "SYSTEM: " << message->content << "\n";
                 } else {
                     ss << message->content << "\n\n";
@@ -19758,7 +19761,7 @@ static int32_t llama_chat_apply_template_internal(
         if (add_ass) {
             ss << "ASSISTANT:";
         }
-    } else if (tmpl == "deepseek" || (tmpl.find("### Instruction:") != std::string::npos && tmpl.find("<|EOT|>") != std::string::npos)) {
+    } else if (tmpl == "deepseek" || (tmpl_contains("### Instruction:") && tmpl_contains("<|EOT|>"))) {
         // deepseek-ai/deepseek-coder-33b-instruct
         for (auto message : chat) {
             std::string role(message->role);
@@ -19773,7 +19776,7 @@ static int32_t llama_chat_apply_template_internal(
         if (add_ass) {
             ss << "### Response:\n";
         }
-    } else if (tmpl == "command-r" || (tmpl.find("<|START_OF_TURN_TOKEN|>") != std::string::npos && tmpl.find("<|USER_TOKEN|>") != std::string::npos)) {
+    } else if (tmpl == "command-r" || (tmpl_contains("<|START_OF_TURN_TOKEN|>") && tmpl_contains("<|USER_TOKEN|>"))) {
         // CohereForAI/c4ai-command-r-plus
         for (auto message : chat) {
             std::string role(message->role);
@@ -19788,7 +19791,7 @@ static int32_t llama_chat_apply_template_internal(
         if (add_ass) {
             ss << "<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>";
         }
-    } else if (tmpl == "llama3" || (tmpl.find("<|start_header_id|>") != std::string::npos && tmpl.find("<|end_header_id|>") != std::string::npos)) {
+    } else if (tmpl == "llama3" || (tmpl_contains("<|start_header_id|>") && tmpl_contains("<|end_header_id|>"))) {
         // Llama 3
         for (auto message : chat) {
             std::string role(message->role);
@@ -19797,6 +19800,33 @@ static int32_t llama_chat_apply_template_internal(
         if (add_ass) {
             ss << "<|start_header_id|>assistant<|end_header_id|>\n\n";
         }
+    } else if (tmpl == "minicpm" || tmpl_contains(u8"<用户>")) {
+        // MiniCPM-3B-OpenHermes-2.5-v2-GGUF
+        for (auto message : chat) {
+            std::string role(message->role);
+            if (role == "user") {
+                ss << u8"<用户>";
+                ss << trim(message->content);
+                ss << "";
+            } else {
+                ss << trim(message->content);
+            }
+        }
+    } else if (tmpl == "deepseek2" || tmpl_contains("'Assistant: ' + message['content'] + eos_token")) {
+        // DeepSeek-V2
+        for (auto message : chat) {
+            std::string role(message->role);
+            if (role == "system") {
+                ss << message->content << "\n\n";
+            } else if (role == "user") {
+                ss << "User: " << message->content << "\n\n";
+            } else if (role == "assistant") {
+                ss << "Assistant: " << message->content << u8"<｜end▁of▁sentence｜>";
+            }
+        }
+        if (add_ass) {
+            ss << "Assistant:";
+        }
     } else {
         // template not supported
         return -1;
diff --git a/tests/test-chat-template.cpp b/tests/test-chat-template.cpp
index d19ba8633e8c2..b154038b2d5c0 100644
--- a/tests/test-chat-template.cpp
+++ b/tests/test-chat-template.cpp
@@ -57,7 +57,11 @@ int main(void) {
         //Phi-3-medium
         "{% for message in messages %}{% if (message['role'] == 'user') %}{{'<|user|>' + '\n' + message['content'] + '<|end|>' + '\n' + '<|assistant|>' + '\n'}}{% elif (message['role'] == 'assistant') %}{{message['content'] + '<|end|>' + '\n'}}{% endif %}{% endfor %}",
         //Phi-3-vision
-        "{% for message in messages %}{{'<|' + message['role'] + '|>' + '\n' + message['content'] + '<|end|>\n' }}{% endfor %}{% if add_generation_prompt and messages[-1]['role'] != 'assistant' %}{{- '<|assistant|>\n' -}}{% endif %}"
+        "{% for message in messages %}{{'<|' + message['role'] + '|>' + '\n' + message['content'] + '<|end|>\n' }}{% endfor %}{% if add_generation_prompt and messages[-1]['role'] != 'assistant' %}{{- '<|assistant|>\n' -}}{% endif %}",
+        // MiniCPM-3B-OpenHermes-2.5-v2-GGUF
+        u8"{% for message in messages %}{% if message['role'] == 'user' %}{{'<用户>' + message['content'].strip() + ''}}{% else %}{{message['content'].strip()}}{% endif %}{% endfor %}",
+        // DeepSeek-V2
+        "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{{ bos_token }}{% for message in messages %}{% if message['role'] == 'user' %}{{ 'User: ' + message['content'] + '\n\n' }}{% elif message['role'] == 'assistant' %}{{ 'Assistant: ' + message['content'] + eos_token }}{% elif message['role'] == 'system' %}{{ message['content'] + '\n\n' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ 'Assistant:' }}{% endif %}",
     };
     std::vector expected_output = {
         // teknium/OpenHermes-2.5-Mistral-7B
@@ -94,6 +98,10 @@ int main(void) {
         "<|system|>\nYou are a helpful assistant<|end|>\n<|user|>\nHello<|end|>\n<|assistant|>\nHi there<|end|>\n<|user|>\nWho are you<|end|>\n<|assistant|>\n   I am an assistant   <|end|>\n<|user|>\nAnother question<|end|>\n<|assistant|>\n",
         //Phi-3-vision
         "<|system|>\nYou are a helpful assistant<|end|>\n<|user|>\nHello<|end|>\n<|assistant|>\nHi there<|end|>\n<|user|>\nWho are you<|end|>\n<|assistant|>\n   I am an assistant   <|end|>\n<|user|>\nAnother question<|end|>\n<|assistant|>\n",
+        // MiniCPM-3B-OpenHermes-2.5-v2-GGUF
+        u8"You are a helpful assistant<用户>HelloHi there<用户>Who are youI am an assistant<用户>Another question",
+        // DeepSeek-V2
+        u8"You are a helpful assistant\n\nUser: Hello\n\nAssistant: Hi there<｜end▁of▁sentence｜>User: Who are you\n\nAssistant:    I am an assistant   <｜end▁of▁sentence｜>User: Another question\n\nAssistant:",
     };
     std::vector formatted_chat(1024);
     int32_t res;

From 8748d8ac6f172b99826ab18f01d9a3a165987d54 Mon Sep 17 00:00:00 2001
From: Olivier Chafik 
Date: Fri, 28 Jun 2024 18:02:05 +0100
Subject: [PATCH 055/326] json: attempt to skip slow tests when running under
 emulator (#8189)

---
 .github/workflows/build.yml           |  1 +
 tests/test-json-schema-to-grammar.cpp | 40 +++++++++++++++------------
 2 files changed, 23 insertions(+), 18 deletions(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index adf67cecc7b2c..1e344db6b09e9 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -799,6 +799,7 @@ jobs:
           7z x "-o${env:RUNNER_TEMP}" $env:RUNNER_TEMP/sde.tar
           $sde = $(join-path $env:RUNNER_TEMP sde-external-${env:SDE_VERSION}-win/sde.exe)
           cd build
+          $env:LLAMA_SKIP_TESTS_SLOW_ON_EMULATOR = 1
           & $sde -future -- ctest -L main -C Release --verbose --timeout 900
 
       - name: Determine tag name
diff --git a/tests/test-json-schema-to-grammar.cpp b/tests/test-json-schema-to-grammar.cpp
index 720a949c73644..65486ac5c2d1b 100755
--- a/tests/test-json-schema-to-grammar.cpp
+++ b/tests/test-json-schema-to-grammar.cpp
@@ -1239,26 +1239,30 @@ int main() {
         }
     });
 
-    if (getenv("LLAMA_PYTHON_AVAILABLE") || (std::system("python -c \"import sys; exit(1) if sys.version_info < (3, 8) else print('Python version is sufficient')\"") == 0)) {
-        test_all("Python", [](const TestCase & tc) {
-            write("test-json-schema-input.tmp", tc.schema);
-            tc.verify_status(std::system(
-                "python ./examples/json_schema_to_grammar.py test-json-schema-input.tmp > test-grammar-output.tmp") == 0 ? SUCCESS : FAILURE);
-            tc.verify(read("test-grammar-output.tmp"));
-        });
+    if (getenv("LLAMA_SKIP_TESTS_SLOW_ON_EMULATOR")) {
+        fprintf(stderr, "\033[33mWARNING: Skipping slow tests on emulator.\n\033[0m");
     } else {
-        fprintf(stderr, "\033[33mWARNING: Python not found (min version required is 3.8), skipping Python JSON schema -> grammar tests.\n\033[0m");
-    }
+        if (getenv("LLAMA_PYTHON_AVAILABLE") || (std::system("python -c \"import sys; exit(1) if sys.version_info < (3, 8) else print('Python version is sufficient')\"") == 0)) {
+            test_all("Python", [](const TestCase & tc) {
+                write("test-json-schema-input.tmp", tc.schema);
+                tc.verify_status(std::system(
+                    "python ./examples/json_schema_to_grammar.py test-json-schema-input.tmp > test-grammar-output.tmp") == 0 ? SUCCESS : FAILURE);
+                tc.verify(read("test-grammar-output.tmp"));
+            });
+        } else {
+            fprintf(stderr, "\033[33mWARNING: Python not found (min version required is 3.8), skipping Python JSON schema -> grammar tests.\n\033[0m");
+        }
 
-    if (getenv("LLAMA_NODE_AVAILABLE") || (std::system("node --version") == 0)) {
-        test_all("JavaScript", [](const TestCase & tc) {
-            write("test-json-schema-input.tmp", tc.schema);
-            tc.verify_status(std::system(
-                "node ./tests/run-json-schema-to-grammar.mjs test-json-schema-input.tmp > test-grammar-output.tmp") == 0 ? SUCCESS : FAILURE);
-            tc.verify(read("test-grammar-output.tmp"));
-        });
-    } else {
-        fprintf(stderr, "\033[33mWARNING: Node not found, skipping JavaScript JSON schema -> grammar tests.\n\033[0m");
+        if (getenv("LLAMA_NODE_AVAILABLE") || (std::system("node --version") == 0)) {
+            test_all("JavaScript", [](const TestCase & tc) {
+                write("test-json-schema-input.tmp", tc.schema);
+                tc.verify_status(std::system(
+                    "node ./tests/run-json-schema-to-grammar.mjs test-json-schema-input.tmp > test-grammar-output.tmp") == 0 ? SUCCESS : FAILURE);
+                tc.verify(read("test-grammar-output.tmp"));
+            });
+        } else {
+            fprintf(stderr, "\033[33mWARNING: Node not found, skipping JavaScript JSON schema -> grammar tests.\n\033[0m");
+        }
     }
 
     test_all("Check Expectations Validity", [](const TestCase & tc) {

From 72272b83a3878e91251218c981b4c6ec16c33912 Mon Sep 17 00:00:00 2001
From: Xuan Son Nguyen 
Date: Sat, 29 Jun 2024 00:14:20 +0200
Subject: [PATCH 056/326] fix code typo in llama-cli (#8198)

---
 examples/main/main.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/main/main.cpp b/examples/main/main.cpp
index cfaf6a6e8ba4a..1114073b84370 100644
--- a/examples/main/main.cpp
+++ b/examples/main/main.cpp
@@ -810,7 +810,7 @@ int main(int argc, char ** argv) {
                         is_antiprompt = true;
                     }
 
-                    chat_add_and_format(model, chat_msgs, "system", assistant_ss.str());
+                    chat_add_and_format(model, chat_msgs, "assistant", assistant_ss.str());
                     is_interacting = true;
                     printf("\n");
                 }

From 1c5eba6f8e628fb0a98afb27d8aaeb3b0e136451 Mon Sep 17 00:00:00 2001
From: Andrei 
Date: Sat, 29 Jun 2024 20:44:08 -0700
Subject: [PATCH 057/326] llama: Add attention and final logit soft-capping,
 update scaling factor to Gemma2 (#8197)

* Add attention and final logit softcapping.

* fix

* Add custom add_ functions

* Disable flash attention for Gemma2

* Update src/llama.cpp

Co-authored-by: slaren 

* Add default value for attention and final logit softcap value

* Add custom kq scaling from Gemma2Attention

* Remove custom pre attention scaling and use computed value instead.

---------

Co-authored-by: slaren 
---
 convert-hf-to-gguf.py       |  6 ++++++
 gguf-py/gguf/constants.py   |  2 ++
 gguf-py/gguf/gguf_writer.py |  6 ++++++
 src/llama.cpp               | 35 ++++++++++++++++++++++++++++++++---
 4 files changed, 46 insertions(+), 3 deletions(-)

diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py
index 5bcc849db999d..3ef2f69e7c0df 100755
--- a/convert-hf-to-gguf.py
+++ b/convert-hf-to-gguf.py
@@ -2363,6 +2363,12 @@ def set_gguf_parameters(self):
         self.gguf_writer.add_key_length(hparams["head_dim"])
         self.gguf_writer.add_value_length(hparams["head_dim"])
         self.gguf_writer.add_file_type(self.ftype)
+        self.gguf_writer.add_attn_logit_softcapping(
+            self.hparams["attn_logit_softcapping"]
+        )
+        self.gguf_writer.add_final_logit_softcapping(
+            self.hparams["final_logit_softcapping"]
+        )
 
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         del bid  # unusem
diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py
index cf3d09e70d3e7..9bfa891d5dc52 100644
--- a/gguf-py/gguf/constants.py
+++ b/gguf-py/gguf/constants.py
@@ -50,6 +50,8 @@ class LLM:
         POOLING_TYPE                      = "{arch}.pooling_type"
         LOGIT_SCALE                       = "{arch}.logit_scale"
         DECODER_START_TOKEN_ID            = "{arch}.decoder_start_token_id"
+        ATTN_LOGIT_SOFTCAPPING            = "{arch}.attn_logit_softcapping"
+        FINAL_LOGIT_SOFTCAPPING           = "{arch}.final_logit_softcapping"
 
     class Attention:
         HEAD_COUNT        = "{arch}.attention.head_count"
diff --git a/gguf-py/gguf/gguf_writer.py b/gguf-py/gguf/gguf_writer.py
index 9869f6fe3445a..1aeb0d9b08685 100644
--- a/gguf-py/gguf/gguf_writer.py
+++ b/gguf-py/gguf/gguf_writer.py
@@ -516,6 +516,12 @@ def add_clamp_kqv(self, value: float) -> None:
     def add_logit_scale(self, value: float) -> None:
         self.add_float32(Keys.LLM.LOGIT_SCALE.format(arch=self.arch), value)
 
+    def add_attn_logit_softcapping(self, value: float) -> None:
+        self.add_float32(Keys.LLM.ATTN_LOGIT_SOFTCAPPING.format(arch=self.arch), value)
+
+    def add_final_logit_softcapping(self, value: float) -> None:
+        self.add_float32(Keys.LLM.FINAL_LOGIT_SOFTCAPPING.format(arch=self.arch), value)
+
     def add_expert_count(self, count: int) -> None:
         self.add_uint32(Keys.LLM.EXPERT_COUNT.format(arch=self.arch), count)
 
diff --git a/src/llama.cpp b/src/llama.cpp
index 3edaa98e8d01b..2a4d73856fcd9 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -302,6 +302,8 @@ enum llm_kv {
     LLM_KV_POOLING_TYPE,
     LLM_KV_LOGIT_SCALE,
     LLM_KV_DECODER_START_TOKEN_ID,
+    LLM_KV_ATTN_LOGIT_SOFTCAPPING,
+    LLM_KV_FINAL_LOGIT_SOFTCAPPING,
 
     LLM_KV_ATTENTION_HEAD_COUNT,
     LLM_KV_ATTENTION_HEAD_COUNT_KV,
@@ -392,6 +394,8 @@ static const std::map LLM_KV_NAMES = {
     { LLM_KV_POOLING_TYPE ,                     "%s.pooling_type"                      },
     { LLM_KV_LOGIT_SCALE,                       "%s.logit_scale"                       },
     { LLM_KV_DECODER_START_TOKEN_ID,            "%s.decoder_start_token_id"            },
+    { LLM_KV_ATTN_LOGIT_SOFTCAPPING,            "%s.attn_logit_softcapping"            },
+    { LLM_KV_FINAL_LOGIT_SOFTCAPPING,           "%s.final_logit_softcapping"           },
 
     { LLM_KV_ATTENTION_HEAD_COUNT,             "%s.attention.head_count"             },
     { LLM_KV_ATTENTION_HEAD_COUNT_KV,          "%s.attention.head_count_kv"          },
@@ -2099,6 +2103,9 @@ struct llama_hparams {
     float f_norm_eps;
     float f_norm_rms_eps;
 
+    float f_attn_logit_softcapping = 50.0f;
+    float f_final_logit_softcapping = 30.0f;
+
     float    rope_attn_factor = 1.0f;
     float    rope_freq_base_train;
     float    rope_freq_scale_train;
@@ -2115,8 +2122,9 @@ struct llama_hparams {
     float f_max_alibi_bias = 0.0f;
     float f_logit_scale    = 0.0f;
 
-    bool causal_attn = true;
-    bool use_alibi   = false;
+    bool causal_attn   = true;
+    bool use_alibi     = false;
+    bool attn_soft_cap = false;
 
     enum llama_pooling_type      pooling_type            = LLAMA_POOLING_TYPE_NONE;
     enum llama_rope_type         rope_type               = LLAMA_ROPE_TYPE_NONE;
@@ -4702,6 +4710,9 @@ static void llm_load_hparams(
         case LLM_ARCH_GEMMA2:
             {
                 ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
+                ml.get_key(LLM_KV_ATTN_LOGIT_SOFTCAPPING, hparams.f_attn_logit_softcapping, false);
+                ml.get_key(LLM_KV_FINAL_LOGIT_SOFTCAPPING, hparams.f_final_logit_softcapping, false);
+                hparams.attn_soft_cap = true;
 
                 switch (hparams.n_layer) {
                     case 42: model.type = e_model::MODEL_9B; break;
@@ -7579,6 +7590,12 @@ static struct ggml_tensor * llm_build_kqv(
             kq = ggml_scale(ctx, kq, 30);
         }
 
+        if (hparams.attn_soft_cap) {
+            kq = ggml_scale(ctx, kq, 1.0f / hparams.f_attn_logit_softcapping);
+            kq = ggml_tanh(ctx, kq);
+            kq = ggml_scale(ctx, kq, hparams.f_attn_logit_softcapping);
+        }
+
         kq = ggml_soft_max_ext(ctx, kq, kq_mask, kq_scale, hparams.f_max_alibi_bias);
         cb(kq, "kq_soft_max_ext", il);
 
@@ -11039,7 +11056,7 @@ struct llm_build_context {
                         ext_factor, attn_factor, beta_fast, beta_slow);
                 cb(Qcur, "Qcur", il);
 
-                Qcur = ggml_scale(ctx0, Qcur, 1.0f / sqrtf(float(n_embd_head_k)));
+                Qcur = ggml_scale(ctx0, Qcur, 1.0f / sqrtf(float(n_embd / n_head)));
                 cb(Qcur, "Qcur_scaled", il);
 
                 Kcur = ggml_rope_ext(
@@ -11106,6 +11123,12 @@ struct llm_build_context {
 
         // lm_head
         cur = ggml_mul_mat(ctx0, model.output, cur);
+
+        // final logit soft-capping
+        cur = ggml_scale(ctx0, cur, 1.0f / hparams.f_final_logit_softcapping);
+        cur = ggml_tanh(ctx0, cur);
+        cur = ggml_scale(ctx0, cur, hparams.f_final_logit_softcapping);
+
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -17379,6 +17402,12 @@ struct llama_context * llama_new_context_with_model(
         params.flash_attn = false;
     }
 
+    if (params.flash_attn && model->hparams.attn_soft_cap) {
+        LLAMA_LOG_WARN("%s: flash_attn is not compatible with attn_soft_cap - forcing off\n", __func__);
+        params.flash_attn = false;
+    }
+
+
     if (params.flash_attn && model->hparams.n_embd_head_k != model->hparams.n_embd_head_v) {
         LLAMA_LOG_WARN("%s: flash_attn requires n_embd_head_k == n_embd_head_v - forcing off\n", __func__);
         params.flash_attn = false;

From 9ef07800622e4c371605f9419864d15667c3558f Mon Sep 17 00:00:00 2001
From: Xuan Son Nguyen 
Date: Sun, 30 Jun 2024 20:27:13 +0200
Subject: [PATCH 058/326] Fix new line issue with chat template, disable
 template when in-prefix/suffix is set (#8203)

* preserve new line llama_chat_format_single

* disable chat template if in-prefix/suffix is set

* remove redundant change
---
 common/common.cpp            | 16 +++++++++++++---
 common/common.h              |  1 +
 examples/main/main.cpp       | 11 +++++++----
 tests/test-chat-template.cpp |  4 ++--
 4 files changed, 23 insertions(+), 9 deletions(-)

diff --git a/common/common.cpp b/common/common.cpp
index 6a00d25be1316..5a0d0ee038123 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -1014,16 +1014,19 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
     }
     if (arg == "--in-prefix-bos") {
         params.input_prefix_bos = true;
+        params.enable_chat_template = false;
         return true;
     }
     if (arg == "--in-prefix") {
         CHECK_ARG
         params.input_prefix = argv[i];
+        params.enable_chat_template = false;
         return true;
     }
     if (arg == "--in-suffix") {
         CHECK_ARG
         params.input_suffix = argv[i];
+        params.enable_chat_template = false;
         return true;
     }
     if (arg == "--spm-infill") {
@@ -1406,7 +1409,7 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
                                                                         "halt generation at PROMPT, return control in interactive mode\n"
                                                                         "can be specified more than once for multiple prompts" });
     options.push_back({ "main",        "-sp,   --special",              "special tokens output enabled (default: %s)", params.special ? "true" : "false" });
-    options.push_back({ "main",        "-cnv,  --conversation",         "run in conversation mode (does not print special tokens and suffix/prefix) (default: %s)", params.conversation ? "true" : "false" });
+    options.push_back({ "main",        "-cnv,  --conversation",         "run in conversation mode (does not print special tokens and suffix/prefix, use default chat template) (default: %s)", params.conversation ? "true" : "false" });
     options.push_back({ "main infill", "-i,    --interactive",          "run in interactive mode (default: %s)", params.interactive ? "true" : "false" });
     options.push_back({ "main infill", "-if,   --interactive-first",    "run in interactive mode and wait for input right away (default: %s)", params.interactive_first ? "true" : "false" });
     options.push_back({ "main infill", "-mli,  --multiline-input",      "allows you to write or paste multiple lines without ending each in '\\'" });
@@ -2668,12 +2671,19 @@ std::string llama_chat_format_single(const struct llama_model * model,
         const std::vector & past_msg,
         const llama_chat_msg & new_msg,
         bool add_ass) {
+    std::ostringstream ss;
     auto fmt_past_msg = llama_chat_apply_template(model, tmpl, past_msg, false);
     std::vector chat_new(past_msg);
+    // if the past_msg ends with a newline, we must preserve it in the formatted version
+    if (add_ass && !fmt_past_msg.empty() && fmt_past_msg.back() == '\n') {
+        ss << "\n";
+    };
+    // format chat with new_msg
     chat_new.push_back(new_msg);
     auto fmt_new_msg = llama_chat_apply_template(model, tmpl, chat_new, add_ass);
-    auto formatted = fmt_new_msg.substr(fmt_past_msg.size(), fmt_new_msg.size() - fmt_past_msg.size());
-    return formatted;
+    // get the diff part
+    ss << fmt_new_msg.substr(fmt_past_msg.size(), fmt_new_msg.size() - fmt_past_msg.size());
+    return ss.str();
 }
 
 std::string llama_chat_format_example(const struct llama_model * model,
diff --git a/common/common.h b/common/common.h
index d6cb814b990e9..627b7ed854757 100644
--- a/common/common.h
+++ b/common/common.h
@@ -200,6 +200,7 @@ struct gpt_params {
     std::string public_path   = "";
     std::string chat_template = "";
     std::string system_prompt = "";
+    bool enable_chat_template = true;
 
     std::vector api_keys;
 
diff --git a/examples/main/main.cpp b/examples/main/main.cpp
index 1114073b84370..d512953b9635c 100644
--- a/examples/main/main.cpp
+++ b/examples/main/main.cpp
@@ -261,7 +261,7 @@ int main(int argc, char ** argv) {
     std::vector embd_inp;
 
     {
-        auto prompt = params.conversation
+        auto prompt = (params.conversation && params.enable_chat_template)
             ? chat_add_and_format(model, chat_msgs, "system", params.prompt) // format the system prompt in conversation mode
             : params.prompt;
         if (params.interactive_first || !params.prompt.empty() || session_tokens.empty()) {
@@ -810,7 +810,9 @@ int main(int argc, char ** argv) {
                         is_antiprompt = true;
                     }
 
-                    chat_add_and_format(model, chat_msgs, "assistant", assistant_ss.str());
+                    if (params.enable_chat_template) {
+                        chat_add_and_format(model, chat_msgs, "assistant", assistant_ss.str());
+                    }
                     is_interacting = true;
                     printf("\n");
                 }
@@ -872,12 +874,13 @@ int main(int argc, char ** argv) {
                         string_process_escapes(buffer);
                     }
 
-                    std::string user_inp = params.conversation
+                    bool format_chat = params.conversation && params.enable_chat_template;
+                    std::string user_inp = format_chat
                         ? chat_add_and_format(model, chat_msgs, "user", std::move(buffer))
                         : std::move(buffer);
                     // TODO: one inconvenient of current chat template implementation is that we can't distinguish between user input and special tokens (prefix/postfix)
                     const auto line_pfx = ::llama_tokenize(ctx, params.input_prefix, false, true);
-                    const auto line_inp = ::llama_tokenize(ctx, user_inp,            false, params.conversation);
+                    const auto line_inp = ::llama_tokenize(ctx, user_inp,            false, format_chat);
                     const auto line_sfx = ::llama_tokenize(ctx, params.input_suffix, false, true);
 
                     LOG("input tokens: %s\n", LOG_TOKENS_TOSTR_PRETTY(ctx, line_inp).c_str());
diff --git a/tests/test-chat-template.cpp b/tests/test-chat-template.cpp
index b154038b2d5c0..03f5369109716 100644
--- a/tests/test-chat-template.cpp
+++ b/tests/test-chat-template.cpp
@@ -142,9 +142,9 @@ int main(void) {
         std::cout << "fmt_single(" << tmpl << ")\n" << output << "\n-------------------------\n";
         return output;
     };
-    assert(fmt_single("chatml") == "<|im_start|>user\nHow are you<|im_end|>\n<|im_start|>assistant\n");
+    assert(fmt_single("chatml") == "\n<|im_start|>user\nHow are you<|im_end|>\n<|im_start|>assistant\n");
     assert(fmt_single("llama2") == "[INST] How are you [/INST]");
-    assert(fmt_single("gemma") == "user\nHow are you\nmodel\n");
+    assert(fmt_single("gemma") == "\nuser\nHow are you\nmodel\n");
     assert(fmt_single("llama3") == "<|start_header_id|>user<|end_header_id|>\n\nHow are you<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n");
 
     return 0;

From d0a7145ba99ed3a8bc3145aa785b5c86ffe65020 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Mon, 1 Jul 2024 02:09:34 +0300
Subject: [PATCH 059/326] flake.lock: Update (#8218)

---
 flake.lock | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/flake.lock b/flake.lock
index 79bb3f63fdc6d..973ff4e5675c7 100644
--- a/flake.lock
+++ b/flake.lock
@@ -20,11 +20,11 @@
     },
     "nixpkgs": {
       "locked": {
-        "lastModified": 1718895438,
-        "narHash": "sha256-k3JqJrkdoYwE3fHE6xGDY676AYmyh4U2Zw+0Bwe5DLU=",
+        "lastModified": 1719506693,
+        "narHash": "sha256-C8e9S7RzshSdHB7L+v9I51af1gDM5unhJ2xO1ywxNH8=",
         "owner": "NixOS",
         "repo": "nixpkgs",
-        "rev": "d603719ec6e294f034936c0d0dc06f689d91b6c3",
+        "rev": "b2852eb9365c6de48ffb0dc2c9562591f652242a",
         "type": "github"
       },
       "original": {

From 197fe6c1d7bec6718ce901f0141b2725240f298c Mon Sep 17 00:00:00 2001
From: zhentaoyu 
Date: Mon, 1 Jul 2024 19:39:06 +0800
Subject: [PATCH 060/326] [SYCL] Update SYCL-Rope op and Refactor (#8157)

* align with rope.cu and move sycl-op to a single file
---
 ggml/src/ggml-sycl.cpp         | 305 +--------------------------------
 ggml/src/ggml-sycl/backend.hpp |   1 +
 ggml/src/ggml-sycl/rope.cpp    | 275 +++++++++++++++++++++++++++++
 ggml/src/ggml-sycl/rope.hpp    |  22 +++
 4 files changed, 300 insertions(+), 303 deletions(-)
 create mode 100644 ggml/src/ggml-sycl/rope.cpp
 create mode 100644 ggml/src/ggml-sycl/rope.hpp

diff --git a/ggml/src/ggml-sycl.cpp b/ggml/src/ggml-sycl.cpp
index 4a668a2c34d3e..30d8a5b33b613 100644
--- a/ggml/src/ggml-sycl.cpp
+++ b/ggml/src/ggml-sycl.cpp
@@ -978,114 +978,6 @@ static void cpy_f32_q(const char * cx, char * cdst, const int ne,
     cpy_blck(cx + x_offset, cdst + dst_offset);
 }
 
-static float rope_yarn_ramp(const float low, const float high, const int i0) {
-    const float y = (i0 / 2 - low) / sycl::max(0.001f, high - low);
-    return 1.0f - sycl::min(1.0f, sycl::max(0.0f, y));
-}
-
-struct rope_corr_dims {
-    float v[4];
-};
-
-// YaRN algorithm based on LlamaYaRNScaledRotaryEmbedding.py from https://github.com/jquesnelle/yarn
-// MIT licensed. Copyright (c) 2023 Jeffrey Quesnelle and Bowen Peng.
-static void rope_yarn(
-    float theta_extrap, float freq_scale, rope_corr_dims corr_dims, int64_t i0, float ext_factor, float mscale,
-    float * cos_theta, float * sin_theta
-) {
-    // Get n-d rotational scaling corrected for extrapolation
-    float theta_interp = freq_scale * theta_extrap;
-    float theta = theta_interp;
-    if (ext_factor != 0.0f) {
-        float ramp_mix = rope_yarn_ramp(corr_dims.v[0], corr_dims.v[1], i0) * ext_factor;
-        theta = theta_interp * (1 - ramp_mix) + theta_extrap * ramp_mix;
-
-        // Get n-d magnitude scaling corrected for interpolation
-        mscale *= 1.0f + 0.1f * sycl::log(1.0f / freq_scale);
-    }
-    *cos_theta = sycl::cos(theta) * mscale;
-    *sin_theta = sycl::sin(theta) * mscale;
-}
-
-// rope == RoPE == rotary positional embedding
-template
-static void rope(
-    const T * x, T * dst, int ncols, const int32_t * pos, float freq_scale, int p_delta_rows, float freq_base,
-    float ext_factor, float attn_factor, rope_corr_dims corr_dims
-,
-    const sycl::nd_item<3> &item_ct1) {
-    const int col = 2 * (item_ct1.get_local_range(1) * item_ct1.get_group(1) +
-                         item_ct1.get_local_id(1));
-
-    if (col >= ncols) {
-        return;
-    }
-
-    const int row = item_ct1.get_local_range(2) * item_ct1.get_group(2) +
-                    item_ct1.get_local_id(2);
-    const int i = row*ncols + col;
-    const int i2 = row/p_delta_rows;
-
-    const int p = has_pos ? pos[i2] : 0;
-    const float theta_base = p * dpct::pow(freq_base, -float(col) / ncols);
-
-    float cos_theta, sin_theta;
-    rope_yarn(theta_base, freq_scale, corr_dims, col, ext_factor, attn_factor, &cos_theta, &sin_theta);
-
-    const float x0 = x[i + 0];
-    const float x1 = x[i + 1];
-
-    dst[i + 0] = x0*cos_theta - x1*sin_theta;
-    dst[i + 1] = x0*sin_theta + x1*cos_theta;
-}
-
-template
-static void rope_neox(
-    const T * x, T * dst, int ncols, int n_dims, const int32_t * pos, float freq_scale, int p_delta_rows,
-    float ext_factor, float attn_factor, rope_corr_dims corr_dims, float theta_scale, float inv_ndims,
-    const float * freq_factors, const sycl::nd_item<3> &item_ct1) {
-    const int col = 2 * (item_ct1.get_local_range(1) * item_ct1.get_group(1) +
-                         item_ct1.get_local_id(1));
-
-    if (col >= ncols) {
-        return;
-    }
-
-    const int row = item_ct1.get_local_range(2) * item_ct1.get_group(2) +
-                    item_ct1.get_local_id(2);
-    const int ib = col / n_dims;
-    const int ic = col % n_dims;
-
-    if (ib > 0) {
-        const int i = row*ncols + ib*n_dims + ic;
-
-        dst[i + 0] = x[i + 0];
-        dst[i + 1] = x[i + 1];
-
-        return;
-    }
-
-    const int i  = row*ncols + ib*n_dims + ic/2;
-    const int i2 = row/p_delta_rows;
-
-    float cur_rot = inv_ndims * ic - ib;
-
-    const int p = has_pos ? pos[i2] : 0;
-    const float freq_factor = has_freq_facs ? freq_factors[ic/2] : 1.0f;
-
-    const float theta_base =
-        p * freq_scale * dpct::pow(theta_scale, col / 2.0f)/freq_factor;
-
-    float cos_theta, sin_theta;
-    rope_yarn(theta_base, freq_scale, corr_dims, cur_rot, ext_factor, attn_factor, &cos_theta, &sin_theta);
-
-    const float x0 = x[i + 0];
-    const float x1 = x[i + n_dims/2];
-
-    dst[i + 0]        = x0*cos_theta - x1*sin_theta;
-    dst[i + n_dims/2] = x0*sin_theta + x1*cos_theta;
-}
-
 static void k_sum_rows_f32(const float * x, float * dst, const int ncols,
                            const sycl::nd_item<3> &item_ct1) {
     const int row = item_ct1.get_group(1);
@@ -2241,110 +2133,6 @@ static void clamp_f32_sycl(const float *x, float *dst, const float min,
         });
 }
 
-template 
-static void rope_sycl(const T *x, T *dst, int ncols, int nrows,
-                      const int32_t *pos, float freq_scale, int p_delta_rows,
-                      float freq_base, float ext_factor, float attn_factor,
-                      rope_corr_dims corr_dims, queue_ptr stream) {
-    GGML_ASSERT(ncols % 2 == 0);
-    const sycl::range<3> block_dims(1, SYCL_ROPE_BLOCK_SIZE, 1);
-    const int num_blocks_x = (ncols + 2*SYCL_ROPE_BLOCK_SIZE - 1) / (2*SYCL_ROPE_BLOCK_SIZE);
-    const sycl::range<3> block_nums(1, num_blocks_x, nrows);
-    if (pos == nullptr) {
-        /*
-        DPCT1049:40: The work-group size passed to the SYCL kernel may exceed
-        the limit. To get the device limit, query
-        info::device::max_work_group_size. Adjust the work-group size if needed.
-        */
-        dpct::has_capability_or_fail(stream->get_device(),
-                                     {sycl::aspect::fp16});
-
-        stream->parallel_for(
-            sycl::nd_range<3>(block_nums * block_dims, block_dims),
-            [=](sycl::nd_item<3> item_ct1) {
-                rope(x, dst, ncols, pos, freq_scale, p_delta_rows,
-                               freq_base, ext_factor, attn_factor, corr_dims,
-                               item_ct1);
-            });
-    } else {
-        /*
-        DPCT1049:41: The work-group size passed to the SYCL kernel may exceed
-        the limit. To get the device limit, query
-        info::device::max_work_group_size. Adjust the work-group size if needed.
-        */
-        dpct::has_capability_or_fail(stream->get_device(),
-                                     {sycl::aspect::fp16});
-
-        stream->parallel_for(
-            sycl::nd_range<3>(block_nums * block_dims, block_dims),
-            [=](sycl::nd_item<3> item_ct1) {
-                rope(x, dst, ncols, pos, freq_scale, p_delta_rows,
-                              freq_base, ext_factor, attn_factor, corr_dims,
-                              item_ct1);
-            });
-    }
-}
-
-template 
-static void rope_neox_sycl(const T *x, T *dst, int ncols, int n_dims, int nrows,
-                           const int32_t *pos, float freq_scale,
-                           int p_delta_rows, float freq_base, float ext_factor,
-                           float attn_factor, rope_corr_dims corr_dims,
-                           const float * freq_factors, queue_ptr stream) {
-    GGML_ASSERT(ncols % 2 == 0);
-    const sycl::range<3> block_dims(1, SYCL_ROPE_BLOCK_SIZE, 1);
-    const int num_blocks_x = (ncols + 2*SYCL_ROPE_BLOCK_SIZE - 1) / (2*SYCL_ROPE_BLOCK_SIZE);
-    const sycl::range<3> block_nums(1, num_blocks_x, nrows);
-
-    const float theta_scale = powf(freq_base, -2.0f/n_dims);
-    const float inv_ndims = -1.0f / n_dims;
-
-    if (pos == nullptr) {
-        dpct::has_capability_or_fail(stream->get_device(),
-                                     {sycl::aspect::fp16});
-        if (freq_factors == nullptr) {
-            stream->parallel_for(
-                sycl::nd_range<3>(block_nums * block_dims, block_dims),
-                [=](sycl::nd_item<3> item_ct1) {
-                    rope_neox(x, dst, ncols, n_dims, pos, freq_scale,
-                                        p_delta_rows, ext_factor, attn_factor,
-                                        corr_dims, theta_scale, inv_ndims, freq_factors,
-                                        item_ct1);
-                });
-        } else {
-            stream->parallel_for(
-                sycl::nd_range<3>(block_nums * block_dims, block_dims),
-                [=](sycl::nd_item<3> item_ct1) {
-                    rope_neox(x, dst, ncols, n_dims, pos, freq_scale,
-                                        p_delta_rows, ext_factor, attn_factor,
-                                        corr_dims, theta_scale, inv_ndims, freq_factors,
-                                        item_ct1);
-                });
-        }
-    } else {
-        dpct::has_capability_or_fail(stream->get_device(),
-                                     {sycl::aspect::fp16});
-
-        if (freq_factors == nullptr) {
-            stream->parallel_for(
-                sycl::nd_range<3>(block_nums * block_dims, block_dims),
-                [=](sycl::nd_item<3> item_ct1) {
-                    rope_neox(x, dst, ncols, n_dims, pos, freq_scale,
-                                       p_delta_rows, ext_factor, attn_factor,
-                                       corr_dims, theta_scale, inv_ndims, freq_factors, item_ct1);
-                });
-        } else {
-            stream->parallel_for(
-                sycl::nd_range<3>(block_nums * block_dims, block_dims),
-                [=](sycl::nd_item<3> item_ct1) {
-                    rope_neox(x, dst, ncols, n_dims, pos, freq_scale,
-                                       p_delta_rows, ext_factor, attn_factor,
-                                       corr_dims, theta_scale, inv_ndims, freq_factors, item_ct1);
-                });
-        }
-    }
-}
-
 static void sum_rows_f32_sycl(const float *x, float *dst, const int ncols,
                               const int nrows, queue_ptr stream) {
     const sycl::range<3> block_dims(1, 1, WARP_SIZE);
@@ -3461,97 +3249,6 @@ catch (sycl::exception const &exc) {
   std::exit(1);
 }
 
-inline void ggml_sycl_op_rope(ggml_backend_sycl_context & ctx, const ggml_tensor *src0, const ggml_tensor *src1,
-                              ggml_tensor *dst, const float *src0_dd,
-                              const float *src1_dd, float *dst_dd,
-                              const queue_ptr &main_stream) {
-    const ggml_tensor * src2 = dst->src[2];
-
-    GGML_ASSERT(src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16);
-    GGML_ASSERT( dst->type == GGML_TYPE_F32 ||  dst->type == GGML_TYPE_F16);
-    GGML_ASSERT(src0->type == dst->type);
-
-    const int64_t ne00 = src0->ne[0];
-    const int64_t ne01 = src0->ne[1];
-    const int64_t ne2 = dst->ne[2];
-    const int64_t nrows = ggml_nrows(src0);
-
-    //const int n_past      = ((int32_t *) dst->op_params)[0];
-    const int n_dims      = ((int32_t *) dst->op_params)[1];
-    const int mode        = ((int32_t *) dst->op_params)[2];
-    //const int n_ctx       = ((int32_t *) dst->op_params)[3];
-    const int n_ctx_orig  = ((int32_t *) dst->op_params)[4];
-
-    // RoPE alteration for extended context
-    float freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow;
-    memcpy(&freq_base,   (int32_t *) dst->op_params +  5, sizeof(float));
-    memcpy(&freq_scale,  (int32_t *) dst->op_params +  6, sizeof(float));
-    memcpy(&ext_factor,  (int32_t *) dst->op_params +  7, sizeof(float));
-    memcpy(&attn_factor, (int32_t *) dst->op_params +  8, sizeof(float));
-    memcpy(&beta_fast,   (int32_t *) dst->op_params +  9, sizeof(float));
-    memcpy(&beta_slow,   (int32_t *) dst->op_params + 10, sizeof(float));
-
-    const float * freq_factors = nullptr;
-    const int32_t * pos = nullptr;
-    if ((mode & 1) == 0) {
-        GGML_ASSERT(src1->type == GGML_TYPE_I32);
-        GGML_ASSERT(src1->ne[0] == ne2);
-        pos = (const int32_t *) src1_dd;
-    }
-
-    const bool is_neox = mode & 2;
-
-#pragma message("TODO: update rope NORM mode to match NEOX mode")
-#pragma message("      https://github.com/ggerganov/llama.cpp/pull/7634")
-
-    if (is_neox) {
-        pos = (const int32_t *) src1_dd;
-
-        if (src2 != nullptr) {
-            freq_factors = (const float *) src2->data;
-        }
-    } else {
-        GGML_ASSERT(src2 == nullptr && "TODO: freq_factors not implemented for !is_neox");
-    }
-
-    rope_corr_dims corr_dims;
-    ggml_rope_yarn_corr_dims(n_dims, n_ctx_orig, freq_base, beta_fast, beta_slow, corr_dims.v);
-
-    // compute
-    if (is_neox) {
-        if (src0->type == GGML_TYPE_F32) {
-            rope_neox_sycl(
-                (const float *)src0_dd, (float *)dst_dd, ne00, n_dims, nrows, pos, freq_scale, ne01, freq_base, ext_factor,
-                attn_factor, corr_dims, freq_factors, main_stream
-            );
-        } else if (src0->type == GGML_TYPE_F16) {
-            rope_neox_sycl((const sycl::half *)src0_dd, (sycl::half *)dst_dd,
-                           ne00, n_dims, nrows, pos, freq_scale, ne01,
-                           freq_base, ext_factor, attn_factor, corr_dims,
-                           freq_factors, main_stream);
-        } else {
-            GGML_ASSERT(false);
-        }
-    } else {
-        if (src0->type == GGML_TYPE_F32) {
-            rope_sycl(
-                (const float *)src0_dd, (float *)dst_dd, ne00, nrows, pos, freq_scale, ne01, freq_base, ext_factor,
-                attn_factor, corr_dims, main_stream
-            );
-        } else if (src0->type == GGML_TYPE_F16) {
-            rope_sycl((const sycl::half *)src0_dd, (sycl::half *)dst_dd, ne00,
-                      nrows, pos, freq_scale, ne01, freq_base, ext_factor,
-                      attn_factor, corr_dims, main_stream);
-        } else {
-            GGML_ASSERT(false);
-        }
-    }
-
-    (void) src1;
-    (void) dst;
-    (void) src1_dd;
-}
-
 static void ggml_sycl_op_pool2d(ggml_backend_sycl_context & ctx, const ggml_tensor *src0,
                                 const ggml_tensor *src1, ggml_tensor *dst,
                                 const float *src0_dd, const float *src1_dd,
@@ -6241,7 +5938,9 @@ GGML_CALL static bool ggml_backend_sycl_supports_op(ggml_backend_t backend, cons
         case GGML_OP_CONT:
         case GGML_OP_DIAG_MASK_INF:
         case GGML_OP_SOFT_MAX:
+            return true;
         case GGML_OP_ROPE:
+            return ggml_is_contiguous(op->src[0]);
         case GGML_OP_IM2COL:
         case GGML_OP_POOL_2D:
         case GGML_OP_SUM_ROWS:
diff --git a/ggml/src/ggml-sycl/backend.hpp b/ggml/src/ggml-sycl/backend.hpp
index 2d37e271f9050..d5a63cd710cc3 100644
--- a/ggml/src/ggml-sycl/backend.hpp
+++ b/ggml/src/ggml-sycl/backend.hpp
@@ -19,5 +19,6 @@
 #include "dmmv.hpp"
 #include "mmq.hpp"
 #include "mmvq.hpp"
+#include "rope.hpp"
 
 #endif // GGML_SYCL_BACKEND_HPP
diff --git a/ggml/src/ggml-sycl/rope.cpp b/ggml/src/ggml-sycl/rope.cpp
new file mode 100644
index 0000000000000..eabf1693e2d2f
--- /dev/null
+++ b/ggml/src/ggml-sycl/rope.cpp
@@ -0,0 +1,275 @@
+#include "rope.hpp"
+
+struct rope_corr_dims {
+    float v[2];
+};
+
+static float rope_yarn_ramp(const float low, const float high, const int i0) {
+    const float y = (i0 / 2 - low) / sycl::max(0.001f, high - low);
+    return 1.0f - sycl::min(1.0f, sycl::max(0.0f, y));
+}
+
+// YaRN algorithm based on LlamaYaRNScaledRotaryEmbedding.py from https://github.com/jquesnelle/yarn
+// MIT licensed. Copyright (c) 2023 Jeffrey Quesnelle and Bowen Peng.
+static void rope_yarn(
+    float theta_extrap, float freq_scale, rope_corr_dims corr_dims, int64_t i0, float ext_factor, float mscale,
+    float * cos_theta, float * sin_theta) {
+    // Get n-d rotational scaling corrected for extrapolation
+    float theta_interp = freq_scale * theta_extrap;
+    float theta = theta_interp;
+    if (ext_factor != 0.0f) {
+        float ramp_mix = rope_yarn_ramp(corr_dims.v[0], corr_dims.v[1], i0) * ext_factor;
+        theta = theta_interp * (1 - ramp_mix) + theta_extrap * ramp_mix;
+
+        // Get n-d magnitude scaling corrected for interpolation
+        mscale *= 1.0f + 0.1f * sycl::log(1.0f / freq_scale);
+    }
+    *cos_theta = sycl::cos(theta) * mscale;
+    *sin_theta = sycl::sin(theta) * mscale;
+}
+
+template
+static void rope_norm(
+    const T * x, T * dst, int ne0, int n_dims, const int32_t * pos, float freq_scale, int p_delta_rows,
+    float ext_factor, float attn_factor, rope_corr_dims corr_dims, float theta_scale, const float * freq_factors,
+    const sycl::nd_item<3> &item_ct1) {
+    const int i0 = 2 * (item_ct1.get_local_range(1) * item_ct1.get_group(1) +
+                         item_ct1.get_local_id(1));
+
+    if (i0 >= ne0) {
+        return;
+    }
+
+    const int row = item_ct1.get_local_range(2) * item_ct1.get_group(2) +
+                    item_ct1.get_local_id(2);
+
+    if (i0 >= n_dims) {
+        const int i = row*ne0 + i0;
+
+        dst[i + 0] = x[i + 0];
+        dst[i + 1] = x[i + 1];
+
+        return;
+    }
+
+    const int i = row*ne0 + i0;
+    const int i2 = row/p_delta_rows;
+
+    const float theta_base = pos[i2]*powf(theta_scale, i0/2.0f);
+
+    const float freq_factor = has_ff ? freq_factors[i0/2] : 1.0f;
+
+    float cos_theta;
+    float sin_theta;
+
+    rope_yarn(theta_base/freq_factor, freq_scale, corr_dims, i0, ext_factor, attn_factor, &cos_theta, &sin_theta);
+
+    const float x0 = x[i + 0];
+    const float x1 = x[i + 1];
+
+    dst[i + 0] = x0*cos_theta - x1*sin_theta;
+    dst[i + 1] = x0*sin_theta + x1*cos_theta;
+}
+
+template
+static void rope_neox(
+    const T * x, T * dst, int ne0, int n_dims, const int32_t * pos, float freq_scale, int p_delta_rows,
+    float ext_factor, float attn_factor, rope_corr_dims corr_dims, float theta_scale, const float * freq_factors,
+    const sycl::nd_item<3> &item_ct1) {
+    const int i0 = 2 * (item_ct1.get_local_range(1) * item_ct1.get_group(1) +
+                         item_ct1.get_local_id(1));
+
+    if (i0 >= ne0) {
+        return;
+    }
+
+    const int row = item_ct1.get_local_range(2) * item_ct1.get_group(2) +
+                    item_ct1.get_local_id(2);
+
+    if (i0 >= n_dims) {
+        const int i = row*ne0 + i0;
+
+        dst[i + 0] = x[i + 0];
+        dst[i + 1] = x[i + 1];
+
+        return;
+    }
+
+    const int i  = row*ne0 + i0/2;
+    const int i2 = row/p_delta_rows;
+
+    const float theta_base = pos[i2]*powf(theta_scale, i0/2.0f);
+
+    const float freq_factor = has_ff ? freq_factors[i0/2] : 1.0f;
+
+    float cos_theta;
+    float sin_theta;
+
+    rope_yarn(theta_base/freq_factor, freq_scale, corr_dims, i0, ext_factor, attn_factor, &cos_theta, &sin_theta);
+
+    const float x0 = x[i + 0];
+    const float x1 = x[i + n_dims/2];
+
+    dst[i + 0]        = x0*cos_theta - x1*sin_theta;
+    dst[i + n_dims/2] = x0*sin_theta + x1*cos_theta;
+}
+
+template 
+static void rope_norm_sycl(
+    const T *x, T *dst, int ne0, int n_dims, int nr, const int32_t *pos, float freq_scale, int p_delta_rows,
+    float freq_base, float ext_factor, float attn_factor, rope_corr_dims corr_dims, const float * freq_factors, queue_ptr stream) {
+    GGML_ASSERT(ne0 % 2 == 0);
+    const sycl::range<3> block_dims(1, SYCL_ROPE_BLOCK_SIZE, 1);
+    const int num_blocks_x = (ne0 + 2*SYCL_ROPE_BLOCK_SIZE - 1) / (2*SYCL_ROPE_BLOCK_SIZE);
+    const sycl::range<3> block_nums(1, num_blocks_x, nr);
+
+    const float theta_scale = powf(freq_base, -2.0f/n_dims);
+
+    dpct::has_capability_or_fail(stream->get_device(),
+                                     {sycl::aspect::fp16});
+
+    if (freq_factors == nullptr) {
+        /*
+        DPCT1049:40: The work-group size passed to the SYCL kernel may exceed
+        the limit. To get the device limit, query
+        info::device::max_work_group_size. Adjust the work-group size if needed.
+        */
+        stream->parallel_for(
+            sycl::nd_range<3>(block_nums * block_dims, block_dims),
+            [=](sycl::nd_item<3> item_ct1) {
+                rope_norm(x, dst, ne0, n_dims, pos, freq_scale, p_delta_rows,
+                               ext_factor, attn_factor, corr_dims, theta_scale, freq_factors,
+                               item_ct1);
+            });
+    } else {
+        /*
+        DPCT1049:41: The work-group size passed to the SYCL kernel may exceed
+        the limit. To get the device limit, query
+        info::device::max_work_group_size. Adjust the work-group size if needed.
+        */
+        stream->parallel_for(
+            sycl::nd_range<3>(block_nums * block_dims, block_dims),
+            [=](sycl::nd_item<3> item_ct1) {
+                rope_norm(x, dst, ne0, n_dims, pos, freq_scale, p_delta_rows,
+                              ext_factor, attn_factor, corr_dims, theta_scale, freq_factors,
+                              item_ct1);
+            });
+    }
+}
+
+template 
+static void rope_neox_sycl(
+    const T *x, T *dst, int ne0, int n_dims, int nr, const int32_t *pos, float freq_scale, int p_delta_rows,
+    float freq_base, float ext_factor, float attn_factor, rope_corr_dims corr_dims, const float * freq_factors, queue_ptr stream) {
+    GGML_ASSERT(ne0 % 2 == 0);
+    const sycl::range<3> block_dims(1, SYCL_ROPE_BLOCK_SIZE, 1);
+    const int num_blocks_x = (ne0 + 2*SYCL_ROPE_BLOCK_SIZE - 1) / (2*SYCL_ROPE_BLOCK_SIZE);
+    const sycl::range<3> block_nums(1, num_blocks_x, nr);
+
+    const float theta_scale = powf(freq_base, -2.0f/n_dims);
+
+    dpct::has_capability_or_fail(stream->get_device(),
+                                    {sycl::aspect::fp16});
+
+    if (freq_factors == nullptr) {
+        stream->parallel_for(
+            sycl::nd_range<3>(block_nums * block_dims, block_dims),
+            [=](sycl::nd_item<3> item_ct1) {
+                rope_neox(x, dst, ne0, n_dims, pos, freq_scale,
+                                    p_delta_rows, ext_factor, attn_factor,
+                                    corr_dims, theta_scale, freq_factors,
+                                    item_ct1);
+            });
+    } else {
+        stream->parallel_for(
+            sycl::nd_range<3>(block_nums * block_dims, block_dims),
+            [=](sycl::nd_item<3> item_ct1) {
+                rope_neox(x, dst, ne0, n_dims, pos, freq_scale,
+                                    p_delta_rows, ext_factor, attn_factor,
+                                    corr_dims, theta_scale, freq_factors,
+                                    item_ct1);
+            });
+    }
+}
+
+void ggml_sycl_op_rope(
+    ggml_backend_sycl_context & ctx, const ggml_tensor *src0, const ggml_tensor *src1, ggml_tensor *dst,
+    const float *src0_dd, const float *src1_dd, float *dst_dd, const queue_ptr &main_stream) {
+    const ggml_tensor * src2 = dst->src[2];
+
+    GGML_ASSERT(src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16);
+    GGML_ASSERT( dst->type == GGML_TYPE_F32 ||  dst->type == GGML_TYPE_F16);
+    GGML_ASSERT(src0->type == dst->type);
+
+    const int64_t ne00 = src0->ne[0];
+    const int64_t ne01 = src0->ne[1];
+    const int64_t nr = ggml_nrows(src0);
+
+    //const int n_past      = ((int32_t *) dst->op_params)[0];
+    const int n_dims      = ((int32_t *) dst->op_params)[1];
+    const int mode        = ((int32_t *) dst->op_params)[2];
+    //const int n_ctx       = ((int32_t *) dst->op_params)[3];
+    const int n_ctx_orig  = ((int32_t *) dst->op_params)[4];
+
+    // RoPE alteration for extended context
+    float freq_base;
+    float freq_scale;
+    float ext_factor;
+    float attn_factor;
+    float beta_fast;
+    float beta_slow;
+
+    memcpy(&freq_base,   (int32_t *) dst->op_params +  5, sizeof(float));
+    memcpy(&freq_scale,  (int32_t *) dst->op_params +  6, sizeof(float));
+    memcpy(&ext_factor,  (int32_t *) dst->op_params +  7, sizeof(float));
+    memcpy(&attn_factor, (int32_t *) dst->op_params +  8, sizeof(float));
+    memcpy(&beta_fast,   (int32_t *) dst->op_params +  9, sizeof(float));
+    memcpy(&beta_slow,   (int32_t *) dst->op_params + 10, sizeof(float));
+
+    const bool is_neox = mode & 2;
+
+    const int32_t * pos = (const int32_t *) src1_dd;
+
+    const float * freq_factors = nullptr;
+    if (src2 != nullptr) {
+        freq_factors = (const float *) src2->data;
+    }
+
+    rope_corr_dims corr_dims;
+    ggml_rope_yarn_corr_dims(n_dims, n_ctx_orig, freq_base, beta_fast, beta_slow, corr_dims.v);
+
+    // compute
+    if (is_neox) {
+        if (src0->type == GGML_TYPE_F32) {
+            rope_neox_sycl(
+                (const float *)src0_dd, (float *)dst_dd, ne00, n_dims, nr, pos, freq_scale, ne01, freq_base, ext_factor,
+                attn_factor, corr_dims, freq_factors, main_stream
+            );
+        } else if (src0->type == GGML_TYPE_F16) {
+            rope_neox_sycl(
+                (const sycl::half *)src0_dd, (sycl::half *)dst_dd, ne00, n_dims, nr, pos, freq_scale, ne01, freq_base, ext_factor,
+                attn_factor, corr_dims, freq_factors, main_stream
+            );
+        } else {
+            GGML_ASSERT(false);
+        }
+    } else {
+        if (src0->type == GGML_TYPE_F32) {
+            rope_norm_sycl(
+                (const float *)src0_dd, (float *)dst_dd, ne00, n_dims, nr, pos, freq_scale, ne01, freq_base, ext_factor,
+                attn_factor, corr_dims, freq_factors, main_stream
+            );
+        } else if (src0->type == GGML_TYPE_F16) {
+            rope_norm_sycl(
+                (const sycl::half *)src0_dd, (sycl::half *)dst_dd, ne00, n_dims, nr, pos, freq_scale, ne01, freq_base, ext_factor,
+                attn_factor, corr_dims, freq_factors, main_stream
+            );
+        } else {
+            GGML_ASSERT(false);
+        }
+    }
+
+    (void) src1;
+    (void) dst;
+    (void) src1_dd;
+}
diff --git a/ggml/src/ggml-sycl/rope.hpp b/ggml/src/ggml-sycl/rope.hpp
new file mode 100644
index 0000000000000..00354c3131bd7
--- /dev/null
+++ b/ggml/src/ggml-sycl/rope.hpp
@@ -0,0 +1,22 @@
+//
+// MIT license
+// Copyright (C) 2024 Intel Corporation
+// SPDX-License-Identifier: MIT
+//
+
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+
+#ifndef GGML_SYCL_ROPE_HPP
+#define GGML_SYCL_ROPE_HPP
+
+#include "common.hpp"
+
+void ggml_sycl_op_rope(
+    ggml_backend_sycl_context & ctx, const ggml_tensor *src0, const ggml_tensor *src1, ggml_tensor *dst,
+    const float *src0_dd, const float *src1_dd, float *dst_dd, const queue_ptr &main_stream);
+
+#endif // GGML_SYCL_ROPE_HPP

From 694c59cb42d1ebd6a7d912ca65d3d7363e0f14c9 Mon Sep 17 00:00:00 2001
From: iacore <74560659+iacore@users.noreply.github.com>
Date: Mon, 1 Jul 2024 11:40:58 +0000
Subject: [PATCH 061/326] Document BERT support. (#8205)

* Update README.md

document BERT support

* Update README.md
---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 99b16f6e29e32..153d837e374ea 100644
--- a/README.md
+++ b/README.md
@@ -108,6 +108,7 @@ Typically finetunes of the base models below are supported as well.
 - [X] [Falcon](https://huggingface.co/models?search=tiiuae/falcon)
 - [X] [Chinese LLaMA / Alpaca](https://github.com/ymcui/Chinese-LLaMA-Alpaca) and [Chinese LLaMA-2 / Alpaca-2](https://github.com/ymcui/Chinese-LLaMA-Alpaca-2)
 - [X] [Vigogne (French)](https://github.com/bofenghuang/vigogne)
+- [X] [BERT](https://github.com/ggerganov/llama.cpp/pull/5423)
 - [X] [Koala](https://bair.berkeley.edu/blog/2023/04/03/koala/)
 - [X] [Baichuan 1 & 2](https://huggingface.co/models?search=baichuan-inc/Baichuan) + [derivations](https://huggingface.co/hiyouga/baichuan-7b-sft)
 - [X] [Aquila 1 & 2](https://huggingface.co/models?search=BAAI/Aquila)

From 257f8e41e24b5bbfc27d9e907189a3e0cdb650d4 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Mon, 1 Jul 2024 14:46:18 +0300
Subject: [PATCH 062/326] nix : remove OpenCL remnants (#8235)

* nix : remove OpenCL remnants

* minor : remove parentheses
---
 .devops/nix/package.nix | 11 ++---------
 1 file changed, 2 insertions(+), 9 deletions(-)

diff --git a/.devops/nix/package.nix b/.devops/nix/package.nix
index 4ee0d62cb49d9..b75d7ff9e5bab 100644
--- a/.devops/nix/package.nix
+++ b/.devops/nix/package.nix
@@ -17,18 +17,15 @@
   rocmPackages,
   vulkan-headers,
   vulkan-loader,
-  clblast,
   useBlas ? builtins.all (x: !x) [
     useCuda
     useMetalKit
-    useOpenCL
     useRocm
     useVulkan
   ] && blas.meta.available,
   useCuda ? config.cudaSupport,
-  useMetalKit ? stdenv.isAarch64 && stdenv.isDarwin && !useOpenCL,
+  useMetalKit ? stdenv.isAarch64 && stdenv.isDarwin,
   useMpi ? false, # Increases the runtime closure size by ~700M
-  useOpenCL ? false,
   useRocm ? config.rocmSupport,
   useVulkan ? false,
   llamaVersion ? "0.0.0", # Arbitrary version, substituted by the flake
@@ -56,7 +53,6 @@ let
     ++ lib.optionals useCuda [ "CUDA" ]
     ++ lib.optionals useMetalKit [ "MetalKit" ]
     ++ lib.optionals useMpi [ "MPI" ]
-    ++ lib.optionals useOpenCL [ "OpenCL" ]
     ++ lib.optionals useRocm [ "ROCm" ]
     ++ lib.optionals useVulkan [ "Vulkan" ];
 
@@ -198,7 +194,6 @@ effectiveStdenv.mkDerivation (
       optionals effectiveStdenv.isDarwin darwinBuildInputs
       ++ optionals useCuda cudaBuildInputs
       ++ optionals useMpi [ mpi ]
-      ++ optionals useOpenCL [ clblast ]
       ++ optionals useRocm rocmBuildInputs
       ++ optionals useBlas [ blas ]
       ++ optionals useVulkan vulkanBuildInputs;
@@ -210,7 +205,6 @@ effectiveStdenv.mkDerivation (
         (cmakeBool "CMAKE_SKIP_BUILD_RPATH" true)
         (cmakeBool "GGML_NATIVE" false)
         (cmakeBool "GGML_BLAS" useBlas)
-        (cmakeBool "GGML_CLBLAST" useOpenCL)
         (cmakeBool "GGML_CUDA" useCuda)
         (cmakeBool "GGML_HIPBLAS" useRocm)
         (cmakeBool "GGML_METAL" useMetalKit)
@@ -254,7 +248,6 @@ effectiveStdenv.mkDerivation (
         useCuda
         useMetalKit
         useMpi
-        useOpenCL
         useRocm
         useVulkan
         ;
@@ -281,7 +274,7 @@ effectiveStdenv.mkDerivation (
       # Configurations we don't want even the CI to evaluate. Results in the
       # "unsupported platform" messages. This is mostly a no-op, because
       # cudaPackages would've refused to evaluate anyway.
-      badPlatforms = optionals (useCuda || useOpenCL) lib.platforms.darwin;
+      badPlatforms = optionals useCuda lib.platforms.darwin;
 
       # Configurations that are known to result in build failures. Can be
       # overridden by importing Nixpkgs with `allowBroken = true`.

From 3840b6f593751a0ba636bfda73b630cd6c29d7b5 Mon Sep 17 00:00:00 2001
From: Michael Francis 
Date: Mon, 1 Jul 2024 07:47:04 -0400
Subject: [PATCH 063/326] nix : enable curl (#8043)

Co-authored-by: Georgi Gerganov 
---
 .devops/nix/package.nix | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/.devops/nix/package.nix b/.devops/nix/package.nix
index b75d7ff9e5bab..49e9b75287b33 100644
--- a/.devops/nix/package.nix
+++ b/.devops/nix/package.nix
@@ -17,6 +17,7 @@
   rocmPackages,
   vulkan-headers,
   vulkan-loader,
+  curl,
   useBlas ? builtins.all (x: !x) [
     useCuda
     useMetalKit
@@ -27,6 +28,7 @@
   useMetalKit ? stdenv.isAarch64 && stdenv.isDarwin,
   useMpi ? false, # Increases the runtime closure size by ~700M
   useRocm ? config.rocmSupport,
+  enableCurl ? true,
   useVulkan ? false,
   llamaVersion ? "0.0.0", # Arbitrary version, substituted by the flake
 
@@ -196,13 +198,15 @@ effectiveStdenv.mkDerivation (
       ++ optionals useMpi [ mpi ]
       ++ optionals useRocm rocmBuildInputs
       ++ optionals useBlas [ blas ]
-      ++ optionals useVulkan vulkanBuildInputs;
+      ++ optionals useVulkan vulkanBuildInputs
+      ++ optionals enableCurl [ curl ];
 
     cmakeFlags =
       [
         (cmakeBool "LLAMA_BUILD_SERVER" true)
         (cmakeBool "BUILD_SHARED_LIBS" (!enableStatic))
         (cmakeBool "CMAKE_SKIP_BUILD_RPATH" true)
+        (cmakeBool "LLAMA_CURL" enableCurl)
         (cmakeBool "GGML_NATIVE" false)
         (cmakeBool "GGML_BLAS" useBlas)
         (cmakeBool "GGML_CUDA" useCuda)

From 0ddeff10230b88f1fa9866bbe5fe0d71ba2323a0 Mon Sep 17 00:00:00 2001
From: Roni 
Date: Mon, 1 Jul 2024 14:48:16 +0200
Subject: [PATCH 064/326] readme : update tool list (#8209)

* Added gppm to Tool list in README

* Update README.md

---------

Co-authored-by: Georgi Gerganov 
---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 153d837e374ea..c136d4a5cb9c9 100644
--- a/README.md
+++ b/README.md
@@ -218,6 +218,7 @@ Unless otherwise noted these projects are open-source with permissive licensing:
 **Tools:**
 
 - [akx/ggify](https://github.com/akx/ggify) – download PyTorch models from HuggingFace Hub and convert them to GGML
+[crashr/gppm](https://github.com/crashr/gppm) – launch llama.cpp instances utilizing NVIDIA Tesla P40 or P100 GPUs with reduced idle power consumption
 
 ---
 

From 49122a873f54615626d1b49a2a39013ed4be98d5 Mon Sep 17 00:00:00 2001
From: Xuan Son Nguyen 
Date: Mon, 1 Jul 2024 18:48:34 +0200
Subject: [PATCH 065/326] gemma2: add sliding window mask (#8227)

* gemma2: add sliding window mask

* fix data_swa uninitialized

* better naming

* add co-author

Co-authored-by: Arlo Phoenix 

* replace list with single tensor

* update

* llama : minor styling

* convert : add sanity check for query_pre_attn_scalar

* fix small typo in README

---------

Co-authored-by: Arlo Phoenix 
Co-authored-by: Georgi Gerganov 
---
 README.md                   |  2 +-
 convert-hf-to-gguf.py       |  6 +++
 gguf-py/gguf/constants.py   |  1 +
 gguf-py/gguf/gguf_writer.py |  3 ++
 src/llama.cpp               | 99 +++++++++++++++++++++++++------------
 5 files changed, 79 insertions(+), 32 deletions(-)

diff --git a/README.md b/README.md
index c136d4a5cb9c9..daba70717312e 100644
--- a/README.md
+++ b/README.md
@@ -218,7 +218,7 @@ Unless otherwise noted these projects are open-source with permissive licensing:
 **Tools:**
 
 - [akx/ggify](https://github.com/akx/ggify) – download PyTorch models from HuggingFace Hub and convert them to GGML
-[crashr/gppm](https://github.com/crashr/gppm) – launch llama.cpp instances utilizing NVIDIA Tesla P40 or P100 GPUs with reduced idle power consumption
+- [crashr/gppm](https://github.com/crashr/gppm) – launch llama.cpp instances utilizing NVIDIA Tesla P40 or P100 GPUs with reduced idle power consumption
 
 ---
 
diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py
index 3ef2f69e7c0df..4a7f500ff7d5c 100755
--- a/convert-hf-to-gguf.py
+++ b/convert-hf-to-gguf.py
@@ -2369,6 +2369,12 @@ def set_gguf_parameters(self):
         self.gguf_writer.add_final_logit_softcapping(
             self.hparams["final_logit_softcapping"]
         )
+        self.gguf_writer.add_sliding_window(self.hparams["sliding_window"])
+
+        # sanity check
+        attn_scalar = self.hparams["query_pre_attn_scalar"]
+        if attn_scalar != hparams["hidden_size"] / hparams["num_attention_heads"]:
+            raise ValueError("query_pre_attn_scalar must be equal to n_embd / n_head")
 
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         del bid  # unusem
diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py
index 9bfa891d5dc52..e87c58266158a 100644
--- a/gguf-py/gguf/constants.py
+++ b/gguf-py/gguf/constants.py
@@ -66,6 +66,7 @@ class Attention:
         Q_LORA_RANK       = "{arch}.attention.q_lora_rank"
         KV_LORA_RANK      = "{arch}.attention.kv_lora_rank"
         REL_BUCKETS_COUNT = "{arch}.attention.relative_buckets_count"
+        SLIDING_WINDOW    = "{arch}.attention.sliding_window"
 
     class Rope:
         DIMENSION_COUNT         = "{arch}.rope.dimension_count"
diff --git a/gguf-py/gguf/gguf_writer.py b/gguf-py/gguf/gguf_writer.py
index 1aeb0d9b08685..75a8b2636a6a2 100644
--- a/gguf-py/gguf/gguf_writer.py
+++ b/gguf-py/gguf/gguf_writer.py
@@ -552,6 +552,9 @@ def add_kv_lora_rank(self, length: int) -> None:
     def add_relative_attn_buckets_count(self, value: int) -> None:
         self.add_uint32(Keys.Attention.REL_BUCKETS_COUNT.format(arch=self.arch), value)
 
+    def add_sliding_window(self, value: int) -> None:
+        self.add_uint32(Keys.Attention.SLIDING_WINDOW.format(arch=self.arch), value)
+
     def add_pooling_type(self, value: PoolingType) -> None:
         self.add_uint32(Keys.LLM.POOLING_TYPE.format(arch=self.arch), value.value)
 
diff --git a/src/llama.cpp b/src/llama.cpp
index 2a4d73856fcd9..eea532f6ac2ff 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -317,6 +317,7 @@ enum llm_kv {
     LLM_KV_ATTENTION_Q_LORA_RANK,
     LLM_KV_ATTENTION_KV_LORA_RANK,
     LLM_KV_ATTENTION_RELATIVE_BUCKETS_COUNT,
+    LLM_KV_ATTENTION_SLIDING_WINDOW,
 
     LLM_KV_ROPE_DIMENSION_COUNT,
     LLM_KV_ROPE_FREQ_BASE,
@@ -409,6 +410,7 @@ static const std::map LLM_KV_NAMES = {
     { LLM_KV_ATTENTION_Q_LORA_RANK,            "%s.attention.q_lora_rank"            },
     { LLM_KV_ATTENTION_KV_LORA_RANK,           "%s.attention.kv_lora_rank"           },
     { LLM_KV_ATTENTION_RELATIVE_BUCKETS_COUNT, "%s.attention.relative_buckets_count" },
+    { LLM_KV_ATTENTION_SLIDING_WINDOW,         "%s.attention.sliding_window"         },
 
     { LLM_KV_ROPE_DIMENSION_COUNT,          "%s.rope.dimension_count"                 },
     { LLM_KV_ROPE_FREQ_BASE,                "%s.rope.freq_base"                       },
@@ -2085,6 +2087,7 @@ struct llama_hparams {
     uint32_t n_head_kv;
     uint32_t n_layer;
     uint32_t n_rot;
+    uint32_t n_swa = 0; // sliding window attention (SWA)
     uint32_t n_embd_head_k; // dimension of keys (d_k). d_q is assumed to be the same, but there are n_head q heads, and only n_head_kv k-v heads
     uint32_t n_embd_head_v; // dimension of values (d_v) aka n_embd_head
     uint32_t n_ff;
@@ -2139,6 +2142,7 @@ struct llama_hparams {
         if (this->n_head_kv     != other.n_head_kv)     return true;
         if (this->n_layer       != other.n_layer)       return true;
         if (this->n_rot         != other.n_rot)         return true;
+        if (this->n_swa         != other.n_swa)         return true;
         if (this->n_embd_head_k != other.n_embd_head_k) return true;
         if (this->n_embd_head_v != other.n_embd_head_v) return true;
         if (this->n_ff          != other.n_ff)          return true;
@@ -2649,17 +2653,18 @@ struct llama_context {
     void *              abort_callback_data = nullptr;
 
     // input tensors
-    struct ggml_tensor * inp_tokens;    // I32 [n_batch]
-    struct ggml_tensor * inp_embd;      // F32 [n_embd, n_batch]
-    struct ggml_tensor * inp_pos;       // I32 [n_batch]
-    struct ggml_tensor * inp_out_ids;   // I32 [n_outputs]
-    struct ggml_tensor * inp_KQ_mask;   // F32 [kv_size, n_batch]
-    struct ggml_tensor * inp_K_shift;   // I32 [kv_size]
-    struct ggml_tensor * inp_mean;      // F32 [n_batch, n_batch]
-    struct ggml_tensor * inp_cls;       // I32 [n_batch]
-    struct ggml_tensor * inp_s_copy;    // I32 [kv_size]
-    struct ggml_tensor * inp_s_mask;    // F32 [1, n_kv]
-    struct ggml_tensor * inp_s_seq;     // I32 [n_kv, n_batch]
+    struct ggml_tensor * inp_tokens;      // I32 [n_batch]
+    struct ggml_tensor * inp_embd;        // F32 [n_embd, n_batch]
+    struct ggml_tensor * inp_pos;         // I32 [n_batch]
+    struct ggml_tensor * inp_out_ids;     // I32 [n_outputs]
+    struct ggml_tensor * inp_KQ_mask;     // F32 [kv_size, n_batch]
+    struct ggml_tensor * inp_KQ_mask_swa; // F32 [kv_size, n_batch]
+    struct ggml_tensor * inp_K_shift;     // I32 [kv_size]
+    struct ggml_tensor * inp_mean;        // F32 [n_batch, n_batch]
+    struct ggml_tensor * inp_cls;         // I32 [n_batch]
+    struct ggml_tensor * inp_s_copy;      // I32 [kv_size]
+    struct ggml_tensor * inp_s_mask;      // F32 [1, n_kv]
+    struct ggml_tensor * inp_s_seq;       // I32 [n_kv, n_batch]
 
     // control vectors
     struct llama_control_vector cvec;
@@ -4709,6 +4714,8 @@ static void llm_load_hparams(
             } break;
         case LLM_ARCH_GEMMA2:
             {
+                hparams.n_swa = 4096; // default value of gemma 2
+                ml.get_key(LLM_KV_ATTENTION_SLIDING_WINDOW, hparams.n_swa, false);
                 ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
                 ml.get_key(LLM_KV_ATTN_LOGIT_SOFTCAPPING, hparams.f_attn_logit_softcapping, false);
                 ml.get_key(LLM_KV_FINAL_LOGIT_SOFTCAPPING, hparams.f_final_logit_softcapping, false);
@@ -5419,6 +5426,7 @@ static void llm_load_print_meta(llama_model_loader & ml, llama_model & model) {
     LLAMA_LOG_INFO("%s: n_head_kv        = %u\n",     __func__, hparams.n_head_kv);
     LLAMA_LOG_INFO("%s: n_layer          = %u\n",     __func__, hparams.n_layer);
     LLAMA_LOG_INFO("%s: n_rot            = %u\n",     __func__, hparams.n_rot);
+    LLAMA_LOG_INFO("%s: n_swa            = %u\n",     __func__, hparams.n_swa);
     LLAMA_LOG_INFO("%s: n_embd_head_k    = %u\n",     __func__, hparams.n_embd_head_k);
     LLAMA_LOG_INFO("%s: n_embd_head_v    = %u\n",     __func__, hparams.n_embd_head_v);
     LLAMA_LOG_INFO("%s: n_gqa            = %u\n",     __func__, hparams.n_gqa());
@@ -7775,17 +7783,18 @@ struct llm_build_context {
 
         ctx0 = ggml_init(params);
 
-        lctx.inp_tokens  = nullptr;
-        lctx.inp_embd    = nullptr;
-        lctx.inp_pos     = nullptr;
-        lctx.inp_out_ids = nullptr;
-        lctx.inp_KQ_mask = nullptr;
-        lctx.inp_K_shift = nullptr;
-        lctx.inp_mean    = nullptr;
-        lctx.inp_cls     = nullptr;
-        lctx.inp_s_copy  = nullptr;
-        lctx.inp_s_mask  = nullptr;
-        lctx.inp_s_seq   = nullptr;
+        lctx.inp_tokens      = nullptr;
+        lctx.inp_embd        = nullptr;
+        lctx.inp_pos         = nullptr;
+        lctx.inp_out_ids     = nullptr;
+        lctx.inp_KQ_mask     = nullptr;
+        lctx.inp_KQ_mask_swa = nullptr;
+        lctx.inp_K_shift     = nullptr;
+        lctx.inp_mean        = nullptr;
+        lctx.inp_cls         = nullptr;
+        lctx.inp_s_copy      = nullptr;
+        lctx.inp_s_mask      = nullptr;
+        lctx.inp_s_seq       = nullptr;
     }
 
     void free() {
@@ -7804,7 +7813,6 @@ struct llm_build_context {
         cb(lctx.inp_K_shift, "K_shift", -1);
         ggml_set_input(lctx.inp_K_shift);
 
-
         for (int il = 0; il < n_layer; ++il) {
             struct ggml_tensor * rope_factors = build_rope_factors(il);
             struct ggml_tensor * tmp =
@@ -7939,16 +7947,27 @@ struct llm_build_context {
     }
 
     struct ggml_tensor * build_inp_KQ_mask(bool causal = true) {
-        if (causal) {
-            lctx.inp_KQ_mask = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_kv,     GGML_PAD(n_tokens, GGML_KQ_MASK_PAD));
-        } else {
-            lctx.inp_KQ_mask = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_tokens, GGML_PAD(n_tokens, GGML_KQ_MASK_PAD));
-        }
+        lctx.inp_KQ_mask = causal
+            ? ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_kv,     GGML_PAD(n_tokens, GGML_KQ_MASK_PAD))
+            : ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_tokens, GGML_PAD(n_tokens, GGML_KQ_MASK_PAD));
         cb(lctx.inp_KQ_mask, "KQ_mask", -1);
         ggml_set_input(lctx.inp_KQ_mask);
+
         return flash_attn ? ggml_cast(ctx0, lctx.inp_KQ_mask, GGML_TYPE_F16) : lctx.inp_KQ_mask;
     }
 
+    struct ggml_tensor * build_inp_KQ_mask_swa(bool causal = true) {
+        GGML_ASSERT(hparams.n_swa > 0);
+
+        lctx.inp_KQ_mask_swa = causal
+            ? ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_kv,     GGML_PAD(n_tokens, GGML_KQ_MASK_PAD))
+            : ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_tokens, GGML_PAD(n_tokens, GGML_KQ_MASK_PAD));
+        cb(lctx.inp_KQ_mask_swa, "KQ_mask_swa", -1);
+        ggml_set_input(lctx.inp_KQ_mask_swa);
+
+        return flash_attn ? ggml_cast(ctx0, lctx.inp_KQ_mask_swa, GGML_TYPE_F16) : lctx.inp_KQ_mask_swa;
+    }
+
     struct ggml_tensor * build_inp_mean() {
         lctx.inp_mean = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_tokens, n_tokens);
         cb(lctx.inp_mean, "inp_mean", -1);
@@ -11029,9 +11048,14 @@ struct llm_build_context {
         struct ggml_tensor * inp_pos = build_inp_pos();
 
         // KQ_mask (mask for 1 head, it will be broadcasted to all heads)
-        struct ggml_tensor * KQ_mask = build_inp_KQ_mask();
+        // gemma 2 requires different mask for layers using sliding window (SWA)
+        struct ggml_tensor * KQ_mask     = build_inp_KQ_mask(true);
+        struct ggml_tensor * KQ_mask_swa = build_inp_KQ_mask_swa(true);
 
         for (int il = 0; il < n_layer; ++il) {
+            // (il % 2) layers use SWA
+            struct ggml_tensor * KQ_mask_l = (il % 2 == 0) ? KQ_mask_swa : KQ_mask;
+
             // norm
             cur = llm_build_norm(ctx0, inpL, hparams,
                     model.layers[il].attn_norm, NULL,
@@ -11067,7 +11091,7 @@ struct llm_build_context {
 
                 cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
                         model.layers[il].wo, NULL,
-                        Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f, cb, il);
+                        Kcur, Vcur, Qcur, KQ_mask_l, n_tokens, kv_head, n_kv, 1.0f, cb, il);
             }
 
             cur = llm_build_norm(ctx0, cur, hparams,
@@ -12670,7 +12694,12 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
 
             GGML_ASSERT(ggml_backend_buffer_is_host(lctx.inp_KQ_mask->buffer));
 
-            float * data = (float *) lctx.inp_KQ_mask->data;
+            float * data     = (float *) lctx.inp_KQ_mask->data;
+            float * data_swa = nullptr;
+
+            if (lctx.inp_KQ_mask_swa) {
+                data_swa = (float *) lctx.inp_KQ_mask_swa->data;
+            }
 
             // For causal attention, use only the previous KV cells
             // of the correct sequence for each token of the batch.
@@ -12692,6 +12721,14 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
                             }
                         }
                         data[h*(n_kv*n_tokens) + j*n_kv + i] = f;
+
+                        // may need to cut off old tokens for sliding window
+                        if (data_swa) {
+                            if (pos - lctx.kv_self.cells[i].pos >= (int32_t)hparams.n_swa) {
+                                f = -INFINITY;
+                            }
+                            data_swa[h*(n_kv*n_tokens) + j*n_kv + i] = f;
+                        }
                     }
                 }
 

From dae57a1ebc1c9bd5693ab999e19d77c5506ae559 Mon Sep 17 00:00:00 2001
From: Mateusz Charytoniuk 
Date: Mon, 1 Jul 2024 19:13:22 +0200
Subject: [PATCH 066/326] readme: add Paddler to the list of projects (#8239)

---
 README.md | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/README.md b/README.md
index daba70717312e..3569b2bbb5e34 100644
--- a/README.md
+++ b/README.md
@@ -220,6 +220,10 @@ Unless otherwise noted these projects are open-source with permissive licensing:
 - [akx/ggify](https://github.com/akx/ggify) – download PyTorch models from HuggingFace Hub and convert them to GGML
 - [crashr/gppm](https://github.com/crashr/gppm) – launch llama.cpp instances utilizing NVIDIA Tesla P40 or P100 GPUs with reduced idle power consumption
 
+**Infrastructure:**
+
+- [Paddler](https://github.com/distantmagic/paddler) - Stateful load balancer custom-tailored for llama.cpp
+
 ---
 
 Here is a typical run using LLaMA v2 13B on M2 Ultra:

From cb5fad4c6c2cbef92e9b8b63449e1cb7664e4846 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= 
Date: Mon, 1 Jul 2024 20:39:06 +0200
Subject: [PATCH 067/326] CUDA: refactor and optimize IQ MMVQ (#8215)

* CUDA: refactor and optimize IQ MMVQ

* uint -> uint32_t

* __dp4a -> ggml_cuda_dp4a

* remove MIN_CC_DP4A checks

* change default

* try CI fix
---
 ggml/src/ggml-common.h              |  14 +-
 ggml/src/ggml-cuda.cu               |  12 +-
 ggml/src/ggml-cuda/common.cuh       |  76 ++-
 ggml/src/ggml-cuda/fattn-common.cuh |  50 +-
 ggml/src/ggml-cuda/mmvq.cu          |  26 +-
 ggml/src/ggml-cuda/vecdotq.cuh      | 688 +++++++++++++---------------
 ggml/src/ggml-sycl/mmvq.cpp         |  12 +-
 ggml/src/ggml-sycl/vecdotq.hpp      |  21 -
 8 files changed, 409 insertions(+), 490 deletions(-)

diff --git a/ggml/src/ggml-common.h b/ggml/src/ggml-common.h
index e8efceb760d40..c74060cc4b991 100644
--- a/ggml/src/ggml-common.h
+++ b/ggml/src/ggml-common.h
@@ -106,19 +106,19 @@ typedef sycl::half2 ggml_half2;
 #define QR6_K 2
 
 #define QI2_XXS (QK_K / (4*QR2_XXS))
-#define QR2_XXS 8
+#define QR2_XXS 4
 
 #define QI2_XS (QK_K / (4*QR2_XS))
-#define QR2_XS 8
+#define QR2_XS 4
 
 #define QI2_S (QK_K / (4*QR2_S))
-#define QR2_S 8
+#define QR2_S 4
 
 #define QI3_XXS (QK_K / (4*QR3_XXS))
-#define QR3_XXS 8
+#define QR3_XXS 4
 
 #define QI3_XS (QK_K / (4*QR3_XS))
-#define QR3_XS 8
+#define QR3_XS 4
 
 #define QI1_S (QK_K / (4*QR1_S))
 #define QR1_S 8
@@ -130,10 +130,10 @@ typedef sycl::half2 ggml_half2;
 #define QR4_NL 2
 
 #define QI4_XS (QK_K / (4*QR4_XS))
-#define QR4_XS 8
+#define QR4_XS 2
 
 #define QI3_S (QK_K / (4*QR3_S))
-#define QR3_S 8
+#define QR3_S 4
 
 #endif // GGML_COMMON_DECL_CUDA || GGML_COMMON_DECL_HIP
 
diff --git a/ggml/src/ggml-cuda.cu b/ggml/src/ggml-cuda.cu
index 0acfda91d3e51..649ef5a081910 100644
--- a/ggml/src/ggml-cuda.cu
+++ b/ggml/src/ggml-cuda.cu
@@ -1882,6 +1882,11 @@ static void ggml_cuda_mul_mat(ggml_backend_cuda_context & ctx, const ggml_tensor
     bool              use_mul_mat_q =  ggml_is_quantized(src0->type)
         && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32;
 
+    // if mmvq is available it's a better choice than dmmv:
+#ifndef GGML_CUDA_FORCE_DMMV
+    use_dequantize_mul_mat_vec = use_dequantize_mul_mat_vec && !use_mul_mat_vec_q;
+#endif // GGML_CUDA_FORCE_DMMV
+
     bool any_gpus_with_slow_fp16 = false;
 
     if (split) {
@@ -1894,22 +1899,15 @@ static void ggml_cuda_mul_mat(ggml_backend_cuda_context & ctx, const ggml_tensor
             }
 
             const int cc            = ggml_cuda_info().devices[id].cc;
-            use_mul_mat_vec_q       = use_mul_mat_vec_q       && cc >= MIN_CC_DP4A;
             use_mul_mat_q           = use_mul_mat_q           && ggml_cuda_should_use_mmq(src0->type, cc, src1->ne[1]);
             any_gpus_with_slow_fp16 = any_gpus_with_slow_fp16 || !fast_fp16_available(cc);
         }
     } else {
         const int cc            = ggml_cuda_info().devices[ctx.device].cc;
-        use_mul_mat_vec_q       = use_mul_mat_vec_q       && cc >= MIN_CC_DP4A;
         use_mul_mat_q           = use_mul_mat_q           && ggml_cuda_should_use_mmq(src0->type, cc, src1->ne[1]);
         any_gpus_with_slow_fp16 = any_gpus_with_slow_fp16 || !fast_fp16_available(cc);
     }
 
-    // if mmvq is available it's a better choice than dmmv:
-#ifndef GGML_CUDA_FORCE_DMMV
-    use_dequantize_mul_mat_vec = use_dequantize_mul_mat_vec && !use_mul_mat_vec_q;
-#endif // GGML_CUDA_FORCE_DMMV
-
     // debug helpers
     //printf("src0: %8d %8d %8d %8d\n", src0->ne[0], src0->ne[1], src0->ne[2], src0->ne[3]);
     //printf("      %8d %8d %8d %8d\n", src0->nb[0], src0->nb[1], src0->nb[2], src0->nb[3]);
diff --git a/ggml/src/ggml-cuda/common.cuh b/ggml/src/ggml-cuda/common.cuh
index 8d00db6c193ff..472f4ace1c2ad 100644
--- a/ggml/src/ggml-cuda/common.cuh
+++ b/ggml/src/ggml-cuda/common.cuh
@@ -3,6 +3,7 @@
 #include "ggml.h"
 #include "ggml-cuda.h"
 
+#include 
 #include 
 
 #if defined(GGML_USE_HIPBLAS)
@@ -268,30 +269,15 @@ static __device__ __forceinline__ unsigned int __vcmpeq4(unsigned int a, unsigne
     return c;
 }
 
-static __device__ __forceinline__ int __dp4a(const int a, const int b, int c) {
-#if defined(__gfx906__) || defined(__gfx908__) || defined(__gfx90a__) || defined(__gfx1030__)
-    c = __builtin_amdgcn_sdot4(a, b, c, false);
-#elif defined(RDNA3)
-    c = __builtin_amdgcn_sudot4( true, a, true, b, c, false);
-#elif defined(__gfx1010__) || defined(__gfx900__)
-    int tmp1;
-    int tmp2;
-    asm("\n \
-        v_mul_i32_i24 %1, sext(%3), sext(%4) dst_sel:DWORD dst_unused:UNUSED_PAD src0_sel:BYTE_0 src1_sel:BYTE_0 \n \
-        v_mul_i32_i24 %2, sext(%3), sext(%4) dst_sel:DWORD dst_unused:UNUSED_PAD src0_sel:BYTE_1 src1_sel:BYTE_1 \n \
-        v_add3_u32 %0, %1, %2, %0 \n \
-        v_mul_i32_i24 %1, sext(%3), sext(%4) dst_sel:DWORD dst_unused:UNUSED_PAD src0_sel:BYTE_2 src1_sel:BYTE_2 \n \
-        v_mul_i32_i24 %2, sext(%3), sext(%4) dst_sel:DWORD dst_unused:UNUSED_PAD src0_sel:BYTE_3 src1_sel:BYTE_3 \n \
-        v_add3_u32 %0, %1, %2, %0 \n \
-        "
-        : "+v"(c), "=&v"(tmp1), "=&v"(tmp2)
-        : "v"(a), "v"(b)
-    );
-#else
-    const int8x4_t va = reinterpret_cast(a);
-    const int8x4_t vb = reinterpret_cast(b);
-    c += va[0] * vb[0] + va[1] * vb[1] + va[2] * vb[2] + va[3] * vb[3];
-#endif
+static __device__ __forceinline__ unsigned int __vcmpne4(unsigned int a, unsigned int b) {
+    const uint8x4_t& va = reinterpret_cast(a);
+    const uint8x4_t& vb = reinterpret_cast(b);
+    unsigned int c;
+    uint8x4_t& vc = reinterpret_cast(c);
+#pragma unroll
+    for (int i = 0; i < 4; ++i) {
+        vc[i] = va[i] == vb[i] ? 0x00 : 0xff;
+    }
     return c;
 }
 
@@ -467,8 +453,48 @@ static __device__ __forceinline__ uint32_t __hgt2_mask(const half2 a, const half
 }
 #endif // CUDART_VERSION < 12000
 
+static __device__ __forceinline__ int ggml_cuda_dp4a(const int a, const int b, int c) {
+#if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
+#if defined(__gfx906__) || defined(__gfx908__) || defined(__gfx90a__) || defined(__gfx1030__)
+    c = __builtin_amdgcn_sdot4(a, b, c, false);
+#elif defined(RDNA3)
+    c = __builtin_amdgcn_sudot4( true, a, true, b, c, false);
+#elif defined(__gfx1010__) || defined(__gfx900__)
+    int tmp1;
+    int tmp2;
+    asm("\n \
+        v_mul_i32_i24 %1, sext(%3), sext(%4) dst_sel:DWORD dst_unused:UNUSED_PAD src0_sel:BYTE_0 src1_sel:BYTE_0 \n \
+        v_mul_i32_i24 %2, sext(%3), sext(%4) dst_sel:DWORD dst_unused:UNUSED_PAD src0_sel:BYTE_1 src1_sel:BYTE_1 \n \
+        v_add3_u32 %0, %1, %2, %0 \n \
+        v_mul_i32_i24 %1, sext(%3), sext(%4) dst_sel:DWORD dst_unused:UNUSED_PAD src0_sel:BYTE_2 src1_sel:BYTE_2 \n \
+        v_mul_i32_i24 %2, sext(%3), sext(%4) dst_sel:DWORD dst_unused:UNUSED_PAD src0_sel:BYTE_3 src1_sel:BYTE_3 \n \
+        v_add3_u32 %0, %1, %2, %0 \n \
+        "
+        : "+v"(c), "=&v"(tmp1), "=&v"(tmp2)
+        : "v"(a), "v"(b)
+    );
+#else
+    const int8x4_t va = reinterpret_cast(a);
+    const int8x4_t vb = reinterpret_cast(b);
+    c += va[0] * vb[0] + va[1] * vb[1] + va[2] * vb[2] + va[3] * vb[3];
+#endif
+    return c;
+
+#else // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
+
+#if __CUDA_ARCH__ >= MIN_CC_DP4A
+    return __dp4a(a, b, c);
+#else // __CUDA_ARCH__ >= MIN_CC_DP4A
+    const int8_t * a8 = (const int8_t *) &a;
+    const int8_t * b8 = (const int8_t *) &b;
+    return c + a8[0]*b8[0] + a8[1]*b8[1] + a8[2]*b8[2] + a8[3]*b8[3];
+#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
+
+#endif // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
+}
+
 // TODO: move to ggml-common.h
-static const __device__ int8_t kvalues_iq4nl[16] = {-127, -104, -83, -65, -49, -35, -22, -10, 1, 13, 25, 38, 53, 69, 89, 113};
+static constexpr __device__ int8_t kvalues_iq4nl[16] = {-127, -104, -83, -65, -49, -35, -22, -10, 1, 13, 25, 38, 53, 69, 89, 113};
 
 typedef void (*dequantize_kernel_t)(const void * vx, const int64_t ib, const int iqs, dfloat2 & v);
 
diff --git a/ggml/src/ggml-cuda/fattn-common.cuh b/ggml/src/ggml-cuda/fattn-common.cuh
index bd7993595467c..650780fd2e462 100644
--- a/ggml/src/ggml-cuda/fattn-common.cuh
+++ b/ggml/src/ggml-cuda/fattn-common.cuh
@@ -54,12 +54,11 @@ typedef float (*vec_dot_KQ_f32_t)(
 template
 static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q4_0(
     const char * __restrict__ K_c, const void * __restrict__ Q_v, const int * __restrict__ Q_q8, const void * __restrict__ Q_ds_v) {
-#if __CUDA_ARCH__ >= MIN_CC_DP4A
 
     const block_q4_0 * K_q4_0 = (const block_q4_0 *) K_c;
     GGML_UNUSED(Q_v);
 
-    half sum = 0.0f;
+    T sum = 0.0f;
 
 #pragma unroll
     for (int k_KQ_0 = 0; k_KQ_0 < D/sizeof(int); k_KQ_0 += WARP_SIZE) {
@@ -72,7 +71,7 @@ static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q4_0(
         const int v = (get_int_from_uint8(K_q4_0[ib].qs, iqs4) >> shift) & 0x0F0F0F0F;
         const int u = Q_q8[k_KQ_0/WARP_SIZE];
 
-        const int sumi = __dp4a(v, u, 0);
+        const int sumi = ggml_cuda_dp4a(v, u, 0);
 
 #ifdef FP16_AVAILABLE
         if (std::is_same::value) {
@@ -90,19 +89,11 @@ static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q4_0(
     }
 
     return sum;
-#else
-    GGML_UNUSED(K_c);
-    GGML_UNUSED(Q_v);
-    GGML_UNUSED(Q_q8);
-    GGML_UNUSED(Q_ds_v);
-    NO_DEVICE_CODE;
-#endif  // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 template
 static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q4_1(
     const char * __restrict__ K_c, const void * __restrict__ Q_v, const int * __restrict__ Q_q8, const void * __restrict__ Q_ds_v) {
-#if __CUDA_ARCH__ >= MIN_CC_DP4A
 
     const block_q4_1 * K_q4_1 = (const block_q4_1 *) K_c;
     GGML_UNUSED(Q_v);
@@ -120,7 +111,7 @@ static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q4_1(
         const int v = (get_int_from_uint8_aligned(K_q4_1[ib].qs, iqs4) >> shift) & 0x0F0F0F0F;
         const int u = Q_q8[k_KQ_0/WARP_SIZE];
 
-        const int sumi = __dp4a(v, u, 0);
+        const int sumi = ggml_cuda_dp4a(v, u, 0);
 
 #ifdef FP16_AVAILABLE
         if (std::is_same::value) {
@@ -142,19 +133,11 @@ static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q4_1(
     }
 
     return sum;
-#else
-    GGML_UNUSED(K_c);
-    GGML_UNUSED(Q_v);
-    GGML_UNUSED(Q_q8);
-    GGML_UNUSED(Q_ds_v);
-    NO_DEVICE_CODE;
-#endif  // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 template
 static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q5_0(
     const char * __restrict__ K_c, const void * __restrict__ Q_v, const int * __restrict__ Q_q8, const void * __restrict__ Q_ds_v) {
-#if __CUDA_ARCH__ >= MIN_CC_DP4A
 
     const block_q5_0 * K_q5_0 = (const block_q5_0 *) K_c;
     GGML_UNUSED(Q_v);
@@ -179,7 +162,7 @@ static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q5_0(
 
         const int u = Q_q8[k_KQ_0/WARP_SIZE];
 
-        const int sumi = __dp4a(v, u, 0);
+        const int sumi = ggml_cuda_dp4a(v, u, 0);
 
 #ifdef FP16_AVAILABLE
         if (std::is_same::value) {
@@ -197,19 +180,11 @@ static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q5_0(
     }
 
     return sum;
-#else
-    GGML_UNUSED(K_c);
-    GGML_UNUSED(Q_v);
-    GGML_UNUSED(Q_q8);
-    GGML_UNUSED(Q_ds_v);
-    NO_DEVICE_CODE;
-#endif  // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 template
 static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q5_1(
     const char * __restrict__ K_c, const void * __restrict__ Q_v, const int * __restrict__ Q_q8, const void * __restrict__ Q_ds_v) {
-#if __CUDA_ARCH__ >= MIN_CC_DP4A
 
     const block_q5_1 * K_q5_1 = (const block_q5_1 *) K_c;
     GGML_UNUSED(Q_v);
@@ -234,7 +209,7 @@ static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q5_1(
 
         const int u = Q_q8[k_KQ_0/WARP_SIZE];
 
-        const int sumi = __dp4a(v, u, 0);
+        const int sumi = ggml_cuda_dp4a(v, u, 0);
 
 #ifdef FP16_AVAILABLE
         if (std::is_same::value) {
@@ -256,19 +231,11 @@ static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q5_1(
     }
 
     return sum;
-#else
-    GGML_UNUSED(K_c);
-    GGML_UNUSED(Q_v);
-    GGML_UNUSED(Q_q8);
-    GGML_UNUSED(Q_ds_v);
-    NO_DEVICE_CODE;
-#endif  // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 template 
 static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q8_0(
     const char * __restrict__ K_c, const void * __restrict__ Q_v, const int * __restrict__ Q_q8, const void * __restrict__ Q_ds_v) {
-#if __CUDA_ARCH__ >= MIN_CC_DP4A
 
     const block_q8_0 * K_q8_0 = (const block_q8_0 *) K_c;
     GGML_UNUSED(Q_v);
@@ -297,13 +264,6 @@ static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q8_0(
     }
 
     return sum;
-#else
-    GGML_UNUSED(K_c);
-    GGML_UNUSED(Q_v);
-    GGML_UNUSED(Q_q8);
-    GGML_UNUSED(Q_ds_v);
-    NO_DEVICE_CODE;
-#endif  // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 template 
diff --git a/ggml/src/ggml-cuda/mmvq.cu b/ggml/src/ggml-cuda/mmvq.cu
index e8d157169544f..e22faf69b7287 100644
--- a/ggml/src/ggml-cuda/mmvq.cu
+++ b/ggml/src/ggml-cuda/mmvq.cu
@@ -28,16 +28,22 @@ static constexpr __device__ vec_dot_q_cuda_t get_vec_dot_q_cuda(ggml_type type)
 
 static constexpr __device__ int get_vdr_mmvq(ggml_type type) {
     return type == GGML_TYPE_Q4_0 ? VDR_Q4_0_Q8_1_MMVQ :
-        type == GGML_TYPE_Q4_1 ? VDR_Q4_1_Q8_1_MMVQ :
-        type == GGML_TYPE_Q5_0 ? VDR_Q5_0_Q8_1_MMVQ :
-        type == GGML_TYPE_Q5_1 ? VDR_Q5_1_Q8_1_MMVQ :
-        type == GGML_TYPE_Q8_0 ? VDR_Q8_0_Q8_1_MMVQ :
-        type == GGML_TYPE_Q2_K ? VDR_Q2_K_Q8_1_MMVQ :
-        type == GGML_TYPE_Q3_K ? VDR_Q3_K_Q8_1_MMVQ :
-        type == GGML_TYPE_Q4_K ? VDR_Q4_K_Q8_1_MMVQ :
-        type == GGML_TYPE_Q5_K ? VDR_Q5_K_Q8_1_MMVQ :
-        type == GGML_TYPE_Q6_K ? VDR_Q6_K_Q8_1_MMVQ :
-        type == GGML_TYPE_IQ4_NL ? VDR_Q4_K_Q8_1_MMVQ :
+        type == GGML_TYPE_Q4_1    ? VDR_Q4_1_Q8_1_MMVQ :
+        type == GGML_TYPE_Q5_0    ? VDR_Q5_0_Q8_1_MMVQ :
+        type == GGML_TYPE_Q5_1    ? VDR_Q5_1_Q8_1_MMVQ :
+        type == GGML_TYPE_Q8_0    ? VDR_Q8_0_Q8_1_MMVQ :
+        type == GGML_TYPE_Q2_K    ? VDR_Q2_K_Q8_1_MMVQ :
+        type == GGML_TYPE_Q3_K    ? VDR_Q3_K_Q8_1_MMVQ :
+        type == GGML_TYPE_Q4_K    ? VDR_Q4_K_Q8_1_MMVQ :
+        type == GGML_TYPE_Q5_K    ? VDR_Q5_K_Q8_1_MMVQ :
+        type == GGML_TYPE_Q6_K    ? VDR_Q6_K_Q8_1_MMVQ :
+        type == GGML_TYPE_IQ2_XXS ? VDR_IQ2_XXS_Q8_1_MMVQ :
+        type == GGML_TYPE_IQ2_XS  ? VDR_IQ2_XS_Q8_1_MMVQ :
+        type == GGML_TYPE_IQ2_S   ? VDR_IQ2_S_Q8_1_MMVQ :
+        type == GGML_TYPE_IQ3_XXS ? VDR_IQ3_XXS_Q8_1_MMVQ :
+        type == GGML_TYPE_IQ3_S   ? VDR_IQ3_S_Q8_1_MMVQ :
+        type == GGML_TYPE_IQ4_NL  ? VDR_IQ4_NL_Q8_1_MMVQ :
+        type == GGML_TYPE_IQ4_XS  ? VDR_IQ4_XS_Q8_1_MMVQ :
         1;
 }
 
diff --git a/ggml/src/ggml-cuda/vecdotq.cuh b/ggml/src/ggml-cuda/vecdotq.cuh
index 3b12d656616be..3f3a87c750b21 100644
--- a/ggml/src/ggml-cuda/vecdotq.cuh
+++ b/ggml/src/ggml-cuda/vecdotq.cuh
@@ -1,4 +1,5 @@
 #include "common.cuh"
+#include 
 
 static __device__ __forceinline__ int get_int_from_int8(const int8_t * x8, const int & i32) {
     const uint16_t * x16 = (const uint16_t *) (x8 + sizeof(int) * i32); // assume at least 2 byte alignment
@@ -28,6 +29,18 @@ static __device__ __forceinline__ int get_int_from_uint8_aligned(const uint8_t *
     return *((const int *) (x8 + sizeof(int) * i32)); // assume at least 4 byte alignment
 }
 
+static __device__ __forceinline__ int get_int_b2(const void * x, const int & i32) {
+    const uint16_t * x16 = (const uint16_t *) x;
+
+    int x32  = x16[2*i32 + 0] <<  0;
+    x32     |= x16[2*i32 + 1] << 16;
+
+    return x32;
+}
+
+static __device__ __forceinline__ int get_int_b4(const void * x, const int & i32) {
+    return ((const int *) x)[i32]; // assume at least 4 byte alignment
+}
 
 // VDR = vec dot ratio, how many contiguous integers each thread processes when the vec dot kernel is called
 // MMVQ = mul_mat_vec_q, MMQ = mul_mat_q
@@ -38,7 +51,6 @@ static __device__ __forceinline__ int get_int_from_uint8_aligned(const uint8_t *
 template  static __device__ __forceinline__ float vec_dot_q4_0_q8_1_impl(
     const int * v, const int * u, const float & d4, const half2 & ds8) {
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     int sumi = 0;
 
 #pragma unroll
@@ -47,17 +59,14 @@ template  static __device__ __forceinline__ float vec_dot_q4_0_q8_1_imp
         const int vi1 = (v[i] >> 4) & 0x0F0F0F0F;
 
         // SIMD dot product of quantized values
-        sumi = __dp4a(vi0, u[2*i+0], sumi);
-        sumi = __dp4a(vi1, u[2*i+1], sumi);
+        sumi = ggml_cuda_dp4a(vi0, u[2*i+0], sumi);
+        sumi = ggml_cuda_dp4a(vi1, u[2*i+1], sumi);
     }
 
     const float2 ds8f = __half22float2(ds8);
 
     // second part effectively subtracts 8 from each quant value
     return d4 * (sumi * ds8f.x - (8*vdr/QI4_0) * ds8f.y);
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 #define VDR_Q4_1_Q8_1_MMVQ 2
@@ -66,7 +75,6 @@ template  static __device__ __forceinline__ float vec_dot_q4_0_q8_1_imp
 template  static __device__ __forceinline__ float vec_dot_q4_1_q8_1_impl(
     const int * v, const int * u, const half2 & dm4, const half2 & ds8) {
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     int sumi = 0;
 
 #pragma unroll
@@ -75,8 +83,8 @@ template  static __device__ __forceinline__ float vec_dot_q4_1_q8_1_imp
         const int vi1 = (v[i] >> 4) & 0x0F0F0F0F;
 
         // SIMD dot product of quantized values
-        sumi = __dp4a(vi0, u[2*i+0], sumi);
-        sumi = __dp4a(vi1, u[2*i+1], sumi);
+        sumi = ggml_cuda_dp4a(vi0, u[2*i+0], sumi);
+        sumi = ggml_cuda_dp4a(vi1, u[2*i+1], sumi);
     }
 
 #ifdef GGML_CUDA_F16
@@ -92,9 +100,6 @@ template  static __device__ __forceinline__ float vec_dot_q4_1_q8_1_imp
 
     // scale second part of sum by QI8_1/(vdr * QR4_1) to compensate for multiple threads adding it
     return sumi * d4d8 + m4s8 / (QI8_1 / (vdr * QR4_1));
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 #define VDR_Q5_0_Q8_1_MMVQ 2
@@ -103,7 +108,6 @@ template  static __device__ __forceinline__ float vec_dot_q4_1_q8_1_imp
 template  static __device__ __forceinline__ float vec_dot_q5_0_q8_1_impl(
     const int * vl, const int * vh, const int * u, const float & d5, const half2 & ds8) {
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     int sumi = 0;
 
 #pragma unroll
@@ -113,23 +117,20 @@ template  static __device__ __forceinline__ float vec_dot_q5_0_q8_1_imp
         vi0    |= (vh[i] << 11) & 0x00001000; // 1 -> 12
         vi0    |= (vh[i] << 18) & 0x00100000; // 2 -> 20
         vi0    |= (vh[i] << 25) & 0x10000000; // 3 -> 28
-        sumi = __dp4a(vi0, u[2*i+0], sumi); // SIMD dot product of quantized values
+        sumi = ggml_cuda_dp4a(vi0, u[2*i+0], sumi); // SIMD dot product of quantized values
 
         int vi1 = (vl[i] >>  4) & 0x0F0F0F0F; // upper 4 qs bits, still need qh as 5th bits
         vi1    |= (vh[i] >> 12) & 0x00000010; // 16 ->  4
         vi1    |= (vh[i] >>  5) & 0x00001000; // 17 -> 12
         vi1    |= (vh[i] <<  2) & 0x00100000; // 18 -> 20
         vi1    |= (vh[i] <<  9) & 0x10000000; // 19 -> 28
-        sumi = __dp4a(vi1, u[2*i+1], sumi); // SIMD dot product of quantized values
+        sumi = ggml_cuda_dp4a(vi1, u[2*i+1], sumi); // SIMD dot product of quantized values
     }
 
     const float2 ds8f = __half22float2(ds8);
 
     // second part effectively subtracts 16 from each quant value
     return d5 * (sumi * ds8f.x - (16*vdr/QI5_0) * ds8f.y);
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 #define VDR_Q5_1_Q8_1_MMVQ 2
@@ -138,7 +139,6 @@ template  static __device__ __forceinline__ float vec_dot_q5_0_q8_1_imp
 template  static __device__ __forceinline__ float vec_dot_q5_1_q8_1_impl(
     const int * vl, const int * vh, const int * u, const half2 & dm5, const half2 & ds8) {
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     int sumi = 0;
 
 #pragma unroll
@@ -148,14 +148,14 @@ template  static __device__ __forceinline__ float vec_dot_q5_1_q8_1_imp
         vi0    |= (vh[i] << 11) & 0x00001000; // 1 -> 12
         vi0    |= (vh[i] << 18) & 0x00100000; // 2 -> 20
         vi0    |= (vh[i] << 25) & 0x10000000; // 3 -> 28
-        sumi = __dp4a(vi0, u[2*i+0], sumi); // SIMD dot product of quantized values
+        sumi = ggml_cuda_dp4a(vi0, u[2*i+0], sumi); // SIMD dot product of quantized values
 
         int vi1 = (vl[i] >>  4) & 0x0F0F0F0F; // upper 4 qs bits, still need qh as 5th bits
         vi1    |= (vh[i] >> 12) & 0x00000010; // 16 ->  4
         vi1    |= (vh[i] >>  5) & 0x00001000; // 17 -> 12
         vi1    |= (vh[i] <<  2) & 0x00100000; // 18 -> 20
         vi1    |= (vh[i] <<  9) & 0x10000000; // 19 -> 28
-        sumi = __dp4a(vi1, u[2*i+1], sumi); // SIMD dot product of quantized values
+        sumi = ggml_cuda_dp4a(vi1, u[2*i+1], sumi); // SIMD dot product of quantized values
     }
 
 #ifdef GGML_CUDA_F16
@@ -171,10 +171,6 @@ template  static __device__ __forceinline__ float vec_dot_q5_1_q8_1_imp
 
     // scale second part of sum by QI5_1 / vdr to compensate for multiple threads adding it
     return sumi*d5d8 + m5s8 / (QI5_1 / vdr);
-
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 #define VDR_Q8_0_Q8_1_MMVQ 2
@@ -183,31 +179,26 @@ template  static __device__ __forceinline__ float vec_dot_q5_1_q8_1_imp
 template  static __device__ __forceinline__ T vec_dot_q8_0_q8_1_impl(
     const int * v, const int * u, const T & d8_0, const T & d8_1) {
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     int sumi = 0;
 
 #pragma unroll
     for (int i = 0; i < vdr; ++i) {
         // SIMD dot product of quantized values
-        sumi = __dp4a(v[i], u[i], sumi);
+        sumi = ggml_cuda_dp4a(v[i], u[i], sumi);
     }
 
     return d8_0*d8_1 * ((T) sumi);
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 template  static __device__ __forceinline__ float vec_dot_q8_1_q8_1_impl(
     const int * v, const int * u, const half2 & dm8, const half2 & ds8) {
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     int sumi = 0;
 
 #pragma unroll
     for (int i = 0; i < vdr; ++i) {
         // SIMD dot product of quantized values
-        sumi = __dp4a(v[i], u[i], sumi);
+        sumi = ggml_cuda_dp4a(v[i], u[i], sumi);
     }
 
 #ifdef GGML_CUDA_F16
@@ -223,9 +214,6 @@ template  static __device__ __forceinline__ float vec_dot_q8_1_q8_1_imp
 
     // scale second part of sum by QI8_1/ vdr to compensate for multiple threads adding it
     return sumi*d8d8 + m8s8 / (QI8_1 / vdr);
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 #define VDR_Q2_K_Q8_1_MMVQ 1
@@ -236,7 +224,6 @@ static __device__ __forceinline__ float vec_dot_q2_K_q8_1_impl_mmvq(
     const int & v, const int * __restrict__ u, const uint8_t * __restrict__ scales,
     const half2 & dm2, const float * __restrict__ d8) {
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     float sumf_d = 0.0f;
     float sumf_m = 0.0f;
 
@@ -246,28 +233,24 @@ static __device__ __forceinline__ float vec_dot_q2_K_q8_1_impl_mmvq(
 
         const int vi = (v >> (2*i)) & 0x03030303;
 
-        sumf_d += d8[i] * (__dp4a(vi, u[i], 0) * (sc & 0xF)); // SIMD dot product
+        sumf_d += d8[i] * (ggml_cuda_dp4a(vi, u[i], 0) * (sc & 0xF)); // SIMD dot product
 
         // fill int with 4x m
         int m = sc >> 4;
         m |= m <<  8;
         m |= m << 16;
-        sumf_m += d8[i] * __dp4a(m, u[i], 0); // multiply constant q2_K part with sum of q8_1 values
+        sumf_m += d8[i] * ggml_cuda_dp4a(m, u[i], 0); // multiply constant q2_K part with sum of q8_1 values
     }
 
     const float2 dm2f = __half22float2(dm2);
 
     return dm2f.x*sumf_d - dm2f.y*sumf_m;
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 // contiguous u/y values
 static __device__ __forceinline__ float vec_dot_q2_K_q8_1_impl_mmq(
     const int * __restrict__ v, const int * __restrict__ u, const half2 * dm2, const float & d8) {
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     float sumf_d = 0.0f;
     float sumf_m = 0.0f;
 
@@ -281,8 +264,8 @@ static __device__ __forceinline__ float vec_dot_q2_K_q8_1_impl_mmq(
 #pragma unroll
         for (int i = i0; i < i0 + QI8_1/2; ++i) {
             const int vi = (vi0 >> (2*(i % (QI8_1/2)))) & 0x03030303;
-            sumi_d = __dp4a(vi,         u[i], sumi_d); // SIMD dot product
-            sumi_m = __dp4a(0x01010101, u[i], sumi_m);
+            sumi_d = ggml_cuda_dp4a(vi,         u[i], sumi_d); // SIMD dot product
+            sumi_m = ggml_cuda_dp4a(0x01010101, u[i], sumi_m);
         }
 
         sumf_d += dm2f.x * sumi_d;
@@ -290,9 +273,6 @@ static __device__ __forceinline__ float vec_dot_q2_K_q8_1_impl_mmq(
     }
 
     return d8*(sumf_d - sumf_m);
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 #define VDR_Q3_K_Q8_1_MMVQ 1
@@ -303,7 +283,6 @@ static __device__ __forceinline__ float vec_dot_q3_K_q8_1_impl_mmvq(
     const int & vl, const int & vh, const int * __restrict__ u, const uint8_t * __restrict__ scales,
     const int & scale_offset, const float & d3, const float * __restrict__ d8) {
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     float sumf = 0.0f;
 
 #pragma unroll
@@ -326,13 +305,10 @@ static __device__ __forceinline__ float vec_dot_q3_K_q8_1_impl_mmvq(
 
         const int vi = __vsubss4(vil, vih);
 
-        sumf += d8[i] * (__dp4a(vi, u[i], 0) * sc); // SIMD dot product
+        sumf += d8[i] * (ggml_cuda_dp4a(vi, u[i], 0) * sc); // SIMD dot product
     }
 
     return d3 * sumf;
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 // contiguous u/y values
@@ -340,7 +316,6 @@ static __device__ __forceinline__ float vec_dot_q3_K_q8_1_impl_mmq(
     const int * __restrict__ v, const int * __restrict__ u, const int8_t * __restrict__ scales,
     const float & d3, const float & d8) {
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     int sumi = 0;
 
 #pragma unroll
@@ -350,16 +325,13 @@ static __device__ __forceinline__ float vec_dot_q3_K_q8_1_impl_mmq(
 #pragma unroll
         for (int i = i0; i < i0 + QI8_1/2; ++i) {
             const int vi = __vsubss4((v[i/2] >> (4*(i%2))) & 0x0F0F0F0F, 0x04040404);
-            sumi_sc = __dp4a(vi, u[i], sumi_sc); // SIMD dot product
+            sumi_sc = ggml_cuda_dp4a(vi, u[i], sumi_sc); // SIMD dot product
         }
 
         sumi += sumi_sc * scales[i0 / (QI8_1/2)];
     }
 
     return d3*d8 * sumi;
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 #define VDR_Q4_K_Q8_1_MMVQ 2
@@ -370,7 +342,6 @@ static __device__ __forceinline__ float vec_dot_q4_K_q8_1_impl_vmmq(
     const int * __restrict__ v, const int * __restrict__ u, const uint8_t * __restrict__ sc,
     const uint8_t * __restrict__ m, const half2 & dm4, const float * __restrict__ d8) {
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     float sumf_d = 0.0f;
     float sumf_m = 0.0f;
 
@@ -379,8 +350,8 @@ static __device__ __forceinline__ float vec_dot_q4_K_q8_1_impl_vmmq(
         const int v0i = (v[0] >> (4*i)) & 0x0F0F0F0F;
         const int v1i = (v[1] >> (4*i)) & 0x0F0F0F0F;
 
-        const int dot1 = __dp4a(v1i, u[2*i+1], __dp4a(v0i, u[2*i+0], 0)); // SIMD dot product
-        const int dot2 = __dp4a(0x01010101, u[2*i+1], __dp4a(0x01010101, u[2*i+0], 0)); // sum of u
+        const int dot1 = ggml_cuda_dp4a(v1i, u[2*i+1], ggml_cuda_dp4a(v0i, u[2*i+0], 0)); // SIMD dot product
+        const int dot2 = ggml_cuda_dp4a(0x01010101, u[2*i+1], ggml_cuda_dp4a(0x01010101, u[2*i+0], 0)); // sum of u
 
         sumf_d += d8[i] * (dot1 * sc[i]);
         sumf_m += d8[i] * (dot2 * m[i]);  // multiply constant part of q4_K with sum of q8_1 values
@@ -389,10 +360,6 @@ static __device__ __forceinline__ float vec_dot_q4_K_q8_1_impl_vmmq(
     const float2 dm4f = __half22float2(dm4);
 
     return dm4f.x*sumf_d - dm4f.y*sumf_m;
-
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 // contiguous u/y values
@@ -400,7 +367,6 @@ static __device__ __forceinline__ float vec_dot_q4_K_q8_1_impl_mmq(
     const int * __restrict__ v, const int * __restrict__ u, const uint8_t * __restrict__ sc,
     const uint8_t * __restrict__ m, const half2 & dm4, const half2 * __restrict__ ds8) {
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     float sumf_d = 0.0f;
     float sumf_m = 0.0f;
 
@@ -410,7 +376,7 @@ static __device__ __forceinline__ float vec_dot_q4_K_q8_1_impl_mmq(
 
 #pragma unroll
         for (int j = 0; j < QI8_1; ++j) {
-            sumi_d = __dp4a((v[j] >> (4*i)) & 0x0F0F0F0F, u[i*QI8_1 + j], sumi_d); // SIMD dot product
+            sumi_d = ggml_cuda_dp4a((v[j] >> (4*i)) & 0x0F0F0F0F, u[i*QI8_1 + j], sumi_d); // SIMD dot product
         }
 
         const float2 ds8f = __half22float2(ds8[i]);
@@ -422,10 +388,6 @@ static __device__ __forceinline__ float vec_dot_q4_K_q8_1_impl_mmq(
     const float2 dm4f = __half22float2(dm4);
 
     return dm4f.x*sumf_d - dm4f.y*sumf_m;
-
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 #define VDR_Q5_K_Q8_1_MMVQ 2
@@ -436,7 +398,6 @@ static __device__ __forceinline__ float vec_dot_q5_K_q8_1_impl_vmmq(
     const int * __restrict__ vl, const int * __restrict__ vh, const int * __restrict__ u, const uint8_t * __restrict__ sc,
     const uint8_t * __restrict__ m, const half2 & dm5, const float * __restrict__ d8) {
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     float sumf_d = 0.0f;
     float sumf_m = 0.0f;
 
@@ -451,8 +412,8 @@ static __device__ __forceinline__ float vec_dot_q5_K_q8_1_impl_vmmq(
         const int v0i = vl0i | vh0i;
         const int v1i = vl1i | vh1i;
 
-        const int dot1 = __dp4a(v0i, u[2*i+0], __dp4a(v1i, u[2*i+1], 0)); // SIMD dot product
-        const int dot2 = __dp4a(0x01010101, u[2*i+0], __dp4a(0x01010101, u[2*i+1], 0)); // sum of u
+        const int dot1 = ggml_cuda_dp4a(v0i, u[2*i+0], ggml_cuda_dp4a(v1i, u[2*i+1], 0)); // SIMD dot product
+        const int dot2 = ggml_cuda_dp4a(0x01010101, u[2*i+0], ggml_cuda_dp4a(0x01010101, u[2*i+1], 0)); // sum of u
 
         sumf_d += d8[i] * (dot1 * sc[i]);
         sumf_m += d8[i] * (dot2 * m[i]);
@@ -462,10 +423,6 @@ static __device__ __forceinline__ float vec_dot_q5_K_q8_1_impl_vmmq(
     const float2 dm5f = __half22float2(dm5);
 
     return dm5f.x*sumf_d - dm5f.y*sumf_m;
-
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 // contiguous u/y values
@@ -473,7 +430,6 @@ static __device__ __forceinline__ float vec_dot_q5_K_q8_1_impl_mmq(
     const int * __restrict__ v, const int * __restrict__ u, const uint8_t * __restrict__ sc,
     const uint8_t * __restrict__ m, const half2 & dm4, const half2 * __restrict__ ds8) {
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     float sumf_d = 0.0f;
     float sumf_m = 0.0f;
 
@@ -483,7 +439,7 @@ static __device__ __forceinline__ float vec_dot_q5_K_q8_1_impl_mmq(
 
 #pragma unroll
         for (int j = 0; j < QI8_1; ++j) {
-            sumi_d = __dp4a(v[i*QI8_1 + j], u[i*QI8_1 + j], sumi_d); // SIMD dot product
+            sumi_d = ggml_cuda_dp4a(v[i*QI8_1 + j], u[i*QI8_1 + j], sumi_d); // SIMD dot product
         }
 
         const float2 ds8f = __half22float2(ds8[i]);
@@ -495,10 +451,6 @@ static __device__ __forceinline__ float vec_dot_q5_K_q8_1_impl_mmq(
     const float2 dm4f = __half22float2(dm4);
 
     return dm4f.x*sumf_d - dm4f.y*sumf_m;
-
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 #define VDR_Q6_K_Q8_1_MMVQ 1
@@ -509,7 +461,6 @@ static __device__ __forceinline__ float vec_dot_q6_K_q8_1_impl_mmvq(
     const int & vl, const int & vh, const int * __restrict__ u, const int8_t * __restrict__ scales,
     const float & d, const float * __restrict__ d8) {
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     float sumf = 0.0f;
 
 #pragma unroll
@@ -522,13 +473,10 @@ static __device__ __forceinline__ float vec_dot_q6_K_q8_1_impl_mmvq(
 
         const int vi = __vsubss4((vil | vih), 0x20202020); // vi = (vil | vih) - 32
 
-        sumf += d8[i] * (__dp4a(vi, u[i], 0) * sc); // SIMD dot product
+        sumf += d8[i] * (ggml_cuda_dp4a(vi, u[i], 0) * sc); // SIMD dot product
     }
 
     return d*sumf;
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 // contiguous u/y values
@@ -536,7 +484,6 @@ static __device__ __forceinline__ float vec_dot_q6_K_q8_1_impl_mmq(
     const int * __restrict__ v, const int * __restrict__ u, const int8_t * __restrict__ sc,
     const float & d6, const float * __restrict__ d8) {
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     float sumf_d = 0.0f;
 
 #pragma unroll
@@ -545,21 +492,17 @@ static __device__ __forceinline__ float vec_dot_q6_K_q8_1_impl_mmq(
 
 #pragma unroll
         for (int i = i0; i < i0 + 2; ++i) {
-            sumi_d.x = __dp4a(v[2*i+0], u[2*i+0], sumi_d.x); // SIMD dot product
-            sumi_d.x = __dp4a(v[2*i+1], u[2*i+1], sumi_d.x); // SIMD dot product
+            sumi_d.x = ggml_cuda_dp4a(v[2*i+0], u[2*i+0], sumi_d.x); // SIMD dot product
+            sumi_d.x = ggml_cuda_dp4a(v[2*i+1], u[2*i+1], sumi_d.x); // SIMD dot product
 
-            sumi_d.y = __dp4a(v[2*i+4], u[2*i+4], sumi_d.y); // SIMD dot product
-            sumi_d.y = __dp4a(v[2*i+5], u[2*i+5], sumi_d.y); // SIMD dot product
+            sumi_d.y = ggml_cuda_dp4a(v[2*i+4], u[2*i+4], sumi_d.y); // SIMD dot product
+            sumi_d.y = ggml_cuda_dp4a(v[2*i+5], u[2*i+5], sumi_d.y); // SIMD dot product
         }
 
         sumf_d += d8[i0/4] * (sc[i0/2+0]*sumi_d.x + sc[i0/2+1]*sumi_d.y);
     }
 
     return d6 * sumf_d;
-
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
 static __device__ __forceinline__ float vec_dot_q4_0_q8_1(
@@ -572,9 +515,9 @@ static __device__ __forceinline__ float vec_dot_q4_0_q8_1(
 
 #pragma unroll
     for (int i = 0; i < VDR_Q4_0_Q8_1_MMVQ; ++i) {
-        v[i]     = get_int_from_uint8(bq4_0->qs, iqs + i);
-        u[2*i+0] = get_int_from_int8_aligned(bq8_1->qs, iqs + i);
-        u[2*i+1] = get_int_from_int8_aligned(bq8_1->qs, iqs + i + QI4_0);
+        v[i]     = get_int_b2(bq4_0->qs, iqs + i);
+        u[2*i+0] = get_int_b4(bq8_1->qs, iqs + i);
+        u[2*i+1] = get_int_b4(bq8_1->qs, iqs + i + QI4_0);
     }
 
     return vec_dot_q4_0_q8_1_impl(v, u, bq4_0->d, bq8_1->ds);
@@ -591,9 +534,9 @@ static __device__ __forceinline__ float vec_dot_q4_1_q8_1(
 
 #pragma unroll
     for (int i = 0; i < VDR_Q4_1_Q8_1_MMVQ; ++i) {
-        v[i]    = get_int_from_uint8_aligned(bq4_1->qs, iqs + i);
-        u[2*i+0] = get_int_from_int8_aligned(bq8_1->qs, iqs + i);
-        u[2*i+1] = get_int_from_int8_aligned(bq8_1->qs, iqs + i + QI4_1);
+        v[i]     = get_int_b4(bq4_1->qs, iqs + i);
+        u[2*i+0] = get_int_b4(bq8_1->qs, iqs + i);
+        u[2*i+1] = get_int_b4(bq8_1->qs, iqs + i + QI4_1);
     }
 
     return vec_dot_q4_1_q8_1_impl(v, u, bq4_1->dm, bq8_1->ds);
@@ -610,10 +553,10 @@ static __device__ __forceinline__ float vec_dot_q5_0_q8_1(
 
 #pragma unroll
     for (int i = 0; i < VDR_Q5_0_Q8_1_MMVQ; ++i) {
-        vl[i]    = get_int_from_uint8(bq5_0->qs, iqs + i);
-        vh[i]    = get_int_from_uint8(bq5_0->qh, 0) >> (4 * (iqs + i));
-        u[2*i+0] = get_int_from_int8_aligned(bq8_1->qs, iqs + i);
-        u[2*i+1] = get_int_from_int8_aligned(bq8_1->qs, iqs + i + QI5_0);
+        vl[i]    = get_int_b2(bq5_0->qs, iqs + i);
+        vh[i]    = get_int_b2(bq5_0->qh, 0) >> (4 * (iqs + i));
+        u[2*i+0] = get_int_b4(bq8_1->qs, iqs + i);
+        u[2*i+1] = get_int_b4(bq8_1->qs, iqs + i + QI5_0);
     }
 
     return vec_dot_q5_0_q8_1_impl(vl, vh, u, bq5_0->d, bq8_1->ds);
@@ -630,10 +573,10 @@ static __device__ __forceinline__ float vec_dot_q5_1_q8_1(
 
 #pragma unroll
     for (int i = 0; i < VDR_Q5_1_Q8_1_MMVQ; ++i) {
-        vl[i]   = get_int_from_uint8_aligned(bq5_1->qs, iqs + i);
-        vh[i]   = get_int_from_uint8_aligned(bq5_1->qh, 0) >> (4 * (iqs + i));
-        u[2*i+0] = get_int_from_int8_aligned(bq8_1->qs, iqs + i);
-        u[2*i+1] = get_int_from_int8_aligned(bq8_1->qs, iqs + i + QI5_1);
+        vl[i]    = get_int_b4(bq5_1->qs, iqs + i);
+        vh[i]    = get_int_b4(bq5_1->qh, 0) >> (4 * (iqs + i));
+        u[2*i+0] = get_int_b4(bq8_1->qs, iqs + i);
+        u[2*i+1] = get_int_b4(bq8_1->qs, iqs + i + QI5_1);
     }
 
     return vec_dot_q5_1_q8_1_impl(vl, vh, u, bq5_1->dm, bq8_1->ds);
@@ -649,8 +592,8 @@ static __device__ __forceinline__ float vec_dot_q8_0_q8_1(
 
 #pragma unroll
     for (int i = 0; i < VDR_Q8_0_Q8_1_MMVQ; ++i) {
-        v[i] = get_int_from_int8(bq8_0->qs, iqs + i);
-        u[i] = get_int_from_int8_aligned(bq8_1->qs, iqs + i);
+        v[i] = get_int_b2(bq8_0->qs, iqs + i);
+        u[i] = get_int_b4(bq8_1->qs, iqs + i);
     }
 
     return vec_dot_q8_0_q8_1_impl(v, u, bq8_0->d, __low2half(bq8_1->ds));
@@ -666,13 +609,13 @@ static __device__ __forceinline__ float vec_dot_q2_K_q8_1(
 
     const uint8_t * scales = bq2_K->scales + scale_offset;
 
-    const int v = get_int_from_uint8_aligned(bq2_K->qs, iqs);
+    const int v = get_int_b4(bq2_K->qs, iqs);
     int    u[QR2_K];
     float d8[QR2_K];
 
 #pragma unroll
     for (int i = 0; i < QR2_K; ++ i) {
-        u[i]  = get_int_from_int8_aligned(bq8_1[bq8_offset + i].qs, iqs % QI8_1);
+        u[i]  = get_int_b4(bq8_1[bq8_offset + i].qs, iqs % QI8_1);
         d8[i] = __low2float(bq8_1[bq8_offset + i].ds);
     }
 
@@ -689,17 +632,17 @@ static __device__ __forceinline__ float vec_dot_q3_K_q8_1(
 
     const float d = bq3_K->d;
 
-    const int vl = get_int_from_uint8(bq3_K->qs, iqs);
+    const int vl = get_int_b2(bq3_K->qs, iqs);
 
     // invert the mask with ~ so that a 0/1 results in 4/0 being subtracted
-    const int vh = ~get_int_from_uint8(bq3_K->hmask, iqs % (QI3_K/2)) >> bq8_offset;
+    const int vh = ~get_int_b2(bq3_K->hmask, iqs % (QI3_K/2)) >> bq8_offset;
 
     int    u[QR3_K];
     float d8[QR3_K];
 
 #pragma unroll
     for (int i = 0; i < QR3_K; ++i) {
-        u[i]  = get_int_from_int8_aligned(bq8_1[bq8_offset + i].qs, iqs % QI8_1);
+        u[i]  = get_int_b4(bq8_1[bq8_offset + i].qs, iqs % QI8_1);
         d8[i] = __low2float(bq8_1[bq8_offset + i].ds);
     }
 
@@ -807,8 +750,8 @@ static __device__ __forceinline__ float vec_dot_q6_K_q8_1(
     const int scale_offset = (QI6_K/4) * (iqs / (QI6_K/2)) + (iqs % (QI6_K/2)) / (QI6_K/8);
     const int vh_shift = 2 * ((iqs % (QI6_K/2)) / (QI6_K/4));
 
-    const int vl = get_int_from_uint8(bq6_K->ql, iqs);
-    const int vh = get_int_from_uint8(bq6_K->qh, (QI6_K/4) * (iqs / (QI6_K/2)) + iqs % (QI6_K/4)) >> vh_shift;
+    const int vl = get_int_b2(bq6_K->ql, iqs);
+    const int vh = get_int_b2(bq6_K->qh, (QI6_K/4) * (iqs / (QI6_K/2)) + iqs % (QI6_K/4)) >> vh_shift;
 
     const int8_t * scales = bq6_K->scales + scale_offset;
 
@@ -817,335 +760,342 @@ static __device__ __forceinline__ float vec_dot_q6_K_q8_1(
 
 #pragma unroll
     for (int i = 0; i < QR6_K; ++i) {
-        u[i]  = get_int_from_int8_aligned(bq8_1[bq8_offset + 2*i].qs, iqs % QI8_1);
+        u[i]  = get_int_b4(bq8_1[bq8_offset + 2*i].qs, iqs % QI8_1);
         d8[i] = __low2float(bq8_1[bq8_offset + 2*i].ds);
     }
 
     return vec_dot_q6_K_q8_1_impl_mmvq(vl, vh, u, scales, bq6_K->d, d8);
 }
 
+#define VDR_IQ2_XXS_Q8_1_MMVQ 2
+
 static __device__ __forceinline__ float vec_dot_iq2_xxs_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {
+
     const block_iq2_xxs * bq2 = (const block_iq2_xxs *) vbq + kbx;
 
-#if QR2_XXS == 8
-    const int ib32 = iqs;
-    const uint16_t * q2 = bq2->qs + 4*ib32;
-    const uint8_t  * aux8 = (const uint8_t *)q2;
-    const int8_t   * q8 = bq8_1[ib32].qs;
-    uint32_t aux32 = q2[2] | (q2[3] << 16);
+    const int q2 = get_int_b2(bq2->qs, iqs);
+    const uint8_t * aux8 = (const uint8_t *) &q2;
+    const uint32_t aux32 = get_int_b2(bq2->qs, iqs + 1);
+
     int sumi = 0;
-    for (int l = 0; l < 4; ++l) {
-        const uint8_t * grid = (const uint8_t *)(iq2xxs_grid + aux8[l]);
-        const uint8_t  signs = ksigns_iq2xs[aux32 & 127];
-        for (int j = 0; j < 8; ++j) {
-            sumi += q8[j] * grid[j] * (signs & kmask_iq2xs[j] ? -1 : 1);
-        }
-        q8 += 8;
-        aux32 >>= 7;
+#pragma unroll
+    for (int k0 = 0; k0 < 8; k0 += 2) {
+        const int * grid_pos = (const int *) (iq2xxs_grid + aux8[k0/2]);
+        const int signs_packed = ksigns_iq2xs[(aux32 >> (7*k0/2)) & 0x7F];
+
+        const int signs0 = __vcmpne4(((signs_packed & 0x03) << 7) | ((signs_packed & 0x0C) << 21), 0x00000000);
+        const int grid0 = __vsub4(grid_pos[0] ^ signs0, signs0);
+        const int u0 = get_int_b4(bq8_1[iqs/2].qs, k0 + 0);
+        sumi = ggml_cuda_dp4a(grid0, u0, sumi);
+
+        const int signs1 = __vcmpne4(((signs_packed & 0x30) << 3) | ((signs_packed & 0xC0) << 17), 0x00000000);
+        const int grid1 = __vsub4(grid_pos[1] ^ signs1, signs1);
+        const int u1 = get_int_b4(bq8_1[iqs/2].qs, k0 + 1);
+        sumi = ggml_cuda_dp4a(grid1, u1, sumi);
     }
-    const float d = (float)bq2->d * (0.5f + aux32) * __low2float(bq8_1[ib32].ds) * 0.25f;
+
+    const int ls = aux32 >> 28;
+    sumi = (ls*sumi + sumi/2)/4;
+    const float d = __half2float(bq2->d) * __low2float(bq8_1[iqs/2].ds);
     return d * sumi;
-#else
-    // iqs is 0...15
-    const int ib32 = iqs/2;
-    const int il = iqs%2;
-    const uint16_t * q2 = bq2->qs + 4*ib32;
-    const uint8_t  * aux8 = (const uint8_t *)q2;
-    const uint8_t  * grid1 = (const uint8_t *)(iq2xxs_grid + aux8[2*il+0]);
-    const uint8_t  * grid2 = (const uint8_t *)(iq2xxs_grid + aux8[2*il+1]);
-    const uint32_t aux32 = q2[2] | (q2[3] << 16);
-    const float d = (float)bq2->d * (0.5f + (aux32 >> 28)) * __low2float(bq8_1[ib32].ds) * 0.25f;
-    const uint8_t signs1 = ksigns_iq2xs[(aux32 >> 14*il) & 127];
-    const uint8_t signs2 = ksigns_iq2xs[(aux32 >> (14*il + 7)) & 127];
-    const int8_t * q8 = bq8_1[ib32].qs + 16*il;
-    int sumi1 = 0, sumi2 = 0;
-    for (int j = 0; j < 8; ++j) {
-        sumi1 += q8[j+0] * grid1[j] * (signs1 & kmask_iq2xs[j] ? -1 : 1);
-        sumi2 += q8[j+8] * grid2[j] * (signs2 & kmask_iq2xs[j] ? -1 : 1);
-    }
-    return d * (sumi1 + sumi2);
-#endif
 }
 
+#define VDR_IQ2_XS_Q8_1_MMVQ 2
+
 static __device__ __forceinline__ float vec_dot_iq2_xs_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
+
     const block_iq2_xs * bq2 = (const block_iq2_xs *) vbq + kbx;
 
-    const int ib32 = iqs;
-    const uint16_t * q2 = bq2->qs + 4*ib32;
-    const int8_t   * q8 = bq8_1[ib32].qs;
-    const uint8_t ls1 = bq2->scales[ib32] & 0xf;
-    const uint8_t ls2 = bq2->scales[ib32] >>  4;
+    const int2 q2_packed = make_int2(get_int_b2(bq2->qs, iqs + 0), get_int_b2(bq2->qs, iqs + 1));
+    const uint16_t * q2 = (const uint16_t *) &q2_packed;
+    const int ls0 = bq2->scales[iqs/2] & 0x0F;
+    const int ls1 = bq2->scales[iqs/2] >> 4;
+
+    int sumi0 = 0;
     int sumi1 = 0;
-    for (int l = 0; l < 2; ++l) {
-        const uint32_t * grid = (const uint32_t *)(iq2xs_grid + (q2[l] & 511));
-        const uint32_t * signs = (const uint32_t *)(ksigns64 + (q2[l] >> 9));
-        const int grid_l = __vsub4(grid[0] ^ signs[0], signs[0]);
-        const int grid_h = __vsub4(grid[1] ^ signs[1], signs[1]);
-        sumi1 = __dp4a(grid_l, *((const int *)q8 + 0), sumi1);
-        sumi1 = __dp4a(grid_h, *((const int *)q8 + 1), sumi1);
-        q8 += 8;
-    }
-    int sumi2 = 0;
-    for (int l = 2; l < 4; ++l) {
-        const uint32_t * grid = (const uint32_t *)(iq2xs_grid + (q2[l] & 511));
-        const uint32_t * signs = (const uint32_t *)(ksigns64 + (q2[l] >> 9));
-        const int grid_l = __vsub4(grid[0] ^ signs[0], signs[0]);
-        const int grid_h = __vsub4(grid[1] ^ signs[1], signs[1]);
-        sumi2 = __dp4a(grid_l, *((const int *)q8 + 0), sumi2);
-        sumi2 = __dp4a(grid_h, *((const int *)q8 + 1), sumi2);
-        q8 += 8;
+#pragma unroll
+    for (int l0 = 0; l0 < 8; l0 += 2) {
+        const uint32_t * grid_pos = (const uint32_t *)(iq2xs_grid + (q2[l0/2] & 0x000001FF));
+        const uint32_t * signs    = (const uint32_t *)(ksigns64   + (q2[l0/2] >> 9));
+
+        const int grid_l = __vsub4(grid_pos[0] ^ signs[0], signs[0]);
+        const int grid_h = __vsub4(grid_pos[1] ^ signs[1], signs[1]);
+
+        const int u0 = get_int_b4(bq8_1[iqs/2].qs, l0 + 0);
+        const int u1 = get_int_b4(bq8_1[iqs/2].qs, l0 + 1);
+
+        if (l0 < 4) {
+            sumi0 = ggml_cuda_dp4a(grid_l, u0, sumi0);
+            sumi0 = ggml_cuda_dp4a(grid_h, u1, sumi0);
+        } else {
+            sumi1 = ggml_cuda_dp4a(grid_l, u0, sumi1);
+            sumi1 = ggml_cuda_dp4a(grid_h, u1, sumi1);
+        }
     }
-    const float d = (float)bq2->d * __low2float(bq8_1[ib32].ds) * 0.25f;
-    return d * ((0.5f + ls1) * sumi1 + (0.5f + ls2) * sumi2);
-#else
-    GGML_UNUSED(ksigns64);
-    NO_DEVICE_CODE;
-#endif
+    const int sumi = (sumi0*ls0 + sumi1*ls1 + (sumi0 + sumi1)/2)/4;
+    const float d = __half2float(bq2->d) * __low2float(bq8_1[iqs/2].ds);
+    return d * sumi;
 }
 
-// TODO
+#define VDR_IQ2_S_Q8_1_MMVQ 2
+
 static __device__ __forceinline__ float vec_dot_iq2_s_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
+
     const block_iq2_s * bq2 = (const block_iq2_s *) vbq + kbx;
 
-    const int ib32 = iqs;
-    const int8_t  * q8 = bq8_1[ib32].qs;
-    const uint8_t * signs = bq2->qs + QK_K/8 + 4*ib32;
-    const uint8_t ls1 = bq2->scales[ib32] & 0xf;
-    const uint8_t ls2 = bq2->scales[ib32] >>  4;
+    const int       qs_packed = get_int_b2(bq2->qs, iqs/2);
+    const uint8_t * qs        = (const uint8_t *) &qs_packed;
+
+    const int qh = bq2->qh[iqs/2];
+
+    const int       signs_packed_32 = get_int_b2(bq2->qs, QK_K/32 + iqs/2);
+    const uint8_t * signs_packed_8  = (const uint8_t *) &signs_packed_32;
+
+    const int ls0 = bq2->scales[iqs/2] & 0x0F;
+    const int ls1 = bq2->scales[iqs/2] >> 4;
+
+    int sumi0 = 0;
     int sumi1 = 0;
-    for (int l = 0; l < 2; ++l) {
-        const uint32_t * grid = (const uint32_t *)(iq2s_grid + (bq2->qs[4*ib32+l] | ((bq2->qh[ib32] << (8-2*l)) & 0x300)));
-        const uint32_t signs0 = __vcmpeq4(((signs[l] & 0xf) * 0x01010101) & 0x08040201, 0x08040201);
-        const uint32_t signs1 = __vcmpeq4(((signs[l] >>  4) * 0x01010101) & 0x08040201, 0x08040201);
-        const int grid_l = __vsub4(grid[0] ^ signs0, signs0);
-        const int grid_h = __vsub4(grid[1] ^ signs1, signs1);
-        sumi1 = __dp4a(grid_l, *((const int *)q8 + 0), sumi1);
-        sumi1 = __dp4a(grid_h, *((const int *)q8 + 1), sumi1);
-        q8 += 8;
-    }
-    int sumi2 = 0;
-    for (int l = 2; l < 4; ++l) {
-        const uint32_t * grid = (const uint32_t *)(iq2s_grid + (bq2->qs[4*ib32+l] | ((bq2->qh[ib32] << (8-2*l)) & 0x300)));
-        const uint32_t signs0 = __vcmpeq4(((signs[l] & 0xf) * 0x01010101) & 0x08040201, 0x08040201);
-        const uint32_t signs1 = __vcmpeq4(((signs[l] >>  4) * 0x01010101) & 0x08040201, 0x08040201);
-        const int grid_l = __vsub4(grid[0] ^ signs0, signs0);
-        const int grid_h = __vsub4(grid[1] ^ signs1, signs1);
-        sumi2 = __dp4a(grid_l, *((const int *)q8 + 0), sumi2);
-        sumi2 = __dp4a(grid_h, *((const int *)q8 + 1), sumi2);
-        q8 += 8;
+#pragma unroll
+    for (int l0 = 0; l0 < 8; l0 += 2) {
+        const int * grid_pos = (const int *)(iq2s_grid + (qs[l0/2] | ((qh << (8-l0)) & 0x300)));
+
+        const int signs0 = __vcmpne4(((signs_packed_8[l0/2] & 0x03) << 7) | ((signs_packed_8[l0/2] & 0x0C) << 21), 0x00000000);
+        const int signs1 = __vcmpne4(((signs_packed_8[l0/2] & 0x30) << 3) | ((signs_packed_8[l0/2] & 0xC0) << 17), 0x00000000);
+
+        const int grid_l = __vsub4(grid_pos[0] ^ signs0, signs0);
+        const int grid_h = __vsub4(grid_pos[1] ^ signs1, signs1);
+
+        const int u0 = get_int_b4(bq8_1[iqs/2].qs, l0 + 0);
+        const int u1 = get_int_b4(bq8_1[iqs/2].qs, l0 + 1);
+
+        if (l0 < 4) {
+            sumi0 = ggml_cuda_dp4a(grid_l, u0, sumi0);
+            sumi0 = ggml_cuda_dp4a(grid_h, u1, sumi0);
+        } else {
+            sumi1 = ggml_cuda_dp4a(grid_l, u0, sumi1);
+            sumi1 = ggml_cuda_dp4a(grid_h, u1, sumi1);
+        }
     }
-    const float d = (float)bq2->d * __low2float(bq8_1[ib32].ds) * 0.25f;
-    return d * ((0.5f + ls1) * sumi1 + (0.5f + ls2) * sumi2);
-#else
-    GGML_UNUSED(ksigns64);
-    NO_DEVICE_CODE;
-#endif
+    const int sumi = (sumi0*ls0 + sumi1*ls1 + (sumi0 + sumi1)/2)/4;
+
+    const float d = __half2float(bq2->d) * __low2float(bq8_1[iqs/2].ds);
+    return d * sumi;
 }
 
+#define VDR_IQ3_XXS_Q8_1_MMVQ 2
+
 static __device__ __forceinline__ float vec_dot_iq3_xxs_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
-    const block_iq3_xxs * bq2 = (const block_iq3_xxs *) vbq + kbx;
-
-    const int ib32 = iqs;
-    const uint8_t  * q3 = bq2->qs + 8*ib32;
-    const uint16_t * gas = (const uint16_t *)(bq2->qs + QK_K/4) + 2*ib32;
-    const int8_t   * q8 = bq8_1[ib32].qs;
-    uint32_t aux32 = gas[0] | (gas[1] << 16);
+
+    const block_iq3_xxs * bq3 = (const block_iq3_xxs *) vbq + kbx;
+
+    const int2 q3_packed = make_int2(get_int_b2(bq3->qs, iqs), get_int_b2(bq3->qs, iqs+1));
+    const uint8_t * q3 = (const uint8_t *) &q3_packed;
+    const uint32_t aux32 = get_int_b2(bq3->qs, QK_K/16 + iqs/2);
+
     int sumi = 0;
-    for (int l = 0; l < 4; ++l) {
-        const uint32_t * grid1 = iq3xxs_grid + q3[2*l+0];
-        const uint32_t * grid2 = iq3xxs_grid + q3[2*l+1];
-        const uint32_t * signs = (const uint32_t *)(ksigns64 + (aux32 & 127));
-        const int grid_l = __vsub4(grid1[0] ^ signs[0], signs[0]);
-        const int grid_h = __vsub4(grid2[0] ^ signs[1], signs[1]);
-        sumi = __dp4a(grid_l, *((int *)q8+0), sumi);
-        sumi = __dp4a(grid_h, *((int *)q8+1), sumi);
-        q8 += 8;
-        aux32 >>= 7;
+#pragma unroll
+    for (int l0 = 0; l0 < 8; l0 += 2) {
+        const int2 grid_pos = make_int2(iq3xxs_grid[q3[l0 + 0]], iq3xxs_grid[q3[l0 + 1]]);
+
+        const int * signs = (const int *)(ksigns64 + ((aux32 >> (7*l0/2)) & 0x7F));
+
+        const int grid_l = __vsub4(grid_pos.x ^ signs[0], signs[0]);
+        const int grid_h = __vsub4(grid_pos.y ^ signs[1], signs[1]);
+
+        const int u0 = get_int_b4(bq8_1[iqs/2].qs, l0 + 0);
+        const int u1 = get_int_b4(bq8_1[iqs/2].qs, l0 + 1);
+
+        sumi = ggml_cuda_dp4a(grid_l, u0, sumi);
+        sumi = ggml_cuda_dp4a(grid_h, u1, sumi);
     }
-    const float d = (float)bq2->d * (0.5f + aux32) * __low2float(bq8_1[ib32].ds) * 0.5f;
+
+    const int ls = aux32 >> 28;
+    sumi = (ls*sumi + sumi/2)/2;
+    const float d = __half2float(bq3->d) * __low2float(bq8_1[iqs/2].ds);
     return d * sumi;
-#else
-    NO_DEVICE_CODE;
-#endif
 }
 
+#define VDR_IQ3_S_Q8_1_MMVQ 2
+
 // TODO: don't use lookup table for signs
 static __device__ __forceinline__ float vec_dot_iq3_s_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
-    const block_iq3_s * bq2 = (const block_iq3_s *) vbq + kbx;
 
-    const int ib32 = iqs;
-    const uint8_t  * qs = bq2->qs + 8*ib32;
-    const int8_t   * q8 = bq8_1[ib32].qs;
+    const block_iq3_s * bq3 = (const block_iq3_s *) vbq + kbx;
+
+    const int2      qs_packed = make_int2(get_int_b2(bq3->qs, iqs + 0), get_int_b2(bq3->qs, iqs + 1));
+    const uint8_t * qs        = (const uint8_t *) &qs_packed;
+
+    const int qh = bq3->qh[iqs/2];
+
+    const int       signs_packed_32 = get_int_b2(bq3->signs, iqs/2);
+    const uint8_t * signs_packed_8  = (const uint8_t *) &signs_packed_32;
+
     int sumi = 0;
-    for (int l = 0; l < 4; ++l) {
-        const uint32_t * grid1 = iq3s_grid + (qs[2*l+0] | ((bq2->qh[ib32] << (8 - 2*l)) & 256));
-        const uint32_t * grid2 = iq3s_grid + (qs[2*l+1] | ((bq2->qh[ib32] << (7 - 2*l)) & 256));
-        uint32_t signs0 = __vcmpeq4(((bq2->signs[4*ib32+l] & 0xf) * 0x01010101) & 0x08040201, 0x08040201);
-        uint32_t signs1 = __vcmpeq4(((bq2->signs[4*ib32+l] >>  4) * 0x01010101) & 0x08040201, 0x08040201);
-        const int grid_l = __vsub4(grid1[0] ^ signs0, signs0);
-        const int grid_h = __vsub4(grid2[0] ^ signs1, signs1);
-        sumi = __dp4a(grid_l, *((int *)q8+0), sumi);
-        sumi = __dp4a(grid_h, *((int *)q8+1), sumi);
-        q8 += 8;
+#pragma unroll
+    for (int l0 = 0; l0 < 8; l0 += 2) {
+        const int2 grid_pos = make_int2(
+            iq3s_grid[qs[l0 + 0] | ((qh << (8 - l0)) & 0x100)],
+            iq3s_grid[qs[l0 + 1] | ((qh << (7 - l0)) & 0x100)]);
+
+        const int signs0 = __vcmpne4(((signs_packed_8[l0/2] & 0x03) << 7) | ((signs_packed_8[l0/2] & 0x0C) << 21), 0x00000000);
+        const int signs1 = __vcmpne4(((signs_packed_8[l0/2] & 0x30) << 3) | ((signs_packed_8[l0/2] & 0xC0) << 17), 0x00000000);
+
+        const int grid_l = __vsub4(grid_pos.x ^ signs0, signs0);
+        const int grid_h = __vsub4(grid_pos.y ^ signs1, signs1);
+
+        const int u0 = get_int_b4(bq8_1[iqs/2].qs, l0 + 0);
+        const int u1 = get_int_b4(bq8_1[iqs/2].qs, l0 + 1);
+
+        sumi = ggml_cuda_dp4a(grid_l, u0, sumi);
+        sumi = ggml_cuda_dp4a(grid_h, u1, sumi);
     }
-    const float d = (float)bq2->d * (1 + 2*((bq2->scales[ib32/2] >> 4*(ib32%2)) & 0xf)) * __low2float(bq8_1[ib32].ds);
+
+    sumi *= 1 + 2*((bq3->scales[iqs/4] >> ((iqs << 1) & 0x04)) & 0x0F);
+
+    const float d = __half2float(bq3->d) * __low2float(bq8_1[iqs/2].ds);
     return d * sumi;
-#else
-    NO_DEVICE_CODE;
-#endif
 }
 
 static __device__ __forceinline__ float vec_dot_iq1_s_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {
     const block_iq1_s * bq1 = (const block_iq1_s *) vbq + kbx;
 
-    const int ib32 = iqs;
+    const int       qs_packed = get_int_b2(bq1->qs, iqs);
+    const uint8_t * qs        = (const uint8_t *) &qs_packed;
+
+    const int qh = bq1->qh[iqs];
+
     int sumi = 0;
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
-    const int * q8 = (const int *)bq8_1[ib32].qs;
-    for (int l = 0; l < 4; ++l) {
-        const int * grid = (const int *)(iq1s_grid_gpu + (bq1->qs[4*ib32+l] | (((bq1->qh[ib32] >> 3*l) & 7) << 8)));
-        int grid0 = grid[0] & 0x0f0f0f0f;
-        int grid1 = (grid[0] >> 4) & 0x0f0f0f0f;
-        sumi = __dp4a(q8[2*l+1], grid1, __dp4a(q8[2*l+0], grid0, sumi));
-    }
-#else
-    const int8_t * q8 = bq8_1[ib32].qs;
-    for (int l = 0; l < 4; ++l) {
-        const uint8_t * grid = (const uint8_t *)(iq1s_grid_gpu + (bq1->qs[4*ib32+l] | (((bq1->qh[ib32] >> 3*l) & 7) << 8)));
-        for (int j = 0; j < 4; ++j) {
-            sumi += q8[j] * (grid[j] & 0xf) + q8[j+4] * (grid[j] >> 4);
-        }
-        q8 += 8;
+#pragma unroll
+    for (int l0 = 0; l0 < 8; l0 += 2) {
+        const int grid = iq1s_grid_gpu[qs[l0/2] | (((qh >> 3*(l0/2)) & 0x07) << 8)];
+
+        const int grid0 = (grid >> 0) & 0x0F0F0F0F;
+        const int grid1 = (grid >> 4) & 0x0F0F0F0F;
+
+        const int u0 = get_int_b4(bq8_1[iqs].qs, l0 + 0);
+        const int u1 = get_int_b4(bq8_1[iqs].qs, l0 + 1);
+
+        sumi = ggml_cuda_dp4a(grid0, u0, sumi);
+        sumi = ggml_cuda_dp4a(grid1, u1, sumi);
     }
-#endif
-    const float delta = bq1->qh[ib32] & 0x8000 ? -1-IQ1S_DELTA : -1+IQ1S_DELTA;
-    const float d1q = (float)bq1->d * (2*((bq1->qh[ib32] >> 12) & 7) + 1);
-    const float d = d1q * __low2float (bq8_1[ib32].ds);
-    const float m = d1q * __high2float(bq8_1[ib32].ds);
-    return d * sumi + m * delta;
+
+    const float  d1q   = __half2float(bq1->d) * (((qh >> 11) & 0x0E) + 1);
+    const float  delta = -1.0f + IQ1S_DELTA - (qh & 0x8000) * (2.0f*IQ1S_DELTA/0x8000);
+    const float2 ds    = __half22float2(bq8_1[iqs].ds);
+    return d1q * (ds.x*sumi + ds.y*delta);
 }
 
 static __device__ __forceinline__ float vec_dot_iq1_m_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {
+
     const block_iq1_m * bq1 = (const block_iq1_m *) vbq + kbx;
 
-    const int ib32 = iqs;
-    int   sumi[2] = {0, 0};
-    float sumf[2] = {0.f, 0.f};
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
-    const int * q8 = (const int *)bq8_1[ib32].qs;
-    for (int l = 0; l < 4; ++l) {
-        const int * grid = (const int *)(iq1s_grid_gpu + (bq1->qs[4*ib32+l] | (((bq1->qh[2*ib32+l/2] >> 4*(l%2)) & 7) << 8)));
-        int grid0 = grid[0] & 0x0f0f0f0f;
-        int grid1 = (grid[0] >> 4) & 0x0f0f0f0f;
-        sumi[l/2] = __dp4a(q8[2*l+1], grid1, __dp4a(q8[2*l+0], grid0, sumi[l/2]));
-        const float delta = (bq1->qh[2*ib32+l/2] >> 4*(l%2)) & 0x08 ? -1-IQ1M_DELTA : -1+IQ1M_DELTA;
-        const int sumy = __dp4a(q8[2*l+1], 0x01010101, __dp4a(q8[2*l+0], 0x01010101, 0));
-        sumf[l/2] += delta*sumy;
-    }
-#else
-    const int8_t * q8 = bq8_1[ib32].qs;
-    for (int l = 0; l < 4; ++l) {
-        const uint8_t * grid = (const uint8_t *)(iq1s_grid_gpu + (bq1->qs[4*ib32+l] | (((bq1->qh[ib32] >> 3*l) & 7) << 8)));
+    const int       qs_packed = get_int_b4(bq1->qs, iqs);
+    const uint8_t * qs        = (const uint8_t *) &qs_packed;
+
+    int   sumi[2] = {0};
+    float sumf[2] = {0.0f};
+#pragma unroll
+    for (int l0 = 0; l0 < 8; l0 += 2) {
+        const int qhl = bq1->qh[2*iqs + l0/4] >> (4 * ((l0/2) % 2));
+
+        const int grid = iq1s_grid_gpu[qs[l0/2] | ((qhl & 0x07) << 8)];
+
+        const int grid0 = (grid >> 0) & 0x0F0F0F0F;
+        const int grid1 = (grid >> 4) & 0x0F0F0F0F;
+
+        const int u0 = get_int_b4(bq8_1[iqs].qs, l0 + 0);
+        const int u1 = get_int_b4(bq8_1[iqs].qs, l0 + 1);
+
+        sumi[l0/4] = ggml_cuda_dp4a(grid0, u0, sumi[l0/4]);
+        sumi[l0/4] = ggml_cuda_dp4a(grid1, u1, sumi[l0/4]);
+
+        const float delta = -1.0f + IQ1M_DELTA - (qhl & 0x08) * (2.0f*IQ1M_DELTA/0x08);
         int sumy = 0;
-        for (int j = 0; j < 4; ++j) {
-            sumi[l/2] += q8[j] * (grid[j] & 0xf) + q8[j+4] * (grid[j] >> 4);
-            sumy += q8[j] + q8[j+4];
-        }
-        const float delta = (bq1->qh[2*ib32+l/2] >> 4*(l%2)) & 0x08 ? -1-IQ1M_DELTA : -1+IQ1M_DELTA;
-        sumf[l/2] += delta*sumy;
-        q8 += 8;
+        sumy = ggml_cuda_dp4a(u0, 0x01010101, sumy);
+        sumy = ggml_cuda_dp4a(u1, 0x01010101, sumy);
+        sumf[l0/4] += delta*sumy;
     }
-#endif
+
+    const uint16_t * sc = (const uint16_t *) bq1->scales;
+
     iq1m_scale_t scale;
-    const uint16_t * sc = (const uint16_t *)bq1->scales;
-    scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
-    const float d = (float)scale.f16 * __low2float (bq8_1[ib32].ds);
-    return d * ((sumi[0] + sumf[0]) * (2*((sc[ib32/2] >> 6*(ib32%2)) & 0x7) + 1) + (sumi[1] + sumf[1]) * (2*((sc[ib32/2] >> (6*(ib32%2)+3)) & 0x7) + 1));
+    scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00F0) | ((sc[2] >> 4) & 0x0F00) | (sc[3] & 0xF000);
+    const float d = __half2float(scale.f16) * __low2float(bq8_1[iqs].ds);
+
+    const int tmp = sc[iqs/2] >> (6*(iqs%2));
+    const int sc0 = 2*((tmp >> 0) & 0x07) + 1;
+    const int sc1 = 2*((tmp >> 3) & 0x07) + 1;
+    return d * ((sumi[0] + sumf[0]) * sc0 + (sumi[1] + sumf[1]) * sc1);
 }
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
-static __device__ __forceinline__ void get_int_from_table_16(const uint32_t & q4, const uint8_t * values,
-        int & val1, int & val2) {
-
-    uint32_t aux32; const uint8_t * q8 = (const uint8_t *)&aux32;
-    aux32 = q4 & 0x0f0f0f0f;
-    uint16_t v1 = values[q8[0]] | (values[q8[1]] << 8);
-    uint16_t v2 = values[q8[2]] | (values[q8[3]] << 8);
-    val1 = v1 | (v2 << 16);
-    aux32 = (q4 >> 4) & 0x0f0f0f0f;
-    v1 = values[q8[0]] | (values[q8[1]] << 8);
-    v2 = values[q8[2]] | (values[q8[3]] << 8);
-    val2 = v1 | (v2 << 16);
+static __device__ __forceinline__ int2 get_int_from_table_16(const int & q4) {
+    const int      q0_32  = (q4 >> 0) & 0x0F0F0F0F;
+    const int8_t * q0_8   = (const int8_t *) &q0_32;
+    const char4    val0_8 = make_char4(
+        kvalues_iq4nl[q0_8[0]], kvalues_iq4nl[q0_8[1]], kvalues_iq4nl[q0_8[2]], kvalues_iq4nl[q0_8[3]]);
+
+    const int      q1_32  = (q4 >> 4) & 0x0F0F0F0F;
+    const int8_t * q1_8   = (const int8_t *) &q1_32;
+    const char4    val1_8 = make_char4(
+        kvalues_iq4nl[q1_8[0]], kvalues_iq4nl[q1_8[1]], kvalues_iq4nl[q1_8[2]], kvalues_iq4nl[q1_8[3]]);
+
+    return make_int2(*((const int *) &val0_8), *((const int *) &val1_8));
 }
-#endif
+
+#define VDR_IQ4_NL_Q8_1_MMVQ 2
 
 static __device__ __forceinline__ float vec_dot_iq4_nl_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {
 
-    const block_iq4_nl * bq = (const block_iq4_nl *) vbq + kbx;
+    const block_iq4_nl * bq4 = (const block_iq4_nl *) vbq + kbx;
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
-    const uint16_t * q4 = (const uint16_t *)bq->qs + 2*iqs;
-    const int32_t  * q8 = (const int32_t  *)bq8_1->qs + iqs;
+    const int * q8 = (const int *) bq8_1->qs + iqs;
 
-    const uint8_t * values = (const uint8_t *)kvalues_iq4nl;
-
-    int v1, v2;
-    int sumi1 = 0, sumi2 = 0;
+    int sumi = 0;
+#pragma unroll
     for (int l = 0; l < VDR_Q4_0_Q8_1_MMVQ; ++l) {
-        const uint32_t aux = q4[2*l] | (q4[2*l+1] << 16);
-        get_int_from_table_16(aux, values, v1, v2);
-        sumi1 = __dp4a(v1, q8[l+0], sumi1);
-        sumi2 = __dp4a(v2, q8[l+4], sumi2);
-    }
-
-#else
-    const uint8_t * q4 = bq->qs + 4*iqs;
-    const int8_t  * q8 = bq8_1->qs + 4*iqs;
+        const int aux_q4 = get_int_b2(bq4->qs, iqs + l);
+        const int2 v = get_int_from_table_16(aux_q4);
 
-    int sumi1 = 0, sumi2 = 0;
-    for (int l = 0; l < 4*VDR_Q4_0_Q8_1_MMVQ; ++l) {
-        sumi1 += q8[l+ 0] * kvalues_iq4nl[q4[l] & 0xf];
-        sumi2 += q8[l+16] * kvalues_iq4nl[q4[l] >>  4];
+        sumi = ggml_cuda_dp4a(v.x, q8[l + 0], sumi);
+        sumi = ggml_cuda_dp4a(v.y, q8[l + 4], sumi);
     }
-#endif
-    const float d = (float)bq->d * __low2float(bq8_1->ds);
-    return d * (sumi1 + sumi2);
+
+    const float d = __half2float(bq4->d) * __low2float(bq8_1->ds);
+    return d * sumi;
 }
 
+#define VDR_IQ4_XS_Q8_1_MMVQ 4
+
 static __device__ __forceinline__ float vec_dot_iq4_xs_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {
 
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     const block_iq4_xs * bq4 = (const block_iq4_xs *) vbq + kbx;
-    const uint8_t * values = (const uint8_t *)kvalues_iq4nl;
-
-    // iqs is 0...7
-    const int ib32 = iqs;
-    const int32_t  * q8 = (const int *)bq8_1[ib32].qs;
-    const uint32_t * q4 = (const uint32_t *)bq4->qs + 4*ib32;
-    const int8_t ls = ((bq4->scales_l[ib32/2] >> 4*(ib32%2)) & 0xf) | (((bq4->scales_h >> 2*ib32) & 3) << 4);
-    const float d = (float)bq4->d * (ls - 32) * __low2float(bq8_1[ib32].ds);
-    int v1, v2;
-    int sumi1 = 0, sumi2 = 0;
+
+    int sumi = 0;
+#pragma unroll
     for (int j = 0; j < 4; ++j) {
-        get_int_from_table_16(q4[j], values, v1, v2);
-        sumi1 = __dp4a(v1, q8[j+0], sumi1);
-        sumi2 = __dp4a(v2, q8[j+4], sumi2);
+        const int aux_q4 = get_int_b4(bq4->qs, iqs + j);
+        const int2 v = get_int_from_table_16(aux_q4);
+
+        const int u0 = get_int_b4(bq8_1[iqs/4].qs, j + 0);
+        const int u1 = get_int_b4(bq8_1[iqs/4].qs, j + 4);
+
+        sumi = ggml_cuda_dp4a(v.x, u0, sumi);
+        sumi = ggml_cuda_dp4a(v.y, u1, sumi);
     }
-    return d * (sumi1 + sumi2);
-#else
-    return vec_dot_iq4_xs_q8_1(vbq, bq8_1, kbx, iqs);
-#endif
+
+    const int ls = ((bq4->scales_l[iqs/8] >> (iqs & 0x04)) & 0x0F) | (((bq4->scales_h >> (iqs/2)) & 0x03) << 4);
+    sumi *= ls - 32;
+
+    const float d = __half2float(bq4->d) * __low2float(bq8_1[iqs/4].ds);
+    return d * sumi;
 }
diff --git a/ggml/src/ggml-sycl/mmvq.cpp b/ggml/src/ggml-sycl/mmvq.cpp
index 23227649e2661..9b751f3c67281 100644
--- a/ggml/src/ggml-sycl/mmvq.cpp
+++ b/ggml/src/ggml-sycl/mmvq.cpp
@@ -735,7 +735,7 @@ static void mul_mat_vec_iq2_xxs_q8_1_sycl(const void *vx, const void *vy,
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
                     [[intel::reqd_sub_group_size(32)]] {
-                        mul_mat_vec_q_iq2_xxs_q8_1(
+                        mul_mat_vec_q_iq2_xxs_q8_1(
                             vx, vy, dst, ncols, nrows, item_ct1);
                     });
         });
@@ -760,7 +760,7 @@ static void mul_mat_vec_iq2_xs_q8_1_sycl(const void *vx, const void *vy,
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
                     [[intel::reqd_sub_group_size(32)]] {
-                        mul_mat_vec_q_iq2_xs_q8_1(
+                        mul_mat_vec_q_iq2_xs_q8_1(
                             vx, vy, dst, ncols, nrows, item_ct1);
                     });
         });
@@ -785,7 +785,7 @@ static void mul_mat_vec_iq2_s_q8_1_sycl(const void *vx, const void *vy,
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
                     [[intel::reqd_sub_group_size(32)]] {
-                        mul_mat_vec_q_iq2_s_q8_1(
+                        mul_mat_vec_q_iq2_s_q8_1(
                             vx, vy, dst, ncols, nrows, item_ct1);
                     });
         });
@@ -810,7 +810,7 @@ static void mul_mat_vec_iq3_xxs_q8_1_sycl(const void *vx, const void *vy,
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
                     [[intel::reqd_sub_group_size(32)]] {
-                        mul_mat_vec_q_iq3_xxs_q8_1(
+                        mul_mat_vec_q_iq3_xxs_q8_1(
                             vx, vy, dst, ncols, nrows, item_ct1);
                     });
         });
@@ -834,7 +834,7 @@ static void mul_mat_vec_iq3_s_q8_1_sycl(const void *vx, const void *vy,
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
                     [[intel::reqd_sub_group_size(32)]] {
-                        mul_mat_vec_q_iq3_s_q8_1(
+                        mul_mat_vec_q_iq3_s_q8_1(
                             vx, vy, dst, ncols, nrows, item_ct1);
                     });
         });
@@ -924,7 +924,7 @@ static void mul_mat_vec_iq4_xs_q8_1_sycl(const void *vx, const void *vy,
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
                     [[intel::reqd_sub_group_size(32)]] {
-                        mul_mat_vec_q_iq4_xs_q8_1(
+                        mul_mat_vec_q_iq4_xs_q8_1(
                             vx, vy, dst, ncols, nrows, item_ct1);
                     });
         });
diff --git a/ggml/src/ggml-sycl/vecdotq.hpp b/ggml/src/ggml-sycl/vecdotq.hpp
index 5e2e825463cde..d2dccade20bfd 100644
--- a/ggml/src/ggml-sycl/vecdotq.hpp
+++ b/ggml/src/ggml-sycl/vecdotq.hpp
@@ -820,7 +820,6 @@ vec_dot_iq2_xxs_q8_1(const void *__restrict__ vbq,
 #if QK_K == 256
     const block_iq2_xxs * bq2 = (const block_iq2_xxs *) vbq;
 
-#if QR2_XXS == 8
     const int ib32 = iqs;
     const uint16_t * q2 = bq2->qs + 4*ib32;
     const uint8_t  * aux8 = (const uint8_t *)q2;
@@ -838,26 +837,6 @@ vec_dot_iq2_xxs_q8_1(const void *__restrict__ vbq,
     }
     const float d = (float)bq2->d * (0.5f + aux32) * bq8_1[ib32].ds[0] * 0.25f;
     return d * sumi;
-#else
-    // iqs is 0...15
-    const int ib32 = iqs/2;
-    const int il = iqs%2;
-    const uint16_t * q2 = bq2->qs + 4*ib32;
-    const uint8_t  * aux8 = (const uint8_t *)q2;
-    const uint8_t  * grid1 = (const uint8_t *)(iq2xxs_grid + aux8[2*il+0]);
-    const uint8_t  * grid2 = (const uint8_t *)(iq2xxs_grid + aux8[2*il+1]);
-    const uint32_t aux32 = q2[2] | (q2[3] << 16);
-    const float d = (float)bq2->d * (0.5f + (aux32 >> 28)) * bq8_1[ib32].ds[0] * 0.25f;
-    const uint8_t signs1 = ksigns_iq2xs[(aux32 >> 14*il) & 127];
-    const uint8_t signs2 = ksigns_iq2xs[(aux32 >> (14*il + 7)) & 127];
-    const int8_t * q8 = bq8_1[ib32].qs + 16*il;
-    int sumi1 = 0, sumi2 = 0;
-    for (int j = 0; j < 8; ++j) {
-        sumi1 += q8[j+0] * grid1[j] * (signs1 & kmask_iq2xs[j] ? -1 : 1);
-        sumi2 += q8[j+8] * grid2[j] * (signs2 & kmask_iq2xs[j] ? -1 : 1);
-    }
-    return d * (sumi1 + sumi2);
-#endif
 #else
     assert(false);
     return 0.f;

From 5fac350b9cc49d0446fc291b9c4ad53666c77591 Mon Sep 17 00:00:00 2001
From: Xuan Son Nguyen 
Date: Tue, 2 Jul 2024 01:07:23 +0200
Subject: [PATCH 068/326] Fix gemma2 tokenizer convert (#8244)

* fix gemma2 tokenizer convert

* remove scores

* improve code, fix new line issue
---
 convert-hf-to-gguf.py | 37 +++++++++++++++++++++++++++----------
 1 file changed, 27 insertions(+), 10 deletions(-)

diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py
index 4a7f500ff7d5c..6833e943765f7 100755
--- a/convert-hf-to-gguf.py
+++ b/convert-hf-to-gguf.py
@@ -576,7 +576,19 @@ def _set_vocab_qwen(self):
         special_vocab._set_special_token("unk", tokenizer.special_tokens["<|endoftext|>"])
         special_vocab.add_to_gguf(self.gguf_writer)
 
-    def _set_vocab_sentencepiece(self):
+    def _set_vocab_sentencepiece(self, add_to_gguf=True):
+        tokens, scores, toktypes = self._create_vocab_sentencepiece()
+
+        self.gguf_writer.add_tokenizer_model("llama")
+        self.gguf_writer.add_tokenizer_pre("default")
+        self.gguf_writer.add_token_list(tokens)
+        self.gguf_writer.add_token_scores(scores)
+        self.gguf_writer.add_token_types(toktypes)
+
+        special_vocab = gguf.SpecialVocab(self.dir_model, n_vocab=len(tokens))
+        special_vocab.add_to_gguf(self.gguf_writer)
+
+    def _create_vocab_sentencepiece(self):
         from sentencepiece import SentencePieceProcessor
 
         tokenizer_path = self.dir_model / 'tokenizer.model'
@@ -638,14 +650,7 @@ def _set_vocab_sentencepiece(self):
                 scores.append(-1000.0)
                 toktypes.append(SentencePieceTokenTypes.UNUSED)
 
-        self.gguf_writer.add_tokenizer_model("llama")
-        self.gguf_writer.add_tokenizer_pre("default")
-        self.gguf_writer.add_token_list(tokens)
-        self.gguf_writer.add_token_scores(scores)
-        self.gguf_writer.add_token_types(toktypes)
-
-        special_vocab = gguf.SpecialVocab(self.dir_model, n_vocab=len(tokens))
-        special_vocab.add_to_gguf(self.gguf_writer)
+        return tokens, scores, toktypes
 
     def _set_vocab_llama_hf(self):
         vocab = gguf.LlamaHfVocab(self.dir_model)
@@ -2345,7 +2350,19 @@ class Gemma2Model(Model):
     model_arch = gguf.MODEL_ARCH.GEMMA2
 
     def set_vocab(self):
-        self._set_vocab_llama_hf()
+        tokens, scores, toktypes = self._create_vocab_sentencepiece()
+        # hack: This is required so that we can properly use start/end-of-turn for chat template
+        for i in range(108):
+            # including , , 
+            toktypes[i] = SentencePieceTokenTypes.CONTROL
+        self.gguf_writer.add_tokenizer_model("llama")
+        self.gguf_writer.add_tokenizer_pre("default")
+        self.gguf_writer.add_token_list(tokens)
+        self.gguf_writer.add_token_scores(scores)
+        self.gguf_writer.add_token_types(toktypes)
+
+        special_vocab = gguf.SpecialVocab(self.dir_model, n_vocab=len(tokens))
+        special_vocab.add_to_gguf(self.gguf_writer)
         self.gguf_writer.add_add_space_prefix(False)
 
     def set_gguf_parameters(self):

From d08c20eddedb24515a3212e2de66bdff41a26b8c Mon Sep 17 00:00:00 2001
From: luoyu-intel 
Date: Tue, 2 Jul 2024 02:16:00 +0000
Subject: [PATCH 069/326] [SYCL] Fix the sub group size of Intel (#8106)

* use warp_size macro for all sycl kernels

* fix mask of permute_sub_group_by_xor

* fix rms_norm with correct warp number

* fix rms_norm_f32/group_norm_f32

* move norm to norm.cpp file

* fix quantize bug

* fix mmvq's batch size
---
 ggml/src/CMakeLists.txt        |   4 +-
 ggml/src/ggml-sycl.cpp         | 472 +++------------------------------
 ggml/src/ggml-sycl/backend.hpp |   1 +
 ggml/src/ggml-sycl/common.hpp  |  55 ++++
 ggml/src/ggml-sycl/dmmv.cpp    |  44 +--
 ggml/src/ggml-sycl/mmvq.cpp    | 113 ++++----
 ggml/src/ggml-sycl/norm.cpp    | 370 ++++++++++++++++++++++++++
 ggml/src/ggml-sycl/norm.hpp    |  35 +++
 ggml/src/ggml-sycl/presets.hpp |   2 +-
 9 files changed, 587 insertions(+), 509 deletions(-)
 create mode 100644 ggml/src/ggml-sycl/norm.cpp
 create mode 100644 ggml/src/ggml-sycl/norm.hpp

diff --git a/ggml/src/CMakeLists.txt b/ggml/src/CMakeLists.txt
index d0f4097d8cd0c..a18198f1693e5 100644
--- a/ggml/src/CMakeLists.txt
+++ b/ggml/src/CMakeLists.txt
@@ -486,9 +486,11 @@ if (GGML_SYCL)
     add_compile_options(-I./) #include DPCT
 
     set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-narrowing")
-    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O3")
     if (GGML_SYCL_TARGET STREQUAL "NVIDIA")
         set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fsycl-targets=nvptx64-nvidia-cuda")
+        add_compile_definitions(GGML_SYCL_WARP_SIZE=32)
+    else()
+        add_compile_definitions(GGML_SYCL_WARP_SIZE=16)
     endif()
 
     file(GLOB   GGML_HEADERS_SYCL "ggml-sycl/*.hpp")
diff --git a/ggml/src/ggml-sycl.cpp b/ggml/src/ggml-sycl.cpp
index 30d8a5b33b613..76bad57e2320b 100644
--- a/ggml/src/ggml-sycl.cpp
+++ b/ggml/src/ggml-sycl.cpp
@@ -74,51 +74,6 @@ typedef void (*ggml_sycl_op_flatten_t)(ggml_backend_sycl_context & ctx, const gg
                                        const float *src1_dd, float *dst_dd,
                                        const queue_ptr &main_stream);
 
-static __dpct_inline__ float warp_reduce_sum(float x,
-                                             const sycl::nd_item<3> &item_ct1) {
-#pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
-        /*
-        DPCT1096:98: The right-most dimension of the work-group used in the SYCL
-        kernel that calls this function may be less than "32". The function
-        "dpct::permute_sub_group_by_xor" may return an unexpected result on the
-        CPU device. Modify the size of the work-group to ensure that the value
-        of the right-most dimension is a multiple of "32".
-        */
-        x += dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), x, mask);
-    }
-    return x;
-}
-
-static __dpct_inline__ sycl::float2
-warp_reduce_sum(sycl::float2 a, const sycl::nd_item<3> &item_ct1) {
-#pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
-        a.x() += dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), a.x(),
-                                                mask);
-        a.y() += dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), a.y(),
-                                                mask);
-    }
-    return a;
-}
-
-static __dpct_inline__ float warp_reduce_max(float x,
-                                             const sycl::nd_item<3> &item_ct1) {
-#pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
-        /*
-        DPCT1096:97: The right-most dimension of the work-group used in the SYCL
-        kernel that calls this function may be less than "32". The function
-        "dpct::permute_sub_group_by_xor" may return an unexpected result on the
-        CPU device. Modify the size of the work-group to ensure that the value
-        of the right-most dimension is a multiple of "32".
-        */
-        x = sycl::fmax(x, dpct::permute_sub_group_by_xor(
-                              item_ct1.get_sub_group(), x, mask));
-    }
-    return x;
-}
-
 static __dpct_inline__ float op_repeat(const float a, const float b) {
     return b;
     GGML_UNUSED(a);
@@ -336,47 +291,6 @@ static void sqr_f32(const float * x, float * dst, const int k,
     dst[i] = x[i] * x[i];
 }
 
-static void norm_f32(const float * x, float * dst, const int ncols, const float eps,
-                     const sycl::nd_item<3> &item_ct1, sycl::float2 *s_sum, int block_size) {
-    const int row = item_ct1.get_group(2) * item_ct1.get_local_range(1) +
-                    item_ct1.get_local_id(1);
-    const int tid = item_ct1.get_local_id(2);
-
-    sycl::float2 mean_var = sycl::float2(0.f, 0.f);
-
-    for (int col = tid; col < ncols; col += block_size) {
-        const float xi = x[row*ncols + col];
-        mean_var.x() += xi;
-        mean_var.y() += xi * xi;
-    }
-
-    // sum up partial sums
-    mean_var = warp_reduce_sum(mean_var, item_ct1);
-    if (block_size > WARP_SIZE) {
-
-        int warp_id = item_ct1.get_local_id(2) / WARP_SIZE;
-        int lane_id = item_ct1.get_local_id(2) % WARP_SIZE;
-        if (lane_id == 0) {
-            s_sum[warp_id] = mean_var;
-        }
-        /*
-        DPCT1118:0: SYCL group functions and algorithms must be encountered in
-        converged control flow. You may need to adjust the code.
-        */
-        item_ct1.barrier(sycl::access::fence_space::local_space);
-        mean_var = s_sum[lane_id];
-        mean_var = warp_reduce_sum(mean_var, item_ct1);
-    }
-
-    const float mean = mean_var.x() / ncols;
-    const float var = mean_var.y() / ncols - mean * mean;
-    const float inv_std = sycl::rsqrt(var + eps);
-
-    for (int col = tid; col < ncols; col += block_size) {
-        dst[row*ncols + col] = (x[row*ncols + col] - mean) * inv_std;
-    }
-}
-
 static void concat_f32(const float  *x,const float  *y, float *dst, const int ne0, const int ne02,
                        const sycl::nd_item<3> &item_ct1) {
     int nidx = item_ct1.get_local_id(2) +
@@ -444,126 +358,11 @@ static void pad_f32(const float  *x, float *dst, const int ne0, const int ne00,
     }
 }
 
-static void group_norm_f32(const float * x, float * dst, const int group_size, const int ne_elements, const float eps,
-                           const sycl::nd_item<3> &item_ct1, float *s_sum, int block_size) {
-    int start = item_ct1.get_group(2) * group_size;
-    int end = start + group_size;
-
-    start += item_ct1.get_local_id(2);
-
-    if (end >= ne_elements) {
-        end = ne_elements;
-    }
-
-    float tmp = 0.0f; // partial sum for thread in warp
-
-    for (int j = start; j < end; j += block_size) {
-        tmp += x[j];
-    }
-
-    tmp = warp_reduce_sum(tmp, item_ct1);
-    if (block_size > WARP_SIZE) {
-
-        int warp_id = item_ct1.get_local_id(2) / WARP_SIZE;
-        int lane_id = item_ct1.get_local_id(2) % WARP_SIZE;
-        if (lane_id == 0) {
-            s_sum[warp_id] = tmp;
-        }
-        /*
-        DPCT1118:1: SYCL group functions and algorithms must be encountered in
-        converged control flow. You may need to adjust the code.
-        */
-        /*
-        DPCT1065:54: Consider replacing sycl::nd_item::barrier() with
-        sycl::nd_item::barrier(sycl::access::fence_space::local_space) for
-        better performance if there is no access to global memory.
-        */
-        item_ct1.barrier();
-        tmp = s_sum[lane_id];
-        tmp = warp_reduce_sum(tmp, item_ct1);
-    }
-
-    float mean = tmp / group_size;
-    tmp = 0.0f;
-
-    for (int j = start; j < end; j += block_size) {
-        float xi = x[j] - mean;
-        dst[j] = xi;
-        tmp += xi * xi;
-    }
-
-    tmp = warp_reduce_sum(tmp, item_ct1);
-    if (block_size > WARP_SIZE) {
-
-        int warp_id = item_ct1.get_local_id(2) / WARP_SIZE;
-        int lane_id = item_ct1.get_local_id(2) % WARP_SIZE;
-        if (lane_id == 0) {
-            s_sum[warp_id] = tmp;
-        }
-        /*
-        DPCT1118:2: SYCL group functions and algorithms must be encountered in
-        converged control flow. You may need to adjust the code.
-        */
-        /*
-        DPCT1065:55: Consider replacing sycl::nd_item::barrier() with
-        sycl::nd_item::barrier(sycl::access::fence_space::local_space) for
-        better performance if there is no access to global memory.
-        */
-        item_ct1.barrier();
-        tmp = s_sum[lane_id];
-        tmp = warp_reduce_sum(tmp, item_ct1);
-    }
-
-    float variance = tmp / group_size;
-    float scale = sycl::rsqrt(variance + eps);
-    for (int j = start; j < end; j += block_size) {
-        dst[j] *= scale;
-    }
-}
-
-static void rms_norm_f32(const float * x, float * dst, const int ncols, const float eps,
-                         const sycl::nd_item<3> &item_ct1, float *s_sum, int block_size) {
-    const int row = item_ct1.get_group(2) * item_ct1.get_local_range(1) +
-                    item_ct1.get_local_id(1);
-    const int tid = item_ct1.get_local_id(2);
-
-    float tmp = 0.0f; // partial sum for thread in warp
-
-    for (int col = tid; col < ncols; col += block_size) {
-        const float xi = x[row*ncols + col];
-        tmp += xi * xi;
-    }
-
-    // sum up partial sums
-    tmp = warp_reduce_sum(tmp, item_ct1);
-    if (block_size > WARP_SIZE) {
-
-        int warp_id = item_ct1.get_local_id(2) / WARP_SIZE;
-        int lane_id = item_ct1.get_local_id(2) % WARP_SIZE;
-        if (lane_id == 0) {
-            s_sum[warp_id] = tmp;
-        }
-        /*
-        DPCT1118:3: SYCL group functions and algorithms must be encountered in
-        converged control flow. You may need to adjust the code.
-        */
-        item_ct1.barrier(sycl::access::fence_space::local_space);
-        tmp = s_sum[lane_id];
-        tmp = warp_reduce_sum(tmp, item_ct1);
-    }
-
-    const float mean = tmp / ncols;
-    const float scale = sycl::rsqrt(mean + eps);
-
-    for (int col = tid; col < ncols; col += block_size) {
-        dst[row*ncols + col] = scale * x[row*ncols + col];
-    }
-}
-
+template
 static void quantize_q8_1(const float * __restrict__ x, void * __restrict__ vy, const int kx, const int kx_padded,
                           const sycl::nd_item<3> &item_ct1) {
-    const int ix = item_ct1.get_local_range(2) * item_ct1.get_group(2) +
-                   item_ct1.get_local_id(2);
+    const int ix = (item_ct1.get_local_range(2) * item_ct1.get_group(2) +
+                    item_ct1.get_local_id(2)) * QUANT_BLOCK_TILE;
 
     if (ix >= kx_padded) {
         return;
@@ -578,23 +377,39 @@ static void quantize_q8_1(const float * __restrict__ x, void * __restrict__ vy,
 
     const int ib = i_padded / QK8_1; // block index
     const int iqs = i_padded % QK8_1; // quant index
-
-    const float xi = ix < kx ? x[iy*kx + ix] : 0.0f;
-    float amax = sycl::fabs((float)xi);
-    float sum = xi;
-
+    typedef  sycl::vec TC;
+    typedef  sycl::vec TQ;
+    TC zeros;
+    TQ qzeros;
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
-        amax = sycl::fmax(amax, dpct::permute_sub_group_by_xor(
-                                    item_ct1.get_sub_group(), amax, mask));
-        sum +=
-            dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), sum, mask);
+    for (int i = 0; i < QUANT_BLOCK_TILE; i++)
+    {
+        zeros[i] = 0.f;
+        qzeros[i] = 0;
+    }
+    const TC xi = ix < kx ? *(TC *)&x[iy * kx + ix] : zeros;
+    float sum = xi[0];
+    float amax = sycl::fabs(xi[0]);
+#pragma unroll
+    for (int i = 1; i < QUANT_BLOCK_TILE; i++)
+    {
+        sum += xi[i];
+        amax = sycl::fmax(sycl::fabs(xi[i]), amax);
     }
+    sum = warp_reduce_sum(sum, item_ct1);
+    amax = warp_reduce_max(amax, item_ct1);
 
     const float d = amax / 127;
-    const int8_t q = amax == 0.0f ? 0 : sycl::round(xi / d);
+    TQ q = qzeros;
+    if (amax != 0.0f)
+    {
+#pragma unroll
+        for (int i = 0; i < QUANT_BLOCK_TILE; i++) {
+            q[i] = sycl::round(xi[i] / d);
+        }
+    }
 
-    y[ib].qs[iqs] = q;
+    *(TQ *)&y[ib].qs[iqs] = q;
 
     if (iqs > 0) {
         return;
@@ -728,7 +543,7 @@ static void mul_mat_p021_f16_f32(
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -781,7 +596,7 @@ static void mul_mat_vec_nc_f16_f32( // nc == non-contiguous
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -1643,99 +1458,6 @@ static void sqr_f32_sycl(const float *x, float *dst, const int k,
         });
 }
 
-static void norm_f32_sycl(const float *x, float *dst, const int ncols,
-                          const int nrows, const float eps,
-                          queue_ptr stream) {
-    GGML_ASSERT(ncols % WARP_SIZE == 0);
-    if (ncols < 1024) {
-        const sycl::range<3> block_dims(1, 1, WARP_SIZE);
-        stream->submit([&](sycl::handler &cgh) {
-            sycl::local_accessor s_sum_acc_ct1(
-                sycl::range<1>(32), cgh);
-
-            cgh.parallel_for(
-                sycl::nd_range<3>(sycl::range<3>(1, 1, nrows) * block_dims,
-                                  block_dims),
-                [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
-                        norm_f32(x, dst, ncols, eps, item_ct1,
-                                            s_sum_acc_ct1.get_pointer(), WARP_SIZE);
-                    });
-        });
-    } else {
-        const int work_group_size = get_work_group_size(stream->get_device());
-        const sycl::range<3> block_dims(1, 1, work_group_size);
-        /*
-        DPCT1049:17: The work-group size passed to the SYCL kernel may exceed
-        the limit. To get the device limit, query
-        info::device::max_work_group_size. Adjust the work-group size if needed.
-        */
-        stream->submit([&](sycl::handler &cgh) {
-            sycl::local_accessor s_sum_acc_ct1(
-                sycl::range<1>(32), cgh);
-
-            cgh.parallel_for(
-                sycl::nd_range<3>(sycl::range<3>(1, 1, nrows) * block_dims,
-                                  block_dims),
-                [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
-                        norm_f32(x, dst, ncols, eps, item_ct1,
-                                       s_sum_acc_ct1.get_pointer(), work_group_size);
-                    });
-        });
-    }
-}
-
-static void group_norm_f32_sycl(const float *x, float *dst,
-                                const int num_groups, const int group_size,
-                                const int ne_elements, queue_ptr stream) {
-    static const float eps = 1e-6f;
-    if (group_size < 1024) {
-        const sycl::range<3> block_dims(1, 1, WARP_SIZE);
-        stream->submit([&](sycl::handler &cgh) {
-            sycl::local_accessor s_sum_acc_ct1(sycl::range<1>(32),
-                                                         cgh);
-
-            const float eps_ct4 = eps;
-
-            cgh.parallel_for(
-                sycl::nd_range<3>(sycl::range<3>(1, 1, num_groups) * block_dims,
-                                  block_dims),
-                [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
-                        group_norm_f32(
-                            x, dst, group_size, ne_elements, eps_ct4, item_ct1,
-                            s_sum_acc_ct1.get_pointer(), WARP_SIZE);
-                    });
-        });
-    } else {
-        const int work_group_size = get_work_group_size(stream->get_device());
-        const sycl::range<3> block_dims(1, 1, work_group_size);
-        /*
-        DPCT1049:18: The work-group size passed to the SYCL kernel may exceed
-        the limit. To get the device limit, query
-        info::device::max_work_group_size. Adjust the work-group size if needed.
-        */
-
-        stream->submit([&](sycl::handler &cgh) {
-            sycl::local_accessor s_sum_acc_ct1(sycl::range<1>(32),
-                                                         cgh);
-
-            const float eps_ct4 = eps;
-
-            cgh.parallel_for(
-                sycl::nd_range<3>(sycl::range<3>(1, 1, num_groups) * block_dims,
-                                  block_dims),
-                [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
-                        group_norm_f32(x, dst, group_size, ne_elements,
-                                             eps_ct4, item_ct1,
-                                             s_sum_acc_ct1.get_pointer(), work_group_size);
-                    });
-        });
-    }
-}
-
 static void concat_f32_sycl(const float *x, const float *y, float *dst,
                             const int ne0, int ne1, int ne2, int ne02,
                             queue_ptr stream) {
@@ -1777,64 +1499,22 @@ static void pad_f32_sycl(const float *x, float *dst, const int ne00,
         });
 }
 
-static void rms_norm_f32_sycl(const float *x, float *dst, const int ncols,
-                              const int nrows, const float eps,
-                              queue_ptr stream) {
-    GGML_ASSERT(ncols % WARP_SIZE == 0);
-    // printf("%s ncols=%d, nrows=%d, WARP_SIZE=%d\n", __func__, ncols, nrows, WARP_SIZE);
-    if (ncols < 1024) {
-        const sycl::range<3> block_dims(1, 1, WARP_SIZE);
-        stream->submit([&](sycl::handler &cgh) {
-            sycl::local_accessor s_sum_acc_ct1(sycl::range<1>(32),
-                                                         cgh);
-
-            cgh.parallel_for(
-                sycl::nd_range<3>(sycl::range<3>(1, 1, nrows) * block_dims,
-                                  block_dims),
-                [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
-                        rms_norm_f32(x, dst, ncols, eps, item_ct1,
-                                                s_sum_acc_ct1.get_pointer(), WARP_SIZE);
-                    });
-        });
-    } else {
-        const int work_group_size = get_work_group_size(stream->get_device());
-        const sycl::range<3> block_dims(1, 1, work_group_size);
-        /*
-        DPCT1049:19: The work-group size passed to the SYCL kernel may exceed
-        the limit. To get the device limit, query
-        info::device::max_work_group_size. Adjust the work-group size if needed.
-        */
-        stream->submit([&](sycl::handler &cgh) {
-            sycl::local_accessor s_sum_acc_ct1(sycl::range<1>(32),
-                                                         cgh);
-
-            cgh.parallel_for(
-                sycl::nd_range<3>(sycl::range<3>(1, 1, nrows) * block_dims,
-                                  block_dims),
-                [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
-                        rms_norm_f32(x, dst, ncols, eps, item_ct1,
-                                           s_sum_acc_ct1.get_pointer(), work_group_size);
-                    });
-        });
-    }
-}
-
 static void quantize_row_q8_1_sycl(const float *x, void *vy, const int kx,
                                    const int ky, const int kx_padded,
                                    queue_ptr stream) {
     const int block_num_x = (kx_padded + SYCL_QUANTIZE_BLOCK_SIZE - 1) / SYCL_QUANTIZE_BLOCK_SIZE;
     const sycl::range<3> num_blocks(1, ky, block_num_x);
-    const sycl::range<3> block_size(1, 1, SYCL_DEQUANTIZE_BLOCK_SIZE);
+    int constexpr QUANT_BLOCK_TILE = QK8_1 / WARP_SIZE;
+    static_assert(QK8_1 % WARP_SIZE == 0);
+    const sycl::range<3> block_size(1, 1, SYCL_QUANTIZE_BLOCK_SIZE / QUANT_BLOCK_TILE);
     {
         dpct::has_capability_or_fail(stream->get_device(),
                                      {sycl::aspect::fp16});
 
         stream->parallel_for(
             sycl::nd_range<3>(num_blocks * block_size, block_size),
-            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] {
-                quantize_q8_1(x, vy, kx, kx_padded, item_ct1);
+            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+                quantize_q8_1(x, vy, kx, kx_padded, item_ct1);
             });
     }
 }
@@ -1854,7 +1534,7 @@ static void ggml_mul_mat_p021_f16_f32_sycl(const void *vx, const float *y,
 
         stream->parallel_for(
             sycl::nd_range<3>(block_nums * block_dims, block_dims),
-            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] {
+            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                 mul_mat_p021_f16_f32(vx, y, dst, ncols_x, nrows_x, nchannels_x,
                                      nchannels_y, item_ct1);
             });
@@ -1874,7 +1554,7 @@ static void ggml_mul_mat_vec_nc_f16_f32_sycl(
 
         stream->parallel_for(
             sycl::nd_range<3>(block_nums * block_dims, block_dims),
-            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] {
+            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                 mul_mat_vec_nc_f16_f32(vx, y, dst, ncols_x, nrows_x,
                                        row_stride_x, channel_stride_x,
                                        nchannels_y / nchannels_x, item_ct1);
@@ -2139,7 +1819,7 @@ static void sum_rows_f32_sycl(const float *x, float *dst, const int ncols,
     const sycl::range<3> block_nums(1, nrows, 1);
     stream->parallel_for(sycl::nd_range<3>(block_nums * block_dims, block_dims),
                          [=](sycl::nd_item<3> item_ct1)
-                             [[intel::reqd_sub_group_size(32)]] {
+                             [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                                  k_sum_rows_f32(x, dst, ncols, item_ct1);
                              });
 }
@@ -2220,7 +1900,7 @@ static void soft_max_f32_submitter(const float * x, const float * mask, float *
 
         cgh.parallel_for(
             sycl::nd_range<3>(block_nums * block_dims, block_dims),
-            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] {
+            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                 soft_max_f32(x, mask, dst, ncols_par,
                                                                              nrows_y, scale, max_bias, m0,
                                                                              m1, n_head_log2, item_ct1,
@@ -2400,12 +2080,6 @@ static inline int get_sycl_env(const char *env_name, int default_val) {
     return user_number;
 }
 
-static inline int get_work_group_size(const sycl::device& device) {
-    dpct::device_info prop;
-    dpct::get_device_info(prop, device);
-    return prop.get_max_work_group_size();
-}
-
 static void ggml_check_sycl() try {
     static bool initialized = false;
 
@@ -2964,45 +2638,6 @@ inline void ggml_sycl_op_sqr(ggml_backend_sycl_context & ctx, const ggml_tensor
     (void) src1_dd;
 }
 
-inline void ggml_sycl_op_norm(ggml_backend_sycl_context & ctx, const ggml_tensor *src0, const ggml_tensor *src1,
-                              ggml_tensor *dst, const float *src0_dd,
-                              const float *src1_dd, float *dst_dd,
-                              const queue_ptr &main_stream) {
-
-    GGML_ASSERT(src0->type == GGML_TYPE_F32);
-    GGML_ASSERT( dst->type == GGML_TYPE_F32);
-
-    const int64_t ne00 = src0->ne[0];
-    const int64_t nrows = ggml_nrows(src0);
-
-    float eps;
-    memcpy(&eps, dst->op_params, sizeof(float));
-
-    norm_f32_sycl(src0_dd, dst_dd, ne00, nrows, eps, main_stream);
-
-    (void) src1;
-    (void) dst;
-    (void) src1_dd;
-}
-
-inline void ggml_sycl_op_group_norm(ggml_backend_sycl_context & ctx, const ggml_tensor *src0,
-                                    const ggml_tensor *src1, ggml_tensor *dst,
-                                    const float *src0_dd, const float *src1_dd,
-                                    float *dst_dd,
-                                    const queue_ptr &main_stream) {
-
-    GGML_ASSERT(src0->type == GGML_TYPE_F32);
-    GGML_ASSERT( dst->type == GGML_TYPE_F32);
-
-    int num_groups = dst->op_params[0];
-    int group_size = src0->ne[0] * src0->ne[1] * ((src0->ne[2] + num_groups - 1) / num_groups);
-    group_norm_f32_sycl(src0_dd, dst_dd, num_groups, group_size, src0->ne[0] * src0->ne[1] * src0->ne[2], main_stream);
-
-    (void) src1;
-    (void) dst;
-    (void) src1_dd;
-}
-
 inline void ggml_sycl_op_concat(ggml_backend_sycl_context & ctx, const ggml_tensor *src0,
                                 const ggml_tensor *src1, ggml_tensor *dst,
                                 const float *src0_dd, const float *src1_dd,
@@ -3066,28 +2701,6 @@ inline void ggml_sycl_op_pad(ggml_backend_sycl_context & ctx, const ggml_tensor
     (void) src1_dd;
 }
 
-inline void ggml_sycl_op_rms_norm(ggml_backend_sycl_context & ctx, const ggml_tensor *src0,
-                                  const ggml_tensor *src1, ggml_tensor *dst,
-                                  const float *src0_dd, const float *src1_dd,
-                                  float *dst_dd,
-                                  const queue_ptr &main_stream) {
-
-    GGML_ASSERT(src0->type == GGML_TYPE_F32);
-    GGML_ASSERT( dst->type == GGML_TYPE_F32);
-
-    const int64_t ne00 = src0->ne[0];
-    const int64_t nrows = ggml_nrows(src0);
-
-    float eps;
-    memcpy(&eps, dst->op_params, sizeof(float));
-
-    rms_norm_f32_sycl(src0_dd, dst_dd, ne00, nrows, eps, main_stream);
-
-    (void) src1;
-    (void) dst;
-    (void) src1_dd;
-}
-
 static int64_t get_row_rounding(ggml_type type, const std::array & tensor_split) {
     int64_t min_compute_capability = INT_MAX;
     int64_t max_compute_capability = INT_MIN;
@@ -4273,7 +3886,6 @@ bool ggml_sycl_supports_dmmv(enum ggml_type type) {
 
 static void ggml_sycl_mul_mat(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
     const bool split = ggml_backend_buffer_is_sycl_split(src0->buffer);
-
     int64_t min_compute_capability = INT_MAX;
 
     if (split) {
diff --git a/ggml/src/ggml-sycl/backend.hpp b/ggml/src/ggml-sycl/backend.hpp
index d5a63cd710cc3..3afa3391938f2 100644
--- a/ggml/src/ggml-sycl/backend.hpp
+++ b/ggml/src/ggml-sycl/backend.hpp
@@ -20,5 +20,6 @@
 #include "mmq.hpp"
 #include "mmvq.hpp"
 #include "rope.hpp"
+#include "norm.hpp"
 
 #endif // GGML_SYCL_BACKEND_HPP
diff --git a/ggml/src/ggml-sycl/common.hpp b/ggml/src/ggml-sycl/common.hpp
index e01f91633a4bf..dfd4a7c2c606b 100644
--- a/ggml/src/ggml-sycl/common.hpp
+++ b/ggml/src/ggml-sycl/common.hpp
@@ -295,5 +295,60 @@ struct ggml_backend_sycl_context {
     }
 };
 
+// common host functions
+
+static inline int get_work_group_size(const sycl::device& device) {
+    dpct::device_info prop;
+    dpct::get_device_info(prop, device);
+    return prop.get_max_work_group_size();
+}
+
+
+// common device functions
+
+static __dpct_inline__ float warp_reduce_sum(float x,
+    const sycl::nd_item<3>& item_ct1) {
+#pragma unroll
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+        /*
+        DPCT1096:98: The right-most dimension of the work-group used in the SYCL
+        kernel that calls this function may be less than "32". The function
+        "dpct::permute_sub_group_by_xor" may return an unexpected result on the
+        CPU device. Modify the size of the work-group to ensure that the value
+        of the right-most dimension is a multiple of "32".
+        */
+        x += dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), x, mask);
+    }
+    return x;
+}
+
+static __dpct_inline__ sycl::float2
+warp_reduce_sum(sycl::float2 a, const sycl::nd_item<3>& item_ct1) {
+#pragma unroll
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+        a.x() += dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), a.x(),
+            mask);
+        a.y() += dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), a.y(),
+            mask);
+    }
+    return a;
+}
+
+static __dpct_inline__ float warp_reduce_max(float x,
+    const sycl::nd_item<3>& item_ct1) {
+#pragma unroll
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+        /*
+        DPCT1096:97: The right-most dimension of the work-group used in the SYCL
+        kernel that calls this function may be less than "32". The function
+        "dpct::permute_sub_group_by_xor" may return an unexpected result on the
+        CPU device. Modify the size of the work-group to ensure that the value
+        of the right-most dimension is a multiple of "32".
+        */
+        x = sycl::fmax(x, dpct::permute_sub_group_by_xor(
+            item_ct1.get_sub_group(), x, mask));
+    }
+    return x;
+}
 
 #endif // GGML_SYCL_COMMON_HPP
diff --git a/ggml/src/ggml-sycl/dmmv.cpp b/ggml/src/ggml-sycl/dmmv.cpp
index 3a87d3ef8e45c..927819281fd0a 100644
--- a/ggml/src/ggml-sycl/dmmv.cpp
+++ b/ggml/src/ggml-sycl/dmmv.cpp
@@ -76,7 +76,7 @@ static void dequantize_mul_mat_vec(const void * __restrict__ vx, const dfloat *
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -104,7 +104,7 @@ static void convert_mul_mat_vec_f16_sycl(const void *vx, const dfloat *y,
 
         stream->parallel_for(
             sycl::nd_range<3>(block_nums * block_dims, block_dims),
-            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] {
+            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                 dequantize_mul_mat_vec<1, 1, convert_f16>(vx, y, dst, ncols,
                                                           nrows, item_ct1);
             });
@@ -227,7 +227,7 @@ static void dequantize_mul_mat_vec_q2_k(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -346,7 +346,7 @@ static void dequantize_mul_mat_vec_q3_k(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -499,7 +499,7 @@ static void dequantize_mul_mat_vec_q4_k(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -633,7 +633,7 @@ static void dequantize_mul_mat_vec_q5_k(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -748,7 +748,7 @@ static void dequantize_mul_mat_vec_q6_k(const void * __restrict__ vx, const floa
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -774,7 +774,7 @@ static void dequantize_mul_mat_vec_q4_0_sycl(const void *vx, const dfloat *y,
 
         stream->parallel_for(
             sycl::nd_range<3>(block_nums * block_dims, block_dims),
-            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] {
+            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                 dequantize_mul_mat_vec(
                     vx, y, dst, ncols, nrows, item_ct1);
             });
@@ -795,7 +795,7 @@ static void dequantize_mul_mat_vec_q4_1_sycl(const void *vx, const dfloat *y,
 
         stream->parallel_for(
             sycl::nd_range<3>(block_nums * block_dims, block_dims),
-            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] {
+            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                 dequantize_mul_mat_vec(
                     vx, y, dst, ncols, nrows, item_ct1);
             });
@@ -816,7 +816,7 @@ static void dequantize_mul_mat_vec_q5_0_sycl(const void *vx, const dfloat *y,
 
         stream->parallel_for(
             sycl::nd_range<3>(block_nums * block_dims, block_dims),
-            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] {
+            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                 dequantize_mul_mat_vec(
                     vx, y, dst, ncols, nrows, item_ct1);
             });
@@ -837,7 +837,7 @@ static void dequantize_mul_mat_vec_q5_1_sycl(const void *vx, const dfloat *y,
 
         stream->parallel_for(
             sycl::nd_range<3>(block_nums * block_dims, block_dims),
-            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] {
+            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                 dequantize_mul_mat_vec(
                     vx, y, dst, ncols, nrows, item_ct1);
             });
@@ -858,7 +858,7 @@ static void dequantize_mul_mat_vec_q8_0_sycl(const void *vx, const dfloat *y,
 
         stream->parallel_for(
             sycl::nd_range<3>(block_nums * block_dims, block_dims),
-            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] {
+            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                 dequantize_mul_mat_vec(
                     vx, y, dst, ncols, nrows, item_ct1);
             });
@@ -873,10 +873,10 @@ static void dequantize_mul_mat_vec_q2_K_sycl(const void *vx, const float *y,
     const int ny = 2; // very slightly faster than 1 even when K_QUANTS_PER_ITERATION = 2
     const int block_num_y = (nrows + ny - 1) / ny;
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, ny, 32);
+    const sycl::range<3> block_dims(1, ny, WARP_SIZE);
     stream->parallel_for(
         sycl::nd_range<3>(block_nums * block_dims, block_dims),
-        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] {
+        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
             dequantize_mul_mat_vec_q2_k(vx, y, dst, ncols, nrows, item_ct1);
         });
 }
@@ -889,10 +889,10 @@ static void dequantize_mul_mat_vec_q3_K_sycl(const void *vx, const float *y,
     const int ny = 2 / K_QUANTS_PER_ITERATION;
     const int block_num_y = (nrows + ny - 1) / ny;
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, ny, 32);
+    const sycl::range<3> block_dims(1, ny, WARP_SIZE);
     stream->parallel_for(
         sycl::nd_range<3>(block_nums * block_dims, block_dims),
-        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] {
+        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
             dequantize_mul_mat_vec_q3_k(vx, y, dst, ncols, nrows, item_ct1);
         });
 }
@@ -905,10 +905,10 @@ static void dequantize_mul_mat_vec_q4_K_sycl(const void *vx, const float *y,
     const int ny = 2 / K_QUANTS_PER_ITERATION;
     const int block_num_y = (nrows + ny - 1) / ny;
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, ny, 32);
+    const sycl::range<3> block_dims(1, ny, WARP_SIZE);
     stream->parallel_for(
         sycl::nd_range<3>(block_nums * block_dims, block_dims),
-        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] {
+        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
             dequantize_mul_mat_vec_q4_k(vx, y, dst, ncols, nrows, item_ct1);
         });
 }
@@ -918,10 +918,10 @@ static void dequantize_mul_mat_vec_q5_K_sycl(const void *vx, const float *y,
                                              const int nrows,
                                              dpct::queue_ptr stream) {
     GGML_ASSERT(ncols % QK_K == 0);
-    const sycl::range<3> block_dims(1, 1, 32);
+    const sycl::range<3> block_dims(1, 1, WARP_SIZE);
     stream->parallel_for(
         sycl::nd_range<3>(sycl::range<3>(1, 1, nrows) * block_dims, block_dims),
-        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] {
+        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
             dequantize_mul_mat_vec_q5_k(vx, y, dst, ncols, item_ct1);
         });
 }
@@ -934,10 +934,10 @@ static void dequantize_mul_mat_vec_q6_K_sycl(const void *vx, const float *y,
     const int ny = 2 / K_QUANTS_PER_ITERATION;
     const int block_num_y = (nrows + ny - 1) / ny;
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, ny, 32);
+    const sycl::range<3> block_dims(1, ny, WARP_SIZE);
     stream->parallel_for(
         sycl::nd_range<3>(block_nums * block_dims, block_dims),
-        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] {
+        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
             dequantize_mul_mat_vec_q6_k(vx, y, dst, ncols, nrows, item_ct1);
         });
 }
diff --git a/ggml/src/ggml-sycl/mmvq.cpp b/ggml/src/ggml-sycl/mmvq.cpp
index 9b751f3c67281..3fbc4dd606bbe 100644
--- a/ggml/src/ggml-sycl/mmvq.cpp
+++ b/ggml/src/ggml-sycl/mmvq.cpp
@@ -37,7 +37,7 @@ static void mul_mat_vec_q(const void * __restrict__ vx, const void * __restrict_
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -85,7 +85,7 @@ static void mul_mat_vec_q_iq2_xxs_q8_1(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -133,7 +133,7 @@ static void mul_mat_vec_q_iq2_xs_q8_1(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -181,7 +181,7 @@ static void mul_mat_vec_q_iq2_s_q8_1(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -229,7 +229,7 @@ static void mul_mat_vec_q_iq3_xxs_q8_1(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -277,7 +277,7 @@ static void mul_mat_vec_q_iq3_s_q8_1(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -325,7 +325,7 @@ static void mul_mat_vec_q_iq1_s_q8_1(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -373,7 +373,7 @@ static void mul_mat_vec_q_iq1_m_q8_1(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -421,7 +421,7 @@ static void mul_mat_vec_q_iq4_nl_q8_1(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -470,7 +470,7 @@ static void mul_mat_vec_q_iq4_xs_q8_1(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = 16; mask > 0; mask >>= 1) {
+    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -495,7 +495,7 @@ static void mul_mat_vec_q4_0_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q(
                             vx, vy, dst, ncols, nrows, item_ct1);
@@ -519,7 +519,7 @@ static void mul_mat_vec_q4_1_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q(
                             vx, vy, dst, ncols, nrows, item_ct1);
@@ -543,7 +543,7 @@ static void mul_mat_vec_q5_0_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q(
                             vx, vy, dst, ncols, nrows, item_ct1);
@@ -567,7 +567,7 @@ static void mul_mat_vec_q5_1_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q(
                             vx, vy, dst, ncols, nrows, item_ct1);
@@ -591,7 +591,7 @@ static void mul_mat_vec_q8_0_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q(
                             vx, vy, dst, ncols, nrows, item_ct1);
@@ -615,7 +615,7 @@ static void mul_mat_vec_q2_K_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q(
                             vx, vy, dst, ncols, nrows, item_ct1);
@@ -639,7 +639,7 @@ static void mul_mat_vec_q3_K_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q(
                             vx, vy, dst, ncols, nrows, item_ct1);
@@ -663,7 +663,7 @@ static void mul_mat_vec_q4_K_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q(
                             vx, vy, dst, ncols, nrows, item_ct1);
@@ -687,7 +687,7 @@ static void mul_mat_vec_q5_K_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q(
                             vx, vy, dst, ncols, nrows, item_ct1);
@@ -711,7 +711,7 @@ static void mul_mat_vec_q6_K_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q(
                             vx, vy, dst, ncols, nrows, item_ct1);
@@ -734,7 +734,7 @@ static void mul_mat_vec_iq2_xxs_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q_iq2_xxs_q8_1(
                             vx, vy, dst, ncols, nrows, item_ct1);
                     });
@@ -759,7 +759,7 @@ static void mul_mat_vec_iq2_xs_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q_iq2_xs_q8_1(
                             vx, vy, dst, ncols, nrows, item_ct1);
                     });
@@ -784,7 +784,7 @@ static void mul_mat_vec_iq2_s_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q_iq2_s_q8_1(
                             vx, vy, dst, ncols, nrows, item_ct1);
                     });
@@ -809,7 +809,7 @@ static void mul_mat_vec_iq3_xxs_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q_iq3_xxs_q8_1(
                             vx, vy, dst, ncols, nrows, item_ct1);
                     });
@@ -833,7 +833,7 @@ static void mul_mat_vec_iq3_s_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q_iq3_s_q8_1(
                             vx, vy, dst, ncols, nrows, item_ct1);
                     });
@@ -858,7 +858,7 @@ static void mul_mat_vec_iq1_s_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q_iq1_s_q8_1(
                             vx, vy, dst, ncols, nrows, item_ct1);
                     });
@@ -879,7 +879,7 @@ static void mul_mat_vec_iq1_m_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q_iq1_m_q8_1(
                             vx, vy, dst, ncols, nrows, item_ct1);
                     });
@@ -901,7 +901,7 @@ static void mul_mat_vec_iq4_nl_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q_iq4_nl_q8_1(
                             vx, vy, dst, ncols, nrows, item_ct1);
                     });
@@ -923,7 +923,7 @@ static void mul_mat_vec_iq4_xs_q8_1_sycl(const void *vx, const void *vy,
             cgh.parallel_for(
                 sycl::nd_range<3>(block_nums * block_dims, block_dims),
                 [=](sycl::nd_item<3> item_ct1)
-                    [[intel::reqd_sub_group_size(32)]] {
+                    [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                         mul_mat_vec_q_iq4_xs_q8_1(
                             vx, vy, dst, ncols, nrows, item_ct1);
                     });
@@ -936,7 +936,7 @@ void ggml_sycl_op_mul_mat_vec_q(
     const ggml_tensor *src0, const ggml_tensor *src1, ggml_tensor *dst,
     const char *src0_dd_i, const float *src1_ddf_i, const char *src1_ddq_i,
     float *dst_dd_i, const int64_t row_low, const int64_t row_high,
-    const int64_t src1_ncols, const int64_t src1_padded_row_size,
+    const int64_t src1_ncols, const int64_t src1_padded_col_size,
     const dpct::queue_ptr &stream) {
 
     const int64_t ne10 = src1->ne[0];
@@ -948,77 +948,80 @@ void ggml_sycl_op_mul_mat_vec_q(
     int id;
     SYCL_CHECK(
         CHECK_TRY_ERROR(id = get_current_device_id()));
-
+    const size_t q8_1_ts = sizeof(block_q8_1);
+    const size_t q8_1_bs = QK8_1;
     // the main device has a larger memory buffer to hold the results from all GPUs
     // nrows_dst == nrows of the matrix that the kernel writes into
     const int64_t nrows_dst = id == ctx.device ? ne00 : row_diff;
-
-    switch (src0->type) {
+    for (int i = 0; i < src1_ncols; i++)
+    {
+        const size_t src1_ddq_i_offset = i * src1_padded_col_size * q8_1_ts / q8_1_bs;
+        const char* src1_ddq_i_bs = src1_ddq_i + src1_ddq_i_offset;
+        float* dst_dd_i_bs = dst_dd_i + i * dst->ne[0];
+        switch (src0->type) {
         case GGML_TYPE_Q4_0:
-            mul_mat_vec_q4_0_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_q4_0_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_Q4_1:
-            mul_mat_vec_q4_1_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_q4_1_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_Q5_0:
-            mul_mat_vec_q5_0_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_q5_0_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_Q5_1:
-            mul_mat_vec_q5_1_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_q5_1_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_Q8_0:
-            mul_mat_vec_q8_0_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_q8_0_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_Q2_K:
-            mul_mat_vec_q2_K_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_q2_K_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_Q3_K:
-            mul_mat_vec_q3_K_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_q3_K_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_Q4_K:
-            mul_mat_vec_q4_K_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_q4_K_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_Q5_K:
-            mul_mat_vec_q5_K_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_q5_K_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_Q6_K:
-            mul_mat_vec_q6_K_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_q6_K_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_IQ1_S:
-            mul_mat_vec_iq1_s_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_iq1_s_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_IQ1_M:
-            mul_mat_vec_iq1_m_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_iq1_m_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_IQ2_XXS:
-            mul_mat_vec_iq2_xxs_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_iq2_xxs_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_IQ2_XS:
-            mul_mat_vec_iq2_xs_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_iq2_xs_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_IQ2_S:
-            mul_mat_vec_iq2_s_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_iq2_s_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_IQ3_XXS:
-            mul_mat_vec_iq3_xxs_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_iq3_xxs_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_IQ3_S:
-            mul_mat_vec_iq3_s_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_iq3_s_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_IQ4_NL:
-            mul_mat_vec_iq4_nl_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_iq4_nl_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         case GGML_TYPE_IQ4_XS:
-            mul_mat_vec_iq4_xs_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            mul_mat_vec_iq4_xs_q8_1_sycl(src0_dd_i, src1_ddq_i_bs, dst_dd_i_bs, ne00, row_diff, stream);
             break;
         default:
             GGML_ASSERT(false);
             break;
+        }
     }
-
     (void) src1;
     (void) dst;
     (void) src1_ddf_i;
-    (void) src1_ncols;
-    (void) src1_padded_row_size;
 }
diff --git a/ggml/src/ggml-sycl/norm.cpp b/ggml/src/ggml-sycl/norm.cpp
new file mode 100644
index 0000000000000..a77f7852ccecd
--- /dev/null
+++ b/ggml/src/ggml-sycl/norm.cpp
@@ -0,0 +1,370 @@
+#include "norm.hpp"
+
+static void norm_f32(const float* x, float* dst, const int ncols, const float eps,
+    const sycl::nd_item<3>& item_ct1, sycl::float2* s_sum, int block_size) {
+    const int row = item_ct1.get_group(2) * item_ct1.get_local_range(1) +
+        item_ct1.get_local_id(1);
+    const int tid = item_ct1.get_local_id(2);
+
+    const int nthreads = item_ct1.get_local_range(2);
+    const int nwarps = nthreads / WARP_SIZE;
+    assert(nwarps % WARP_SIZE == 0);
+    sycl::float2 mean_var = sycl::float2(0.f, 0.f);
+
+    for (int col = tid; col < ncols; col += block_size) {
+        const float xi = x[row * ncols + col];
+        mean_var.x() += xi;
+        mean_var.y() += xi * xi;
+    }
+
+    // sum up partial sums
+    mean_var = warp_reduce_sum(mean_var, item_ct1);
+    if (block_size > WARP_SIZE) {
+
+        int warp_id = item_ct1.get_local_id(2) / WARP_SIZE;
+        int lane_id = item_ct1.get_local_id(2) % WARP_SIZE;
+        if (lane_id == 0) {
+            s_sum[warp_id] = mean_var;
+        }
+        /*
+        DPCT1118:0: SYCL group functions and algorithms must be encountered in
+        converged control flow. You may need to adjust the code.
+        */
+        item_ct1.barrier(sycl::access::fence_space::local_space);
+        mean_var = 0.f;
+        int nreduce = nwarps / WARP_SIZE;
+        for (size_t i = 0; i < nreduce; i += 1)
+        {
+            mean_var += s_sum[lane_id + i * WARP_SIZE];
+        }
+        mean_var = warp_reduce_sum(mean_var, item_ct1);
+    }
+
+    const float mean = mean_var.x() / ncols;
+    const float var = mean_var.y() / ncols - mean * mean;
+    const float inv_std = sycl::rsqrt(var + eps);
+
+    for (int col = tid; col < ncols; col += block_size) {
+        dst[row * ncols + col] = (x[row * ncols + col] - mean) * inv_std;
+    }
+}
+
+static void group_norm_f32(const float* x, float* dst, const int group_size, const int ne_elements, const float eps,
+    const sycl::nd_item<3>& item_ct1, float* s_sum, int block_size) {
+    int start = item_ct1.get_group(2) * group_size;
+    int end = start + group_size;
+    const int nthreads = item_ct1.get_local_range(2);
+    const int nwarps = nthreads / WARP_SIZE;
+    assert(nwarps % WARP_SIZE == 0);
+    start += item_ct1.get_local_id(2);
+
+    if (end >= ne_elements) {
+        end = ne_elements;
+    }
+
+    float tmp = 0.0f; // partial sum for thread in warp
+
+    for (int j = start; j < end; j += block_size) {
+        tmp += x[j];
+    }
+
+    tmp = warp_reduce_sum(tmp, item_ct1);
+    if (block_size > WARP_SIZE) {
+
+        int warp_id = item_ct1.get_local_id(2) / WARP_SIZE;
+        int lane_id = item_ct1.get_local_id(2) % WARP_SIZE;
+        if (lane_id == 0) {
+            s_sum[warp_id] = tmp;
+        }
+        /*
+        DPCT1118:1: SYCL group functions and algorithms must be encountered in
+        converged control flow. You may need to adjust the code.
+        */
+        /*
+        DPCT1065:54: Consider replacing sycl::nd_item::barrier() with
+        sycl::nd_item::barrier(sycl::access::fence_space::local_space) for
+        better performance if there is no access to global memory.
+        */
+        item_ct1.barrier();
+        tmp = 0.f;
+        int nreduce = nwarps / WARP_SIZE;
+        for (size_t i = 0; i < nreduce; i += 1)
+        {
+            tmp += s_sum[lane_id + i * WARP_SIZE];
+        }
+        tmp = warp_reduce_sum(tmp, item_ct1);
+    }
+
+    float mean = tmp / group_size;
+    tmp = 0.0f;
+
+    for (int j = start; j < end; j += block_size) {
+        float xi = x[j] - mean;
+        dst[j] = xi;
+        tmp += xi * xi;
+    }
+
+    tmp = warp_reduce_sum(tmp, item_ct1);
+    if (block_size > WARP_SIZE) {
+
+        int warp_id = item_ct1.get_local_id(2) / WARP_SIZE;
+        int lane_id = item_ct1.get_local_id(2) % WARP_SIZE;
+        if (lane_id == 0) {
+            s_sum[warp_id] = tmp;
+        }
+        /*
+        DPCT1118:2: SYCL group functions and algorithms must be encountered in
+        converged control flow. You may need to adjust the code.
+        */
+        /*
+        DPCT1065:55: Consider replacing sycl::nd_item::barrier() with
+        sycl::nd_item::barrier(sycl::access::fence_space::local_space) for
+        better performance if there is no access to global memory.
+        */
+        item_ct1.barrier();
+        tmp = s_sum[lane_id];
+        tmp = warp_reduce_sum(tmp, item_ct1);
+    }
+
+    float variance = tmp / group_size;
+    float scale = sycl::rsqrt(variance + eps);
+    for (int j = start; j < end; j += block_size) {
+        dst[j] *= scale;
+    }
+}
+
+static void rms_norm_f32(const float* x, float* dst, const int ncols, const float eps,
+    const sycl::nd_item<3>& item_ct1, float* s_sum, int block_size) {
+    const int row = item_ct1.get_group(2) * item_ct1.get_local_range(1) +
+        item_ct1.get_local_id(1);
+    const int tid = item_ct1.get_local_id(2);
+    const int nthreads = item_ct1.get_local_range(2);
+    const int nwarps = nthreads / WARP_SIZE;
+    assert(nwarps % WARP_SIZE == 0);
+    float tmp = 0.0f; // partial sum for thread in warp
+
+    for (int col = tid; col < ncols; col += block_size) {
+        const float xi = x[row * ncols + col];
+        tmp += xi * xi;
+    }
+
+    // sum up partial sums
+    tmp = warp_reduce_sum(tmp, item_ct1);
+    if (block_size > WARP_SIZE) {
+
+        int warp_id = item_ct1.get_local_id(2) / WARP_SIZE;
+        int lane_id = item_ct1.get_local_id(2) % WARP_SIZE;
+        if (lane_id == 0) {
+            s_sum[warp_id] = tmp;
+        }
+        /*
+        DPCT1118:3: SYCL group functions and algorithms must be encountered in
+        converged control flow. You may need to adjust the code.
+        */
+        item_ct1.barrier(sycl::access::fence_space::local_space);
+        int nreduce = nwarps / WARP_SIZE;
+        tmp = 0.f;
+        for (size_t i = 0; i < nreduce; i += 1)
+        {
+            tmp += s_sum[lane_id + i * WARP_SIZE];
+        }
+        tmp = warp_reduce_sum(tmp, item_ct1);
+    }
+
+    const float mean = tmp / ncols;
+    const float scale = sycl::rsqrt(mean + eps);
+
+    for (int col = tid; col < ncols; col += block_size) {
+        dst[row * ncols + col] = scale * x[row * ncols + col];
+    }
+}
+
+static void norm_f32_sycl(const float* x, float* dst, const int ncols,
+    const int nrows, const float eps,
+    queue_ptr stream) {
+    GGML_ASSERT(ncols % WARP_SIZE == 0);
+    if (ncols < 1024) {
+        const sycl::range<3> block_dims(1, 1, WARP_SIZE);
+        stream->submit([&](sycl::handler& cgh) {
+            cgh.parallel_for(
+                sycl::nd_range<3>(sycl::range<3>(1, 1, nrows) * block_dims,
+                    block_dims),
+                [=](sycl::nd_item<3> item_ct1)
+                [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+                    norm_f32(x, dst, ncols, eps, item_ct1,
+                        nullptr, WARP_SIZE);
+                });
+            });
+    }
+    else {
+        const int work_group_size = get_work_group_size(stream->get_device());
+        const sycl::range<3> block_dims(1, 1, work_group_size);
+        /*
+        DPCT1049:17: The work-group size passed to the SYCL kernel may exceed
+        the limit. To get the device limit, query
+        info::device::max_work_group_size. Adjust the work-group size if needed.
+        */
+        stream->submit([&](sycl::handler& cgh) {
+            sycl::local_accessor s_sum_acc_ct1(
+                sycl::range<1>(work_group_size / WARP_SIZE), cgh);
+
+            cgh.parallel_for(
+                sycl::nd_range<3>(sycl::range<3>(1, 1, nrows) * block_dims,
+                    block_dims),
+                [=](sycl::nd_item<3> item_ct1)
+                [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+                    norm_f32(x, dst, ncols, eps, item_ct1,
+                        s_sum_acc_ct1.get_pointer(), work_group_size);
+                });
+            });
+    }
+}
+
+static void group_norm_f32_sycl(const float* x, float* dst,
+    const int num_groups, const int group_size,
+    const int ne_elements, queue_ptr stream) {
+    static const float eps = 1e-6f;
+    if (group_size < 1024) {
+        const sycl::range<3> block_dims(1, 1, WARP_SIZE);
+        stream->submit([&](sycl::handler& cgh) {
+            const float eps_ct4 = eps;
+            cgh.parallel_for(
+                sycl::nd_range<3>(sycl::range<3>(1, 1, num_groups) * block_dims,
+                    block_dims),
+                [=](sycl::nd_item<3> item_ct1)
+                [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+                    group_norm_f32(
+                        x, dst, group_size, ne_elements, eps_ct4, item_ct1,
+                        nullptr, WARP_SIZE);
+                });
+            });
+    }
+    else {
+        const int work_group_size = get_work_group_size(stream->get_device());
+        const sycl::range<3> block_dims(1, 1, work_group_size);
+        /*
+        DPCT1049:18: The work-group size passed to the SYCL kernel may exceed
+        the limit. To get the device limit, query
+        info::device::max_work_group_size. Adjust the work-group size if needed.
+        */
+
+        stream->submit([&](sycl::handler& cgh) {
+            sycl::local_accessor s_sum_acc_ct1(sycl::range<1>(work_group_size / WARP_SIZE),
+                cgh);
+
+            const float eps_ct4 = eps;
+
+            cgh.parallel_for(
+                sycl::nd_range<3>(sycl::range<3>(1, 1, num_groups) * block_dims,
+                    block_dims),
+                [=](sycl::nd_item<3> item_ct1)
+                [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+                    group_norm_f32(x, dst, group_size, ne_elements,
+                        eps_ct4, item_ct1,
+                        s_sum_acc_ct1.get_pointer(), work_group_size);
+                });
+            });
+    }
+}
+
+static void rms_norm_f32_sycl(const float* x, float* dst, const int ncols,
+    const int nrows, const float eps,
+    queue_ptr stream) {
+    GGML_ASSERT(ncols % WARP_SIZE == 0);
+    // printf("%s ncols=%d, nrows=%d, WARP_SIZE=%d\n", __func__, ncols, nrows, WARP_SIZE);
+    if (ncols < 1024) {
+        const sycl::range<3> block_dims(1, 1, WARP_SIZE);
+        stream->submit([&](sycl::handler& cgh) {
+            cgh.parallel_for(
+                sycl::nd_range<3>(sycl::range<3>(1, 1, nrows) * block_dims,
+                    block_dims),
+                [=](sycl::nd_item<3> item_ct1)
+                [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+                    rms_norm_f32(x, dst, ncols, eps, item_ct1,
+                        nullptr, WARP_SIZE);
+                });
+            });
+    }
+    else {
+        const int work_group_size = get_work_group_size(stream->get_device());
+        const sycl::range<3> block_dims(1, 1, work_group_size);
+        /*
+        DPCT1049:19: The work-group size passed to the SYCL kernel may exceed
+        the limit. To get the device limit, query
+        info::device::max_work_group_size. Adjust the work-group size if needed.
+        */
+        stream->submit([&](sycl::handler& cgh) {
+            sycl::local_accessor s_sum_acc_ct1(sycl::range<1>(work_group_size / WARP_SIZE),
+                cgh);
+            cgh.parallel_for(
+                sycl::nd_range<3>(sycl::range<3>(1, 1, nrows) * block_dims,
+                    block_dims),
+                [=](sycl::nd_item<3> item_ct1)
+                [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+                    rms_norm_f32(x, dst, ncols, eps, item_ct1,
+                        s_sum_acc_ct1.get_pointer(), work_group_size);
+                });
+            });
+    }
+}
+
+void ggml_sycl_op_norm(ggml_backend_sycl_context& ctx, const ggml_tensor* src0, const ggml_tensor* src1,
+    ggml_tensor* dst, const float* src0_dd,
+    const float* src1_dd, float* dst_dd,
+    const queue_ptr& main_stream) {
+
+    GGML_ASSERT(src0->type == GGML_TYPE_F32);
+    GGML_ASSERT(dst->type == GGML_TYPE_F32);
+
+    const int64_t ne00 = src0->ne[0];
+    const int64_t nrows = ggml_nrows(src0);
+
+    float eps;
+    memcpy(&eps, dst->op_params, sizeof(float));
+
+    norm_f32_sycl(src0_dd, dst_dd, ne00, nrows, eps, main_stream);
+
+    (void)src1;
+    (void)dst;
+    (void)src1_dd;
+}
+
+void ggml_sycl_op_group_norm(ggml_backend_sycl_context& ctx, const ggml_tensor* src0,
+    const ggml_tensor* src1, ggml_tensor* dst,
+    const float* src0_dd, const float* src1_dd,
+    float* dst_dd,
+    const queue_ptr& main_stream) {
+
+    GGML_ASSERT(src0->type == GGML_TYPE_F32);
+    GGML_ASSERT(dst->type == GGML_TYPE_F32);
+
+    int num_groups = dst->op_params[0];
+    int group_size = src0->ne[0] * src0->ne[1] * ((src0->ne[2] + num_groups - 1) / num_groups);
+    group_norm_f32_sycl(src0_dd, dst_dd, num_groups, group_size, src0->ne[0] * src0->ne[1] * src0->ne[2], main_stream);
+
+    (void)src1;
+    (void)dst;
+    (void)src1_dd;
+}
+
+void ggml_sycl_op_rms_norm(ggml_backend_sycl_context& ctx, const ggml_tensor* src0,
+    const ggml_tensor* src1, ggml_tensor* dst,
+    const float* src0_dd, const float* src1_dd,
+    float* dst_dd,
+    const queue_ptr& main_stream) {
+
+    GGML_ASSERT(src0->type == GGML_TYPE_F32);
+    GGML_ASSERT(dst->type == GGML_TYPE_F32);
+
+    const int64_t ne00 = src0->ne[0];
+    const int64_t nrows = ggml_nrows(src0);
+
+    float eps;
+    memcpy(&eps, dst->op_params, sizeof(float));
+
+    rms_norm_f32_sycl(src0_dd, dst_dd, ne00, nrows, eps, main_stream);
+
+    (void)src1;
+    (void)dst;
+    (void)src1_dd;
+}
diff --git a/ggml/src/ggml-sycl/norm.hpp b/ggml/src/ggml-sycl/norm.hpp
new file mode 100644
index 0000000000000..a9ad9156fa33e
--- /dev/null
+++ b/ggml/src/ggml-sycl/norm.hpp
@@ -0,0 +1,35 @@
+//
+// MIT license
+// Copyright (C) 2024 Intel Corporation
+// SPDX-License-Identifier: MIT
+//
+
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+
+#ifndef GGML_SYCL_NORM_HPP
+#define GGML_SYCL_NORM_HPP
+
+#include "common.hpp"
+
+void ggml_sycl_op_norm(ggml_backend_sycl_context& ctx, const ggml_tensor* src0, const ggml_tensor* src1,
+    ggml_tensor* dst, const float* src0_dd,
+    const float* src1_dd, float* dst_dd,
+    const queue_ptr& main_stream);
+
+void ggml_sycl_op_rms_norm(ggml_backend_sycl_context& ctx, const ggml_tensor* src0,
+    const ggml_tensor* src1, ggml_tensor* dst,
+    const float* src0_dd, const float* src1_dd,
+    float* dst_dd,
+    const queue_ptr& main_stream);
+
+void ggml_sycl_op_group_norm(ggml_backend_sycl_context& ctx, const ggml_tensor* src0,
+    const ggml_tensor* src1, ggml_tensor* dst,
+    const float* src0_dd, const float* src1_dd,
+    float* dst_dd,
+    const queue_ptr& main_stream);
+
+#endif // GGML_SYCL_NORM_HPP
diff --git a/ggml/src/ggml-sycl/presets.hpp b/ggml/src/ggml-sycl/presets.hpp
index fe9d41770b76a..c09c75dc7c73c 100644
--- a/ggml/src/ggml-sycl/presets.hpp
+++ b/ggml/src/ggml-sycl/presets.hpp
@@ -16,7 +16,7 @@
 #define GGML_SYCL_MAX_STREAMS       8
 #define GGML_SYCL_MAX_BUFFERS       256
 
-#define WARP_SIZE 32
+#define WARP_SIZE GGML_SYCL_WARP_SIZE
 #define MATRIX_ROW_PADDING 512 // last row of quant. matrices is a multiple of this to avoid out-of-bounds memory accesses
 
 #define SYCL_GELU_BLOCK_SIZE 256

From a9f3b102157ba992cfe058909b7f6e1906d2d647 Mon Sep 17 00:00:00 2001
From: luoyu-intel 
Date: Tue, 2 Jul 2024 04:50:07 +0000
Subject: [PATCH 070/326] [SYCL] Fix win build conflict of math library (#8230)

* fix win build conflict of math library

* fix the condition: !(win32 & SYCL)

* revert warp_size=16
---
 CMakePresets.json       | 1 +
 ggml/src/CMakeLists.txt | 6 ++++--
 2 files changed, 5 insertions(+), 2 deletions(-)

diff --git a/CMakePresets.json b/CMakePresets.json
index d69bc03447ae9..bdad38952d3cb 100644
--- a/CMakePresets.json
+++ b/CMakePresets.json
@@ -19,6 +19,7 @@
         "cacheVariables": {
             "CMAKE_EXPORT_COMPILE_COMMANDS": "ON",
             "CMAKE_CXX_COMPILER": "icx",
+            "CMAKE_C_COMPILER": "cl",
             "GGML_SYCL": "ON",
             "CMAKE_INSTALL_RPATH": "$ORIGIN;$ORIGIN/.."
         }
diff --git a/ggml/src/CMakeLists.txt b/ggml/src/CMakeLists.txt
index a18198f1693e5..08b71d410d82e 100644
--- a/ggml/src/CMakeLists.txt
+++ b/ggml/src/CMakeLists.txt
@@ -490,7 +490,7 @@ if (GGML_SYCL)
         set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fsycl-targets=nvptx64-nvidia-cuda")
         add_compile_definitions(GGML_SYCL_WARP_SIZE=32)
     else()
-        add_compile_definitions(GGML_SYCL_WARP_SIZE=16)
+        add_compile_definitions(GGML_SYCL_WARP_SIZE=32)
     endif()
 
     file(GLOB   GGML_HEADERS_SYCL "ggml-sycl/*.hpp")
@@ -1168,7 +1168,9 @@ target_link_libraries(ggml PRIVATE Threads::Threads ${GGML_EXTRA_LIBS})
 
 find_library(MATH_LIBRARY m)
 if (MATH_LIBRARY)
-    target_link_libraries(ggml PRIVATE ${MATH_LIBRARY})
+    if (NOT WIN32 OR NOT GGML_SYCL)
+        target_link_libraries(ggml PRIVATE ${MATH_LIBRARY})
+    endif()
 endif()
 
 if (BUILD_SHARED_LIBS)

From 0e0590adab9f367b15ae2bf090a6d24f9df47ff1 Mon Sep 17 00:00:00 2001
From: slaren 
Date: Tue, 2 Jul 2024 08:39:38 +0200
Subject: [PATCH 071/326] cuda : update supports_op for matrix multiplication
 (#8245)

---
 ggml/src/ggml-cuda.cu      | 47 ++++++++++++++++++++++++--------------
 tests/test-backend-ops.cpp |  1 +
 2 files changed, 31 insertions(+), 17 deletions(-)

diff --git a/ggml/src/ggml-cuda.cu b/ggml/src/ggml-cuda.cu
index 649ef5a081910..1c9ccc8a15e54 100644
--- a/ggml/src/ggml-cuda.cu
+++ b/ggml/src/ggml-cuda.cu
@@ -2711,27 +2711,40 @@ GGML_CALL static bool ggml_backend_cuda_supports_op(ggml_backend_t backend, cons
         case GGML_OP_MUL_MAT:
         case GGML_OP_MUL_MAT_ID:
             {
-                struct ggml_tensor * a;
-                struct ggml_tensor * b;
+                struct ggml_tensor * a = op->src[0];
                 if (op->op == GGML_OP_MUL_MAT) {
-                    a = op->src[0];
-                    b = op->src[1];
-                } else {
-                    a = op->src[2];
-                    b = op->src[1];
-                }
-                if (a->ne[3] != b->ne[3]) {
-                    return false;
-                }
-                ggml_type a_type = a->type;
-                if (a_type == GGML_TYPE_IQ2_XXS || a_type == GGML_TYPE_IQ2_XS || a_type == GGML_TYPE_IQ3_XXS ||
-                    a_type == GGML_TYPE_IQ1_S   || a_type == GGML_TYPE_IQ4_NL || a_type == GGML_TYPE_IQ3_S   ||
-                    a_type == GGML_TYPE_IQ1_M   || a_type == GGML_TYPE_IQ2_S  || a_type == GGML_TYPE_IQ4_XS) {
-                    if (b->ne[1] == 1 && ggml_nrows(b) > 1) {
+                    struct ggml_tensor * b = op->src[1];
+                    if (a->ne[3] != b->ne[3]) {
                         return false;
                     }
                 }
-                return true;
+                switch (a->type) {
+                    case GGML_TYPE_F32:
+                    case GGML_TYPE_F16:
+                    case GGML_TYPE_Q4_0:
+                    case GGML_TYPE_Q4_1:
+                    case GGML_TYPE_Q5_0:
+                    case GGML_TYPE_Q5_1:
+                    case GGML_TYPE_Q8_0:
+                    case GGML_TYPE_Q2_K:
+                    case GGML_TYPE_Q3_K:
+                    case GGML_TYPE_Q4_K:
+                    case GGML_TYPE_Q5_K:
+                    case GGML_TYPE_Q6_K:
+                    case GGML_TYPE_Q8_K:
+                    case GGML_TYPE_IQ1_M:
+                    case GGML_TYPE_IQ1_S:
+                    case GGML_TYPE_IQ2_S:
+                    case GGML_TYPE_IQ2_XS:
+                    case GGML_TYPE_IQ2_XXS:
+                    case GGML_TYPE_IQ3_S:
+                    case GGML_TYPE_IQ3_XXS:
+                    case GGML_TYPE_IQ4_NL:
+                    case GGML_TYPE_IQ4_XS:
+                        return true;
+                    default:
+                        return false;
+                }
             } break;
         case GGML_OP_GET_ROWS:
             {
diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp
index f74c0db475e2e..2bb71ac03817f 100644
--- a/tests/test-backend-ops.cpp
+++ b/tests/test-backend-ops.cpp
@@ -2052,6 +2052,7 @@ static bool test_backend(ggml_backend_t backend, test_mode mode, const char * op
         GGML_TYPE_IQ2_XS, GGML_TYPE_IQ2_S,
         GGML_TYPE_IQ3_XXS, GGML_TYPE_IQ1_S, GGML_TYPE_IQ1_M,
         GGML_TYPE_IQ4_NL, GGML_TYPE_IQ3_S, GGML_TYPE_IQ4_XS,
+        GGML_TYPE_BF16,
     };
 
     // unary ops

From 023b8807e10bc3ade24a255f01c1ad2a01bb4228 Mon Sep 17 00:00:00 2001
From: Daniel Bevenius 
Date: Tue, 2 Jul 2024 08:40:49 +0200
Subject: [PATCH 072/326] convert-hf : print output file name when completed
 (#8181)

* convert-hf : print output file name when completed

This commit adds the output file name to the log message when the
conversion is completed.

The motivation for this change is that when `--outfile` option is not
specified it migth not be obvious where the output file is written.

With this change the output of running the script will be something like
the following:
```console
INFO:hf-to-gguf:Model successfully exported to models/gemma-2-9b-it.gguf.
```

Signed-off-by: Daniel Bevenius 

* squash! convert-hf : print output file name when completed

Updates the output of to support printing the directory if the output is
split into multiple files. Also the output file name is now retrieved
from the model_instance object.

Signed-off-by: Daniel Bevenius 

* squash! convert-hf : print output file name when completed

Use parent attribute of Path object and string interpolation.

Signed-off-by: Daniel Bevenius 

* squash! convert-hf : print output file name when completed

Use os.sep instead of hardcoding the path separator.

Signed-off-by: Daniel Bevenius 

---------

Signed-off-by: Daniel Bevenius 
---
 convert-hf-to-gguf.py | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py
index 6833e943765f7..05fd70171de38 100755
--- a/convert-hf-to-gguf.py
+++ b/convert-hf-to-gguf.py
@@ -3120,7 +3120,8 @@ def main() -> None:
         "auto": gguf.LlamaFileType.GUESSED,
     }
 
-    if args.use_temp_file and (args.split_max_tensors > 0 or args.split_max_size != "0"):
+    is_split = args.split_max_tensors > 0 or args.split_max_size != "0"
+    if args.use_temp_file and is_split:
         logger.error("Error: Cannot use temp file when splitting")
         sys.exit(1)
 
@@ -3157,11 +3158,12 @@ def main() -> None:
         if args.vocab_only:
             logger.info("Exporting model vocab...")
             model_instance.write_vocab()
-            logger.info("Model vocab successfully exported.")
+            logger.info(f"Model vocab successfully exported to {model_instance.fname_out}")
         else:
             logger.info("Exporting model...")
             model_instance.write()
-            logger.info("Model successfully exported.")
+            out_path = f"{model_instance.fname_out.parent}{os.sep}" if is_split else model_instance.fname_out
+            logger.info(f"Model successfully exported to {out_path}")
 
 
 if __name__ == '__main__':

From 968967376dc2c018d29f897c4883d335bbf384fb Mon Sep 17 00:00:00 2001
From: Faisal Zaghloul 
Date: Tue, 2 Jul 2024 10:36:00 -0400
Subject: [PATCH 073/326] Add `JAIS` model(s) (#8118)

* Add `JAIS` model(s)

* cleanup

* address review comments

* remove hack

* un-hardcode max-alibi-bias

* minor tweaks

---------

Co-authored-by: fmz 
---
 convert-hf-to-gguf-update.py   |   1 +
 convert-hf-to-gguf.py          |  93 ++++++++++++++++++
 gguf-py/gguf/constants.py      |  14 +++
 gguf-py/gguf/tensor_mapping.py |  19 ++--
 include/llama.h                |   1 +
 src/llama.cpp                  | 169 +++++++++++++++++++++++++++++++++
 6 files changed, 288 insertions(+), 9 deletions(-)

diff --git a/convert-hf-to-gguf-update.py b/convert-hf-to-gguf-update.py
index 2758214fa8730..944e9d15abdcc 100755
--- a/convert-hf-to-gguf-update.py
+++ b/convert-hf-to-gguf-update.py
@@ -86,6 +86,7 @@ class TOKENIZER_TYPE(IntEnum):
     {"name": "poro-chat",      "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/LumiOpen/Poro-34B-chat", },
     {"name": "jina-v2-code",   "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-code", },
     {"name": "viking",         "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/LumiOpen/Viking-7B", }, # Also used for Viking 13B and 33B
+    {"name": "jais",           "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/core42/jais-13b", },
 ]
 
 
diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py
index 05fd70171de38..6add27cbb11a6 100755
--- a/convert-hf-to-gguf.py
+++ b/convert-hf-to-gguf.py
@@ -490,6 +490,9 @@ def get_vocab_base_pre(self, tokenizer) -> str:
         if chkhsh == "7fc505bd3104ca1083b150b17d088b59534ede9bde81f0dd2090967d7fe52cee":
             # ref: https://huggingface.co/LumiOpen/Viking-7B
             res = "viking"
+        if chkhsh == "b53802fb28e26d645c3a310b34bfe07da813026ec7c7716883404d5e0f8b1901":
+            # ref: https://huggingface.co/core42/jais-13b
+            res = "jais"
 
         if res is None:
             logger.warning("\n")
@@ -2965,6 +2968,96 @@ def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iter
         return [(self.map_tensor_name(name), data_torch)]
 
 
+@Model.register("JAISLMHeadModel")
+class JaisModel(Model):
+    model_arch = gguf.MODEL_ARCH.JAIS
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+
+        # SwigLU activation
+        assert self.hparams["activation_function"] == "swiglu"
+        # ALiBi position embedding
+        assert self.hparams["position_embedding_type"] == "alibi"
+
+        # Embeddings scale
+        self.embeddings_scale = 1.0
+        # note: For some JAIS flavors, output is tied to (same as) wte in original model
+        self.output_is_wte = False
+        if 'mup_embeddings_scale' in self.hparams:
+            self.output_is_wte = True   # Hack (?)
+            self.embeddings_scale = self.hparams['mup_embeddings_scale']
+        elif 'embeddings_scale' in self.hparams:
+            self.embeddings_scale = self.hparams['embeddings_scale']
+        else:
+            assert False
+
+        self.width_scale = 1.0
+        if 'mup_output_alpha' in self.hparams:
+            assert 'mup_width_scale' in self.hparams
+            self.width_scale = self.hparams['mup_output_alpha'] * self.hparams['mup_width_scale']
+        elif 'width_scale' in self.hparams:
+            self.width_scale = self.hparams['width_scale']
+        else:
+            assert False
+
+        self.max_alibi_bias = 8.0
+
+    def set_vocab(self):
+        self._set_vocab_gpt2()
+
+    def set_gguf_parameters(self):
+        self.gguf_writer.add_name(self.dir_model.name)
+        self.gguf_writer.add_block_count(self.hparams["n_layer"])
+        self.gguf_writer.add_context_length(self.hparams["n_positions"])
+        self.gguf_writer.add_embedding_length(self.hparams["n_embd"])
+        self.gguf_writer.add_feed_forward_length(self.hparams["n_inner"])
+        self.gguf_writer.add_head_count(self.hparams["n_head"])
+        self.gguf_writer.add_layer_norm_eps(self.hparams["layer_norm_epsilon"])
+        self.gguf_writer.add_file_type(self.ftype)
+
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        del bid  # unused
+
+        tensors: list[tuple[str, Tensor]] = []
+
+        # we don't need these
+        if name.endswith((".attn.bias")):
+            return tensors
+
+        if name.endswith(("relative_pe.slopes")):
+            # Calculate max ALiBi bias (this is the inverse of the ALiBi calculation)
+            # Some other models has max_alibi_bias spelled out explicitly in the hyperparams,
+            # but Jais's PyTorch model simply precalculates the slope values and places them
+            # in relative_pes.slopes
+            n_head_closest_log2 = 2 ** math.floor(math.log2(self.hparams["n_head"]))
+            first_val = float(data_torch._data[0])
+            self.max_alibi_bias = -round(math.log2(first_val) * n_head_closest_log2)
+
+            return tensors
+
+        if name.endswith((".c_attn.weight", ".c_proj.weight", ".c_fc.weight", ".c_fc2.weight")):
+            data_torch = data_torch.transpose(1, 0)
+
+        new_name = self.map_tensor_name(name)
+
+        if new_name == self.format_tensor_name(gguf.MODEL_TENSOR.TOKEN_EMBD):
+            tensors.append((new_name, data_torch * self.embeddings_scale))
+            if self.output_is_wte:
+                tensors.append((self.format_tensor_name(gguf.MODEL_TENSOR.OUTPUT), data_torch * self.width_scale))
+        elif new_name == self.format_tensor_name(gguf.MODEL_TENSOR.OUTPUT):
+            assert not self.output_is_wte
+            tensors.append((new_name, data_torch * self.width_scale))
+        else:
+            tensors.append((new_name, data_torch))
+
+        return tensors
+
+    def write_tensors(self):
+        super().write_tensors()
+        self.gguf_writer.add_max_alibi_bias(self.max_alibi_bias)
+
+
 ###### CONVERSION LOGIC ######
 
 
diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py
index e87c58266158a..419f10cee74a7 100644
--- a/gguf-py/gguf/constants.py
+++ b/gguf-py/gguf/constants.py
@@ -164,6 +164,7 @@ class MODEL_ARCH(IntEnum):
     DEEPSEEK2    = auto()
     BITNET       = auto()
     T5           = auto()
+    JAIS         = auto()
 
 
 class MODEL_TENSOR(IntEnum):
@@ -288,6 +289,7 @@ class MODEL_TENSOR(IntEnum):
     MODEL_ARCH.DEEPSEEK2:      "deepseek2",
     MODEL_ARCH.BITNET:         "bitnet",
     MODEL_ARCH.T5:             "t5",
+    MODEL_ARCH.JAIS:           "jais",
 }
 
 TENSOR_NAMES: dict[MODEL_TENSOR, str] = {
@@ -954,6 +956,18 @@ class MODEL_TENSOR(IntEnum):
         MODEL_TENSOR.ENC_FFN_UP,
         MODEL_TENSOR.ENC_OUTPUT_NORM,
     ],
+    MODEL_ARCH.JAIS: [
+        MODEL_TENSOR.TOKEN_EMBD,
+        MODEL_TENSOR.OUTPUT_NORM,
+        MODEL_TENSOR.OUTPUT,
+        MODEL_TENSOR.ATTN_NORM,
+        MODEL_TENSOR.ATTN_QKV,
+        MODEL_TENSOR.ATTN_OUT,
+        MODEL_TENSOR.FFN_NORM,
+        MODEL_TENSOR.FFN_DOWN,
+        MODEL_TENSOR.FFN_GATE,
+        MODEL_TENSOR.FFN_UP,
+    ],
     # TODO
 }
 
diff --git a/gguf-py/gguf/tensor_mapping.py b/gguf-py/gguf/tensor_mapping.py
index 0bed439397bcd..20e28423b9a99 100644
--- a/gguf-py/gguf/tensor_mapping.py
+++ b/gguf-py/gguf/tensor_mapping.py
@@ -10,7 +10,7 @@ class TensorNameMap:
         # Token embeddings
         MODEL_TENSOR.TOKEN_EMBD: (
             "gpt_neox.embed_in",                         # gptneox
-            "transformer.wte",                           # gpt2 gpt-j mpt refact qwen dbrx
+            "transformer.wte",                           # gpt2 gpt-j mpt refact qwen dbrx jais
             "transformer.word_embeddings",               # falcon
             "word_embeddings",                           # bloom
             "model.embed_tokens",                        # llama-hf
@@ -49,7 +49,7 @@ class TensorNameMap:
         # Output
         MODEL_TENSOR.OUTPUT: (
             "embed_out",                 # gptneox
-            "lm_head",                   # gpt2 mpt falcon llama-hf baichuan qwen mamba dbrx
+            "lm_head",                   # gpt2 mpt falcon llama-hf baichuan qwen mamba dbrx jais
             "output",                    # llama-pth bloom internlm2
             "word_embeddings_for_head",  # persimmon
             "lm_head.linear",            # phi2
@@ -58,7 +58,7 @@ class TensorNameMap:
         # Output norm
         MODEL_TENSOR.OUTPUT_NORM: (
             "gpt_neox.final_layer_norm",               # gptneox
-            "transformer.ln_f",                        # gpt2 gpt-j falcon
+            "transformer.ln_f",                        # gpt2 gpt-j falcon jais
             "model.norm",                              # llama-hf baichuan internlm2
             "norm",                                    # llama-pth
             "transformer.norm_f",                      # mpt dbrx
@@ -81,7 +81,7 @@ class TensorNameMap:
         # Attention norm
         MODEL_TENSOR.ATTN_NORM: (
             "gpt_neox.layers.{bid}.input_layernorm",                # gptneox
-            "transformer.h.{bid}.ln_1",                             # gpt2 gpt-j refact qwen
+            "transformer.h.{bid}.ln_1",                             # gpt2 gpt-j refact qwen jais
             "transformer.blocks.{bid}.norm_1",                      # mpt
             "transformer.h.{bid}.input_layernorm",                  # falcon7b
             "h.{bid}.input_layernorm",                              # bloom
@@ -109,7 +109,7 @@ class TensorNameMap:
         # Attention query-key-value
         MODEL_TENSOR.ATTN_QKV: (
             "gpt_neox.layers.{bid}.attention.query_key_value",                     # gptneox
-            "transformer.h.{bid}.attn.c_attn",                                     # gpt2 qwen
+            "transformer.h.{bid}.attn.c_attn",                                     # gpt2 qwen jais
             "transformer.blocks.{bid}.attn.Wqkv",                                  # mpt
             "transformer.blocks.{bid}.norm_attn_norm.attn.Wqkv",                   # dbrx
             "transformer.h.{bid}.self_attention.query_key_value",                  # falcon
@@ -160,7 +160,7 @@ class TensorNameMap:
         # Attention output
         MODEL_TENSOR.ATTN_OUT: (
             "gpt_neox.layers.{bid}.attention.dense",                        # gptneox
-            "transformer.h.{bid}.attn.c_proj",                              # gpt2 refact qwen
+            "transformer.h.{bid}.attn.c_proj",                              # gpt2 refact qwen jais
             "transformer.blocks.{bid}.attn.out_proj",                       # mpt
             "transformer.h.{bid}.self_attention.dense",                     # falcon
             "h.{bid}.self_attention.dense",                                 # bloom
@@ -202,7 +202,7 @@ class TensorNameMap:
         # Feed-forward norm
         MODEL_TENSOR.FFN_NORM: (
             "gpt_neox.layers.{bid}.post_attention_layernorm",                # gptneox
-            "transformer.h.{bid}.ln_2",                                      # gpt2 refact qwen
+            "transformer.h.{bid}.ln_2",                                      # gpt2 refact qwen jais
             "h.{bid}.post_attention_layernorm",                              # bloom
             "transformer.blocks.{bid}.norm_2",                               # mpt
             "model.layers.{bid}.post_attention_layernorm",                   # llama-hf
@@ -239,7 +239,7 @@ class TensorNameMap:
         # Feed-forward up
         MODEL_TENSOR.FFN_UP: (
             "gpt_neox.layers.{bid}.mlp.dense_h_to_4h",                # gptneox
-            "transformer.h.{bid}.mlp.c_fc",                           # gpt2
+            "transformer.h.{bid}.mlp.c_fc",                           # gpt2 jais
             "transformer.blocks.{bid}.ffn.up_proj",                   # mpt
             "transformer.h.{bid}.mlp.dense_h_to_4h",                  # falcon
             "h.{bid}.mlp.dense_h_to_4h",                              # bloom
@@ -285,6 +285,7 @@ class TensorNameMap:
             "model.layers.{bid}.mlp.gate_proj",           # llama-hf refact
             "layers.{bid}.feed_forward.w1",               # llama-pth
             "transformer.h.{bid}.mlp.w2",                 # qwen
+            "transformer.h.{bid}.mlp.c_fc2",              # jais
             "model.layers.layers.{bid}.mlp.gate_proj",    # plamo
             "model.layers.{bid}.feed_forward.w1",         # internlm2
             "encoder.layers.{bid}.mlp.fc12",              # nomic-bert
@@ -308,7 +309,7 @@ class TensorNameMap:
         # Feed-forward down
         MODEL_TENSOR.FFN_DOWN: (
             "gpt_neox.layers.{bid}.mlp.dense_4h_to_h",                # gptneox
-            "transformer.h.{bid}.mlp.c_proj",                         # gpt2 refact qwen
+            "transformer.h.{bid}.mlp.c_proj",                         # gpt2 refact qwen jais
             "transformer.blocks.{bid}.ffn.down_proj",                 # mpt
             "transformer.h.{bid}.mlp.dense_4h_to_h",                  # falcon
             "h.{bid}.mlp.dense_4h_to_h",                              # bloom
diff --git a/include/llama.h b/include/llama.h
index cafeafb85dbc7..c5b6182920428 100644
--- a/include/llama.h
+++ b/include/llama.h
@@ -89,6 +89,7 @@ extern "C" {
         LLAMA_VOCAB_PRE_TYPE_SMAUG          = 14,
         LLAMA_VOCAB_PRE_TYPE_PORO           = 15,
         LLAMA_VOCAB_PRE_TYPE_VIKING         = 16,
+        LLAMA_VOCAB_PRE_TYPE_JAIS           = 17,
     };
 
     // note: these values should be synchronized with ggml_rope
diff --git a/src/llama.cpp b/src/llama.cpp
index eea532f6ac2ff..73f52435a503e 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -228,6 +228,7 @@ enum llm_arch {
     LLM_ARCH_DEEPSEEK2,
     LLM_ARCH_BITNET,
     LLM_ARCH_T5,
+    LLM_ARCH_JAIS,
     LLM_ARCH_UNKNOWN,
 };
 
@@ -269,6 +270,7 @@ static const std::map LLM_ARCH_NAMES = {
     { LLM_ARCH_DEEPSEEK2,       "deepseek2"    },
     { LLM_ARCH_BITNET,          "bitnet"       },
     { LLM_ARCH_T5,              "t5"           },
+    { LLM_ARCH_JAIS,            "jais"         },
     { LLM_ARCH_UNKNOWN,         "(unknown)"    },
 };
 
@@ -1236,6 +1238,21 @@ static const std::map> LLM_TENSOR_NA
             { LLM_TENSOR_ENC_FFN_UP,           "enc.blk.%d.ffn_up" },
         },
     },
+    {
+        LLM_ARCH_JAIS,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,      "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM,     "output_norm" },
+            { LLM_TENSOR_OUTPUT,          "output" },
+            { LLM_TENSOR_ATTN_NORM,       "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_QKV,        "blk.%d.attn_qkv" },
+            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output" },
+            { LLM_TENSOR_FFN_NORM,        "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
+            { LLM_TENSOR_FFN_GATE,        "blk.%d.ffn_gate" },
+            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
+        },
+    },
     {
         LLM_ARCH_UNKNOWN,
         {
@@ -2035,6 +2052,7 @@ enum e_model {
     MODEL_410M,
     MODEL_0_5B,
     MODEL_1B,
+    MODEL_1_3B,
     MODEL_1_4B,
     MODEL_2B,
     MODEL_2_8B,
@@ -4276,6 +4294,7 @@ static const char * llama_model_type_name(e_model type) {
         case MODEL_410M:          return "410M";
         case MODEL_0_5B:          return "0.5B";
         case MODEL_1B:            return "1B";
+        case MODEL_1_3B:          return "1.3B";
         case MODEL_1_4B:          return "1.4B";
         case MODEL_2B:            return "2B";
         case MODEL_2_8B:          return "2.8B";
@@ -4898,6 +4917,18 @@ static void llm_load_hparams(
                     default: model.type = e_model::MODEL_UNKNOWN;
                 }
             } break;
+        case LLM_ARCH_JAIS:
+            {
+                ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps);
+                ml.get_key(LLM_KV_ATTENTION_MAX_ALIBI_BIAS, hparams.f_max_alibi_bias);
+
+                switch (hparams.n_layer) {
+                    case 24: model.type = e_model::MODEL_1_3B; break;
+                    case 40: model.type = e_model::MODEL_13B; break;
+                    /* TODO: add variants */
+                    default: model.type = e_model::MODEL_UNKNOWN;
+                }
+            } break;
         default: (void)0;
     }
 
@@ -5129,6 +5160,9 @@ static void llm_load_vocab(
             } else if (
                 tokenizer_pre == "viking") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_VIKING;
+            } else if (
+                tokenizer_pre == "jais") {
+                vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_JAIS;
             } else {
                 throw std::runtime_error(format("unknown pre-tokenizer type: '%s'", tokenizer_pre.c_str()));
             }
@@ -6962,6 +6996,44 @@ static bool llm_load_tensors(
                         layer.ffn_up_scale = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP, "scale", i), {1});
                     }
                 } break;
+            case LLM_ARCH_JAIS:
+                {
+                    model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
+
+                    // Output
+                    {
+                        model.output_norm   = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
+                        model.output_norm_b = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "bias"),   {n_embd});
+                        model.output        = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab});
+                    }
+                    for (int i = 0; i < n_layer; ++i) {
+                        ggml_context * ctx_layer = ctx_for_layer(i);
+                        ggml_context * ctx_split = ctx_for_layer_split(i);
+
+                        auto & layer = model.layers[i];
+
+                        layer.attn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM,   "weight", i), {n_embd});
+                        layer.attn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM,   "bias", i),   {n_embd});
+
+                        layer.wqkv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_embd + 2*n_embd_gqa});
+                        layer.bqkv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_QKV, "bias", i),   {n_embd + 2*n_embd_gqa});
+
+                        layer.wo   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
+                        layer.bo   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT, "bias", i),   {n_embd});
+
+                        layer.ffn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
+                        layer.ffn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "bias", i),   {n_embd});
+
+                        layer.ffn_down   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd});
+                        layer.ffn_down_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_DOWN, "bias", i),   {n_embd});
+
+                        layer.ffn_gate     = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE,   "weight", i), {n_embd, n_ff});
+                        layer.ffn_gate_b   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_GATE,   "bias", i),   {n_ff});
+
+                        layer.ffn_up     = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd, n_ff});
+                        layer.ffn_up_b   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP,   "bias", i),   {n_ff});
+                    }
+                } break;
             default:
                 throw std::runtime_error("unknown architecture");
         }
@@ -12354,6 +12426,97 @@ struct llm_build_context {
         return gf;
     }
 
+    struct ggml_cgraph * build_jais() {
+        struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
+
+        const int64_t n_embd_head = hparams.n_embd_head_v;
+        const int64_t n_embd_gqa  = hparams.n_embd_v_gqa();
+        GGML_ASSERT(n_embd_head == hparams.n_embd_head_k);
+
+        struct ggml_tensor * cur;
+        struct ggml_tensor * inpL;
+
+        inpL = llm_build_inp_embd(ctx0, lctx, hparams, batch, model.tok_embd, cb);
+
+        // KQ_mask (mask for 1 head, it will be broadcasted to all heads)
+        struct ggml_tensor * KQ_mask = build_inp_KQ_mask();
+
+        for (int il = 0; il < n_layer; ++il) {
+            cur = llm_build_norm(ctx0, inpL, hparams,
+                    model.layers[il].attn_norm,
+                    model.layers[il].attn_norm_b,
+                    LLM_NORM, cb, il);
+            cb(cur, "attn_norm", il);
+
+            // self-attention
+            {
+                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
+                cb(cur, "wqkv", il);
+
+                cur = ggml_add(ctx0, cur, model.layers[il].bqkv);
+                cb(cur, "bqkv", il);
+
+                struct ggml_tensor * Qcur = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, n_embd,     n_tokens, cur->nb[1], 0*cur->nb[0]*(n_embd)));
+                struct ggml_tensor * Kcur = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, n_embd_gqa, n_tokens, cur->nb[1], 1*cur->nb[0]*(n_embd)));
+                struct ggml_tensor * Vcur = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, n_embd_gqa, n_tokens, cur->nb[1], 1*cur->nb[0]*(n_embd + n_embd_gqa)));
+
+                cb(Qcur, "Qcur", il);
+                cb(Kcur, "Kcur", il);
+                cb(Vcur, "Vcur", il);
+
+                Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens);
+
+                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                        model.layers[il].wo, model.layers[il].bo,
+                        Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/float(n_embd_head), cb, il);
+            }
+
+            if (il == n_layer - 1) {
+                // skip computing output for unused tokens
+                struct ggml_tensor * inp_out_ids = build_inp_out_ids();
+                cur  = ggml_get_rows(ctx0,  cur, inp_out_ids);
+                inpL = ggml_get_rows(ctx0, inpL, inp_out_ids);
+            }
+
+            // add the input
+            struct ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpL);
+            cb(ffn_inp, "ffn_inp", il);
+
+            // FF
+            {
+                cur = llm_build_norm(ctx0, ffn_inp, hparams,
+                        model.layers[il].ffn_norm,
+                        model.layers[il].ffn_norm_b,
+                        LLM_NORM, cb, il);
+                cb(cur, "ffn_norm", il);
+
+                cur = llm_build_ffn(ctx0, cur,
+                        model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,
+                        model.layers[il].ffn_gate, model.layers[il].ffn_gate_b, NULL,
+                        model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,
+                        NULL,
+                        LLM_FFN_SILU, LLM_FFN_PAR, cb, il);
+                cb(cur, "ffn_out", il);
+            }
+
+            inpL = ggml_add(ctx0, cur, ffn_inp);
+            cb(inpL, "l_out", il);
+        }
+
+        cur = llm_build_norm(ctx0, inpL, hparams,
+                model.output_norm,
+                model.output_norm_b,
+                LLM_NORM, cb, -1);
+        cb(cur, "result_norm", -1);
+
+        cur = ggml_mul_mat(ctx0, model.output, cur);
+
+        cb(cur, "result_output", -1);
+
+        ggml_build_forward_expand(gf, cur);
+
+        return gf;
+    }
 };
 
 static struct ggml_cgraph * llama_build_graph_defrag(llama_context & lctx, const std::vector & ids) {
@@ -12585,6 +12748,10 @@ static struct ggml_cgraph * llama_build_graph(
             {
                 result = llm.build_bitnet();
             } break;
+        case LLM_ARCH_JAIS:
+            {
+                result = llm.build_jais();
+            } break;
         default:
             GGML_ASSERT(false);
     }
@@ -13947,6 +14114,7 @@ struct llm_tokenizer_bpe {
                 break;
             case LLAMA_VOCAB_PRE_TYPE_GPT2:
             case LLAMA_VOCAB_PRE_TYPE_OLMO:
+            case LLAMA_VOCAB_PRE_TYPE_JAIS:
                 regex_exprs = {
                     "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)",
                 };
@@ -17826,6 +17994,7 @@ enum llama_rope_type llama_rope_type(const struct llama_model * model) {
         case LLM_ARCH_MAMBA:
         case LLM_ARCH_JINA_BERT_V2:
         case LLM_ARCH_T5:
+        case LLM_ARCH_JAIS:
             return LLAMA_ROPE_TYPE_NONE;
 
         // use what we call a normal RoPE, operating on pairs of consecutive head values

From 07a3fc0608a68c0c93a5fbfa9c58f4c9ec64cb81 Mon Sep 17 00:00:00 2001
From: Clint Herron 
Date: Tue, 2 Jul 2024 12:18:10 -0400
Subject: [PATCH 074/326] Removes multiple newlines at the end of files that is
 breaking the editorconfig step of CI. (#8258)

---
 .github/ISSUE_TEMPLATE/config.yml              | 2 --
 common/common.h                                | 1 -
 examples/embedding/README.md                   | 1 -
 examples/infill/infill.cpp                     | 1 -
 examples/lookup/README.md                      | 1 -
 examples/main-cmake-pkg/.gitignore             | 1 -
 examples/main-cmake-pkg/CMakeLists.txt         | 1 -
 examples/server-embd.py                        | 1 -
 examples/server/tests/features/passkey.feature | 1 -
 examples/server/themes/buttons-top/index.html  | 1 -
 examples/server/themes/wild/index.html         | 1 -
 examples/sycl/run-llama2.sh                    | 1 -
 examples/sycl/win-build-sycl.bat               | 1 -
 examples/sycl/win-run-llama2.bat               | 2 --
 ggml/include/ggml-metal.h                      | 1 -
 ggml/src/ggml-cuda/cpy.cu                      | 1 -
 ggml/src/ggml-metal.metal                      | 1 -
 ggml/src/ggml-quants.h                         | 1 -
 ggml/src/ggml-vulkan-shaders.hpp               | 1 -
 scripts/pod-llama.sh                           | 1 -
 src/unicode-data.cpp                           | 1 -
 tests/test-rope.cpp                            | 1 -
 22 files changed, 24 deletions(-)

diff --git a/.github/ISSUE_TEMPLATE/config.yml b/.github/ISSUE_TEMPLATE/config.yml
index c88134dbb644a..eb8c4b472df4c 100644
--- a/.github/ISSUE_TEMPLATE/config.yml
+++ b/.github/ISSUE_TEMPLATE/config.yml
@@ -9,5 +9,3 @@ contact_links:
   - name: Want to contribute?
     url: https://github.com/ggerganov/llama.cpp/wiki/contribute
     about: Head to the contribution guide page of the wiki for areas you can help with
-
-
diff --git a/common/common.h b/common/common.h
index 627b7ed854757..65c0ef81adf7c 100644
--- a/common/common.h
+++ b/common/common.h
@@ -459,4 +459,3 @@ void yaml_dump_string_multiline(FILE * stream, const char * prop_name, const cha
 void yaml_dump_non_result_info(
     FILE * stream, const gpt_params & params, const llama_context * lctx,
     const std::string & timestamp, const std::vector & prompt_tokens, const char * model_desc);
-
diff --git a/examples/embedding/README.md b/examples/embedding/README.md
index 86df189587846..e3705b4547677 100644
--- a/examples/embedding/README.md
+++ b/examples/embedding/README.md
@@ -58,4 +58,3 @@ The above command will output space-separated float values.
 ```powershell
 embedding.exe -p 'Castle<#sep#>Stronghold<#sep#>Dog<#sep#>Cat' --embd-separator '<#sep#>' --embd-normalize 2  --embd-output-format '' -m './path/to/model.gguf' --n-gpu-layers 99 --log-disable 2>/dev/null
 ```
-
diff --git a/examples/infill/infill.cpp b/examples/infill/infill.cpp
index ca71dd687f30e..0e682154d5f6b 100644
--- a/examples/infill/infill.cpp
+++ b/examples/infill/infill.cpp
@@ -659,4 +659,3 @@ int main(int argc, char ** argv) {
 
     return 0;
 }
-
diff --git a/examples/lookup/README.md b/examples/lookup/README.md
index 5bfb0de936041..71c345c037a2f 100644
--- a/examples/lookup/README.md
+++ b/examples/lookup/README.md
@@ -10,4 +10,3 @@ More info:
 
 https://github.com/ggerganov/llama.cpp/pull/4484
 https://github.com/ggerganov/llama.cpp/issues/4226
-
diff --git a/examples/main-cmake-pkg/.gitignore b/examples/main-cmake-pkg/.gitignore
index e32c11c7f4653..67c01d64cb7ab 100644
--- a/examples/main-cmake-pkg/.gitignore
+++ b/examples/main-cmake-pkg/.gitignore
@@ -48,4 +48,3 @@
 build*/
 out/
 tmp/
-
diff --git a/examples/main-cmake-pkg/CMakeLists.txt b/examples/main-cmake-pkg/CMakeLists.txt
index a97ded3653f0c..3b38db292320f 100644
--- a/examples/main-cmake-pkg/CMakeLists.txt
+++ b/examples/main-cmake-pkg/CMakeLists.txt
@@ -30,4 +30,3 @@ target_include_directories(${TARGET} PRIVATE ${_common_path})
 install(TARGETS ${TARGET} RUNTIME)
 target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
 target_compile_features(${TARGET} PRIVATE cxx_std_11)
-
diff --git a/examples/server-embd.py b/examples/server-embd.py
index 118e042716c02..a9a36a44ccac5 100644
--- a/examples/server-embd.py
+++ b/examples/server-embd.py
@@ -31,4 +31,3 @@ async def main():
         embedding2 = np.array(result[j])
         similarity = np.dot(embedding1, embedding2) / (np.linalg.norm(embedding1) * np.linalg.norm(embedding2))
         print(f"Similarity between {i} and {j}: {similarity:.2f}")
-
diff --git a/examples/server/tests/features/passkey.feature b/examples/server/tests/features/passkey.feature
index 1bde7aab8bab0..6a5a84e6a1941 100644
--- a/examples/server/tests/features/passkey.feature
+++ b/examples/server/tests/features/passkey.feature
@@ -52,4 +52,3 @@ Feature: Passkey / Self-extend with context shift
       #| TheBloke/Llama-2-7B-GGUF        | llama-2-7b.Q2_K.gguf        | 4096        | 3   | 16384 | 512     | 4    | 512    | 500    | 300   | 1234    | 5           | 1234           |
       #| TheBloke/Mixtral-8x7B-v0.1-GGUF | mixtral-8x7b-v0.1.Q2_K.gguf | 32768       | 2   | 16384 | 512     | 4    | 512    | 500    | 100   | 0987    | 5           | 0
       # 987           |
-
diff --git a/examples/server/themes/buttons-top/index.html b/examples/server/themes/buttons-top/index.html
index 6af30d307a4b5..8334bcde5049c 100644
--- a/examples/server/themes/buttons-top/index.html
+++ b/examples/server/themes/buttons-top/index.html
@@ -1054,4 +1054,3 @@ 
llama.cpp

 
 
 
-
diff --git a/examples/server/themes/wild/index.html b/examples/server/themes/wild/index.html
index 772e716cdb2e0..8361c577494d7 100644
--- a/examples/server/themes/wild/index.html
+++ b/examples/server/themes/wild/index.html
@@ -1058,4 +1058,3 @@
 
 
 
-
diff --git a/examples/sycl/run-llama2.sh b/examples/sycl/run-llama2.sh
index da0e4aaba688c..111366fb036a5 100755
--- a/examples/sycl/run-llama2.sh
+++ b/examples/sycl/run-llama2.sh
@@ -34,4 +34,3 @@ fi
 
 #use multiple GPUs with same max compute units
 #ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -m models/llama-2-7b.Q4_0.gguf -p "${INPUT2}" -n 400 -e -ngl 33 -s 0
-
diff --git a/examples/sycl/win-build-sycl.bat b/examples/sycl/win-build-sycl.bat
index cdae5a52855a2..17dd1ff5c169e 100644
--- a/examples/sycl/win-build-sycl.bat
+++ b/examples/sycl/win-build-sycl.bat
@@ -31,4 +31,3 @@ exit /B 0
 :ERROR
 echo comomand error: %errorlevel%
 exit /B %errorlevel%
-
diff --git a/examples/sycl/win-run-llama2.bat b/examples/sycl/win-run-llama2.bat
index 1d4d7d2cdcb6f..f0385cdf0783e 100644
--- a/examples/sycl/win-run-llama2.bat
+++ b/examples/sycl/win-run-llama2.bat
@@ -7,5 +7,3 @@ set INPUT2="Building a website can be done in 10 simple steps:\nStep 1:"
 
 
 .\build\bin\main.exe -m models\llama-2-7b.Q4_0.gguf -p %INPUT2% -n 400 -e -ngl 33 -s 0
-
-
diff --git a/ggml/include/ggml-metal.h b/ggml/include/ggml-metal.h
index e7543ae795d28..6c3226c37e0ef 100644
--- a/ggml/include/ggml-metal.h
+++ b/ggml/include/ggml-metal.h
@@ -63,4 +63,3 @@ GGML_API void ggml_backend_metal_capture_next_compute(ggml_backend_t backend);
 #ifdef __cplusplus
 }
 #endif
-
diff --git a/ggml/src/ggml-cuda/cpy.cu b/ggml/src/ggml-cuda/cpy.cu
index 12d741f017d3b..3db57034b488d 100644
--- a/ggml/src/ggml-cuda/cpy.cu
+++ b/ggml/src/ggml-cuda/cpy.cu
@@ -487,4 +487,3 @@ void* ggml_cuda_cpy_fn(const ggml_tensor * src0, ggml_tensor * src1) {
         GGML_ASSERT(false);
     }
 }
-
diff --git a/ggml/src/ggml-metal.metal b/ggml/src/ggml-metal.metal
index e2796fd601281..c3503479b35ba 100644
--- a/ggml/src/ggml-metal.metal
+++ b/ggml/src/ggml-metal.metal
@@ -6537,4 +6537,3 @@ template [[host_name("kernel_mul_mv_id_iq3_s_f32")]]   kernel kernel_mul_mv_id_t
 template [[host_name("kernel_mul_mv_id_iq2_s_f32")]]   kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
 template [[host_name("kernel_mul_mv_id_iq4_nl_f32")]]  kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
 template [[host_name("kernel_mul_mv_id_iq4_xs_f32")]]  kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
-
diff --git a/ggml/src/ggml-quants.h b/ggml/src/ggml-quants.h
index 4d436a8f06b3e..30983b8728fa2 100644
--- a/ggml/src/ggml-quants.h
+++ b/ggml/src/ggml-quants.h
@@ -130,4 +130,3 @@ void iq3xs_free_impl(int grid_size);
 #ifdef __cplusplus
 }
 #endif
-
diff --git a/ggml/src/ggml-vulkan-shaders.hpp b/ggml/src/ggml-vulkan-shaders.hpp
index 01ff66f71fcf0..f0c4c6baf592b 100644
--- a/ggml/src/ggml-vulkan-shaders.hpp
+++ b/ggml/src/ggml-vulkan-shaders.hpp
@@ -144954,4 +144954,3 @@ unsigned char sum_rows_f32_data[] = {
 
 };
 const uint64_t sum_rows_f32_len = 2112;
-
diff --git a/scripts/pod-llama.sh b/scripts/pod-llama.sh
index 586d6ea18af01..0d6d4032d8a9e 100644
--- a/scripts/pod-llama.sh
+++ b/scripts/pod-llama.sh
@@ -210,4 +210,3 @@ fi
 # more benches
 #GGML_CUDA=1 make -j && ./llama-batched-bench ./models/codellama-7b/ggml-model-q4_k.gguf  4096 1 99 1 512,3200 128,128,800 1
 #GGML_CUDA=1 make -j && ./llama-batched-bench ./models/codellama-13b/ggml-model-q4_k.gguf 4096 1 99 1 512,3200 128,128,800 1
-
diff --git a/src/unicode-data.cpp b/src/unicode-data.cpp
index 4a939898b367f..02bdf782380fe 100644
--- a/src/unicode-data.cpp
+++ b/src/unicode-data.cpp
@@ -7030,4 +7030,3 @@ const std::vector unicode_ranges_nfd = {  // start, last, nfd
 {0x02FA1C, 0x02FA1C, 0x009F3B},
 {0x02FA1D, 0x02FA1D, 0x02A600},
 };
-
diff --git a/tests/test-rope.cpp b/tests/test-rope.cpp
index f0895ffaad6a1..8159e276af617 100644
--- a/tests/test-rope.cpp
+++ b/tests/test-rope.cpp
@@ -218,4 +218,3 @@ int main(int /*argc*/, const char ** /*argv*/) {
 
     return 0;
 }
-

From 3e2618bc7bf9e9fbf58c32cc3c8dd7d5df1de27e Mon Sep 17 00:00:00 2001
From: Clint Herron 
Date: Tue, 2 Jul 2024 13:19:56 -0400
Subject: [PATCH 075/326] Adding step to `clean` target to remove legacy binary
 names to reduce upgrade / migration confusion arising from #7809. (#8257)

---
 Makefile | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/Makefile b/Makefile
index 8ae4f1dc4ede3..2730d8b602093 100644
--- a/Makefile
+++ b/Makefile
@@ -62,6 +62,11 @@ TEST_TARGETS = \
 	tests/test-tokenizer-1-bpe \
 	tests/test-tokenizer-1-spm
 
+# Legacy build targets that were renamed in #7809, but should still be removed when the project is cleaned
+LEGACY_TARGETS = main quantize quantize-stats perplexity imatrix embedding vdot q8dot train-text-from-scratch convert-llama2c-to-ggml \
+	simple batched batched-bench save-load-state server gguf gguf-split eval-callback llama-bench libllava.a llava-cli baby-llama \
+	retrieval speculative infill tokenize benchmark-matmult parallel finetune export-lora lookahead lookup passkey gritlm
+
 # Deprecation aliases
 ifdef LLAMA_CUBLAS
 $(error LLAMA_CUBLAS is removed. Use GGML_CUDA instead.)
@@ -1086,6 +1091,7 @@ clean:
 	rm -vrf ggml/src/ggml-cuda/template-instances/*.o
 	rm -rvf $(BUILD_TARGETS)
 	rm -rvf $(TEST_TARGETS)
+	rm -rvf $(LEGACY_TARGETS)
 	find examples pocs -type f -name "*.o" -delete
 
 #

From a27152b602b369e76f85b7cb7b872a321b7218f7 Mon Sep 17 00:00:00 2001
From: MistApproach <98988043+MistApproach@users.noreply.github.com>
Date: Tue, 2 Jul 2024 22:56:46 +0200
Subject: [PATCH 076/326] fix: add missing short command line argument -mli for
 multiline-input (#8261)

---
 common/common.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/common/common.cpp b/common/common.cpp
index 5a0d0ee038123..2c05a4d4a17c1 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -757,7 +757,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
         params.cache_type_v = argv[++i];
         return true;
     }
-    if (arg == "--multiline-input") {
+    if (arg == "-mli" || arg == "--multiline-input") {
         params.multiline_input = true;
         return true;
     }

From fadde6713506d9e6c124f5680ab8c7abebe31837 Mon Sep 17 00:00:00 2001
From: AidanBeltonS 
Date: Wed, 3 Jul 2024 02:55:34 +0100
Subject: [PATCH 077/326] Dequant improvements rebase (#8255)

* Single load for half2

* Store scales in local mem

* Vec load quantized values
---
 ggml/src/ggml-sycl/common.hpp     |  6 ++++++
 ggml/src/ggml-sycl/convert.cpp    |  7 +++++--
 ggml/src/ggml-sycl/dequantize.hpp | 30 +++++++++++++++++++-----------
 3 files changed, 30 insertions(+), 13 deletions(-)

diff --git a/ggml/src/ggml-sycl/common.hpp b/ggml/src/ggml-sycl/common.hpp
index dfd4a7c2c606b..476d847ca575e 100644
--- a/ggml/src/ggml-sycl/common.hpp
+++ b/ggml/src/ggml-sycl/common.hpp
@@ -351,4 +351,10 @@ static __dpct_inline__ float warp_reduce_max(float x,
     return x;
 }
 
+// Helper for vec loading aligned data
+template 
+inline sycl::vec vec_aligned_load(const Tp* aligned_ptr) {
+    return *reinterpret_cast*>(aligned_ptr);
+}
+
 #endif // GGML_SYCL_COMMON_HPP
diff --git a/ggml/src/ggml-sycl/convert.cpp b/ggml/src/ggml-sycl/convert.cpp
index ce9de2b42b722..a15271b516fa8 100644
--- a/ggml/src/ggml-sycl/convert.cpp
+++ b/ggml/src/ggml-sycl/convert.cpp
@@ -152,12 +152,15 @@ static void dequantize_row_q4_K_sycl(const void *vx, dst_t *y, const int k,
         dpct::has_capability_or_fail(stream->get_device(),
                                      {sycl::aspect::fp16});
 
-        stream->parallel_for(sycl::nd_range<3>(sycl::range<3>(1, 1, nb) *
+        stream->submit([&](sycl::handler &cgh) {
+            sycl::local_accessor scale_local_acc(sycl::range<1>(12), cgh);
+            cgh.parallel_for(sycl::nd_range<3>(sycl::range<3>(1, 1, nb) *
                                                    sycl::range<3>(1, 1, 32),
                                                sycl::range<3>(1, 1, 32)),
                              [=](sycl::nd_item<3> item_ct1) {
-                                 dequantize_block_q4_K(vx, y, item_ct1);
+                                 dequantize_block_q4_K(vx, y, scale_local_acc.get_pointer(), item_ct1);
                              });
+        });
     }
 }
 
diff --git a/ggml/src/ggml-sycl/dequantize.hpp b/ggml/src/ggml-sycl/dequantize.hpp
index b6080d83a33eb..ed8ad098bcb2f 100644
--- a/ggml/src/ggml-sycl/dequantize.hpp
+++ b/ggml/src/ggml-sycl/dequantize.hpp
@@ -293,7 +293,8 @@ static void dequantize_block_q3_K(const void * __restrict__ vx, dst_t * __restri
 #if QK_K == 256
 static inline void get_scale_min_k4(int j, const uint8_t * q, uint8_t & d, uint8_t & m) {
     if (j < 4) {
-        d = q[j] & 63; m = q[j + 4] & 63;
+        d = q[j] & 63;
+        m = q[j + 4] & 63;
     } else {
         d = (q[j+4] & 0xF) | ((q[j-4] >> 6) << 4);
         m = (q[j+4] >>  4) | ((q[j-0] >> 6) << 4);
@@ -303,7 +304,7 @@ static inline void get_scale_min_k4(int j, const uint8_t * q, uint8_t & d, uint8
 
 template
 static void dequantize_block_q4_K(const void * __restrict__ vx, dst_t * __restrict__ yy,
-                                  const sycl::nd_item<3> &item_ct1) {
+                                  uint8_t* scales_local, const sycl::nd_item<3> &item_ct1) {
     const block_q4_K * x = (const block_q4_K *) vx;
 
     const int i = item_ct1.get_group(2);
@@ -318,19 +319,26 @@ static void dequantize_block_q4_K(const void * __restrict__ vx, dst_t * __restri
 
     dst_t * y = yy + i*QK_K + 64*il + n*ir;
 
-    const float dall = x[i].dm[0];
-    const float dmin = x[i].dm[1];
+    const sycl::half2 dm = x[i].dm;
+    const float dall = dm[0];
+    const float dmin = dm[1];
 
-    const uint8_t * q = x[i].qs + 32*il + n*ir;
+    if (tid < 12)
+        scales_local[tid] = x[i].scales[tid];
+    item_ct1.barrier(sycl::access::fence_space::local_space);
 
     uint8_t sc, m;
-    get_scale_min_k4(is + 0, x[i].scales, sc, m);
-    const float d1 = dall * sc; const float m1 = dmin * m;
-    get_scale_min_k4(is + 1, x[i].scales, sc, m);
-    const float d2 = dall * sc; const float m2 = dmin * m;
+    get_scale_min_k4(is + 0, scales_local, sc, m);
+    const float d1 = dall * sc;
+    const float m1 = dmin * m;
+    get_scale_min_k4(is + 1, scales_local, sc, m);
+    const float d2 = dall * sc;
+    const float m2 = dmin * m;
+
+    sycl::vec q_vec = vec_aligned_load(x[i].qs + 32*il + n*ir);
     for (int l = 0; l < n; ++l) {
-        y[l + 0] = d1 * (q[l] & 0xF) - m1;
-        y[l +32] = d2 * (q[l] >>  4) - m2;
+        y[l + 0] = d1 * (q_vec[l] & 0xF) - m1;
+        y[l +32] = d2 * (q_vec[l] >>  4) - m2;
     }
 #else
     const int tid = item_ct1.get_local_id(2);

From f8d6a23804f3798ff2869da68c1223b618df09ec Mon Sep 17 00:00:00 2001
From: Judd 
Date: Wed, 3 Jul 2024 20:40:16 +0800
Subject: [PATCH 078/326] fix typo (#8267)

Co-authored-by: Judd 
---
 ggml/src/ggml.c | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c
index f5502afbe98b3..bc91ac3a726ab 100644
--- a/ggml/src/ggml.c
+++ b/ggml/src/ggml.c
@@ -5312,7 +5312,7 @@ void ggml_mul_mat_set_prec(
     as  -> [cols, rows, n_expert]
     ids -> [n_experts_used, n_tokens] (i32)
     b   -> [cols, n_expert_used, n_tokens]
-    c   -> [cols, n_expert_used, n_tokens]
+    c   -> [rows, n_expert_used, n_tokens]
 
     in b, n_experts_used can be broadcasted to match the n_expert_used of ids
 

From 916248af1f3c16abd7408de848e025da095c621c Mon Sep 17 00:00:00 2001
From: Xuan Son Nguyen 
Date: Wed, 3 Jul 2024 16:01:54 +0200
Subject: [PATCH 079/326] fix phi 3 conversion (#8262)

---
 convert-hf-to-gguf.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py
index 6add27cbb11a6..d01aed224d600 100755
--- a/convert-hf-to-gguf.py
+++ b/convert-hf-to-gguf.py
@@ -1942,7 +1942,7 @@ def set_gguf_parameters(self):
         if len(rope_scaling_type) == 0:
             raise KeyError('Missing the required key rope_scaling.type')
 
-        if rope_scaling_type == 'su':
+        if rope_scaling_type == 'su' or rope_scaling_type == 'longrope':
             attn_factor = math.sqrt(1 + math.log(scale) / math.log(orig_max_pos_embds)) if scale > 1.0 else 1.0
         elif rope_scaling_type == 'yarn':
             attn_factor = 0.1 * math.log(scale) + 1.0 if scale > 1.0 else 1.0

From 5f2d4e60e202aabee10051e6615bb821e51787be Mon Sep 17 00:00:00 2001
From: slaren 
Date: Wed, 3 Jul 2024 19:33:31 +0200
Subject: [PATCH 080/326] ppl : fix n_seq_max for perplexity (#8277)

* ppl : fix n_seq_max for perplexity

* use 1 seq for kl_divergence
---
 examples/perplexity/perplexity.cpp | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/examples/perplexity/perplexity.cpp b/examples/perplexity/perplexity.cpp
index efde8dfdff47b..dbe445391736c 100644
--- a/examples/perplexity/perplexity.cpp
+++ b/examples/perplexity/perplexity.cpp
@@ -1991,6 +1991,12 @@ int main(int argc, char ** argv) {
         params.n_batch = std::min(params.n_batch, n_kv);
     } else {
         params.n_batch = std::min(params.n_batch, params.n_ctx);
+        if (params.kl_divergence) {
+            params.n_parallel = 1;
+        } else {
+            // ensure there's at least enough seq_ids for HellaSwag
+            params.n_parallel = std::max(4, params.n_parallel);
+        }
     }
 
     if (params.ppl_stride > 0) {
@@ -2015,9 +2021,6 @@ int main(int argc, char ** argv) {
     llama_model * model;
     llama_context * ctx;
 
-    // ensure there's at least enough seq_ids for HellaSwag
-    params.n_parallel = std::max(4, params.n_parallel);
-
     // load the model and apply lora adapter, if any
     std::tie(model, ctx) = llama_init_from_gpt_params(params);
     if (model == NULL) {

From d23287f122c34ebef368742116d53a0ccb2041ee Mon Sep 17 00:00:00 2001
From: Daniele <57776841+daniandtheweb@users.noreply.github.com>
Date: Wed, 3 Jul 2024 23:02:58 +0000
Subject: [PATCH 081/326] Define and optimize  RDNA1 (#8085)

---
 ggml/src/ggml-cuda/common.cuh |  4 ++++
 ggml/src/ggml-cuda/mmq.cuh    | 10 +++++++---
 2 files changed, 11 insertions(+), 3 deletions(-)

diff --git a/ggml/src/ggml-cuda/common.cuh b/ggml/src/ggml-cuda/common.cuh
index 472f4ace1c2ad..4ff06b8719d37 100644
--- a/ggml/src/ggml-cuda/common.cuh
+++ b/ggml/src/ggml-cuda/common.cuh
@@ -227,6 +227,10 @@ typedef float2 dfloat2;
 #define RDNA2
 #endif
 
+#if defined(__gfx1010__) || defined(__gfx1012__)
+#define RDNA1
+#endif
+
 #ifndef __has_builtin
     #define __has_builtin(x) 0
 #endif
diff --git a/ggml/src/ggml-cuda/mmq.cuh b/ggml/src/ggml-cuda/mmq.cuh
index 1396e7a753ac3..deaed066f7c90 100644
--- a/ggml/src/ggml-cuda/mmq.cuh
+++ b/ggml/src/ggml-cuda/mmq.cuh
@@ -60,12 +60,16 @@ static constexpr __device__ int get_mmq_x_max_device() {
 }
 
 static constexpr int get_mmq_y_host(const int cc) {
-    return int8_mma_available(cc) || cc >= CC_VOLTA ? 128 : 64;
+    return cc >= CC_OFFSET_AMD ? (cc == CC_RDNA1 ? 64 : 128) : (cc >= CC_VOLTA ? 128 : 64);
 }
 
 static constexpr __device__ int get_mmq_y_device() {
 #if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
+#if defined(RDNA1)
+    return 64;
+#else
     return 128;
+#endif // defined RDNA1
 #else
 #if __CUDA_ARCH__ >= CC_VOLTA
     return 128;
@@ -2259,9 +2263,9 @@ static __device__ void mul_mat_q_process_tile(
 
 template 
 #if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
-#if defined(RDNA3) || defined(RDNA2)
+#if defined(RDNA3) || defined(RDNA2) || defined(RDNA1)
     __launch_bounds__(WARP_SIZE*nwarps, 2)
-#endif // defined(RDNA3) || defined(RDNA2)
+#endif // defined(RDNA3) || defined(RDNA2) || defined(RDNA1)
 #else
 #if __CUDA_ARCH__ >= CC_VOLTA
     __launch_bounds__(WARP_SIZE*nwarps, 1)

From f619024764e72261f14d7c31d892b8fb976603b4 Mon Sep 17 00:00:00 2001
From: AidanBeltonS 
Date: Thu, 4 Jul 2024 02:07:19 +0100
Subject: [PATCH 082/326] [SYCL] Remove unneeded semicolons (#8280)

---
 ggml/src/ggml-sycl/dpct/helper.hpp | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/ggml/src/ggml-sycl/dpct/helper.hpp b/ggml/src/ggml-sycl/dpct/helper.hpp
index 1ff297218c685..5e98660dc888d 100644
--- a/ggml/src/ggml-sycl/dpct/helper.hpp
+++ b/ggml/src/ggml-sycl/dpct/helper.hpp
@@ -255,7 +255,7 @@ namespace dpct
         void set_pitch(size_t pitch) { _pitch = pitch; }
 
         size_t get_x() { return _x; }
-        void set_x(size_t x) { _x = x; };
+        void set_x(size_t x) { _x = x; }
 
         size_t get_y() { return _y; }
         void set_y(size_t y) { _y = y; }
@@ -1056,7 +1056,7 @@ namespace dpct
 #error "Only support Windows and Linux."
 #endif
                 next_free = mapped_address_space;
-            };
+            }
 
         public:
             using buffer_id_t = int;
@@ -1077,7 +1077,7 @@ namespace dpct
 #else
 #error "Only support Windows and Linux."
 #endif
-            };
+            }
 
             mem_mgr(const mem_mgr &) = delete;
             mem_mgr &operator=(const mem_mgr &) = delete;

From 20fc3804bfb727074bc270b6eacb60af8d0bf7d4 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Thu, 4 Jul 2024 10:41:03 +0300
Subject: [PATCH 083/326] convert : fix gemma v1 tokenizer convert (#8248)

ggml-ci
---
 convert-hf-to-gguf-update.py              | 5 ++++-
 convert-hf-to-gguf.py                     | 3 +++
 models/ggml-vocab-bert-bge.gguf.inp       | 4 ++++
 models/ggml-vocab-bert-bge.gguf.out       | 2 ++
 models/ggml-vocab-command-r.gguf.inp      | 4 ++++
 models/ggml-vocab-command-r.gguf.out      | 2 ++
 models/ggml-vocab-deepseek-coder.gguf.inp | 4 ++++
 models/ggml-vocab-deepseek-coder.gguf.out | 2 ++
 models/ggml-vocab-deepseek-llm.gguf.inp   | 4 ++++
 models/ggml-vocab-deepseek-llm.gguf.out   | 2 ++
 models/ggml-vocab-falcon.gguf.inp         | 4 ++++
 models/ggml-vocab-falcon.gguf.out         | 2 ++
 models/ggml-vocab-gpt-2.gguf.inp          | 4 ++++
 models/ggml-vocab-gpt-2.gguf.out          | 2 ++
 models/ggml-vocab-llama-bpe.gguf.inp      | 6 ++++--
 models/ggml-vocab-llama-bpe.gguf.out      | 3 ++-
 models/ggml-vocab-llama-spm.gguf.inp      | 4 ++++
 models/ggml-vocab-llama-spm.gguf.out      | 2 ++
 models/ggml-vocab-mpt.gguf.inp            | 4 ++++
 models/ggml-vocab-mpt.gguf.out            | 2 ++
 models/ggml-vocab-phi-3.gguf.inp          | 4 ++++
 models/ggml-vocab-phi-3.gguf.out          | 2 ++
 models/ggml-vocab-qwen2.gguf.inp          | 4 ++++
 models/ggml-vocab-qwen2.gguf.out          | 2 ++
 models/ggml-vocab-refact.gguf.inp         | 4 ++++
 models/ggml-vocab-refact.gguf.out         | 2 ++
 models/ggml-vocab-starcoder.gguf.inp      | 4 ++++
 models/ggml-vocab-starcoder.gguf.out      | 2 ++
 28 files changed, 85 insertions(+), 4 deletions(-)

diff --git a/convert-hf-to-gguf-update.py b/convert-hf-to-gguf-update.py
index 944e9d15abdcc..9eb406cb87868 100755
--- a/convert-hf-to-gguf-update.py
+++ b/convert-hf-to-gguf-update.py
@@ -86,6 +86,8 @@ class TOKENIZER_TYPE(IntEnum):
     {"name": "poro-chat",      "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/LumiOpen/Poro-34B-chat", },
     {"name": "jina-v2-code",   "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-code", },
     {"name": "viking",         "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/LumiOpen/Viking-7B", }, # Also used for Viking 13B and 33B
+    {"name": "gemma",          "tokt": TOKENIZER_TYPE.SPM, "repo": "https://huggingface.co/google/gemma-2b", },
+    {"name": "gemma-2",        "tokt": TOKENIZER_TYPE.SPM, "repo": "https://huggingface.co/google/gemma-2-9b", },
     {"name": "jais",           "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/core42/jais-13b", },
 ]
 
@@ -273,7 +275,8 @@ def get_vocab_base_pre(self, tokenizer) -> str:
     "3333333",
     "33333333",
     "333333333",
-    # "Cửa Việt", # llama-bpe fails on this
+    "Cửa Việt", # llama-bpe fails on this
+    " discards",
     chktxt,
 ]
 
diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py
index d01aed224d600..bae14558992c8 100755
--- a/convert-hf-to-gguf.py
+++ b/convert-hf-to-gguf.py
@@ -2316,6 +2316,8 @@ def set_vocab(self):
         special_vocab._set_special_token("eot",    107)
         special_vocab.add_to_gguf(self.gguf_writer)
 
+        self.gguf_writer.add_add_space_prefix(False)
+
     def set_gguf_parameters(self):
         hparams = self.hparams
         block_count = hparams["num_hidden_layers"]
@@ -2366,6 +2368,7 @@ def set_vocab(self):
 
         special_vocab = gguf.SpecialVocab(self.dir_model, n_vocab=len(tokens))
         special_vocab.add_to_gguf(self.gguf_writer)
+
         self.gguf_writer.add_add_space_prefix(False)
 
     def set_gguf_parameters(self):
diff --git a/models/ggml-vocab-bert-bge.gguf.inp b/models/ggml-vocab-bert-bge.gguf.inp
index 0a89107c60d7f..5b4aeb31ac9c6 100644
--- a/models/ggml-vocab-bert-bge.gguf.inp
+++ b/models/ggml-vocab-bert-bge.gguf.inp
@@ -91,6 +91,10 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 333333333
 __ggml_vocab_test__
+Cửa Việt
+__ggml_vocab_test__
+ discards
+__ggml_vocab_test__
 
  
 
diff --git a/models/ggml-vocab-bert-bge.gguf.out b/models/ggml-vocab-bert-bge.gguf.out
index e4a76cdb07d3f..82d4ed1c13654 100644
--- a/models/ggml-vocab-bert-bge.gguf.out
+++ b/models/ggml-vocab-bert-bge.gguf.out
@@ -40,4 +40,6 @@
  21211 22394 22394
  21211 22394 22394 2509
  21211 22394 22394 22394
+ 12731 2050 19710
+ 5860 18117
  100 1006 3671 1007 100 1006 3674 7861 29147 2483 9530 16280 23854 1007 100 100 1017 3943 21211 21211 2509 21211 22394 21211 22394 2509 21211 22394 22394 21211 22394 22394 2509 1017 1012 1017 1017 1012 1012 1017 1017 1012 1012 1012 1017 100 1029 1855 100 100 6207 100 100 14677 23632 22203 1811 1995 1011 1011 1011 1011 1011 1011 1027 1027 1027 1027 1027 1027 1027 1192 15290 29754 14150 1192 10260 1181 29755 29436 29741 10260 16856 29747 23925 10325 1005 1005 1005 1005 1005 1005 1036 1036 1036 1036 1036 1036 1036 1000 1000 1000 1000 1012 1012 1012 1012 1012 1012 999 999 999 999 999 999 1029 1029 1029 1029 1029 1029 1045 1005 2310 2042 1005 2409 2002 1005 1055 2045 1010 1005 2128 2017 2469 1029 1005 1049 2025 2469 1045 1005 2222 2191 2009 1010 1005 1040 2017 2066 2070 5572 1029 2057 1005 2310 1037 1005 2222
diff --git a/models/ggml-vocab-command-r.gguf.inp b/models/ggml-vocab-command-r.gguf.inp
index 0a89107c60d7f..5b4aeb31ac9c6 100644
--- a/models/ggml-vocab-command-r.gguf.inp
+++ b/models/ggml-vocab-command-r.gguf.inp
@@ -91,6 +91,10 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 333333333
 __ggml_vocab_test__
+Cửa Việt
+__ggml_vocab_test__
+ discards
+__ggml_vocab_test__
 
  
 
diff --git a/models/ggml-vocab-command-r.gguf.out b/models/ggml-vocab-command-r.gguf.out
index cc4277daa1d25..939b9dc30a63e 100644
--- a/models/ggml-vocab-command-r.gguf.out
+++ b/models/ggml-vocab-command-r.gguf.out
@@ -40,4 +40,6 @@
  26 26 26 26 26 26 26
  26 26 26 26 26 26 26 26
  26 26 26 26 26 26 26 26 26
+ 42 30719 12584
+ 3642 4388
  127731 51628 205 57788 18494 97469 126134 206 2226 256 230 1737 18258 16 80503 122 35927 2226 242 112 57462 1737 54457 223165 106230 2096 16 48389 11254 107 255 2226 107 255 228 26 228 26 26 228 26 26 26 228 26 26 26 26 228 26 26 26 26 26 228 26 26 26 26 26 26 228 26 26 26 26 26 26 26 228 26 26 26 26 26 26 26 26 228 26 21 26 228 26 2271 26 228 26 3834 26 182018 230 174833 38111 249 86325 241 38111 245 86325 232 38111 252 38111 123 38111 261 165 24629 38111 261 38111 103 174833 38111 235 188568 231 5691 12081 13336 2648 29325 14315 24 26 24 27 24 28 24 5123 18372 8391 158343 3512 40071 2196 3236 8750 1764 37097 41168 29721 32797 25646 3802 4975 4975 116167 57178 10251 154048 27292 1767 5125 2632 2155 91 2378 1919 1914 2782 19 2155 3354 1933 5470 38 2155 52 2068 5470 1767 4961 3059 1894 19 2155 43 1933 3026 2725 23186 38 2930 14 20676 1671 14 83 51
diff --git a/models/ggml-vocab-deepseek-coder.gguf.inp b/models/ggml-vocab-deepseek-coder.gguf.inp
index 0a89107c60d7f..5b4aeb31ac9c6 100644
--- a/models/ggml-vocab-deepseek-coder.gguf.inp
+++ b/models/ggml-vocab-deepseek-coder.gguf.inp
@@ -91,6 +91,10 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 333333333
 __ggml_vocab_test__
+Cửa Việt
+__ggml_vocab_test__
+ discards
+__ggml_vocab_test__
 
  
 
diff --git a/models/ggml-vocab-deepseek-coder.gguf.out b/models/ggml-vocab-deepseek-coder.gguf.out
index 9ccc560d694ca..a43e3f0f115d2 100644
--- a/models/ggml-vocab-deepseek-coder.gguf.out
+++ b/models/ggml-vocab-deepseek-coder.gguf.out
@@ -40,4 +40,6 @@
  18 18 18 18 18 18 18
  18 18 18 18 18 18 18 18
  18 18 18 18 18 18 18 18 18
+ 34 155 119 242 64 24297 155 119 216 83
+ 1607 2539
  185 207 185 185 207 185 185 185 207 12405 459 22758 185 243 185 315 185 251 185 730 185 10047 235 209 334 8760 8 12394 233 114 350 222 10047 221 104 169 116 224 334 4684 3909 992 24330 262 29651 612 8 207 156 237 214 12394 99 234 10047 99 234 207 18 207 18 18 207 18 18 18 207 18 18 18 18 207 18 18 18 18 18 207 18 18 18 18 18 18 207 18 18 18 18 18 18 18 207 18 18 18 18 18 18 18 18 207 18 13 18 207 18 524 18 207 18 1202 18 207 155 239 209 155 239 114 155 239 228 155 240 220 155 239 224 155 240 211 155 239 231 155 239 115 155 239 240 155 240 210 155 239 240 155 239 95 155 239 114 155 239 214 10047 233 210 3015 19100 608 9413 2668 16 18 16 19 16 20 16 1393 169 121 239 18155 374 17194 28 2861 6478 616 2251 14994 31269 4191 6 4686 4686 10252 3358 3358 3409 524 15330 3023 15031 5668 303 6 312 798 651 83 839 362 6 82 741 11 651 1369 340 2037 30 651 44 441 2037 303 6 642 1098 359 11 651 35 340 833 738 10860 30 998 6 10709 245 6 75 43
diff --git a/models/ggml-vocab-deepseek-llm.gguf.inp b/models/ggml-vocab-deepseek-llm.gguf.inp
index 0a89107c60d7f..5b4aeb31ac9c6 100644
--- a/models/ggml-vocab-deepseek-llm.gguf.inp
+++ b/models/ggml-vocab-deepseek-llm.gguf.inp
@@ -91,6 +91,10 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 333333333
 __ggml_vocab_test__
+Cửa Việt
+__ggml_vocab_test__
+ discards
+__ggml_vocab_test__
 
  
 
diff --git a/models/ggml-vocab-deepseek-llm.gguf.out b/models/ggml-vocab-deepseek-llm.gguf.out
index fd94b896d24e7..d31ac1cc6696e 100644
--- a/models/ggml-vocab-deepseek-llm.gguf.out
+++ b/models/ggml-vocab-deepseek-llm.gguf.out
@@ -40,4 +40,6 @@
  18 18 18 18 18 18 18
  18 18 18 18 18 18 18 18
  18 18 18 18 18 18 18 18 18
+ 34 32555 242 64 23708 32555 216 83
+ 1763 2550
  185 207 185 185 207 185 185 185 207 11969 486 22504 185 243 185 300 185 251 185 663 185 10044 95300 334 8754 8 33701 114 350 222 10044 221 104 46713 334 34732 996 24250 262 80923 8 207 37103 214 12356 99 234 10044 99 234 207 18 207 18 18 207 18 18 18 207 18 18 18 18 207 18 18 18 18 18 207 18 18 18 18 18 18 207 18 18 18 18 18 18 18 207 18 18 18 18 18 18 18 18 207 18 13 18 207 18 526 18 207 18 1204 18 207 71374 209 71374 114 71374 228 155 240 220 71374 224 155 240 211 71374 231 71374 115 71374 240 155 240 210 71374 240 71374 95 71374 114 71374 214 71899 210 3025 19017 612 9407 2681 16 18 16 19 16 20 16 1398 68940 239 78827 55170 76659 620 91754 31116 36804 4885 4885 10897 4390 4390 41047 15278 3033 14986 5675 304 6 313 803 655 33326 362 6 82 745 11 655 1374 340 2049 30 655 44 441 2049 304 6 647 1099 359 11 655 35 340 837 742 10842 30 1003 6 10699 245 6 75 43
diff --git a/models/ggml-vocab-falcon.gguf.inp b/models/ggml-vocab-falcon.gguf.inp
index 0a89107c60d7f..5b4aeb31ac9c6 100644
--- a/models/ggml-vocab-falcon.gguf.inp
+++ b/models/ggml-vocab-falcon.gguf.inp
@@ -91,6 +91,10 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 333333333
 __ggml_vocab_test__
+Cửa Việt
+__ggml_vocab_test__
+ discards
+__ggml_vocab_test__
 
  
 
diff --git a/models/ggml-vocab-falcon.gguf.out b/models/ggml-vocab-falcon.gguf.out
index 209b04cdaf330..1ab70fe70ba7e 100644
--- a/models/ggml-vocab-falcon.gguf.out
+++ b/models/ggml-vocab-falcon.gguf.out
@@ -40,4 +40,6 @@
  22287 22287 30
  22287 22287 3138
  22287 22287 22287
+ 46 19768 239 76 9634 19768 213 95
+ 1080 1502
  1212 4824 1001 1212 192 204 663 49453 2069 742 561 1501 193 2571 232 206 204 19 11003 20 8196 126 283 219 48778 116 13392 204 19 51831 732 63209 1741 7955 522 20 22438 211 3346 111 231 2571 111 231 204 30 204 3138 204 22287 204 22287 30 204 22287 3138 204 22287 22287 204 22287 22287 30 204 22287 22287 3138 204 30 25 30 204 30 513 30 204 30 951 30 27171 236 206 38154 126 38154 225 167 237 217 38154 221 167 237 208 38154 228 38154 127 38154 237 167 237 207 38154 237 38154 107 38154 126 38154 211 20589 207 204 42 50087 123 2727 20300 32022 133 234 17419 30137 28 7858 181 133 236 204 37057 2228 10666 5052 133 6207 151 215 150 134 5052 133 6279 5052 223 151 216 49679 123 53110 47043 7795 204 7544 7544 7544 8543 8543 17593 3513 3513 12844 51520 17664 4247 295 18 298 650 204 18 95 693 332 18 94 629 23 204 18 1553 299 1310 42 204 18 56 416 1310 295 18 567 717 334 23 204 18 47 299 606 596 6696 42 703 18 16139 241 18 87 55
diff --git a/models/ggml-vocab-gpt-2.gguf.inp b/models/ggml-vocab-gpt-2.gguf.inp
index 0a89107c60d7f..5b4aeb31ac9c6 100644
--- a/models/ggml-vocab-gpt-2.gguf.inp
+++ b/models/ggml-vocab-gpt-2.gguf.inp
@@ -91,6 +91,10 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 333333333
 __ggml_vocab_test__
+Cửa Việt
+__ggml_vocab_test__
+ discards
+__ggml_vocab_test__
 
  
 
diff --git a/models/ggml-vocab-gpt-2.gguf.out b/models/ggml-vocab-gpt-2.gguf.out
index 78430f0d31fdc..88217d3fa787f 100644
--- a/models/ggml-vocab-gpt-2.gguf.out
+++ b/models/ggml-vocab-gpt-2.gguf.out
@@ -40,4 +40,6 @@
  24840 20370
  24840 24840
  24840 2091 20370
+ 34 157 119 255 64 16049 157 119 229 83
+ 1221 1371
  198 220 628 220 628 198 220 197 220 197 197 220 197 198 220 220 198 220 220 220 198 220 220 220 220 198 220 220 220 220 220 198 8582 248 222 357 11265 8 30325 114 447 235 8582 234 104 37929 357 48101 795 13210 271 1673 36686 515 8 14519 227 12520 99 247 8582 99 247 513 4747 23460 513 20370 23460 2091 23460 20370 23460 24840 23460 2091 20370 513 13 18 513 492 18 513 986 18 28053 252 222 157 252 114 157 252 241 157 253 233 157 252 237 157 253 224 157 252 244 157 252 115 157 252 253 157 253 223 157 252 253 157 252 95 157 252 114 157 252 227 47249 223 5633 22755 239 46349 111 28839 101 18040 32432 98 43291 1485 1415 24309 25465 171 121 252 40103 1421 18604 12466 121 16843 141 231 15166 12466 121 16142 12466 239 141 232 30143 140 111 16142 21169 21727 31583 18849 705 39115 6 33153 15506 63 15931 15931 16317 13896 3228 9805 3548 314 1053 587 705 44040 339 338 612 11 705 2200 345 1654 30 705 44 407 1654 314 1183 787 340 11 705 35 345 588 617 8887 30 775 6 26979 257 6 75 43
diff --git a/models/ggml-vocab-llama-bpe.gguf.inp b/models/ggml-vocab-llama-bpe.gguf.inp
index 9380bf355202a..5b4aeb31ac9c6 100644
--- a/models/ggml-vocab-llama-bpe.gguf.inp
+++ b/models/ggml-vocab-llama-bpe.gguf.inp
@@ -91,6 +91,10 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 333333333
 __ggml_vocab_test__
+Cửa Việt
+__ggml_vocab_test__
+ discards
+__ggml_vocab_test__
 
  
 
@@ -104,5 +108,3 @@ __ggml_vocab_test__
      
 🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
 __ggml_vocab_test__
- Việt
-__ggml_vocab_test__
diff --git a/models/ggml-vocab-llama-bpe.gguf.out b/models/ggml-vocab-llama-bpe.gguf.out
index 1f3607fb6a378..bb1fe229c6071 100644
--- a/models/ggml-vocab-llama-bpe.gguf.out
+++ b/models/ggml-vocab-llama-bpe.gguf.out
@@ -40,5 +40,6 @@
  8765 8765 18
  8765 8765 1644
  8765 8765 8765
+ 34 91163 101798
+ 2624 2402
  198 4815 15073 66597 8004 1602 2355 79772 11187 9468 248 222 320 8416 8 27623 114 102470 9468 234 104 31643 320 36773 100166 98634 8 26602 227 11410 99 247 9468 99 247 220 18 220 1644 220 8765 220 8765 18 220 8765 1644 220 8765 8765 220 8765 8765 18 220 8765 8765 1644 220 18 13 18 220 18 497 18 220 18 1131 18 220 21549 222 98629 241 45358 233 21549 237 45358 224 21549 244 21549 115 21549 253 45358 223 21549 253 21549 95 98629 227 76460 223 949 37046 101067 19000 23182 102301 9263 18136 16 36827 21909 56560 54337 19175 102118 13373 64571 34694 3114 112203 80112 3436 106451 14196 14196 74694 3089 3089 29249 17523 3001 27708 7801 358 3077 1027 364 83 820 568 596 1070 11 364 793 499 2771 30 364 44 539 2771 358 3358 1304 433 11 364 35 499 1093 1063 15600 30 1226 6 43712 264 64966 43
- 101798
diff --git a/models/ggml-vocab-llama-spm.gguf.inp b/models/ggml-vocab-llama-spm.gguf.inp
index 0a89107c60d7f..5b4aeb31ac9c6 100644
--- a/models/ggml-vocab-llama-spm.gguf.inp
+++ b/models/ggml-vocab-llama-spm.gguf.inp
@@ -91,6 +91,10 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 333333333
 __ggml_vocab_test__
+Cửa Việt
+__ggml_vocab_test__
+ discards
+__ggml_vocab_test__
 
  
 
diff --git a/models/ggml-vocab-llama-spm.gguf.out b/models/ggml-vocab-llama-spm.gguf.out
index 9c3327cb54380..1c3b0a2c979c5 100644
--- a/models/ggml-vocab-llama-spm.gguf.out
+++ b/models/ggml-vocab-llama-spm.gguf.out
@@ -40,4 +40,6 @@
  29871 29941 29941 29941 29941 29941 29941 29941
  29871 29941 29941 29941 29941 29941 29941 29941 29941
  29871 29941 29941 29941 29941 29941 29941 29941 29941 29941
+ 315 228 190 176 29874 10630 30529 29873
+ 29871 2313 3163
  29871 13 29871 13 13 29871 13 13 13 29871 12 29871 12 12 29871 12 13 259 13 1678 13 268 13 418 13 243 162 157 131 313 8945 29897 29871 243 162 155 185 30722 243 162 143 174 30598 313 20787 953 3848 275 16125 630 29897 29871 31681 29871 243 162 169 156 243 162 169 156 29871 29941 29871 29941 29941 29871 29941 29941 29941 29871 29941 29941 29941 29941 29871 29941 29941 29941 29941 29941 29871 29941 29941 29941 29941 29941 29941 29871 29941 29941 29941 29941 29941 29941 29941 29871 29941 29941 29941 29941 29941 29941 29941 29941 29871 29941 29889 29941 29871 29941 636 29941 29871 29941 856 29941 29871 31849 31324 31934 228 162 142 228 161 146 228 162 133 228 161 153 228 161 186 31708 228 162 132 31708 228 161 165 31324 228 161 136 243 162 155 132 1577 30672 31522 30505 11548 31041 30732 29896 29941 29896 29946 29896 29945 29896 30408 30739 448 23648 2751 25512 1538 4851 665 1386 29713 1305 14550 4907 11120 16159 16159 16159 15945 15945 3045 636 6824 6824 6824 8773 8773 8773 306 29915 345 1063 525 29873 1025 540 29915 29879 727 29892 525 1525 366 1854 29973 525 29924 451 1854 306 29915 645 1207 372 29892 525 29928 366 763 777 23429 29973 1334 29915 29963 29872 263 29915 29880 29931
diff --git a/models/ggml-vocab-mpt.gguf.inp b/models/ggml-vocab-mpt.gguf.inp
index 0a89107c60d7f..5b4aeb31ac9c6 100644
--- a/models/ggml-vocab-mpt.gguf.inp
+++ b/models/ggml-vocab-mpt.gguf.inp
@@ -91,6 +91,10 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 333333333
 __ggml_vocab_test__
+Cửa Việt
+__ggml_vocab_test__
+ discards
+__ggml_vocab_test__
 
  
 
diff --git a/models/ggml-vocab-mpt.gguf.out b/models/ggml-vocab-mpt.gguf.out
index d8d0fe90900bb..d4a877d1c2641 100644
--- a/models/ggml-vocab-mpt.gguf.out
+++ b/models/ggml-vocab-mpt.gguf.out
@@ -40,4 +40,6 @@
  26409 20084
  26409 26409
  26409 1610 20084
+ 36 6829 244 66 17721 35177 85
+ 1262 2196
  586 1744 33525 186 209 623 28910 187 50276 187 50275 187 50274 187 50273 187 14931 237 211 313 6320 10 49042 116 325 224 14931 223 106 171 118 226 313 34263 802 13511 261 32147 456 10 3384 239 216 22692 101 236 14931 101 236 495 5922 30057 495 20084 495 26409 30057 20084 495 26409 1610 495 26409 20084 495 15 20 495 537 20 495 1051 20 209 18081 211 18081 116 18081 230 39936 222 18081 226 39936 213 18081 233 18081 117 18081 242 39936 212 18081 242 18081 97 18081 116 18081 216 14931 235 212 3736 15367 41197 13610 19934 41869 21275 1012 1047 18795 40120 20422 241 16081 6877 12880 11514 1068 8713 38177 13396 3415 9925 12559 10453 1389 42011 35033 34842 11202 9739 9739 33021 18963 4672 25561 8220 309 1849 644 686 42618 344 434 627 13 686 1848 368 2119 32 686 46 417 2119 309 1833 1056 352 13 686 37 368 751 690 10331 32 844 8 31516 247 8 77 45
diff --git a/models/ggml-vocab-phi-3.gguf.inp b/models/ggml-vocab-phi-3.gguf.inp
index 0a89107c60d7f..5b4aeb31ac9c6 100644
--- a/models/ggml-vocab-phi-3.gguf.inp
+++ b/models/ggml-vocab-phi-3.gguf.inp
@@ -91,6 +91,10 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 333333333
 __ggml_vocab_test__
+Cửa Việt
+__ggml_vocab_test__
+ discards
+__ggml_vocab_test__
 
  
 
diff --git a/models/ggml-vocab-phi-3.gguf.out b/models/ggml-vocab-phi-3.gguf.out
index 9c3327cb54380..1c3b0a2c979c5 100644
--- a/models/ggml-vocab-phi-3.gguf.out
+++ b/models/ggml-vocab-phi-3.gguf.out
@@ -40,4 +40,6 @@
  29871 29941 29941 29941 29941 29941 29941 29941
  29871 29941 29941 29941 29941 29941 29941 29941 29941
  29871 29941 29941 29941 29941 29941 29941 29941 29941 29941
+ 315 228 190 176 29874 10630 30529 29873
+ 29871 2313 3163
  29871 13 29871 13 13 29871 13 13 13 29871 12 29871 12 12 29871 12 13 259 13 1678 13 268 13 418 13 243 162 157 131 313 8945 29897 29871 243 162 155 185 30722 243 162 143 174 30598 313 20787 953 3848 275 16125 630 29897 29871 31681 29871 243 162 169 156 243 162 169 156 29871 29941 29871 29941 29941 29871 29941 29941 29941 29871 29941 29941 29941 29941 29871 29941 29941 29941 29941 29941 29871 29941 29941 29941 29941 29941 29941 29871 29941 29941 29941 29941 29941 29941 29941 29871 29941 29941 29941 29941 29941 29941 29941 29941 29871 29941 29889 29941 29871 29941 636 29941 29871 29941 856 29941 29871 31849 31324 31934 228 162 142 228 161 146 228 162 133 228 161 153 228 161 186 31708 228 162 132 31708 228 161 165 31324 228 161 136 243 162 155 132 1577 30672 31522 30505 11548 31041 30732 29896 29941 29896 29946 29896 29945 29896 30408 30739 448 23648 2751 25512 1538 4851 665 1386 29713 1305 14550 4907 11120 16159 16159 16159 15945 15945 3045 636 6824 6824 6824 8773 8773 8773 306 29915 345 1063 525 29873 1025 540 29915 29879 727 29892 525 1525 366 1854 29973 525 29924 451 1854 306 29915 645 1207 372 29892 525 29928 366 763 777 23429 29973 1334 29915 29963 29872 263 29915 29880 29931
diff --git a/models/ggml-vocab-qwen2.gguf.inp b/models/ggml-vocab-qwen2.gguf.inp
index 0a89107c60d7f..5b4aeb31ac9c6 100644
--- a/models/ggml-vocab-qwen2.gguf.inp
+++ b/models/ggml-vocab-qwen2.gguf.inp
@@ -91,6 +91,10 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 333333333
 __ggml_vocab_test__
+Cửa Việt
+__ggml_vocab_test__
+ discards
+__ggml_vocab_test__
 
  
 
diff --git a/models/ggml-vocab-qwen2.gguf.out b/models/ggml-vocab-qwen2.gguf.out
index 401a510e86f3a..4ab275396631d 100644
--- a/models/ggml-vocab-qwen2.gguf.out
+++ b/models/ggml-vocab-qwen2.gguf.out
@@ -40,4 +40,6 @@
  18 18 18 18 18 18 18
  18 18 18 18 18 18 18 18
  18 18 18 18 18 18 18 18 18
+ 34 90063 128324
+ 2560 2347
  198 4710 14731 65497 7847 1572 2303 78672 10947 145836 320 8252 8 26525 114 378 235 149921 30543 320 35673 99066 97534 8 25521 227 11162 99 247 149955 220 18 220 18 18 220 18 18 18 220 18 18 18 18 220 18 18 18 18 18 220 18 18 18 18 18 18 220 18 18 18 18 18 18 18 220 18 18 18 18 18 18 18 18 220 18 13 18 220 18 496 18 220 18 1112 18 220 146394 97529 241 44258 233 146568 44258 224 147603 20879 115 146280 44258 223 146280 147272 97529 227 144534 937 104100 18493 22377 99257 16 18 16 19 16 20 16 35727 21216 55460 53237 18658 14144 1456 13073 63471 33594 3038 133178 79012 3355 4605 4605 13874 13874 73594 3014 3014 28149 17085 2928 26610 7646 358 3003 1012 364 83 813 566 594 1052 11 364 787 498 2704 30 364 44 537 2704 358 3278 1281 432 11 364 35 498 1075 1045 15243 30 1205 6 42612 264 63866 43
diff --git a/models/ggml-vocab-refact.gguf.inp b/models/ggml-vocab-refact.gguf.inp
index 0a89107c60d7f..5b4aeb31ac9c6 100644
--- a/models/ggml-vocab-refact.gguf.inp
+++ b/models/ggml-vocab-refact.gguf.inp
@@ -91,6 +91,10 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 333333333
 __ggml_vocab_test__
+Cửa Việt
+__ggml_vocab_test__
+ discards
+__ggml_vocab_test__
 
  
 
diff --git a/models/ggml-vocab-refact.gguf.out b/models/ggml-vocab-refact.gguf.out
index 06b15c090c0f8..46d8b4aec7e19 100644
--- a/models/ggml-vocab-refact.gguf.out
+++ b/models/ggml-vocab-refact.gguf.out
@@ -40,4 +40,6 @@
  37 37 37 37 37 37 37
  37 37 37 37 37 37 37 37
  37 37 37 37 37 37 37 37 37
+ 53 33934 83 33217 17102 102
+ 1214 12258
  334 719 8878 202 10885 4222 16104 28570 203 3807 253 227 308 4382 27 18458 133 46113 44967 123 13868 308 12565 19775 33071 40824 733 27 41889 5945 118 252 3807 118 252 225 37 225 37 37 225 37 37 37 225 37 37 37 37 225 37 37 37 37 37 225 37 37 37 37 37 37 225 37 37 37 37 37 37 37 225 37 37 37 37 37 37 37 37 225 37 32 37 225 37 497 37 225 37 1179 37 225 14574 227 14574 133 14574 246 30457 238 14574 242 30457 229 14574 249 14574 134 14574 258 30457 228 14574 258 14574 114 14574 133 14574 232 36628 228 1018 4982 13368 2909 9513 17827 35 37 35 38 35 39 35 11873 47838 20921 16623 13028 8372 1039 9446 40242 13852 2053 8949 12531 1520 10700 5881 9592 13299 914 31753 31359 9163 3202 35472 10397 439 4763 2583 330 102 1455 938 1182 2017 30 330 613 844 3654 49 330 63 646 3654 439 4621 1930 561 30 330 54 844 2124 1629 35993 49 2688 25 7709 312 25 94 62
diff --git a/models/ggml-vocab-starcoder.gguf.inp b/models/ggml-vocab-starcoder.gguf.inp
index 0a89107c60d7f..5b4aeb31ac9c6 100644
--- a/models/ggml-vocab-starcoder.gguf.inp
+++ b/models/ggml-vocab-starcoder.gguf.inp
@@ -91,6 +91,10 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 333333333
 __ggml_vocab_test__
+Cửa Việt
+__ggml_vocab_test__
+ discards
+__ggml_vocab_test__
 
  
 
diff --git a/models/ggml-vocab-starcoder.gguf.out b/models/ggml-vocab-starcoder.gguf.out
index ccb55c7feeef8..9ce2698a97d7b 100644
--- a/models/ggml-vocab-starcoder.gguf.out
+++ b/models/ggml-vocab-starcoder.gguf.out
@@ -40,4 +40,6 @@
  56 56 56 56 56 56 56
  56 56 56 56 56 56 56 56
  56 56 56 56 56 56 56 56 56
+ 72 34269 102 33245 17234 121
+ 1236 12266
  353 736 8886 221 10883 4238 16101 28540 222 3822 272 246 327 4434 46 18445 152 46030 45022 142 13878 327 12585 19884 33773 40920 751 46 41839 5954 137 271 3822 137 271 244 56 244 56 56 244 56 56 56 244 56 56 56 56 244 56 56 56 56 56 244 56 56 56 56 56 56 244 56 56 56 56 56 56 56 244 56 56 56 56 56 56 56 56 244 56 51 56 244 56 516 56 244 56 1198 56 244 14566 246 14566 152 14566 265 30428 257 14566 261 30428 248 14566 268 14566 153 14566 277 30428 247 14566 277 14566 133 14566 152 14566 251 36570 247 1037 4995 13379 2924 9515 17823 54 56 54 57 54 58 54 11904 47892 20895 16625 13047 8389 1059 9504 40216 13858 2073 8983 12571 1539 10721 5918 9643 13298 932 31723 31330 9221 3226 35426 10400 457 4783 2602 349 121 1477 957 1200 2038 49 349 632 863 3673 68 349 82 666 3673 457 4650 1949 580 49 349 73 863 2144 1649 35941 68 2726 44 7728 331 44 113 81

From 402d6feffa0572d1c7a957901b6d1702bd188484 Mon Sep 17 00:00:00 2001
From: Daniel Bevenius 
Date: Thu, 4 Jul 2024 12:50:57 +0200
Subject: [PATCH 084/326] llama : suppress unref var in Windows MSVC (#8150)

* llama : suppress unref var in Windows MSVC

This commit suppresses two warnings that are currently generated for
src/llama.cpp when building on Windows MSVC

```console
C:\llama.cpp\src\llama.cpp(14349,45): warning C4101: 'ex':
unreferenced local variable [C:\llama.cpp\build\src\llama.vcxproj]
C:\llama.cpp\src\llama.cpp(19285,44): warning C4101: 'e':
unreferenced local variable [C:\llama.cpp\build\src\llama.vcxproj]
```

* Update src/llama.cpp

---------

Co-authored-by: Georgi Gerganov 
---
 src/llama.cpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/llama.cpp b/src/llama.cpp
index 73f52435a503e..3d131b325ef20 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -14781,7 +14781,7 @@ struct llm_tokenizer_ugm {
                 size_t prefix_offset = input_offset;
                 unicode_cpt_from_utf8(input, prefix_offset);
                 return { &input[input_offset], prefix_offset - input_offset, prefix_offset - input_offset };
-            } catch(std::invalid_argument & ex) {
+            } catch (std::invalid_argument & /*ex*/) {
                 // if no, consume 1 byte and return U+FFFD - REPLACEMENT CHARACTER
                 return { "\xEF\xBF\xBD", 3, 1 };
             }
@@ -19725,7 +19725,7 @@ static std::string llama_decode_text(const std::string & text) {
         const auto utf8 = unicode_cpt_to_utf8(cpt);
         try {
             decoded_text += unicode_utf8_to_byte(utf8);
-        } catch (const std::out_of_range & e) {
+        } catch (const std::out_of_range & /*e*/) {
             decoded_text += "[UNK_BYTE_0x";
             for (const auto c : utf8) {
                 decoded_text += format("%02x", (uint8_t) c);

From f8c4c0738d72d2162736edd72dd5db8b269adca1 Mon Sep 17 00:00:00 2001
From: Daniel Bevenius 
Date: Thu, 4 Jul 2024 12:53:42 +0200
Subject: [PATCH 085/326] tests : add _CRT_SECURE_NO_WARNINGS for WIN32 (#8231)

This commit adds the compile definition `_CRT_SECURE_NO_WARNINGS`
to the root cmake subproject.

The motivation for this is that currently the following warnings are
displayed when compiling the tests and common cmake subprojects:
```console
test-llama-grammar.cpp
C:\llama.cpp\src\.\llama.cpp(1406,77): warning C4996: 'strerror':
This function or variable may be unsafe. Consider using strerror_s
instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See
online help for details.
[C:\llama.cpp\build\tests\test-llama-grammar.vcxproj]
...
```

This compile definition is currently set for the `src` subproject
and this change moves into the root cmake project so that it is applied
to all cmake subprojects.
---
 CMakeLists.txt     | 4 ++++
 src/CMakeLists.txt | 2 --
 2 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/CMakeLists.txt b/CMakeLists.txt
index e3a0cc369e364..d95414d710f56 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -42,6 +42,10 @@ endif()
 
 option(BUILD_SHARED_LIBS "build shared libraries" ${BUILD_SHARED_LIBS_DEFAULT})
 
+if (WIN32)
+    add_compile_definitions(_CRT_SECURE_NO_WARNINGS)
+endif()
+
 #
 # option list
 #
diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt
index ccb607e56d336..c2049df79c212 100644
--- a/src/CMakeLists.txt
+++ b/src/CMakeLists.txt
@@ -1,7 +1,5 @@
 # TODO: should not use this
 if (WIN32)
-    add_compile_definitions(_CRT_SECURE_NO_WARNINGS)
-
     if (BUILD_SHARED_LIBS)
         set(CMAKE_WINDOWS_EXPORT_ALL_SYMBOLS ON)
     endif()

From 807b0c49ff7071094f97ebc3a0a8e2b9e274f503 Mon Sep 17 00:00:00 2001
From: fairydreaming <166155368+fairydreaming@users.noreply.github.com>
Date: Thu, 4 Jul 2024 15:46:11 +0200
Subject: [PATCH 086/326] Inference support for T5 and FLAN-T5 model families
 (#5763)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

* llama : add inference support and model types for T5 and FLAN-T5 model families

* llama : add new API functions to support encoder-decoder models: llama_encode(), llama_model_has_encoder(), llama_model_decoder_start_token()

* common, llama-cli, llama-batched : add support for encoder-decoder models

* convert-hf : handle shared token embeddings tensors in T5Model

* convert-hf : add support for SentencePiece BPE tokenizer in T5Model (for Pile-T5 models)

* convert-hf : add MT5ForConditionalGeneration and UMT5ForConditionalGeneration to architectures supported by T5Model

* convert : add t5 tokenizer tests, use "slow" HF tokenizer for t5

---------

Co-authored-by: Stanisław Szymczyk 
Co-authored-by: Georgi Gerganov 
---
 common/common.cpp                         |  19 +-
 convert-hf-to-gguf-update.py              |  19 +-
 convert-hf-to-gguf.py                     |  46 +-
 examples/batched/batched.cpp              |  34 +-
 examples/main/main.cpp                    |  22 +-
 include/llama.h                           |  15 +
 models/ggml-vocab-bert-bge.gguf.inp       |   2 +
 models/ggml-vocab-bert-bge.gguf.out       |   1 +
 models/ggml-vocab-command-r.gguf.inp      |   2 +
 models/ggml-vocab-command-r.gguf.out      |   1 +
 models/ggml-vocab-deepseek-coder.gguf.inp |   2 +
 models/ggml-vocab-deepseek-coder.gguf.out |   1 +
 models/ggml-vocab-deepseek-llm.gguf.inp   |   2 +
 models/ggml-vocab-deepseek-llm.gguf.out   |   1 +
 models/ggml-vocab-falcon.gguf.inp         |   2 +
 models/ggml-vocab-falcon.gguf.out         |   1 +
 models/ggml-vocab-gpt-2.gguf.inp          |   2 +
 models/ggml-vocab-gpt-2.gguf.out          |   1 +
 models/ggml-vocab-llama-bpe.gguf.inp      |   2 +
 models/ggml-vocab-llama-bpe.gguf.out      |   1 +
 models/ggml-vocab-llama-spm.gguf.inp      |   2 +
 models/ggml-vocab-llama-spm.gguf.out      |   1 +
 models/ggml-vocab-mpt.gguf.inp            |   2 +
 models/ggml-vocab-mpt.gguf.out            |   1 +
 models/ggml-vocab-phi-3.gguf.inp          |   2 +
 models/ggml-vocab-phi-3.gguf.out          |   1 +
 models/ggml-vocab-qwen2.gguf.inp          |   2 +
 models/ggml-vocab-qwen2.gguf.out          |   1 +
 models/ggml-vocab-refact.gguf.inp         |   2 +
 models/ggml-vocab-refact.gguf.out         |   1 +
 models/ggml-vocab-starcoder.gguf.inp      |   2 +
 models/ggml-vocab-starcoder.gguf.out      |   1 +
 src/llama.cpp                             | 783 +++++++++++++++++++++-
 33 files changed, 946 insertions(+), 31 deletions(-)

diff --git a/common/common.cpp b/common/common.cpp
index 2c05a4d4a17c1..4138dc3b62cd8 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -2070,7 +2070,24 @@ std::tuple llama_init_from_gpt_par
     if (params.warmup) {
         LOG("warming up the model with an empty run\n");
 
-        std::vector tmp = { llama_token_bos(model), llama_token_eos(model), };
+        std::vector tmp;
+        llama_token bos = llama_token_bos(model);
+        llama_token eos = llama_token_eos(model);
+        // some models (e.g. T5) don't have a BOS token
+        if (bos != -1) {
+            tmp.push_back(bos);
+        }
+        tmp.push_back(eos);
+
+        if (llama_model_has_encoder(model)) {
+            llama_encode(lctx, llama_batch_get_one(tmp.data(), tmp.size(), 0, 0));
+            llama_token decoder_start_token_id = llama_model_decoder_start_token(model);
+            if (decoder_start_token_id == -1) {
+                decoder_start_token_id = bos;
+            }
+            tmp.clear();
+            tmp.push_back(decoder_start_token_id);
+        }
         llama_decode(lctx, llama_batch_get_one(tmp.data(), std::min(tmp.size(), (size_t) params.n_batch), 0, 0));
         llama_kv_cache_clear(lctx);
         llama_synchronize(lctx);
diff --git a/convert-hf-to-gguf-update.py b/convert-hf-to-gguf-update.py
index 9eb406cb87868..21a3062554578 100755
--- a/convert-hf-to-gguf-update.py
+++ b/convert-hf-to-gguf-update.py
@@ -45,6 +45,7 @@ class TOKENIZER_TYPE(IntEnum):
     SPM = auto()
     BPE = auto()
     WPM = auto()
+    UGM = auto()
 
 
 # TODO: this string has to exercise as much pre-tokenizer functionality as possible
@@ -89,6 +90,7 @@ class TOKENIZER_TYPE(IntEnum):
     {"name": "gemma",          "tokt": TOKENIZER_TYPE.SPM, "repo": "https://huggingface.co/google/gemma-2b", },
     {"name": "gemma-2",        "tokt": TOKENIZER_TYPE.SPM, "repo": "https://huggingface.co/google/gemma-2-9b", },
     {"name": "jais",           "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/core42/jais-13b", },
+    {"name": "t5",             "tokt": TOKENIZER_TYPE.UGM, "repo": "https://huggingface.co/google-t5/t5-small", },
 ]
 
 
@@ -110,9 +112,13 @@ def download_model(model):
     os.makedirs(f"models/tokenizers/{name}", exist_ok=True)
 
     files = ["config.json", "tokenizer.json", "tokenizer_config.json"]
+
     if tokt == TOKENIZER_TYPE.SPM:
         files.append("tokenizer.model")
 
+    if tokt == TOKENIZER_TYPE.UGM:
+        files.append("spiece.model")
+
     for file in files:
         save_path = f"models/tokenizers/{name}/{file}"
         if os.path.isfile(save_path):
@@ -135,7 +141,7 @@ def download_model(model):
     name = model["name"]
     tokt = model["tokt"]
 
-    if tokt == TOKENIZER_TYPE.SPM:
+    if tokt == TOKENIZER_TYPE.SPM or tokt == TOKENIZER_TYPE.UGM:
         continue
 
     # Skip if the tokenizer folder does not exist or there are other download issues previously
@@ -145,7 +151,10 @@ def download_model(model):
 
     # create the tokenizer
     try:
-        tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}")
+        if name == "t5":
+            tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}", use_fast=False)
+        else:
+            tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}")
     except OSError as e:
         logger.error(f"Error loading tokenizer for model {name}. The model may not exist or is not accessible with the provided token. Error: {e}")
         continue  # Skip to the next model if the tokenizer can't be loaded
@@ -266,6 +275,7 @@ def get_vocab_base_pre(self, tokenizer) -> str:
     "\n =",
     "' era",
     "Hello, y'all! How are you 😁 ?我想在apple工作1314151天～",
+    "!!!!!!",
     "3",
     "33",
     "333",
@@ -304,7 +314,10 @@ def get_vocab_base_pre(self, tokenizer) -> str:
 
     # create the tokenizer
     try:
-        tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}")
+        if name == "t5":
+            tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}", use_fast=False)
+        else:
+            tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}")
     except OSError as e:
         logger.error(f"Failed to load tokenizer for model {name}. Error: {e}")
         continue  # Skip this model and continue with the next one in the loop
diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py
index bae14558992c8..a1d165023ce73 100755
--- a/convert-hf-to-gguf.py
+++ b/convert-hf-to-gguf.py
@@ -2853,11 +2853,17 @@ def write_tensors(self):
                 raise ValueError(f"Unprocessed experts: {experts}")
 
 
-@Model.register("T5ForConditionalGeneration")
 @Model.register("T5WithLMHeadModel")
+@Model.register("T5ForConditionalGeneration")
+@Model.register("MT5ForConditionalGeneration")
+@Model.register("UMT5ForConditionalGeneration")
 class T5Model(Model):
     model_arch = gguf.MODEL_ARCH.T5
 
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.shared_token_embeddings_found = False
+
     def set_vocab(self):
         # to avoid TypeError: Descriptors cannot be created directly
         # exception when importing sentencepiece_model_pb2
@@ -2865,17 +2871,29 @@ def set_vocab(self):
         from sentencepiece import SentencePieceProcessor
         from sentencepiece import sentencepiece_model_pb2 as model
 
-        tokenizer_path = self.dir_model / 'spiece.model'
+        tokenizer_path = self.dir_model / 'tokenizer.model'
+
+        # many older models use spiece.model tokenizer model filename
+        if not tokenizer_path.is_file():
+            tokenizer_path = self.dir_model / 'spiece.model'
 
         if not tokenizer_path.is_file():
             raise FileNotFoundError(f"File not found: {tokenizer_path}")
 
         sentencepiece_model = model.ModelProto()
         sentencepiece_model.ParseFromString(open(tokenizer_path, "rb").read())
+
+        # some models like Pile-T5 family use BPE tokenizer instead of Unigram
+        if sentencepiece_model.trainer_spec.model_type == 2: # BPE
+            # assure the tokenizer model file name is correct
+            assert tokenizer_path.name == 'tokenizer.model'
+            return self._set_vocab_sentencepiece()
+        else:
+            assert sentencepiece_model.trainer_spec.model_type == 1 # UNIGRAM
+
         add_prefix = sentencepiece_model.normalizer_spec.add_dummy_prefix
         remove_whitespaces = sentencepiece_model.normalizer_spec.remove_extra_whitespaces
         precompiled_charsmap = sentencepiece_model.normalizer_spec.precompiled_charsmap
-        assert sentencepiece_model.trainer_spec.model_type == 1 # UNIGRAM
 
         tokenizer = SentencePieceProcessor()
         tokenizer.LoadFromFile(str(tokenizer_path))
@@ -2945,7 +2963,10 @@ def set_vocab(self):
 
     def set_gguf_parameters(self):
         self.gguf_writer.add_name("T5")
-        self.gguf_writer.add_context_length(self.hparams["n_positions"])
+        if (n_ctx := self.find_hparam(["n_positions"], optional=True)) is None:
+            logger.warning("Couldn't find context length in config.json, assuming default value of 512")
+            n_ctx = 512
+        self.gguf_writer.add_context_length(n_ctx)
         self.gguf_writer.add_embedding_length(self.hparams["d_model"])
         self.gguf_writer.add_feed_forward_length(self.hparams["d_ff"])
         self.gguf_writer.add_block_count(self.hparams["num_layers"])
@@ -2961,12 +2982,17 @@ def set_gguf_parameters(self):
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         del bid  # unused
 
-        # Sometimes T5 and Flan-T5 based models contain "encoder.embed_tokens.weight" tensor or
-        # "decoder.embed_tokens.weight" tensors that are duplicates of "shared.weight" tensor
-        # To prevent errors caused by an unnecessary unmapped tensor, skip both of them and use only "shared.weight".
-        if name == "decoder.embed_tokens.weight" or name == "encoder.embed_tokens.weight":
-            logger.debug(f"Skipping tensor {name!r} in safetensors so that convert can end normally.")
-            return []
+        # T5 based models contain shared token embeddings tensors saved randomly as either "encoder.embed_tokens.weight",
+        # "decoder.embed_tokens.weight" or "shared.weight" tensor. In some models there are even multiple of them stored
+        # in the safetensors files. We use the first tensor from these three as the token embeddings for both encoder
+        # and decoder and ignore the remaining ones.
+        if name in ["decoder.embed_tokens.weight", "encoder.embed_tokens.weight", "shared.weight"]:
+            if not self.shared_token_embeddings_found:
+                name = "shared.weight"
+                self.shared_token_embeddings_found = True
+            else:
+                logger.debug(f"Skipping shared tensor {name!r} in safetensors so that convert can end normally.")
+                return []
 
         return [(self.map_tensor_name(name), data_torch)]
 
diff --git a/examples/batched/batched.cpp b/examples/batched/batched.cpp
index 62d9b144d3340..2442e954dcc1a 100644
--- a/examples/batched/batched.cpp
+++ b/examples/batched/batched.cpp
@@ -93,14 +93,34 @@ int main(int argc, char ** argv) {
 
     // create a llama_batch
     // we use this object to submit token data for decoding
-    llama_batch batch = llama_batch_init(std::max(tokens_list.size(), (size_t)n_parallel), 0, 1);
+    llama_batch batch = llama_batch_init(std::max(tokens_list.size(), (size_t) n_parallel), 0, n_parallel);
+
+    std::vector seq_ids(n_parallel, 0);
+    for (int32_t i = 0; i < n_parallel; ++i) {
+        seq_ids[i] = i;
+    }
 
     // evaluate the initial prompt
     for (size_t i = 0; i < tokens_list.size(); ++i) {
-        llama_batch_add(batch, tokens_list[i], i, { 0 }, false);
+        llama_batch_add(batch, tokens_list[i], i, seq_ids, false);
     }
     GGML_ASSERT(batch.n_tokens == (int) tokens_list.size());
 
+    if (llama_model_has_encoder(model)) {
+        if (llama_encode(ctx, batch)) {
+            LOG_TEE("%s : failed to eval\n", __func__);
+            return 1;
+        }
+
+        llama_token decoder_start_token_id = llama_model_decoder_start_token(model);
+        if (decoder_start_token_id == -1) {
+            decoder_start_token_id = llama_token_bos(model);
+        }
+
+        llama_batch_clear(batch);
+        llama_batch_add(batch, decoder_start_token_id, 0, seq_ids, false);
+    }
+
     // llama_decode will output logits only for the last token of the prompt
     batch.logits[batch.n_tokens - 1] = true;
 
@@ -109,11 +129,11 @@ int main(int argc, char ** argv) {
         return 1;
     }
 
-    // assign the system KV cache to all parallel sequences
-    // this way, the parallel sequences will "reuse" the prompt tokens without having to copy them
-    for (int32_t i = 1; i < n_parallel; ++i) {
-        llama_kv_cache_seq_cp(ctx, 0, i, -1, -1);
-    }
+    //// assign the system KV cache to all parallel sequences
+    //// this way, the parallel sequences will "reuse" the prompt tokens without having to copy them
+    //for (int32_t i = 1; i < n_parallel; ++i) {
+    //    llama_kv_cache_seq_cp(ctx, 0, i, -1, -1);
+    //}
 
     if (n_parallel > 1) {
         LOG_TEE("\n\n%s: generating %d sequences ...\n", __func__, n_parallel);
diff --git a/examples/main/main.cpp b/examples/main/main.cpp
index d512953b9635c..22bb37889bf8e 100644
--- a/examples/main/main.cpp
+++ b/examples/main/main.cpp
@@ -255,7 +255,9 @@ int main(int argc, char ** argv) {
     }
 
     const bool add_bos = llama_should_add_bos_token(model);
-    GGML_ASSERT(llama_add_eos_token(model) != 1);
+    if (!llama_model_has_encoder(model)) {
+        GGML_ASSERT(llama_add_eos_token(model) != 1);
+    }
     LOG("add_bos: %d\n", add_bos);
 
     std::vector embd_inp;
@@ -517,6 +519,24 @@ int main(int argc, char ** argv) {
         exit(1);
     }
 
+    if (llama_model_has_encoder(model)) {
+        int enc_input_size = embd_inp.size();
+        llama_token * enc_input_buf = embd_inp.data();
+
+        if (llama_encode(ctx, llama_batch_get_one(enc_input_buf, enc_input_size, 0, 0))) {
+            LOG_TEE("%s : failed to eval\n", __func__);
+            return 1;
+        }
+
+        llama_token decoder_start_token_id = llama_model_decoder_start_token(model);
+        if (decoder_start_token_id == -1) {
+            decoder_start_token_id = llama_token_bos(model);
+        }
+
+        embd_inp.clear();
+        embd_inp.push_back(decoder_start_token_id);
+    }
+
     while ((n_remain != 0 && !is_antiprompt) || params.interactive) {
         // predict
         if (!embd.empty()) {
diff --git a/include/llama.h b/include/llama.h
index c5b6182920428..aca79d2b864b8 100644
--- a/include/llama.h
+++ b/include/llama.h
@@ -485,6 +485,13 @@ extern "C" {
     // Get a llama model tensor
     LLAMA_API struct ggml_tensor * llama_get_model_tensor(struct llama_model * model, const char * name);
 
+    // Returns true if the model contains an encoder that requires llama_encode() call
+    LLAMA_API bool llama_model_has_encoder(const struct llama_model * model);
+
+    // For encoder-decoder models, this function returns id of the token that must be provided
+    // to the decoder to start generating output sequence. For other models, it returns -1.
+    LLAMA_API llama_token llama_model_decoder_start_token(const struct llama_model * model);
+
     // Returns 0 on success
     LLAMA_API uint32_t llama_model_quantize(
             const char * fname_inp,
@@ -770,6 +777,14 @@ extern "C" {
     // Frees a batch of tokens allocated with llama_batch_init()
     LLAMA_API void llama_batch_free(struct llama_batch batch);
 
+    // Processes a batch of tokens with the ecoder part of the encoder-decoder model.
+    // Stores the encoder output internally for later use by the decoder cross-attention layers.
+    //   0 - success
+    // < 0 - error
+    LLAMA_API int32_t llama_encode(
+            struct llama_context * ctx,
+              struct llama_batch   batch);
+
     // Positive return values does not mean a fatal error, but rather a warning.
     //   0 - success
     //   1 - could not find a KV slot for the batch (try reducing the size of the batch or increase the context)
diff --git a/models/ggml-vocab-bert-bge.gguf.inp b/models/ggml-vocab-bert-bge.gguf.inp
index 5b4aeb31ac9c6..9baf7d77ae6b5 100644
--- a/models/ggml-vocab-bert-bge.gguf.inp
+++ b/models/ggml-vocab-bert-bge.gguf.inp
@@ -73,6 +73,8 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
 __ggml_vocab_test__
+!!!!!!
+__ggml_vocab_test__
 3
 __ggml_vocab_test__
 33
diff --git a/models/ggml-vocab-bert-bge.gguf.out b/models/ggml-vocab-bert-bge.gguf.out
index 82d4ed1c13654..a62566ce75676 100644
--- a/models/ggml-vocab-bert-bge.gguf.out
+++ b/models/ggml-vocab-bert-bge.gguf.out
@@ -31,6 +31,7 @@
  1027
  1005 3690
  7592 1010 1061 1005 2035 999 2129 2024 2017 100 1029 1855 100 100 6207 100 100 14677 23632 22203 1811 1995
+ 999 999 999 999 999 999
  1017
  3943
  21211
diff --git a/models/ggml-vocab-command-r.gguf.inp b/models/ggml-vocab-command-r.gguf.inp
index 5b4aeb31ac9c6..9baf7d77ae6b5 100644
--- a/models/ggml-vocab-command-r.gguf.inp
+++ b/models/ggml-vocab-command-r.gguf.inp
@@ -73,6 +73,8 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
 __ggml_vocab_test__
+!!!!!!
+__ggml_vocab_test__
 3
 __ggml_vocab_test__
 33
diff --git a/models/ggml-vocab-command-r.gguf.out b/models/ggml-vocab-command-r.gguf.out
index 939b9dc30a63e..3f6b418888740 100644
--- a/models/ggml-vocab-command-r.gguf.out
+++ b/models/ggml-vocab-command-r.gguf.out
@@ -31,6 +31,7 @@
  206 1857
  14 4515
  28339 19 1770 14 1954 8 4070 1955 1933 80503 231 5691 12081 13336 2648 29325 14315 24 26 24 27 24 28 24 5123 18372
+ 57178 10251
  26
  26 26
  26 26 26
diff --git a/models/ggml-vocab-deepseek-coder.gguf.inp b/models/ggml-vocab-deepseek-coder.gguf.inp
index 5b4aeb31ac9c6..9baf7d77ae6b5 100644
--- a/models/ggml-vocab-deepseek-coder.gguf.inp
+++ b/models/ggml-vocab-deepseek-coder.gguf.inp
@@ -73,6 +73,8 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
 __ggml_vocab_test__
+!!!!!!
+__ggml_vocab_test__
 3
 __ggml_vocab_test__
 33
diff --git a/models/ggml-vocab-deepseek-coder.gguf.out b/models/ggml-vocab-deepseek-coder.gguf.out
index a43e3f0f115d2..52c4111a18d73 100644
--- a/models/ggml-vocab-deepseek-coder.gguf.out
+++ b/models/ggml-vocab-deepseek-coder.gguf.out
@@ -31,6 +31,7 @@
  185 405
  6 2895
  17535 11 320 6 435 0 1717 417 340 12394 233 210 3015 19100 608 9413 2668 16 18 16 19 16 20 16 1393 169 121 239
+ 15330 3023
  18
  18 18
  18 18 18
diff --git a/models/ggml-vocab-deepseek-llm.gguf.inp b/models/ggml-vocab-deepseek-llm.gguf.inp
index 5b4aeb31ac9c6..9baf7d77ae6b5 100644
--- a/models/ggml-vocab-deepseek-llm.gguf.inp
+++ b/models/ggml-vocab-deepseek-llm.gguf.inp
@@ -73,6 +73,8 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
 __ggml_vocab_test__
+!!!!!!
+__ggml_vocab_test__
 3
 __ggml_vocab_test__
 33
diff --git a/models/ggml-vocab-deepseek-llm.gguf.out b/models/ggml-vocab-deepseek-llm.gguf.out
index d31ac1cc6696e..0191b7a115582 100644
--- a/models/ggml-vocab-deepseek-llm.gguf.out
+++ b/models/ggml-vocab-deepseek-llm.gguf.out
@@ -31,6 +31,7 @@
  185 403
  6 2906
  17464 11 320 6 436 0 1724 418 340 33701 210 3025 19017 612 9407 2681 16 18 16 19 16 20 16 1398 68940 239
+ 15278 3033
  18
  18 18
  18 18 18
diff --git a/models/ggml-vocab-falcon.gguf.inp b/models/ggml-vocab-falcon.gguf.inp
index 5b4aeb31ac9c6..9baf7d77ae6b5 100644
--- a/models/ggml-vocab-falcon.gguf.inp
+++ b/models/ggml-vocab-falcon.gguf.inp
@@ -73,6 +73,8 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
 __ggml_vocab_test__
+!!!!!!
+__ggml_vocab_test__
 3
 __ggml_vocab_test__
 33
diff --git a/models/ggml-vocab-falcon.gguf.out b/models/ggml-vocab-falcon.gguf.out
index 1ab70fe70ba7e..64a48d97f71f4 100644
--- a/models/ggml-vocab-falcon.gguf.out
+++ b/models/ggml-vocab-falcon.gguf.out
@@ -31,6 +31,7 @@
  1212 40
  18 4932
  9856 23 291 18 436 12 1265 362 299 8196 207 204 42 50087 123 2727 20300 32022 133 234 17419 30137 28 7858 181 133 236
+ 51520
  30
  3138
  22287
diff --git a/models/ggml-vocab-gpt-2.gguf.inp b/models/ggml-vocab-gpt-2.gguf.inp
index 5b4aeb31ac9c6..9baf7d77ae6b5 100644
--- a/models/ggml-vocab-gpt-2.gguf.inp
+++ b/models/ggml-vocab-gpt-2.gguf.inp
@@ -73,6 +73,8 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
 __ggml_vocab_test__
+!!!!!!
+__ggml_vocab_test__
 3
 __ggml_vocab_test__
 33
diff --git a/models/ggml-vocab-gpt-2.gguf.out b/models/ggml-vocab-gpt-2.gguf.out
index 88217d3fa787f..17a13bdfc3d93 100644
--- a/models/ggml-vocab-gpt-2.gguf.out
+++ b/models/ggml-vocab-gpt-2.gguf.out
@@ -31,6 +31,7 @@
  198 796
  6 6980
  15496 11 331 6 439 0 1374 389 345 30325 223 5633 22755 239 46349 111 28839 101 18040 32432 98 43291 1485 1415 24309 25465 171 121 252
+ 13896 3228
  18
  2091
  20370
diff --git a/models/ggml-vocab-llama-bpe.gguf.inp b/models/ggml-vocab-llama-bpe.gguf.inp
index 5b4aeb31ac9c6..9baf7d77ae6b5 100644
--- a/models/ggml-vocab-llama-bpe.gguf.inp
+++ b/models/ggml-vocab-llama-bpe.gguf.inp
@@ -73,6 +73,8 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
 __ggml_vocab_test__
+!!!!!!
+__ggml_vocab_test__
 3
 __ggml_vocab_test__
 33
diff --git a/models/ggml-vocab-llama-bpe.gguf.out b/models/ggml-vocab-llama-bpe.gguf.out
index bb1fe229c6071..4b35cf93f7133 100644
--- a/models/ggml-vocab-llama-bpe.gguf.out
+++ b/models/ggml-vocab-llama-bpe.gguf.out
@@ -31,6 +31,7 @@
  198 284
  6 11639
  9906 11 379 65948 0 2650 527 499 27623 223 949 37046 101067 19000 23182 102301 9263 18136 16 36827 21909
+ 17523 3001
  18
  1644
  8765
diff --git a/models/ggml-vocab-llama-spm.gguf.inp b/models/ggml-vocab-llama-spm.gguf.inp
index 5b4aeb31ac9c6..9baf7d77ae6b5 100644
--- a/models/ggml-vocab-llama-spm.gguf.inp
+++ b/models/ggml-vocab-llama-spm.gguf.inp
@@ -73,6 +73,8 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
 __ggml_vocab_test__
+!!!!!!
+__ggml_vocab_test__
 3
 __ggml_vocab_test__
 33
diff --git a/models/ggml-vocab-llama-spm.gguf.out b/models/ggml-vocab-llama-spm.gguf.out
index 1c3b0a2c979c5..93aacf8bae4bf 100644
--- a/models/ggml-vocab-llama-spm.gguf.out
+++ b/models/ggml-vocab-llama-spm.gguf.out
@@ -31,6 +31,7 @@
  29871 13 353
  525 3152
  15043 29892 343 29915 497 29991 1128 526 366 29871 243 162 155 132 1577 30672 31522 30505 11548 31041 30732 29896 29941 29896 29946 29896 29945 29896 30408 30739
+ 1738 6824 21004
  29871 29941
  29871 29941 29941
  29871 29941 29941 29941
diff --git a/models/ggml-vocab-mpt.gguf.inp b/models/ggml-vocab-mpt.gguf.inp
index 5b4aeb31ac9c6..9baf7d77ae6b5 100644
--- a/models/ggml-vocab-mpt.gguf.inp
+++ b/models/ggml-vocab-mpt.gguf.inp
@@ -73,6 +73,8 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
 __ggml_vocab_test__
+!!!!!!
+__ggml_vocab_test__
 3
 __ggml_vocab_test__
 33
diff --git a/models/ggml-vocab-mpt.gguf.out b/models/ggml-vocab-mpt.gguf.out
index d4a877d1c2641..372c751bf77da 100644
--- a/models/ggml-vocab-mpt.gguf.out
+++ b/models/ggml-vocab-mpt.gguf.out
@@ -31,6 +31,7 @@
  187 426
  8 8685
  12092 13 340 8 455 2 1359 403 368 49042 212 3736 15367 41197 13610 19934 41869 21275 1012 1047 18795 40120 20422 241
+ 18963 4672
  20
  1610
  20084
diff --git a/models/ggml-vocab-phi-3.gguf.inp b/models/ggml-vocab-phi-3.gguf.inp
index 5b4aeb31ac9c6..9baf7d77ae6b5 100644
--- a/models/ggml-vocab-phi-3.gguf.inp
+++ b/models/ggml-vocab-phi-3.gguf.inp
@@ -73,6 +73,8 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
 __ggml_vocab_test__
+!!!!!!
+__ggml_vocab_test__
 3
 __ggml_vocab_test__
 33
diff --git a/models/ggml-vocab-phi-3.gguf.out b/models/ggml-vocab-phi-3.gguf.out
index 1c3b0a2c979c5..93aacf8bae4bf 100644
--- a/models/ggml-vocab-phi-3.gguf.out
+++ b/models/ggml-vocab-phi-3.gguf.out
@@ -31,6 +31,7 @@
  29871 13 353
  525 3152
  15043 29892 343 29915 497 29991 1128 526 366 29871 243 162 155 132 1577 30672 31522 30505 11548 31041 30732 29896 29941 29896 29946 29896 29945 29896 30408 30739
+ 1738 6824 21004
  29871 29941
  29871 29941 29941
  29871 29941 29941 29941
diff --git a/models/ggml-vocab-qwen2.gguf.inp b/models/ggml-vocab-qwen2.gguf.inp
index 5b4aeb31ac9c6..9baf7d77ae6b5 100644
--- a/models/ggml-vocab-qwen2.gguf.inp
+++ b/models/ggml-vocab-qwen2.gguf.inp
@@ -73,6 +73,8 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
 __ggml_vocab_test__
+!!!!!!
+__ggml_vocab_test__
 3
 __ggml_vocab_test__
 33
diff --git a/models/ggml-vocab-qwen2.gguf.out b/models/ggml-vocab-qwen2.gguf.out
index 4ab275396631d..18b4b45cd152f 100644
--- a/models/ggml-vocab-qwen2.gguf.out
+++ b/models/ggml-vocab-qwen2.gguf.out
@@ -31,6 +31,7 @@
  198 284
  6 11385
  9707 11 379 64848 0 2585 525 498 26525 223 937 104100 18493 22377 99257 16 18 16 19 16 20 16 35727 21216
+ 17085 2928
  18
  18 18
  18 18 18
diff --git a/models/ggml-vocab-refact.gguf.inp b/models/ggml-vocab-refact.gguf.inp
index 5b4aeb31ac9c6..9baf7d77ae6b5 100644
--- a/models/ggml-vocab-refact.gguf.inp
+++ b/models/ggml-vocab-refact.gguf.inp
@@ -73,6 +73,8 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
 __ggml_vocab_test__
+!!!!!!
+__ggml_vocab_test__
 3
 __ggml_vocab_test__
 33
diff --git a/models/ggml-vocab-refact.gguf.out b/models/ggml-vocab-refact.gguf.out
index 46d8b4aec7e19..63d8305c3f1f3 100644
--- a/models/ggml-vocab-refact.gguf.out
+++ b/models/ggml-vocab-refact.gguf.out
@@ -31,6 +31,7 @@
  203 280
  25 34666
  8279 30 533 25 464 19 4971 884 844 18458 228 1018 4982 13368 2909 9513 17827 35 37 35 38 35 39 35 11873 47838
+ 9163 3202
  37
  37 37
  37 37 37
diff --git a/models/ggml-vocab-starcoder.gguf.inp b/models/ggml-vocab-starcoder.gguf.inp
index 5b4aeb31ac9c6..9baf7d77ae6b5 100644
--- a/models/ggml-vocab-starcoder.gguf.inp
+++ b/models/ggml-vocab-starcoder.gguf.inp
@@ -73,6 +73,8 @@ __ggml_vocab_test__
 __ggml_vocab_test__
 Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
 __ggml_vocab_test__
+!!!!!!
+__ggml_vocab_test__
 3
 __ggml_vocab_test__
 33
diff --git a/models/ggml-vocab-starcoder.gguf.out b/models/ggml-vocab-starcoder.gguf.out
index 9ce2698a97d7b..87e2465d363e4 100644
--- a/models/ggml-vocab-starcoder.gguf.out
+++ b/models/ggml-vocab-starcoder.gguf.out
@@ -31,6 +31,7 @@
  222 299
  44 34719
  8302 49 553 44 483 38 4998 904 863 18445 247 1037 4995 13379 2924 9515 17823 54 56 54 57 54 58 54 11904 47892
+ 9221 3226
  56
  56 56
  56 56 56
diff --git a/src/llama.cpp b/src/llama.cpp
index 3d131b325ef20..1fe2b9f79d320 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -2044,12 +2044,18 @@ enum e_model {
     MODEL_17M,
     MODEL_22M,
     MODEL_33M,
+    MODEL_60M,
     MODEL_70M,
+    MODEL_80M,
     MODEL_109M,
     MODEL_137M,
     MODEL_160M,
+    MODEL_220M,
+    MODEL_250M,
     MODEL_335M,
     MODEL_410M,
+    MODEL_770M,
+    MODEL_780M,
     MODEL_0_5B,
     MODEL_1B,
     MODEL_1_3B,
@@ -2061,6 +2067,7 @@ enum e_model {
     MODEL_6_9B,
     MODEL_7B,
     MODEL_8B,
+    MODEL_11B,
     MODEL_12B,
     MODEL_13B,
     MODEL_14B,
@@ -2112,6 +2119,7 @@ struct llama_hparams {
     uint32_t n_expert = 0;
     uint32_t n_expert_used = 0;
     uint32_t n_vocab_type = 0; // for BERT-style token types
+    uint32_t n_rel_attn_bkts = 0;
 
     uint32_t n_layer_dense_lead = 0;
     uint32_t n_lora_q = 0;
@@ -2147,6 +2155,10 @@ struct llama_hparams {
     bool use_alibi     = false;
     bool attn_soft_cap = false;
 
+    // needed by encoder-decoder models (e.g. T5, FLAN-T5)
+    // ref: https://github.com/ggerganov/llama.cpp/pull/8141
+    llama_token dec_start_token_id = -1;
+
     enum llama_pooling_type      pooling_type            = LLAMA_POOLING_TYPE_NONE;
     enum llama_rope_type         rope_type               = LLAMA_ROPE_TYPE_NONE;
     enum llama_rope_scaling_type rope_scaling_type_train = LLAMA_ROPE_SCALING_TYPE_NONE;
@@ -2167,6 +2179,7 @@ struct llama_hparams {
         if (this->n_expert      != other.n_expert)      return true;
         if (this->n_expert_used != other.n_expert_used) return true;
 
+        if (this->n_rel_attn_bkts    != other.n_rel_attn_bkts)    return true;
         if (this->n_layer_dense_lead != other.n_layer_dense_lead) return true;
         if (this->n_lora_q           != other.n_lora_q)           return true;
         if (this->n_lora_kv          != other.n_lora_kv)          return true;
@@ -2182,6 +2195,8 @@ struct llama_hparams {
         if (this->ssm_d_state != other.ssm_d_state) return true;
         if (this->ssm_dt_rank != other.ssm_dt_rank) return true;
 
+        if (this->dec_start_token_id != other.dec_start_token_id) return true;
+
         const float EPSILON = 1e-9f;
 
         if (!is_float_close(this->f_norm_eps,            other.f_norm_eps,            EPSILON)) return true;
@@ -2254,6 +2269,7 @@ struct llama_cparams {
     void * cb_eval_user_data;
 };
 
+// TODO: separate into "llama_layer_enc" and "llama_layer_dec"
 struct llama_layer {
     // normalization
     struct ggml_tensor * attn_norm;
@@ -2271,6 +2287,8 @@ struct llama_layer {
     struct ggml_tensor * attn_sub_norm;
     struct ggml_tensor * attn_post_norm;
     struct ggml_tensor * ffn_sub_norm;
+    struct ggml_tensor * attn_norm_cross;
+    struct ggml_tensor * attn_norm_enc;
 
     // attention
     struct ggml_tensor * wq;
@@ -2282,6 +2300,14 @@ struct llama_layer {
     struct ggml_tensor * wq_b;
     struct ggml_tensor * wkv_a_mqa;
     struct ggml_tensor * wkv_b;
+    struct ggml_tensor * wq_cross;
+    struct ggml_tensor * wk_cross;
+    struct ggml_tensor * wv_cross;
+    struct ggml_tensor * wo_cross;
+    struct ggml_tensor * wq_enc;
+    struct ggml_tensor * wk_enc;
+    struct ggml_tensor * wv_enc;
+    struct ggml_tensor * wo_enc;
 
     // attention bias
     struct ggml_tensor * bq;
@@ -2290,6 +2316,11 @@ struct llama_layer {
     struct ggml_tensor * bo;
     struct ggml_tensor * bqkv;
 
+    // relative position bias
+    struct ggml_tensor * attn_rel_b;
+    struct ggml_tensor * attn_rel_b_enc;
+    struct ggml_tensor * attn_rel_b_cross;
+
     // normalization
     struct ggml_tensor * ffn_norm;
     struct ggml_tensor * ffn_norm_b;
@@ -2297,11 +2328,15 @@ struct llama_layer {
     struct ggml_tensor * layer_out_norm;
     struct ggml_tensor * layer_out_norm_b;
     struct ggml_tensor * ffn_norm_exps;
+    struct ggml_tensor * ffn_norm_enc;
 
     // ff
     struct ggml_tensor * ffn_gate; // w1
     struct ggml_tensor * ffn_down; // w2
     struct ggml_tensor * ffn_up;   // w3
+    struct ggml_tensor * ffn_gate_enc;
+    struct ggml_tensor * ffn_down_enc;
+    struct ggml_tensor * ffn_up_enc;
 
     // ff MoE
     struct ggml_tensor * ffn_gate_inp;
@@ -2535,6 +2570,7 @@ struct llama_model {
     struct ggml_tensor * output_norm_b;
     struct ggml_tensor * output;
     struct ggml_tensor * output_b;
+    struct ggml_tensor * output_norm_enc;
 
     std::vector layers;
 
@@ -2663,6 +2699,13 @@ struct llama_context {
     // populated only when pooling_type != LLAMA_POOLING_TYPE_NONE
     std::map> embd_seq;
 
+    // whether we are computing encoder output or decoder output
+    bool is_encoding = false;
+
+    // output of the encoder part of the encoder-decoder models
+    std::vector embd_enc;
+    std::vector> seq_ids_enc;
+
     // memory buffers used to evaluate the model
     std::vector buf_compute_meta;
     ggml_backend_sched_t sched = nullptr;
@@ -2683,6 +2726,9 @@ struct llama_context {
     struct ggml_tensor * inp_s_copy;      // I32 [kv_size]
     struct ggml_tensor * inp_s_mask;      // F32 [1, n_kv]
     struct ggml_tensor * inp_s_seq;       // I32 [n_kv, n_batch]
+    struct ggml_tensor * inp_pos_bucket;    // I32 [n_batch|n_kv, n_batch]
+    struct ggml_tensor * inp_embd_enc;      // F32 [n_embd, n_outputs_enc]
+    struct ggml_tensor * inp_KQ_mask_cross; // F32 [n_outputs_enc, n_batch]
 
     // control vectors
     struct llama_control_vector cvec;
@@ -4286,12 +4332,18 @@ static const char * llama_model_type_name(e_model type) {
         case MODEL_17M:           return "17M";
         case MODEL_22M:           return "22M";
         case MODEL_33M:           return "33M";
+        case MODEL_60M:           return "60M";
         case MODEL_70M:           return "70M";
+        case MODEL_80M:           return "80M";
         case MODEL_109M:          return "109M";
         case MODEL_137M:          return "137M";
         case MODEL_160M:          return "160M";
+        case MODEL_220M:          return "220M";
+        case MODEL_250M:          return "250M";
         case MODEL_335M:          return "335M";
         case MODEL_410M:          return "410M";
+        case MODEL_770M:          return "770M";
+        case MODEL_780M:          return "780M";
         case MODEL_0_5B:          return "0.5B";
         case MODEL_1B:            return "1B";
         case MODEL_1_3B:          return "1.3B";
@@ -4303,6 +4355,7 @@ static const char * llama_model_type_name(e_model type) {
         case MODEL_6_9B:          return "6.9B";
         case MODEL_7B:            return "7B";
         case MODEL_8B:            return "8B";
+        case MODEL_11B:           return "11B";
         case MODEL_12B:           return "12B";
         case MODEL_13B:           return "13B";
         case MODEL_14B:           return "14B";
@@ -4917,6 +4970,38 @@ static void llm_load_hparams(
                     default: model.type = e_model::MODEL_UNKNOWN;
                 }
             } break;
+        case LLM_ARCH_T5:
+            {
+                ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
+                ml.get_key(LLM_KV_ATTENTION_RELATIVE_BUCKETS_COUNT, hparams.n_rel_attn_bkts);
+
+                uint32_t dec_start_token_id;
+                if (ml.get_key(LLM_KV_DECODER_START_TOKEN_ID, dec_start_token_id, false)) {
+                    hparams.dec_start_token_id = dec_start_token_id;
+                }
+
+                switch (hparams.n_layer) {
+                    case 6:  model.type = e_model::MODEL_60M;  break; // t5-small
+                    case 8:  model.type = e_model::MODEL_80M;  break; // flan-t5-small
+                    case 12:
+                        switch (hparams.n_ff) {
+                            case 3072: model.type = e_model::MODEL_220M; break; // t5-base
+                            case 2048: model.type = e_model::MODEL_250M; break; // flan-t5-base
+                            default: model.type = e_model::MODEL_UNKNOWN;
+                        } break;
+                    case 24:
+                        switch (hparams.n_ff) {
+                            case 4096:  model.type = e_model::MODEL_770M; break; // t5-large
+                            case 2816:  model.type = e_model::MODEL_780M; break; // flan-t5-large
+                            case 16384: model.type = e_model::MODEL_3B;   break; // t5-3b
+                            case 5120:  model.type = e_model::MODEL_3B;   break; // flan-t5-xl
+                            case 65536: model.type = e_model::MODEL_11B;  break; // t5-11b
+                            case 10240: model.type = e_model::MODEL_11B;  break; // flan-t5-xxl
+                            default: model.type = e_model::MODEL_UNKNOWN;
+                        } break;
+                    default: model.type = e_model::MODEL_UNKNOWN;
+               }
+            } break;
         case LLM_ARCH_JAIS:
             {
                 ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps);
@@ -6996,6 +7081,64 @@ static bool llm_load_tensors(
                         layer.ffn_up_scale = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP, "scale", i), {1});
                     }
                 } break;
+            case LLM_ARCH_T5:
+                {
+                    model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
+
+                    // output
+                    {
+                        model.output_norm_enc = ml.create_tensor(ctx_output, tn(LLM_TENSOR_ENC_OUTPUT_NORM, "weight"), {n_embd});
+                        model.output_norm     = ml.create_tensor(ctx_output, tn(LLM_TENSOR_DEC_OUTPUT_NORM, "weight"), {n_embd});
+
+                        model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        // if output is NULL, init from the input tok embed
+                        if (model.output == NULL) {
+                            model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED);
+                        }
+                    }
+
+                    for (int i = 0; i < n_layer; ++i) {
+                        ggml_context * ctx_layer = ctx_for_layer(i);
+                        ggml_context * ctx_split = ctx_for_layer_split(i);
+
+                        auto & layer = model.layers[i];
+
+                        layer.attn_norm_enc  = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ENC_ATTN_NORM,  "weight", i), {n_embd});
+                        layer.attn_rel_b_enc = ml.create_tensor(ctx_input, tn(LLM_TENSOR_ENC_ATTN_REL_B, "weight", i), {hparams.n_head, hparams.n_rel_attn_bkts}, llama_model_loader::TENSOR_NOT_REQUIRED);
+
+                        layer.wq_enc = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ENC_ATTN_Q,   "weight", i), {n_embd, n_embd_k_gqa});
+                        layer.wk_enc = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ENC_ATTN_K,   "weight", i), {n_embd, n_embd_k_gqa});
+                        layer.wv_enc = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ENC_ATTN_V,   "weight", i), {n_embd, n_embd_v_gqa});
+                        layer.wo_enc = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ENC_ATTN_OUT, "weight", i), {n_embd_v_gqa, n_embd});
+
+                        layer.ffn_norm_enc = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ENC_FFN_NORM, "weight", i), {n_embd});
+                        layer.ffn_gate_enc = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ENC_FFN_GATE, "weight", i), {n_embd,   n_ff}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.ffn_down_enc = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ENC_FFN_DOWN, "weight", i), {  n_ff, n_embd});
+                        layer.ffn_up_enc   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ENC_FFN_UP,   "weight", i), {n_embd,   n_ff});
+
+                        layer.attn_norm  = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_DEC_ATTN_NORM,  "weight", i), {n_embd});
+                        layer.attn_rel_b = ml.create_tensor(ctx_input, tn(LLM_TENSOR_DEC_ATTN_REL_B, "weight", i), {hparams.n_head, hparams.n_rel_attn_bkts}, llama_model_loader::TENSOR_NOT_REQUIRED);
+
+                        layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_ATTN_Q,   "weight", i), {n_embd, n_embd_k_gqa});
+                        layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_ATTN_K,   "weight", i), {n_embd, n_embd_k_gqa});
+                        layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_ATTN_V,   "weight", i), {n_embd, n_embd_v_gqa});
+                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_ATTN_OUT, "weight", i), {n_embd_v_gqa, n_embd});
+
+                        layer.attn_norm_cross  = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_DEC_CROSS_ATTN_NORM,  "weight", i), {n_embd});
+                        // this tensor seems to be unused in HF transformers implementation
+                        layer.attn_rel_b_cross = ml.create_tensor(ctx_input, tn(LLM_TENSOR_DEC_CROSS_ATTN_REL_B, "weight", i), {hparams.n_head, hparams.n_rel_attn_bkts}, llama_model_loader::TENSOR_NOT_REQUIRED);
+
+                        layer.wq_cross = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_CROSS_ATTN_Q,   "weight", i), {n_embd, n_embd_k_gqa});
+                        layer.wk_cross = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_CROSS_ATTN_K,   "weight", i), {n_embd, n_embd_k_gqa});
+                        layer.wv_cross = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_CROSS_ATTN_V,   "weight", i), {n_embd, n_embd_v_gqa});
+                        layer.wo_cross = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_CROSS_ATTN_OUT, "weight", i), {n_embd_v_gqa, n_embd});
+
+                        layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_DEC_FFN_NORM, "weight", i), {n_embd});
+                        layer.ffn_gate = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_DEC_FFN_GATE, "weight", i), {n_embd,   n_ff}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_FFN_DOWN, "weight", i), {  n_ff, n_embd});
+                        layer.ffn_up   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_FFN_UP,   "weight", i), {n_embd,   n_ff});
+                    }
+                } break;
             case LLM_ARCH_JAIS:
                 {
                     model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
@@ -7787,6 +7930,7 @@ struct llm_build_context {
     const int32_t n_tokens;
     const int32_t n_kv;     // size of KV cache to consider (n_kv <= kv_self.size)
     const int32_t n_outputs;
+    const int32_t n_outputs_enc;
     const int32_t kv_head;  // index of where we store new KV data in the cache
     const int32_t n_ctx_orig;
 
@@ -7836,6 +7980,7 @@ struct llm_build_context {
         n_tokens         (batch.n_tokens),
         n_kv             (worst_case ? kv_self.size : kv_self.n),
         n_outputs        (worst_case ? n_tokens : lctx.n_outputs),
+        n_outputs_enc    (worst_case ? n_tokens : lctx.embd_enc.size() / hparams.n_embd),
         kv_head          (worst_case ? (kv_self.recurrent ? 0 : kv_self.size - n_tokens) : kv_self.head),
         n_ctx_orig       (cparams.n_ctx_orig_yarn),
         flash_attn       (cparams.flash_attn),
@@ -7867,6 +8012,9 @@ struct llm_build_context {
         lctx.inp_s_copy      = nullptr;
         lctx.inp_s_mask      = nullptr;
         lctx.inp_s_seq       = nullptr;
+        lctx.inp_pos_bucket    = nullptr;
+        lctx.inp_embd_enc      = nullptr;
+        lctx.inp_KQ_mask_cross = nullptr;
     }
 
     void free() {
@@ -8119,6 +8267,53 @@ struct llm_build_context {
         return gf;
     }
 
+    struct ggml_tensor * llm_build_pos_bucket(bool causal) {
+        if (causal) {
+            lctx.inp_pos_bucket = ggml_new_tensor_2d(ctx0, GGML_TYPE_I32, n_kv,     n_tokens);
+        } else {
+            lctx.inp_pos_bucket = ggml_new_tensor_2d(ctx0, GGML_TYPE_I32, n_tokens, n_tokens);
+        }
+
+        ggml_set_input(lctx.inp_pos_bucket);
+        cb(lctx.inp_pos_bucket, "pos_bucket", -1);
+
+        return lctx.inp_pos_bucket;
+    }
+
+    struct ggml_tensor * llm_build_pos_bias(struct ggml_tensor * pos_bucket, struct ggml_tensor * attn_rel_b) {
+        struct ggml_tensor * pos_bucket_1d = ggml_view_1d(ctx0, pos_bucket, pos_bucket->ne[0] * pos_bucket->ne[1], 0);
+        cb(pos_bucket_1d, "pos_bucket_1d", -1);
+
+        struct ggml_tensor * pos_bias = ggml_get_rows(ctx0, attn_rel_b, pos_bucket_1d);
+        cb(pos_bias, "pos_bias", -1);
+
+        pos_bias = ggml_view_3d(ctx0, pos_bias, pos_bias->ne[0], lctx.inp_pos_bucket->ne[0], lctx.inp_pos_bucket->ne[1], ggml_element_size(pos_bias) * pos_bias->ne[0], ggml_element_size(pos_bias) * pos_bias->ne[0] * lctx.inp_pos_bucket->ne[0],  0);
+        cb(pos_bias, "pos_bias", -1);
+
+        pos_bias = ggml_permute(ctx0, pos_bias, 2, 0, 1, 3);
+        cb(pos_bias, "pos_bias", -1);
+
+        pos_bias = ggml_cont(ctx0, pos_bias);
+        cb(pos_bias, "pos_bias", -1);
+
+        return pos_bias;
+    }
+
+    struct ggml_tensor * llm_build_inp_embd_enc() {
+        const int64_t n_embd = hparams.n_embd;
+        lctx.inp_embd_enc = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_embd, n_outputs_enc);
+        ggml_set_input(lctx.inp_embd_enc);
+        cb(lctx.inp_embd_enc, "embd_enc", -1);
+        return lctx.inp_embd_enc;
+    }
+
+    struct ggml_tensor * llm_build_inp_KQ_mask_cross() {
+        lctx.inp_KQ_mask_cross = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_outputs_enc, GGML_PAD(n_tokens, GGML_KQ_MASK_PAD));
+        ggml_set_input(lctx.inp_KQ_mask_cross);
+        cb(lctx.inp_KQ_mask_cross, "KQ_mask_cross", -1);
+        return lctx.inp_KQ_mask_cross;
+    }
+
     struct ggml_cgraph * build_llama() {
         struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
 
@@ -12426,6 +12621,321 @@ struct llm_build_context {
         return gf;
     }
 
+    struct ggml_cgraph * build_t5() {
+        struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
+
+        // mutable variable, needed during the last layer of the computation to skip unused tokens
+        int32_t n_tokens = this->n_tokens;
+
+        const int64_t n_embd_head = hparams.n_embd_head_v;
+        const int64_t n_embd_gqa  = hparams.n_embd_v_gqa();
+        GGML_ASSERT(n_embd_head == hparams.n_embd_head_k);
+
+        struct ggml_tensor * cur;
+        struct ggml_tensor * inpL;
+
+        inpL = llm_build_inp_embd(ctx0, lctx, hparams, batch, model.tok_embd, cb);
+
+        if (lctx.is_encoding) {
+            struct ggml_tensor * pos_bucket_enc = llm_build_pos_bucket(false);
+
+            // KQ_mask (mask for 1 head, it will be broadcasted to all heads)
+            struct ggml_tensor * KQ_mask_enc = build_inp_KQ_mask(false);
+
+            for (int il = 0; il < n_layer; ++il) {
+                struct ggml_tensor * inpSA = inpL;
+
+                // norm
+                cur = llm_build_norm(ctx0, inpL, hparams,
+                        model.layers[il].attn_norm_enc, NULL,
+                        LLM_NORM_RMS, cb, il);
+                cb(cur, "attn_norm", il);
+
+                // self-attention
+                {
+                    struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq_enc, cur);
+                    cb(Qcur, "Qcur", il);
+
+                    struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk_enc, cur);
+                    cb(Kcur, "Kcur", il);
+
+                    struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv_enc, cur);
+                    cb(Vcur, "Vcur", il);
+
+                    Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens);
+                    Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens);
+
+                    struct ggml_tensor * q =                 ggml_permute(ctx0, Qcur, 0, 2, 1, 3);
+                    struct ggml_tensor * k = ggml_cont(ctx0, ggml_permute(ctx0, Kcur, 0, 2, 1, 3));
+
+                    struct ggml_tensor * kq = ggml_mul_mat(ctx0, k, q);
+                    cb(kq, "kq", il);
+
+                    struct ggml_tensor * attn_rel_b = model.layers[il].attn_rel_b_enc ? model.layers[il].attn_rel_b_enc : model.layers[0].attn_rel_b_enc;
+                    struct ggml_tensor * pos_bias = llm_build_pos_bias(pos_bucket_enc, attn_rel_b);
+                    struct ggml_tensor * kq_b = ggml_add(ctx0, kq, pos_bias);
+                    cb(kq_b, "kq_b", il);
+
+                    kq = ggml_soft_max_ext(ctx0, kq_b, KQ_mask_enc, 1.0f, hparams.f_max_alibi_bias);
+                    cb(kq, "kq_soft_max_ext", il);
+
+                    struct ggml_tensor * v = ggml_cont(ctx0, ggml_transpose(ctx0, ggml_reshape_2d(ctx0, Vcur, n_embd_gqa, n_tokens)));
+                    cb(v, "v", il);
+
+                    struct ggml_tensor * kqv = ggml_mul_mat(ctx0, ggml_reshape_3d(ctx0, v, n_tokens, n_embd_head, n_head_kv), kq);
+                    cb(kqv, "kqv", il);
+
+                    struct ggml_tensor * kqv_merged = ggml_permute(ctx0, kqv, 0, 2, 1, 3);
+                    cb(kqv_merged, "kqv_merged", il);
+
+                    cur = ggml_cont_2d(ctx0, kqv_merged, n_embd_gqa, n_tokens);
+                    cb(cur, "kqv_merged_cont", il);
+
+                    ggml_build_forward_expand(gf, cur);
+
+                    cur = ggml_mul_mat(ctx0, model.layers[il].wo_enc, cur);
+                    cb(cur, "kqv_out", il);
+                }
+
+                if (il == n_layer - 1) {
+                    // skip computing output for unused tokens
+                    struct ggml_tensor * inp_out_ids = build_inp_out_ids();
+                    n_tokens = n_outputs;
+                    cur   = ggml_get_rows(ctx0,   cur, inp_out_ids);
+                    inpSA = ggml_get_rows(ctx0, inpSA, inp_out_ids);
+                }
+
+                struct ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpSA);
+                cb(ffn_inp, "ffn_inp", il);
+
+                // feed-forward network
+                {
+                    cur = llm_build_norm(ctx0, ffn_inp, hparams,
+                            model.layers[il].ffn_norm_enc, NULL,
+                            LLM_NORM_RMS, cb, il);
+                    cb(cur, "ffn_norm", il);
+
+                    // T5 uses relu, flan-T5 uses gelu-gated
+                    cur = llm_build_ffn(ctx0, cur,
+                            model.layers[il].ffn_up_enc,   NULL, NULL,
+                            model.layers[il].ffn_gate_enc, NULL, NULL,
+                            model.layers[il].ffn_down_enc, NULL, NULL,
+                            NULL,
+                            model.layers[il].ffn_gate_enc ? LLM_FFN_GELU : LLM_FFN_RELU,
+                            model.layers[il].ffn_gate_enc ? LLM_FFN_PAR  : LLM_FFN_SEQ,
+                            cb, il);
+                    cb(cur, "ffn_out", il);
+                }
+
+                cur = ggml_add(ctx0, cur, ffn_inp);
+                cb(cur, "ffn_out", il);
+
+                ggml_tensor * layer_dir = lctx.cvec.tensor_for(il);
+                if (layer_dir != nullptr) {
+                    cur = ggml_add(ctx0, cur, layer_dir);
+                }
+                cb(cur, "l_out", il);
+
+                // input for next layer
+                inpL = cur;
+            }
+
+            cur = inpL;
+            cb(cur, "result_embd", -1);
+
+            cur = llm_build_norm(ctx0, cur, hparams,
+                    model.output_norm_enc, NULL,
+                    LLM_NORM_RMS, cb, -1);
+            cb(cur, "result_norm", -1);
+        } else {
+            struct ggml_tensor * embd_enc       = llm_build_inp_embd_enc();
+            struct ggml_tensor * pos_bucket_dec = llm_build_pos_bucket(true);
+
+            struct ggml_tensor * KQ_mask_dec   = build_inp_KQ_mask();
+            struct ggml_tensor * KQ_mask_cross = llm_build_inp_KQ_mask_cross();
+
+            for (int il = 0; il < n_layer; ++il) {
+                struct ggml_tensor * inpSA = inpL;
+
+                // norm
+                cur = llm_build_norm(ctx0, inpL, hparams,
+                        model.layers[il].attn_norm, NULL,
+                        LLM_NORM_RMS, cb, il);
+                cb(cur, "attn_norm", il);
+
+                // self-attention
+                {
+                    struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                    cb(Qcur, "Qcur", il);
+
+                    struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                    cb(Kcur, "Kcur", il);
+
+                    struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                    cb(Vcur, "Vcur", il);
+
+                    llm_build_kv_store(ctx0, hparams, cparams, kv_self, gf, Kcur, Vcur, n_tokens, kv_head, cb, il);
+
+                    struct ggml_tensor * k =
+                        ggml_view_3d(ctx0, kv_self.k_l[il],
+                                n_embd_head_k, n_kv, n_head_kv,
+                                ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa),
+                                ggml_row_size(kv_self.k_l[il]->type, n_embd_head_k),
+                                0);
+                    cb(k, "k", il);
+
+                    struct ggml_tensor * v =
+                        ggml_view_3d(ctx0, kv_self.v_l[il],
+                                n_kv, n_embd_head_v, n_head_kv,
+                                ggml_element_size(kv_self.v_l[il])*n_ctx,
+                                ggml_element_size(kv_self.v_l[il])*n_ctx*n_embd_head_v,
+                                0);
+                    cb(v, "v", il);
+
+                    Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens);
+
+                    struct ggml_tensor * q = ggml_permute(ctx0, Qcur, 0, 2, 1, 3);
+
+                    struct ggml_tensor * kq = ggml_mul_mat(ctx0, k, q);
+                    cb(kq, "kq", il);
+
+                    struct ggml_tensor * attn_rel_b = model.layers[il].attn_rel_b ? model.layers[il].attn_rel_b : model.layers[0].attn_rel_b;
+                    struct ggml_tensor * pos_bias = llm_build_pos_bias(pos_bucket_dec, attn_rel_b);
+                    struct ggml_tensor * kq_b = ggml_add(ctx0, kq, pos_bias);
+                    cb(kq_b, "kq_b", il);
+
+                    kq = ggml_soft_max_ext(ctx0, kq_b, KQ_mask_dec, 1.0f, hparams.f_max_alibi_bias);
+                    cb(kq, "kq_soft_max_ext", il);
+
+                    struct ggml_tensor * kqv = ggml_mul_mat(ctx0, v, kq);
+                    cb(kqv, "kqv", il);
+
+                    struct ggml_tensor * kqv_merged = ggml_permute(ctx0, kqv, 0, 2, 1, 3);
+                    cb(kqv_merged, "kqv_merged", il);
+
+                    cur = ggml_cont_2d(ctx0, kqv_merged, n_embd_gqa, n_tokens);
+                    cb(cur, "kqv_merged_cont", il);
+
+                    ggml_build_forward_expand(gf, cur);
+
+                    cur = ggml_mul_mat(ctx0, model.layers[il].wo, cur);
+                    cb(cur, "kqv_out", il);
+                }
+
+                cur = ggml_add(ctx0, cur, inpSA);
+                cb(cur, "cross_inp", il);
+
+                struct ggml_tensor * inpCA = cur;
+
+                // norm
+                cur = llm_build_norm(ctx0, cur, hparams,
+                        model.layers[il].attn_norm_cross, NULL,
+                        LLM_NORM_RMS, cb, il);
+                cb(cur, "attn_norm_cross", il);
+
+                // cross-attention
+                {
+                    struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq_cross, cur);
+                    cb(Qcur, "Qcur", il);
+
+                    struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk_cross, embd_enc);
+                    cb(Kcur, "Kcur", il);
+
+                    struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv_cross, embd_enc);
+                    cb(Vcur, "Vcur", il);
+
+                    Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head,    n_tokens);
+                    Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_outputs_enc);
+
+                    struct ggml_tensor * q =                 ggml_permute(ctx0, Qcur, 0, 2, 1, 3);
+                    struct ggml_tensor * k = ggml_cont(ctx0, ggml_permute(ctx0, Kcur, 0, 2, 1, 3));
+
+                    struct ggml_tensor * kq = ggml_mul_mat(ctx0, k, q);
+                    cb(kq, "kq", il);
+
+                    kq = ggml_soft_max_ext(ctx0, kq, KQ_mask_cross, 1.0f, hparams.f_max_alibi_bias);
+                    cb(kq, "kq_soft_max_ext", il);
+
+                    struct ggml_tensor * v = ggml_cont(ctx0, ggml_transpose(ctx0, ggml_reshape_2d(ctx0, Vcur, n_embd_gqa, n_outputs_enc)));
+                    cb(v, "v", il);
+
+                    struct ggml_tensor * kqv = ggml_mul_mat(ctx0, ggml_reshape_3d(ctx0, v, n_outputs_enc, n_embd_head, n_head_kv), kq);
+                    cb(kqv, "kqv", il);
+
+                    struct ggml_tensor * kqv_merged = ggml_permute(ctx0, kqv, 0, 2, 1, 3);
+                    cb(kqv_merged, "kqv_merged", il);
+
+                    cur = ggml_cont_2d(ctx0, kqv_merged, n_embd_gqa, n_tokens);
+                    cb(cur, "kqv_merged_cont", il);
+
+                    ggml_build_forward_expand(gf, cur);
+
+                    cur = ggml_mul_mat(ctx0, model.layers[il].wo_cross, cur);
+                    cb(cur, "kqv_out", il);
+                }
+
+                if (il == n_layer - 1) {
+                    // skip computing output for unused tokens
+                    struct ggml_tensor * inp_out_ids = build_inp_out_ids();
+                    n_tokens = n_outputs;
+                    cur   = ggml_get_rows(ctx0,   cur, inp_out_ids);
+                    inpSA = ggml_get_rows(ctx0, inpSA, inp_out_ids);
+                    inpCA = ggml_get_rows(ctx0, inpCA, inp_out_ids);
+                }
+
+                struct ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpCA);
+                cb(ffn_inp, "ffn_inp", il);
+
+                // feed-forward network
+                {
+                    cur = llm_build_norm(ctx0, ffn_inp, hparams,
+                            model.layers[il].ffn_norm, NULL,
+                            LLM_NORM_RMS, cb, il);
+                    cb(cur, "ffn_norm", il);
+
+                    // T5 uses relu, flan-T5 uses gelu-gated
+                    cur = llm_build_ffn(ctx0, cur,
+                            model.layers[il].ffn_up,   NULL, NULL,
+                            model.layers[il].ffn_gate, NULL, NULL,
+                            model.layers[il].ffn_down, NULL, NULL,
+                            NULL,
+                            model.layers[il].ffn_gate_enc ? LLM_FFN_GELU : LLM_FFN_RELU,
+                            model.layers[il].ffn_gate_enc ? LLM_FFN_PAR : LLM_FFN_SEQ,
+                            cb, il);
+                    cb(cur, "ffn_out", il);
+                }
+
+                cur = ggml_add(ctx0, cur, ffn_inp);
+                cb(cur, "ffn_out", il);
+
+                ggml_tensor * layer_dir = lctx.cvec.tensor_for(il);
+                if (layer_dir != nullptr) {
+                    cur = ggml_add(ctx0, cur, layer_dir);
+                }
+                cb(cur, "l_out", il);
+
+                // input for next layer
+                inpL = cur;
+            }
+
+            cur = inpL;
+            cb(cur, "result_embd", -1);
+
+            cur = llm_build_norm(ctx0, cur, hparams,
+                    model.output_norm, NULL,
+                    LLM_NORM_RMS, cb, -1);
+            cb(cur, "result_norm", -1);
+
+            // lm_head
+            cur = ggml_mul_mat(ctx0, model.output, cur);
+            cb(cur, "result_output", -1);
+        }
+
+        ggml_build_forward_expand(gf, cur);
+
+        return gf;
+    }
+
     struct ggml_cgraph * build_jais() {
         struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
 
@@ -12748,6 +13258,10 @@ static struct ggml_cgraph * llama_build_graph(
             {
                 result = llm.build_bitnet();
             } break;
+        case LLM_ARCH_T5:
+            {
+                result = llm.build_t5();
+            } break;
         case LLM_ARCH_JAIS:
             {
                 result = llm.build_jais();
@@ -12790,6 +13304,30 @@ static void llama_set_s_copy(llama_context & lctx) {
     }
 }
 
+static int32_t llama_relative_position_bucket(llama_pos x, llama_pos y, uint64_t n_buckets, bool bidirectional) {
+    // TODO move to hparams if a T5 variant appears that uses a different value
+    const int64_t max_distance = 128;
+
+    if (bidirectional) {
+        n_buckets >>= 1;
+    }
+
+    const int64_t max_exact = n_buckets >> 1;
+
+    int32_t relative_position = x - y;
+    int32_t relative_bucket = 0;
+    if (bidirectional) {
+        relative_bucket += (relative_position > 0) * n_buckets;
+        relative_position = abs(relative_position);
+    } else {
+        relative_position = -std::min(relative_position, 0);
+    }
+    int32_t relative_position_if_large = floorf(max_exact + logf(1.0 * relative_position / max_exact) * (n_buckets - max_exact) / log(1.0 * max_distance / max_exact));
+    relative_position_if_large = std::min(relative_position_if_large, n_buckets - 1);
+    relative_bucket += (relative_position < max_exact ? relative_position : relative_position_if_large);
+    return relative_bucket;
+}
+
 static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
     //
     // set input data
@@ -12855,7 +13393,7 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
 
     if (lctx.inp_KQ_mask) {
         // NOTE: hparams.causal_attn indicates the model is capable of generation and uses the kv cache.
-        if (cparams.causal_attn) {
+        if (cparams.causal_attn && !lctx.is_encoding) {
             const int64_t n_kv     = kv_self.n;
             const int64_t n_tokens = batch.n_tokens;
 
@@ -12908,7 +13446,7 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
         } else {
             // when using kv cache, the mask needs to match the kv cache size
             const int64_t n_tokens = batch.n_tokens;
-            const int64_t n_stride = hparams.causal_attn ? kv_self.n : n_tokens;
+            const int64_t n_stride = hparams.causal_attn && !lctx.is_encoding ? kv_self.n : n_tokens;
 
             GGML_ASSERT(ggml_backend_buffer_is_host(lctx.inp_KQ_mask->buffer));
 
@@ -13072,6 +13610,70 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
             }
         }
     }
+
+    if (lctx.inp_pos_bucket) {
+        const int64_t n_tokens = batch.n_tokens;
+
+        GGML_ASSERT(ggml_backend_buffer_is_host(lctx.inp_pos_bucket->buffer));
+
+        int32_t * data = (int32_t *) lctx.inp_pos_bucket->data;
+
+        if (!lctx.is_encoding) {
+            const int64_t n_kv = kv_self.n;
+            for (int h = 0; h < 1; ++h) {
+                for (int j = 0; j < n_tokens; ++j) {
+                    for (int i = 0; i < n_kv; ++i) {
+                        data[h*(n_kv*n_tokens) + j*n_kv + i] = llama_relative_position_bucket(lctx.kv_self.cells[i].pos, batch.pos[j], hparams.n_rel_attn_bkts, lctx.is_encoding);
+                    }
+                }
+            }
+        } else {
+            for (int h = 0; h < 1; ++h) {
+                for (int j = 0; j < n_tokens; ++j) {
+                    for (int i = 0; i < n_tokens; ++i) {
+                        data[h*(n_tokens*n_tokens) + j*n_tokens + i] = llama_relative_position_bucket(batch.pos[i], batch.pos[j], hparams.n_rel_attn_bkts, lctx.is_encoding);
+                    }
+                }
+            }
+        }
+    }
+
+    if (!lctx.is_encoding && lctx.inp_embd_enc) {
+        assert(lctx.inp_embd_enc->type == GGML_TYPE_F32);
+        assert((size_t) ggml_nelements(lctx.inp_embd_enc) == lctx.embd_enc.size());
+
+        ggml_backend_tensor_set(lctx.inp_embd_enc, lctx.embd_enc.data(), 0, ggml_nbytes(lctx.inp_embd_enc));
+    }
+
+    if (!lctx.is_encoding && lctx.inp_KQ_mask_cross) {
+        const int64_t n_output_enc = lctx.embd_enc.size() / hparams.n_embd;
+        const int64_t n_tokens = batch.n_tokens;
+
+        GGML_ASSERT(ggml_backend_buffer_is_host(lctx.inp_KQ_mask_cross->buffer));
+
+        float * data = (float *) lctx.inp_KQ_mask_cross->data;
+
+        for (int h = 0; h < 1; ++h) {
+            for (int j = 0; j < n_tokens; ++j) {
+                for (int i = 0; i < n_output_enc; ++i) {
+                    float f = -INFINITY;
+                    for (int s = 0; s < batch.n_seq_id[j]; ++s) {
+                        const llama_seq_id seq_id = batch.seq_id[j][s];
+                        if (lctx.seq_ids_enc[i].find(seq_id) != lctx.seq_ids_enc[i].end()) {
+                            f = 0.0f;
+                        }
+                    }
+                    data[h*(n_output_enc*n_tokens) + j*n_output_enc + i] = f;
+                }
+            }
+
+            for (int i = n_tokens; i < GGML_PAD(n_tokens, GGML_KQ_MASK_PAD); ++i) {
+                for (int j = 0; j < n_output_enc; ++j) {
+                    data[h*(n_output_enc*n_tokens) + i*n_output_enc + j] = -INFINITY;
+                }
+            }
+        }
+    }
 }
 
 // Make sure enough space is available for outputs.
@@ -13088,7 +13690,7 @@ static size_t llama_output_reserve(llama_context & lctx, size_t n_outputs) {
 
     // TODO: use a per-batch flag for logits presence instead
     const bool has_logits = !cparams.embeddings;
-    const bool has_embd   =  cparams.embeddings && (cparams.pooling_type == LLAMA_POOLING_TYPE_NONE);
+    const bool has_embd   =  lctx.is_encoding || (cparams.embeddings && (cparams.pooling_type == LLAMA_POOLING_TYPE_NONE));
 
     const size_t logits_size = has_logits ? n_vocab*n_outputs_max : 0;
     const size_t embd_size   = has_embd   ?  n_embd*n_outputs_max : 0;
@@ -13180,6 +13782,7 @@ static int llama_decode_internal(
          llama_context & lctx,
            llama_batch   batch_all) { // TODO: rename back to batch
 
+    lctx.is_encoding = false;
     const uint32_t n_tokens_all = batch_all.n_tokens;
 
     if (n_tokens_all == 0) {
@@ -13212,6 +13815,7 @@ static int llama_decode_internal(
 
     const auto n_ubatch = cparams.n_ubatch;
 
+    // TODO: simplify or deprecate
     std::vector pos;
     std::vector                   n_seq_id;
     std::vector            seq_id_arr;
@@ -13475,6 +14079,138 @@ static int llama_decode_internal(
     return 0;
 }
 
+// encode a batch of tokens by evaluating the encoder part of the transformer
+//
+//   - lctx:      llama context
+//   - batch:     batch to evaluate
+//
+// return 0 on success
+// return positive int on warning
+// return negative int on error
+//
+static int llama_encode_internal(
+         llama_context & lctx,
+           llama_batch   batch) {
+
+    lctx.is_encoding = true;
+
+    const uint32_t n_tokens = batch.n_tokens;
+
+    if (n_tokens == 0) {
+        LLAMA_LOG_ERROR("%s: n_tokens == 0", __func__);
+        return -1;
+    }
+
+    const auto & model   = lctx.model;
+    const auto & hparams = model.hparams;
+    const auto & cparams = lctx.cparams;
+
+    GGML_ASSERT((!batch.token && batch.embd) || (batch.token && !batch.embd)); // NOLINT
+
+    // micro-batching is not possible for non-causal encoding, so we process the batch in a single shot
+    GGML_ASSERT(cparams.n_ubatch >= n_tokens && "encoder requires n_ubatch >= n_tokens");
+
+    if (lctx.t_compute_start_us == 0) {
+        lctx.t_compute_start_us = ggml_time_us();
+    }
+
+    lctx.n_queued_tokens += n_tokens;
+
+    const int64_t n_embd = hparams.n_embd;
+
+    // TODO: simplify or deprecate
+    std::vector pos;
+    std::vector                   n_seq_id;
+    std::vector            seq_id_arr;
+    std::vector> seq_id;
+
+    // reserve output buffer
+    if (llama_output_reserve(lctx, n_tokens) < n_tokens) {
+        LLAMA_LOG_ERROR("%s: could not reserve space for batch with %u outputs\n", __func__, n_tokens);
+        return -2;
+    };
+
+    for (uint32_t i = 0; i < n_tokens; ++i) {
+        lctx.output_ids[i] = i;
+    }
+
+    lctx.inp_embd_enc = NULL;
+    lctx.n_outputs = n_tokens;
+
+    const int n_threads = n_tokens == 1 ? cparams.n_threads : cparams.n_threads_batch;
+    GGML_ASSERT(n_threads > 0);
+
+    // helpers for smoother batch API transition
+    // after deprecating the llama_eval calls, these will be removed
+    if (batch.pos == nullptr) {
+        pos.resize(n_tokens);
+        for (uint32_t i = 0; i < n_tokens; i++) {
+            pos[i] = batch.all_pos_0 + i*batch.all_pos_1;
+        }
+
+        batch.pos = pos.data();
+    }
+
+    if (batch.seq_id == nullptr) {
+        n_seq_id.resize(n_tokens);
+        seq_id.resize(n_tokens);
+        seq_id_arr.resize(n_tokens);
+        for (uint32_t i = 0; i < n_tokens; i++) {
+            n_seq_id[i] = 1;
+            seq_id[i].resize(1);
+            seq_id[i][0] = batch.all_seq_id;
+            seq_id_arr[i] = seq_id[i].data();
+        }
+
+        batch.n_seq_id = n_seq_id.data();
+        batch.seq_id = seq_id_arr.data();
+    }
+
+    ggml_backend_sched_reset(lctx.sched);
+    ggml_backend_sched_set_eval_callback(lctx.sched, lctx.cparams.cb_eval, lctx.cparams.cb_eval_user_data);
+
+    ggml_cgraph * gf = llama_build_graph(lctx, batch, false);
+
+    // the output embeddings after the final encoder normalization
+    struct ggml_tensor * embd = gf->nodes[gf->n_nodes - 1];
+
+    GGML_ASSERT(strcmp(embd->name, "result_norm") == 0);
+
+    ggml_backend_sched_alloc_graph(lctx.sched, gf);
+
+    llama_set_inputs(lctx, batch);
+
+    llama_graph_compute(lctx, gf, n_threads);
+
+    // extract embeddings
+    if (embd) {
+        ggml_backend_t backend_embd = ggml_backend_sched_get_tensor_backend(lctx.sched, embd);
+        GGML_ASSERT(backend_embd != nullptr);
+
+        // extract token embeddings
+        GGML_ASSERT(lctx.embd != nullptr);
+
+        lctx.embd_enc.resize(n_tokens*n_embd);
+        float * embd_out = lctx.embd_enc.data();
+
+        ggml_backend_tensor_get_async(backend_embd, embd, embd_out, 0, n_tokens*n_embd*sizeof(float));
+
+        // remember the sequence ids used during the encoding - needed for cross attention later
+        lctx.seq_ids_enc.resize(n_tokens);
+        for (uint32_t i = 0; i < n_tokens; i++) {
+            for (int s = 0; s < batch.n_seq_id[i]; s++) {
+                llama_seq_id seq_id = batch.seq_id[i][s];
+                lctx.seq_ids_enc[i].insert(seq_id);
+            }
+        }
+    }
+
+    // Reset state for the next token before backend sync, to allow the CPU activities in the reset to
+    // overlap with device computation.
+    ggml_backend_sched_reset(lctx.sched);
+
+    return 0;
+}
 
 // find holes from the beginning of the KV cache and fill them by moving data from the end of the cache
 static void llama_kv_cache_defrag_internal(struct llama_context & lctx) {
@@ -14547,11 +15283,14 @@ struct llm_tokenizer_ugm {
         std::string normalized;
         normalize(text, &normalized);
         size_t input_len = normalized.size();
+        if (input_len == 0) {
+            return;
+        }
 
         // initialize score_sum to -FLT_MAX so it will be always lower than sums of token scores
-        std::vector tokenization_results(input_len + 1, {0, 0, -FLT_MAX});
+        std::vector tokenization_results(input_len + 1, {vocab.special_unk_id, 0, -FLT_MAX});
         // at the beginning tokenization score is zero
-        tokenization_results[0] = { 0, 0, 0 };
+        tokenization_results[0] = { vocab.special_unk_id, 0, 0 };
 
         for (size_t input_offset = 0; input_offset < input_len;) {
             size_t prefix_offset = input_offset;
@@ -14571,7 +15310,7 @@ struct llm_tokenizer_ugm {
                         single_codepoint_token_found = true;
                     }
                     llama_token token_id = node->value;
-                    const auto &token_data = vocab.id_to_token[token_id];
+                    const auto & token_data = vocab.id_to_token[token_id];
 
                     // we set the user-defined token scores to 0 to make them more likely to be selected
                     // (normal token scores are log probabilities, so they are negative)
@@ -16854,10 +17593,11 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
 
     // sanity checks
     //
-    //  - qs.n_attention_wv == 0                     for Mamba       models
-    //  - qs.n_attention_wv == model.hparams.n_layer for Transformer models
+    //  - qs.n_attention_wv == 0                         for Mamba           models
+    //  - qs.n_attention_wv == model.hparams.n_layer     for Transformer     models
+    //  - qs.n_attention_wv == 3 * model.hparams.n_layer for Encoder-Decoder models
     //
-    GGML_ASSERT((qs.n_attention_wv == 0 || qs.n_attention_wv == (int)model.hparams.n_layer) && "n_attention_wv is unexpected");
+    GGML_ASSERT((qs.n_attention_wv == 0 || qs.n_attention_wv == (int)model.hparams.n_layer || qs.n_attention_wv == 3 * (int)model.hparams.n_layer) && "n_attention_wv is unexpected");
 
     size_t total_size_org = 0;
     size_t total_size_new = 0;
@@ -16982,6 +17722,9 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
         quantize &= name.find("ssm_x.weight")      == std::string::npos;
         quantize &= name.find("ssm_dt.weight")     == std::string::npos;
 
+        // do not quantize relative position bias (T5)
+        quantize &= name.find("attn_rel_b.weight") == std::string::npos;
+
         enum ggml_type new_type;
         void * new_data;
         size_t new_size;
@@ -18138,6 +18881,17 @@ struct ggml_tensor * llama_get_model_tensor(struct llama_model * model, const ch
     return it->second;
 }
 
+bool llama_model_has_encoder(const struct llama_model * model) {
+    switch (model->arch) {
+        case LLM_ARCH_T5: return true;
+        default:          return false;
+    }
+}
+
+llama_token llama_model_decoder_start_token(const struct llama_model * model) {
+    return model->hparams.dec_start_token_id;
+}
+
 uint32_t llama_model_quantize(
         const char * fname_inp,
         const char * fname_out,
@@ -19484,6 +20238,17 @@ void llama_batch_free(struct llama_batch batch) {
     if (batch.logits)   free(batch.logits);
 }
 
+int32_t llama_encode(
+        struct llama_context * ctx,
+          struct llama_batch   batch) {
+    const int ret = llama_encode_internal(*ctx, batch);
+    if (ret < 0) {
+        LLAMA_LOG_ERROR("%s: failed to encode, ret = %d\n", __func__, ret);
+    }
+
+    return ret;
+}
+
 int32_t llama_decode(
         struct llama_context * ctx,
           struct llama_batch   batch) {

From b0a46993dfbf8b8127598f319d4dcfdd83824ba8 Mon Sep 17 00:00:00 2001
From: ditsuke 
Date: Tue, 27 Feb 2024 12:01:02 +0530
Subject: [PATCH 087/326] build(python): Package scripts with pip-0517
 compliance

---
 .gitignore                                    |   11 +-
 __init__.py                                   |    0
 ...ert-hf-to-gguf.py => convert_hf_to_gguf.py |    0
 ...-update.py => convert_hf_to_gguf_update.py |   20 +-
 ...o-gguf.py => convert_llama_ggml_to_gguf.py |    0
 convert_lora_to_ggml.py                       |  149 ++
 convert_persimmon_to_gguf.py                  |  137 ++
 poetry.lock                                   | 1197 +++++++++++++++++
 pyproject.toml                                |   44 +
 9 files changed, 1546 insertions(+), 12 deletions(-)
 create mode 100644 __init__.py
 rename convert-hf-to-gguf.py => convert_hf_to_gguf.py (100%)
 rename convert-hf-to-gguf-update.py => convert_hf_to_gguf_update.py (94%)
 mode change 100755 => 100644
 rename convert-llama-ggml-to-gguf.py => convert_llama_ggml_to_gguf.py (100%)
 create mode 100755 convert_lora_to_ggml.py
 create mode 100755 convert_persimmon_to_gguf.py
 create mode 100644 poetry.lock
 create mode 100644 pyproject.toml

diff --git a/.gitignore b/.gitignore
index 177e6a8dbb117..7a63cda197862 100644
--- a/.gitignore
+++ b/.gitignore
@@ -98,13 +98,14 @@ examples/server/*.mjs.hpp
 
 # Python
 
-__pycache__
-.venv
-/Pipfile
-dist
-poetry.lock
+/.venv
+/__pycache__/
+*/poetry.lock
 poetry.toml
 
+# Nix
+/result
+
 # Test binaries
 /tests/test-backend-ops
 /tests/test-double-float
diff --git a/__init__.py b/__init__.py
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/convert-hf-to-gguf.py b/convert_hf_to_gguf.py
similarity index 100%
rename from convert-hf-to-gguf.py
rename to convert_hf_to_gguf.py
diff --git a/convert-hf-to-gguf-update.py b/convert_hf_to_gguf_update.py
old mode 100755
new mode 100644
similarity index 94%
rename from convert-hf-to-gguf-update.py
rename to convert_hf_to_gguf_update.py
index 21a3062554578..ca337af2c7d70
--- a/convert-hf-to-gguf-update.py
+++ b/convert_hf_to_gguf_update.py
@@ -50,7 +50,7 @@ class TOKENIZER_TYPE(IntEnum):
 
 # TODO: this string has to exercise as much pre-tokenizer functionality as possible
 #       will be updated with time - contributions welcome
-chktxt = '\n \n\n \n\n\n \t \t\t \t\n  \n   \n    \n     \n🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български \'\'\'\'\'\'```````\"\"\"\"......!!!!!!?????? I\'ve been \'told he\'s there, \'RE you sure? \'M not sure I\'ll make it, \'D you like some tea? We\'Ve a\'lL'
+chktxt = "\n \n\n \n\n\n \t \t\t \t\n  \n   \n    \n     \n🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български ''''''```````\"\"\"\"......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL"
 
 if len(sys.argv) == 2:
     token = sys.argv[1]
@@ -99,7 +99,7 @@ def download_file_with_auth(url, token, save_path):
     response = sess.get(url, headers=headers)
     response.raise_for_status()
     os.makedirs(os.path.dirname(save_path), exist_ok=True)
-    with open(save_path, 'wb') as f:
+    with open(save_path, "wb") as f:
         f.write(response.content)
     logger.info(f"File {save_path} downloaded successfully")
 
@@ -156,7 +156,9 @@ def download_model(model):
         else:
             tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}")
     except OSError as e:
-        logger.error(f"Error loading tokenizer for model {name}. The model may not exist or is not accessible with the provided token. Error: {e}")
+        logger.error(
+            f"Error loading tokenizer for model {name}. The model may not exist or is not accessible with the provided token. Error: {e}"
+        )
         continue  # Skip to the next model if the tokenizer can't be loaded
 
     chktok = tokenizer.encode(chktxt)
@@ -176,13 +178,15 @@ def download_model(model):
         pre_tokenizer = cfg["pre_tokenizer"]
         logger.info("pre_tokenizer: " + json.dumps(pre_tokenizer, indent=4))
         if "ignore_merges" in cfg["model"]:
-            logger.info("ignore_merges: " + json.dumps(cfg["model"]["ignore_merges"], indent=4))
+            logger.info(
+                "ignore_merges: " + json.dumps(cfg["model"]["ignore_merges"], indent=4)
+            )
 
     logger.info("")
 
-    src_ifs += f"        if chkhsh == \"{chkhsh}\":\n"
+    src_ifs += f'        if chkhsh == "{chkhsh}":\n'
     src_ifs += f"            # ref: {model['repo']}\n"
-    src_ifs += f"            res = \"{name}\"\n"
+    src_ifs += f'            res = "{name}"\n'
 
 src_func = f"""
     def get_vocab_base_pre(self, tokenizer) -> str:
@@ -343,6 +347,8 @@ def get_vocab_base_pre(self, tokenizer) -> str:
 for model in models:
     name = model["name"]
 
-    print(f"python3 convert-hf-to-gguf.py models/tokenizers/{name}/ --outfile models/ggml-vocab-{name}.gguf --vocab-only") # noqa: NP100
+    print(
+        f"python3 convert-hf-to-gguf.py models/tokenizers/{name}/ --outfile models/ggml-vocab-{name}.gguf --vocab-only"
+    )  # noqa: NP100
 
 logger.info("\n")
diff --git a/convert-llama-ggml-to-gguf.py b/convert_llama_ggml_to_gguf.py
similarity index 100%
rename from convert-llama-ggml-to-gguf.py
rename to convert_llama_ggml_to_gguf.py
diff --git a/convert_lora_to_ggml.py b/convert_lora_to_ggml.py
new file mode 100755
index 0000000000000..276d0d63a68ec
--- /dev/null
+++ b/convert_lora_to_ggml.py
@@ -0,0 +1,149 @@
+#!/usr/bin/env python3
+from __future__ import annotations
+
+import json
+import os
+import struct
+import sys
+from pathlib import Path
+from typing import Any, BinaryIO, Sequence
+
+import numpy as np
+import torch
+
+if 'NO_LOCAL_GGUF' not in os.environ:
+    sys.path.insert(1, str(Path(__file__).parent / 'gguf-py' / 'gguf'))
+import gguf
+
+NUMPY_TYPE_TO_FTYPE: dict[str, int] = {"float32": 0, "float16": 1}
+
+
+def write_file_header(fout: BinaryIO, params: dict[str, Any]) -> None:
+    fout.write(b"ggla"[::-1])  # magic (ggml lora)
+    fout.write(struct.pack("i", 1))  # file version
+    fout.write(struct.pack("i", params["r"]))
+    # https://opendelta.readthedocs.io/en/latest/modules/deltas.html says that `lora_alpha` is an int
+    # but some models ship a float value instead
+    # let's convert to int, but fail if lossless conversion is not possible
+    assert (
+        int(params["lora_alpha"]) == params["lora_alpha"]
+    ), "cannot convert float to int losslessly"
+    fout.write(struct.pack("i", int(params["lora_alpha"])))
+
+
+def write_tensor_header(fout: BinaryIO, name: str, shape: Sequence[int], data_type: np.dtype[Any]) -> None:
+    sname = name.encode("utf-8")
+    fout.write(
+        struct.pack(
+            "iii",
+            len(shape),
+            len(sname),
+            NUMPY_TYPE_TO_FTYPE[data_type.name],
+        )
+    )
+    fout.write(struct.pack("i" * len(shape), *shape[::-1]))
+    fout.write(sname)
+    fout.seek((fout.tell() + 31) & -32)
+
+
+if __name__ == '__main__':
+    if len(sys.argv) < 2:
+        print(f"Usage: python {sys.argv[0]}  [arch]")
+        print(
+            "Path must contain HuggingFace PEFT LoRA files 'adapter_config.json' and 'adapter_model.bin'"
+        )
+        print(f"Arch must be one of {list(gguf.MODEL_ARCH_NAMES.values())} (default: llama)")
+        sys.exit(1)
+
+    input_json = os.path.join(sys.argv[1], "adapter_config.json")
+    input_model = os.path.join(sys.argv[1], "adapter_model.bin")
+    output_path = os.path.join(sys.argv[1], "ggml-adapter-model.bin")
+
+    if os.path.exists(input_model):
+        model = torch.load(input_model, map_location="cpu")
+    else:
+        input_model = os.path.join(sys.argv[1], "adapter_model.safetensors")
+        # lazy import load_file only if lora is in safetensors format.
+        from safetensors.torch import load_file
+        model = load_file(input_model, device="cpu")
+
+    arch_name = sys.argv[2] if len(sys.argv) == 3 else "llama"
+
+    if arch_name not in gguf.MODEL_ARCH_NAMES.values():
+        print(f"Error: unsupported architecture {arch_name}")
+        sys.exit(1)
+
+    arch = list(gguf.MODEL_ARCH_NAMES.keys())[list(gguf.MODEL_ARCH_NAMES.values()).index(arch_name)]
+    name_map = gguf.TensorNameMap(arch, 200) # 200 layers ought to be enough for anyone
+
+    with open(input_json, "r") as f:
+        params = json.load(f)
+
+    if params["peft_type"] != "LORA":
+        print(f"Error: unsupported adapter type {params['peft_type']}, expected LORA")
+        sys.exit(1)
+
+    if params["fan_in_fan_out"] is True:
+        print("Error: param fan_in_fan_out is not supported")
+        sys.exit(1)
+
+    if params["bias"] is not None and params["bias"] != "none":
+        print("Error: param bias is not supported")
+        sys.exit(1)
+
+    # TODO: these seem to be layers that have been trained but without lora.
+    # doesn't seem widely used but eventually should be supported
+    if params["modules_to_save"] is not None and len(params["modules_to_save"]) > 0:
+        print("Error: param modules_to_save is not supported")
+        sys.exit(1)
+
+    with open(output_path, "wb") as fout:
+        fout.truncate()
+
+        write_file_header(fout, params)
+        for k, v in model.items():
+            orig_k = k
+            if k.endswith(".default.weight"):
+                k = k.replace(".default.weight", ".weight")
+            if k in ["llama_proj.weight", "llama_proj.bias"]:
+                continue
+            if k.endswith("lora_A.weight"):
+                if v.dtype != torch.float16 and v.dtype != torch.float32:
+                    v = v.float()
+                v = v.T
+            else:
+                v = v.float()
+
+            t = v.detach().numpy()
+
+            prefix = "base_model.model."
+            if k.startswith(prefix):
+                k = k[len(prefix) :]
+
+            lora_suffixes = (".lora_A.weight", ".lora_B.weight")
+            if k.endswith(lora_suffixes):
+                suffix = k[-len(lora_suffixes[0]):]
+                k = k[: -len(lora_suffixes[0])]
+            else:
+                print(f"Error: unrecognized tensor name {orig_k}")
+                sys.exit(1)
+
+            tname = name_map.get_name(k)
+            if tname is None:
+                print(f"Error: could not map tensor name {orig_k}")
+                print(" Note: the arch parameter must be specified if the model is not llama")
+                sys.exit(1)
+
+            if suffix == ".lora_A.weight":
+                tname += ".weight.loraA"
+            elif suffix == ".lora_B.weight":
+                tname += ".weight.loraB"
+            else:
+                assert False
+
+            print(f"{k} => {tname} {t.shape} {t.dtype} {t.nbytes/1024/1024:.2f}MB")
+            write_tensor_header(fout, tname, t.shape, t.dtype)
+            t.tofile(fout)
+
+    print(f"Converted {input_json} and {input_model} to {output_path}")
+
diff --git a/convert_persimmon_to_gguf.py b/convert_persimmon_to_gguf.py
new file mode 100755
index 0000000000000..e1fe3c52159bb
--- /dev/null
+++ b/convert_persimmon_to_gguf.py
@@ -0,0 +1,137 @@
+#!/usr/bin/env python3
+import argparse
+import os
+import sys
+from pathlib import Path
+from pprint import pprint
+
+import torch
+from sentencepiece import SentencePieceProcessor
+
+if 'NO_LOCAL_GGUF' not in os.environ:
+    sys.path.insert(1, str(Path(__file__).parent / 'gguf-py'))
+import gguf
+
+
+def _flatten_dict(dct, tensors, prefix=None):
+    assert isinstance(dct, dict)
+    for key in dct.keys():
+        new_prefix = prefix + '.' + key if prefix is not None else key
+        if isinstance(dct[key], torch.Tensor):
+            tensors[new_prefix] = dct[key]
+        elif isinstance(dct[key], dict):
+            _flatten_dict(dct[key], tensors, new_prefix)
+        else:
+            raise ValueError(type(dct[key]))
+    return None
+
+
+def _get_sentencepiece_tokenizer_info(dir_model: Path):
+    tokenizer_path = dir_model / 'adept_vocab.model'
+    print('gguf: getting sentencepiece tokenizer from', tokenizer_path)
+    tokenizer = SentencePieceProcessor(str(tokenizer_path))
+    print('gguf: adding tokens')
+    tokens: list[bytes] = []
+    scores: list[float] = []
+    toktypes: list[int] = []
+
+    for i in range(tokenizer.vocab_size()):
+        text: bytes
+        score: float
+
+        piece = tokenizer.id_to_piece(i)
+        text = piece.encode("utf-8")
+        score = tokenizer.get_score(i)
+
+        toktype = 1
+        if tokenizer.is_unknown(i):
+            toktype = 2
+        if tokenizer.is_control(i):
+            toktype = 3
+        if tokenizer.is_unused(i):
+            toktype = 5
+        if tokenizer.is_byte(i):
+            toktype = 6
+
+        tokens.append(text)
+        scores.append(score)
+        toktypes.append(toktype)
+        pass
+    return tokens, scores, toktypes
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Convert a Persimmon model from Adept (e.g. Persimmon 8b chat) to a GGML compatible file")
+    parser.add_argument("--outfile",             type=Path, help="path to write to; default: based on input")
+    parser.add_argument("--ckpt-path",           type=Path, help="path to persimmon checkpoint .pt file")
+    parser.add_argument("--model-dir",           type=Path, help="directory containing model e.g. 8b_chat_model_release")
+    parser.add_argument("--adept-inference-dir", type=str, help="path to adept-inference code directory")
+    args = parser.parse_args()
+    sys.path.append(str(args.adept_inference_dir))
+    persimmon_model = torch.load(args.ckpt_path)
+    hparams = persimmon_model['args']
+    pprint(hparams)
+    tensors: dict[str, torch.Tensor] = {}
+    _flatten_dict(persimmon_model['model'], tensors, None)
+
+    arch = gguf.MODEL_ARCH.PERSIMMON
+    gguf_writer = gguf.GGUFWriter(args.outfile, gguf.MODEL_ARCH_NAMES[arch])
+
+    block_count = hparams.num_layers
+    head_count = hparams.num_attention_heads
+    head_count_kv = head_count
+    ctx_length = hparams.seq_length
+    hidden_size = hparams.hidden_size
+
+    gguf_writer.add_name('persimmon-8b-chat')
+    gguf_writer.add_context_length(ctx_length)
+    gguf_writer.add_embedding_length(hidden_size)
+    gguf_writer.add_block_count(block_count)
+    gguf_writer.add_feed_forward_length(hparams.ffn_hidden_size)
+    # ref: https://github.com/ggerganov/llama.cpp/pull/4889/commits/eea19039fc52ea2dbd1aab45b59ab4e3e29a3443
+    gguf_writer.add_rope_dimension_count(hidden_size // head_count // 2)
+    gguf_writer.add_head_count(head_count)
+    gguf_writer.add_head_count_kv(head_count_kv)
+    gguf_writer.add_rope_freq_base(hparams.rotary_emb_base)
+    gguf_writer.add_layer_norm_eps(hparams.layernorm_epsilon)
+
+    tokens, scores, toktypes = _get_sentencepiece_tokenizer_info(args.model_dir)
+    gguf_writer.add_tokenizer_model('llama')
+    gguf_writer.add_token_list(tokens)
+    gguf_writer.add_token_scores(scores)
+    gguf_writer.add_token_types(toktypes)
+    gguf_writer.add_bos_token_id(71013)
+    gguf_writer.add_eos_token_id(71013)
+
+    tensor_map = gguf.get_tensor_name_map(arch, block_count)
+    print(tensor_map)
+    for name in tensors.keys():
+        data = tensors[name]
+        if name.endswith(".self_attention.rotary_emb.inv_freq"):
+            continue
+        old_dtype = data.dtype
+        # TODO: FP16 conversion produces garbage outputs. (Q8_0 does not, so..?)
+        data = data.to(torch.float32).squeeze().numpy()
+        new_name = tensor_map.get_name(name, try_suffixes = (".weight", ".bias"))
+        if new_name is None:
+            print("Can not map tensor '" + name + "'")
+            sys.exit()
+        n_dims = len(data.shape)
+        print(new_name + ", n_dims = " + str(n_dims) + ", " + str(old_dtype) + " --> " + str(data.dtype))
+        gguf_writer.add_tensor(new_name, data)
+    print("gguf: write header")
+    gguf_writer.write_header_to_file()
+    print("gguf: write metadata")
+    gguf_writer.write_kv_data_to_file()
+    print("gguf: write tensors")
+    gguf_writer.write_tensors_to_file()
+
+    gguf_writer.close()
+
+    print(f"gguf: model successfully exported to '{args.outfile}'")
+    print("")
+
+
+if __name__ == '__main__':
+    main()
+
diff --git a/poetry.lock b/poetry.lock
new file mode 100644
index 0000000000000..eb6baa6c749c0
--- /dev/null
+++ b/poetry.lock
@@ -0,0 +1,1197 @@
+# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
+
+[[package]]
+name = "atomicwrites"
+version = "1.4.1"
+description = "Atomic file writes."
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+files = [
+    {file = "atomicwrites-1.4.1.tar.gz", hash = "sha256:81b2c9071a49367a7f770170e5eec8cb66567cfbbc8c73d20ce5ca4a8d71cf11"},
+]
+
+[[package]]
+name = "attrs"
+version = "23.2.0"
+description = "Classes Without Boilerplate"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "attrs-23.2.0-py3-none-any.whl", hash = "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1"},
+    {file = "attrs-23.2.0.tar.gz", hash = "sha256:935dc3b529c262f6cf76e50877d35a4bd3c1de194fd41f47a2b7ae8f19971f30"},
+]
+
+[package.extras]
+cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
+dev = ["attrs[tests]", "pre-commit"]
+docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
+tests = ["attrs[tests-no-zope]", "zope-interface"]
+tests-mypy = ["mypy (>=1.6)", "pytest-mypy-plugins"]
+tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
+
+[[package]]
+name = "certifi"
+version = "2024.2.2"
+description = "Python package for providing Mozilla's CA Bundle."
+optional = false
+python-versions = ">=3.6"
+files = [
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+]
+
+[[package]]
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+version = "3.3.2"
+description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
+optional = false
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diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000000000..8759d99e1ec6a
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,44 @@
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+[tool.poetry.dependencies]
+python = ">=3.9"
+numpy = "^1.25.0"
+sentencepiece = ">=0.1.98,<0.2.0"
+transformers = ">=4.35.2,<5.0.0"
+protobuf = ">=4.21.0,<5.0.0"
+gguf = { path = "./gguf-py" }
+torch = {version = "^2.2.0", source = "pytorch"}
+
+[tool.poetry.dev-dependencies]
+pytest = "^5.2"
+
+[[tool.poetry.source]]
+name = "pytorch"
+url = "https://download.pytorch.org/whl/cpu"
+priority = "explicit"
+
+[build-system]
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"
+
+[tool.poetry.scripts]
+llama-convert-hf-to-gguf = "convert_hf_to_gguf:main"
+llama-convert-llama-ggml-to-gguf = "convert_llama_ggml_to_gguf:main"
+llama-convert-lora-to-ggml = "convert_lora_to_ggml:main"
+llama-convert-persimmon-to-gguf = "convert_persimmon_to_gguf:main"
+llama-convert = "convert:main"
+llama-ggml_vk_generate_shaders = "ggml_vk_generate_shaders:main"

From b1c3f26e5e882fa46d7a6704d893b31a025e9000 Mon Sep 17 00:00:00 2001
From: ditsuke 
Date: Thu, 29 Feb 2024 01:47:15 +0530
Subject: [PATCH 088/326] fix: Actually include scripts in build

Not namespaced though :(
---
 __init__.py    | 0
 pyproject.toml | 4 ++--
 2 files changed, 2 insertions(+), 2 deletions(-)
 delete mode 100644 __init__.py

diff --git a/__init__.py b/__init__.py
deleted file mode 100644
index e69de29bb2d1d..0000000000000
diff --git a/pyproject.toml b/pyproject.toml
index 8759d99e1ec6a..2c6e855e38510 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -7,7 +7,7 @@ readme = "README.md"
 homepage = "https://ggml.ai"
 repository = "https://github.com/ggerganov/llama.cpp"
 keywords = ["ggml", "gguf", "llama.cpp"]
-packages = [{ include = "__init__.py", from = "." }]
+packages = [{ include = "*.py", from = "." }]
 classifiers = [
     "Programming Language :: Python :: 3",
     "License :: OSI Approved :: MIT License",
@@ -21,7 +21,7 @@ sentencepiece = ">=0.1.98,<0.2.0"
 transformers = ">=4.35.2,<5.0.0"
 protobuf = ">=4.21.0,<5.0.0"
 gguf = { path = "./gguf-py" }
-torch = {version = "^2.2.0", source = "pytorch"}
+torch = { version = "^2.2.0", source = "pytorch" }
 
 [tool.poetry.dev-dependencies]
 pytest = "^5.2"

From 821922916f95cc3853fc7f58ea2f1e15a0ffa669 Mon Sep 17 00:00:00 2001
From: ditsuke 
Date: Sun, 10 Mar 2024 23:21:46 +0530
Subject: [PATCH 089/326] fix: Update script paths in CI scripts

---
 ci/run.sh                                                   | 2 +-
 requirements.txt                                            | 6 +++---
 ...-gguf-update.txt => requirements-convert_hf_to_gguf.txt} | 0
 ...-gguf.txt => requirements-convert_hf_to_gguf_update.txt} | 0
 ...gguf.txt => requirements-convert_llama_ggml_to_gguf.txt} | 0
 requirements/requirements-convert_lora_to_ggml.txt          | 3 +++
 requirements/requirements-convert_persimmon_to_gguf.txt     | 3 +++
 scripts/check-requirements.sh                               | 4 ++--
 8 files changed, 12 insertions(+), 6 deletions(-)
 rename requirements/{requirements-convert-hf-to-gguf-update.txt => requirements-convert_hf_to_gguf.txt} (100%)
 rename requirements/{requirements-convert-hf-to-gguf.txt => requirements-convert_hf_to_gguf_update.txt} (100%)
 rename requirements/{requirements-convert-llama-ggml-to-gguf.txt => requirements-convert_llama_ggml_to_gguf.txt} (100%)
 create mode 100644 requirements/requirements-convert_lora_to_ggml.txt
 create mode 100644 requirements/requirements-convert_persimmon_to_gguf.txt

diff --git a/ci/run.sh b/ci/run.sh
index e0cedb24f5a58..067ac405b412a 100755
--- a/ci/run.sh
+++ b/ci/run.sh
@@ -688,7 +688,7 @@ function gg_run_embd_bge_small {
     (time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
     (time make -j                                            ) 2>&1 | tee -a $OUT/${ci}-make.log
 
-    python3 ../convert-hf-to-gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
+    python3 ../convert_hf_to_gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
 
     model_f16="${path_models}/ggml-model-f16.gguf"
     model_q8_0="${path_models}/ggml-model-q8_0.gguf"
diff --git a/requirements.txt b/requirements.txt
index e5cfbf10b3da5..1eca1a13f999e 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -6,6 +6,6 @@
 
 -r ./requirements/requirements-convert-legacy-llama.txt
 
--r ./requirements/requirements-convert-hf-to-gguf.txt
--r ./requirements/requirements-convert-hf-to-gguf-update.txt
--r ./requirements/requirements-convert-llama-ggml-to-gguf.txt
+-r ./requirements/requirements-convert_hf_to_gguf.txt
+-r ./requirements/requirements-convert_hf_to_gguf_update.txt
+-r ./requirements/requirements-convert_llama_ggml_to_gguf.txt
diff --git a/requirements/requirements-convert-hf-to-gguf-update.txt b/requirements/requirements-convert_hf_to_gguf.txt
similarity index 100%
rename from requirements/requirements-convert-hf-to-gguf-update.txt
rename to requirements/requirements-convert_hf_to_gguf.txt
diff --git a/requirements/requirements-convert-hf-to-gguf.txt b/requirements/requirements-convert_hf_to_gguf_update.txt
similarity index 100%
rename from requirements/requirements-convert-hf-to-gguf.txt
rename to requirements/requirements-convert_hf_to_gguf_update.txt
diff --git a/requirements/requirements-convert-llama-ggml-to-gguf.txt b/requirements/requirements-convert_llama_ggml_to_gguf.txt
similarity index 100%
rename from requirements/requirements-convert-llama-ggml-to-gguf.txt
rename to requirements/requirements-convert_llama_ggml_to_gguf.txt
diff --git a/requirements/requirements-convert_lora_to_ggml.txt b/requirements/requirements-convert_lora_to_ggml.txt
new file mode 100644
index 0000000000000..fe5d13dd8a1d4
--- /dev/null
+++ b/requirements/requirements-convert_lora_to_ggml.txt
@@ -0,0 +1,3 @@
+-r ./requirements-convert.txt
+torch~=2.1.1
+
diff --git a/requirements/requirements-convert_persimmon_to_gguf.txt b/requirements/requirements-convert_persimmon_to_gguf.txt
new file mode 100644
index 0000000000000..fe5d13dd8a1d4
--- /dev/null
+++ b/requirements/requirements-convert_persimmon_to_gguf.txt
@@ -0,0 +1,3 @@
+-r ./requirements-convert.txt
+torch~=2.1.1
+
diff --git a/scripts/check-requirements.sh b/scripts/check-requirements.sh
index 0c6afdd591aaa..69a08c8410768 100755
--- a/scripts/check-requirements.sh
+++ b/scripts/check-requirements.sh
@@ -167,11 +167,11 @@ if (( do_cleanup )); then
 fi
 
 check_convert_script examples/convert-legacy-llama.py
-for py in convert-*.py; do
+for py in convert_*.py; do
     # skip convert-hf-to-gguf-update.py
     # TODO: the check is failing for some reason:
     #       https://github.com/ggerganov/llama.cpp/actions/runs/8875330981/job/24364557177?pr=6920
-    [[ $py == convert-hf-to-gguf-update.py ]] && continue
+    [[ $py == convert_hf_to_gguf_update.py ]] && continue
 
     check_convert_script "$py"
 done

From de14e2ea2b542386dcb800226eb360be76f433fd Mon Sep 17 00:00:00 2001
From: ditsuke 
Date: Tue, 2 Jul 2024 15:18:13 +0530
Subject: [PATCH 090/326] chore: ignore all __pychache__

---
 .gitignore | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.gitignore b/.gitignore
index 7a63cda197862..6125e350c09d7 100644
--- a/.gitignore
+++ b/.gitignore
@@ -99,7 +99,7 @@ examples/server/*.mjs.hpp
 # Python
 
 /.venv
-/__pycache__/
+__pycache__/
 */poetry.lock
 poetry.toml
 

From 07786a61a2097306ee496f565f78796f1aa205e6 Mon Sep 17 00:00:00 2001
From: ditsuke 
Date: Tue, 2 Jul 2024 15:35:43 +0530
Subject: [PATCH 091/326] chore: Fixup requirements and build

---
 CMakeLists.txt                                          | 4 +++-
 examples/llava/requirements.txt                         | 2 +-
 pyproject.toml                                          | 2 +-
 requirements.txt                                        | 2 ++
 requirements/requirements-convert_lora_to_ggml.txt      | 4 ++--
 requirements/requirements-convert_persimmon_to_gguf.txt | 4 ++--
 6 files changed, 11 insertions(+), 7 deletions(-)

diff --git a/CMakeLists.txt b/CMakeLists.txt
index d95414d710f56..f7b6601b33814 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -156,7 +156,7 @@ install(FILES ${CMAKE_CURRENT_BINARY_DIR}/llama-config.cmake
         DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/llama)
 
 install(
-    FILES convert-hf-to-gguf.py
+    FILES convert_hf_to_gguf.py
     PERMISSIONS
         OWNER_READ
         OWNER_WRITE
@@ -165,6 +165,8 @@ install(
         GROUP_EXECUTE
         WORLD_READ
         WORLD_EXECUTE
+    RENAME
+        convert-hf-to-gguf.py
     DESTINATION ${CMAKE_INSTALL_BINDIR})
 
 configure_file(cmake/llama.pc.in
diff --git a/examples/llava/requirements.txt b/examples/llava/requirements.txt
index 17cb4d5e5ee8e..21149d6fe1494 100644
--- a/examples/llava/requirements.txt
+++ b/examples/llava/requirements.txt
@@ -1,3 +1,3 @@
 -r ../../requirements/requirements-convert-legacy-llama.txt
 pillow~=10.2.0
-torch~=2.1.1
+torch~=2.2.1
diff --git a/pyproject.toml b/pyproject.toml
index 2c6e855e38510..e94cd1ba6e069 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -41,4 +41,4 @@ llama-convert-llama-ggml-to-gguf = "convert_llama_ggml_to_gguf:main"
 llama-convert-lora-to-ggml = "convert_lora_to_ggml:main"
 llama-convert-persimmon-to-gguf = "convert_persimmon_to_gguf:main"
 llama-convert = "convert:main"
-llama-ggml_vk_generate_shaders = "ggml_vk_generate_shaders:main"
+llama-ggml-vk-generate-shaders = "ggml_vk_generate_shaders:main"
diff --git a/requirements.txt b/requirements.txt
index 1eca1a13f999e..4f9bcc9ca239d 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -9,3 +9,5 @@
 -r ./requirements/requirements-convert_hf_to_gguf.txt
 -r ./requirements/requirements-convert_hf_to_gguf_update.txt
 -r ./requirements/requirements-convert_llama_ggml_to_gguf.txt
+-r ./requirements/requirements-convert_lora_to_ggml.txt
+-r ./requirements/requirements-convert_persimmon_to_gguf.txt
diff --git a/requirements/requirements-convert_lora_to_ggml.txt b/requirements/requirements-convert_lora_to_ggml.txt
index fe5d13dd8a1d4..4135cd6557168 100644
--- a/requirements/requirements-convert_lora_to_ggml.txt
+++ b/requirements/requirements-convert_lora_to_ggml.txt
@@ -1,3 +1,3 @@
--r ./requirements-convert.txt
-torch~=2.1.1
+-r ./requirements-convert-legacy-llama.txt
+torch~=2.2.1
 
diff --git a/requirements/requirements-convert_persimmon_to_gguf.txt b/requirements/requirements-convert_persimmon_to_gguf.txt
index fe5d13dd8a1d4..4135cd6557168 100644
--- a/requirements/requirements-convert_persimmon_to_gguf.txt
+++ b/requirements/requirements-convert_persimmon_to_gguf.txt
@@ -1,3 +1,3 @@
--r ./requirements-convert.txt
-torch~=2.1.1
+-r ./requirements-convert-legacy-llama.txt
+torch~=2.2.1
 

From 01a5f06550a866bd63717635e5e7e1ff4203b873 Mon Sep 17 00:00:00 2001
From: ditsuke 
Date: Tue, 2 Jul 2024 15:48:13 +0530
Subject: [PATCH 092/326] chore: Remove rebase artifacts

---
 convert_hf_to_gguf_update.py                  |  20 +--
 convert_lora_to_ggml.py                       | 149 ------------------
 convert_persimmon_to_gguf.py                  | 137 ----------------
 pyproject.toml                                |   3 -
 requirements.txt                              |   2 -
 .../requirements-convert_lora_to_ggml.txt     |   3 -
 ...requirements-convert_persimmon_to_gguf.txt |   3 -
 7 files changed, 7 insertions(+), 310 deletions(-)
 mode change 100644 => 100755 convert_hf_to_gguf_update.py
 delete mode 100755 convert_lora_to_ggml.py
 delete mode 100755 convert_persimmon_to_gguf.py
 delete mode 100644 requirements/requirements-convert_lora_to_ggml.txt
 delete mode 100644 requirements/requirements-convert_persimmon_to_gguf.txt

diff --git a/convert_hf_to_gguf_update.py b/convert_hf_to_gguf_update.py
old mode 100644
new mode 100755
index ca337af2c7d70..21a3062554578
--- a/convert_hf_to_gguf_update.py
+++ b/convert_hf_to_gguf_update.py
@@ -50,7 +50,7 @@ class TOKENIZER_TYPE(IntEnum):
 
 # TODO: this string has to exercise as much pre-tokenizer functionality as possible
 #       will be updated with time - contributions welcome
-chktxt = "\n \n\n \n\n\n \t \t\t \t\n  \n   \n    \n     \n🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български ''''''```````\"\"\"\"......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL"
+chktxt = '\n \n\n \n\n\n \t \t\t \t\n  \n   \n    \n     \n🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български \'\'\'\'\'\'```````\"\"\"\"......!!!!!!?????? I\'ve been \'told he\'s there, \'RE you sure? \'M not sure I\'ll make it, \'D you like some tea? We\'Ve a\'lL'
 
 if len(sys.argv) == 2:
     token = sys.argv[1]
@@ -99,7 +99,7 @@ def download_file_with_auth(url, token, save_path):
     response = sess.get(url, headers=headers)
     response.raise_for_status()
     os.makedirs(os.path.dirname(save_path), exist_ok=True)
-    with open(save_path, "wb") as f:
+    with open(save_path, 'wb') as f:
         f.write(response.content)
     logger.info(f"File {save_path} downloaded successfully")
 
@@ -156,9 +156,7 @@ def download_model(model):
         else:
             tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}")
     except OSError as e:
-        logger.error(
-            f"Error loading tokenizer for model {name}. The model may not exist or is not accessible with the provided token. Error: {e}"
-        )
+        logger.error(f"Error loading tokenizer for model {name}. The model may not exist or is not accessible with the provided token. Error: {e}")
         continue  # Skip to the next model if the tokenizer can't be loaded
 
     chktok = tokenizer.encode(chktxt)
@@ -178,15 +176,13 @@ def download_model(model):
         pre_tokenizer = cfg["pre_tokenizer"]
         logger.info("pre_tokenizer: " + json.dumps(pre_tokenizer, indent=4))
         if "ignore_merges" in cfg["model"]:
-            logger.info(
-                "ignore_merges: " + json.dumps(cfg["model"]["ignore_merges"], indent=4)
-            )
+            logger.info("ignore_merges: " + json.dumps(cfg["model"]["ignore_merges"], indent=4))
 
     logger.info("")
 
-    src_ifs += f'        if chkhsh == "{chkhsh}":\n'
+    src_ifs += f"        if chkhsh == \"{chkhsh}\":\n"
     src_ifs += f"            # ref: {model['repo']}\n"
-    src_ifs += f'            res = "{name}"\n'
+    src_ifs += f"            res = \"{name}\"\n"
 
 src_func = f"""
     def get_vocab_base_pre(self, tokenizer) -> str:
@@ -347,8 +343,6 @@ def get_vocab_base_pre(self, tokenizer) -> str:
 for model in models:
     name = model["name"]
 
-    print(
-        f"python3 convert-hf-to-gguf.py models/tokenizers/{name}/ --outfile models/ggml-vocab-{name}.gguf --vocab-only"
-    )  # noqa: NP100
+    print(f"python3 convert-hf-to-gguf.py models/tokenizers/{name}/ --outfile models/ggml-vocab-{name}.gguf --vocab-only") # noqa: NP100
 
 logger.info("\n")
diff --git a/convert_lora_to_ggml.py b/convert_lora_to_ggml.py
deleted file mode 100755
index 276d0d63a68ec..0000000000000
--- a/convert_lora_to_ggml.py
+++ /dev/null
@@ -1,149 +0,0 @@
-#!/usr/bin/env python3
-from __future__ import annotations
-
-import json
-import os
-import struct
-import sys
-from pathlib import Path
-from typing import Any, BinaryIO, Sequence
-
-import numpy as np
-import torch
-
-if 'NO_LOCAL_GGUF' not in os.environ:
-    sys.path.insert(1, str(Path(__file__).parent / 'gguf-py' / 'gguf'))
-import gguf
-
-NUMPY_TYPE_TO_FTYPE: dict[str, int] = {"float32": 0, "float16": 1}
-
-
-def write_file_header(fout: BinaryIO, params: dict[str, Any]) -> None:
-    fout.write(b"ggla"[::-1])  # magic (ggml lora)
-    fout.write(struct.pack("i", 1))  # file version
-    fout.write(struct.pack("i", params["r"]))
-    # https://opendelta.readthedocs.io/en/latest/modules/deltas.html says that `lora_alpha` is an int
-    # but some models ship a float value instead
-    # let's convert to int, but fail if lossless conversion is not possible
-    assert (
-        int(params["lora_alpha"]) == params["lora_alpha"]
-    ), "cannot convert float to int losslessly"
-    fout.write(struct.pack("i", int(params["lora_alpha"])))
-
-
-def write_tensor_header(fout: BinaryIO, name: str, shape: Sequence[int], data_type: np.dtype[Any]) -> None:
-    sname = name.encode("utf-8")
-    fout.write(
-        struct.pack(
-            "iii",
-            len(shape),
-            len(sname),
-            NUMPY_TYPE_TO_FTYPE[data_type.name],
-        )
-    )
-    fout.write(struct.pack("i" * len(shape), *shape[::-1]))
-    fout.write(sname)
-    fout.seek((fout.tell() + 31) & -32)
-
-
-if __name__ == '__main__':
-    if len(sys.argv) < 2:
-        print(f"Usage: python {sys.argv[0]}  [arch]")
-        print(
-            "Path must contain HuggingFace PEFT LoRA files 'adapter_config.json' and 'adapter_model.bin'"
-        )
-        print(f"Arch must be one of {list(gguf.MODEL_ARCH_NAMES.values())} (default: llama)")
-        sys.exit(1)
-
-    input_json = os.path.join(sys.argv[1], "adapter_config.json")
-    input_model = os.path.join(sys.argv[1], "adapter_model.bin")
-    output_path = os.path.join(sys.argv[1], "ggml-adapter-model.bin")
-
-    if os.path.exists(input_model):
-        model = torch.load(input_model, map_location="cpu")
-    else:
-        input_model = os.path.join(sys.argv[1], "adapter_model.safetensors")
-        # lazy import load_file only if lora is in safetensors format.
-        from safetensors.torch import load_file
-        model = load_file(input_model, device="cpu")
-
-    arch_name = sys.argv[2] if len(sys.argv) == 3 else "llama"
-
-    if arch_name not in gguf.MODEL_ARCH_NAMES.values():
-        print(f"Error: unsupported architecture {arch_name}")
-        sys.exit(1)
-
-    arch = list(gguf.MODEL_ARCH_NAMES.keys())[list(gguf.MODEL_ARCH_NAMES.values()).index(arch_name)]
-    name_map = gguf.TensorNameMap(arch, 200) # 200 layers ought to be enough for anyone
-
-    with open(input_json, "r") as f:
-        params = json.load(f)
-
-    if params["peft_type"] != "LORA":
-        print(f"Error: unsupported adapter type {params['peft_type']}, expected LORA")
-        sys.exit(1)
-
-    if params["fan_in_fan_out"] is True:
-        print("Error: param fan_in_fan_out is not supported")
-        sys.exit(1)
-
-    if params["bias"] is not None and params["bias"] != "none":
-        print("Error: param bias is not supported")
-        sys.exit(1)
-
-    # TODO: these seem to be layers that have been trained but without lora.
-    # doesn't seem widely used but eventually should be supported
-    if params["modules_to_save"] is not None and len(params["modules_to_save"]) > 0:
-        print("Error: param modules_to_save is not supported")
-        sys.exit(1)
-
-    with open(output_path, "wb") as fout:
-        fout.truncate()
-
-        write_file_header(fout, params)
-        for k, v in model.items():
-            orig_k = k
-            if k.endswith(".default.weight"):
-                k = k.replace(".default.weight", ".weight")
-            if k in ["llama_proj.weight", "llama_proj.bias"]:
-                continue
-            if k.endswith("lora_A.weight"):
-                if v.dtype != torch.float16 and v.dtype != torch.float32:
-                    v = v.float()
-                v = v.T
-            else:
-                v = v.float()
-
-            t = v.detach().numpy()
-
-            prefix = "base_model.model."
-            if k.startswith(prefix):
-                k = k[len(prefix) :]
-
-            lora_suffixes = (".lora_A.weight", ".lora_B.weight")
-            if k.endswith(lora_suffixes):
-                suffix = k[-len(lora_suffixes[0]):]
-                k = k[: -len(lora_suffixes[0])]
-            else:
-                print(f"Error: unrecognized tensor name {orig_k}")
-                sys.exit(1)
-
-            tname = name_map.get_name(k)
-            if tname is None:
-                print(f"Error: could not map tensor name {orig_k}")
-                print(" Note: the arch parameter must be specified if the model is not llama")
-                sys.exit(1)
-
-            if suffix == ".lora_A.weight":
-                tname += ".weight.loraA"
-            elif suffix == ".lora_B.weight":
-                tname += ".weight.loraB"
-            else:
-                assert False
-
-            print(f"{k} => {tname} {t.shape} {t.dtype} {t.nbytes/1024/1024:.2f}MB")
-            write_tensor_header(fout, tname, t.shape, t.dtype)
-            t.tofile(fout)
-
-    print(f"Converted {input_json} and {input_model} to {output_path}")
-
diff --git a/convert_persimmon_to_gguf.py b/convert_persimmon_to_gguf.py
deleted file mode 100755
index e1fe3c52159bb..0000000000000
--- a/convert_persimmon_to_gguf.py
+++ /dev/null
@@ -1,137 +0,0 @@
-#!/usr/bin/env python3
-import argparse
-import os
-import sys
-from pathlib import Path
-from pprint import pprint
-
-import torch
-from sentencepiece import SentencePieceProcessor
-
-if 'NO_LOCAL_GGUF' not in os.environ:
-    sys.path.insert(1, str(Path(__file__).parent / 'gguf-py'))
-import gguf
-
-
-def _flatten_dict(dct, tensors, prefix=None):
-    assert isinstance(dct, dict)
-    for key in dct.keys():
-        new_prefix = prefix + '.' + key if prefix is not None else key
-        if isinstance(dct[key], torch.Tensor):
-            tensors[new_prefix] = dct[key]
-        elif isinstance(dct[key], dict):
-            _flatten_dict(dct[key], tensors, new_prefix)
-        else:
-            raise ValueError(type(dct[key]))
-    return None
-
-
-def _get_sentencepiece_tokenizer_info(dir_model: Path):
-    tokenizer_path = dir_model / 'adept_vocab.model'
-    print('gguf: getting sentencepiece tokenizer from', tokenizer_path)
-    tokenizer = SentencePieceProcessor(str(tokenizer_path))
-    print('gguf: adding tokens')
-    tokens: list[bytes] = []
-    scores: list[float] = []
-    toktypes: list[int] = []
-
-    for i in range(tokenizer.vocab_size()):
-        text: bytes
-        score: float
-
-        piece = tokenizer.id_to_piece(i)
-        text = piece.encode("utf-8")
-        score = tokenizer.get_score(i)
-
-        toktype = 1
-        if tokenizer.is_unknown(i):
-            toktype = 2
-        if tokenizer.is_control(i):
-            toktype = 3
-        if tokenizer.is_unused(i):
-            toktype = 5
-        if tokenizer.is_byte(i):
-            toktype = 6
-
-        tokens.append(text)
-        scores.append(score)
-        toktypes.append(toktype)
-        pass
-    return tokens, scores, toktypes
-
-
-def main():
-    parser = argparse.ArgumentParser(description="Convert a Persimmon model from Adept (e.g. Persimmon 8b chat) to a GGML compatible file")
-    parser.add_argument("--outfile",             type=Path, help="path to write to; default: based on input")
-    parser.add_argument("--ckpt-path",           type=Path, help="path to persimmon checkpoint .pt file")
-    parser.add_argument("--model-dir",           type=Path, help="directory containing model e.g. 8b_chat_model_release")
-    parser.add_argument("--adept-inference-dir", type=str, help="path to adept-inference code directory")
-    args = parser.parse_args()
-    sys.path.append(str(args.adept_inference_dir))
-    persimmon_model = torch.load(args.ckpt_path)
-    hparams = persimmon_model['args']
-    pprint(hparams)
-    tensors: dict[str, torch.Tensor] = {}
-    _flatten_dict(persimmon_model['model'], tensors, None)
-
-    arch = gguf.MODEL_ARCH.PERSIMMON
-    gguf_writer = gguf.GGUFWriter(args.outfile, gguf.MODEL_ARCH_NAMES[arch])
-
-    block_count = hparams.num_layers
-    head_count = hparams.num_attention_heads
-    head_count_kv = head_count
-    ctx_length = hparams.seq_length
-    hidden_size = hparams.hidden_size
-
-    gguf_writer.add_name('persimmon-8b-chat')
-    gguf_writer.add_context_length(ctx_length)
-    gguf_writer.add_embedding_length(hidden_size)
-    gguf_writer.add_block_count(block_count)
-    gguf_writer.add_feed_forward_length(hparams.ffn_hidden_size)
-    # ref: https://github.com/ggerganov/llama.cpp/pull/4889/commits/eea19039fc52ea2dbd1aab45b59ab4e3e29a3443
-    gguf_writer.add_rope_dimension_count(hidden_size // head_count // 2)
-    gguf_writer.add_head_count(head_count)
-    gguf_writer.add_head_count_kv(head_count_kv)
-    gguf_writer.add_rope_freq_base(hparams.rotary_emb_base)
-    gguf_writer.add_layer_norm_eps(hparams.layernorm_epsilon)
-
-    tokens, scores, toktypes = _get_sentencepiece_tokenizer_info(args.model_dir)
-    gguf_writer.add_tokenizer_model('llama')
-    gguf_writer.add_token_list(tokens)
-    gguf_writer.add_token_scores(scores)
-    gguf_writer.add_token_types(toktypes)
-    gguf_writer.add_bos_token_id(71013)
-    gguf_writer.add_eos_token_id(71013)
-
-    tensor_map = gguf.get_tensor_name_map(arch, block_count)
-    print(tensor_map)
-    for name in tensors.keys():
-        data = tensors[name]
-        if name.endswith(".self_attention.rotary_emb.inv_freq"):
-            continue
-        old_dtype = data.dtype
-        # TODO: FP16 conversion produces garbage outputs. (Q8_0 does not, so..?)
-        data = data.to(torch.float32).squeeze().numpy()
-        new_name = tensor_map.get_name(name, try_suffixes = (".weight", ".bias"))
-        if new_name is None:
-            print("Can not map tensor '" + name + "'")
-            sys.exit()
-        n_dims = len(data.shape)
-        print(new_name + ", n_dims = " + str(n_dims) + ", " + str(old_dtype) + " --> " + str(data.dtype))
-        gguf_writer.add_tensor(new_name, data)
-    print("gguf: write header")
-    gguf_writer.write_header_to_file()
-    print("gguf: write metadata")
-    gguf_writer.write_kv_data_to_file()
-    print("gguf: write tensors")
-    gguf_writer.write_tensors_to_file()
-
-    gguf_writer.close()
-
-    print(f"gguf: model successfully exported to '{args.outfile}'")
-    print("")
-
-
-if __name__ == '__main__':
-    main()
-
diff --git a/pyproject.toml b/pyproject.toml
index e94cd1ba6e069..198cb43dde824 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -38,7 +38,4 @@ build-backend = "poetry.core.masonry.api"
 [tool.poetry.scripts]
 llama-convert-hf-to-gguf = "convert_hf_to_gguf:main"
 llama-convert-llama-ggml-to-gguf = "convert_llama_ggml_to_gguf:main"
-llama-convert-lora-to-ggml = "convert_lora_to_ggml:main"
-llama-convert-persimmon-to-gguf = "convert_persimmon_to_gguf:main"
-llama-convert = "convert:main"
 llama-ggml-vk-generate-shaders = "ggml_vk_generate_shaders:main"
diff --git a/requirements.txt b/requirements.txt
index 4f9bcc9ca239d..1eca1a13f999e 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -9,5 +9,3 @@
 -r ./requirements/requirements-convert_hf_to_gguf.txt
 -r ./requirements/requirements-convert_hf_to_gguf_update.txt
 -r ./requirements/requirements-convert_llama_ggml_to_gguf.txt
--r ./requirements/requirements-convert_lora_to_ggml.txt
--r ./requirements/requirements-convert_persimmon_to_gguf.txt
diff --git a/requirements/requirements-convert_lora_to_ggml.txt b/requirements/requirements-convert_lora_to_ggml.txt
deleted file mode 100644
index 4135cd6557168..0000000000000
--- a/requirements/requirements-convert_lora_to_ggml.txt
+++ /dev/null
@@ -1,3 +0,0 @@
--r ./requirements-convert-legacy-llama.txt
-torch~=2.2.1
-
diff --git a/requirements/requirements-convert_persimmon_to_gguf.txt b/requirements/requirements-convert_persimmon_to_gguf.txt
deleted file mode 100644
index 4135cd6557168..0000000000000
--- a/requirements/requirements-convert_persimmon_to_gguf.txt
+++ /dev/null
@@ -1,3 +0,0 @@
--r ./requirements-convert-legacy-llama.txt
-torch~=2.2.1
-

From 1e920018d38aee270a044cc48eaefe7c64cb8750 Mon Sep 17 00:00:00 2001
From: ditsuke 
Date: Wed, 3 Jul 2024 01:02:56 +0530
Subject: [PATCH 093/326] doc: Add context for why we add an explicit pytorch
 source

---
 pyproject.toml | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/pyproject.toml b/pyproject.toml
index 198cb43dde824..25e2e20b24896 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -26,6 +26,9 @@ torch = { version = "^2.2.0", source = "pytorch" }
 [tool.poetry.dev-dependencies]
 pytest = "^5.2"
 
+
+# Force wheel + cpu
+# For discussion and context see https://github.com/python-poetry/poetry#6409
 [[tool.poetry.source]]
 name = "pytorch"
 url = "https://download.pytorch.org/whl/cpu"

From 51d2ebadbbf365b894f3888361df42dbacb12b7a Mon Sep 17 00:00:00 2001
From: ditsuke 
Date: Thu, 4 Jul 2024 20:54:35 +0530
Subject: [PATCH 094/326] build: Export hf-to-gguf as snakecase

---
 CMakeLists.txt | 2 --
 1 file changed, 2 deletions(-)

diff --git a/CMakeLists.txt b/CMakeLists.txt
index f7b6601b33814..4f6cd68724aa6 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -165,8 +165,6 @@ install(
         GROUP_EXECUTE
         WORLD_READ
         WORLD_EXECUTE
-    RENAME
-        convert-hf-to-gguf.py
     DESTINATION ${CMAKE_INSTALL_BINDIR})
 
 configure_file(cmake/llama.pc.in

From 6f63d646c1a06a6e09f721009a2676864ae04e31 Mon Sep 17 00:00:00 2001
From: Daniel Bevenius 
Date: Thu, 4 Jul 2024 18:38:58 +0200
Subject: [PATCH 095/326] tokenize : add --show-count (token) option (#8299)

This commit adds a new option to the tokenize example, --show-count.
When this is set the total number of tokens are printed to stdout.

This was added as an option as I was concerned that there might be
scripts that use the output from this program and it might be better to
not print this information by default.

The motivation for this is that can be useful to find out how many
tokens a file contains, for example when trying to determine prompt
input file sizes for testing.

Signed-off-by: Daniel Bevenius 
---
 examples/tokenize/tokenize.cpp | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/examples/tokenize/tokenize.cpp b/examples/tokenize/tokenize.cpp
index 54c9834afb1b9..0180c87d863bf 100644
--- a/examples/tokenize/tokenize.cpp
+++ b/examples/tokenize/tokenize.cpp
@@ -30,6 +30,7 @@ static void print_usage_information(const char * argv0, FILE * stream) {
     fprintf(stream, "    --stdin                              read prompt from standard input.\n");
     fprintf(stream, "    --no-bos                             do not ever add a BOS token to the prompt, even if normally the model uses a BOS token.\n");
     fprintf(stream, "    --log-disable                        disable logs. Makes stderr quiet when loading the model.\n");
+    fprintf(stream, "    --show-count                         print the total number of tokens.\n");
 }
 
 static void llama_log_callback_null(ggml_log_level level, const char * text, void * user_data) {
@@ -195,6 +196,7 @@ int main(int raw_argc, char ** raw_argv) {
     bool printing_ids = false;
     bool no_bos = false;
     bool disable_logging = false;
+    bool show_token_count = false;
     const char * model_path = NULL;
     const char * prompt_path = NULL;
     const char * prompt_arg = NULL;
@@ -249,6 +251,9 @@ int main(int raw_argc, char ** raw_argv) {
         else if (arg == "--log-disable") {
             disable_logging = true;
         }
+        else if (arg == "--show-count") {
+            show_token_count = true;
+        }
         else {
             fprintf(stderr, "Error: unknown option '%s'\n", argv[iarg].c_str());
             return 1;
@@ -384,6 +389,9 @@ int main(int raw_argc, char ** raw_argv) {
         printf("]\n");
     }
 
+    if (show_token_count) {
+        printf("Total number of tokens: %ld\n", tokens.size());
+    }
     // silence valgrind
     llama_free(ctx);
     llama_free_model(model);

From d7fd29fff16456ce9c3a23fd2d09a66256b05aff Mon Sep 17 00:00:00 2001
From: Icecream95 
Date: Fri, 5 Jul 2024 05:14:21 +1200
Subject: [PATCH 096/326] llama : add OpenELM support (#7359)

* Initial OpenELM support (270M only so far)

* Fill out missing entries in llama_model_type_name

* fixup! Initial OpenELM support (270M only so far)

Fix formatting

* llama : support all OpenELM models

* llama : add variable GQA and variable FFN sizes

Some metadata keys can now also be arrays to support setting
their value per-layer for models like OpenELM.

* llama : minor spacing changes

Co-authored-by: Georgi Gerganov 

* llama : use std::array for per-layer hparams

* llama : fix save/load state

* llama : do not print hparams for vocab-only models

* llama : handle n_head == 0

* llama : use const ref for print_f and fix division by zero

* llama : fix t5 uses of n_head and n_ff

* llama : minor comment

---------

Co-authored-by: Francis Couture-Harpin 
Co-authored-by: Georgi Gerganov 
---
 convert_hf_to_gguf.py          | 157 ++++++--
 gguf-py/gguf/constants.py      |  15 +
 gguf-py/gguf/gguf_writer.py    |  21 +-
 gguf-py/gguf/tensor_mapping.py |  16 +-
 src/llama.cpp                  | 641 ++++++++++++++++++++++++++-------
 5 files changed, 675 insertions(+), 175 deletions(-)

diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py
index a1d165023ce73..bdc336644e626 100755
--- a/convert_hf_to_gguf.py
+++ b/convert_hf_to_gguf.py
@@ -13,7 +13,7 @@
 from enum import IntEnum
 from pathlib import Path
 from hashlib import sha256
-from typing import TYPE_CHECKING, Any, Callable, ContextManager, Iterable, Iterator, Sequence, TypeVar, cast
+from typing import TYPE_CHECKING, Any, Callable, ContextManager, Iterable, Iterator, Literal, Sequence, TypeVar, cast
 
 import math
 import numpy as np
@@ -677,6 +677,51 @@ def _set_vocab_llama_hf(self):
         special_vocab = gguf.SpecialVocab(self.dir_model, n_vocab=len(tokens))
         special_vocab.add_to_gguf(self.gguf_writer)
 
+    def _set_vocab_builtin(self, model_name: Literal["gpt-neox", "llama-spm"], vocab_size: int):
+        tokenizer_path = Path(sys.path[0]) / "models" / f"ggml-vocab-{model_name}.gguf"
+        logger.warning(f"Using tokenizer from '{os.path.relpath(tokenizer_path, os.getcwd())}'")
+        vocab_reader = gguf.GGUFReader(tokenizer_path, "r")
+
+        default_pre = "mpt" if model_name == "gpt-neox" else "default"
+
+        field = vocab_reader.get_field(gguf.Keys.Tokenizer.MODEL)
+        assert field  # tokenizer model
+        self.gguf_writer.add_tokenizer_model(bytes(field.parts[-1]).decode("utf-8"))
+
+        field = vocab_reader.get_field(gguf.Keys.Tokenizer.PRE)
+        self.gguf_writer.add_tokenizer_pre(bytes(field.parts[-1]).decode("utf-8") if field else default_pre)
+
+        field = vocab_reader.get_field(gguf.Keys.Tokenizer.LIST)
+        assert field  # token list
+        self.gguf_writer.add_token_list([bytes(field.parts[i]) for i in field.data][:vocab_size])
+
+        if model_name == "llama-spm":
+            field = vocab_reader.get_field(gguf.Keys.Tokenizer.SCORES)
+            assert field  # token scores
+            self.gguf_writer.add_token_scores([field.parts[i].tolist()[0] for i in field.data][:vocab_size])
+
+        field = vocab_reader.get_field(gguf.Keys.Tokenizer.TOKEN_TYPE)
+        assert field  # token types
+        self.gguf_writer.add_token_types([field.parts[i].tolist()[0] for i in field.data][:vocab_size])
+
+        if model_name != "llama-spm":
+            field = vocab_reader.get_field(gguf.Keys.Tokenizer.MERGES)
+            assert field  # token merges
+            self.gguf_writer.add_token_merges([bytes(field.parts[i]) for i in field.data])
+
+        if (field := vocab_reader.get_field(gguf.Keys.Tokenizer.BOS_ID)) is not None:
+            self.gguf_writer.add_bos_token_id(field.parts[-1].tolist()[0])
+        if (field := vocab_reader.get_field(gguf.Keys.Tokenizer.EOS_ID)) is not None:
+            self.gguf_writer.add_eos_token_id(field.parts[-1].tolist()[0])
+        if (field := vocab_reader.get_field(gguf.Keys.Tokenizer.UNK_ID)) is not None:
+            self.gguf_writer.add_unk_token_id(field.parts[-1].tolist()[0])
+        if (field := vocab_reader.get_field(gguf.Keys.Tokenizer.PAD_ID)) is not None:
+            self.gguf_writer.add_pad_token_id(field.parts[-1].tolist()[0])
+        if (field := vocab_reader.get_field(gguf.Keys.Tokenizer.ADD_BOS)) is not None:
+            self.gguf_writer.add_add_bos_token(field.parts[-1].tolist()[0])
+        if (field := vocab_reader.get_field(gguf.Keys.Tokenizer.ADD_EOS)) is not None:
+            self.gguf_writer.add_add_eos_token(field.parts[-1].tolist()[0])
+
 
 @Model.register("GPTNeoXForCausalLM")
 class GPTNeoXModel(Model):
@@ -2439,39 +2484,7 @@ def set_vocab(self):
             self._set_vocab_sentencepiece()
         else:
             # Use the GPT-NeoX tokenizer when no tokenizer files are present
-            tokenizer_path = Path(sys.path[0]) / "models" / "ggml-vocab-gpt-neox.gguf"
-            logger.warning(f"Using tokenizer from '{os.path.relpath(tokenizer_path, os.getcwd())}'")
-            neox_reader = gguf.GGUFReader(tokenizer_path, "r")
-
-            field = neox_reader.get_field(gguf.Keys.Tokenizer.MODEL)
-            self.gguf_writer.add_tokenizer_model(bytes(field.parts[-1]).decode("utf-8") if field else "gpt2")
-
-            field = neox_reader.get_field(gguf.Keys.Tokenizer.PRE)
-            self.gguf_writer.add_tokenizer_pre(bytes(field.parts[-1]).decode("utf-8") if field else "mpt")
-
-            field = neox_reader.get_field(gguf.Keys.Tokenizer.LIST)
-            assert field
-            self.gguf_writer.add_token_list([bytes(field.parts[i]) for i in field.data][:vocab_size])
-
-            field = neox_reader.get_field(gguf.Keys.Tokenizer.TOKEN_TYPE)
-            assert field
-            self.gguf_writer.add_token_types([field.parts[i].tolist()[0] for i in field.data][:vocab_size])
-
-            field = neox_reader.get_field(gguf.Keys.Tokenizer.MERGES)
-            assert field
-            self.gguf_writer.add_token_merges([bytes(field.parts[i]) for i in field.data])
-
-            field = neox_reader.get_field(gguf.Keys.Tokenizer.BOS_ID)
-            self.gguf_writer.add_bos_token_id(field.parts[-1].tolist()[0] if field else 1)
-
-            field = neox_reader.get_field(gguf.Keys.Tokenizer.EOS_ID)
-            self.gguf_writer.add_eos_token_id(field.parts[-1].tolist()[0] if field else 0)
-
-            field = neox_reader.get_field(gguf.Keys.Tokenizer.UNK_ID)
-            self.gguf_writer.add_unk_token_id(field.parts[-1].tolist()[0] if field else 0)
-
-            field = neox_reader.get_field(gguf.Keys.Tokenizer.PAD_ID)
-            self.gguf_writer.add_pad_token_id(field.parts[-1].tolist()[0] if field else 0)
+            self._set_vocab_builtin("gpt-neox", vocab_size)
 
     def set_gguf_parameters(self):
         d_model = self.find_hparam(["hidden_size",       "d_model"])
@@ -2623,6 +2636,82 @@ def set_vocab(self, *args, **kwargs):
         self.gguf_writer.add_add_eos_token(True)
 
 
+@Model.register("OpenELMForCausalLM")
+class OpenELMModel(Model):
+    model_arch = gguf.MODEL_ARCH.OPENELM
+
+    @staticmethod
+    def _make_divisible(v: float | int, divisor: int) -> int:
+        # ref: https://huggingface.co/apple/OpenELM-270M-Instruct/blob/eb111ff2e6724348e5b905984063d4064d4bc579/configuration_openelm.py#L34-L38
+        new_v = max(divisor, int(v + divisor / 2) // divisor * divisor)
+        # Make sure that round down does not go down by more than 10%.
+        if new_v < 0.9 * v:
+            new_v += divisor
+        return new_v
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+
+        ffn_multipliers: list[float] = self.hparams["ffn_multipliers"]
+        ffn_dim_divisor: int = self.hparams["ffn_dim_divisor"]
+        self._n_embd: int = self.hparams["model_dim"]
+        self._num_kv_heads: list[int] = self.hparams["num_kv_heads"]
+        self._num_query_heads: list[int] = self.hparams["num_query_heads"]
+        self._ffn_dims: list[int] = [
+            OpenELMModel._make_divisible(multiplier * self._n_embd, ffn_dim_divisor)
+            for multiplier in ffn_multipliers
+        ]
+        assert isinstance(self._num_kv_heads, list) and isinstance(self._num_kv_heads[0], int)
+        assert isinstance(self._num_query_heads, list) and isinstance(self._num_query_heads[0], int)
+
+    # Uses the tokenizer from meta-llama/Llama-2-7b-hf
+    def set_vocab(self):
+        try:
+            self._set_vocab_sentencepiece()
+        except FileNotFoundError:
+            self._set_vocab_builtin("llama-spm", self.hparams["vocab_size"])
+
+    def set_gguf_parameters(self):
+        n_embd = self._n_embd
+        head_dim = self.hparams["head_dim"]
+        rot_pct = 1.0
+        assert self.block_count == len(self._num_kv_heads)
+        assert self.block_count == len(self._num_query_heads)
+        assert self.block_count == len(self._ffn_dims)
+
+        self.gguf_writer.add_name(self.dir_model.name if self.model_name is None else self.model_name)
+        self.gguf_writer.add_block_count(self.block_count)
+        self.gguf_writer.add_context_length(self.hparams["max_context_length"])
+        self.gguf_writer.add_embedding_length(n_embd)
+        self.gguf_writer.add_feed_forward_length(self._ffn_dims)
+        self.gguf_writer.add_head_count(self._num_query_heads)
+        self.gguf_writer.add_head_count_kv(self._num_kv_heads)
+        self.gguf_writer.add_rope_freq_base(self.hparams["rope_freq_constant"])
+        # https://huggingface.co/apple/OpenELM-270M-Instruct/blob/c401df2/modeling_openelm.py#L30
+        self.gguf_writer.add_layer_norm_rms_eps(1e-6)
+        self.gguf_writer.add_rope_dimension_count(int(rot_pct * head_dim))
+        self.gguf_writer.add_key_length(head_dim)
+        self.gguf_writer.add_value_length(head_dim)
+        self.gguf_writer.add_file_type(self.ftype)
+
+    def find_hparam(self, keys: Iterable[str], optional: bool = False) -> Any:
+        if "n_layers" in keys:
+            return self.hparams["num_transformer_layers"]
+
+        return super().find_hparam(keys, optional)
+
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+
+        # split ff
+        if bid is not None and name == f"transformer.layers.{bid}.ffn.proj_1.weight":
+            ff_dim = self._ffn_dims[bid]
+            yield (self.format_tensor_name(gguf.MODEL_TENSOR.FFN_GATE, bid), data_torch[:ff_dim])
+            yield (self.format_tensor_name(gguf.MODEL_TENSOR.FFN_UP, bid), data_torch[ff_dim:])
+            return
+
+        yield (self.map_tensor_name(name), data_torch)
+
+
 @Model.register("ArcticForCausalLM")
 class ArcticModel(Model):
     model_arch = gguf.MODEL_ARCH.ARCTIC
diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py
index 419f10cee74a7..d78fb1e44b29e 100644
--- a/gguf-py/gguf/constants.py
+++ b/gguf-py/gguf/constants.py
@@ -160,6 +160,7 @@ class MODEL_ARCH(IntEnum):
     COMMAND_R    = auto()
     DBRX         = auto()
     OLMO         = auto()
+    OPENELM      = auto()
     ARCTIC       = auto()
     DEEPSEEK2    = auto()
     BITNET       = auto()
@@ -285,6 +286,7 @@ class MODEL_TENSOR(IntEnum):
     MODEL_ARCH.COMMAND_R:      "command-r",
     MODEL_ARCH.DBRX:           "dbrx",
     MODEL_ARCH.OLMO:           "olmo",
+    MODEL_ARCH.OPENELM:        "openelm",
     MODEL_ARCH.ARCTIC:         "arctic",
     MODEL_ARCH.DEEPSEEK2:      "deepseek2",
     MODEL_ARCH.BITNET:         "bitnet",
@@ -861,6 +863,19 @@ class MODEL_TENSOR(IntEnum):
         MODEL_TENSOR.FFN_DOWN,
         MODEL_TENSOR.FFN_UP,
     ],
+    MODEL_ARCH.OPENELM: [
+        MODEL_TENSOR.TOKEN_EMBD,
+        MODEL_TENSOR.OUTPUT_NORM,
+        MODEL_TENSOR.ATTN_NORM,
+        MODEL_TENSOR.ATTN_QKV,
+        MODEL_TENSOR.ATTN_Q_NORM,
+        MODEL_TENSOR.ATTN_K_NORM,
+        MODEL_TENSOR.ATTN_OUT,
+        MODEL_TENSOR.FFN_NORM,
+        MODEL_TENSOR.FFN_GATE,
+        MODEL_TENSOR.FFN_DOWN,
+        MODEL_TENSOR.FFN_UP,
+    ],
     MODEL_ARCH.ARCTIC: [
         MODEL_TENSOR.TOKEN_EMBD,
         MODEL_TENSOR.OUTPUT_NORM,
diff --git a/gguf-py/gguf/gguf_writer.py b/gguf-py/gguf/gguf_writer.py
index 75a8b2636a6a2..cf95541629032 100644
--- a/gguf-py/gguf/gguf_writer.py
+++ b/gguf-py/gguf/gguf_writer.py
@@ -480,8 +480,11 @@ def add_block_count(self, length: int) -> None:
     def add_leading_dense_block_count(self, length: int) -> None:
         self.add_uint32(Keys.LLM.LEADING_DENSE_BLOCK_COUNT.format(arch=self.arch), length)
 
-    def add_feed_forward_length(self, length: int) -> None:
-        self.add_uint32(Keys.LLM.FEED_FORWARD_LENGTH.format(arch=self.arch), length)
+    def add_feed_forward_length(self, length: int | Sequence[int]) -> None:
+        if isinstance(length, int):
+            self.add_uint32(Keys.LLM.FEED_FORWARD_LENGTH.format(arch=self.arch), length)
+        else:
+            self.add_array(Keys.LLM.FEED_FORWARD_LENGTH.format(arch=self.arch), length)
 
     def add_expert_feed_forward_length(self, length: int) -> None:
         self.add_uint32(Keys.LLM.EXPERT_FEED_FORWARD_LENGTH.format(arch=self.arch), length)
@@ -495,11 +498,17 @@ def add_parallel_residual(self, use: bool) -> None:
     def add_decoder_start_token_id(self, id: int) -> None:
         self.add_uint32(Keys.LLM.DECODER_START_TOKEN_ID.format(arch=self.arch), id)
 
-    def add_head_count(self, count: int) -> None:
-        self.add_uint32(Keys.Attention.HEAD_COUNT.format(arch=self.arch), count)
+    def add_head_count(self, count: int | Sequence[int]) -> None:
+        if isinstance(count, int):
+            self.add_uint32(Keys.Attention.HEAD_COUNT.format(arch=self.arch), count)
+        else:
+            self.add_array(Keys.Attention.HEAD_COUNT.format(arch=self.arch), count)
 
-    def add_head_count_kv(self, count: int) -> None:
-        self.add_uint32(Keys.Attention.HEAD_COUNT_KV.format(arch=self.arch), count)
+    def add_head_count_kv(self, count: int | Sequence[int]) -> None:
+        if isinstance(count, int):
+            self.add_uint32(Keys.Attention.HEAD_COUNT_KV.format(arch=self.arch), count)
+        else:
+            self.add_array(Keys.Attention.HEAD_COUNT_KV.format(arch=self.arch), count)
 
     def add_key_length(self, length: int) -> None:
         self.add_uint32(Keys.Attention.KEY_LENGTH.format(arch=self.arch), length)
diff --git a/gguf-py/gguf/tensor_mapping.py b/gguf-py/gguf/tensor_mapping.py
index 20e28423b9a99..6054f61595e13 100644
--- a/gguf-py/gguf/tensor_mapping.py
+++ b/gguf-py/gguf/tensor_mapping.py
@@ -24,6 +24,7 @@ class TensorNameMap:
             "backbone.embedding",                        # mamba
             "backbone.embeddings",                       # mamba-hf
             "transformer.in_out_embed",                  # Grok
+            "transformer.token_embeddings",              # openelm
             "shared",                                    # t5
         ),
 
@@ -37,6 +38,7 @@ class TensorNameMap:
             "word_embeddings_layernorm",  # bloom
             "embeddings.LayerNorm",       # bert
             "emb_ln",                     # nomic-bert
+            "transformer.norm",           # openelm
         ),
 
         # Position embeddings
@@ -69,6 +71,7 @@ class TensorNameMap:
             "model.norm_f",                            # mamba-qbert
             "backbone.norm_f",                         # mamba
             "transformer.rms_norm",                    # Grok
+            "transformer.norm",                        # openelm
         ),
 
         # Rope frequencies
@@ -98,6 +101,7 @@ class TensorNameMap:
             "backbone.layers.{bid}.norm",                           # mamba
             "transformer.decoder_layer.{bid}.rms_norm",             # Grok
             "transformer.blocks.{bid}.norm_attn_norm.norm_1",       # dbrx
+            "transformer.layers.{bid}.attn_norm",                   # openelm
         ),
 
         # Attention norm 2
@@ -119,7 +123,8 @@ class TensorNameMap:
             "h.{bid}.attn.c_attn",                                                 # gpt2
             "transformer.h.{bid}.mixer.Wqkv",                                      # phi2
             "encoder.layers.{bid}.attn.Wqkv",                                      # nomic-bert
-            "model.layers.{bid}.self_attn.qkv_proj"                                # phi3
+            "model.layers.{bid}.self_attn.qkv_proj",                               # phi3
+            "transformer.layers.{bid}.attn.qkv_proj",                              # openelm
         ),
 
         # Attention query
@@ -177,6 +182,7 @@ class TensorNameMap:
             "encoder.layers.{bid}.attn.out_proj",                           # nomic-bert
             "transformer.decoder_layer.{bid}.multi_head_attention.linear",  # Grok
             "transformer.blocks.{bid}.norm_attn_norm.attn.out_proj",        # dbrx
+            "transformer.layers.{bid}.attn.out_proj",                       # openelm
         ),
 
         # Attention output norm
@@ -212,6 +218,7 @@ class TensorNameMap:
             "h.{bid}.ln_2",                                                  # gpt2
             "model.layers.{bid}.ffn_norm",                                   # internlm2
             "transformer.decoder_layer.{bid}.rms_norm_2",                    # Grok
+            "transformer.layers.{bid}.ffn_norm",                             # openelm
         ),
 
         # Post feed-forward norm
@@ -327,6 +334,7 @@ class TensorNameMap:
             "encoder.layers.{bid}.mlp.fc2",                           # nomic-bert
             "model.layers.{bid}.mlp.c_proj",                          # starcoder2
             "encoder.layer.{bid}.mlp.wo",                             # jina-bert-v2
+            "transformer.layers.{bid}.ffn.proj_2",                    # openelm
             "model.layers.{bid}.residual_mlp.w2",                     # arctic
             "encoder.layer.{bid}.mlp.down_layer",                     # jina-bert-v2
         ),
@@ -348,7 +356,8 @@ class TensorNameMap:
             "model.layers.{bid}.self_attn.q_layernorm",                       # persimmon
             "model.layers.{bid}.self_attn.q_norm",                            # cohere
             "transformer.blocks.{bid}.attn.q_ln",                             # sea-lion
-            "encoder.layer.{bid}.attention.self.layer_norm_q"                 # jina-bert-v2
+            "encoder.layer.{bid}.attention.self.layer_norm_q",                # jina-bert-v2
+            "transformer.layers.{bid}.attn.q_norm",                           # openelm
         ),
 
         MODEL_TENSOR.ATTN_K_NORM: (
@@ -356,7 +365,8 @@ class TensorNameMap:
             "model.layers.{bid}.self_attn.k_layernorm",                       # persimmon
             "model.layers.{bid}.self_attn.k_norm",                            # cohere
             "transformer.blocks.{bid}.attn.k_ln",                             # sea-lion
-            "encoder.layer.{bid}.attention.self.layer_norm_k"                 # jina-bert-v2
+            "encoder.layer.{bid}.attention.self.layer_norm_k",                # jina-bert-v2
+            "transformer.layers.{bid}.attn.k_norm",                           # openelm
         ),
 
         MODEL_TENSOR.ROPE_FREQS: (
diff --git a/src/llama.cpp b/src/llama.cpp
index 1fe2b9f79d320..721b8f4e5931b 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -104,8 +104,10 @@
 #define LLAMA_ATTRIBUTE_FORMAT(...)
 #endif
 
+// bump if necessary
 #define LLAMA_MAX_NODES   8192
-#define LLAMA_MAX_EXPERTS 160
+#define LLAMA_MAX_LAYERS  256
+#define LLAMA_MAX_EXPERTS 160  // DeepSeekV2
 
 //
 // logging
@@ -224,6 +226,7 @@ enum llm_arch {
     LLM_ARCH_COMMAND_R,
     LLM_ARCH_DBRX,
     LLM_ARCH_OLMO,
+    LLM_ARCH_OPENELM,
     LLM_ARCH_ARCTIC,
     LLM_ARCH_DEEPSEEK2,
     LLM_ARCH_BITNET,
@@ -266,6 +269,7 @@ static const std::map LLM_ARCH_NAMES = {
     { LLM_ARCH_COMMAND_R,       "command-r"    },
     { LLM_ARCH_DBRX,            "dbrx"         },
     { LLM_ARCH_OLMO,            "olmo"         },
+    { LLM_ARCH_OPENELM,         "openelm"      },
     { LLM_ARCH_ARCTIC,          "arctic"       },
     { LLM_ARCH_DEEPSEEK2,       "deepseek2"    },
     { LLM_ARCH_BITNET,          "bitnet"       },
@@ -1134,6 +1138,22 @@ static const std::map> LLM_TENSOR_NA
             { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
         },
     },
+    {
+        LLM_ARCH_OPENELM,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,      "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM,     "output_norm" },
+            { LLM_TENSOR_ATTN_NORM,       "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_QKV,        "blk.%d.attn_qkv" },
+            { LLM_TENSOR_ATTN_Q_NORM,     "blk.%d.attn_q_norm" },
+            { LLM_TENSOR_ATTN_K_NORM,     "blk.%d.attn_k_norm" },
+            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output" },
+            { LLM_TENSOR_FFN_NORM,        "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_GATE,        "blk.%d.ffn_gate" },
+            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
+            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
+        },
+    },
     {
         LLM_ARCH_ARCTIC,
         {
@@ -2052,8 +2072,10 @@ enum e_model {
     MODEL_160M,
     MODEL_220M,
     MODEL_250M,
+    MODEL_270M,
     MODEL_335M,
     MODEL_410M,
+    MODEL_450M,
     MODEL_770M,
     MODEL_780M,
     MODEL_0_5B,
@@ -2108,19 +2130,20 @@ struct llama_hparams {
     uint32_t n_vocab;
     uint32_t n_ctx_train; // context size the model was trained on
     uint32_t n_embd;
-    uint32_t n_head;
-    uint32_t n_head_kv;
     uint32_t n_layer;
     uint32_t n_rot;
     uint32_t n_swa = 0; // sliding window attention (SWA)
     uint32_t n_embd_head_k; // dimension of keys (d_k). d_q is assumed to be the same, but there are n_head q heads, and only n_head_kv k-v heads
     uint32_t n_embd_head_v; // dimension of values (d_v) aka n_embd_head
-    uint32_t n_ff;
     uint32_t n_expert = 0;
     uint32_t n_expert_used = 0;
     uint32_t n_vocab_type = 0; // for BERT-style token types
     uint32_t n_rel_attn_bkts = 0;
 
+    std::array n_head_arr;
+    std::array n_head_kv_arr;
+    std::array n_ff_arr;
+
     uint32_t n_layer_dense_lead = 0;
     uint32_t n_lora_q = 0;
     uint32_t n_lora_kv = 0;
@@ -2168,17 +2191,18 @@ struct llama_hparams {
         if (this->n_vocab       != other.n_vocab)       return true;
         if (this->n_ctx_train   != other.n_ctx_train)   return true;
         if (this->n_embd        != other.n_embd)        return true;
-        if (this->n_head        != other.n_head)        return true;
-        if (this->n_head_kv     != other.n_head_kv)     return true;
         if (this->n_layer       != other.n_layer)       return true;
         if (this->n_rot         != other.n_rot)         return true;
         if (this->n_swa         != other.n_swa)         return true;
         if (this->n_embd_head_k != other.n_embd_head_k) return true;
         if (this->n_embd_head_v != other.n_embd_head_v) return true;
-        if (this->n_ff          != other.n_ff)          return true;
         if (this->n_expert      != other.n_expert)      return true;
         if (this->n_expert_used != other.n_expert_used) return true;
 
+        if (this->n_head_arr    != other.n_head_arr)    return true;
+        if (this->n_head_kv_arr != other.n_head_kv_arr) return true;
+        if (this->n_ff_arr      != other.n_ff_arr)      return true;
+
         if (this->n_rel_attn_bkts    != other.n_rel_attn_bkts)    return true;
         if (this->n_layer_dense_lead != other.n_layer_dense_lead) return true;
         if (this->n_lora_q           != other.n_lora_q)           return true;
@@ -2210,18 +2234,53 @@ struct llama_hparams {
         return false;
     }
 
-    uint32_t n_gqa() const {
+    uint32_t n_head(uint32_t il = 0) const {
+        if (il < n_layer) {
+            return n_head_arr[il];
+        }
+
+        GGML_ASSERT(false);
+        return 0;
+    }
+
+    uint32_t n_head_kv(uint32_t il = 0) const {
+        if (il < n_layer) {
+            return n_head_kv_arr[il];
+        }
+
+        GGML_ASSERT(false);
+        return 0;
+    }
+
+    uint32_t n_ff(uint32_t il = 0) const {
+        if (il < n_layer) {
+            return n_ff_arr[il];
+        }
+
+        GGML_ASSERT(false);
+        return 0;
+    }
+
+    uint32_t n_gqa(uint32_t il = 0) const {
+        const uint32_t n_head    = this->n_head(il);
+        const uint32_t n_head_kv = this->n_head_kv(il);
+
         if (n_head_kv == 0) {
             return 0;
         }
+
         return n_head/n_head_kv;
     }
 
-    uint32_t n_embd_k_gqa() const { // dimension of key embeddings across all k-v heads
+    uint32_t n_embd_k_gqa(uint32_t il = 0) const { // dimension of key embeddings across all k-v heads
+        const uint32_t n_head_kv = this->n_head_kv(il);
+
         return n_embd_head_k * n_head_kv;
     }
 
-    uint32_t n_embd_v_gqa() const { // dimension of value embeddings across all k-v heads
+    uint32_t n_embd_v_gqa(uint32_t il = 0) const { // dimension of value embeddings across all k-v heads
+        const uint32_t n_head_kv = this->n_head_kv(il);
+
         return n_embd_head_v * n_head_kv;
     }
 
@@ -2238,6 +2297,8 @@ struct llama_hparams {
     }
 };
 
+static_assert(std::is_trivially_copyable::value, "llama_hparams must be trivially copyable");
+
 struct llama_cparams {
     uint32_t n_ctx;           // context size used during inference
     uint32_t n_batch;
@@ -2857,9 +2918,7 @@ static bool llama_kv_cache_init(
 
     const struct llama_hparams & hparams = model.hparams;
 
-    const uint32_t n_embd_k_gqa = hparams.n_embd_k_gqa() + hparams.n_embd_k_s();
-    const uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa() + hparams.n_embd_v_s();
-    const int64_t  n_layer      = hparams.n_layer;
+    const int64_t  n_layer = hparams.n_layer;
 
     cache.has_shift = false;
 
@@ -2867,13 +2926,6 @@ static bool llama_kv_cache_init(
     cache.recurrent = model.arch == LLM_ARCH_MAMBA;
     cache.v_trans   = !cparams.flash_attn;
 
-    // TODO: support mixed recurrent Transformer architectures
-    // NOTE: (!a || b) is a logical implication (a -> b)
-    GGML_ASSERT(!cache.recurrent || n_embd_k_gqa == hparams.n_embd_k_s());
-    GGML_ASSERT(!cache.recurrent || n_embd_v_gqa == hparams.n_embd_v_s());
-    GGML_ASSERT( cache.recurrent || n_embd_k_gqa == hparams.n_embd_k_gqa());
-    GGML_ASSERT( cache.recurrent || n_embd_v_gqa == hparams.n_embd_v_gqa());
-
     cache.head = 0;
     cache.size = kv_size;
     cache.used = 0;
@@ -2923,6 +2975,9 @@ static bool llama_kv_cache_init(
     cache.v_l.reserve(n_layer);
 
     for (int i = 0; i < (int) n_layer; i++) {
+        const uint32_t n_embd_k_gqa = hparams.n_embd_k_gqa(i) + hparams.n_embd_k_s();
+        const uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa(i) + hparams.n_embd_v_s();
+
         struct ggml_context * ctx = offload ? ctx_map.at(model.buft_layer[i].buft) : cache.ctxs.front();
         ggml_tensor * k = ggml_new_tensor_1d(ctx, type_k, n_embd_k_gqa*kv_size);
         ggml_tensor * v = ggml_new_tensor_1d(ctx, type_v, n_embd_v_gqa*kv_size);
@@ -3798,9 +3853,9 @@ struct llama_model_loader {
     bool get_arr(const std::string & key, std::vector & result, const bool required = true) {
         const int kid = gguf_find_key(meta, key.c_str());
 
-        if (kid < 0) {
+        if (kid < 0 || gguf_get_kv_type(meta, kid) != GGUF_TYPE_ARRAY) {
             if (required) {
-                throw std::runtime_error(format("key not found in model: %s", key.c_str()));
+                throw std::runtime_error(format("array key not found in model: %s", key.c_str()));
             }
             return false;
         }
@@ -3808,22 +3863,53 @@ struct llama_model_loader {
         struct GGUFMeta::ArrayInfo arr_info =
             GGUFMeta::GKV::get_kv(meta, kid);
 
-        if (arr_info.gt != GGUF_TYPE_FLOAT32 && arr_info.gt != GGUF_TYPE_INT32) {
-            throw std::runtime_error(format("%s is not a float32 or int32 array", key.c_str()));
+        switch (arr_info.gt) {
+            case GGUF_TYPE_FLOAT32: GGML_ASSERT((std::is_same::value)); break;
+            case GGUF_TYPE_INT32:   GGML_ASSERT(
+                                            (std::is_same::value) ||
+                                            (std::is_same::value));  break;
+            default:
+                throw std::runtime_error(format("%s is not a float32, int32 array", key.c_str()));
         }
 
-        // GGML_ASSERT(gguf_type_size(arr_info.gt) == sizeof(T));
-        GGML_ASSERT((arr_info.gt != GGUF_TYPE_FLOAT32 || std::is_same::value));
-        GGML_ASSERT((arr_info.gt != GGUF_TYPE_INT32   || std::is_same::value));
-
         result.resize(arr_info.length);
         result.assign((const T*)arr_info.data, (const T *)arr_info.data + arr_info.length);
 
         return true;
     }
 
+    template
+    bool get_arr(const std::string & key, std::array & result, const bool required = true) {
+        const int kid = gguf_find_key(meta, key.c_str());
+
+        if (kid < 0 || gguf_get_kv_type(meta, kid) != GGUF_TYPE_ARRAY) {
+            if (required) {
+                throw std::runtime_error(format("array key not found in model: %s", key.c_str()));
+            }
+            return false;
+        }
+
+        struct GGUFMeta::ArrayInfo arr_info =
+            GGUFMeta::GKV::get_kv(meta, kid);
+
+        switch (arr_info.gt) {
+            case GGUF_TYPE_FLOAT32: GGML_ASSERT((std::is_same::value)); break;
+            case GGUF_TYPE_INT32:   GGML_ASSERT(
+                                            (std::is_same::value) ||
+                                            (std::is_same::value));  break;
+            default:
+                throw std::runtime_error(format("%s is not a float32, int32 array", key.c_str()));
+        }
+
+        GGML_ASSERT(arr_info.length <= N_MAX);
+
+        std::copy((const T*)arr_info.data, (const T *)arr_info.data + arr_info.length, result.begin());
+
+        return true;
+    }
+
     template
-    bool get_arr(const enum llm_kv kid, T& result, const bool required = true) {
+    bool get_arr(const enum llm_kv kid, T & result, const bool required = true) {
         return get_arr(llm_kv(kid), result, required);
     }
 
@@ -3848,6 +3934,50 @@ struct llama_model_loader {
         return get_key(llm_kv(kid), result, required);
     }
 
+    // get array of n <= N_MAX elements, or a single element repeated n times
+    template
+    bool get_key_or_arr(const std::string & key, std::array & result, uint32_t n, const bool required = true) {
+        GGML_ASSERT(n <= N_MAX);
+
+        const int kid = gguf_find_key(meta, key.c_str());
+
+        if (kid < 0) {
+            if (required) {
+                throw std::runtime_error(format("key not found in model: %s", key.c_str()));
+            }
+            return false;
+        }
+
+        if (gguf_get_kv_type(meta, kid) == GGUF_TYPE_ARRAY) {
+            struct GGUFMeta::ArrayInfo arr_info =
+                GGUFMeta::GKV::get_kv(meta, kid);
+
+            if (n != arr_info.length) {
+                throw std::runtime_error(format("key %s has wrong array length; expected %u, got %u", key.c_str(), n, (uint32_t) arr_info.length));
+            }
+
+            return get_arr(key, result, required);
+        } else {
+            T value;
+
+            bool ok = get_key(key, value, required);
+            if (!ok) {
+                return false;
+            }
+
+            for (uint32_t i = 0; i < n; i++) {
+                result[i] = value;
+            }
+
+            return true;
+        }
+    }
+
+    template
+    bool get_key_or_arr(const enum llm_kv kid, T & result, uint32_t n, const bool required = true) {
+        return get_key_or_arr(llm_kv(kid), result, n, required);
+    }
+
     std::string get_arch_name() const {
         return arch_name;
     }
@@ -4340,8 +4470,10 @@ static const char * llama_model_type_name(e_model type) {
         case MODEL_160M:          return "160M";
         case MODEL_220M:          return "220M";
         case MODEL_250M:          return "250M";
+        case MODEL_270M:          return "270M";
         case MODEL_335M:          return "335M";
         case MODEL_410M:          return "410M";
+        case MODEL_450M:          return "450M";
         case MODEL_770M:          return "770M";
         case MODEL_780M:          return "780M";
         case MODEL_0_5B:          return "0.5B";
@@ -4425,20 +4557,18 @@ static void llm_load_hparams(
     ml.get_key(LLM_KV_GENERAL_NAME, model.name, false);
 
     // get hparams kv
-    ml.get_key(LLM_KV_VOCAB_SIZE,           hparams.n_vocab,       false) || ml.get_arr_n(LLM_KV_TOKENIZER_LIST, hparams.n_vocab);
+    ml.get_key(LLM_KV_VOCAB_SIZE, hparams.n_vocab, false) || ml.get_arr_n(LLM_KV_TOKENIZER_LIST, hparams.n_vocab);
 
     // everything past this point is not vocab-related
     if (hparams.vocab_only) {
         return;
     }
 
-    ml.get_key(LLM_KV_CONTEXT_LENGTH,       hparams.n_ctx_train);
-    ml.get_key(LLM_KV_EMBEDDING_LENGTH,     hparams.n_embd);
-    ml.get_key(LLM_KV_FEED_FORWARD_LENGTH,  hparams.n_ff);
-    ml.get_key(LLM_KV_ATTENTION_HEAD_COUNT, hparams.n_head);
-    ml.get_key(LLM_KV_BLOCK_COUNT,          hparams.n_layer);
-    ml.get_key(LLM_KV_EXPERT_COUNT,         hparams.n_expert,      false);
-    ml.get_key(LLM_KV_EXPERT_USED_COUNT,    hparams.n_expert_used, false);
+    ml.get_key(LLM_KV_CONTEXT_LENGTH,    hparams.n_ctx_train);
+    ml.get_key(LLM_KV_EMBEDDING_LENGTH,  hparams.n_embd);
+    ml.get_key(LLM_KV_BLOCK_COUNT,       hparams.n_layer);
+    ml.get_key(LLM_KV_EXPERT_COUNT,      hparams.n_expert,      false);
+    ml.get_key(LLM_KV_EXPERT_USED_COUNT, hparams.n_expert_used, false);
 
     GGML_ASSERT(hparams.n_expert <= LLAMA_MAX_EXPERTS);
     GGML_ASSERT(hparams.n_expert_used <= hparams.n_expert);
@@ -4448,9 +4578,18 @@ static void llm_load_hparams(
         GGML_ASSERT(hparams.n_expert_used == 0);
     }
 
+    // zero-out the per-layer hparams
+    std::fill(hparams.n_head_arr.begin(),    hparams.n_head_arr.end(),    0);
+    std::fill(hparams.n_head_kv_arr.begin(), hparams.n_head_kv_arr.end(), 0);
+    std::fill(hparams.n_ff_arr.begin(),      hparams.n_ff_arr.end(),      0);
+
+    ml.get_key_or_arr(LLM_KV_FEED_FORWARD_LENGTH,  hparams.n_ff_arr,   hparams.n_layer);
+    ml.get_key_or_arr(LLM_KV_ATTENTION_HEAD_COUNT, hparams.n_head_arr, hparams.n_layer);
+
     // n_head_kv is optional, default to n_head
-    hparams.n_head_kv = hparams.n_head;
-    ml.get_key(LLM_KV_ATTENTION_HEAD_COUNT_KV, hparams.n_head_kv, false);
+    hparams.n_head_kv_arr = hparams.n_head_arr;
+
+    ml.get_key_or_arr(LLM_KV_ATTENTION_HEAD_COUNT_KV, hparams.n_head_kv_arr, hparams.n_layer, false);
 
     bool rope_finetuned = false;
     ml.get_key(LLM_KV_ROPE_SCALING_FINETUNED, rope_finetuned, false);
@@ -4478,26 +4617,31 @@ static void llm_load_hparams(
 
     ml.get_key(LLM_KV_ROPE_SCALING_ATTN_FACTOR, hparams.rope_attn_factor, false);
 
-    // sanity check for n_rot (optional)
-    {
-        hparams.n_rot = (hparams.n_head == 0) ? 0 : hparams.n_embd / hparams.n_head;
+    // non-transformer models do not have attention heads
+    if (hparams.n_head() > 0) {
+        // sanity check for n_rot (optional)
+        hparams.n_rot = hparams.n_embd / hparams.n_head();
 
         ml.get_key(LLM_KV_ROPE_DIMENSION_COUNT, hparams.n_rot, false);
 
         if (model.arch == LLM_ARCH_LLAMA || model.arch == LLM_ARCH_FALCON) {
-            if (hparams.n_rot != hparams.n_embd / hparams.n_head) {
-                throw std::runtime_error(format("invalid n_rot: %u, expected %u", hparams.n_rot, hparams.n_embd / hparams.n_head));
+            if (hparams.n_rot != hparams.n_embd / hparams.n_head()) {
+                throw std::runtime_error(format("invalid n_rot: %u, expected %u", hparams.n_rot, hparams.n_embd / hparams.n_head()));
             }
         }
         // gpt-neox n_rot = rotary_pct * (n_embd / n_head)
         // gpt-j n_rot = rotary_dim
-    }
 
-    hparams.n_embd_head_k = (hparams.n_head == 0) ? 0 : hparams.n_embd / hparams.n_head;
-    ml.get_key(LLM_KV_ATTENTION_KEY_LENGTH, hparams.n_embd_head_k, false);
+        hparams.n_embd_head_k = hparams.n_embd / hparams.n_head();
+        ml.get_key(LLM_KV_ATTENTION_KEY_LENGTH, hparams.n_embd_head_k, false);
 
-    hparams.n_embd_head_v = (hparams.n_head == 0) ? 0 : hparams.n_embd / hparams.n_head;
-    ml.get_key(LLM_KV_ATTENTION_VALUE_LENGTH, hparams.n_embd_head_v, false);
+        hparams.n_embd_head_v = hparams.n_embd / hparams.n_head();
+        ml.get_key(LLM_KV_ATTENTION_VALUE_LENGTH, hparams.n_embd_head_v, false);
+    } else {
+        hparams.n_rot = 0;
+        hparams.n_embd_head_k = 0;
+        hparams.n_embd_head_v = 0;
+    }
 
     // arch-specific KVs
     switch (model.arch) {
@@ -4521,7 +4665,7 @@ static void llm_load_hparams(
                         case 40: model.type = e_model::MODEL_13B; break;
                         case 48: model.type = e_model::MODEL_34B; break;
                         case 60: model.type = e_model::MODEL_30B; break;
-                        case 80: model.type = hparams.n_head == hparams.n_head_kv ? e_model::MODEL_65B : e_model::MODEL_70B; break;
+                        case 80: model.type = hparams.n_head() == hparams.n_head_kv() ? e_model::MODEL_65B : e_model::MODEL_70B; break;
                         default: model.type = e_model::MODEL_UNKNOWN;
                     }
                 }
@@ -4690,7 +4834,7 @@ static void llm_load_hparams(
                 switch (hparams.n_layer) {
                     case 24: model.type = hparams.n_embd == 1024 ? e_model::MODEL_0_5B : e_model::MODEL_1B; break;
                     case 32: model.type = e_model::MODEL_7B; break;
-                    case 40: model.type = hparams.n_head == 20 ? e_model::MODEL_4B : e_model::MODEL_13B; break;
+                    case 40: model.type = hparams.n_head() == 20 ? e_model::MODEL_4B : e_model::MODEL_13B; break;
                     case 80: model.type = e_model::MODEL_70B; break;
                     default: model.type = e_model::MODEL_UNKNOWN;
                 }
@@ -4882,46 +5026,58 @@ static void llm_load_hparams(
                     default: model.type = e_model::MODEL_UNKNOWN;
                 }
             } break;
+        case LLM_ARCH_OPENELM:
+            {
+                ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
+
+                switch (hparams.n_layer) {
+                case 16: model.type = e_model::MODEL_270M; break;
+                case 20: model.type = e_model::MODEL_450M; break;
+                case 28: model.type = e_model::MODEL_1B; break;
+                case 36: model.type = e_model::MODEL_3B; break;
+                default: model.type = e_model::MODEL_UNKNOWN;
+                }
+            } break;
         case LLM_ARCH_GPTNEOX:
             {
                 ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps);
                 ml.get_key(LLM_KV_USE_PARALLEL_RESIDUAL, hparams.use_par_res);
                 switch (hparams.n_layer) {
                     case 6:
-                        switch (hparams.n_ff) {
+                        switch (hparams.n_ff()) {
                             case 512: model.type = e_model::MODEL_14M; break;
                             case 2048: model.type = e_model::MODEL_70M; break;
                             default: model.type = e_model::MODEL_UNKNOWN;
                         } break;
                     case 12:
-                        switch (hparams.n_ff) {
+                        switch (hparams.n_ff()) {
                             case 3072: model.type = e_model::MODEL_160M; break;
                             default: model.type = e_model::MODEL_UNKNOWN;
                         } break;
                     case 16:
-                        switch (hparams.n_ff) {
+                        switch (hparams.n_ff()) {
                             case 8192: model.type = e_model::MODEL_1B; break;
                             default: model.type = e_model::MODEL_UNKNOWN;
                         } break;
                     case 24:
-                        switch (hparams.n_ff) {
+                        switch (hparams.n_ff()) {
                             case 4096: model.type = e_model::MODEL_410M; break;
                             case 8192: model.type = e_model::MODEL_1_4B; break;
                             default: model.type = e_model::MODEL_UNKNOWN;
                         } break;
                     case 32:
-                        switch (hparams.n_ff) {
+                        switch (hparams.n_ff()) {
                             case 10240: model.type = e_model::MODEL_2_8B; break;
                             case 16384: model.type = e_model::MODEL_6_9B; break;
                             default: model.type = e_model::MODEL_UNKNOWN;
                         } break;
                     case 36:
-                        switch (hparams.n_ff) {
+                        switch (hparams.n_ff()) {
                             case 20480: model.type = e_model::MODEL_12B; break;
                             default: model.type = e_model::MODEL_UNKNOWN;
                         } break;
                     case 44:
-                        switch (hparams.n_ff) {
+                        switch (hparams.n_ff()) {
                             case 24576: model.type = e_model::MODEL_20B; break;
                             default: model.type = e_model::MODEL_UNKNOWN;
                         } break;
@@ -4984,13 +5140,13 @@ static void llm_load_hparams(
                     case 6:  model.type = e_model::MODEL_60M;  break; // t5-small
                     case 8:  model.type = e_model::MODEL_80M;  break; // flan-t5-small
                     case 12:
-                        switch (hparams.n_ff) {
+                        switch (hparams.n_ff()) {
                             case 3072: model.type = e_model::MODEL_220M; break; // t5-base
                             case 2048: model.type = e_model::MODEL_250M; break; // flan-t5-base
                             default: model.type = e_model::MODEL_UNKNOWN;
                         } break;
                     case 24:
-                        switch (hparams.n_ff) {
+                        switch (hparams.n_ff()) {
                             case 4096:  model.type = e_model::MODEL_770M; break; // t5-large
                             case 2816:  model.type = e_model::MODEL_780M; break; // flan-t5-large
                             case 16384: model.type = e_model::MODEL_3B;   break; // t5-3b
@@ -5533,44 +5689,78 @@ static void llm_load_print_meta(llama_model_loader & ml, llama_model & model) {
 
     const char * rope_scaling_type = LLAMA_ROPE_SCALING_TYPES.at(hparams.rope_scaling_type_train);
 
+    auto print_f = [](const std::function & f, uint32_t n) {
+        bool is_var = false;
+
+        std::vector v;
+        for (uint32_t i = 0; i < n; ++i) {
+            v.push_back(f(i));
+            if (v[i] != v[0]) {
+                is_var = true;
+            }
+        }
+
+        std::stringstream ss;
+
+        if (is_var) {
+            ss << "[";
+            for (uint32_t i = 0; i < n; ++i) {
+                ss << v[i];
+                if (i < n - 1) {
+                    ss << ", ";
+                }
+            }
+            ss << "]";
+        } else {
+            ss << v[0];
+        }
+
+        return ss.str();
+    };
+
     // hparams
     LLAMA_LOG_INFO("%s: format           = %s\n",     __func__, llama_file_version_name(ml.fver));
     LLAMA_LOG_INFO("%s: arch             = %s\n",     __func__, LLM_ARCH_NAMES.at(model.arch));
     LLAMA_LOG_INFO("%s: vocab type       = %s\n",     __func__, llama_model_vocab_type_name(vocab.type));
     LLAMA_LOG_INFO("%s: n_vocab          = %u\n",     __func__, hparams.n_vocab);
     LLAMA_LOG_INFO("%s: n_merges         = %u\n",     __func__, (int) vocab.bpe_ranks.size());
-    LLAMA_LOG_INFO("%s: n_ctx_train      = %u\n",     __func__, hparams.n_ctx_train);
-    LLAMA_LOG_INFO("%s: n_embd           = %u\n",     __func__, hparams.n_embd);
-    LLAMA_LOG_INFO("%s: n_head           = %u\n",     __func__, hparams.n_head);
-    LLAMA_LOG_INFO("%s: n_head_kv        = %u\n",     __func__, hparams.n_head_kv);
-    LLAMA_LOG_INFO("%s: n_layer          = %u\n",     __func__, hparams.n_layer);
-    LLAMA_LOG_INFO("%s: n_rot            = %u\n",     __func__, hparams.n_rot);
-    LLAMA_LOG_INFO("%s: n_swa            = %u\n",     __func__, hparams.n_swa);
-    LLAMA_LOG_INFO("%s: n_embd_head_k    = %u\n",     __func__, hparams.n_embd_head_k);
-    LLAMA_LOG_INFO("%s: n_embd_head_v    = %u\n",     __func__, hparams.n_embd_head_v);
-    LLAMA_LOG_INFO("%s: n_gqa            = %u\n",     __func__, hparams.n_gqa());
-    LLAMA_LOG_INFO("%s: n_embd_k_gqa     = %u\n",     __func__, hparams.n_embd_k_gqa());
-    LLAMA_LOG_INFO("%s: n_embd_v_gqa     = %u\n",     __func__, hparams.n_embd_v_gqa());
-    LLAMA_LOG_INFO("%s: f_norm_eps       = %.1e\n",   __func__, hparams.f_norm_eps);
-    LLAMA_LOG_INFO("%s: f_norm_rms_eps   = %.1e\n",   __func__, hparams.f_norm_rms_eps);
-    LLAMA_LOG_INFO("%s: f_clamp_kqv      = %.1e\n",   __func__, hparams.f_clamp_kqv);
-    LLAMA_LOG_INFO("%s: f_max_alibi_bias = %.1e\n",   __func__, hparams.f_max_alibi_bias);
-    LLAMA_LOG_INFO("%s: f_logit_scale    = %.1e\n",   __func__, hparams.f_logit_scale);
-    LLAMA_LOG_INFO("%s: n_ff             = %u\n",     __func__, hparams.n_ff);
-    LLAMA_LOG_INFO("%s: n_expert         = %u\n",     __func__, hparams.n_expert);
-    LLAMA_LOG_INFO("%s: n_expert_used    = %u\n",     __func__, hparams.n_expert_used);
-    LLAMA_LOG_INFO("%s: causal attn      = %d\n",     __func__, hparams.causal_attn);
-    LLAMA_LOG_INFO("%s: pooling type     = %d\n",     __func__, hparams.pooling_type);
-    LLAMA_LOG_INFO("%s: rope type        = %d\n",     __func__, hparams.rope_type);
-    LLAMA_LOG_INFO("%s: rope scaling     = %s\n",     __func__, rope_scaling_type);
-    LLAMA_LOG_INFO("%s: freq_base_train  = %.1f\n",   __func__, hparams.rope_freq_base_train);
-    LLAMA_LOG_INFO("%s: freq_scale_train = %g\n",     __func__, hparams.rope_freq_scale_train);
-    LLAMA_LOG_INFO("%s: n_ctx_orig_yarn  = %u\n",     __func__, hparams.n_ctx_orig_yarn);
-    LLAMA_LOG_INFO("%s: rope_finetuned   = %s\n",     __func__, hparams.rope_finetuned ? "yes" : "unknown");
-    LLAMA_LOG_INFO("%s: ssm_d_conv       = %u\n",     __func__, hparams.ssm_d_conv);
-    LLAMA_LOG_INFO("%s: ssm_d_inner      = %u\n",     __func__, hparams.ssm_d_inner);
-    LLAMA_LOG_INFO("%s: ssm_d_state      = %u\n",     __func__, hparams.ssm_d_state);
-    LLAMA_LOG_INFO("%s: ssm_dt_rank      = %u\n",     __func__, hparams.ssm_dt_rank);
+    LLAMA_LOG_INFO("%s: vocab_only       = %d\n",     __func__, hparams.vocab_only);
+
+    if (!hparams.vocab_only) {
+        LLAMA_LOG_INFO("%s: n_ctx_train      = %u\n",     __func__, hparams.n_ctx_train);
+        LLAMA_LOG_INFO("%s: n_embd           = %u\n",     __func__, hparams.n_embd);
+        LLAMA_LOG_INFO("%s: n_layer          = %u\n",     __func__, hparams.n_layer);
+        LLAMA_LOG_INFO("%s: n_head           = %s\n",     __func__, print_f([&](uint32_t il) { return hparams.n_head(il);    }, hparams.n_layer).c_str());
+        LLAMA_LOG_INFO("%s: n_head_kv        = %s\n",     __func__, print_f([&](uint32_t il) { return hparams.n_head_kv(il); }, hparams.n_layer).c_str());
+        LLAMA_LOG_INFO("%s: n_rot            = %u\n",     __func__, hparams.n_rot);
+        LLAMA_LOG_INFO("%s: n_swa            = %u\n",     __func__, hparams.n_swa);
+        LLAMA_LOG_INFO("%s: n_embd_head_k    = %u\n",     __func__, hparams.n_embd_head_k);
+        LLAMA_LOG_INFO("%s: n_embd_head_v    = %u\n",     __func__, hparams.n_embd_head_v);
+        LLAMA_LOG_INFO("%s: n_gqa            = %s\n",     __func__, print_f([&](uint32_t il) { return hparams.n_gqa(il);        }, hparams.n_layer).c_str());
+        LLAMA_LOG_INFO("%s: n_embd_k_gqa     = %s\n",     __func__, print_f([&](uint32_t il) { return hparams.n_embd_k_gqa(il); }, hparams.n_layer).c_str());
+        LLAMA_LOG_INFO("%s: n_embd_v_gqa     = %s\n",     __func__, print_f([&](uint32_t il) { return hparams.n_embd_v_gqa(il); }, hparams.n_layer).c_str());
+        LLAMA_LOG_INFO("%s: f_norm_eps       = %.1e\n",   __func__, hparams.f_norm_eps);
+        LLAMA_LOG_INFO("%s: f_norm_rms_eps   = %.1e\n",   __func__, hparams.f_norm_rms_eps);
+        LLAMA_LOG_INFO("%s: f_clamp_kqv      = %.1e\n",   __func__, hparams.f_clamp_kqv);
+        LLAMA_LOG_INFO("%s: f_max_alibi_bias = %.1e\n",   __func__, hparams.f_max_alibi_bias);
+        LLAMA_LOG_INFO("%s: f_logit_scale    = %.1e\n",   __func__, hparams.f_logit_scale);
+        LLAMA_LOG_INFO("%s: n_ff             = %s\n",     __func__, print_f([&](uint32_t il) { return hparams.n_ff(il); }, hparams.n_layer).c_str());
+        LLAMA_LOG_INFO("%s: n_expert         = %u\n",     __func__, hparams.n_expert);
+        LLAMA_LOG_INFO("%s: n_expert_used    = %u\n",     __func__, hparams.n_expert_used);
+        LLAMA_LOG_INFO("%s: causal attn      = %d\n",     __func__, hparams.causal_attn);
+        LLAMA_LOG_INFO("%s: pooling type     = %d\n",     __func__, hparams.pooling_type);
+        LLAMA_LOG_INFO("%s: rope type        = %d\n",     __func__, hparams.rope_type);
+        LLAMA_LOG_INFO("%s: rope scaling     = %s\n",     __func__, rope_scaling_type);
+        LLAMA_LOG_INFO("%s: freq_base_train  = %.1f\n",   __func__, hparams.rope_freq_base_train);
+        LLAMA_LOG_INFO("%s: freq_scale_train = %g\n",     __func__, hparams.rope_freq_scale_train);
+        LLAMA_LOG_INFO("%s: n_ctx_orig_yarn  = %u\n",     __func__, hparams.n_ctx_orig_yarn);
+        LLAMA_LOG_INFO("%s: rope_finetuned   = %s\n",     __func__, hparams.rope_finetuned ? "yes" : "unknown");
+        LLAMA_LOG_INFO("%s: ssm_d_conv       = %u\n",     __func__, hparams.ssm_d_conv);
+        LLAMA_LOG_INFO("%s: ssm_d_inner      = %u\n",     __func__, hparams.ssm_d_inner);
+        LLAMA_LOG_INFO("%s: ssm_d_state      = %u\n",     __func__, hparams.ssm_d_state);
+        LLAMA_LOG_INFO("%s: ssm_dt_rank      = %u\n",     __func__, hparams.ssm_dt_rank);
+    }
+
     LLAMA_LOG_INFO("%s: model type       = %s\n",     __func__, llama_model_type_name(model.type));
     LLAMA_LOG_INFO("%s: model ftype      = %s\n",     __func__, llama_model_ftype_name(model.ftype).c_str());
     if (ml.n_elements >= 1e12) {
@@ -5765,13 +5955,13 @@ static bool llm_load_tensors(
     // create tensors for the weights
     {
         const int64_t n_embd       = hparams.n_embd;
-        const int64_t n_embd_head  = (hparams.n_head == 0) ? 0 : n_embd / hparams.n_head;
+        const int64_t n_embd_head  = hparams.n_head() > 0 ? n_embd / hparams.n_head() : 0;
         const int64_t n_embd_k_gqa = hparams.n_embd_k_gqa();
         const int64_t n_embd_v_gqa = hparams.n_embd_v_gqa();
         const int64_t n_embd_gqa   = n_embd_v_gqa;
         const int64_t n_vocab      = hparams.n_vocab;
         const int64_t n_vocab_type = hparams.n_vocab_type;
-        const int64_t n_ff         = hparams.n_ff;
+        const int64_t n_ff         = hparams.n_ff();
         const int64_t n_expert     = hparams.n_expert;
 
         if (n_expert > 0 && hparams.n_expert_used == 0) {
@@ -6292,8 +6482,8 @@ static bool llm_load_tensors(
                         layer.bv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_V,   "bias", i), {n_embd_gqa}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         // optional q and k layernorms, present in StableLM 2 12B
-                        layer.attn_q_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head}, llama_model_loader::TENSOR_NOT_REQUIRED);
-                        layer.attn_k_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head_kv}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_q_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head()}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_k_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head_kv()}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         // optional FFN norm, not present in StableLM 2 12B which uses parallel residual
                         layer.ffn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
@@ -6664,7 +6854,7 @@ static bool llm_load_tensors(
                     model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
                     model.output      = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD,  "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED); // same as tok_embd, duplicated to allow offloading
 
-                    const int64_t n_ff          = hparams.n_ff;
+                    const int64_t n_ff          = hparams.n_ff();
                     const int64_t n_embd_head_k = hparams.n_embd_head_k;
                     const int64_t n_embd_k_gqa  = hparams.n_embd_k_gqa();
                     const int64_t n_embd_v_gqa  = hparams.n_embd_v_gqa();
@@ -6677,10 +6867,10 @@ static bool llm_load_tensors(
 
                         layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
 
-                        layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd_head_k * hparams.n_head});
+                        layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd_head_k * hparams.n_head()});
                         layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K,   "weight", i), {n_embd, n_embd_k_gqa});
                         layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V,   "weight", i), {n_embd, n_embd_v_gqa});
-                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd_head_k * hparams.n_head, n_embd});
+                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd_head_k * hparams.n_head(), n_embd});
 
                         layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
                         layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd,   n_ff});
@@ -6696,7 +6886,7 @@ static bool llm_load_tensors(
                     model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
                     model.output      = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD,  "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED); // same as tok_embd, duplicated to allow offloading
 
-                    const int64_t n_ff          = hparams.n_ff;
+                    const int64_t n_ff          = hparams.n_ff();
                     const int64_t n_embd_head_k = hparams.n_embd_head_k;
                     const int64_t n_embd_k_gqa  = hparams.n_embd_k_gqa();
                     const int64_t n_embd_v_gqa  = hparams.n_embd_v_gqa();
@@ -6709,10 +6899,10 @@ static bool llm_load_tensors(
 
                         layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
 
-                        layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd_head_k * hparams.n_head});
+                        layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd_head_k * hparams.n_head()});
                         layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K,   "weight", i), {n_embd, n_embd_k_gqa});
                         layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V,   "weight", i), {n_embd, n_embd_v_gqa});
-                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd_head_k * hparams.n_head, n_embd});
+                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd_head_k * hparams.n_head(), n_embd});
                         layer.attn_post_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_POST_NORM, "weight", i), {n_embd});
 
                         layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
@@ -6861,8 +7051,8 @@ static bool llm_load_tensors(
                         layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
 
                         if (n_layer >= 64){
-                            layer.attn_q_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head});
-                            layer.attn_k_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head_kv});
+                            layer.attn_q_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head()});
+                            layer.attn_k_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head_kv()});
                         }
 
                         layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd});
@@ -6904,6 +7094,42 @@ static bool llm_load_tensors(
                         layer.ffn_up   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd,   n_ff});
                     }
                 } break;
+            case LLM_ARCH_OPENELM:
+                {
+                    model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
+
+                    // output
+                    {
+                        model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
+                        // init output from the input tok embed
+                        model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED);
+                    }
+
+                    for (int i = 0; i < n_layer; ++i) {
+                        const int64_t n_head = hparams.n_head(i);
+                        const int64_t n_head_qkv = 2*hparams.n_head_kv(i) + n_head;
+                        const int64_t n_embd_head = hparams.n_embd_head_k;
+
+                        const int64_t n_ff = hparams.n_ff(i);
+
+                        ggml_context * ctx_layer = ctx_for_layer(i);
+                        ggml_context * ctx_split = ctx_for_layer_split(i);
+
+                        auto & layer = model.layers[i];
+
+                        layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
+
+                        layer.wqkv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_head_qkv*n_embd_head});
+                        layer.attn_q_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {n_embd_head});
+                        layer.attn_k_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {n_embd_head});
+                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_head*n_embd_head, n_embd});
+
+                        layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
+                        layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff});
+                        layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd});
+                        layer.ffn_up   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd, n_ff});
+                    }
+                } break;
             case LLM_ARCH_GPTNEOX:
                 {
                     model.tok_embd   = ml.create_tensor(ctx_input,  tn(LLM_TENSOR_TOKEN_EMBD,      "weight"), {n_embd, n_vocab});
@@ -7011,13 +7237,13 @@ static bool llm_load_tensors(
 
                         if (!is_lite) {
                             layer.wq_a = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q_A,   "weight", i), {n_embd, q_lora_rank});
-                            layer.wq_b = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q_B,   "weight", i), {q_lora_rank, hparams.n_head * hparams.n_embd_head_k});
+                            layer.wq_b = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q_B,   "weight", i), {q_lora_rank, hparams.n_head() * hparams.n_embd_head_k});
                         } else {
                             layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd_k_gqa});
                         }
                         layer.wkv_a_mqa = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_KV_A_MQA,   "weight", i), {n_embd, kv_lora_rank + n_embd_head_qk_rope});
-                        layer.wkv_b = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_KV_B,   "weight", i), {kv_lora_rank, hparams.n_head * (n_embd_head_qk_nope + hparams.n_embd_head_v)});
-                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {hparams.n_head * hparams.n_embd_head_v, n_embd});
+                        layer.wkv_b = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_KV_B, "weight", i), {kv_lora_rank, hparams.n_head() * (n_embd_head_qk_nope + hparams.n_embd_head_v)});
+                        layer.wo    = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT,  "weight", i), {              hparams.n_head() * (                      hparams.n_embd_head_v), n_embd});
 
                         layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
 
@@ -7104,7 +7330,7 @@ static bool llm_load_tensors(
                         auto & layer = model.layers[i];
 
                         layer.attn_norm_enc  = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ENC_ATTN_NORM,  "weight", i), {n_embd});
-                        layer.attn_rel_b_enc = ml.create_tensor(ctx_input, tn(LLM_TENSOR_ENC_ATTN_REL_B, "weight", i), {hparams.n_head, hparams.n_rel_attn_bkts}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_rel_b_enc = ml.create_tensor(ctx_input, tn(LLM_TENSOR_ENC_ATTN_REL_B, "weight", i), {hparams.n_head(), hparams.n_rel_attn_bkts}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         layer.wq_enc = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ENC_ATTN_Q,   "weight", i), {n_embd, n_embd_k_gqa});
                         layer.wk_enc = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ENC_ATTN_K,   "weight", i), {n_embd, n_embd_k_gqa});
@@ -7117,7 +7343,7 @@ static bool llm_load_tensors(
                         layer.ffn_up_enc   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ENC_FFN_UP,   "weight", i), {n_embd,   n_ff});
 
                         layer.attn_norm  = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_DEC_ATTN_NORM,  "weight", i), {n_embd});
-                        layer.attn_rel_b = ml.create_tensor(ctx_input, tn(LLM_TENSOR_DEC_ATTN_REL_B, "weight", i), {hparams.n_head, hparams.n_rel_attn_bkts}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_rel_b = ml.create_tensor(ctx_input, tn(LLM_TENSOR_DEC_ATTN_REL_B, "weight", i), {hparams.n_head(), hparams.n_rel_attn_bkts}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_ATTN_Q,   "weight", i), {n_embd, n_embd_k_gqa});
                         layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_ATTN_K,   "weight", i), {n_embd, n_embd_k_gqa});
@@ -7126,7 +7352,7 @@ static bool llm_load_tensors(
 
                         layer.attn_norm_cross  = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_DEC_CROSS_ATTN_NORM,  "weight", i), {n_embd});
                         // this tensor seems to be unused in HF transformers implementation
-                        layer.attn_rel_b_cross = ml.create_tensor(ctx_input, tn(LLM_TENSOR_DEC_CROSS_ATTN_REL_B, "weight", i), {hparams.n_head, hparams.n_rel_attn_bkts}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_rel_b_cross = ml.create_tensor(ctx_input, tn(LLM_TENSOR_DEC_CROSS_ATTN_REL_B, "weight", i), {hparams.n_head(), hparams.n_rel_attn_bkts}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         layer.wq_cross = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_CROSS_ATTN_Q,   "weight", i), {n_embd, n_embd_k_gqa});
                         layer.wk_cross = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_CROSS_ATTN_K,   "weight", i), {n_embd, n_embd_k_gqa});
@@ -7455,8 +7681,8 @@ static void llm_build_kv_store(
                     int64_t   il) {
     const int64_t n_ctx = cparams.n_ctx;
 
-    const int64_t n_embd_k_gqa = hparams.n_embd_k_gqa();
-    const int64_t n_embd_v_gqa = hparams.n_embd_v_gqa();
+    const int64_t n_embd_k_gqa = hparams.n_embd_k_gqa(il);
+    const int64_t n_embd_v_gqa = hparams.n_embd_v_gqa(il);
 
     GGML_ASSERT(kv.size == n_ctx);
 
@@ -7749,12 +7975,12 @@ static struct ggml_tensor * llm_build_kqv(
          const llm_build_cb & cb,
                     int       il) {
     const int64_t n_ctx         = cparams.n_ctx;
-    const int64_t n_head        = hparams.n_head;
-    const int64_t n_head_kv     = hparams.n_head_kv;
+    const int64_t n_head        = hparams.n_head(il);
+    const int64_t n_head_kv     = hparams.n_head_kv(il);
     const int64_t n_embd_head_k = hparams.n_embd_head_k;
-    const int64_t n_embd_k_gqa  = hparams.n_embd_k_gqa();
+    const int64_t n_embd_k_gqa  = hparams.n_embd_k_gqa(il);
     const int64_t n_embd_head_v = hparams.n_embd_head_v;
-    const int64_t n_embd_v_gqa  = hparams.n_embd_v_gqa();
+    const int64_t n_embd_v_gqa  = hparams.n_embd_v_gqa(il);
 
     struct ggml_tensor * q = ggml_permute(ctx, q_cur, 0, 2, 1, 3);
     cb(q, "q", il);
@@ -7961,8 +8187,8 @@ struct llm_build_context {
         n_layer          (hparams.n_layer),
         n_rot            (hparams.n_rot),
         n_ctx            (cparams.n_ctx),
-        n_head           (hparams.n_head),
-        n_head_kv        (hparams.n_head_kv),
+        n_head           (hparams.n_head()),
+        n_head_kv        (hparams.n_head_kv()),
         n_embd_head_k    (hparams.n_embd_head_k),
         n_embd_k_gqa     (hparams.n_embd_k_gqa()),
         n_embd_head_v    (hparams.n_embd_head_v),
@@ -8034,6 +8260,8 @@ struct llm_build_context {
         ggml_set_input(lctx.inp_K_shift);
 
         for (int il = 0; il < n_layer; ++il) {
+            const int64_t n_head_kv = hparams.n_head_kv(il);
+            const int64_t n_embd_k_gqa = hparams.n_embd_k_gqa(il);
             struct ggml_tensor * rope_factors = build_rope_factors(il);
             struct ggml_tensor * tmp =
                 // we rotate only the first n_rot dimensions
@@ -8093,6 +8321,9 @@ struct llm_build_context {
             }
 
             for (int il = 0; il < n_layer; ++il) {
+                const int64_t n_embd_k_gqa = hparams.n_embd_k_gqa(il);
+                const int64_t n_embd_v_gqa = hparams.n_embd_v_gqa(il);
+
                 ggml_tensor * view_k_src = ggml_view_2d(ctx0, kv_self.k_l[il],
                         n_embd_k_gqa, nm,
                         ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa),
@@ -11974,6 +12205,131 @@ struct llm_build_context {
         return gf;
     }
 
+    struct ggml_cgraph * build_openelm() {
+        struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
+
+        const int64_t n_embd_head = hparams.n_embd_head_v;
+        GGML_ASSERT(n_embd_head == hparams.n_embd_head_k);
+
+        struct ggml_tensor * cur;
+        struct ggml_tensor * inpL;
+        inpL = llm_build_inp_embd(ctx0, lctx, hparams, batch, model.tok_embd, cb);
+
+        // inp_pos - contains the positions
+        struct ggml_tensor * inp_pos = build_inp_pos();
+
+        // KQ_mask (mask for 1 head, it will be broadcasted to all heads)
+        struct ggml_tensor * KQ_mask = build_inp_KQ_mask();
+
+        for (int il = 0; il < n_layer; ++il) {
+            const int64_t n_head    = hparams.n_head(il);
+            const int64_t n_head_kv = hparams.n_head_kv(il);
+            const int64_t n_head_qkv = 2*n_head_kv + n_head;
+
+            cur = inpL;
+            struct ggml_tensor * residual = cur;
+
+            // norm
+            cur = llm_build_norm(ctx0, inpL, hparams,
+                    model.layers[il].attn_norm, NULL,
+                    LLM_NORM_RMS, cb, il);
+            cb(cur, "attn_norm", il);
+
+            // self-attention
+            {
+                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
+                cb(cur, "wqkv", il);
+
+                cur = ggml_reshape_3d(ctx0, cur, n_embd_head_k, n_head_qkv, n_tokens);
+
+                struct ggml_tensor * Qcur = ggml_cont(ctx0, ggml_view_3d(ctx0, cur, n_embd_head, n_head, n_tokens, cur->nb[1], cur->nb[2], 0));
+                cb(Qcur, "Qcur", il);
+
+                struct ggml_tensor * Kcur = ggml_cont(ctx0, ggml_view_3d(ctx0, cur, n_embd_head, n_head_kv, n_tokens, cur->nb[1], cur->nb[2], cur->nb[1]*n_head));
+                cb(Kcur, "Kcur", il);
+
+                struct ggml_tensor * Vcur = ggml_cont(ctx0, ggml_view_3d(ctx0, cur, n_embd_head, n_head_kv, n_tokens, cur->nb[1], cur->nb[2], cur->nb[1]*(n_head+n_head_kv)));
+                cb(Vcur, "Vcur", il);
+
+                Qcur = llm_build_norm(ctx0, Qcur, hparams,
+                        model.layers[il].attn_q_norm, NULL,
+                        LLM_NORM_RMS, cb, il);
+                cb(Qcur, "Qcur", il);
+
+                Kcur = llm_build_norm(ctx0, Kcur, hparams,
+                        model.layers[il].attn_k_norm, NULL,
+                        LLM_NORM_RMS, cb, il);
+                cb(Kcur, "Kcur", il);
+
+                Qcur = ggml_rope_ext(
+                    ctx0, Qcur, inp_pos, NULL, n_rot, rope_type, n_ctx_orig,
+                    freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow
+                );
+                cb(Qcur, "Qcur", il);
+
+                Kcur = ggml_rope_ext(
+                    ctx0, Kcur, inp_pos, NULL, n_rot, rope_type, n_ctx_orig,
+                    freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow
+                );
+                cb(Kcur, "Kcur", il);
+
+                Vcur = ggml_reshape_2d(ctx0, Vcur, n_embd_head * n_head_kv, n_tokens);
+                cb(Qcur, "Vcur", il);
+
+                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                        model.layers[il].wo, NULL,
+                        Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
+            }
+
+            if (il == n_layer - 1) {
+                // skip computing output for unused tokens
+                struct ggml_tensor * inp_out_ids = build_inp_out_ids();
+                residual = ggml_get_rows(ctx0, residual, inp_out_ids);
+                cur = ggml_get_rows(ctx0, cur, inp_out_ids);
+            }
+
+            struct ggml_tensor * ffn_inp = ggml_add(ctx0, residual, cur);
+            cb(ffn_inp, "ffn_inp", il);
+
+            // feed-forward network
+            {
+                cur = llm_build_norm(ctx0, ffn_inp, hparams,
+                        model.layers[il].ffn_norm, NULL,
+                        LLM_NORM_RMS, cb, il);
+                cb(cur, "ffn_norm", il);
+
+                cur = llm_build_ffn(ctx0, cur,
+                        model.layers[il].ffn_up,   NULL, NULL,
+                        model.layers[il].ffn_gate, NULL, NULL,
+                        model.layers[il].ffn_down, NULL, NULL,
+                        NULL,
+                        LLM_FFN_SILU, LLM_FFN_PAR, cb, il);
+                cb(cur, "ffn_out", il);
+            }
+
+            cur = ggml_add(ctx0, cur, ffn_inp);
+            cur = lctx.cvec.apply_to(ctx0, cur, il);
+            cb(cur, "l_out", il);
+
+            inpL = cur;
+        }
+
+        cur = inpL;
+
+        // norm
+        cur = llm_build_norm(ctx0, cur, hparams,
+                model.output_norm, NULL,
+                LLM_NORM_RMS, cb, -1);
+        cb(cur, "result_norm", -1);
+
+        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cb(cur, "result_output", -1);
+
+        ggml_build_forward_expand(gf, cur);
+
+        return gf;
+    }
+
     struct ggml_cgraph * build_gptneox() {
         struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
 
@@ -13242,6 +13598,10 @@ static struct ggml_cgraph * llama_build_graph(
             {
                 result = llm.build_olmo();
             } break;
+        case LLM_ARCH_OPENELM:
+            {
+                result = llm.build_openelm();
+            } break;
         case LLM_ARCH_GPTNEOX:
             {
                 result = llm.build_gptneox();
@@ -18772,6 +19132,7 @@ enum llama_rope_type llama_rope_type(const struct llama_model * model) {
         case LLM_ARCH_GEMMA:
         case LLM_ARCH_GEMMA2:
         case LLM_ARCH_STARCODER2:
+        case LLM_ARCH_OPENELM:
         case LLM_ARCH_GPTNEOX:
             return LLAMA_ROPE_TYPE_NEOX;
 
@@ -19365,8 +19726,6 @@ static void llama_state_get_data_internal(struct llama_context * ctx, llama_data
         const auto & hparams = ctx->model.hparams;
 
         const uint32_t n_layer      = hparams.n_layer;
-        const uint32_t n_embd_k_gqa = hparams.n_embd_k_gqa() + hparams.n_embd_k_s();
-        const uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa() + hparams.n_embd_v_s();
 
         // NOTE: kv_size and kv_buf_size are mostly used for sanity checks
         const uint32_t kv_head     = llama_kv_cache_cell_max(kv_self);
@@ -19386,6 +19745,9 @@ static void llama_state_get_data_internal(struct llama_context * ctx, llama_data
 
             std::vector tmp_buf;
             for (int il = 0; il < (int) n_layer; ++il) {
+                const uint32_t n_embd_k_gqa = hparams.n_embd_k_gqa(il) + hparams.n_embd_k_s();
+                const uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa(il) + hparams.n_embd_v_s();
+
                 const size_t k_size = ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa*kv_head);
 
                 tmp_buf.resize(k_size);
@@ -19518,8 +19880,6 @@ size_t llama_state_set_data(struct llama_context * ctx, const uint8_t * src) {
         const auto & hparams = ctx->model.hparams;
 
         const uint32_t n_layer      = hparams.n_layer;
-        const uint32_t n_embd_k_gqa = hparams.n_embd_k_gqa() + hparams.n_embd_k_s();
-        const uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa() + hparams.n_embd_v_s();
 
         size_t   kv_buf_size;
         uint32_t kv_head;
@@ -19551,6 +19911,9 @@ size_t llama_state_set_data(struct llama_context * ctx, const uint8_t * src) {
             GGML_ASSERT(kv_self.total_size() >= kv_buf_size);
 
             for (int il = 0; il < (int) n_layer; ++il) {
+                const uint32_t n_embd_k_gqa = hparams.n_embd_k_gqa(il) + hparams.n_embd_k_s();
+                const uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa(il) + hparams.n_embd_v_s();
+
                 const size_t k_size = ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa*kv_head);
 
                 ggml_backend_tensor_set(kv_self.k_l[il], inp, 0, k_size);
@@ -19713,8 +20076,6 @@ size_t llama_state_seq_get_size(struct llama_context* ctx, llama_seq_id seq_id)
     const auto & hparams = ctx->model.hparams;
 
     const uint32_t n_layer = hparams.n_layer;
-    const uint32_t n_embd_k_gqa = hparams.n_embd_k_gqa() + hparams.n_embd_k_s();
-    const uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa() + hparams.n_embd_v_s();
 
     for (uint32_t i = 0; i < kv_self.size; ++i) {
         const auto & cell = kv_self.cells[i];
@@ -19725,6 +20086,9 @@ size_t llama_state_seq_get_size(struct llama_context* ctx, llama_seq_id seq_id)
     }
 
     for (int il = 0; il < (int)n_layer; ++il) {
+        const uint32_t n_embd_k_gqa = hparams.n_embd_k_gqa(il) + hparams.n_embd_k_s();
+        const uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa(il) + hparams.n_embd_v_s();
+
         // types of keys and values
         s_cell_data_size += sizeof(int32_t) * 2;
         // k_size_row and v_size_el values of layer
@@ -19799,14 +20163,15 @@ static size_t llama_state_seq_get_data_internal(struct llama_context * ctx, llam
 
     const auto & hparams = ctx->model.hparams;
     const uint32_t n_layer = hparams.n_layer;
-    const uint32_t n_embd_k_gqa = hparams.n_embd_k_gqa() + hparams.n_embd_k_s();
-    const uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa() + hparams.n_embd_v_s();
 
     // Write the layer count
     data_ctx.write(&n_layer, sizeof(n_layer));
 
-    // Write n_embd_v_gqa
-    data_ctx.write(&n_embd_v_gqa, sizeof(n_embd_v_gqa));
+    // Write n_embd_v_gqa (reference value)
+    {
+        const uint32_t n_embd_v_gqa_ref = hparams.n_embd_v_gqa() + hparams.n_embd_k_s();
+        data_ctx.write(&n_embd_v_gqa_ref, sizeof(n_embd_v_gqa_ref));
+    }
 
     // Iterate the ranges and write all the pos (this is the token position in the prompt)
     for (const auto & range : cell_ranges) {
@@ -19820,6 +20185,8 @@ static size_t llama_state_seq_get_data_internal(struct llama_context * ctx, llam
     // Get whole range at a time
     std::vector tmp_buf;
     for (int il = 0; il < (int)n_layer; ++il) {
+        const uint32_t n_embd_k_gqa = hparams.n_embd_k_gqa(il) + hparams.n_embd_k_s();
+
         // Write key type
         const int32_t k_type_i = (int32_t)kv_self.k_l[il]->type;
         data_ctx.write(&k_type_i, sizeof(k_type_i));
@@ -19840,6 +20207,8 @@ static size_t llama_state_seq_get_data_internal(struct llama_context * ctx, llam
     // TODO: simplify, reduce copy-paste
     if (!kv_self.v_trans) {
         for (int il = 0; il < (int)n_layer; ++il) {
+            const uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa(il) + hparams.n_embd_v_s();
+
             // Write value type
             const int32_t v_type_i = (int32_t)kv_self.v_l[il]->type;
             data_ctx.write(&v_type_i, sizeof(v_type_i));
@@ -19860,6 +20229,8 @@ static size_t llama_state_seq_get_data_internal(struct llama_context * ctx, llam
         // For the values, they are transposed, so we also need the element size and get the element ranges from each row
         const uint32_t kv_size = kv_self.size;
         for (int il = 0; il < (int)n_layer; ++il) {
+            const uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa(il) + hparams.n_embd_v_s();
+
             // Write value type
             const int32_t v_type_i = (int32_t)kv_self.v_l[il]->type;
             data_ctx.write(&v_type_i, sizeof(v_type_i));
@@ -19928,14 +20299,14 @@ size_t llama_state_seq_set_data(struct llama_context * ctx, const uint8_t * src,
     // Sanity check model compatibility
     const auto & hparams = ctx->model.hparams;
     const uint32_t n_layer = hparams.n_layer;
-    const uint32_t n_embd_k_gqa = hparams.n_embd_k_gqa() + hparams.n_embd_k_s();
-    const uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa() + hparams.n_embd_v_s();
+
     if (n_layer != n_layer_ref) {
         LLAMA_LOG_ERROR("%s: mismatched n_layer (%d != %d)\n", __func__, n_layer, n_layer_ref);
         return 0;
     }
-    if (n_embd_v_gqa != n_embd_v_gqa_ref) {
-        LLAMA_LOG_ERROR("%s: mismatched n_embd_v_gqa (%d != %d)\n", __func__, n_embd_v_gqa, n_embd_v_gqa_ref);
+
+    if (hparams.n_embd_v_gqa() != n_embd_v_gqa_ref) {
+        LLAMA_LOG_ERROR("%s: mismatched n_embd_v_gqa (%d != %d)\n", __func__, hparams.n_embd_v_gqa(), n_embd_v_gqa_ref);
         return 0;
     }
 
@@ -19975,6 +20346,8 @@ size_t llama_state_seq_set_data(struct llama_context * ctx, const uint8_t * src,
 
     // For each layer, read the keys for each cell, one row is one cell, read as one contiguous blo
     for (int il = 0; il < (int)n_layer; ++il) {
+        const uint32_t n_embd_k_gqa = hparams.n_embd_k_gqa(il) + hparams.n_embd_k_s();
+
         // Read type of key
         int32_t k_type_i_ref;
         memcpy(&k_type_i_ref, inp, sizeof(k_type_i_ref));
@@ -20007,6 +20380,8 @@ size_t llama_state_seq_set_data(struct llama_context * ctx, const uint8_t * src,
     // TODO: simplify, reduce copy-paste
     if (!kv_self.v_trans) {
         for (int il = 0; il < (int)n_layer; ++il) {
+            const uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa(il) + hparams.n_embd_v_s();
+
             // Read type of value
             int32_t v_type_i_ref;
             memcpy(&v_type_i_ref, inp, sizeof(v_type_i_ref));
@@ -20038,6 +20413,8 @@ size_t llama_state_seq_set_data(struct llama_context * ctx, const uint8_t * src,
     } else {
         // For each layer, read the values for each cell (transposed)
         for (int il = 0; il < (int)n_layer; ++il) {
+            const uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa(il) + hparams.n_embd_v_s();
+
             // Read type of value
             int32_t v_type_i_ref;
             memcpy(&v_type_i_ref, inp, sizeof(v_type_i_ref));

From a38b884c6c4b0c256583acfaaabdf556c62fabea Mon Sep 17 00:00:00 2001
From: Xuan Son Nguyen 
Date: Thu, 4 Jul 2024 20:55:03 +0200
Subject: [PATCH 097/326] cli: add EOT when user hit Ctrl+C (#8296)

* main: add need_insert_eot

* do not format system prompt if it is empty
---
 common/common.cpp      |  9 +++++++--
 examples/main/main.cpp | 24 ++++++++++++++++++++----
 2 files changed, 27 insertions(+), 6 deletions(-)

diff --git a/common/common.cpp b/common/common.cpp
index 4138dc3b62cd8..1f7359980a94d 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -1394,7 +1394,9 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
     options.push_back({ "*",           "       --keep N",               "number of tokens to keep from the initial prompt (default: %d, -1 = all)", params.n_keep });
     options.push_back({ "*",           "       --chunks N",             "max number of chunks to process (default: %d, -1 = all)", params.n_chunks });
     options.push_back({ "*",           "-fa,   --flash-attn",           "enable Flash Attention (default: %s)", params.flash_attn ? "enabled" : "disabled" });
-    options.push_back({ "*",           "-p,    --prompt PROMPT",        "prompt to start generation with (default: '%s')", params.prompt.c_str() });
+    options.push_back({ "*",           "-p,    --prompt PROMPT",        "prompt to start generation with\n"
+                                                                        "in conversation mode, this will be used as system prompt\n"
+                                                                        "(default: '%s')", params.prompt.c_str() });
     options.push_back({ "*",           "-f,    --file FNAME",           "a file containing the prompt (default: none)" });
     options.push_back({ "*",           "       --in-file FNAME",        "an input file (repeat to specify multiple files)" });
     options.push_back({ "*",           "-bf,   --binary-file FNAME",    "binary file containing the prompt (default: none)" });
@@ -1409,7 +1411,9 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
                                                                         "halt generation at PROMPT, return control in interactive mode\n"
                                                                         "can be specified more than once for multiple prompts" });
     options.push_back({ "main",        "-sp,   --special",              "special tokens output enabled (default: %s)", params.special ? "true" : "false" });
-    options.push_back({ "main",        "-cnv,  --conversation",         "run in conversation mode (does not print special tokens and suffix/prefix, use default chat template) (default: %s)", params.conversation ? "true" : "false" });
+    options.push_back({ "main",        "-cnv,  --conversation",         "run in conversation mode, does not print special tokens and suffix/prefix\n"
+                                                                        "if suffix/prefix are not specified, default chat template will be used\n"
+                                                                        "(default: %s)", params.conversation ? "true" : "false" });
     options.push_back({ "main infill", "-i,    --interactive",          "run in interactive mode (default: %s)", params.interactive ? "true" : "false" });
     options.push_back({ "main infill", "-if,   --interactive-first",    "run in interactive mode and wait for input right away (default: %s)", params.interactive_first ? "true" : "false" });
     options.push_back({ "main infill", "-mli,  --multiline-input",      "allows you to write or paste multiple lines without ending each in '\\'" });
@@ -1453,6 +1457,7 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
     options.push_back({ "main",        "       --cfg-scale N",          "strength of guidance (default: %.1f, 1.0 = disable)", (double)sparams.cfg_scale });
     options.push_back({ "main",        "       --chat-template JINJA_TEMPLATE",
                                                                         "set custom jinja chat template (default: template taken from model's metadata)\n"
+                                                                        "if suffix/prefix are specified, template will be disabled\n"
                                                                         "only commonly used templates are accepted:\n"
                                                                         "https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template" });
     options.push_back({ "grammar" });
diff --git a/examples/main/main.cpp b/examples/main/main.cpp
index 22bb37889bf8e..4ef55c1e6b3cf 100644
--- a/examples/main/main.cpp
+++ b/examples/main/main.cpp
@@ -37,7 +37,8 @@ static gpt_params               * g_params;
 static std::vector * g_input_tokens;
 static std::ostringstream       * g_output_ss;
 static std::vector * g_output_tokens;
-static bool is_interacting = false;
+static bool is_interacting  = false;
+static bool need_insert_eot = false;
 
 static bool file_exists(const std::string & path) {
     std::ifstream f(path.c_str());
@@ -99,7 +100,8 @@ static void write_logfile(
 static void sigint_handler(int signo) {
     if (signo == SIGINT) {
         if (!is_interacting && g_params->interactive) {
-            is_interacting = true;
+            is_interacting  = true;
+            need_insert_eot = true;
         } else {
             console::cleanup();
             printf("\n");
@@ -224,7 +226,14 @@ int main(int argc, char ** argv) {
                 __func__, n_ctx_train, n_ctx);
     }
 
-    LOG_TEE("%s: chat template example: %s\n", __func__, llama_chat_format_example(model, params.chat_template).c_str());
+    // print chat template example in conversation mode
+    if (params.conversation) {
+        if (params.enable_chat_template) {
+            LOG_TEE("%s: chat template example: %s\n", __func__, llama_chat_format_example(model, params.chat_template).c_str());
+        } else {
+            LOG_TEE("%s: in-suffix/prefix is specified, chat template will be disabled\n", __func__);
+        }
+    }
 
     // print system information
     {
@@ -263,7 +272,7 @@ int main(int argc, char ** argv) {
     std::vector embd_inp;
 
     {
-        auto prompt = (params.conversation && params.enable_chat_template)
+        auto prompt = (params.conversation && params.enable_chat_template && !params.prompt.empty())
             ? chat_add_and_format(model, chat_msgs, "system", params.prompt) // format the system prompt in conversation mode
             : params.prompt;
         if (params.interactive_first || !params.prompt.empty() || session_tokens.empty()) {
@@ -905,6 +914,13 @@ int main(int argc, char ** argv) {
 
                     LOG("input tokens: %s\n", LOG_TOKENS_TOSTR_PRETTY(ctx, line_inp).c_str());
 
+                    // if user stop generation mid-way, we must add EOT to finish model's last response
+                    if (need_insert_eot && format_chat) {
+                        llama_token eot = llama_token_eot(model);
+                        embd_inp.push_back(eot == -1 ? llama_token_eos(model) : eot);
+                        need_insert_eot = false;
+                    }
+
                     embd_inp.insert(embd_inp.end(), line_pfx.begin(), line_pfx.end());
                     embd_inp.insert(embd_inp.end(), line_inp.begin(), line_inp.end());
                     embd_inp.insert(embd_inp.end(), line_sfx.begin(), line_sfx.end());

From f09b7cb609d80b8031803f89255991dc8b35db69 Mon Sep 17 00:00:00 2001
From: Neo Zhang Jianyu 
Date: Fri, 5 Jul 2024 10:32:29 +0800
Subject: [PATCH 098/326] rm get_work_group_size() by local cache for
 performance (#8286)

Co-authored-by: arthw <14088817+arthw@users.noreply.github.com>
---
 ggml/src/ggml-sycl.cpp        | 10 ++++++----
 ggml/src/ggml-sycl/common.hpp | 15 ++-------------
 ggml/src/ggml-sycl/norm.cpp   | 18 +++++++++---------
 3 files changed, 17 insertions(+), 26 deletions(-)

diff --git a/ggml/src/ggml-sycl.cpp b/ggml/src/ggml-sycl.cpp
index 76bad57e2320b..dde55335bb6da 100644
--- a/ggml/src/ggml-sycl.cpp
+++ b/ggml/src/ggml-sycl.cpp
@@ -49,7 +49,7 @@ bool   ggml_backend_is_sycl(ggml_backend_t backend);
 int    ggml_backend_sycl_get_device(ggml_backend_t backend);
 static bool ggml_backend_buffer_is_sycl_split(ggml_backend_buffer_t buffer);
 static inline int get_sycl_env(const char *env_name, int default_val);
-static inline int get_work_group_size(const sycl::device& device);
+
 
 void dev2dev_memcpy(sycl::queue &q_dst, sycl::queue &q_src, void *ptr_dst,
                     const void *ptr_src, size_t size) {
@@ -1912,9 +1912,9 @@ static void soft_max_f32_submitter(const float * x, const float * mask, float *
 static void soft_max_f32_sycl(const float * x, const float * mask,
                               float * dst, const int ncols_x, const int nrows_x,
                               const int nrows_y, const float scale, const float max_bias,
-                              queue_ptr stream) {
+                              queue_ptr stream, int device) {
     int nth = WARP_SIZE;
-    int max_block_size = get_work_group_size(stream->get_device());
+    int max_block_size = ggml_sycl_info().max_work_group_sizes[device];
     while (nth < ncols_x && nth < max_block_size) nth *= 2;
     if (nth>max_block_size) nth = max_block_size;
 
@@ -2156,6 +2156,8 @@ static ggml_sycl_device_info ggml_sycl_init() {
 
         info.devices[i].cc =
             100 * prop.get_major_version() + 10 * prop.get_minor_version();
+
+        info.max_work_group_sizes[i] = prop.get_max_work_group_size();
     }
 
     for (int id = 0; id < info.device_count; ++id) {
@@ -3031,7 +3033,7 @@ inline void ggml_sycl_op_soft_max(ggml_backend_sycl_context & ctx, const ggml_te
     memcpy(&max_bias, dst->op_params + 1, sizeof(float));
 
     soft_max_f32_sycl(src0_dd, src1 ? src1_dd : nullptr, dst_dd, ne00,
-                      nrows_x, nrows_y, scale, max_bias, main_stream);
+                      nrows_x, nrows_y, scale, max_bias, main_stream, ctx.device);
 }
 
 inline void ggml_sycl_op_scale(ggml_backend_sycl_context & ctx, const ggml_tensor *src0, const ggml_tensor *src1,
diff --git a/ggml/src/ggml-sycl/common.hpp b/ggml/src/ggml-sycl/common.hpp
index 476d847ca575e..9a1c161b69db5 100644
--- a/ggml/src/ggml-sycl/common.hpp
+++ b/ggml/src/ggml-sycl/common.hpp
@@ -47,10 +47,6 @@ static int g_ggml_sycl_debug = 0;
     }                                                                    \
   }()
 
-// #define DEBUG_SYCL_MALLOC
-
-static int g_work_group_size = 0;
-// typedef sycl::half ggml_fp16_t;
 
 #define __SYCL_ARCH__ DPCT_COMPATIBILITY_TEMP
 #define VER_4VEC 610 // todo for hardward optimize.
@@ -193,6 +189,8 @@ struct ggml_sycl_device_info {
     sycl_device_info devices[GGML_SYCL_MAX_DEVICES] = {};
 
     std::array default_tensor_split = {};
+
+    int max_work_group_sizes[GGML_SYCL_MAX_DEVICES] = {0};
 };
 
 const ggml_sycl_device_info & ggml_sycl_info();
@@ -295,15 +293,6 @@ struct ggml_backend_sycl_context {
     }
 };
 
-// common host functions
-
-static inline int get_work_group_size(const sycl::device& device) {
-    dpct::device_info prop;
-    dpct::get_device_info(prop, device);
-    return prop.get_max_work_group_size();
-}
-
-
 // common device functions
 
 static __dpct_inline__ float warp_reduce_sum(float x,
diff --git a/ggml/src/ggml-sycl/norm.cpp b/ggml/src/ggml-sycl/norm.cpp
index a77f7852ccecd..ed0fa7e31762b 100644
--- a/ggml/src/ggml-sycl/norm.cpp
+++ b/ggml/src/ggml-sycl/norm.cpp
@@ -181,7 +181,7 @@ static void rms_norm_f32(const float* x, float* dst, const int ncols, const floa
 
 static void norm_f32_sycl(const float* x, float* dst, const int ncols,
     const int nrows, const float eps,
-    queue_ptr stream) {
+    queue_ptr stream, int device) {
     GGML_ASSERT(ncols % WARP_SIZE == 0);
     if (ncols < 1024) {
         const sycl::range<3> block_dims(1, 1, WARP_SIZE);
@@ -197,7 +197,7 @@ static void norm_f32_sycl(const float* x, float* dst, const int ncols,
             });
     }
     else {
-        const int work_group_size = get_work_group_size(stream->get_device());
+        const int work_group_size = ggml_sycl_info().max_work_group_sizes[device];
         const sycl::range<3> block_dims(1, 1, work_group_size);
         /*
         DPCT1049:17: The work-group size passed to the SYCL kernel may exceed
@@ -222,7 +222,7 @@ static void norm_f32_sycl(const float* x, float* dst, const int ncols,
 
 static void group_norm_f32_sycl(const float* x, float* dst,
     const int num_groups, const int group_size,
-    const int ne_elements, queue_ptr stream) {
+    const int ne_elements, queue_ptr stream, int device) {
     static const float eps = 1e-6f;
     if (group_size < 1024) {
         const sycl::range<3> block_dims(1, 1, WARP_SIZE);
@@ -240,7 +240,7 @@ static void group_norm_f32_sycl(const float* x, float* dst,
             });
     }
     else {
-        const int work_group_size = get_work_group_size(stream->get_device());
+        const int work_group_size = ggml_sycl_info().max_work_group_sizes[device];
         const sycl::range<3> block_dims(1, 1, work_group_size);
         /*
         DPCT1049:18: The work-group size passed to the SYCL kernel may exceed
@@ -269,7 +269,7 @@ static void group_norm_f32_sycl(const float* x, float* dst,
 
 static void rms_norm_f32_sycl(const float* x, float* dst, const int ncols,
     const int nrows, const float eps,
-    queue_ptr stream) {
+    queue_ptr stream, int device) {
     GGML_ASSERT(ncols % WARP_SIZE == 0);
     // printf("%s ncols=%d, nrows=%d, WARP_SIZE=%d\n", __func__, ncols, nrows, WARP_SIZE);
     if (ncols < 1024) {
@@ -286,7 +286,7 @@ static void rms_norm_f32_sycl(const float* x, float* dst, const int ncols,
             });
     }
     else {
-        const int work_group_size = get_work_group_size(stream->get_device());
+        const int work_group_size = ggml_sycl_info().max_work_group_sizes[device];
         const sycl::range<3> block_dims(1, 1, work_group_size);
         /*
         DPCT1049:19: The work-group size passed to the SYCL kernel may exceed
@@ -322,7 +322,7 @@ void ggml_sycl_op_norm(ggml_backend_sycl_context& ctx, const ggml_tensor* src0,
     float eps;
     memcpy(&eps, dst->op_params, sizeof(float));
 
-    norm_f32_sycl(src0_dd, dst_dd, ne00, nrows, eps, main_stream);
+    norm_f32_sycl(src0_dd, dst_dd, ne00, nrows, eps, main_stream, ctx.device);
 
     (void)src1;
     (void)dst;
@@ -340,7 +340,7 @@ void ggml_sycl_op_group_norm(ggml_backend_sycl_context& ctx, const ggml_tensor*
 
     int num_groups = dst->op_params[0];
     int group_size = src0->ne[0] * src0->ne[1] * ((src0->ne[2] + num_groups - 1) / num_groups);
-    group_norm_f32_sycl(src0_dd, dst_dd, num_groups, group_size, src0->ne[0] * src0->ne[1] * src0->ne[2], main_stream);
+    group_norm_f32_sycl(src0_dd, dst_dd, num_groups, group_size, src0->ne[0] * src0->ne[1] * src0->ne[2], main_stream, ctx.device);
 
     (void)src1;
     (void)dst;
@@ -362,7 +362,7 @@ void ggml_sycl_op_rms_norm(ggml_backend_sycl_context& ctx, const ggml_tensor* sr
     float eps;
     memcpy(&eps, dst->op_params, sizeof(float));
 
-    rms_norm_f32_sycl(src0_dd, dst_dd, ne00, nrows, eps, main_stream);
+    rms_norm_f32_sycl(src0_dd, dst_dd, ne00, nrows, eps, main_stream, ctx.device);
 
     (void)src1;
     (void)dst;

From e235b267a2539d043734ff340eff74107722eb57 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Fri, 5 Jul 2024 07:53:33 +0300
Subject: [PATCH 099/326] py : switch to snake_case (#8305)

* py : switch to snake_case

ggml-ci

* cont

ggml-ci

* cont

ggml-ci

* cont : fix link

* gguf-py : use snake_case in scripts entrypoint export

* py : rename requirements for convert_legacy_llama.py

Needed for scripts/check-requirements.sh

---------

Co-authored-by: Francis Couture-Harpin 
---
 README.md                                     |  8 +++---
 ci/run.sh                                     |  6 ++---
 convert_hf_to_gguf.py                         |  8 +++---
 convert_hf_to_gguf_update.py                  | 26 +++++++++----------
 docs/HOWTO-add-model.md                       |  2 +-
 ...egacy-llama.py => convert_legacy_llama.py} |  0
 ...=> convert_finetune_checkpoint_to_gguf.py} |  0
 ...ple.py => json_schema_pydantic_example.py} |  2 +-
 examples/llava/MobileVLM-README.md            | 14 +++++-----
 examples/llava/README.md                      | 20 +++++++-------
 ...uf.py => convert_image_encoder_to_gguf.py} |  0
 .../{llava-surgery.py => llava_surgery.py}    |  0
 ...lava-surgery-v2.py => llava_surgery_v2.py} |  0
 examples/llava/requirements.txt               |  2 +-
 ...=> pydantic_models_to_grammar_examples.py} |  0
 ...egex-to-grammar.py => regex_to_grammar.py} |  0
 examples/{server-embd.py => server_embd.py}   |  0
 ...py => convert_train_checkpoint_to_gguf.py} |  0
 gguf-py/README.md                             | 10 +++----
 gguf-py/scripts/__init__.py                   | 17 +++---------
 ...nvert-endian.py => gguf_convert_endian.py} |  0
 .../scripts/{gguf-dump.py => gguf_dump.py}    |  0
 ...f-new-metadata.py => gguf_new_metadata.py} |  0
 ...f-set-metadata.py => gguf_set_metadata.py} |  0
 requirements.txt                              |  2 +-
 .../requirements-convert_hf_to_gguf.txt       |  2 +-
 ...requirements-convert_hf_to_gguf_update.txt |  2 +-
 ... => requirements-convert_legacy_llama.txt} |  0
 ...equirements-convert_llama_ggml_to_gguf.txt |  2 +-
 scripts/check-requirements.sh                 | 10 +++----
 scripts/convert-gg.sh                         | 26 -------------------
 scripts/pod-llama.sh                          | 14 +++++-----
 32 files changed, 69 insertions(+), 104 deletions(-)
 rename examples/{convert-legacy-llama.py => convert_legacy_llama.py} (100%)
 rename examples/finetune/{convert-finetune-checkpoint-to-gguf.py => convert_finetune_checkpoint_to_gguf.py} (100%)
 rename examples/{json-schema-pydantic-example.py => json_schema_pydantic_example.py} (98%)
 rename examples/llava/{convert-image-encoder-to-gguf.py => convert_image_encoder_to_gguf.py} (100%)
 rename examples/llava/{llava-surgery.py => llava_surgery.py} (100%)
 rename examples/llava/{llava-surgery-v2.py => llava_surgery_v2.py} (100%)
 rename examples/{pydantic-models-to-grammar-examples.py => pydantic_models_to_grammar_examples.py} (100%)
 rename examples/{regex-to-grammar.py => regex_to_grammar.py} (100%)
 rename examples/{server-embd.py => server_embd.py} (100%)
 rename examples/train-text-from-scratch/{convert-train-checkpoint-to-gguf.py => convert_train_checkpoint_to_gguf.py} (100%)
 rename gguf-py/scripts/{gguf-convert-endian.py => gguf_convert_endian.py} (100%)
 rename gguf-py/scripts/{gguf-dump.py => gguf_dump.py} (100%)
 rename gguf-py/scripts/{gguf-new-metadata.py => gguf_new_metadata.py} (100%)
 rename gguf-py/scripts/{gguf-set-metadata.py => gguf_set_metadata.py} (100%)
 rename requirements/{requirements-convert-legacy-llama.txt => requirements-convert_legacy_llama.txt} (100%)
 delete mode 100755 scripts/convert-gg.sh

diff --git a/README.md b/README.md
index 3569b2bbb5e34..0cc1d10f4cb08 100644
--- a/README.md
+++ b/README.md
@@ -26,7 +26,7 @@ Inference of Meta's [LLaMA](https://arxiv.org/abs/2302.13971) model (and others)
 
 ### Hot topics
 
-- **`convert.py` has been deprecated and moved to `examples/convert-legacy-llama.py`, please use `convert-hf-to-gguf.py`** https://github.com/ggerganov/llama.cpp/pull/7430
+- **`convert.py` has been deprecated and moved to `examples/convert_legacy_llama.py`, please use `convert_hf_to_gguf.py`** https://github.com/ggerganov/llama.cpp/pull/7430
 - Initial Flash-Attention support: https://github.com/ggerganov/llama.cpp/pull/5021
 - BPE pre-tokenization support has been added: https://github.com/ggerganov/llama.cpp/pull/6920
 - MoE memory layout has been updated - reconvert models for `mmap` support and regenerate `imatrix` https://github.com/ggerganov/llama.cpp/pull/6387
@@ -636,8 +636,8 @@ Building the program with BLAS support may lead to some performance improvements
 
 To obtain the official LLaMA 2 weights please see the Obtaining and using the Facebook LLaMA 2 model section. There is also a large selection of pre-quantized `gguf` models available on Hugging Face.
 
-Note: `convert.py` has been moved to `examples/convert-legacy-llama.py` and shouldn't be used for anything other than `Llama/Llama2/Mistral` models and their derivatives.
-It does not support LLaMA 3, you can use `convert-hf-to-gguf.py` with LLaMA 3 downloaded from Hugging Face.
+Note: `convert.py` has been moved to `examples/convert_legacy_llama.py` and shouldn't be used for anything other than `Llama/Llama2/Mistral` models and their derivatives.
+It does not support LLaMA 3, you can use `convert_hf_to_gguf.py` with LLaMA 3 downloaded from Hugging Face.
 
 ```bash
 # obtain the official LLaMA model weights and place them in ./models
@@ -654,7 +654,7 @@ ls ./models
 python3 -m pip install -r requirements.txt
 
 # convert the model to ggml FP16 format
-python3 convert-hf-to-gguf.py models/mymodel/
+python3 convert_hf_to_gguf.py models/mymodel/
 
 # quantize the model to 4-bits (using Q4_K_M method)
 ./llama-quantize ./models/mymodel/ggml-model-f16.gguf ./models/mymodel/ggml-model-Q4_K_M.gguf Q4_K_M
diff --git a/ci/run.sh b/ci/run.sh
index 067ac405b412a..9703b77ce51db 100755
--- a/ci/run.sh
+++ b/ci/run.sh
@@ -287,7 +287,7 @@ function gg_run_open_llama_7b_v2 {
     (time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} -DGGML_CUDA=1 .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
     (time make -j                                                           ) 2>&1 | tee -a $OUT/${ci}-make.log
 
-    python3 ../examples/convert-legacy-llama.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
+    python3 ../examples/convert_legacy_llama.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
 
     model_f16="${path_models}/ggml-model-f16.gguf"
     model_q8_0="${path_models}/ggml-model-q8_0.gguf"
@@ -421,7 +421,7 @@ function gg_run_pythia_1_4b {
     (time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
     (time make -j                                            ) 2>&1 | tee -a $OUT/${ci}-make.log
 
-    python3 ../convert-hf-to-gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
+    python3 ../convert_hf_to_gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
 
     model_f16="${path_models}/ggml-model-f16.gguf"
     model_q8_0="${path_models}/ggml-model-q8_0.gguf"
@@ -553,7 +553,7 @@ function gg_run_pythia_2_8b {
     (time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} -DGGML_CUDA=1 .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
     (time make -j                                                           ) 2>&1 | tee -a $OUT/${ci}-make.log
 
-    python3 ../convert-hf-to-gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
+    python3 ../convert_hf_to_gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
 
     model_f16="${path_models}/ggml-model-f16.gguf"
     model_q8_0="${path_models}/ggml-model-q8_0.gguf"
diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py
index bdc336644e626..ed54905932044 100755
--- a/convert_hf_to_gguf.py
+++ b/convert_hf_to_gguf.py
@@ -404,7 +404,7 @@ def get_vocab_base(self) -> tuple[list[str], list[int], str]:
 
         return tokens, toktypes, tokpre
 
-    # NOTE: this function is generated by convert-hf-to-gguf-update.py
+    # NOTE: this function is generated by convert_hf_to_gguf_update.py
     #       do not modify it manually!
     # ref:  https://github.com/ggerganov/llama.cpp/pull/6920
     # Marker: Start get_vocab_base_pre
@@ -424,7 +424,7 @@ def get_vocab_base_pre(self, tokenizer) -> str:
 
         res = None
 
-        # NOTE: if you get an error here, you need to update the convert-hf-to-gguf-update.py script
+        # NOTE: if you get an error here, you need to update the convert_hf_to_gguf_update.py script
         #       or pull the latest version of the model from Huggingface
         #       don't edit the hashes manually!
         if chkhsh == "0ef9807a4087ebef797fc749390439009c3b9eda9ad1a097abbe738f486c01e5":
@@ -499,9 +499,9 @@ def get_vocab_base_pre(self, tokenizer) -> str:
             logger.warning("**************************************************************************************")
             logger.warning("** WARNING: The BPE pre-tokenizer was not recognized!")
             logger.warning("**          There are 2 possible reasons for this:")
-            logger.warning("**          - the model has not been added to convert-hf-to-gguf-update.py yet")
+            logger.warning("**          - the model has not been added to convert_hf_to_gguf_update.py yet")
             logger.warning("**          - the pre-tokenization config has changed upstream")
-            logger.warning("**          Check your model files and convert-hf-to-gguf-update.py and update them accordingly.")
+            logger.warning("**          Check your model files and convert_hf_to_gguf_update.py and update them accordingly.")
             logger.warning("** ref:     https://github.com/ggerganov/llama.cpp/pull/6920")
             logger.warning("**")
             logger.warning(f"** chkhsh:  {chkhsh}")
diff --git a/convert_hf_to_gguf_update.py b/convert_hf_to_gguf_update.py
index 21a3062554578..e4165ae2d977c 100755
--- a/convert_hf_to_gguf_update.py
+++ b/convert_hf_to_gguf_update.py
@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 
 # This script downloads the tokenizer models of the specified models from Huggingface and
-# generates the get_vocab_base_pre() function for convert-hf-to-gguf.py
+# generates the get_vocab_base_pre() function for convert_hf_to_gguf.py
 #
 # This is necessary in order to analyze the type of pre-tokenizer used by the model and
 # provide the necessary information to llama.cpp via the GGUF header in order to implement
@@ -15,9 +15,9 @@
 # - Add a new model to the "models" list
 # - Run the script with your huggingface token:
 #
-#   python3 convert-hf-to-gguf-update.py 
+#   python3 convert_hf_to_gguf_update.py 
 #
-# - Copy-paste the generated get_vocab_base_pre() function into convert-hf-to-gguf.py
+# - Copy-paste the generated get_vocab_base_pre() function into convert_hf_to_gguf.py
 # - Update llama.cpp with the new pre-tokenizer if necessary
 #
 # TODO: generate tokenizer tests for llama.cpp
@@ -37,7 +37,7 @@
 from transformers import AutoTokenizer
 
 logging.basicConfig(level=logging.DEBUG)
-logger = logging.getLogger("convert-hf-to-gguf-update")
+logger = logging.getLogger("convert_hf_to_gguf_update")
 sess = requests.Session()
 
 
@@ -56,10 +56,10 @@ class TOKENIZER_TYPE(IntEnum):
     token = sys.argv[1]
     if not token.startswith("hf_"):
         logger.info("Huggingface token seems invalid")
-        logger.info("Usage: python convert-hf-to-gguf-update.py ")
+        logger.info("Usage: python convert_hf_to_gguf_update.py ")
         sys.exit(1)
 else:
-    logger.info("Usage: python convert-hf-to-gguf-update.py ")
+    logger.info("Usage: python convert_hf_to_gguf_update.py ")
     sys.exit(1)
 
 # TODO: add models here, base models preferred
@@ -134,7 +134,7 @@ def download_model(model):
         logger.error(f"Failed to download model {model['name']}. Error: {e}")
 
 
-# generate the source code for the convert-hf-to-gguf.py:get_vocab_base_pre() function:
+# generate the source code for the convert_hf_to_gguf.py:get_vocab_base_pre() function:
 
 src_ifs = ""
 for model in models:
@@ -201,7 +201,7 @@ def get_vocab_base_pre(self, tokenizer) -> str:
 
         res = None
 
-        # NOTE: if you get an error here, you need to update the convert-hf-to-gguf-update.py script
+        # NOTE: if you get an error here, you need to update the convert_hf_to_gguf_update.py script
         #       or pull the latest version of the model from Huggingface
         #       don't edit the hashes manually!
 {src_ifs}
@@ -210,9 +210,9 @@ def get_vocab_base_pre(self, tokenizer) -> str:
             logger.warning("**************************************************************************************")
             logger.warning("** WARNING: The BPE pre-tokenizer was not recognized!")
             logger.warning("**          There are 2 possible reasons for this:")
-            logger.warning("**          - the model has not been added to convert-hf-to-gguf-update.py yet")
+            logger.warning("**          - the model has not been added to convert_hf_to_gguf_update.py yet")
             logger.warning("**          - the pre-tokenization config has changed upstream")
-            logger.warning("**          Check your model files and convert-hf-to-gguf-update.py and update them accordingly.")
+            logger.warning("**          Check your model files and convert_hf_to_gguf_update.py and update them accordingly.")
             logger.warning("** ref:     https://github.com/ggerganov/llama.cpp/pull/6920")
             logger.warning("**")
             logger.warning(f"** chkhsh:  {{chkhsh}}")
@@ -226,7 +226,7 @@ def get_vocab_base_pre(self, tokenizer) -> str:
         return res
 """
 
-convert_py_pth = pathlib.Path("convert-hf-to-gguf.py")
+convert_py_pth = pathlib.Path("convert_hf_to_gguf.py")
 convert_py = convert_py_pth.read_text(encoding="utf-8")
 convert_py = re.sub(
     r"(# Marker: Start get_vocab_base_pre)(.+?)( +# Marker: End get_vocab_base_pre)",
@@ -237,7 +237,7 @@ def get_vocab_base_pre(self, tokenizer) -> str:
 
 convert_py_pth.write_text(convert_py, encoding="utf-8")
 
-logger.info("+++ convert-hf-to-gguf.py was updated")
+logger.info("+++ convert_hf_to_gguf.py was updated")
 
 # generate tests for each tokenizer model
 
@@ -343,6 +343,6 @@ def get_vocab_base_pre(self, tokenizer) -> str:
 for model in models:
     name = model["name"]
 
-    print(f"python3 convert-hf-to-gguf.py models/tokenizers/{name}/ --outfile models/ggml-vocab-{name}.gguf --vocab-only") # noqa: NP100
+    print(f"python3 convert_hf_to_gguf.py models/tokenizers/{name}/ --outfile models/ggml-vocab-{name}.gguf --vocab-only") # noqa: NP100
 
 logger.info("\n")
diff --git a/docs/HOWTO-add-model.md b/docs/HOWTO-add-model.md
index 3eec077ea7bd9..87093cedd9ab6 100644
--- a/docs/HOWTO-add-model.md
+++ b/docs/HOWTO-add-model.md
@@ -17,7 +17,7 @@ Also, it is important to check that the examples and main ggml backends (CUDA, M
 ### 1. Convert the model to GGUF
 
 This step is done in python with a `convert` script using the [gguf](https://pypi.org/project/gguf/) library.
-Depending on the model architecture, you can use either [convert-hf-to-gguf.py](../convert-hf-to-gguf.py) or [examples/convert-legacy-llama.py](../examples/convert-legacy-llama.py) (for `llama/llama2` models in `.pth` format).
+Depending on the model architecture, you can use either [convert_hf_to_gguf.py](../convert_hf_to_gguf.py) or [examples/convert_legacy_llama.py](../examples/convert_legacy_llama.py) (for `llama/llama2` models in `.pth` format).
 
 The convert script reads the model configuration, tokenizer, tensor names+data and converts them to GGUF metadata and tensors.
 
diff --git a/examples/convert-legacy-llama.py b/examples/convert_legacy_llama.py
similarity index 100%
rename from examples/convert-legacy-llama.py
rename to examples/convert_legacy_llama.py
diff --git a/examples/finetune/convert-finetune-checkpoint-to-gguf.py b/examples/finetune/convert_finetune_checkpoint_to_gguf.py
similarity index 100%
rename from examples/finetune/convert-finetune-checkpoint-to-gguf.py
rename to examples/finetune/convert_finetune_checkpoint_to_gguf.py
diff --git a/examples/json-schema-pydantic-example.py b/examples/json_schema_pydantic_example.py
similarity index 98%
rename from examples/json-schema-pydantic-example.py
rename to examples/json_schema_pydantic_example.py
index 2a24f81189fb1..c7ca7b8d9041a 100644
--- a/examples/json-schema-pydantic-example.py
+++ b/examples/json_schema_pydantic_example.py
@@ -1,7 +1,7 @@
 # Usage:
 #! ./llama-server -m some-model.gguf &
 #! pip install pydantic
-#! python json-schema-pydantic-example.py
+#! python json_schema_pydantic_example.py
 
 from pydantic import BaseModel, Extra, TypeAdapter
 from annotated_types import MinLen
diff --git a/examples/llava/MobileVLM-README.md b/examples/llava/MobileVLM-README.md
index f6c619c87df55..06a65fba4787a 100644
--- a/examples/llava/MobileVLM-README.md
+++ b/examples/llava/MobileVLM-README.md
@@ -30,16 +30,16 @@ git clone https://huggingface.co/mtgv/MobileVLM-1.7B
 git clone https://huggingface.co/openai/clip-vit-large-patch14-336
 ```
 
-2. Use `llava-surgery.py` to split the LLaVA model to LLaMA and multimodel projector constituents:
+2. Use `llava_surgery.py` to split the LLaVA model to LLaMA and multimodel projector constituents:
 
 ```sh
-python ./examples/llava/llava-surgery.py -m path/to/MobileVLM-1.7B
+python ./examples/llava/llava_surgery.py -m path/to/MobileVLM-1.7B
 ```
 
-3. Use `convert-image-encoder-to-gguf.py` with `--projector-type ldp` (for **V2** please use `--projector-type ldpv2`) to convert the LLaVA image encoder to GGUF:
+3. Use `convert_image_encoder_to_gguf.py` with `--projector-type ldp` (for **V2** please use `--projector-type ldpv2`) to convert the LLaVA image encoder to GGUF:
 
 ```sh
-python ./examples/llava/convert-image-encoder-to-gguf \
+python ./examples/llava/convert_image_encoder_to_gguf \
     -m path/to/clip-vit-large-patch14-336 \
     --llava-projector path/to/MobileVLM-1.7B/llava.projector \
     --output-dir path/to/MobileVLM-1.7B \
@@ -47,17 +47,17 @@ python ./examples/llava/convert-image-encoder-to-gguf \
 ```
 
 ```sh
-python ./examples/llava/convert-image-encoder-to-gguf \
+python ./examples/llava/convert_image_encoder_to_gguf \
     -m path/to/clip-vit-large-patch14-336 \
     --llava-projector path/to/MobileVLM-1.7B_V2/llava.projector \
     --output-dir path/to/MobileVLM-1.7B_V2 \
     --projector-type ldpv2
 ```
 
-4. Use `examples/convert-legacy-llama.py` to convert the LLaMA part of LLaVA to GGUF:
+4. Use `examples/convert_legacy_llama.py` to convert the LLaMA part of LLaVA to GGUF:
 
 ```sh
-python ./examples/convert-legacy-llama.py path/to/MobileVLM-1.7B
+python ./examples/convert_legacy_llama.py path/to/MobileVLM-1.7B
 ```
 
 5. Use `quantize` to convert LLaMA part's DataType from `fp16` to `q4_k`
diff --git a/examples/llava/README.md b/examples/llava/README.md
index f4554de676e4c..012451361763c 100644
--- a/examples/llava/README.md
+++ b/examples/llava/README.md
@@ -38,22 +38,22 @@ git clone https://huggingface.co/openai/clip-vit-large-patch14-336
 pip install -r examples/llava/requirements.txt
 ```
 
-3. Use `llava-surgery.py` to split the LLaVA model to LLaMA and multimodel projector constituents:
+3. Use `llava_surgery.py` to split the LLaVA model to LLaMA and multimodel projector constituents:
 
 ```sh
-python ./examples/llava/llava-surgery.py -m ../llava-v1.5-7b
+python ./examples/llava/llava_surgery.py -m ../llava-v1.5-7b
 ```
 
-4. Use `convert-image-encoder-to-gguf.py` to convert the LLaVA image encoder to GGUF:
+4. Use `convert_image_encoder_to_gguf.py` to convert the LLaVA image encoder to GGUF:
 
 ```sh
-python ./examples/llava/convert-image-encoder-to-gguf.py -m ../clip-vit-large-patch14-336 --llava-projector ../llava-v1.5-7b/llava.projector --output-dir ../llava-v1.5-7b
+python ./examples/llava/convert_image_encoder_to_gguf.py -m ../clip-vit-large-patch14-336 --llava-projector ../llava-v1.5-7b/llava.projector --output-dir ../llava-v1.5-7b
 ```
 
-5. Use `examples/convert-legacy-llama.py` to convert the LLaMA part of LLaVA to GGUF:
+5. Use `examples/convert_legacy_llama.py` to convert the LLaMA part of LLaVA to GGUF:
 
 ```sh
-python ./examples/convert-legacy-llama.py ../llava-v1.5-7b --skip-unknown
+python ./examples/convert_legacy_llama.py ../llava-v1.5-7b --skip-unknown
 ```
 
 Now both the LLaMA part and the image encoder are in the `llava-v1.5-7b` directory.
@@ -70,9 +70,9 @@ git clone https://huggingface.co/liuhaotian/llava-v1.6-vicuna-7b
 pip install -r examples/llava/requirements.txt
 ```
 
-3) Use `llava-surgery-v2.py` which also supports llava-1.5 variants pytorch as well as safetensor models:
+3) Use `llava_surgery_v2.py` which also supports llava-1.5 variants pytorch as well as safetensor models:
 ```console
-python examples/llava/llava-surgery-v2.py -C -m ../llava-v1.6-vicuna-7b/
+python examples/llava/llava_surgery_v2.py -C -m ../llava-v1.6-vicuna-7b/
 ```
 - you will find a llava.projector and a llava.clip file in your model directory
 
@@ -86,13 +86,13 @@ curl -s -q https://huggingface.co/cmp-nct/llava-1.6-gguf/raw/main/config_vit.jso
 
 5) Create the visual gguf model:
 ```console
-python ./examples/llava/convert-image-encoder-to-gguf.py -m vit --llava-projector vit/llava.projector --output-dir vit --clip-model-is-vision
+python ./examples/llava/convert_image_encoder_to_gguf.py -m vit --llava-projector vit/llava.projector --output-dir vit --clip-model-is-vision
 ```
 - This is similar to llava-1.5, the difference is that we tell the encoder that we are working with the pure vision model part of CLIP
 
 6) Then convert the model to gguf format:
 ```console
-python ./examples/convert-legacy-llama.py ../llava-v1.6-vicuna-7b/ --skip-unknown
+python ./examples/convert_legacy_llama.py ../llava-v1.6-vicuna-7b/ --skip-unknown
 ```
 
 7) And finally we can run the llava cli using the 1.6 model version:
diff --git a/examples/llava/convert-image-encoder-to-gguf.py b/examples/llava/convert_image_encoder_to_gguf.py
similarity index 100%
rename from examples/llava/convert-image-encoder-to-gguf.py
rename to examples/llava/convert_image_encoder_to_gguf.py
diff --git a/examples/llava/llava-surgery.py b/examples/llava/llava_surgery.py
similarity index 100%
rename from examples/llava/llava-surgery.py
rename to examples/llava/llava_surgery.py
diff --git a/examples/llava/llava-surgery-v2.py b/examples/llava/llava_surgery_v2.py
similarity index 100%
rename from examples/llava/llava-surgery-v2.py
rename to examples/llava/llava_surgery_v2.py
diff --git a/examples/llava/requirements.txt b/examples/llava/requirements.txt
index 21149d6fe1494..4713f0a3460f4 100644
--- a/examples/llava/requirements.txt
+++ b/examples/llava/requirements.txt
@@ -1,3 +1,3 @@
--r ../../requirements/requirements-convert-legacy-llama.txt
+-r ../../requirements/requirements-convert_legacy_llama.txt
 pillow~=10.2.0
 torch~=2.2.1
diff --git a/examples/pydantic-models-to-grammar-examples.py b/examples/pydantic_models_to_grammar_examples.py
similarity index 100%
rename from examples/pydantic-models-to-grammar-examples.py
rename to examples/pydantic_models_to_grammar_examples.py
diff --git a/examples/regex-to-grammar.py b/examples/regex_to_grammar.py
similarity index 100%
rename from examples/regex-to-grammar.py
rename to examples/regex_to_grammar.py
diff --git a/examples/server-embd.py b/examples/server_embd.py
similarity index 100%
rename from examples/server-embd.py
rename to examples/server_embd.py
diff --git a/examples/train-text-from-scratch/convert-train-checkpoint-to-gguf.py b/examples/train-text-from-scratch/convert_train_checkpoint_to_gguf.py
similarity index 100%
rename from examples/train-text-from-scratch/convert-train-checkpoint-to-gguf.py
rename to examples/train-text-from-scratch/convert_train_checkpoint_to_gguf.py
diff --git a/gguf-py/README.md b/gguf-py/README.md
index a04c22759793d..bc46d6e1dd708 100644
--- a/gguf-py/README.md
+++ b/gguf-py/README.md
@@ -3,7 +3,7 @@
 This is a Python package for writing binary files in the [GGUF](https://github.com/ggerganov/ggml/pull/302)
 (GGML Universal File) format.
 
-See [convert-llama-hf-to-gguf.py](https://github.com/ggerganov/llama.cpp/blob/master/convert-hf-to-gguf.py)
+See [convert_hf_to_gguf.py](https://github.com/ggerganov/llama.cpp/blob/master/convert_hf_to_gguf.py)
 as an example for its usage.
 
 ## Installation
@@ -15,13 +15,13 @@ pip install gguf
 
 [examples/writer.py](https://github.com/ggerganov/llama.cpp/blob/master/gguf-py/examples/writer.py) — Generates `example.gguf` in the current directory to demonstrate generating a GGUF file. Note that this file cannot be used as a model.
 
-[scripts/gguf-dump.py](https://github.com/ggerganov/llama.cpp/blob/master/gguf-py/scripts/gguf-dump.py) — Dumps a GGUF file's metadata to the console.
+[scripts/gguf_dump.py](https://github.com/ggerganov/llama.cpp/blob/master/gguf-py/scripts/gguf_dump.py) — Dumps a GGUF file's metadata to the console.
 
-[scripts/gguf-set-metadata.py](https://github.com/ggerganov/llama.cpp/blob/master/gguf-py/scripts/gguf-set-metadata.py) — Allows changing simple metadata values in a GGUF file by key.
+[scripts/gguf_set_metadata.py](https://github.com/ggerganov/llama.cpp/blob/master/gguf-py/scripts/gguf_set_metadata.py) — Allows changing simple metadata values in a GGUF file by key.
 
-[scripts/gguf-convert-endian.py](https://github.com/ggerganov/llama.cpp/blob/master/gguf-py/scripts/gguf-convert-endian.py) — Allows converting the endianness of GGUF files.
+[scripts/gguf_convert_endian.py](https://github.com/ggerganov/llama.cpp/blob/master/gguf-py/scripts/gguf_convert_endian.py) — Allows converting the endianness of GGUF files.
 
-[scripts/gguf-new-metadata.py](https://github.com/ggerganov/llama.cpp/blob/master/gguf-py/scripts/gguf-new-metadata.py) — Copies a GGUF file with added/modified/removed metadata values.
+[scripts/gguf_new_metadata.py](https://github.com/ggerganov/llama.cpp/blob/master/gguf-py/scripts/gguf_new_metadata.py) — Copies a GGUF file with added/modified/removed metadata values.
 
 ## Development
 Maintainers who participate in development of this package are advised to install it in editable mode:
diff --git a/gguf-py/scripts/__init__.py b/gguf-py/scripts/__init__.py
index 1ad45639a62ea..f9d29cb691d62 100644
--- a/gguf-py/scripts/__init__.py
+++ b/gguf-py/scripts/__init__.py
@@ -1,13 +1,4 @@
-import os
-
-from importlib import import_module
-
-
-os.environ["NO_LOCAL_GGUF"] = "TRUE"
-
-gguf_convert_endian_entrypoint = import_module("scripts.gguf-convert-endian").main
-gguf_dump_entrypoint           = import_module("scripts.gguf-dump").main
-gguf_set_metadata_entrypoint   = import_module("scripts.gguf-set-metadata").main
-gguf_new_metadata_entrypoint   = import_module("scripts.gguf-new-metadata").main
-
-del import_module, os
+from .gguf_convert_endian import main as gguf_convert_endian_entrypoint
+from .gguf_dump import main as gguf_dump_entrypoint
+from .gguf_set_metadata import main as gguf_set_metadata_entrypoint
+from .gguf_new_metadata import main as gguf_new_metadata_entrypoint
diff --git a/gguf-py/scripts/gguf-convert-endian.py b/gguf-py/scripts/gguf_convert_endian.py
similarity index 100%
rename from gguf-py/scripts/gguf-convert-endian.py
rename to gguf-py/scripts/gguf_convert_endian.py
diff --git a/gguf-py/scripts/gguf-dump.py b/gguf-py/scripts/gguf_dump.py
similarity index 100%
rename from gguf-py/scripts/gguf-dump.py
rename to gguf-py/scripts/gguf_dump.py
diff --git a/gguf-py/scripts/gguf-new-metadata.py b/gguf-py/scripts/gguf_new_metadata.py
similarity index 100%
rename from gguf-py/scripts/gguf-new-metadata.py
rename to gguf-py/scripts/gguf_new_metadata.py
diff --git a/gguf-py/scripts/gguf-set-metadata.py b/gguf-py/scripts/gguf_set_metadata.py
similarity index 100%
rename from gguf-py/scripts/gguf-set-metadata.py
rename to gguf-py/scripts/gguf_set_metadata.py
diff --git a/requirements.txt b/requirements.txt
index 1eca1a13f999e..52456c2e6fd24 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -4,7 +4,7 @@
 # Package versions must stay compatible across all top-level python scripts.
 #
 
--r ./requirements/requirements-convert-legacy-llama.txt
+-r ./requirements/requirements-convert_legacy_llama.txt
 
 -r ./requirements/requirements-convert_hf_to_gguf.txt
 -r ./requirements/requirements-convert_hf_to_gguf_update.txt
diff --git a/requirements/requirements-convert_hf_to_gguf.txt b/requirements/requirements-convert_hf_to_gguf.txt
index a7112f39655ee..653355c07d68c 100644
--- a/requirements/requirements-convert_hf_to_gguf.txt
+++ b/requirements/requirements-convert_hf_to_gguf.txt
@@ -1,2 +1,2 @@
--r ./requirements-convert-legacy-llama.txt
+-r ./requirements-convert_legacy_llama.txt
 torch~=2.2.1
diff --git a/requirements/requirements-convert_hf_to_gguf_update.txt b/requirements/requirements-convert_hf_to_gguf_update.txt
index a7112f39655ee..653355c07d68c 100644
--- a/requirements/requirements-convert_hf_to_gguf_update.txt
+++ b/requirements/requirements-convert_hf_to_gguf_update.txt
@@ -1,2 +1,2 @@
--r ./requirements-convert-legacy-llama.txt
+-r ./requirements-convert_legacy_llama.txt
 torch~=2.2.1
diff --git a/requirements/requirements-convert-legacy-llama.txt b/requirements/requirements-convert_legacy_llama.txt
similarity index 100%
rename from requirements/requirements-convert-legacy-llama.txt
rename to requirements/requirements-convert_legacy_llama.txt
diff --git a/requirements/requirements-convert_llama_ggml_to_gguf.txt b/requirements/requirements-convert_llama_ggml_to_gguf.txt
index e80c29012a674..afe2747d448d4 100644
--- a/requirements/requirements-convert_llama_ggml_to_gguf.txt
+++ b/requirements/requirements-convert_llama_ggml_to_gguf.txt
@@ -1 +1 @@
--r ./requirements-convert-legacy-llama.txt
+-r ./requirements-convert_legacy_llama.txt
diff --git a/scripts/check-requirements.sh b/scripts/check-requirements.sh
index 69a08c8410768..48f924c02d32c 100755
--- a/scripts/check-requirements.sh
+++ b/scripts/check-requirements.sh
@@ -97,9 +97,9 @@ check_requirements() {
 }
 
 check_convert_script() {
-    local py=$1             # e.g. ./convert-hf-to-gguf.py
-    local pyname=${py##*/}  # e.g. convert-hf-to-gguf.py
-    pyname=${pyname%.py}    # e.g. convert-hf-to-gguf
+    local py=$1             # e.g. ./convert_hf_to_gguf.py
+    local pyname=${py##*/}  # e.g. convert_hf_to_gguf.py
+    pyname=${pyname%.py}    # e.g. convert_hf_to_gguf
 
     info "$py: beginning check"
 
@@ -166,9 +166,9 @@ if (( do_cleanup )); then
     rm -rf -- "$all_venv"
 fi
 
-check_convert_script examples/convert-legacy-llama.py
+check_convert_script examples/convert_legacy_llama.py
 for py in convert_*.py; do
-    # skip convert-hf-to-gguf-update.py
+    # skip convert_hf_to_gguf_update.py
     # TODO: the check is failing for some reason:
     #       https://github.com/ggerganov/llama.cpp/actions/runs/8875330981/job/24364557177?pr=6920
     [[ $py == convert_hf_to_gguf_update.py ]] && continue
diff --git a/scripts/convert-gg.sh b/scripts/convert-gg.sh
deleted file mode 100755
index 8a016843290b9..0000000000000
--- a/scripts/convert-gg.sh
+++ /dev/null
@@ -1,26 +0,0 @@
-#!/bin/bash
-
-set -e
-
-# LLaMA v1
-python3 examples/convert-legacy-llama.py ../llama1/7B  --outfile models/llama-7b/ggml-model-f16.gguf  --outtype f16
-python3 examples/convert-legacy-llama.py ../llama1/13B --outfile models/llama-13b/ggml-model-f16.gguf --outtype f16
-python3 examples/convert-legacy-llama.py ../llama1/30B --outfile models/llama-30b/ggml-model-f16.gguf --outtype f16
-python3 examples/convert-legacy-llama.py ../llama1/65B --outfile models/llama-65b/ggml-model-f16.gguf --outtype f16
-
-# LLaMA v2
-python3 examples/convert-legacy-llama.py ../llama2/llama-2-7b  --outfile models/llama-7b-v2/ggml-model-f16.gguf  --outtype f16
-python3 examples/convert-legacy-llama.py ../llama2/llama-2-13b --outfile models/llama-13b-v2/ggml-model-f16.gguf --outtype f16
-python3 examples/convert-legacy-llama.py ../llama2/llama-2-70b --outfile models/llama-70b-v2/ggml-model-f16.gguf --outtype f16
-
-# Code Llama
-python3 examples/convert-legacy-llama.py ../codellama/CodeLlama-7b/  --outfile models/codellama-7b/ggml-model-f16.gguf  --outtype f16
-python3 examples/convert-legacy-llama.py ../codellama/CodeLlama-13b/ --outfile models/codellama-13b/ggml-model-f16.gguf --outtype f16
-python3 examples/convert-legacy-llama.py ../codellama/CodeLlama-34b/ --outfile models/codellama-34b/ggml-model-f16.gguf --outtype f16
-
-# Falcon
-python3 convert-falcon-hf-to-gguf.py ../falcon/falcon-7b  1
-mv -v ../falcon/falcon-7b/ggml-model-f16.gguf models/falcon-7b/ggml-model-f16.gguf
-
-python3 convert-falcon-hf-to-gguf.py ../falcon/falcon-40b 1
-mv -v ../falcon/falcon-40b/ggml-model-f16.gguf models/falcon-40b/ggml-model-f16.gguf
diff --git a/scripts/pod-llama.sh b/scripts/pod-llama.sh
index 0d6d4032d8a9e..6e56e1ed0908c 100644
--- a/scripts/pod-llama.sh
+++ b/scripts/pod-llama.sh
@@ -75,7 +75,7 @@ if [ "$1" -eq "1" ]; then
 
     cd /workspace/llama.cpp
 
-    python3 examples/convert-legacy-llama.py ./models/tinyllama-1b  --outfile ./models/tinyllama-1b/ggml-model-f16.gguf  --outtype f16
+    python3 examples/convert_legacy_llama.py ./models/tinyllama-1b  --outfile ./models/tinyllama-1b/ggml-model-f16.gguf  --outtype f16
 
     ./llama-quantize ./models/tinyllama-1b/ggml-model-f16.gguf ./models/tinyllama-1b/ggml-model-q4_0.gguf q4_0
     ./llama-quantize ./models/tinyllama-1b/ggml-model-f16.gguf ./models/tinyllama-1b/ggml-model-q4_k.gguf q4_k
@@ -90,7 +90,7 @@ if [ "$1" -eq "2" ]; then
 
     cd /workspace/llama.cpp
 
-    python3 examples/convert-legacy-llama.py ./models/codellama-7b  --outfile ./models/codellama-7b/ggml-model-f16.gguf  --outtype f16
+    python3 examples/convert_legacy_llama.py ./models/codellama-7b  --outfile ./models/codellama-7b/ggml-model-f16.gguf  --outtype f16
 
     ./llama-quantize ./models/codellama-7b/ggml-model-f16.gguf ./models/codellama-7b/ggml-model-q4_0.gguf q4_0
     ./llama-quantize ./models/codellama-7b/ggml-model-f16.gguf ./models/codellama-7b/ggml-model-q4_k.gguf q4_k
@@ -105,7 +105,7 @@ if [ "$1" -eq "3" ]; then
 
     cd /workspace/llama.cpp
 
-    python3 examples/convert-legacy-llama.py ./models/codellama-13b --outfile ./models/codellama-13b/ggml-model-f16.gguf --outtype f16
+    python3 examples/convert_legacy_llama.py ./models/codellama-13b --outfile ./models/codellama-13b/ggml-model-f16.gguf --outtype f16
 
     ./llama-quantize ./models/codellama-13b/ggml-model-f16.gguf ./models/codellama-13b/ggml-model-q4_0.gguf q4_0
     ./llama-quantize ./models/codellama-13b/ggml-model-f16.gguf ./models/codellama-13b/ggml-model-q4_k.gguf q4_k
@@ -120,7 +120,7 @@ if [ "$1" -eq "4" ]; then
 
     cd /workspace/llama.cpp
 
-    python3 examples/convert-legacy-llama.py ./models/codellama-34b --outfile ./models/codellama-34b/ggml-model-f16.gguf --outtype f16
+    python3 examples/convert_legacy_llama.py ./models/codellama-34b --outfile ./models/codellama-34b/ggml-model-f16.gguf --outtype f16
 
     ./llama-quantize ./models/codellama-34b/ggml-model-f16.gguf ./models/codellama-34b/ggml-model-q4_0.gguf q4_0
     ./llama-quantize ./models/codellama-34b/ggml-model-f16.gguf ./models/codellama-34b/ggml-model-q4_k.gguf q4_k
@@ -135,7 +135,7 @@ if [ "$1" -eq "5" ]; then
 
     cd /workspace/llama.cpp
 
-    python3 examples/convert-legacy-llama.py ./models/codellama-7b-instruct  --outfile ./models/codellama-7b-instruct/ggml-model-f16.gguf  --outtype f16
+    python3 examples/convert_legacy_llama.py ./models/codellama-7b-instruct  --outfile ./models/codellama-7b-instruct/ggml-model-f16.gguf  --outtype f16
 
     ./llama-quantize ./models/codellama-7b-instruct/ggml-model-f16.gguf ./models/codellama-7b-instruct/ggml-model-q4_0.gguf q4_0
     ./llama-quantize ./models/codellama-7b-instruct/ggml-model-f16.gguf ./models/codellama-7b-instruct/ggml-model-q4_k.gguf q4_k
@@ -150,7 +150,7 @@ if [ "$1" -eq "6" ]; then
 
     cd /workspace/llama.cpp
 
-    python3 examples/convert-legacy-llama.py ./models/codellama-13b-instruct --outfile ./models/codellama-13b-instruct/ggml-model-f16.gguf --outtype f16
+    python3 examples/convert_legacy_llama.py ./models/codellama-13b-instruct --outfile ./models/codellama-13b-instruct/ggml-model-f16.gguf --outtype f16
 
     ./llama-quantize ./models/codellama-13b-instruct/ggml-model-f16.gguf ./models/codellama-13b-instruct/ggml-model-q4_0.gguf q4_0
     ./llama-quantize ./models/codellama-13b-instruct/ggml-model-f16.gguf ./models/codellama-13b-instruct/ggml-model-q4_k.gguf q4_k
@@ -165,7 +165,7 @@ if [ "$1" -eq "7" ]; then
 
     cd /workspace/llama.cpp
 
-    python3 examples/convert-legacy-llama.py ./models/codellama-34b-instruct --outfile ./models/codellama-34b-instruct/ggml-model-f16.gguf --outtype f16
+    python3 examples/convert_legacy_llama.py ./models/codellama-34b-instruct --outfile ./models/codellama-34b-instruct/ggml-model-f16.gguf --outtype f16
 
     ./llama-quantize ./models/codellama-34b-instruct/ggml-model-f16.gguf ./models/codellama-34b-instruct/ggml-model-q4_0.gguf q4_0
     ./llama-quantize ./models/codellama-34b-instruct/ggml-model-f16.gguf ./models/codellama-34b-instruct/ggml-model-q4_k.gguf q4_k

From a9554e20b66546b0549aebe2e1034bc8afe9d809 Mon Sep 17 00:00:00 2001
From: luoyu-intel 
Date: Fri, 5 Jul 2024 05:06:13 +0000
Subject: [PATCH 100/326] [SYCL] Fix WARP_SIZE=16 bug of Intel GPU (#8266)

* fix group_norm ut

* split softmax

* fix softmax

* add concat support condition

* revert debug code

* move QK_WARP_SIZE to presets.hpp
---
 ggml/src/CMakeLists.txt        |   2 +-
 ggml/src/ggml-sycl.cpp         | 241 +------------------------------
 ggml/src/ggml-sycl/backend.hpp |   1 +
 ggml/src/ggml-sycl/dmmv.cpp    |  31 ++--
 ggml/src/ggml-sycl/norm.cpp    |   8 +-
 ggml/src/ggml-sycl/presets.hpp |   1 +
 ggml/src/ggml-sycl/softmax.cpp | 250 +++++++++++++++++++++++++++++++++
 ggml/src/ggml-sycl/softmax.hpp |  24 ++++
 8 files changed, 301 insertions(+), 257 deletions(-)
 create mode 100644 ggml/src/ggml-sycl/softmax.cpp
 create mode 100644 ggml/src/ggml-sycl/softmax.hpp

diff --git a/ggml/src/CMakeLists.txt b/ggml/src/CMakeLists.txt
index 08b71d410d82e..8d96a04b57beb 100644
--- a/ggml/src/CMakeLists.txt
+++ b/ggml/src/CMakeLists.txt
@@ -490,7 +490,7 @@ if (GGML_SYCL)
         set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fsycl-targets=nvptx64-nvidia-cuda")
         add_compile_definitions(GGML_SYCL_WARP_SIZE=32)
     else()
-        add_compile_definitions(GGML_SYCL_WARP_SIZE=32)
+        add_compile_definitions(GGML_SYCL_WARP_SIZE=16)
     endif()
 
     file(GLOB   GGML_HEADERS_SYCL "ggml-sycl/*.hpp")
diff --git a/ggml/src/ggml-sycl.cpp b/ggml/src/ggml-sycl.cpp
index dde55335bb6da..053cc950a8a39 100644
--- a/ggml/src/ggml-sycl.cpp
+++ b/ggml/src/ggml-sycl.cpp
@@ -892,117 +892,6 @@ static void diag_mask_inf_f32(const float * x, float * dst, const int ncols, con
     dst[i] = x[i] - (col > n_past + row % rows_per_channel) * FLT_MAX;
 }
 
-
-template 
-static void soft_max_f32(const float * x, const float * mask, float * dst, const int ncols_par,
-                         const int nrows_y, const float scale, const float max_bias, const float m0,
-                         const float m1, uint32_t n_head_log2, const sycl::nd_item<3> &item_ct1, float *buf) {
-    const int ncols = ncols_template == 0 ? ncols_par : ncols_template;
-
-    const int tid = item_ct1.get_local_id(2);
-    const int rowx = item_ct1.get_group(2);
-    const int rowy = rowx % nrows_y; // broadcast the mask (y) in the row dimension
-
-    const int block_size = block_size_template == 0 ? item_ct1.get_local_range(2) : block_size_template;
-
-    const int warp_id = item_ct1.get_local_id(2) / WARP_SIZE;
-    const int lane_id = item_ct1.get_local_id(2) % WARP_SIZE;
-
-    float slope = 1.0f;
-
-    // ALiBi
-    if (max_bias > 0.0f) {
-        const uint32_t h = rowx/nrows_y; // head index
-
-        const float base = h < n_head_log2 ? m0 : m1;
-        const int   exp  = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1;
-
-        slope = sycl::pow(base, float(exp));
-    }
-
-    float * vals = vals_smem ? buf + WARP_SIZE : dst + rowx*ncols;
-    float max_val = -INFINITY;
-
-    for (int col0 = 0; col0 < ncols; col0 += block_size) {
-        const int col = col0 + tid;
-
-        if (ncols_template == 0 && col >= ncols) {
-            break;
-        }
-
-        const int ix = rowx*ncols + col;
-        const int iy = rowy*ncols + col;
-
-        const float val = x[ix]*scale + (mask ? slope*mask[iy] : 0.0f);
-
-        vals[col] = val;
-        max_val = sycl::max(max_val, val);
-    }
-
-    // find the max value in the block
-    max_val = warp_reduce_max(max_val, item_ct1);
-    if (block_size > WARP_SIZE) {
-        if (warp_id == 0) {
-            buf[lane_id] = -INFINITY;
-        }
-        item_ct1.barrier(sycl::access::fence_space::local_space);
-
-        if (lane_id == 0) {
-            buf[warp_id] = max_val;
-        }
-        item_ct1.barrier(sycl::access::fence_space::local_space);
-
-        max_val = buf[lane_id];
-        max_val = warp_reduce_max(max_val, item_ct1);
-    }
-
-    float tmp = 0.f;
-
-#pragma unroll
-    for (int col0 = 0; col0 < ncols; col0 += block_size) {
-        const int col = col0 + tid;
-                if (ncols_template == 0 && col >= ncols) {
-            break;
-        }
-
-        const float val = sycl::native::exp(vals[col] - max_val);
-        tmp += val;
-        vals[col] = val;
-    }
-
-    // find the sum of exps in the block
-    tmp = warp_reduce_sum(tmp, item_ct1);
-    if (block_size > WARP_SIZE) {
-        item_ct1.barrier(sycl::access::fence_space::local_space);
-        if (warp_id == 0) {
-            buf[lane_id] = 0.f;
-        }
-        item_ct1.barrier(sycl::access::fence_space::local_space);
-
-        if (lane_id == 0) {
-            buf[warp_id] = tmp;
-        }
-        item_ct1.barrier(sycl::access::fence_space::local_space);
-
-        tmp = buf[lane_id];
-        tmp = warp_reduce_sum(tmp, item_ct1);
-    }
-
-    const float inv_sum = 1.f / tmp;
-
-#pragma unroll
-    for (int col0 = 0; col0 < ncols; col0 += block_size) {
-        const int col = col0 + tid;
-
-        if (ncols_template == 0 && col >= ncols) {
-            return;
-        }
-
-        const int idst = rowx*ncols + col;
-        dst[idst] = vals[col] * inv_sum;
-    }
-}
-
 static void scale_f32(const float * x, float * dst, const float scale, const int k,
                       const sycl::nd_item<3> &item_ct1) {
     const int i = item_ct1.get_local_range(2) * item_ct1.get_group(2) +
@@ -1890,106 +1779,6 @@ static void diag_mask_inf_f32_sycl(const float *x, float *dst,
                          });
 }
 
-template 
-static void soft_max_f32_submitter(const float * x, const float * mask, float * dst, const int ncols_par,
-                                   const int nrows_y, const float scale, const float max_bias, const float m0,
-                                   const float m1, uint32_t n_head_log2, sycl::range<3> block_nums, sycl::range<3> block_dims,
-                                   const size_t n_local_scratch, queue_ptr stream) {
-    stream->submit([&](sycl::handler &cgh) {
-        sycl::local_accessor local_buf_acc(n_local_scratch, cgh);
-
-        cgh.parallel_for(
-            sycl::nd_range<3>(block_nums * block_dims, block_dims),
-            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
-                soft_max_f32(x, mask, dst, ncols_par,
-                                                                             nrows_y, scale, max_bias, m0,
-                                                                             m1, n_head_log2, item_ct1,
-                                                                             local_buf_acc.get_pointer());
-            });
-    });
-}
-
-static void soft_max_f32_sycl(const float * x, const float * mask,
-                              float * dst, const int ncols_x, const int nrows_x,
-                              const int nrows_y, const float scale, const float max_bias,
-                              queue_ptr stream, int device) {
-    int nth = WARP_SIZE;
-    int max_block_size = ggml_sycl_info().max_work_group_sizes[device];
-    while (nth < ncols_x && nth < max_block_size) nth *= 2;
-    if (nth>max_block_size) nth = max_block_size;
-
-    const sycl::range<3> block_dims(1, 1, nth);
-    const sycl::range<3> block_nums(1, 1, nrows_x);
-    const size_t n_local_scratch = (GGML_PAD(ncols_x, WARP_SIZE) + WARP_SIZE);
-
-    const uint32_t n_head_kv   = nrows_x/nrows_y;
-    const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head_kv));
-
-    const float m0 = powf(2.0f, -(max_bias       ) / n_head_log2);
-    const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2);
-
-    const size_t local_mem_size = stream->get_device().get_info();
-    if (n_local_scratch*sizeof(float) < local_mem_size) {
-        if (ncols_x > max_block_size) {
-            soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
-                                               max_bias, m0, m1, n_head_log2, block_nums,
-                                               block_dims, n_local_scratch, stream);
-            return;
-        }
-        switch (ncols_x) {
-            case 32:
-                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
-                                                     max_bias, m0, m1, n_head_log2, block_nums,
-                                                     block_dims, n_local_scratch, stream);
-                break;
-            case 64:
-                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
-                                                     max_bias, m0, m1, n_head_log2, block_nums,
-                                                     block_dims, n_local_scratch, stream);
-                break;
-            case 128:
-                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
-                                                       max_bias, m0, m1, n_head_log2, block_nums,
-                                                       block_dims, n_local_scratch, stream);
-                break;
-            case 256:
-                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
-                                                       max_bias, m0, m1, n_head_log2, block_nums,
-                                                       block_dims, n_local_scratch, stream);
-                break;
-            case 512:
-                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
-                                                       max_bias, m0, m1, n_head_log2, block_nums,
-                                                       block_dims, n_local_scratch, stream);
-                break;
-            case 1024:
-                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
-                                                         max_bias, m0, m1, n_head_log2, block_nums,
-                                                         block_dims, n_local_scratch, stream);
-                break;
-            case 2048:
-                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
-                                                         max_bias, m0, m1, n_head_log2, block_nums,
-                                                         block_dims, n_local_scratch, stream);
-                break;
-            case 4096:
-                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
-                                                         max_bias, m0, m1, n_head_log2, block_nums,
-                                                         block_dims, n_local_scratch, stream);
-                break;
-            default:
-                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
-                                                   max_bias, m0, m1, n_head_log2, block_nums,
-                                                   block_dims, n_local_scratch, stream);
-                break;
-        }
-    } else {
-        soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
-                                            max_bias, m0, m1, n_head_log2, block_nums,
-                                            block_dims, WARP_SIZE, stream);
-    }
-}
-
 template 
 static void im2col_sycl(const float *x, T *dst, int IW, int IH,
                                 int OW, int OH, int KW, int KH, int IC,
@@ -3009,33 +2798,6 @@ inline void ggml_sycl_op_diag_mask_inf(ggml_backend_sycl_context & ctx, const gg
     (void) src1_dd;
 }
 
-inline void ggml_sycl_op_soft_max(ggml_backend_sycl_context & ctx, const ggml_tensor *src0,
-                                  const ggml_tensor *src1, ggml_tensor *dst,
-                                  const float *src0_dd, const float *src1_dd,
-                                  float *dst_dd,
-                                  const queue_ptr &main_stream) {
-
-    GGML_ASSERT(src0->type == GGML_TYPE_F32);
-    GGML_ASSERT( dst->type == GGML_TYPE_F32);
-
-#pragma message("TODO: add ggml_sycl_op_soft_max() F16 src1 support")
-#pragma message("ref:  https://github.com/ggerganov/llama.cpp/pull/5021")
-    GGML_ASSERT(!src1 || src1->type == GGML_TYPE_F32); // src1 contains mask and it is optional
-
-    const int64_t ne00 = src0->ne[0];
-    const int64_t nrows_x = ggml_nrows(src0);
-    const int64_t nrows_y = src0->ne[1];
-
-    float scale = 1.0f;
-    float max_bias = 0.0f;
-
-    memcpy(&scale, dst->op_params + 0, sizeof(float));
-    memcpy(&max_bias, dst->op_params + 1, sizeof(float));
-
-    soft_max_f32_sycl(src0_dd, src1 ? src1_dd : nullptr, dst_dd, ne00,
-                      nrows_x, nrows_y, scale, max_bias, main_stream, ctx.device);
-}
-
 inline void ggml_sycl_op_scale(ggml_backend_sycl_context & ctx, const ggml_tensor *src0, const ggml_tensor *src1,
                                ggml_tensor *dst, const float *src0_dd,
                                const float *src1_dd, float *dst_dd,
@@ -5532,7 +5294,8 @@ GGML_CALL static bool ggml_backend_sycl_supports_op(ggml_backend_t backend, cons
         case GGML_OP_CONCAT:
             {
                 ggml_type src0_type = op->src[0]->type;
-                return src0_type != GGML_TYPE_I32 && src0_type != GGML_TYPE_I16;
+                int dim = op->op_params[0];
+                return ggml_is_contiguous(op->src[0]) && ggml_is_contiguous(op->src[1]) && src0_type != GGML_TYPE_I32 && src0_type != GGML_TYPE_I16 && dim == 2;
             } break;
         case GGML_OP_DUP:
         case GGML_OP_NONE:
diff --git a/ggml/src/ggml-sycl/backend.hpp b/ggml/src/ggml-sycl/backend.hpp
index 3afa3391938f2..2a789edfc909d 100644
--- a/ggml/src/ggml-sycl/backend.hpp
+++ b/ggml/src/ggml-sycl/backend.hpp
@@ -21,5 +21,6 @@
 #include "mmvq.hpp"
 #include "rope.hpp"
 #include "norm.hpp"
+#include "softmax.hpp"
 
 #endif // GGML_SYCL_BACKEND_HPP
diff --git a/ggml/src/ggml-sycl/dmmv.cpp b/ggml/src/ggml-sycl/dmmv.cpp
index 927819281fd0a..70a94fc16b99d 100644
--- a/ggml/src/ggml-sycl/dmmv.cpp
+++ b/ggml/src/ggml-sycl/dmmv.cpp
@@ -3,6 +3,7 @@
 #include "dequantize.hpp"
 #include "presets.hpp"
 
+
 static void convert_f16(const void * vx, const int ib, const int iqs, dfloat2 & v){
     const sycl::half *x = (const sycl::half *)vx;
 
@@ -227,7 +228,7 @@ static void dequantize_mul_mat_vec_q2_k(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+    for (int mask = QK_WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -346,7 +347,7 @@ static void dequantize_mul_mat_vec_q3_k(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+    for (int mask = QK_WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -499,7 +500,7 @@ static void dequantize_mul_mat_vec_q4_k(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+    for (int mask = QK_WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -633,7 +634,7 @@ static void dequantize_mul_mat_vec_q5_k(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+    for (int mask = QK_WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -748,7 +749,7 @@ static void dequantize_mul_mat_vec_q6_k(const void * __restrict__ vx, const floa
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+    for (int mask = QK_WARP_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -873,10 +874,10 @@ static void dequantize_mul_mat_vec_q2_K_sycl(const void *vx, const float *y,
     const int ny = 2; // very slightly faster than 1 even when K_QUANTS_PER_ITERATION = 2
     const int block_num_y = (nrows + ny - 1) / ny;
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, ny, WARP_SIZE);
+    const sycl::range<3> block_dims(1, ny, QK_WARP_SIZE);
     stream->parallel_for(
         sycl::nd_range<3>(block_nums * block_dims, block_dims),
-        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
             dequantize_mul_mat_vec_q2_k(vx, y, dst, ncols, nrows, item_ct1);
         });
 }
@@ -889,10 +890,10 @@ static void dequantize_mul_mat_vec_q3_K_sycl(const void *vx, const float *y,
     const int ny = 2 / K_QUANTS_PER_ITERATION;
     const int block_num_y = (nrows + ny - 1) / ny;
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, ny, WARP_SIZE);
+    const sycl::range<3> block_dims(1, ny, QK_WARP_SIZE);
     stream->parallel_for(
         sycl::nd_range<3>(block_nums * block_dims, block_dims),
-        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
             dequantize_mul_mat_vec_q3_k(vx, y, dst, ncols, nrows, item_ct1);
         });
 }
@@ -905,10 +906,10 @@ static void dequantize_mul_mat_vec_q4_K_sycl(const void *vx, const float *y,
     const int ny = 2 / K_QUANTS_PER_ITERATION;
     const int block_num_y = (nrows + ny - 1) / ny;
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, ny, WARP_SIZE);
+    const sycl::range<3> block_dims(1, ny, QK_WARP_SIZE);
     stream->parallel_for(
         sycl::nd_range<3>(block_nums * block_dims, block_dims),
-        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
             dequantize_mul_mat_vec_q4_k(vx, y, dst, ncols, nrows, item_ct1);
         });
 }
@@ -918,10 +919,10 @@ static void dequantize_mul_mat_vec_q5_K_sycl(const void *vx, const float *y,
                                              const int nrows,
                                              dpct::queue_ptr stream) {
     GGML_ASSERT(ncols % QK_K == 0);
-    const sycl::range<3> block_dims(1, 1, WARP_SIZE);
+    const sycl::range<3> block_dims(1, 1, QK_WARP_SIZE);
     stream->parallel_for(
         sycl::nd_range<3>(sycl::range<3>(1, 1, nrows) * block_dims, block_dims),
-        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
             dequantize_mul_mat_vec_q5_k(vx, y, dst, ncols, item_ct1);
         });
 }
@@ -934,10 +935,10 @@ static void dequantize_mul_mat_vec_q6_K_sycl(const void *vx, const float *y,
     const int ny = 2 / K_QUANTS_PER_ITERATION;
     const int block_num_y = (nrows + ny - 1) / ny;
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, ny, WARP_SIZE);
+    const sycl::range<3> block_dims(1, ny, QK_WARP_SIZE);
     stream->parallel_for(
         sycl::nd_range<3>(block_nums * block_dims, block_dims),
-        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
             dequantize_mul_mat_vec_q6_k(vx, y, dst, ncols, nrows, item_ct1);
         });
 }
diff --git a/ggml/src/ggml-sycl/norm.cpp b/ggml/src/ggml-sycl/norm.cpp
index ed0fa7e31762b..e0c5dfeca96ca 100644
--- a/ggml/src/ggml-sycl/norm.cpp
+++ b/ggml/src/ggml-sycl/norm.cpp
@@ -57,6 +57,7 @@ static void group_norm_f32(const float* x, float* dst, const int group_size, con
     const int nwarps = nthreads / WARP_SIZE;
     assert(nwarps % WARP_SIZE == 0);
     start += item_ct1.get_local_id(2);
+    int nreduce = nwarps / WARP_SIZE;
 
     if (end >= ne_elements) {
         end = ne_elements;
@@ -87,7 +88,6 @@ static void group_norm_f32(const float* x, float* dst, const int group_size, con
         */
         item_ct1.barrier();
         tmp = 0.f;
-        int nreduce = nwarps / WARP_SIZE;
         for (size_t i = 0; i < nreduce; i += 1)
         {
             tmp += s_sum[lane_id + i * WARP_SIZE];
@@ -122,7 +122,11 @@ static void group_norm_f32(const float* x, float* dst, const int group_size, con
         better performance if there is no access to global memory.
         */
         item_ct1.barrier();
-        tmp = s_sum[lane_id];
+        tmp = 0.f;
+        for (size_t i = 0; i < nreduce; i += 1)
+        {
+            tmp += s_sum[lane_id + i * WARP_SIZE];
+        }
         tmp = warp_reduce_sum(tmp, item_ct1);
     }
 
diff --git a/ggml/src/ggml-sycl/presets.hpp b/ggml/src/ggml-sycl/presets.hpp
index c09c75dc7c73c..15ddcac1fa148 100644
--- a/ggml/src/ggml-sycl/presets.hpp
+++ b/ggml/src/ggml-sycl/presets.hpp
@@ -62,4 +62,5 @@ static_assert(K_QUANTS_PER_ITERATION == 1 || K_QUANTS_PER_ITERATION == 2, "K_QUA
 
 #define MUL_MAT_SRC1_COL_STRIDE 128
 
+#define QK_WARP_SIZE 32
 #endif // GGML_SYCL_PRESETS_HPP
diff --git a/ggml/src/ggml-sycl/softmax.cpp b/ggml/src/ggml-sycl/softmax.cpp
new file mode 100644
index 0000000000000..e624b6ba31b0d
--- /dev/null
+++ b/ggml/src/ggml-sycl/softmax.cpp
@@ -0,0 +1,250 @@
+#include "norm.hpp"
+
+template 
+static void soft_max_f32(const float * x, const float * mask, float * dst, const int ncols_par,
+                         const int nrows_y, const float scale, const float max_bias, const float m0,
+                         const float m1, uint32_t n_head_log2, const sycl::nd_item<3> &item_ct1, float *buf) {
+    const int ncols = ncols_template == 0 ? ncols_par : ncols_template;
+
+    const int tid = item_ct1.get_local_id(2);
+    const int rowx = item_ct1.get_group(2);
+    const int rowy = rowx % nrows_y; // broadcast the mask (y) in the row dimension
+
+    const int block_size = block_size_template == 0 ? item_ct1.get_local_range(2) : block_size_template;
+
+    const int warp_id = item_ct1.get_local_id(2) / WARP_SIZE;
+    const int lane_id = item_ct1.get_local_id(2) % WARP_SIZE;
+    const int nthreads = block_size;
+    const int nwarps = nthreads / WARP_SIZE;
+    int nreduce = nwarps / WARP_SIZE;
+    float slope = 1.0f;
+
+    // ALiBi
+    if (max_bias > 0.0f) {
+        const uint32_t h = rowx/nrows_y; // head index
+
+        const float base = h < n_head_log2 ? m0 : m1;
+        const int   exp  = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1;
+
+        slope = sycl::pow(base, float(exp));
+    }
+
+    float *vals = vals_smem ? buf + std::max(nwarps, WARP_SIZE) : dst + rowx * ncols;
+    float max_val = -INFINITY;
+
+    for (int col0 = 0; col0 < ncols; col0 += block_size) {
+        const int col = col0 + tid;
+
+        if (ncols_template == 0 && col >= ncols) {
+            break;
+        }
+
+        const int ix = rowx*ncols + col;
+        const int iy = rowy*ncols + col;
+
+        const float val = x[ix]*scale + (mask ? slope*mask[iy] : 0.0f);
+
+        vals[col] = val;
+        max_val = sycl::max(max_val, val);
+    }
+
+    // find the max value in the block
+    max_val = warp_reduce_max(max_val, item_ct1);
+    if (block_size > WARP_SIZE) {
+        if (warp_id == 0) {
+            buf[lane_id] = -INFINITY;
+            for (size_t i = 1; i < nreduce; i += 1)
+                buf[lane_id + i * WARP_SIZE] = -INFINITY;
+        }
+        item_ct1.barrier(sycl::access::fence_space::local_space);
+
+        if (lane_id == 0) {
+            buf[warp_id] = max_val;
+        }
+        item_ct1.barrier(sycl::access::fence_space::local_space);
+        max_val = buf[lane_id];
+        for (size_t i = 1; i < nreduce; i += 1)
+        {
+            max_val = std::max(max_val, buf[lane_id + i * WARP_SIZE]);
+        }
+        max_val = warp_reduce_max(max_val, item_ct1);
+    }
+
+    float tmp = 0.f;
+#pragma unroll
+    for (int col0 = 0; col0 < ncols; col0 += block_size) {
+        const int col = col0 + tid;
+                if (ncols_template == 0 && col >= ncols) {
+            break;
+        }
+
+        const float val = sycl::native::exp(vals[col] - max_val);
+        tmp += val;
+        vals[col] = val;
+    }
+
+    // find the sum of exps in the block
+    tmp = warp_reduce_sum(tmp, item_ct1);
+    if (block_size > WARP_SIZE) {
+        item_ct1.barrier(sycl::access::fence_space::local_space);
+        if (warp_id == 0) {
+            buf[lane_id] = 0.f;
+            for (size_t i = 1; i < nreduce; i += 1)
+                buf[lane_id + i * WARP_SIZE] = 0.f;
+        }
+        item_ct1.barrier(sycl::access::fence_space::local_space);
+
+        if (lane_id == 0) {
+            buf[warp_id] = tmp;
+        }
+        item_ct1.barrier(sycl::access::fence_space::local_space);
+
+        tmp = buf[lane_id];
+        for (size_t i = 1; i < nreduce; i += 1)
+        {
+            tmp += buf[lane_id + i * WARP_SIZE];
+        }
+        tmp = warp_reduce_sum(tmp, item_ct1);
+    }
+
+    const float inv_sum = 1.f / tmp;
+
+#pragma unroll
+    for (int col0 = 0; col0 < ncols; col0 += block_size) {
+        const int col = col0 + tid;
+
+        if (ncols_template == 0 && col >= ncols) {
+            return;
+        }
+
+        const int idst = rowx*ncols + col;
+        dst[idst] = vals[col] * inv_sum;
+    }
+}
+
+template 
+static void soft_max_f32_submitter(const float * x, const float * mask, float * dst, const int ncols_par,
+                                   const int nrows_y, const float scale, const float max_bias, const float m0,
+                                   const float m1, uint32_t n_head_log2, sycl::range<3> block_nums, sycl::range<3> block_dims,
+                                   const size_t n_local_scratch, queue_ptr stream) {
+    stream->submit([&](sycl::handler &cgh) {
+        sycl::local_accessor local_buf_acc(n_local_scratch, cgh);
+
+        cgh.parallel_for(
+            sycl::nd_range<3>(block_nums * block_dims, block_dims),
+            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+                soft_max_f32(x, mask, dst, ncols_par,
+                                                                             nrows_y, scale, max_bias, m0,
+                                                                             m1, n_head_log2, item_ct1,
+                                                                             local_buf_acc.get_pointer());
+            });
+    });
+}
+
+static void soft_max_f32_sycl(const float * x, const float * mask,
+                              float * dst, const int ncols_x, const int nrows_x,
+                              const int nrows_y, const float scale, const float max_bias,
+                              queue_ptr stream, int device) {
+    int nth = WARP_SIZE;
+    int max_block_size = ggml_sycl_info().max_work_group_sizes[device];
+    while (nth < ncols_x && nth < max_block_size) nth *= 2;
+    if (nth>max_block_size) nth = max_block_size;
+
+    const sycl::range<3> block_dims(1, 1, nth);
+    const sycl::range<3> block_nums(1, 1, nrows_x);
+    const size_t n_local_scratch = (GGML_PAD(ncols_x, WARP_SIZE) + WARP_SIZE);
+
+    const uint32_t n_head_kv   = nrows_x/nrows_y;
+    const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head_kv));
+
+    const float m0 = powf(2.0f, -(max_bias       ) / n_head_log2);
+    const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2);
+
+    const size_t local_mem_size = stream->get_device().get_info();
+    if (n_local_scratch*sizeof(float) < local_mem_size) {
+        if (ncols_x > max_block_size) {
+            soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
+                                               max_bias, m0, m1, n_head_log2, block_nums,
+                                               block_dims, n_local_scratch, stream);
+            return;
+        }
+        switch (ncols_x) {
+            case 32:
+                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
+                                                     max_bias, m0, m1, n_head_log2, block_nums,
+                                                     block_dims, n_local_scratch, stream);
+                break;
+            case 64:
+                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
+                                                     max_bias, m0, m1, n_head_log2, block_nums,
+                                                     block_dims, n_local_scratch, stream);
+                break;
+            case 128:
+                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
+                                                       max_bias, m0, m1, n_head_log2, block_nums,
+                                                       block_dims, n_local_scratch, stream);
+                break;
+            case 256:
+                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
+                                                       max_bias, m0, m1, n_head_log2, block_nums,
+                                                       block_dims, n_local_scratch, stream);
+                break;
+            case 512:
+                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
+                                                       max_bias, m0, m1, n_head_log2, block_nums,
+                                                       block_dims, n_local_scratch, stream);
+                break;
+            case 1024:
+                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
+                                                         max_bias, m0, m1, n_head_log2, block_nums,
+                                                         block_dims, n_local_scratch, stream);
+                break;
+            case 2048:
+                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
+                                                         max_bias, m0, m1, n_head_log2, block_nums,
+                                                         block_dims, n_local_scratch, stream);
+                break;
+            case 4096:
+                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
+                                                         max_bias, m0, m1, n_head_log2, block_nums,
+                                                         block_dims, n_local_scratch, stream);
+                break;
+            default:
+                soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
+                                                   max_bias, m0, m1, n_head_log2, block_nums,
+                                                   block_dims, n_local_scratch, stream);
+                break;
+        }
+    } else {
+        soft_max_f32_submitter(x, mask, dst, ncols_x, nrows_y, scale,
+                                            max_bias, m0, m1, n_head_log2, block_nums,
+                                            block_dims, WARP_SIZE, stream);
+    }
+}
+
+void ggml_sycl_op_soft_max(ggml_backend_sycl_context & ctx, const ggml_tensor *src0,
+                                  const ggml_tensor *src1, ggml_tensor *dst,
+                                  const float *src0_dd, const float *src1_dd,
+                                  float *dst_dd,
+                                  const queue_ptr &main_stream) {
+
+    GGML_ASSERT(src0->type == GGML_TYPE_F32);
+    GGML_ASSERT( dst->type == GGML_TYPE_F32);
+
+#pragma message("TODO: add ggml_sycl_op_soft_max() F16 src1 support")
+#pragma message("ref:  https://github.com/ggerganov/llama.cpp/pull/5021")
+    GGML_ASSERT(!src1 || src1->type == GGML_TYPE_F32); // src1 contains mask and it is optional
+
+    const int64_t ne00 = src0->ne[0];
+    const int64_t nrows_x = ggml_nrows(src0);
+    const int64_t nrows_y = src0->ne[1];
+
+    float scale = 1.0f;
+    float max_bias = 0.0f;
+
+    memcpy(&scale, dst->op_params + 0, sizeof(float));
+    memcpy(&max_bias, dst->op_params + 1, sizeof(float));
+
+    soft_max_f32_sycl(src0_dd, src1 ? src1_dd : nullptr, dst_dd, ne00,
+        nrows_x, nrows_y, scale, max_bias, main_stream, ctx.device);
+}
diff --git a/ggml/src/ggml-sycl/softmax.hpp b/ggml/src/ggml-sycl/softmax.hpp
new file mode 100644
index 0000000000000..bdb8f712e32f8
--- /dev/null
+++ b/ggml/src/ggml-sycl/softmax.hpp
@@ -0,0 +1,24 @@
+//
+// MIT license
+// Copyright (C) 2024 Intel Corporation
+// SPDX-License-Identifier: MIT
+//
+
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+
+#ifndef GGML_SYCL_SOFTMAX_HPP
+#define GGML_SYCL_SOFTMAX_HPP
+
+#include "common.hpp"
+
+void ggml_sycl_op_soft_max(ggml_backend_sycl_context &ctx, const ggml_tensor *src0,
+    const ggml_tensor *src1, ggml_tensor *dst,
+    const float *src0_dd, const float *src1_dd,
+    float *dst_dd,
+    const queue_ptr &main_stream);
+
+#endif // GGML_SYCL_SOFTMAX_HPP

From 6c05752c507f51b88348f16d9e2c8df49f66c028 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Fri, 5 Jul 2024 09:09:47 +0300
Subject: [PATCH 101/326] contributing : update guidelines (#8316)

---
 CONTRIBUTING.md | 30 ++++++++++++++++++++----------
 README.md       | 15 ++-------------
 2 files changed, 22 insertions(+), 23 deletions(-)

diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index 991d85e493be4..9ad5160495a8e 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -1,14 +1,24 @@
-# Contributing Guidelines
+# Pull requests
 
-## Checklist
+- Always squash-merge the PR before merging
+- Use the following format for your final commit: ` :  (#)`. For example: `utils : fix typo in utils.py (#1234)`
+- Test your changes:
+  - Using the commands in the [`tests`](tests) folder. For instance, running the `./tests/test-backend-ops` command tests different backend implementations of the GGML library
+  - Execute [the full CI locally on your machine](ci/README.md) before publishing
+- If the pull request contains only documentation changes (e.g., updating READMEs, adding new wiki pages), please add `[no ci]` to the commit title. This will skip unnecessary CI checks and help reduce build times
+- Please rate the complexity of your PR (i.e. `Review Complexity : Low`, `Review Complexity : Medium`, `Review Complexity : High`). This makes it easier for maintainers to triage the PRs.
+  - The PR template has a series of review complexity checkboxes `[ ]` that [you can mark as](https://docs.github.com/en/get-started/writing-on-github/working-with-advanced-formatting/about-task-lists) `[X]` for your conveience
 
-* Make sure your PR follows the [coding guidelines](https://github.com/ggerganov/llama.cpp/blob/master/README.md#coding-guidelines)
-* Test your changes using the commands in the [`tests`](tests) folder. For instance, running the `./tests/test-backend-ops` command tests different backend implementations of the GGML library
-* Execute [the full CI locally on your machine](ci/README.md) before publishing
+# Coding guidelines
 
-## PR formatting
+- Avoid adding third-party dependencies, extra files, extra headers, etc.
+- Always consider cross-compatibility with other operating systems and architectures
+- Avoid fancy looking modern STL constructs, use basic `for` loops, avoid templates, keep it simple
+- There are no strict rules for the code style, but try to follow the patterns in the code (indentation, spaces, etc.). Vertical alignment makes things more readable and easier to batch edit
+- Clean-up any trailing whitespaces, use 4 spaces for indentation, brackets on the same line, `void * ptr`, `int & a`
+- Naming usually optimizes for common prefix (see https://github.com/ggerganov/ggml/pull/302#discussion_r1243240963)
+- Tensors store data in row-major order. We refer to dimension 0 as columns, 1 as rows, 2 as matrices
+- Matrix multiplication is unconventional: [`C = ggml_mul_mat(ctx, A, B)`](https://github.com/ggerganov/llama.cpp/blob/880e352277fc017df4d5794f0c21c44e1eae2b84/ggml.h#L1058-L1064) means $C^T = A B^T \Leftrightarrow C = B A^T.$
+
+![matmul](media/matmul.png)
 
-* Please rate the complexity of your PR (i.e. `Review Complexity : Low`, `Review Complexity : Medium`, `Review Complexity : High`). This makes it easier for maintainers to triage the PRs.
-    - The PR template has a series of review complexity checkboxes `[ ]` that you can mark as `[X]` for your conveience. Refer to [About task lists](https://docs.github.com/en/get-started/writing-on-github/working-with-advanced-formatting/about-task-lists) for more information.
-* If the pull request only contains documentation changes (e.g., updating READMEs, adding new wiki pages), please add `[no ci]` to the commit title. This will skip unnecessary CI checks and help reduce build times.
-* When squashing multiple commits on merge, use the following format for your commit title: ` :  (#)`. For example: `utils : Fix typo in utils.py (#1234)`
diff --git a/README.md b/README.md
index 0cc1d10f4cb08..875fed4371dba 100644
--- a/README.md
+++ b/README.md
@@ -976,22 +976,11 @@ docker run --gpus all -v /path/to/models:/models local/llama.cpp:server-cuda -m
 - Collaborators can push to branches in the `llama.cpp` repo and merge PRs into the `master` branch
 - Collaborators will be invited based on contributions
 - Any help with managing issues and PRs is very appreciated!
+- See [good first issues](https://github.com/ggerganov/llama.cpp/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) for tasks suitable for first contributions
+- Read the [CONTRIBUTING.md](CONTRIBUTING.md) for more information
 - Make sure to read this: [Inference at the edge](https://github.com/ggerganov/llama.cpp/discussions/205)
 - A bit of backstory for those who are interested: [Changelog podcast](https://changelog.com/podcast/532)
 
-### Coding guidelines
-
-- Avoid adding third-party dependencies, extra files, extra headers, etc.
-- Always consider cross-compatibility with other operating systems and architectures
-- Avoid fancy looking modern STL constructs, use basic `for` loops, avoid templates, keep it simple
-- There are no strict rules for the code style, but try to follow the patterns in the code (indentation, spaces, etc.). Vertical alignment makes things more readable and easier to batch edit
-- Clean-up any trailing whitespaces, use 4 spaces for indentation, brackets on the same line, `void * ptr`, `int & a`
-- See [good first issues](https://github.com/ggerganov/llama.cpp/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) for tasks suitable for first contributions
-- Tensors store data in row-major order. We refer to dimension 0 as columns, 1 as rows, 2 as matrices
-- Matrix multiplication is unconventional: [`C = ggml_mul_mat(ctx, A, B)`](https://github.com/ggerganov/llama.cpp/blob/880e352277fc017df4d5794f0c21c44e1eae2b84/ggml.h#L1058-L1064) means $C^T = A B^T \Leftrightarrow C = B A^T.$
-
-![matmul](media/matmul.png)
-
 ### Docs
 
 - [main (cli)](./examples/main/README.md)

From aa5898dc53afcf77f16222cd719e10b29049f95a Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Fri, 5 Jul 2024 09:10:03 +0300
Subject: [PATCH 102/326] llama : prefer n_ over num_ prefix (#8308)

---
 src/llama.cpp | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/src/llama.cpp b/src/llama.cpp
index 721b8f4e5931b..b7ef829756383 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -4210,7 +4210,7 @@ struct llama_model_loader {
 #if defined(GGML_USE_CUDA)
         // 4 staging buffers for async uploads, each sized 1MB seems to be a good default for single NVMe drives.
         // NVMe raid configurations might require more / larger buffers.
-        constexpr size_t num_buffers = 4;
+        constexpr size_t n_buffers = 4;
         constexpr size_t buffer_size = 1 * 1024 * 1024; // 1MB
 
         std::vector host_buffers;
@@ -4236,7 +4236,7 @@ struct llama_model_loader {
 
             // If the cuda backend is active create pinned memory buffers and events for synchronisation.
             if (cuda_backend) {
-                for (size_t idx = 0; idx < num_buffers; ++idx) {
+                for (size_t idx = 0; idx < n_buffers; ++idx) {
                     host_buffers.emplace_back(ggml_backend_buft_alloc_buffer(llama_default_buffer_type_cpu(true), buffer_size));
                     host_ptrs.emplace_back(ggml_backend_buffer_get_base(host_buffers[idx]));
                     events.emplace_back(ggml_backend_event_new(cuda_backend));
@@ -4317,7 +4317,7 @@ struct llama_model_loader {
 
                             bytes_read += read_iteration;
                             ++buffer_idx;
-                            buffer_idx %= num_buffers;
+                            buffer_idx %= n_buffers;
                         }
                     }
                     else
@@ -4340,7 +4340,7 @@ struct llama_model_loader {
 #if defined(GGML_USE_CUDA)
         // free temporary resources used for async cuda uploads
         if (cuda_backend) {
-            for (size_t idx = 0; idx < num_buffers;++idx) {
+            for (size_t idx = 0; idx < n_buffers;++idx) {
                 ggml_backend_event_synchronize(events[idx]);
                 ggml_backend_event_free(events[idx]);
                 ggml_backend_buffer_free(host_buffers[idx]);
@@ -17488,8 +17488,8 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
     const llm_arch arch = qs.model.arch;
     const auto       tn = LLM_TN(arch);
 
-    auto use_more_bits = [](int i_layer, int num_layers) -> bool {
-        return i_layer < num_layers/8 || i_layer >= 7*num_layers/8 || (i_layer - num_layers/8)%3 == 2;
+    auto use_more_bits = [](int i_layer, int n_layers) -> bool {
+        return i_layer < n_layers/8 || i_layer >= 7*n_layers/8 || (i_layer - n_layers/8)%3 == 2;
     };
     const int n_expert = std::max(1, (int)qs.model.hparams.n_expert);
     auto layer_info = [n_expert] (int i_layer, int n_layer, const char * name) {

From 61ecafa3905a02a299b7ae889b5578cfeb8d79df Mon Sep 17 00:00:00 2001
From: Daniel Bevenius 
Date: Fri, 5 Jul 2024 08:14:24 +0200
Subject: [PATCH 103/326] passkey : add short intro to README.md [no-ci]
 (#8317)

* passkey : add short intro to README.md [no-ci]

This commit adds a short introduction to the README.md file in the
examples/passkey directory.

Signed-off-by: Daniel Bevenius 

* Update examples/passkey/README.md

---------

Signed-off-by: Daniel Bevenius 
Co-authored-by: Georgi Gerganov 
---
 examples/passkey/README.md | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/examples/passkey/README.md b/examples/passkey/README.md
index a48a6283a0b27..2b8e910f9658d 100644
--- a/examples/passkey/README.md
+++ b/examples/passkey/README.md
@@ -1,5 +1,8 @@
 # llama.cpp/example/passkey
 
+A passkey retrieval task is an evaluation method used to measure a language
+models ability to recall information from long contexts.
+
 See the following PRs for more info:
 
 - https://github.com/ggerganov/llama.cpp/pull/3856

From 5a7447c5692c9e3dde1161e8e69edb76d3d34714 Mon Sep 17 00:00:00 2001
From: Pieter Ouwerkerk 
Date: Fri, 5 Jul 2024 02:58:41 -0400
Subject: [PATCH 104/326] readme : fix minor typos [no ci] (#8314)

---
 examples/server/README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/server/README.md b/examples/server/README.md
index 4fab006bb9a43..aa4cbbe63907b 100644
--- a/examples/server/README.md
+++ b/examples/server/README.md
@@ -375,7 +375,7 @@ Notice that each `probs` is an array of length `n_probs`.
 - `default_generation_settings` - the default generation settings for the `/completion` endpoint, which has the same fields as the `generation_settings` response object from the `/completion` endpoint.
 - `total_slots` - the total number of slots for process requests (defined by `--parallel` option)
 
-- **POST** `/v1/chat/completions`: OpenAI-compatible Chat Completions API. Given a ChatML-formatted json description in `messages`, it returns the predicted completion. Both synchronous and streaming mode are supported, so scripted and interactive applications work fine. While no strong claims of compatibility with OpenAI API spec is being made, in our experience it suffices to support many apps. Only model with [supported chat template](https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template) can be used optimally with this endpoint. By default, ChatML template will be used.
+- **POST** `/v1/chat/completions`: OpenAI-compatible Chat Completions API. Given a ChatML-formatted json description in `messages`, it returns the predicted completion. Both synchronous and streaming mode are supported, so scripted and interactive applications work fine. While no strong claims of compatibility with OpenAI API spec is being made, in our experience it suffices to support many apps. Only models with a [supported chat template](https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template) can be used optimally with this endpoint. By default, the ChatML template will be used.
 
     *Options:*
 

From bcefa03bc01a41aace2e200ee8e77827d6d39b4f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= 
Date: Fri, 5 Jul 2024 09:05:34 +0200
Subject: [PATCH 105/326] CUDA: fix MMQ stream-k rounding if ne00 % 128 != 0
 (#8311)

---
 ggml/src/ggml-cuda/mmq.cuh | 14 ++++++++++----
 1 file changed, 10 insertions(+), 4 deletions(-)

diff --git a/ggml/src/ggml-cuda/mmq.cuh b/ggml/src/ggml-cuda/mmq.cuh
index deaed066f7c90..a97afc7ac80aa 100644
--- a/ggml/src/ggml-cuda/mmq.cuh
+++ b/ggml/src/ggml-cuda/mmq.cuh
@@ -2305,8 +2305,11 @@ static __global__ void mul_mat_q(
     const int nty = (ne01 + mmq_y - 1) / mmq_y; // Number of tiles y
 
     // kbc == k block continuous, current index in continuous ijk space.
-    int64_t       kbc      = GGML_PAD((int64_t) blockIdx.x     *blocks_per_ne00*ntx*nty / gridDim.x, blocks_per_warp);
-    const int64_t kbc_stop = GGML_PAD((int64_t)(blockIdx.x + 1)*blocks_per_ne00*ntx*nty / gridDim.x, blocks_per_warp);
+    int64_t kbc      = (int64_t) blockIdx.x     *blocks_per_ne00*ntx*nty / gridDim.x;
+    int64_t kbc_stop = (int64_t)(blockIdx.x + 1)*blocks_per_ne00*ntx*nty / gridDim.x;
+
+    kbc      -= (kbc      % blocks_per_ne00) % blocks_per_warp;
+    kbc_stop -= (kbc_stop % blocks_per_ne00) % blocks_per_warp;
 
     // kb0 == k index when doing the matrix multiplication for an output tile.
     int kb0_start = kbc % blocks_per_ne00;
@@ -2362,8 +2365,11 @@ static __global__ void mul_mat_q_stream_k_fixup(
     const int bidx_stop  = (blockIdx.y*nty + blockIdx.x + 1) * block_num_mmq / (gridDim.y*gridDim.x) + 1;
 
     for (int bidx = bidx_start; bidx < bidx_stop; ++bidx) {
-        const int64_t kbc      = GGML_PAD((int64_t) bidx     *blocks_per_ne00*ntx*nty / block_num_mmq, blocks_per_warp);
-        const int64_t kbc_stop = GGML_PAD((int64_t)(bidx + 1)*blocks_per_ne00*ntx*nty / block_num_mmq, blocks_per_warp);
+        int64_t kbc      = (int64_t) bidx     *blocks_per_ne00*ntx*nty / block_num_mmq;
+        int64_t kbc_stop = (int64_t)(bidx + 1)*blocks_per_ne00*ntx*nty / block_num_mmq;
+
+        kbc      -= (kbc      % blocks_per_ne00) % blocks_per_warp;
+        kbc_stop -= (kbc_stop % blocks_per_ne00) % blocks_per_warp;
 
         // Skip fixup tile if the MMQ CUDA block never wrote anything to it:
         if (kbc == kbc_stop || kbc_stop % blocks_per_ne00 == 0) {

From d12f781074b92589a72a36ffabb583933f7b9dc0 Mon Sep 17 00:00:00 2001
From: Douglas Hanley 
Date: Fri, 5 Jul 2024 02:05:56 -0500
Subject: [PATCH 106/326] llama : streamline embeddings from "non-embedding"
 models (#8087)

---
 common/common.cpp | 13 ++++++++++++-
 common/common.h   |  1 +
 include/llama.h   |  7 +++++++
 src/llama.cpp     | 25 ++++++++++++++++---------
 4 files changed, 36 insertions(+), 10 deletions(-)

diff --git a/common/common.cpp b/common/common.cpp
index 1f7359980a94d..42ae85f5f11c2 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -472,6 +472,14 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
         else { invalid_param = true; }
         return true;
     }
+    if (arg == "--attention") {
+        CHECK_ARG
+        std::string value(argv[i]);
+        /**/ if (value == "causal") { params.attention_type = LLAMA_ATTENTION_TYPE_CAUSAL; }
+        else if (value == "non-causal") { params.attention_type = LLAMA_ATTENTION_TYPE_NON_CAUSAL; }
+        else { invalid_param = true; }
+        return true;
+    }
     if (arg == "--defrag-thold" || arg == "-dt") {
         CHECK_ARG
         params.defrag_thold = std::stof(argv[i]);
@@ -1468,8 +1476,10 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
                                                                         "For schemas w/ external $refs, use --grammar + example/json_schema_to_grammar.py instead" });
 
     options.push_back({ "embedding" });
-    options.push_back({ "embedding",   "       --pooling {none,mean,cls}",
+    options.push_back({ "embedding",   "       --pooling {none,mean,cls,last}",
                                                                         "pooling type for embeddings, use model default if unspecified" });
+    options.push_back({ "embedding",   "       --attention {causal,non-causal}",
+                                                                        "attention type for embeddings, use model default if unspecified" });
 
     options.push_back({ "context hacking" });
     options.push_back({ "*",           "       --rope-scaling {none,linear,yarn}",
@@ -2175,6 +2185,7 @@ struct llama_context_params llama_context_params_from_gpt_params(const gpt_param
     cparams.yarn_beta_slow    = params.yarn_beta_slow;
     cparams.yarn_orig_ctx     = params.yarn_orig_ctx;
     cparams.pooling_type      = params.pooling_type;
+    cparams.attention_type    = params.attention_type;
     cparams.defrag_thold      = params.defrag_thold;
     cparams.cb_eval           = params.cb_eval;
     cparams.cb_eval_user_data = params.cb_eval_user_data;
diff --git a/common/common.h b/common/common.h
index 65c0ef81adf7c..ac86483ffa1c9 100644
--- a/common/common.h
+++ b/common/common.h
@@ -99,6 +99,7 @@ struct gpt_params {
     enum llama_split_mode        split_mode        = LLAMA_SPLIT_MODE_LAYER; // how to split the model across GPUs
     enum llama_rope_scaling_type rope_scaling_type = LLAMA_ROPE_SCALING_TYPE_UNSPECIFIED;
     enum llama_pooling_type      pooling_type      = LLAMA_POOLING_TYPE_UNSPECIFIED; // pooling type for embeddings
+    enum llama_attention_type    attention_type    = LLAMA_ATTENTION_TYPE_UNSPECIFIED; // attention type for embeddings
 
     // // sampling parameters
     struct llama_sampling_params sparams;
diff --git a/include/llama.h b/include/llama.h
index aca79d2b864b8..7a9a25609c9c1 100644
--- a/include/llama.h
+++ b/include/llama.h
@@ -180,6 +180,12 @@ extern "C" {
         LLAMA_POOLING_TYPE_LAST = 3,
     };
 
+    enum llama_attention_type {
+        LLAMA_ATTENTION_TYPE_UNSPECIFIED = -1,
+        LLAMA_ATTENTION_TYPE_CAUSAL      = 0,
+        LLAMA_ATTENTION_TYPE_NON_CAUSAL  = 1,
+    };
+
     enum llama_split_mode {
         LLAMA_SPLIT_MODE_NONE    = 0, // single GPU
         LLAMA_SPLIT_MODE_LAYER   = 1, // split layers and KV across GPUs
@@ -297,6 +303,7 @@ extern "C" {
 
         enum llama_rope_scaling_type rope_scaling_type; // RoPE scaling type, from `enum llama_rope_scaling_type`
         enum llama_pooling_type      pooling_type;      // whether to pool (sum) embedding results by sequence id
+        enum llama_attention_type    attention_type;    // attention type to use for embeddings
 
         // ref: https://github.com/ggerganov/llama.cpp/pull/2054
         float    rope_freq_base;   // RoPE base frequency, 0 = from model
diff --git a/src/llama.cpp b/src/llama.cpp
index b7ef829756383..132055888b9f1 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -13840,7 +13840,7 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
         }
     }
 
-    if (cparams.pooling_type == LLAMA_POOLING_TYPE_MEAN) {
+    if (cparams.embeddings && cparams.pooling_type == LLAMA_POOLING_TYPE_MEAN) {
         const int64_t n_tokens = batch.n_tokens;
 
         GGML_ASSERT(lctx.inp_mean);
@@ -13872,7 +13872,7 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
         }
     }
 
-    if (cparams.pooling_type == LLAMA_POOLING_TYPE_CLS) {
+    if (cparams.embeddings && cparams.pooling_type == LLAMA_POOLING_TYPE_CLS) {
         const int64_t n_tokens = batch.n_tokens;
 
         GGML_ASSERT(lctx.inp_cls);
@@ -13893,7 +13893,7 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
         }
     }
 
-    if (cparams.pooling_type == LLAMA_POOLING_TYPE_LAST) {
+    if (cparams.embeddings && cparams.pooling_type == LLAMA_POOLING_TYPE_LAST) {
         const int64_t n_tokens = batch.n_tokens;
 
         GGML_ASSERT(lctx.inp_cls);
@@ -14181,14 +14181,15 @@ static int llama_decode_internal(
     std::vector            seq_id_arr;
     std::vector> seq_id;
 
+    // this indicates we are doing pooled embedding, so we ignore batch.logits and output all tokens
+    const bool embd_pooled = cparams.embeddings && cparams.pooling_type != LLAMA_POOLING_TYPE_NONE;
+
     // count outputs
-    if (cparams.embeddings && cparams.pooling_type != LLAMA_POOLING_TYPE_NONE) {
-        n_outputs = n_tokens_all;
-    } else if (batch_all.logits) {
+    if (batch_all.logits && !embd_pooled) {
         for (uint32_t i = 0; i < n_tokens_all; ++i) {
             n_outputs += batch_all.logits[i] != 0;
         }
-    } else if (lctx.logits_all) {
+    } else if (lctx.logits_all || embd_pooled) {
         n_outputs = n_tokens_all;
     } else {
         // keep last output only
@@ -14234,7 +14235,7 @@ static int llama_decode_internal(
         {
             int32_t n_outputs_new = 0;
 
-            if (u_batch.logits) {
+            if (u_batch.logits && !embd_pooled) {
                 for (uint32_t i = 0; i < n_tokens; i++) {
                     n_outputs_new += u_batch.logits[i] != 0;
                 }
@@ -18533,6 +18534,7 @@ struct llama_context_params llama_context_default_params() {
         /*.n_threads_batch             =*/ GGML_DEFAULT_N_THREADS,
         /*.rope_scaling_type           =*/ LLAMA_ROPE_SCALING_TYPE_UNSPECIFIED,
         /*.pooling_type                =*/ LLAMA_POOLING_TYPE_UNSPECIFIED,
+        /*.attention_type              =*/ LLAMA_ATTENTION_TYPE_UNSPECIFIED,
         /*.rope_freq_base              =*/ 0.0f,
         /*.rope_freq_scale             =*/ 0.0f,
         /*.yarn_ext_factor             =*/ -1.0f,
@@ -18785,7 +18787,6 @@ struct llama_context * llama_new_context_with_model(
     }
 
     cparams.yarn_attn_factor *= hparams.rope_attn_factor;
-    cparams.causal_attn = hparams.causal_attn;
 
     if (cparams.pooling_type == LLAMA_POOLING_TYPE_UNSPECIFIED) {
         if (hparams.pooling_type == LLAMA_POOLING_TYPE_UNSPECIFIED) {
@@ -18795,6 +18796,12 @@ struct llama_context * llama_new_context_with_model(
         }
     }
 
+    if (params.attention_type == LLAMA_ATTENTION_TYPE_UNSPECIFIED) {
+        cparams.causal_attn = hparams.causal_attn;
+    } else {
+        cparams.causal_attn = params.attention_type == LLAMA_ATTENTION_TYPE_CAUSAL;
+    }
+
     if (params.seed == LLAMA_DEFAULT_SEED) {
         params.seed = time(NULL);
     }

From 0a423800ffe4e5da3d83527ef3473da88cd78146 Mon Sep 17 00:00:00 2001
From: Daniele <57776841+daniandtheweb@users.noreply.github.com>
Date: Fri, 5 Jul 2024 07:06:09 +0000
Subject: [PATCH 107/326] CUDA: revert part of the RDNA1 optimizations (#8309)

The change on the launch_bounds was causing a small performance drop in perplexity of 25 t/s
---
 ggml/src/ggml-cuda/mmq.cuh | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/ggml/src/ggml-cuda/mmq.cuh b/ggml/src/ggml-cuda/mmq.cuh
index a97afc7ac80aa..fca93618dc754 100644
--- a/ggml/src/ggml-cuda/mmq.cuh
+++ b/ggml/src/ggml-cuda/mmq.cuh
@@ -2263,9 +2263,9 @@ static __device__ void mul_mat_q_process_tile(
 
 template 
 #if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
-#if defined(RDNA3) || defined(RDNA2) || defined(RDNA1)
+#if defined(RDNA3) || defined(RDNA2)
     __launch_bounds__(WARP_SIZE*nwarps, 2)
-#endif // defined(RDNA3) || defined(RDNA2) || defined(RDNA1)
+#endif // defined(RDNA3) || defined(RDNA2)
 #else
 #if __CUDA_ARCH__ >= CC_VOLTA
     __launch_bounds__(WARP_SIZE*nwarps, 1)

From 8e558309dc149dc1f9fd159185b0b9071527ffb5 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= 
Date: Fri, 5 Jul 2024 09:06:31 +0200
Subject: [PATCH 108/326] CUDA: MMQ support for iq4_nl, iq4_xs (#8278)

---
 ggml/src/ggml-cuda/fattn-common.cuh           |  18 +-
 ggml/src/ggml-cuda/mmq.cu                     |   8 +
 ggml/src/ggml-cuda/mmq.cuh                    | 224 ++++++++++++++----
 .../template-instances/generate_cu_files.py   |   3 +-
 .../template-instances/mmq-instance-iq4_nl.cu |   5 +
 .../template-instances/mmq-instance-iq4_xs.cu |   5 +
 ggml/src/ggml-cuda/vecdotq.cuh                |  43 ++--
 7 files changed, 226 insertions(+), 80 deletions(-)
 create mode 100644 ggml/src/ggml-cuda/template-instances/mmq-instance-iq4_nl.cu
 create mode 100644 ggml/src/ggml-cuda/template-instances/mmq-instance-iq4_xs.cu

diff --git a/ggml/src/ggml-cuda/fattn-common.cuh b/ggml/src/ggml-cuda/fattn-common.cuh
index 650780fd2e462..f24312dd0bc90 100644
--- a/ggml/src/ggml-cuda/fattn-common.cuh
+++ b/ggml/src/ggml-cuda/fattn-common.cuh
@@ -68,7 +68,7 @@ static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q4_0(
         const int iqs4  = k_KQ %  QI4_0;
         const int shift = k_KQ & (QI8_1/2);
 
-        const int v = (get_int_from_uint8(K_q4_0[ib].qs, iqs4) >> shift) & 0x0F0F0F0F;
+        const int v = (get_int_b2(K_q4_0[ib].qs, iqs4) >> shift) & 0x0F0F0F0F;
         const int u = Q_q8[k_KQ_0/WARP_SIZE];
 
         const int sumi = ggml_cuda_dp4a(v, u, 0);
@@ -108,7 +108,7 @@ static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q4_1(
         const int iqs4  = k_KQ %  QI4_1;
         const int shift = k_KQ & (QI8_1/2);
 
-        const int v = (get_int_from_uint8_aligned(K_q4_1[ib].qs, iqs4) >> shift) & 0x0F0F0F0F;
+        const int v = (get_int_b4(K_q4_1[ib].qs, iqs4) >> shift) & 0x0F0F0F0F;
         const int u = Q_q8[k_KQ_0/WARP_SIZE];
 
         const int sumi = ggml_cuda_dp4a(v, u, 0);
@@ -153,8 +153,8 @@ static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q5_0(
         const int iqs8  = k_KQ %  QI8_1;
         const int shift = k_KQ & (QI8_1/2);
 
-        int v = (get_int_from_uint8(K_q5_0[ib].qs, iqs4) >> shift) & 0x0F0F0F0F;
-        const int vh = get_int_from_uint8(K_q5_0[ib].qh, 0) >> (iqs8 * QI5_0);
+        int v = (get_int_b2(K_q5_0[ib].qs, iqs4) >> shift) & 0x0F0F0F0F;
+        const int vh = get_int_b2(K_q5_0[ib].qh, 0) >> (iqs8 * QI5_0);
         v |= (vh <<  4) & 0x00000010; // 0 ->  4
         v |= (vh << 11) & 0x00001000; // 1 -> 12
         v |= (vh << 18) & 0x00100000; // 2 -> 20
@@ -200,8 +200,8 @@ static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q5_1(
         const int iqs8  = k_KQ %  QI8_1;
         const int shift = k_KQ & (QI8_1/2);
 
-        int v = (get_int_from_uint8(K_q5_1[ib].qs, iqs4) >> shift) & 0x0F0F0F0F;
-        const int vh = get_int_from_uint8(K_q5_1[ib].qh, 0) >> (iqs8 * QI5_1);
+        int v = (get_int_b2(K_q5_1[ib].qs, iqs4) >> shift) & 0x0F0F0F0F;
+        const int vh = get_int_b2(K_q5_1[ib].qh, 0) >> (iqs8 * QI5_1);
         v |= (vh <<  4) & 0x00000010; // 0 ->  4
         v |= (vh << 11) & 0x00001000; // 1 -> 12
         v |= (vh << 18) & 0x00100000; // 2 -> 20
@@ -249,7 +249,7 @@ static __device__ __forceinline__ T vec_dot_fattn_vec_KQ_q8_0(
         const int ib  = k_KQ / QI8_0;
         const int iqs = k_KQ % QI8_0;
 
-        const int v = get_int_from_int8(K_q8_0[ib].qs, iqs);
+        const int v = get_int_b2(K_q8_0[ib].qs, iqs);
 
         T Q_d;
         if (std::is_same::value) {
@@ -408,7 +408,7 @@ static __device__ __forceinline__ T dequantize_1_q5_0(const void * __restrict__
 
     const T   d   = x[ib].d;
     const int ql0 = x[ib].qs[iqs];
-    const int qh0 = get_int_from_uint8(x[ib].qh, 0);
+    const int qh0 = get_int_b2(x[ib].qh, 0);
     const int ql  = ((ql0 >> (4*shift)) & 0x0F);
     const int qh  = ((qh0 >> idq) << 4) & 0x10;
     const int q   = (ql | qh) - 16;
@@ -433,7 +433,7 @@ static __device__ __forceinline__ T dequantize_1_q5_1(const void * __restrict__
 
     const half2 dm  = x[ib].dm;
     const int   ql0 = x[ib].qs[iqs];
-    const int   qh0 = get_int_from_uint8_aligned(x[ib].qh, 0);
+    const int   qh0 = get_int_b4(x[ib].qh, 0);
     const int   ql  = ((ql0 >> (4*shift)) & 0x0F);
     const int   qh  = ((qh0 >> idq) << 4) & 0x10;
     const int   q   = (ql | qh);
diff --git a/ggml/src/ggml-cuda/mmq.cu b/ggml/src/ggml-cuda/mmq.cu
index 0308beaccbaa3..3af2eec2f4163 100644
--- a/ggml/src/ggml-cuda/mmq.cu
+++ b/ggml/src/ggml-cuda/mmq.cu
@@ -59,6 +59,12 @@ void ggml_cuda_op_mul_mat_q(
         case GGML_TYPE_Q6_K:
             mul_mat_q_case(ctx, args, stream);
             break;
+        case GGML_TYPE_IQ4_XS:
+            mul_mat_q_case(ctx, args, stream);
+            break;
+        case GGML_TYPE_IQ4_NL:
+            mul_mat_q_case(ctx, args, stream);
+            break;
         default:
             GGML_ASSERT(false);
             break;
@@ -87,6 +93,8 @@ bool ggml_cuda_should_use_mmq(enum ggml_type type, int cc, int64_t ne11) {
         case GGML_TYPE_Q4_K:
         case GGML_TYPE_Q5_K:
         case GGML_TYPE_Q6_K:
+        case GGML_TYPE_IQ4_XS:
+        case GGML_TYPE_IQ4_NL:
             mmq_supported = true;
             break;
         default:
diff --git a/ggml/src/ggml-cuda/mmq.cuh b/ggml/src/ggml-cuda/mmq.cuh
index fca93618dc754..118e34d2847fc 100644
--- a/ggml/src/ggml-cuda/mmq.cuh
+++ b/ggml/src/ggml-cuda/mmq.cuh
@@ -92,15 +92,17 @@ static constexpr __device__ int get_mmq_y_device() {
 
 static constexpr __host__ __device__ tile_x_sizes mmq_get_dp4a_tile_x_sizes(ggml_type type, int mmq_y) {
     return type == GGML_TYPE_Q4_0 ? MMQ_DP4A_TXS_Q4_0 :
-        type == GGML_TYPE_Q4_1 ? MMQ_DP4A_TXS_Q4_1 :
-        type == GGML_TYPE_Q5_0 ? MMQ_DP4A_TXS_Q5_0 :
-        type == GGML_TYPE_Q5_1 ? MMQ_DP4A_TXS_Q5_1 :
-        type == GGML_TYPE_Q8_0 ? MMQ_DP4A_TXS_Q8_0 :
-        type == GGML_TYPE_Q2_K ? MMQ_DP4A_TXS_Q2_K :
-        type == GGML_TYPE_Q3_K ? MMQ_DP4A_TXS_Q3_K :
-        type == GGML_TYPE_Q4_K ? MMQ_DP4A_TXS_Q4_K :
-        type == GGML_TYPE_Q5_K ? MMQ_DP4A_TXS_Q5_K :
-        type == GGML_TYPE_Q6_K ? MMQ_DP4A_TXS_Q6_K :
+        type == GGML_TYPE_Q4_1    ? MMQ_DP4A_TXS_Q4_1 :
+        type == GGML_TYPE_Q5_0    ? MMQ_DP4A_TXS_Q5_0 :
+        type == GGML_TYPE_Q5_1    ? MMQ_DP4A_TXS_Q5_1 :
+        type == GGML_TYPE_Q8_0    ? MMQ_DP4A_TXS_Q8_0 :
+        type == GGML_TYPE_Q2_K    ? MMQ_DP4A_TXS_Q2_K :
+        type == GGML_TYPE_Q3_K    ? MMQ_DP4A_TXS_Q3_K :
+        type == GGML_TYPE_Q4_K    ? MMQ_DP4A_TXS_Q4_K :
+        type == GGML_TYPE_Q5_K    ? MMQ_DP4A_TXS_Q5_K :
+        type == GGML_TYPE_Q6_K    ? MMQ_DP4A_TXS_Q6_K :
+        type == GGML_TYPE_IQ4_XS  ? MMQ_DP4A_TXS_Q5_0 :
+        type == GGML_TYPE_IQ4_NL  ? MMQ_DP4A_TXS_Q5_0 :
         tile_x_sizes{0, 0, 0};
 }
 
@@ -128,15 +130,17 @@ static_assert(MMQ_MMA_TILE_X_K_Q6_K % 8 == 4, "Wrong padding.");
 
 static constexpr __host__ __device__ int mmq_get_mma_tile_x_k(ggml_type type) {
     return type == GGML_TYPE_Q4_0 ? MMQ_MMA_TILE_X_K_Q4_0 :
-        type == GGML_TYPE_Q4_1 ? MMQ_MMA_TILE_X_K_Q4_1 :
-        type == GGML_TYPE_Q5_0 ? MMQ_MMA_TILE_X_K_Q5_0 :
-        type == GGML_TYPE_Q5_1 ? MMQ_MMA_TILE_X_K_Q5_1 :
-        type == GGML_TYPE_Q8_0 ? MMQ_MMA_TILE_X_K_Q8_0 :
-        type == GGML_TYPE_Q2_K ? MMQ_MMA_TILE_X_K_Q2_K :
-        type == GGML_TYPE_Q3_K ? MMQ_MMA_TILE_X_K_Q3_K :
-        type == GGML_TYPE_Q4_K ? MMQ_MMA_TILE_X_K_Q4_K :
-        type == GGML_TYPE_Q5_K ? MMQ_MMA_TILE_X_K_Q5_K :
-        type == GGML_TYPE_Q6_K ? MMQ_MMA_TILE_X_K_Q6_K :
+        type == GGML_TYPE_Q4_1    ? MMQ_MMA_TILE_X_K_Q4_1 :
+        type == GGML_TYPE_Q5_0    ? MMQ_MMA_TILE_X_K_Q5_0 :
+        type == GGML_TYPE_Q5_1    ? MMQ_MMA_TILE_X_K_Q5_1 :
+        type == GGML_TYPE_Q8_0    ? MMQ_MMA_TILE_X_K_Q8_0 :
+        type == GGML_TYPE_Q2_K    ? MMQ_MMA_TILE_X_K_Q2_K :
+        type == GGML_TYPE_Q3_K    ? MMQ_MMA_TILE_X_K_Q3_K :
+        type == GGML_TYPE_Q4_K    ? MMQ_MMA_TILE_X_K_Q4_K :
+        type == GGML_TYPE_Q5_K    ? MMQ_MMA_TILE_X_K_Q5_K :
+        type == GGML_TYPE_Q6_K    ? MMQ_MMA_TILE_X_K_Q6_K :
+        type == GGML_TYPE_IQ4_XS  ? MMQ_MMA_TILE_X_K_Q5_0 :
+        type == GGML_TYPE_IQ4_NL  ? MMQ_MMA_TILE_X_K_Q5_0 :
         0;
 }
 
@@ -185,9 +189,9 @@ template  static __device__ __forceinlin
         const block_q4_0 * bxi = (const block_q4_0 *) x + kbx0 + i*stride + kbx;
 
 #ifdef INT8_MMA_AVAILABLE
-        x_qs[i*MMQ_MMA_TILE_X_K_Q4_0 + threadIdx.x] = get_int_from_uint8(bxi->qs, kqsx);
+        x_qs[i*MMQ_MMA_TILE_X_K_Q4_0 + threadIdx.x] = get_int_b2(bxi->qs, kqsx);
 #else
-        x_qs[i*(WARP_SIZE + 1)       + threadIdx.x] = get_int_from_uint8(bxi->qs, kqsx);
+        x_qs[i*(WARP_SIZE + 1)       + threadIdx.x] = get_int_b2(bxi->qs, kqsx);
 #endif // INT8_MMA_AVAILABLE
     }
 
@@ -348,9 +352,9 @@ template  static __device__ __forceinlin
         const block_q4_1 * bxi = (const block_q4_1 *) x + kbx0 + i*stride + kbx;
 
 #ifdef INT8_MMA_AVAILABLE
-        x_qs[i*MMQ_MMA_TILE_X_K_Q4_1 + threadIdx.x] = get_int_from_uint8_aligned(bxi->qs, kqsx);
+        x_qs[i*MMQ_MMA_TILE_X_K_Q4_1 + threadIdx.x] = get_int_b4(bxi->qs, kqsx);
 #else
-        x_qs[i*(WARP_SIZE + 1)       + threadIdx.x] = get_int_from_uint8_aligned(bxi->qs, kqsx);
+        x_qs[i*(WARP_SIZE + 1)       + threadIdx.x] = get_int_b4(bxi->qs, kqsx);
 #endif // INT8_MMA_AVAILABLE
     }
 
@@ -509,8 +513,8 @@ template  static __device__ __forceinlin
 
         const block_q5_0 * bxi = (const block_q5_0 *) x + kbx0 + i*stride + kbx;
 
-        const int ql = get_int_from_uint8(bxi->qs, kqsx);
-        const int qh = get_int_from_uint8(bxi->qh, 0) >> (4 * (threadIdx.x % QI5_0));
+        const int ql = get_int_b2(bxi->qs, kqsx);
+        const int qh = get_int_b2(bxi->qh, 0) >> (4 * (threadIdx.x % QI5_0));
 
         int qs0 = (ql >>  0)   & 0x0F0F0F0F;
         qs0    |= (qh <<  4)   & 0x00000010;  // 0 ->  4
@@ -674,8 +678,8 @@ template  static __device__ __forceinlin
 
         const block_q5_1 * bxi = (const block_q5_1 *) x + kbx0 + i*stride + kbx;
 
-        const int ql = get_int_from_uint8_aligned(bxi->qs, kqsx);
-        const int qh = get_int_from_uint8_aligned(bxi->qh, 0) >> (4 * (threadIdx.x % QI5_1));
+        const int ql = get_int_b4(bxi->qs, kqsx);
+        const int qh = get_int_b4(bxi->qh, 0) >> (4 * (threadIdx.x % QI5_1));
 
         int qs0 = (ql >>  0) & 0x0F0F0F0F;
         qs0    |= (qh <<  4) & 0x00000010; // 0 ->  4
@@ -839,9 +843,9 @@ template  static __device__ __forceinlin
         const block_q8_0 * bxi = (const block_q8_0 *) x + kbx0 + i*stride + kbx;
 
 #ifdef INT8_MMA_AVAILABLE
-        x_qs[i*MMQ_MMA_TILE_X_K_Q8_0 + threadIdx.x] = get_int_from_int8(bxi->qs, kqsx);
+        x_qs[i*MMQ_MMA_TILE_X_K_Q8_0 + threadIdx.x] = get_int_b2(bxi->qs, kqsx);
 #else
-        x_qs[i*(WARP_SIZE + 1)       + threadIdx.x] = get_int_from_int8(bxi->qs, kqsx);
+        x_qs[i*(WARP_SIZE + 1)       + threadIdx.x] = get_int_b2(bxi->qs, kqsx);
 #endif // INT8_MMA_AVAILABLE
     }
 
@@ -984,7 +988,7 @@ template  static __device__ __forceinlin
 
         const block_q2_K * bxi = (const block_q2_K *) x + kbx0 + i*stride + kbx;
 
-        const int x_ql_0 = get_int_from_uint8(bxi->qs, kqsx);
+        const int x_ql_0 = get_int_b2(bxi->qs, kqsx);
 
 #pragma unroll
         for (int l = 0; l < QR2_K; ++l) {
@@ -1166,8 +1170,8 @@ template  static __device__ __forceinlin
 
         const block_q3_K * bxi = (const block_q3_K *) x + kbx0 + i*stride + kbx;
 
-        const int x_ql_0 = get_int_from_uint8(bxi->qs,    kqsx);
-        const int x_qh_0 = get_int_from_uint8(bxi->hmask, kqsx % (QI3_K/2)) >> (4 * (kqsx / (QI3_K/2)));
+        const int x_ql_0 = get_int_b2(bxi->qs,    kqsx);
+        const int x_qh_0 = get_int_b2(bxi->hmask, kqsx % (QI3_K/2)) >> (4 * (kqsx / (QI3_K/2)));
 
 #pragma unroll
         for (int l = 0; l < QR3_K; ++l) {
@@ -1225,11 +1229,11 @@ template  static __device__ __forceinlin
 
         const int ksc_low = ksc % (QI3_K/8);
         const int shift_low = 4 * (ksc / (QI3_K/8));
-        const int sc_low = (get_int_from_uint8(bxi->scales, ksc_low) >> shift_low) & 0x0F0F0F0F;
+        const int sc_low = (get_int_b2(bxi->scales, ksc_low) >> shift_low) & 0x0F0F0F0F;
 
         const int ksc_high = QI3_K/8;
         const int shift_high = 2 * ksc;
-        const int sc_high = ((get_int_from_uint8(bxi->scales, ksc_high) >> shift_high) << 4) & 0x30303030;
+        const int sc_high = ((get_int_b2(bxi->scales, ksc_high) >> shift_high) << 4) & 0x30303030;
 
         const int sc = __vsubss4(sc_low | sc_high, 0x20202020);
 
@@ -1393,9 +1397,9 @@ template  static __device__ __forceinlin
         const block_q4_K * bxi = (const block_q4_K *) x + kbx0 + i*stride + kbx;
 
 #ifdef INT8_MMA_AVAILABLE
-        x_qs[i*MMQ_MMA_TILE_X_K_Q4_K + threadIdx.x] = get_int_from_uint8_aligned(bxi->qs, kqsx);
+        x_qs[i*MMQ_MMA_TILE_X_K_Q4_K + threadIdx.x] = get_int_b4(bxi->qs, kqsx);
 #else
-        x_qs[i*(WARP_SIZE + 1)       + threadIdx.x] = get_int_from_uint8_aligned(bxi->qs, kqsx);
+        x_qs[i*(WARP_SIZE + 1)       + threadIdx.x] = get_int_b4(bxi->qs, kqsx);
 #endif // INT8_MMA_AVAILABLE
     }
 
@@ -1610,11 +1614,11 @@ template  static __device__ __forceinlin
         const block_q5_K * bxi = (const block_q5_K *) x + kbx0 + i*stride + kbx;
         const int ky = QR5_K*kqsx;
 
-        const int ql = get_int_from_uint8_aligned(bxi->qs, kqsx);
+        const int ql = get_int_b4(bxi->qs, kqsx);
         const int ql0 = (ql >> 0) & 0x0F0F0F0F;
         const int ql1 = (ql >> 4) & 0x0F0F0F0F;
 
-        const int qh = get_int_from_uint8_aligned(bxi->qh, kqsx % (QI5_K/4));
+        const int qh = get_int_b4(bxi->qh, kqsx % (QI5_K/4));
         const int qh0 = ((qh >> (2 * (kqsx / (QI5_K/4)) + 0)) << 4) & 0x10101010;
         const int qh1 = ((qh >> (2 * (kqsx / (QI5_K/4)) + 1)) << 4) & 0x10101010;
 
@@ -1832,11 +1836,11 @@ template  static __device__ __forceinlin
         const block_q6_K * bxi = (const block_q6_K *) x + kbx0 + i*stride + kbx;
         const int ky = QR6_K*kqsx;
 
-        const int ql = get_int_from_uint8(bxi->ql, kqsx);
+        const int ql = get_int_b2(bxi->ql, kqsx);
         const int ql0 = (ql >> 0) & 0x0F0F0F0F;
         const int ql1 = (ql >> 4) & 0x0F0F0F0F;
 
-        const int qh = get_int_from_uint8(bxi->qh, (QI6_K/4) * (kqsx / (QI6_K/2)) + kqsx % (QI6_K/4));
+        const int qh = get_int_b2(bxi->qh, (QI6_K/4) * (kqsx / (QI6_K/2)) + kqsx % (QI6_K/4));
         const int qh0 = ((qh >> (2 * ((kqsx % (QI6_K/2)) / (QI6_K/4)))) << 4) & 0x30303030;
         const int qh1 =  (qh >> (2 * ((kqsx % (QI6_K/2)) / (QI6_K/4))))       & 0x30303030;
 
@@ -1883,9 +1887,9 @@ template  static __device__ __forceinlin
         const block_q6_K * bxi = (const block_q6_K *) x + kbx0 + i*stride + (threadIdx.x % (WARP_SIZE/8)) / 4;
 
 #ifdef INT8_MMA_AVAILABLE
-        x_sc[i*MMQ_MMA_TILE_X_K_Q6_K + threadIdx.x % (WARP_SIZE/8)] = get_int_from_int8(bxi->scales, threadIdx.x % (QI6_K/8));
+        x_sc[i*MMQ_MMA_TILE_X_K_Q6_K + threadIdx.x % (WARP_SIZE/8)] = get_int_b2(bxi->scales, threadIdx.x % (QI6_K/8));
 #else
-        x_sc[i*(WARP_SIZE/8) + i/8   + threadIdx.x % (WARP_SIZE/8)] = get_int_from_int8(bxi->scales, threadIdx.x % (QI6_K/8));
+        x_sc[i*(WARP_SIZE/8) + i/8   + threadIdx.x % (WARP_SIZE/8)] = get_int_b2(bxi->scales, threadIdx.x % (QI6_K/8));
 #endif // INT8_MMA_AVAILABLE
     }
 }
@@ -2018,6 +2022,124 @@ static __device__ __forceinline__ void vec_dot_q6_K_q8_1_mma(
 #endif // INT8_MMA_AVAILABLE
 }
 
+template  static __device__ __forceinline__ void load_tiles_iq4_nl(
+    const char * __restrict__ x, int * __restrict__ x_tile, const int & kbx0, const int & i_max, const int & stride) {
+
+#ifdef INT8_MMA_AVAILABLE
+    int   * x_qs = (int   *)  x_tile;
+    float * x_df = (float *) (x_qs + WARP_SIZE*2);
+#else
+    constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_IQ4_NL, mmq_y);
+    int   * x_qs = (int   *)  x_tile;
+    float * x_df = (float *) (x_qs + txs.qs);
+#endif // INT8_MMA_AVAILABLE
+
+    const int kbx  = threadIdx.x / QI4_NL;
+    const int kqsx = threadIdx.x % QI4_NL;
+
+#pragma unroll
+    for (int i0 = 0; i0 < mmq_y; i0 += nwarps) {
+        int i = i0 + threadIdx.y;
+
+        if (need_check) {
+            i = min(i, i_max);
+        }
+
+        const block_iq4_nl * bxi = (const block_iq4_nl *) x + kbx0 + i*stride + kbx;
+
+        const int aux_q4 = get_int_b2(bxi->qs, kqsx);
+        const int2 v = get_int_from_table_16(aux_q4);
+        const int k0 = 8 * (threadIdx.x / 4) + threadIdx.x % 4;
+#ifdef INT8_MMA_AVAILABLE
+        x_qs[i*MMQ_MMA_TILE_X_K_Q5_0 + k0 + 0] = v.x;
+        x_qs[i*MMQ_MMA_TILE_X_K_Q5_0 + k0 + 4] = v.y;
+#else
+        x_qs[i*(2*WARP_SIZE + 1)     + k0 + 0] = v.x;
+        x_qs[i*(2*WARP_SIZE + 1)     + k0 + 4] = v.y;
+#endif // INT8_MMA_AVAILABLE
+    }
+
+    const int blocks_per_tile_x_row = WARP_SIZE / QI4_NL;
+    const int kbxd = threadIdx.x % blocks_per_tile_x_row;
+
+#pragma unroll
+    for (int i0 = 0; i0 < mmq_y; i0 += nwarps * QI4_NL) {
+        int i = i0 + threadIdx.y * QI4_NL + threadIdx.x / blocks_per_tile_x_row;
+
+        if (need_check) {
+            i = min(i, i_max);
+        }
+
+        const block_iq4_nl * bxi = (const block_iq4_nl *) x + kbx0 + i*stride + kbxd;
+
+#ifdef INT8_MMA_AVAILABLE
+        x_df[i*MMQ_MMA_TILE_X_K_Q5_0 + kbxd] = __half2float(bxi->d);
+#else
+        x_df[i*(WARP_SIZE/4) + i/4   + kbxd] = __half2float(bxi->d);
+#endif // INT8_MMA_AVAILABLE
+    }
+}
+
+template  static __device__ __forceinline__ void load_tiles_iq4_xs(
+    const char * __restrict__ x, int * __restrict__ x_tile, const int & kbx0, const int & i_max, const int & stride) {
+
+#ifdef INT8_MMA_AVAILABLE
+    int   * x_qs = (int   *)  x_tile;
+    float * x_df = (float *) (x_qs + WARP_SIZE*2);
+#else
+    constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_IQ4_XS, mmq_y);
+    int   * x_qs = (int   *)  x_tile;
+    float * x_df = (float *) (x_qs + txs.qs);
+#endif // INT8_MMA_AVAILABLE
+
+    const int kbx  = 0;           // threadIdx.x / QI4_XS
+    const int kqsx = threadIdx.x; // threadIdx.x % QI4_XS
+
+#pragma unroll
+    for (int i0 = 0; i0 < mmq_y; i0 += nwarps) {
+        int i = i0 + threadIdx.y;
+
+        if (need_check) {
+            i = min(i, i_max);
+        }
+
+        const block_iq4_xs * bxi = (const block_iq4_xs *) x + kbx0 + i*stride + kbx;
+
+        const int aux_q4 = get_int_b4(bxi->qs, kqsx);
+        const int2 v = get_int_from_table_16(aux_q4);
+        const int k0 = 8 * (threadIdx.x / 4) + threadIdx.x % 4;
+#ifdef INT8_MMA_AVAILABLE
+        x_qs[i*MMQ_MMA_TILE_X_K_Q5_0 + k0 + 0] = v.x;
+        x_qs[i*MMQ_MMA_TILE_X_K_Q5_0 + k0 + 4] = v.y;
+#else
+        x_qs[i*(2*WARP_SIZE + 1)     + k0 + 0] = v.x;
+        x_qs[i*(2*WARP_SIZE + 1)     + k0 + 4] = v.y;
+#endif // INT8_MMA_AVAILABLE
+    }
+
+#pragma unroll
+    for (int i0 = 0; i0 < mmq_y; i0 += nwarps * 4) {
+        int i = i0 + threadIdx.y * 4 + threadIdx.x / (WARP_SIZE/4);
+
+        if (need_check) {
+            i = min(i, i_max);
+        }
+
+        const block_iq4_xs * bxi = (const block_iq4_xs *) x + kbx0 + i*stride;
+
+        const float d = __half2float(bxi->d);
+
+        const int ls = ((bxi->scales_l[(threadIdx.x % 8)/2] >> (4*(threadIdx.x % 2))) & 0x0F)
+            | (((bxi->scales_h >> (2*(threadIdx.x % 8))) & 0x03) << 4);
+
+#ifdef INT8_MMA_AVAILABLE
+        x_df[i*MMQ_MMA_TILE_X_K_Q5_0 + threadIdx.x % 8] = d * (ls - 32);
+#else
+        x_df[i*(WARP_SIZE/4) + i/4   + threadIdx.x % 8] = d * (ls - 32);
+#endif // INT8_MMA_AVAILABLE
+    }
+}
+
 template
 static __device__ __forceinline__ void mmq_write_back_dp4a(
     const float * __restrict__ sum, float * __restrict__ dst, const int & stride, const int & i_max, const int & j_max) {
@@ -2167,6 +2289,22 @@ struct mmq_type_traits {
     static constexpr vec_dot_mmq_t    vec_dot_dp4a = vec_dot_q6_K_q8_1_dp4a;
 };
 
+template 
+struct mmq_type_traits {
+    static constexpr int              vdr          = VDR_IQ4_NL_Q8_1_MMQ;
+    static constexpr load_tiles_mmq_t load_tiles   = load_tiles_iq4_nl;
+    static constexpr vec_dot_mmq_t    vec_dot_mma  = vec_dot_q5_0_q8_1_mma;
+    static constexpr vec_dot_mmq_t    vec_dot_dp4a = vec_dot_q5_0_q8_1_dp4a;
+};
+
+template 
+struct mmq_type_traits {
+    static constexpr int              vdr          = VDR_IQ4_XS_Q8_1_MMQ;
+    static constexpr load_tiles_mmq_t load_tiles   = load_tiles_iq4_xs;
+    static constexpr vec_dot_mmq_t    vec_dot_mma  = vec_dot_q5_0_q8_1_mma;
+    static constexpr vec_dot_mmq_t    vec_dot_dp4a = vec_dot_q5_0_q8_1_dp4a;
+};
+
 static bool mmq_need_sum(const ggml_type type_x) {
     switch (type_x) {
         case GGML_TYPE_Q4_0:
@@ -2184,6 +2322,8 @@ static bool mmq_need_sum(const ggml_type type_x) {
         case GGML_TYPE_Q5_K:
             return true;
         case GGML_TYPE_Q6_K:
+        case GGML_TYPE_IQ4_XS:
+        case GGML_TYPE_IQ4_NL:
             return false;
         default:
             GGML_ASSERT(false);
@@ -2608,6 +2748,8 @@ extern DECL_MMQ_CASE(GGML_TYPE_Q3_K);
 extern DECL_MMQ_CASE(GGML_TYPE_Q4_K);
 extern DECL_MMQ_CASE(GGML_TYPE_Q5_K);
 extern DECL_MMQ_CASE(GGML_TYPE_Q6_K);
+extern DECL_MMQ_CASE(GGML_TYPE_IQ4_NL);
+extern DECL_MMQ_CASE(GGML_TYPE_IQ4_XS);
 
 // -------------------------------------------------------------------------------------------------------------------------
 
diff --git a/ggml/src/ggml-cuda/template-instances/generate_cu_files.py b/ggml/src/ggml-cuda/template-instances/generate_cu_files.py
index ea58d09680231..ffeb3c27df2f4 100755
--- a/ggml/src/ggml-cuda/template-instances/generate_cu_files.py
+++ b/ggml/src/ggml-cuda/template-instances/generate_cu_files.py
@@ -22,7 +22,8 @@
 
 TYPES_MMQ = [
     "GGML_TYPE_Q4_0", "GGML_TYPE_Q4_1", "GGML_TYPE_Q5_0", "GGML_TYPE_Q5_1", "GGML_TYPE_Q8_0",
-    "GGML_TYPE_Q2_K", "GGML_TYPE_Q3_K", "GGML_TYPE_Q4_K", "GGML_TYPE_Q5_K", "GGML_TYPE_Q6_K"
+    "GGML_TYPE_Q2_K", "GGML_TYPE_Q3_K", "GGML_TYPE_Q4_K", "GGML_TYPE_Q5_K", "GGML_TYPE_Q6_K",
+    "GGML_TYPE_IQ4_NL", "GGML_TYPE_IQ4_XS"
 ]
 
 SOURCE_MMQ = """// This file has been autogenerated by generate_cu_files.py, do not edit manually.
diff --git a/ggml/src/ggml-cuda/template-instances/mmq-instance-iq4_nl.cu b/ggml/src/ggml-cuda/template-instances/mmq-instance-iq4_nl.cu
new file mode 100644
index 0000000000000..eb02fab002ecc
--- /dev/null
+++ b/ggml/src/ggml-cuda/template-instances/mmq-instance-iq4_nl.cu
@@ -0,0 +1,5 @@
+// This file has been autogenerated by generate_cu_files.py, do not edit manually.
+
+#include "../mmq.cuh"
+
+DECL_MMQ_CASE(GGML_TYPE_IQ4_NL);
diff --git a/ggml/src/ggml-cuda/template-instances/mmq-instance-iq4_xs.cu b/ggml/src/ggml-cuda/template-instances/mmq-instance-iq4_xs.cu
new file mode 100644
index 0000000000000..1eb3b7430726f
--- /dev/null
+++ b/ggml/src/ggml-cuda/template-instances/mmq-instance-iq4_xs.cu
@@ -0,0 +1,5 @@
+// This file has been autogenerated by generate_cu_files.py, do not edit manually.
+
+#include "../mmq.cuh"
+
+DECL_MMQ_CASE(GGML_TYPE_IQ4_XS);
diff --git a/ggml/src/ggml-cuda/vecdotq.cuh b/ggml/src/ggml-cuda/vecdotq.cuh
index 3f3a87c750b21..1d510484ac474 100644
--- a/ggml/src/ggml-cuda/vecdotq.cuh
+++ b/ggml/src/ggml-cuda/vecdotq.cuh
@@ -1,36 +1,8 @@
 #include "common.cuh"
 #include 
 
-static __device__ __forceinline__ int get_int_from_int8(const int8_t * x8, const int & i32) {
-    const uint16_t * x16 = (const uint16_t *) (x8 + sizeof(int) * i32); // assume at least 2 byte alignment
-
-    int x32 = 0;
-    x32 |= x16[0] <<  0;
-    x32 |= x16[1] << 16;
-
-    return x32;
-}
-
-static __device__ __forceinline__ int get_int_from_uint8(const uint8_t * x8, const int & i32) {
-    const uint16_t * x16 = (const uint16_t *) (x8 + sizeof(int) * i32); // assume at least 2 byte alignment
-
-    int x32 = 0;
-    x32 |= x16[0] <<  0;
-    x32 |= x16[1] << 16;
-
-    return x32;
-}
-
-static __device__ __forceinline__ int get_int_from_int8_aligned(const int8_t * x8, const int & i32) {
-    return *((const int *) (x8 + sizeof(int) * i32)); // assume at least 4 byte alignment
-}
-
-static __device__ __forceinline__ int get_int_from_uint8_aligned(const uint8_t * x8, const int & i32) {
-    return *((const int *) (x8 + sizeof(int) * i32)); // assume at least 4 byte alignment
-}
-
 static __device__ __forceinline__ int get_int_b2(const void * x, const int & i32) {
-    const uint16_t * x16 = (const uint16_t *) x;
+    const uint16_t * x16 = (const uint16_t *) x; // assume at least 2 byte alignment
 
     int x32  = x16[2*i32 + 0] <<  0;
     x32     |= x16[2*i32 + 1] << 16;
@@ -768,6 +740,7 @@ static __device__ __forceinline__ float vec_dot_q6_K_q8_1(
 }
 
 #define VDR_IQ2_XXS_Q8_1_MMVQ 2
+#define VDR_IQ2_XXS_Q8_1_MMQ  2
 
 static __device__ __forceinline__ float vec_dot_iq2_xxs_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {
@@ -802,6 +775,7 @@ static __device__ __forceinline__ float vec_dot_iq2_xxs_q8_1(
 }
 
 #define VDR_IQ2_XS_Q8_1_MMVQ 2
+#define VDR_IQ2_XS_Q8_1_MMQ  2
 
 static __device__ __forceinline__ float vec_dot_iq2_xs_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {
@@ -840,6 +814,7 @@ static __device__ __forceinline__ float vec_dot_iq2_xs_q8_1(
 }
 
 #define VDR_IQ2_S_Q8_1_MMVQ 2
+#define VDR_IQ2_S_Q8_1_MMQ  2
 
 static __device__ __forceinline__ float vec_dot_iq2_s_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {
@@ -887,6 +862,7 @@ static __device__ __forceinline__ float vec_dot_iq2_s_q8_1(
 }
 
 #define VDR_IQ3_XXS_Q8_1_MMVQ 2
+#define VDR_IQ3_XXS_Q8_1_MMQ  2
 
 static __device__ __forceinline__ float vec_dot_iq3_xxs_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {
@@ -921,6 +897,7 @@ static __device__ __forceinline__ float vec_dot_iq3_xxs_q8_1(
 }
 
 #define VDR_IQ3_S_Q8_1_MMVQ 2
+#define VDR_IQ3_S_Q8_1_MMQ  2
 
 // TODO: don't use lookup table for signs
 static __device__ __forceinline__ float vec_dot_iq3_s_q8_1(
@@ -962,6 +939,9 @@ static __device__ __forceinline__ float vec_dot_iq3_s_q8_1(
     return d * sumi;
 }
 
+#define VDR_IQ1_S_Q8_1_MMVQ 1
+#define VDR_IQ1_S_Q8_1_MMQ  1
+
 static __device__ __forceinline__ float vec_dot_iq1_s_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {
     const block_iq1_s * bq1 = (const block_iq1_s *) vbq + kbx;
@@ -992,6 +972,9 @@ static __device__ __forceinline__ float vec_dot_iq1_s_q8_1(
     return d1q * (ds.x*sumi + ds.y*delta);
 }
 
+#define VDR_IQ1_M_Q8_1_MMVQ 1
+#define VDR_IQ1_M_Q8_1_MMQ  1
+
 static __device__ __forceinline__ float vec_dot_iq1_m_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {
 
@@ -1051,6 +1034,7 @@ static __device__ __forceinline__ int2 get_int_from_table_16(const int & q4) {
 }
 
 #define VDR_IQ4_NL_Q8_1_MMVQ 2
+#define VDR_IQ4_NL_Q8_1_MMQ  4
 
 static __device__ __forceinline__ float vec_dot_iq4_nl_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {
@@ -1074,6 +1058,7 @@ static __device__ __forceinline__ float vec_dot_iq4_nl_q8_1(
 }
 
 #define VDR_IQ4_XS_Q8_1_MMVQ 4
+#define VDR_IQ4_XS_Q8_1_MMQ  4
 
 static __device__ __forceinline__ float vec_dot_iq4_xs_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {

From 2cccbaa0086c62801f95405131a5b2faf3ba1de8 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Fri, 5 Jul 2024 10:15:24 +0300
Subject: [PATCH 109/326] llama : minor indentation during tensor loading
 (#8304)

* llama : minor indentation during tensor loading

ggml-ci

* llama : use int for layer iterators [no ci]
---
 src/llama.cpp | 335 ++++++++++++++++++++++++++------------------------
 1 file changed, 176 insertions(+), 159 deletions(-)

diff --git a/src/llama.cpp b/src/llama.cpp
index 132055888b9f1..95184c1083a1c 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -5840,8 +5840,8 @@ static bool llm_load_tensors(
     model.main_gpu     = main_gpu;
     model.n_gpu_layers = n_gpu_layers;
 
-    const int64_t n_layer     = hparams.n_layer;
-    const int64_t i_gpu_start = std::max((int64_t) hparams.n_layer - n_gpu_layers, (int64_t) 0);
+    const int n_layer     = hparams.n_layer;
+    const int i_gpu_start = std::max((int) hparams.n_layer - n_gpu_layers, (int) 0);
     bool use_mmap_buffer = true;
 
     // there is very little benefit to offloading the input layer, so always keep it on the CPU
@@ -5851,7 +5851,7 @@ static bool llm_load_tensors(
     model.buft_layer.resize(n_layer);
 
     // assign cpu layers
-    for (int64_t i = 0; i < i_gpu_start; ++i) {
+    for (int i = 0; i < i_gpu_start; ++i) {
         model.buft_layer[i] = llama_default_buffer_type_cpu(true);
     }
 
@@ -5881,7 +5881,7 @@ static bool llm_load_tensors(
 
         // assign the repeating layers to the devices according to the splits
         int act_gpu_layers = std::min(n_gpu_layers, (int)n_layer + 1);
-        for (int64_t i = i_gpu_start; i < n_layer; ++i) {
+        for (int i = i_gpu_start; i < n_layer; ++i) {
             int layer_gpu = std::upper_bound(splits.begin(), splits.begin() + device_count, float(i - i_gpu_start)/act_gpu_layers) - splits.begin();
             model.buft_layer[i] = llama_default_buffer_type_offload(model, layer_gpu);
         }
@@ -5901,7 +5901,7 @@ static bool llm_load_tensors(
             split_buft = llama_default_buffer_type_offload(model, main_gpu);
         }
         // assign the repeating layers
-        for (int64_t i = i_gpu_start; i < n_layer; ++i) {
+        for (int i = i_gpu_start; i < n_layer; ++i) {
             model.buft_layer[i] = {
                 split_buft,
                 llama_default_buffer_type_offload(model, main_gpu)
@@ -5924,7 +5924,7 @@ static bool llm_load_tensors(
     buft_layer_count[model.buft_input.buft_matrix]++;
     buft_layer_count[model.buft_output.buft]++;
     buft_layer_count[model.buft_output.buft_matrix]++;
-    for (int64_t i = 0; i < n_layer; ++i) {
+    for (int i = 0; i < n_layer; ++i) {
         buft_layer_count[model.buft_layer[i].buft]++;
         buft_layer_count[model.buft_layer[i].buft_matrix]++;
     }
@@ -5954,15 +5954,21 @@ static bool llm_load_tensors(
 
     // create tensors for the weights
     {
-        const int64_t n_embd       = hparams.n_embd;
-        const int64_t n_embd_head  = hparams.n_head() > 0 ? n_embd / hparams.n_head() : 0;
-        const int64_t n_embd_k_gqa = hparams.n_embd_k_gqa();
-        const int64_t n_embd_v_gqa = hparams.n_embd_v_gqa();
-        const int64_t n_embd_gqa   = n_embd_v_gqa;
-        const int64_t n_vocab      = hparams.n_vocab;
-        const int64_t n_vocab_type = hparams.n_vocab_type;
-        const int64_t n_ff         = hparams.n_ff();
-        const int64_t n_expert     = hparams.n_expert;
+        // note: cast to int64_t since we will use these for the tensor dimensions
+        const int64_t n_head        = hparams.n_head();
+        const int64_t n_head_kv     = hparams.n_head_kv();
+        const int64_t n_embd        = hparams.n_embd;
+        const int64_t n_embd_k_gqa  = hparams.n_embd_k_gqa();
+        const int64_t n_embd_v_gqa  = hparams.n_embd_v_gqa();
+        const int64_t n_embd_head_k = hparams.n_embd_head_k;
+        const int64_t n_embd_head_v = hparams.n_embd_head_v;
+        const int64_t n_ff          = hparams.n_ff();
+        const int64_t n_embd_gqa    = n_embd_v_gqa;
+        const int64_t n_vocab       = hparams.n_vocab;
+        const int64_t n_vocab_type  = hparams.n_vocab_type;
+        const int64_t n_expert      = hparams.n_expert;
+        const int64_t n_expert_used = hparams.n_expert_used;
+        const int64_t n_ctx_train   = hparams.n_ctx_train;
 
         if (n_expert > 0 && hparams.n_expert_used == 0) {
             throw std::runtime_error("model has expert layers but no expert layers are used");
@@ -5971,8 +5977,9 @@ static bool llm_load_tensors(
         ggml_context * ctx_input        = ctx_map.at(model.buft_input.buft);
         ggml_context * ctx_output       = ctx_map.at(model.buft_output.buft);
         ggml_context * ctx_output_split = ctx_map.at(model.buft_output.buft_matrix);
-        auto ctx_for_layer              = [&](int i) { return ctx_map.at(model.buft_layer[i].buft); };
-        auto ctx_for_layer_split        = [&](int i) { return ctx_map.at(model.buft_layer[i].buft_matrix); };
+
+        auto ctx_for_layer       = [&](int i) { return ctx_map.at(model.buft_layer[i].buft); };
+        auto ctx_for_layer_split = [&](int i) { return ctx_map.at(model.buft_layer[i].buft_matrix); };
 
         model.layers.resize(n_layer);
 
@@ -5987,7 +5994,8 @@ static bool llm_load_tensors(
                     // output
                     {
                         model.output_norm = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
-                        model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        model.output      = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
+
                         // if output is NULL, init from the input tok embed
                         if (model.output == NULL) {
                             model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED);
@@ -6070,6 +6078,7 @@ static bool llm_load_tensors(
                     {
                         model.output_norm = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
                         model.output      = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
+
                         // if output is NULL, init from the input tok embed
                         if (model.output == NULL) {
                             model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED);
@@ -6093,9 +6102,9 @@ static bool llm_load_tensors(
 
                         layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
 
-                        layer.ffn_gate_inp = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_GATE_INP, "weight", i), {n_embd, n_expert});
-
+                        layer.ffn_gate_inp  = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_GATE_INP,  "weight", i), {n_embd, n_expert});
                         layer.ffn_gate_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_EXPS, "weight", i), {n_embd, n_ff, n_expert}, llama_model_loader::TENSOR_NOT_REQUIRED);
+
                         if (layer.ffn_gate_exps) {
                             layer.ffn_down_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN_EXPS, "weight", i), {  n_ff, n_embd, n_expert});
                             layer.ffn_up_exps   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP_EXPS,   "weight", i), {n_embd,   n_ff, n_expert});
@@ -6147,12 +6156,12 @@ static bool llm_load_tensors(
 
                     auto & layer = model.layers[i];
 
-                    layer.attn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM,  "weight", i), {n_embd});
+                    layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
 
                     layer.wqkv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_embd + 2*n_embd_gqa});
                     layer.wo   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
 
-                    layer.attn_out_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT_NORM, "weight", i), {n_embd});
+                    layer.attn_out_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT_NORM, "weight", i), {n_embd});
 
                     layer.ffn_gate_inp  = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_GATE_INP,  "weight", i), {n_embd, n_expert});
                     layer.ffn_gate_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_EXPS, "weight", i), {n_embd, n_ff,   n_expert});
@@ -6194,10 +6203,10 @@ static bool llm_load_tensors(
 
                     // output
                     {
-                        model.output_norm   = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
-                        model.output_norm_b = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "bias"),   {n_embd});
+                        model.output_norm   = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
+                        model.output_norm_b = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "bias"),   {n_embd});
 
-                        model.output        = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
                         if (!model.output) {
                             model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED); // needs to be on GPU
                         }
@@ -6225,7 +6234,7 @@ static bool llm_load_tensors(
             case LLM_ARCH_STARCODER:
                 {
                     model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
-                    model.pos_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_POS_EMBD,   "weight"), {n_embd, hparams.n_ctx_train});
+                    model.pos_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_POS_EMBD,   "weight"), {n_embd, n_ctx_train});
 
                     // output
                     {
@@ -6251,8 +6260,8 @@ static bool llm_load_tensors(
                         layer.wqkv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_embd + 2*n_embd_gqa});
                         layer.bqkv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_QKV, "bias", i),   {n_embd + 2*n_embd_gqa});
 
-                        layer.wo   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
-                        layer.bo   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT, "bias", i),   {n_embd});
+                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
+                        layer.bo = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT, "bias", i),   {n_embd});
 
                         layer.ffn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
                         layer.ffn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "bias", i),   {n_embd});
@@ -6260,8 +6269,8 @@ static bool llm_load_tensors(
                         layer.ffn_down   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd});
                         layer.ffn_down_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_DOWN, "bias", i),   {n_embd});
 
-                        layer.ffn_up     = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP, "weight", i),   {n_embd, n_ff});
-                        layer.ffn_up_b   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP, "bias", i),     {n_ff});
+                        layer.ffn_up   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP, "weight", i),   {n_embd, n_ff});
+                        layer.ffn_up_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP, "bias", i),     {n_ff});
                     }
                 } break;
             case LLM_ARCH_BERT:
@@ -6269,8 +6278,9 @@ static bool llm_load_tensors(
                 {
                     model.tok_embd     = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD,  "weight"), {n_embd, n_vocab});
                     model.type_embd    = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_TYPES, "weight"), {n_embd, n_vocab_type});
+
                     if (model.arch == LLM_ARCH_BERT) {
-                        model.pos_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_POS_EMBD,    "weight"), {n_embd, hparams.n_ctx_train});
+                        model.pos_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_POS_EMBD,    "weight"), {n_embd, n_ctx_train});
                     }
 
                     model.tok_norm   = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD_NORM, "weight"), {n_embd});
@@ -6283,31 +6293,30 @@ static bool llm_load_tensors(
                         auto & layer = model.layers[i];
 
                         if (model.arch == LLM_ARCH_BERT) {
-                            layer.wq   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd});
-                            layer.bq   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q,   "bias", i),   {n_embd});
+                            layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd});
+                            layer.bq = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q,   "bias", i),   {n_embd});
 
-                            layer.wk   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K,   "weight", i), {n_embd, n_embd_gqa});
-                            layer.bk   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K,   "bias", i),   {n_embd_gqa});
+                            layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K,   "weight", i), {n_embd, n_embd_gqa});
+                            layer.bk = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K,   "bias", i),   {n_embd_gqa});
 
-                            layer.wv   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V,   "weight", i), {n_embd, n_embd_gqa});
-                            layer.bv   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_V,   "bias", i),   {n_embd_gqa});
+                            layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V,   "weight", i), {n_embd, n_embd_gqa});
+                            layer.bv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_V,   "bias", i),   {n_embd_gqa});
                         } else {
                             layer.wqkv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_embd + 2*n_embd_gqa});
                         }
 
-                        layer.wo              = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT,      "weight", i), {n_embd, n_embd});
+                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT,      "weight", i), {n_embd, n_embd});
 
                         layer.attn_out_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT_NORM, "weight", i), {n_embd});
                         layer.attn_out_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT_NORM, "bias", i),   {n_embd});
 
-                        layer.ffn_up          = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,        "weight", i), {n_embd, n_ff});
-                        layer.ffn_down        = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN,      "weight", i), {n_ff, n_embd});
+                        layer.ffn_up   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,        "weight", i), {n_embd, n_ff});
+                        layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN,      "weight", i), {n_ff, n_embd});
 
                         if (model.arch == LLM_ARCH_BERT) {
-                            layer.bo         = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT, "bias", i),   {n_embd});
-                            layer.ffn_up_b   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP,   "bias", i),   {n_ff});
-
-                            layer.ffn_down_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_DOWN, "bias", i),   {n_embd});
+                            layer.bo         = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT, "bias", i), {n_embd});
+                            layer.ffn_up_b   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP,   "bias", i), {n_ff});
+                            layer.ffn_down_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_DOWN, "bias", i), {n_embd});
                         } else {
                             layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff});
                         }
@@ -6318,8 +6327,9 @@ static bool llm_load_tensors(
                 } break;
             case LLM_ARCH_JINA_BERT_V2:
                 {
-                    model.tok_embd     = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD,  "weight"), {n_embd, n_vocab}); // word_embeddings
-                    model.type_embd    = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_TYPES, "weight"), {n_embd, n_vocab_type}); //token_type_embeddings
+                    model.tok_embd  = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD,  "weight"), {n_embd, n_vocab}); // word_embeddings
+                    model.type_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_TYPES, "weight"), {n_embd, n_vocab_type}); // token_type_embeddings
+
                     model.tok_norm   = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD_NORM, "weight"), {n_embd}); // LayerNorm
                     model.tok_norm_b = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD_NORM, "bias"),   {n_embd}); //LayerNorm bias
 
@@ -6329,38 +6339,38 @@ static bool llm_load_tensors(
 
                         auto & layer = model.layers[i]; // JinaBertLayer
 
-                        layer.wq   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd});
-                        layer.bq   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q,   "bias", i),   {n_embd});
+                        layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q, "weight", i), {n_embd, n_embd});
+                        layer.bq = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q, "bias", i),   {n_embd});
 
                         layer.attn_q_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
-                        layer.attn_q_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "bias", i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_q_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "bias",   i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
-                        layer.wk   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K,   "weight", i), {n_embd, n_embd_gqa});
-                        layer.bk   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K,   "bias", i),   {n_embd_gqa});
+                        layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K, "weight", i), {n_embd, n_embd_gqa});
+                        layer.bk = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K, "bias",   i), {n_embd_gqa});
 
                         layer.attn_k_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
-                        layer.attn_k_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "bias", i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_k_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "bias",   i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
-                        layer.wv   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V,   "weight", i), {n_embd, n_embd_gqa});
-                        layer.bv   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_V,   "bias", i),   {n_embd_gqa});
+                        layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V, "weight", i), {n_embd, n_embd_gqa});
+                        layer.bv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_V, "bias",   i), {n_embd_gqa});
 
-                        layer.wo              = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT,      "weight", i), {n_embd, n_embd}); //output_dens
-                        layer.bo              = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT,      "bias", i), {n_embd}); //output_dens
+                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd}); //output_dens
+                        layer.bo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "bias",   i), {n_embd}); //output_dens
 
                         layer.attn_out_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT_NORM, "weight", i), {n_embd}); //output_norm
-                        layer.attn_out_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT_NORM, "bias", i),   {n_embd});
+                        layer.attn_out_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT_NORM, "bias",   i), {n_embd});
 
                         layer.attn_norm_2   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM_2, "weight", i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
-                        layer.attn_norm_2_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM_2, "bias", i),   {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_norm_2_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM_2, "bias",   i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
-                        layer.ffn_up = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,        "weight", i), {n_embd, n_ff});
-                        layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE,    "weight", i), {n_embd, n_ff});
+                        layer.ffn_up   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd, n_ff});
+                        layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff});
 
-                        layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN,        "weight", i), {n_ff, n_embd});
-                        layer.ffn_down_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_DOWN,      "bias", i), {n_embd});
+                        layer.ffn_down   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd});
+                        layer.ffn_down_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_DOWN, "bias",   i), {n_embd});
 
-                        layer.layer_out_norm = ml.create_tensor(ctx_split, tn(LLM_TENSOR_LAYER_OUT_NORM,        "weight", i), {n_embd});
-                        layer.layer_out_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_LAYER_OUT_NORM,        "bias", i), {n_embd});
+                        layer.layer_out_norm   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_LAYER_OUT_NORM, "weight", i), {n_embd});
+                        layer.layer_out_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_LAYER_OUT_NORM, "bias",   i), {n_embd});
                     }
                 } break;
             case LLM_ARCH_BLOOM:
@@ -6383,35 +6393,35 @@ static bool llm_load_tensors(
                         auto & layer = model.layers[i];
 
                         layer.attn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
-                        layer.attn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "bias", i),   {n_embd});
+                        layer.attn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "bias",   i), {n_embd});
 
                         layer.wqkv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_embd + 2*n_embd_gqa});
-                        layer.bqkv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_QKV, "bias", i),   {n_embd + 2*n_embd_gqa});
+                        layer.bqkv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_QKV, "bias",   i), {n_embd + 2*n_embd_gqa});
 
                         layer.wo   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
-                        layer.bo   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT, "bias", i),   {n_embd});
+                        layer.bo   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT, "bias",   i), {n_embd});
 
                         layer.ffn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
-                        layer.ffn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "bias", i),   {n_embd});
+                        layer.ffn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "bias",   i), {n_embd});
 
                         layer.ffn_down   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd});
-                        layer.ffn_down_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_DOWN, "bias", i),   {n_embd});
+                        layer.ffn_down_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_DOWN, "bias",   i), {n_embd});
 
-                        layer.ffn_up     = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd, n_ff});
-                        layer.ffn_up_b   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP,   "bias", i),   {n_ff});
+                        layer.ffn_up     = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP, "weight", i), {n_embd, n_ff});
+                        layer.ffn_up_b   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP, "bias",   i), {n_ff});
                     }
                 } break;
             case LLM_ARCH_MPT:
                 {
                     model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
-                    model.pos_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_POS_EMBD,   "weight"), {n_embd, hparams.n_ctx_train}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                    model.pos_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_POS_EMBD,   "weight"), {n_embd, n_ctx_train}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                     // output
                     {
-                        model.output_norm   = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
-                        model.output_norm_b = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "bias"),   {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        model.output_norm   = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
+                        model.output_norm_b = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "bias"),   {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
-                        model.output        = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        model.output        = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
                         if (!model.output) {
                             model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED); // needs to be on GPU
                         }
@@ -6482,8 +6492,8 @@ static bool llm_load_tensors(
                         layer.bv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_V,   "bias", i), {n_embd_gqa}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         // optional q and k layernorms, present in StableLM 2 12B
-                        layer.attn_q_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head()}, llama_model_loader::TENSOR_NOT_REQUIRED);
-                        layer.attn_k_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head_kv()}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_q_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {n_embd_head_k, n_head},    llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_k_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {n_embd_head_k, n_head_kv}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         // optional FFN norm, not present in StableLM 2 12B which uses parallel residual
                         layer.ffn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
@@ -6594,21 +6604,23 @@ static bool llm_load_tensors(
 
                         layer.ffn_gate_inp = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_GATE_INP, "weight", i), {n_embd, n_expert});
 
-                        GGML_ASSERT(hparams.n_expert      > 0);
-                        GGML_ASSERT(hparams.n_expert_used > 0);
+                        GGML_ASSERT(n_expert      > 0);
+                        GGML_ASSERT(n_expert_used > 0);
 
                         // MoE branch
-                        auto n_ff_exp = hparams.n_ff_exp ? hparams.n_ff_exp : n_ff / hparams.n_expert_used;
+                        const int64_t n_ff_exp = hparams.n_ff_exp ? hparams.n_ff_exp : n_ff / n_expert_used;
+
                         layer.ffn_gate_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_EXPS, "weight", i), {  n_embd, n_ff_exp, n_expert});
                         layer.ffn_down_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN_EXPS, "weight", i), {n_ff_exp,   n_embd, n_expert});
                         layer.ffn_up_exps   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP_EXPS,   "weight", i), {  n_embd, n_ff_exp, n_expert});
 
                         // Shared expert branch
-                        auto n_ff_shexp = hparams.n_ff_shexp ? hparams.n_ff_shexp : n_ff;
+                        const int64_t n_ff_shexp = hparams.n_ff_shexp ? hparams.n_ff_shexp : n_ff;
+
                         layer.ffn_gate_inp_shexp = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_GATE_INP_SHEXP, "weight", i), {n_embd});
-                        layer.ffn_gate_shexp = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_SHEXP, "weight", i), {n_embd, n_ff_shexp});
-                        layer.ffn_down_shexp = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN_SHEXP, "weight", i), {n_ff_shexp, n_embd});
-                        layer.ffn_up_shexp   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP_SHEXP,   "weight", i), {n_embd, n_ff_shexp});
+                        layer.ffn_gate_shexp = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_SHEXP, "weight", i), {    n_embd, n_ff_shexp});
+                        layer.ffn_down_shexp = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN_SHEXP, "weight", i), {n_ff_shexp,     n_embd});
+                        layer.ffn_up_shexp   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP_SHEXP,   "weight", i), {    n_embd, n_ff_shexp});
                     }
                 } break;
             case LLM_ARCH_PHI2:
@@ -6658,6 +6670,8 @@ static bool llm_load_tensors(
                 } break;
             case LLM_ARCH_PHI3:
                 {
+                    const int64_t n_embd_head = n_embd / n_head;
+
                     model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), { n_embd, n_vocab });
 
                     // output
@@ -6667,8 +6681,8 @@ static bool llm_load_tensors(
                     }
 
                     for (int i = 0; i < n_layer; ++i) {
-                        ggml_context* ctx_layer = ctx_for_layer(i);
-                        ggml_context* ctx_split = ctx_for_layer_split(i);
+                        ggml_context * ctx_layer = ctx_for_layer(i);
+                        ggml_context * ctx_split = ctx_for_layer_split(i);
 
                         auto & layer = model.layers[i];
 
@@ -6717,7 +6731,7 @@ static bool llm_load_tensors(
             case LLM_ARCH_GPT2:
                 {
                     model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
-                    model.pos_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_POS_EMBD,   "weight"),   {n_embd, hparams.n_ctx_train});
+                    model.pos_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_POS_EMBD,   "weight"), {n_embd, n_ctx_train});
 
                     // output
                     {
@@ -6854,12 +6868,7 @@ static bool llm_load_tensors(
                     model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
                     model.output      = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD,  "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED); // same as tok_embd, duplicated to allow offloading
 
-                    const int64_t n_ff          = hparams.n_ff();
-                    const int64_t n_embd_head_k = hparams.n_embd_head_k;
-                    const int64_t n_embd_k_gqa  = hparams.n_embd_k_gqa();
-                    const int64_t n_embd_v_gqa  = hparams.n_embd_v_gqa();
-
-                    for (uint32_t i = 0; i < n_layer; ++i) {
+                    for (int i = 0; i < n_layer; ++i) {
                         ggml_context * ctx_layer = ctx_for_layer(i);
                         ggml_context * ctx_split = ctx_for_layer_split(i);
 
@@ -6867,10 +6876,10 @@ static bool llm_load_tensors(
 
                         layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
 
-                        layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd_head_k * hparams.n_head()});
+                        layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd_head_k * n_head});
                         layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K,   "weight", i), {n_embd, n_embd_k_gqa});
                         layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V,   "weight", i), {n_embd, n_embd_v_gqa});
-                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd_head_k * hparams.n_head(), n_embd});
+                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd_head_k * n_head, n_embd});
 
                         layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
                         layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd,   n_ff});
@@ -6886,12 +6895,7 @@ static bool llm_load_tensors(
                     model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
                     model.output      = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD,  "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED); // same as tok_embd, duplicated to allow offloading
 
-                    const int64_t n_ff          = hparams.n_ff();
-                    const int64_t n_embd_head_k = hparams.n_embd_head_k;
-                    const int64_t n_embd_k_gqa  = hparams.n_embd_k_gqa();
-                    const int64_t n_embd_v_gqa  = hparams.n_embd_v_gqa();
-
-                    for (uint32_t i = 0; i < n_layer; ++i) {
+                    for (int i = 0; i < n_layer; ++i) {
                         ggml_context * ctx_layer = ctx_for_layer(i);
                         ggml_context * ctx_split = ctx_for_layer_split(i);
 
@@ -6899,10 +6903,10 @@ static bool llm_load_tensors(
 
                         layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
 
-                        layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd_head_k * hparams.n_head()});
+                        layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd_head_k * n_head});
                         layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K,   "weight", i), {n_embd, n_embd_k_gqa});
                         layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V,   "weight", i), {n_embd, n_embd_v_gqa});
-                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd_head_k * hparams.n_head(), n_embd});
+                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd_head_k * n_head, n_embd});
                         layer.attn_post_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_POST_NORM, "weight", i), {n_embd});
 
                         layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
@@ -6966,6 +6970,7 @@ static bool llm_load_tensors(
                     const int64_t d_inner = hparams.ssm_d_inner;
                     const int64_t d_state = hparams.ssm_d_state;
                     const int64_t dt_rank = hparams.ssm_dt_rank;
+
                     // only an expansion factor of 2 is supported for now
                     GGML_ASSERT(2 * n_embd == d_inner);
 
@@ -7016,15 +7021,20 @@ static bool llm_load_tensors(
                         model.output_norm = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
                         model.output      = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab});
                     }
+
                     for (int i = 0; i < n_layer; ++i) {
                         ggml_context * ctx_layer = ctx_for_layer(i);
                         ggml_context * ctx_split = ctx_for_layer_split(i);
+
                         auto & layer = model.layers[i];
+
                         layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
+
                         layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd});
                         layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K,   "weight", i), {n_embd, n_embd_gqa});
                         layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V,   "weight", i), {n_embd, n_embd_gqa});
                         layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
+
                         layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
                         layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd,   n_ff});
                         layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {  n_ff, n_embd});
@@ -7051,8 +7061,8 @@ static bool llm_load_tensors(
                         layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
 
                         if (n_layer >= 64){
-                            layer.attn_q_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head()});
-                            layer.attn_k_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head_kv()});
+                            layer.attn_q_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {n_embd_head_k, n_head});
+                            layer.attn_k_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {n_embd_head_k, n_head_kv});
                         }
 
                         layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd});
@@ -7088,7 +7098,6 @@ static bool llm_load_tensors(
                         layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V,   "weight", i), {n_embd, n_embd_gqa});
                         layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
 
-
                         layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd,   n_ff});
                         layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {  n_ff, n_embd});
                         layer.ffn_up   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd,   n_ff});
@@ -7106,11 +7115,9 @@ static bool llm_load_tensors(
                     }
 
                     for (int i = 0; i < n_layer; ++i) {
-                        const int64_t n_head = hparams.n_head(i);
-                        const int64_t n_head_qkv = 2*hparams.n_head_kv(i) + n_head;
-                        const int64_t n_embd_head = hparams.n_embd_head_k;
-
-                        const int64_t n_ff = hparams.n_ff(i);
+                        const int64_t n_head      =   hparams.n_head(i);
+                        const int64_t n_head_qkv  = 2*hparams.n_head_kv(i) + n_head;
+                        const int64_t n_ff        =   hparams.n_ff(i);
 
                         ggml_context * ctx_layer = ctx_for_layer(i);
                         ggml_context * ctx_split = ctx_for_layer_split(i);
@@ -7119,10 +7126,10 @@ static bool llm_load_tensors(
 
                         layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
 
-                        layer.wqkv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_head_qkv*n_embd_head});
-                        layer.attn_q_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {n_embd_head});
-                        layer.attn_k_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {n_embd_head});
-                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_head*n_embd_head, n_embd});
+                        layer.wqkv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_head_qkv*n_embd_head_k});
+                        layer.attn_q_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {n_embd_head_k});
+                        layer.attn_k_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {n_embd_head_k});
+                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_head*n_embd_head_k, n_embd});
 
                         layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
                         layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff});
@@ -7132,7 +7139,8 @@ static bool llm_load_tensors(
                 } break;
             case LLM_ARCH_GPTNEOX:
                 {
-                    model.tok_embd   = ml.create_tensor(ctx_input,  tn(LLM_TENSOR_TOKEN_EMBD,      "weight"), {n_embd, n_vocab});
+                    model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
+
                     // output
                     {
                         model.output_norm   = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
@@ -7171,8 +7179,9 @@ static bool llm_load_tensors(
 
                     // output
                     {
-                        model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
-                        model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        model.output_norm = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
+                        model.output      = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
+
                         // if output is NULL, init from the input tok embed
                         if (model.output == NULL) {
                             model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED);
@@ -7207,13 +7216,16 @@ static bool llm_load_tensors(
                 } break;
             case LLM_ARCH_DEEPSEEK2:
                 {
-                    bool is_lite = (hparams.n_layer == 27);
+                    const bool is_lite = (hparams.n_layer == 27);
 
-                    const uint32_t n_embd_head_qk_rope = hparams.n_rot;
-                    const uint32_t n_embd_head_qk_nope = hparams.n_embd_head_k - hparams.n_rot;
-                    const uint32_t q_lora_rank = hparams.n_lora_q;
-                    const uint32_t kv_lora_rank = hparams.n_lora_kv;
-                    const uint32_t n_ff_exp = hparams.n_ff_exp;
+                    const int64_t n_embd_head_qk_rope = hparams.n_rot;
+                    const int64_t n_embd_head_qk_nope = hparams.n_embd_head_k - hparams.n_rot;
+
+                    const int64_t q_lora_rank  = hparams.n_lora_q;
+                    const int64_t kv_lora_rank = hparams.n_lora_kv;
+
+                    const int64_t n_ff_exp        = hparams.n_ff_exp;
+                    const int64_t n_expert_shared = hparams.n_expert_shared;
 
                     model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
 
@@ -7233,29 +7245,31 @@ static bool llm_load_tensors(
                         if (!is_lite) {
                             layer.attn_q_a_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_A_NORM, "weight", i), {q_lora_rank});
                         }
+
                         layer.attn_kv_a_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_KV_A_NORM, "weight", i), {kv_lora_rank});
 
                         if (!is_lite) {
-                            layer.wq_a = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q_A,   "weight", i), {n_embd, q_lora_rank});
-                            layer.wq_b = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q_B,   "weight", i), {q_lora_rank, hparams.n_head() * hparams.n_embd_head_k});
+                            layer.wq_a = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q_A, "weight", i), {n_embd, q_lora_rank});
+                            layer.wq_b = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q_B, "weight", i), {q_lora_rank, n_head * n_embd_head_k});
                         } else {
-                            layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd_k_gqa});
+                            layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q, "weight", i), {n_embd, n_embd_k_gqa});
                         }
-                        layer.wkv_a_mqa = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_KV_A_MQA,   "weight", i), {n_embd, kv_lora_rank + n_embd_head_qk_rope});
-                        layer.wkv_b = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_KV_B, "weight", i), {kv_lora_rank, hparams.n_head() * (n_embd_head_qk_nope + hparams.n_embd_head_v)});
-                        layer.wo    = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT,  "weight", i), {              hparams.n_head() * (                      hparams.n_embd_head_v), n_embd});
+
+                        layer.wkv_a_mqa = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_KV_A_MQA, "weight", i), {n_embd, kv_lora_rank + (n_embd_head_qk_rope)});
+                        layer.wkv_b     = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_KV_B,     "weight", i), {kv_lora_rank, n_head * (n_embd_head_qk_nope + n_embd_head_v)});
+                        layer.wo        = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT,      "weight", i), {              n_head * (                      n_embd_head_v), n_embd});
 
                         layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
 
-                        if ((uint32_t) i < hparams.n_layer_dense_lead) {
+                        if (i < hparams.n_layer_dense_lead) {
                             layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd,   n_ff});
                             layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {  n_ff, n_embd});
                             layer.ffn_up   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd,   n_ff});
                         } else {
                             layer.ffn_gate_inp = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_GATE_INP, "weight", i), {n_embd, n_expert});
 
-                            GGML_ASSERT(hparams.n_expert      > 0);
-                            GGML_ASSERT(hparams.n_expert_used > 0);
+                            GGML_ASSERT(n_expert      > 0);
+                            GGML_ASSERT(n_expert_used > 0);
 
                             // MoE branch
                             layer.ffn_gate_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_EXPS, "weight", i), {  n_embd, n_ff_exp, n_expert});
@@ -7263,9 +7277,9 @@ static bool llm_load_tensors(
                             layer.ffn_up_exps   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP_EXPS,   "weight", i), {  n_embd, n_ff_exp, n_expert});
 
                             // Shared expert branch
-                            layer.ffn_gate_shexp = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_SHEXP, "weight", i), {n_embd,   n_ff_exp * hparams.n_expert_shared});
-                            layer.ffn_down_shexp = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN_SHEXP, "weight", i), {  n_ff_exp * hparams.n_expert_shared, n_embd});
-                            layer.ffn_up_shexp   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP_SHEXP,   "weight", i), {n_embd,   n_ff_exp * hparams.n_expert_shared});
+                            layer.ffn_gate_shexp = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_SHEXP, "weight", i), {n_embd, n_ff_exp * n_expert_shared});
+                            layer.ffn_down_shexp = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN_SHEXP, "weight", i), {        n_ff_exp * n_expert_shared, n_embd});
+                            layer.ffn_up_shexp   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP_SHEXP,   "weight", i), {n_embd, n_ff_exp * n_expert_shared});
                         }
                     }
                 } break;
@@ -7284,31 +7298,33 @@ static bool llm_load_tensors(
 
                         auto & layer = model.layers[i];
 
-                        layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
+                        layer.attn_norm     = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM,     "weight", i), {n_embd});
                         layer.attn_sub_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_SUB_NORM, "weight", i), {n_embd});
 
-                        layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q, "weight", i), {n_embd, n_embd});
-                        layer.wq_scale = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q, "scale", i), {1});
-                        layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K, "weight", i), {n_embd, n_embd_gqa});
-                        layer.wk_scale = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K, "scale", i), {1});
-                        layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V, "weight", i), {n_embd, n_embd_gqa});
-                        layer.wv_scale = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_V, "scale", i), {1});
-                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
-                        layer.wo_scale = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT, "scale", i), {1});
+                        layer.wq       = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd});
+                        layer.wq_scale = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q,   "scale",  i), {1});
+                        layer.wk       = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K,   "weight", i), {n_embd, n_embd_gqa});
+                        layer.wk_scale = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K,   "scale",  i), {1});
+                        layer.wv       = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V,   "weight", i), {n_embd, n_embd_gqa});
+                        layer.wv_scale = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_V,   "scale",  i), {1});
+                        layer.wo       = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
+                        layer.wo_scale = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT, "scale",  i), {1});
 
-                        layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
+                        layer.ffn_norm     = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM,     "weight", i), {n_embd});
                         layer.ffn_sub_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_SUB_NORM, "weight", i), {n_ff});
 
-                        layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff});
-                        layer.ffn_gate_scale = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_GATE, "scale", i), {1});
-                        layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd});
-                        layer.ffn_down_scale = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_DOWN, "scale", i), {1});
-                        layer.ffn_up   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd, n_ff});
-                        layer.ffn_up_scale = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP, "scale", i), {1});
+                        layer.ffn_gate       = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff});
+                        layer.ffn_gate_scale = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_GATE, "scale",  i), {1});
+                        layer.ffn_down       = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd});
+                        layer.ffn_down_scale = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_DOWN, "scale",  i), {1});
+                        layer.ffn_up         = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd, n_ff});
+                        layer.ffn_up_scale   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP,   "scale",  i), {1});
                     }
                 } break;
             case LLM_ARCH_T5:
                 {
+                    const auto n_rel_attn_bkts = hparams.n_rel_attn_bkts;
+
                     model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
 
                     // output
@@ -7330,7 +7346,7 @@ static bool llm_load_tensors(
                         auto & layer = model.layers[i];
 
                         layer.attn_norm_enc  = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ENC_ATTN_NORM,  "weight", i), {n_embd});
-                        layer.attn_rel_b_enc = ml.create_tensor(ctx_input, tn(LLM_TENSOR_ENC_ATTN_REL_B, "weight", i), {hparams.n_head(), hparams.n_rel_attn_bkts}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_rel_b_enc = ml.create_tensor(ctx_input, tn(LLM_TENSOR_ENC_ATTN_REL_B, "weight", i), {n_head, n_rel_attn_bkts}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         layer.wq_enc = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ENC_ATTN_Q,   "weight", i), {n_embd, n_embd_k_gqa});
                         layer.wk_enc = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ENC_ATTN_K,   "weight", i), {n_embd, n_embd_k_gqa});
@@ -7343,7 +7359,7 @@ static bool llm_load_tensors(
                         layer.ffn_up_enc   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ENC_FFN_UP,   "weight", i), {n_embd,   n_ff});
 
                         layer.attn_norm  = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_DEC_ATTN_NORM,  "weight", i), {n_embd});
-                        layer.attn_rel_b = ml.create_tensor(ctx_input, tn(LLM_TENSOR_DEC_ATTN_REL_B, "weight", i), {hparams.n_head(), hparams.n_rel_attn_bkts}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_rel_b = ml.create_tensor(ctx_input, tn(LLM_TENSOR_DEC_ATTN_REL_B, "weight", i), {n_head, n_rel_attn_bkts}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_ATTN_Q,   "weight", i), {n_embd, n_embd_k_gqa});
                         layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_ATTN_K,   "weight", i), {n_embd, n_embd_k_gqa});
@@ -7352,7 +7368,7 @@ static bool llm_load_tensors(
 
                         layer.attn_norm_cross  = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_DEC_CROSS_ATTN_NORM,  "weight", i), {n_embd});
                         // this tensor seems to be unused in HF transformers implementation
-                        layer.attn_rel_b_cross = ml.create_tensor(ctx_input, tn(LLM_TENSOR_DEC_CROSS_ATTN_REL_B, "weight", i), {hparams.n_head(), hparams.n_rel_attn_bkts}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_rel_b_cross = ml.create_tensor(ctx_input, tn(LLM_TENSOR_DEC_CROSS_ATTN_REL_B, "weight", i), {n_head, n_rel_attn_bkts}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         layer.wq_cross = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_CROSS_ATTN_Q,   "weight", i), {n_embd, n_embd_k_gqa});
                         layer.wk_cross = ml.create_tensor(ctx_split, tn(LLM_TENSOR_DEC_CROSS_ATTN_K,   "weight", i), {n_embd, n_embd_k_gqa});
@@ -7375,6 +7391,7 @@ static bool llm_load_tensors(
                         model.output_norm_b = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "bias"),   {n_embd});
                         model.output        = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab});
                     }
+
                     for (int i = 0; i < n_layer; ++i) {
                         ggml_context * ctx_layer = ctx_for_layer(i);
                         ggml_context * ctx_split = ctx_for_layer_split(i);
@@ -7387,8 +7404,8 @@ static bool llm_load_tensors(
                         layer.wqkv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_embd + 2*n_embd_gqa});
                         layer.bqkv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_QKV, "bias", i),   {n_embd + 2*n_embd_gqa});
 
-                        layer.wo   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
-                        layer.bo   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT, "bias", i),   {n_embd});
+                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
+                        layer.bo = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT, "bias", i),   {n_embd});
 
                         layer.ffn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
                         layer.ffn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "bias", i),   {n_embd});
@@ -7396,8 +7413,8 @@ static bool llm_load_tensors(
                         layer.ffn_down   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd});
                         layer.ffn_down_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_DOWN, "bias", i),   {n_embd});
 
-                        layer.ffn_gate     = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE,   "weight", i), {n_embd, n_ff});
-                        layer.ffn_gate_b   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_GATE,   "bias", i),   {n_ff});
+                        layer.ffn_gate   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE,   "weight", i), {n_embd, n_ff});
+                        layer.ffn_gate_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_GATE,   "bias", i),   {n_ff});
 
                         layer.ffn_up     = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd, n_ff});
                         layer.ffn_up_b   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP,   "bias", i),   {n_ff});

From 148ec970b62c3c5ae0a8bfdaad2fc237aaae350d Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Fri, 5 Jul 2024 10:15:36 +0300
Subject: [PATCH 110/326] convert : remove AWQ remnants (#8320)

---
 convert_hf_to_gguf.py | 19 +------------------
 1 file changed, 1 insertion(+), 18 deletions(-)

diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py
index ed54905932044..455eea883b93b 100755
--- a/convert_hf_to_gguf.py
+++ b/convert_hf_to_gguf.py
@@ -2445,7 +2445,7 @@ def set_gguf_parameters(self):
             raise ValueError("query_pre_attn_scalar must be equal to n_embd / n_head")
 
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
-        del bid  # unusem
+        del bid  # unused
 
         # lm_head is not used in llama.cpp, while autoawq will include this tensor in model
         # To prevent errors, skip loading lm_head.weight.
@@ -3225,10 +3225,6 @@ def parse_args() -> argparse.Namespace:
         "--vocab-only", action="store_true",
         help="extract only the vocab",
     )
-    parser.add_argument(
-        "--awq-path", type=Path, default=None,
-        help="Path to scale awq cache file",
-    )
     parser.add_argument(
         "--outfile", type=Path,
         help="path to write to; default: based on input. {ftype} will be replaced by the outtype.",
@@ -3306,19 +3302,6 @@ def main() -> None:
 
     dir_model = args.model
 
-    if args.awq_path:
-        sys.path.insert(1, str(Path(__file__).parent / 'awq-py'))
-        from awq.apply_awq import add_scale_weights  # type: ignore[import-not-found]
-        tmp_model_path = args.model / "weighted_model"
-        dir_model = tmp_model_path
-        if tmp_model_path.is_dir():
-            logger.info(f"{tmp_model_path} exists as a weighted model.")
-        else:
-            tmp_model_path.mkdir(parents=True, exist_ok=True)
-            logger.info("Saving new weighted model ...")
-            add_scale_weights(str(args.model), str(args.awq_path), str(tmp_model_path))
-            logger.info(f"Saved weighted model at {tmp_model_path}.")
-
     if not dir_model.is_dir():
         logger.error(f'Error: {args.model} is not a directory')
         sys.exit(1)

From 1f3e1b66e21310ed78b964f72f19766549633f0e Mon Sep 17 00:00:00 2001
From: Ouadie EL FAROUKI 
Date: Fri, 5 Jul 2024 13:23:25 +0100
Subject: [PATCH 111/326] Enabled more data types for oneMKL gemm_batch (#8236)

---
 ggml/src/ggml-sycl.cpp             | 30 ------------------------------
 ggml/src/ggml-sycl/dpct/helper.hpp |  4 ++--
 2 files changed, 2 insertions(+), 32 deletions(-)

diff --git a/ggml/src/ggml-sycl.cpp b/ggml/src/ggml-sycl.cpp
index 053cc950a8a39..21006cd7bebf7 100644
--- a/ggml/src/ggml-sycl.cpp
+++ b/ggml/src/ggml-sycl.cpp
@@ -3493,10 +3493,6 @@ static void ggml_sycl_mul_mat_batched_sycl(ggml_backend_sycl_context & ctx,
     SYCL_CHECK(ggml_sycl_set_device(ctx.device));
     queue_ptr main_stream = ctx.stream();;
 
-    bool no_mixed_dtypes = main_stream->get_backend() == sycl::backend::ext_oneapi_cuda ||
-                           main_stream->get_backend() == sycl::backend::ext_oneapi_hip;
-
-
     void * src0_ddq = src0->data;
     sycl::half *src0_as_f16 = (sycl::half *)src0_ddq;
     float * src1_ddf = (float *) src1->data;
@@ -3514,15 +3510,10 @@ static void ggml_sycl_mul_mat_batched_sycl(ggml_backend_sycl_context & ctx,
     sycl::half *src1_f16 = src1->type == GGML_TYPE_F16 ? (sycl::half *)src1_ddf
                                                        : src1_f16_alloc.get();
 
-    ggml_sycl_pool_alloc dst_f16(ctx.pool());
     char * dst_t;
 
     dpct::library_data_t cu_compute_type = dpct::library_data_t::real_float;
     dpct::library_data_t cu_data_type = dpct::library_data_t::real_float;
-    if (no_mixed_dtypes) {
-        cu_compute_type = dpct::library_data_t::real_half;
-        cu_data_type = dpct::library_data_t::real_half;
-    }
 
     // dst strides
     size_t nbd2 = dst->nb[2];
@@ -3531,26 +3522,10 @@ static void ggml_sycl_mul_mat_batched_sycl(ggml_backend_sycl_context & ctx,
     const float alpha_f32 = 1.0f;
     const float beta_f32 = 0.0f;
 
-    const sycl::half alpha_f16 = 1.0f;
-    const sycl::half beta_f16 = 0.0f;
-
     const void * alpha = &alpha_f32;
     const void * beta  = &beta_f32;
-    if (no_mixed_dtypes) {
-        alpha = &alpha_f16;
-        beta  = &beta_f16;
-    }
-
-    // TODO: Renable (dst->op_params[0] =! GGML_PREC_DEFAULT) pathway
-    // when oneMKL open source supports half, half, float, float: datatypes
 
     dst_t = (char *) dst_ddf;
-    if (no_mixed_dtypes) {
-        dst_t = (char *) dst_f16.alloc(ne_dst);
-
-        nbd2 /= sizeof(float) / sizeof(sycl::half);
-        nbd3 /= sizeof(float) / sizeof(sycl::half);
-    }
 
     GGML_ASSERT(ne12 % ne02 == 0);
     GGML_ASSERT(ne13 % ne03 == 0);
@@ -3612,11 +3587,6 @@ static void ggml_sycl_mul_mat_batched_sycl(ggml_backend_sycl_context & ctx,
             (void **)(ptrs_dst.get() + 0 * ne23), cu_data_type, ne01, ne23,
             cu_compute_type)));
     }
-
-    if (no_mixed_dtypes) {
-        const to_fp32_sycl_t to_fp32_sycl = ggml_get_to_fp32_sycl(GGML_TYPE_F16);
-        to_fp32_sycl(dst_f16.get(), dst_ddf, ne_dst, main_stream);
-    }
 }
 catch (sycl::exception const &exc) {
   std::cerr << exc.what() << "Exception caught at file:" << __FILE__
diff --git a/ggml/src/ggml-sycl/dpct/helper.hpp b/ggml/src/ggml-sycl/dpct/helper.hpp
index 5e98660dc888d..31df1cb9e2cf4 100644
--- a/ggml/src/ggml-sycl/dpct/helper.hpp
+++ b/ggml/src/ggml-sycl/dpct/helper.hpp
@@ -2426,6 +2426,7 @@ namespace dpct
                                            b, ldb, beta, c, ldc, batch_size);
             break;
         }
+#endif
         case detail::get_type_combination_id(
             library_data_t::real_int8, library_data_t::real_int8,
             library_data_t::real_int32, library_data_t::real_int32):
@@ -2458,7 +2459,6 @@ namespace dpct
                 batch_size);
             break;
         }
-#endif
         case detail::get_type_combination_id(
             library_data_t::real_half, library_data_t::real_half,
             library_data_t::real_half, library_data_t::real_float):
@@ -2595,6 +2595,7 @@ namespace dpct
                                            stride_c, batch_size);
             break;
         }
+#endif
         case detail::get_type_combination_id(
             library_data_t::real_int8, library_data_t::real_int8,
             library_data_t::real_int32, library_data_t::real_int32):
@@ -2623,7 +2624,6 @@ namespace dpct
                 beta, c, ldc, stride_c, batch_size);
             break;
         }
-#endif
         case detail::get_type_combination_id(
             library_data_t::real_half, library_data_t::real_half,
             library_data_t::real_half, library_data_t::real_float):

From 1d894a790e62b10d066adcdd9c9feb559455b7d2 Mon Sep 17 00:00:00 2001
From: Natsu 
Date: Fri, 5 Jul 2024 22:29:35 +0800
Subject: [PATCH 112/326] cmake : add GGML_BUILD and GGML_SHARED macro
 definitions (#8281)

---
 ggml/src/CMakeLists.txt | 1 +
 1 file changed, 1 insertion(+)

diff --git a/ggml/src/CMakeLists.txt b/ggml/src/CMakeLists.txt
index 8d96a04b57beb..c6694df678fff 100644
--- a/ggml/src/CMakeLists.txt
+++ b/ggml/src/CMakeLists.txt
@@ -1175,4 +1175,5 @@ endif()
 
 if (BUILD_SHARED_LIBS)
     set_target_properties(ggml PROPERTIES POSITION_INDEPENDENT_CODE ON)
+    target_compile_definitions(ggml PRIVATE GGML_SHARED GGML_BUILD)
 endif()

From 7ed03b8974269b6c48e55c4245d12fb3264a6cf5 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Fri, 5 Jul 2024 17:32:09 +0300
Subject: [PATCH 113/326] llama : fix compile warning (#8304)

---
 src/llama.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/llama.cpp b/src/llama.cpp
index 95184c1083a1c..18956d441409f 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -7261,7 +7261,7 @@ static bool llm_load_tensors(
 
                         layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
 
-                        if (i < hparams.n_layer_dense_lead) {
+                        if (i < (int) hparams.n_layer_dense_lead) {
                             layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd,   n_ff});
                             layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {  n_ff, n_embd});
                             layer.ffn_up   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd,   n_ff});

From be20e7f49d9e5c6d9e8d9b4871eeba3df7a1639d Mon Sep 17 00:00:00 2001
From: Xuan Son Nguyen 
Date: Fri, 5 Jul 2024 18:08:32 +0200
Subject: [PATCH 114/326] Reorganize documentation pages (#8325)

* re-organize docs

* add link among docs

* add link to build docs

* fix style

* de-duplicate sections
---
 .gitignore                                    |   1 +
 README.md                                     | 668 ++----------------
 docs/android.md                               |  56 ++
 docs/{ => backend}/BLIS.md                    |   0
 README-sycl.md => docs/backend/SYCL.md        |   0
 docs/build.md                                 | 288 ++++++++
 docs/{ => development}/HOWTO-add-model.md     |   2 +-
 docs/{ => development}/debugging-tests.md     |   0
 .../llama-star/idea-arch.key                  | Bin
 .../llama-star/idea-arch.pdf                  | Bin
 .../token_generation_performance_tips.md      |   0
 docs/docker.md                                |  86 +++
 docs/install.md                               |  39 +
 examples/quantize/README.md                   |  89 ++-
 14 files changed, 626 insertions(+), 603 deletions(-)
 create mode 100644 docs/android.md
 rename docs/{ => backend}/BLIS.md (100%)
 rename README-sycl.md => docs/backend/SYCL.md (100%)
 create mode 100644 docs/build.md
 rename docs/{ => development}/HOWTO-add-model.md (99%)
 rename docs/{ => development}/debugging-tests.md (100%)
 rename docs/{ => development}/llama-star/idea-arch.key (100%)
 rename docs/{ => development}/llama-star/idea-arch.pdf (100%)
 rename docs/{ => development}/token_generation_performance_tips.md (100%)
 create mode 100644 docs/docker.md
 create mode 100644 docs/install.md

diff --git a/.gitignore b/.gitignore
index 6125e350c09d7..4866f612277f7 100644
--- a/.gitignore
+++ b/.gitignore
@@ -47,6 +47,7 @@ build*
 !build-info.cpp.in
 !build-info.sh
 !build.zig
+!docs/build.md
 /libllama.so
 /llama-*
 android-ndk-*
diff --git a/README.md b/README.md
index 875fed4371dba..a4bbf00bdae94 100644
--- a/README.md
+++ b/README.md
@@ -13,7 +13,7 @@ Inference of Meta's [LLaMA](https://arxiv.org/abs/2302.13971) model (and others)
 > [!IMPORTANT]
 [2024 Jun 12] Binaries have been renamed w/ a `llama-` prefix. `main` is now `llama-cli`, `server` is `llama-server`, etc (https://github.com/ggerganov/llama.cpp/pull/7809)
 
-### Recent API changes
+## Recent API changes
 
 - [2024 Jun 26] The source code and CMake build scripts have been restructured https://github.com/ggerganov/llama.cpp/pull/8006
 - [2024 Apr 21] `llama_token_to_piece` can now optionally render special tokens https://github.com/ggerganov/llama.cpp/pull/6807
@@ -24,7 +24,7 @@ Inference of Meta's [LLaMA](https://arxiv.org/abs/2302.13971) model (and others)
 - [2024 Mar 4] Embeddings API updated https://github.com/ggerganov/llama.cpp/pull/5796
 - [2024 Mar 3] `struct llama_context_params` https://github.com/ggerganov/llama.cpp/pull/5849
 
-### Hot topics
+## Hot topics
 
 - **`convert.py` has been deprecated and moved to `examples/convert_legacy_llama.py`, please use `convert_hf_to_gguf.py`** https://github.com/ggerganov/llama.cpp/pull/7430
 - Initial Flash-Attention support: https://github.com/ggerganov/llama.cpp/pull/5021
@@ -39,37 +39,6 @@ Inference of Meta's [LLaMA](https://arxiv.org/abs/2302.13971) model (and others)
 
 ----
 
-

-  Table of Contents
-  
    
-    
  1. 
-      Description
-    
    2. 
-    
  2. 
-      Usage
-      
-    
    3. 
-    
  3. Contributing
    4. 
-    
  4. Coding guidelines
    5. 
-    
  5. Docs
    6. 
-  

-

-
 ## Description
 
 The main goal of `llama.cpp` is to enable LLM inference with minimal setup and state-of-the-art performance on a wide
@@ -87,14 +56,6 @@ Since its [inception](https://github.com/ggerganov/llama.cpp/issues/33#issuecomm
 improved significantly thanks to many contributions. It is the main playground for developing new features for the
 [ggml](https://github.com/ggerganov/ggml) library.
 
-**Supported platforms:**
-
-- [X] Mac OS
-- [X] Linux
-- [X] Windows (via CMake)
-- [X] Docker
-- [X] FreeBSD
-
 **Supported models:**
 
 Typically finetunes of the base models below are supported as well.
@@ -150,12 +111,6 @@ Typically finetunes of the base models below are supported as well.
 - [x] [Moondream](https://huggingface.co/vikhyatk/moondream2)
 - [x] [Bunny](https://github.com/BAAI-DCAI/Bunny)
 
-**HTTP server**
-
-[llama.cpp web server](./examples/server) is a lightweight [OpenAI API](https://github.com/openai/openai-openapi) compatible HTTP server that can be used to serve local models and easily connect them to existing clients.
-
-[simplechat](./examples/server/public_simplechat) is a simple chat client, which can be used to chat with the model exposed using above web server (use --path to point to simplechat), from a local web browser.
-
 **Bindings:**
 
 - Python: [abetlen/llama-cpp-python](https://github.com/abetlen/llama-cpp-python)
@@ -224,9 +179,10 @@ Unless otherwise noted these projects are open-source with permissive licensing:
 
 - [Paddler](https://github.com/distantmagic/paddler) - Stateful load balancer custom-tailored for llama.cpp
 
----
+## Demo
 
-Here is a typical run using LLaMA v2 13B on M2 Ultra:
+

+Typical run using LLaMA v2 13B on M2 Ultra
 
 ```
 $ make -j && ./llama-cli -m models/llama-13b-v2/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e
@@ -306,454 +262,85 @@ llama_print_timings:        eval time = 24513.59 ms /   399 runs   (   61.44 ms
 llama_print_timings:       total time = 25431.49 ms
 ```
 
+

+
+

+Demo of running both LLaMA-7B and whisper.cpp on a single M1 Pro MacBook
+
 And here is another demo of running both LLaMA-7B and [whisper.cpp](https://github.com/ggerganov/whisper.cpp) on a single M1 Pro MacBook:
 
 https://user-images.githubusercontent.com/1991296/224442907-7693d4be-acaa-4e01-8b4f-add84093ffff.mp4
 
+

+
 ## Usage
 
 Here are the end-to-end binary build and model conversion steps for most supported models.
 
-### Get the Code
-
-```bash
-git clone https://github.com/ggerganov/llama.cpp
-cd llama.cpp
-```
-
-### Build
-
-In order to build llama.cpp you have four different options.
-
-- Using `make`:
-  - On Linux or MacOS:
-
-      ```bash
-      make
-      ```
+### Basic usage
 
-  - On Windows:
+Firstly, you need to get the binary. There are different methods that you can follow:
+- Method 1: Clone this repository and build locally, see [how to build](./docs/build.md)
+- Method 2: If you are using MacOS or Linux, you can install llama.cpp via [brew, flox or nix](./docs/install.md)
+- Method 3: Use a Docker image, see [documentation for Docker](./docs/docker.md)
+- Method 4: Download pre-built binary from [releases](https://github.com/ggerganov/llama.cpp/releases)
 
-    1. Download the latest fortran version of [w64devkit](https://github.com/skeeto/w64devkit/releases).
-    2. Extract `w64devkit` on your pc.
-    3. Run `w64devkit.exe`.
-    4. Use the `cd` command to reach the `llama.cpp` folder.
-    5. From here you can run:
-        ```bash
-        make
-        ```
+You can run a basic completion using this command:
 
-  - Notes:
-    - For faster compilation, add the `-j` argument to run multiple jobs in parallel. For example, `make -j 8` will run 8 jobs in parallel.
-    - For faster repeated compilation, install [ccache](https://ccache.dev/).
-    - For debug builds, run `make LLAMA_DEBUG=1`
-
-- Using `CMake`:
-
-  ```bash
-  cmake -B build
-  cmake --build build --config Release
-  ```
-
-  **Notes**:
-
-    - For faster compilation, add the `-j` argument to run multiple jobs in parallel. For example, `cmake --build build --config Release -j 8` will run 8 jobs in parallel.
-    - For faster repeated compilation, install [ccache](https://ccache.dev/).
-    - For debug builds, there are two cases:
-
-      1. Single-config generators (e.g. default = `Unix Makefiles`; note that they just ignore the `--config` flag):
-
-      ```bash
-      cmake -B build -DCMAKE_BUILD_TYPE=Debug
-      cmake --build build
-      ```
-
-      2. Multi-config generators (`-G` param set to Visual Studio, XCode...):
-
-      ```bash
-      cmake -B build -G "Xcode"
-      cmake --build build --config Debug
-      ```
-
--   Using `gmake` (FreeBSD):
-
-    1. Install and activate [DRM in FreeBSD](https://wiki.freebsd.org/Graphics)
-    2. Add your user to **video** group
-    3. Install compilation dependencies.
-
-        ```bash
-        sudo pkg install gmake automake autoconf pkgconf llvm15 openblas
-
-        gmake CC=/usr/local/bin/clang15 CXX=/usr/local/bin/clang++15 -j4
-        ```
-
-### Homebrew
+```bash
+llama-cli -m your_model.gguf -p "I believe the meaning of life is" -n 128
 
-On Mac and Linux, the homebrew package manager can be used via
+# Output:
+# I believe the meaning of life is to find your own truth and to live in accordance with it. For me, this means being true to myself and following my passions, even if they don't align with societal expectations. I think that's what I love about yoga – it's not just a physical practice, but a spiritual one too. It's about connecting with yourself, listening to your inner voice, and honoring your own unique journey.
 ```
-brew install llama.cpp
-```
-The formula is automatically updated with new `llama.cpp` releases. More info: https://github.com/ggerganov/llama.cpp/discussions/7668
-
-### Nix
 
-On Mac and Linux, the Nix package manager can be used via
-```
-nix profile install nixpkgs#llama-cpp
-```
-For flake enabled installs.
+See [this page](./examples/main/README.md) for a full list of parameters.
 
-Or
-```
-nix-env --file '' --install --attr llama-cpp
-```
-For non-flake enabled installs.
+### Conversation mode
 
-This expression is automatically updated within the [nixpkgs repo](https://github.com/NixOS/nixpkgs/blob/nixos-24.05/pkgs/by-name/ll/llama-cpp/package.nix#L164).
+If you want a more ChatGPT-like experience, you can run in conversation mode by passing `-cnv` as a parameter:
 
-#### Flox
+```bash
+llama-cli -m your_model.gguf -p "You are a helpful assistant" -cnv
 
-On Mac and Linux, Flox can be used to install llama.cpp within a Flox environment via
+# Output:
+# > hi, who are you?
+# Hi there! I'm your helpful assistant! I'm an AI-powered chatbot designed to assist and provide information to users like you. I'm here to help answer your questions, provide guidance, and offer support on a wide range of topics. I'm a friendly and knowledgeable AI, and I'm always happy to help with anything you need. What's on your mind, and how can I assist you today?
+#
+# > what is 1+1?
+# Easy peasy! The answer to 1+1 is... 2!
 ```
-flox install llama-cpp
-```
-Flox follows the nixpkgs build of llama.cpp.
-
-### Metal Build
-
-On MacOS, Metal is enabled by default. Using Metal makes the computation run on the GPU.
-To disable the Metal build at compile time use the `GGML_NO_METAL=1` flag or the `GGML_METAL=OFF` cmake option.
-
-When built with Metal support, you can explicitly disable GPU inference with the `--n-gpu-layers|-ngl 0` command-line
-argument.
-
-### BLAS Build
-
-Building the program with BLAS support may lead to some performance improvements in prompt processing using batch sizes higher than 32 (the default is 512). Support with CPU-only BLAS implementations doesn't affect the normal generation performance. We may see generation performance improvements with GPU-involved BLAS implementations, e.g. cuBLAS, hipBLAS. There are currently several different BLAS implementations available for build and use:
-
-- #### Accelerate Framework:
-
-  This is only available on Mac PCs and it's enabled by default. You can just build using the normal instructions.
-
-- #### OpenBLAS:
-
-  This provides BLAS acceleration using only the CPU. Make sure to have OpenBLAS installed on your machine.
-
-  - Using `make`:
-    - On Linux:
-      ```bash
-      make GGML_OPENBLAS=1
-      ```
-
-    - On Windows:
-
-      1. Download the latest fortran version of [w64devkit](https://github.com/skeeto/w64devkit/releases).
-      2. Download the latest version of [OpenBLAS for Windows](https://github.com/xianyi/OpenBLAS/releases).
-      3. Extract `w64devkit` on your pc.
-      4. From the OpenBLAS zip that you just downloaded copy `libopenblas.a`, located inside the `lib` folder, inside `w64devkit\x86_64-w64-mingw32\lib`.
-      5. From the same OpenBLAS zip copy the content of the `include` folder inside `w64devkit\x86_64-w64-mingw32\include`.
-      6. Run `w64devkit.exe`.
-      7. Use the `cd` command to reach the `llama.cpp` folder.
-      8. From here you can run:
-
-          ```bash
-          make GGML_OPENBLAS=1
-          ```
-
-  - Using `CMake` on Linux:
-
-      ```bash
-      cmake -B build -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
-      cmake --build build --config Release
-      ```
-
-- #### BLIS
-
-  Check [BLIS.md](docs/BLIS.md) for more information.
-
-- #### SYCL
-  SYCL is a higher-level programming model to improve programming productivity on various hardware accelerators.
-
-  llama.cpp based on SYCL is used to **support Intel GPU** (Data Center Max series, Flex series, Arc series, Built-in GPU and iGPU).
-
-  For detailed info, please refer to [llama.cpp for SYCL](README-sycl.md).
-
-- #### Intel oneMKL
-  Building through oneAPI compilers will make avx_vnni instruction set available for intel processors that do not support avx512 and avx512_vnni. Please note that this build config **does not support Intel GPU**. For Intel GPU support, please refer to [llama.cpp for SYCL](./README-sycl.md).
-
-  - Using manual oneAPI installation:
-    By default, `GGML_BLAS_VENDOR` is set to `Generic`, so if you already sourced intel environment script and assign `-DGGML_BLAS=ON` in cmake, the mkl version of Blas will automatically been selected. Otherwise please install oneAPI and follow the below steps:
-      ```bash
-      source /opt/intel/oneapi/setvars.sh # You can skip this step if  in oneapi-basekit docker image, only required for manual installation
-      cmake -B build -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=Intel10_64lp -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_NATIVE=ON
-      cmake --build build --config Release
-      ```
-
-  - Using oneAPI docker image:
-    If you do not want to source the environment vars and install oneAPI manually, you can also build the code using intel docker container: [oneAPI-basekit](https://hub.docker.com/r/intel/oneapi-basekit). Then, you can use the commands given above.
-
-  Check [Optimizing and Running LLaMA2 on Intel® CPU](https://www.intel.com/content/www/us/en/content-details/791610/optimizing-and-running-llama2-on-intel-cpu.html) for more information.
 
-- #### CUDA
-
-  This provides GPU acceleration using the CUDA cores of your Nvidia GPU. Make sure to have the CUDA toolkit installed. You can download it from your Linux distro's package manager (e.g. `apt install nvidia-cuda-toolkit`) or from here: [CUDA Toolkit](https://developer.nvidia.com/cuda-downloads).
-
-  For Jetson user, if you have Jetson Orin, you can try this: [Offical Support](https://www.jetson-ai-lab.com/tutorial_text-generation.html). If you are using an old model(nano/TX2), need some additional operations before compiling.
-
-  - Using `make`:
-    ```bash
-    make GGML_CUDA=1
-    ```
-  - Using `CMake`:
-
-    ```bash
-    cmake -B build -DGGML_CUDA=ON
-    cmake --build build --config Release
-    ```
-
-  The environment variable [`CUDA_VISIBLE_DEVICES`](https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#env-vars) can be used to specify which GPU(s) will be used. The following compilation options are also available to tweak performance:
-
-  | Option                        | Legal values           | Default | Description                                                                                                                                                                                                                                                                             |
-  |-------------------------------|------------------------|---------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-  | GGML_CUDA_FORCE_DMMV          | Boolean                | false   | Force the use of dequantization + matrix vector multiplication kernels instead of using kernels that do matrix vector multiplication on quantized data. By default the decision is made based on compute capability (MMVQ for 6.1/Pascal/GTX 1000 or higher). Does not affect k-quants. |
-  | GGML_CUDA_DMMV_X              | Positive integer >= 32 | 32      | Number of values in x direction processed by the CUDA dequantization + matrix vector multiplication kernel per iteration. Increasing this value can improve performance on fast GPUs. Power of 2 heavily recommended. Does not affect k-quants.                                         |
-  | GGML_CUDA_MMV_Y               | Positive integer       | 1       | Block size in y direction for the CUDA mul mat vec kernels. Increasing this value can improve performance on fast GPUs. Power of 2 recommended.                                                                                                                                         |
-  | GGML_CUDA_FORCE_MMQ           | Boolean                | false   | Force the use of custom matrix multiplication kernels for quantized models instead of FP16 cuBLAS even if there is no int8 tensor core implementation available (affects V100, RDNA3). MMQ kernels are enabled by default on GPUs with int8 tensor core support. With MMQ force enabled, speed for large batch sizes will be worse but VRAM consumption will be lower.                       |
-  | GGML_CUDA_FORCE_CUBLAS        | Boolean                | false   | Force the use of FP16 cuBLAS instead of custom matrix multiplication kernels for quantized models                                                                                                                                                                                       |
-  | GGML_CUDA_F16                 | Boolean                | false   | If enabled, use half-precision floating point arithmetic for the CUDA dequantization + mul mat vec kernels and for the q4_1 and q5_1 matrix matrix multiplication kernels. Can improve performance on relatively recent GPUs.                                                           |
-  | GGML_CUDA_KQUANTS_ITER        | 1 or 2                 | 2       | Number of values processed per iteration and per CUDA thread for Q2_K and Q6_K quantization formats. Setting this value to 1 can improve performance for slow GPUs.                                                                                                                     |
-  | GGML_CUDA_PEER_MAX_BATCH_SIZE | Positive integer       | 128     | Maximum batch size for which to enable peer access between multiple GPUs. Peer access requires either Linux or NVLink. When using NVLink enabling peer access for larger batch sizes is potentially beneficial.                                                                         |
-  | GGML_CUDA_FA_ALL_QUANTS       | Boolean                | false   | Compile support for all KV cache quantization type (combinations) for the FlashAttention CUDA kernels. More fine-grained control over KV cache size but compilation takes much longer.                                                                                                  |
-
-- #### hipBLAS
-
-  This provides BLAS acceleration on HIP-supported AMD GPUs.
-  Make sure to have ROCm installed.
-  You can download it from your Linux distro's package manager or from here: [ROCm Quick Start (Linux)](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/tutorial/quick-start.html#rocm-install-quick).
-
-  - Using `make`:
-    ```bash
-    make GGML_HIPBLAS=1
-    ```
-  - Using `CMake` for Linux (assuming a gfx1030-compatible AMD GPU):
-    ```bash
-    HIPCXX="$(hipconfig -l)/clang" HIP_PATH="$(hipconfig -R)" \
-        cmake -S . -B build -DGGML_HIPBLAS=ON -DAMDGPU_TARGETS=gfx1030 -DCMAKE_BUILD_TYPE=Release \
-        && cmake --build build --config Release -- -j 16
-    ```
-    On Linux it is also possible to use unified memory architecture (UMA) to share main memory between the CPU and integrated GPU by setting `-DGGML_HIP_UMA=ON`.
-    However, this hurts performance for non-integrated GPUs (but enables working with integrated GPUs).
-
-    Note that if you get the following error:
-    ```
-    clang: error: cannot find ROCm device library; provide its path via '--rocm-path' or '--rocm-device-lib-path', or pass '-nogpulib' to build without ROCm device library
-    ```
-    Try searching for a directory under `HIP_PATH` that contains the file
-    `oclc_abi_version_400.bc`. Then, add the following to the start of the
-    command: `HIP_DEVICE_LIB_PATH=`, so something
-    like:
-    ```bash
-    HIPCXX="$(hipconfig -l)/clang" HIP_PATH="$(hipconfig -p)" \
-    HIP_DEVICE_LIB_PATH= \
-        cmake -S . -B build -DGGML_HIPBLAS=ON -DAMDGPU_TARGETS=gfx1030 -DCMAKE_BUILD_TYPE=Release \
-        && cmake --build build -- -j 16
-    ```
-
-  - Using `make` (example for target gfx1030, build with 16 CPU threads):
-    ```bash
-    make -j16 GGML_HIPBLAS=1 GGML_HIP_UMA=1 AMDGPU_TARGETS=gfx1030
-    ```
-
-  - Using `CMake` for Windows (using x64 Native Tools Command Prompt for VS, and assuming a gfx1100-compatible AMD GPU):
-    ```bash
-    set PATH=%HIP_PATH%\bin;%PATH%
-    cmake -S . -B build -G Ninja -DAMDGPU_TARGETS=gfx1100 -DGGML_HIPBLAS=ON -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_BUILD_TYPE=Release
-    cmake --build build
-    ```
-    Make sure that `AMDGPU_TARGETS` is set to the GPU arch you want to compile for. The above example uses `gfx1100` that corresponds to Radeon RX 7900XTX/XT/GRE. You can find a list of targets [here](https://llvm.org/docs/AMDGPUUsage.html#processors)
-    Find your gpu version string by matching the most significant version information from `rocminfo | grep gfx | head -1 | awk '{print $2}'` with the list of processors, e.g. `gfx1035` maps to `gfx1030`.
-
-
-  The environment variable [`HIP_VISIBLE_DEVICES`](https://rocm.docs.amd.com/en/latest/understand/gpu_isolation.html#hip-visible-devices) can be used to specify which GPU(s) will be used.
-  If your GPU is not officially supported you can use the environment variable [`HSA_OVERRIDE_GFX_VERSION`] set to a similar GPU, for example 10.3.0 on RDNA2 (e.g. gfx1030, gfx1031, or gfx1035) or 11.0.0 on RDNA3.
-  The following compilation options are also available to tweak performance (yes, they refer to CUDA, not HIP, because it uses the same code as the cuBLAS version above):
-
-  | Option                 | Legal values           | Default | Description                                                                                                                                                                                                                                    |
-  |------------------------|------------------------|---------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-  | GGML_CUDA_DMMV_X       | Positive integer >= 32 | 32      | Number of values in x direction processed by the HIP dequantization + matrix vector multiplication kernel per iteration. Increasing this value can improve performance on fast GPUs. Power of 2 heavily recommended. Does not affect k-quants. |
-  | GGML_CUDA_MMV_Y        | Positive integer       | 1       | Block size in y direction for the HIP mul mat vec kernels. Increasing this value can improve performance on fast GPUs. Power of 2 recommended. Does not affect k-quants.                                                                       |
-  | GGML_CUDA_KQUANTS_ITER | 1 or 2                 | 2       | Number of values processed per iteration and per HIP thread for Q2_K and Q6_K quantization formats. Setting this value to 1 can improve performance for slow GPUs.                                                                             |
-
-- #### Vulkan
-
-  **With docker**:
-
-  You don't need to install Vulkan SDK. It will be installed inside the container.
-
-  ```sh
-  # Build the image
-  docker build -t llama-cpp-vulkan -f .devops/llama-cli-vulkan.Dockerfile .
-
-  # Then, use it:
-  docker run -it --rm -v "$(pwd):/app:Z" --device /dev/dri/renderD128:/dev/dri/renderD128 --device /dev/dri/card1:/dev/dri/card1 llama-cpp-vulkan -m "/app/models/YOUR_MODEL_FILE" -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 33
-  ```
-
-  **Without docker**:
-
-  Firstly, you need to make sure you have installed [Vulkan SDK](https://vulkan.lunarg.com/doc/view/latest/linux/getting_started_ubuntu.html)
-
-  For example, on Ubuntu 22.04 (jammy), use the command below:
-
-  ```bash
-  wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add -
-  wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list
-  apt update -y
-  apt-get install -y vulkan-sdk
-  # To verify the installation, use the command below:
-  vulkaninfo
-  ```
-
-  Alternatively your package manager might be able to provide the appropriate libraries.
-  For example for Ubuntu 22.04 you can install `libvulkan-dev` instead.
-  For Fedora 40, you can install `vulkan-devel`, `glslc` and `glslang` packages.
-
-  Then, build llama.cpp using the cmake command below:
-
-  ```bash
-  cmake -B build -DGGML_VULKAN=1
-  cmake --build build --config Release
-  # Test the output binary (with "-ngl 33" to offload all layers to GPU)
-  ./bin/llama-cli -m "PATH_TO_MODEL" -p "Hi you how are you" -n 50 -e -ngl 33 -t 4
-
-  # You should see in the output, ggml_vulkan detected your GPU. For example:
-  # ggml_vulkan: Using Intel(R) Graphics (ADL GT2) | uma: 1 | fp16: 1 | warp size: 32
-  ```
-
-### Prepare and Quantize
-
-> [!NOTE]
-> You can use the [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space on Hugging Face to quantise your model weights without any setup too. It is synced from `llama.cpp` main every 6 hours.
-
-To obtain the official LLaMA 2 weights please see the Obtaining and using the Facebook LLaMA 2 model section. There is also a large selection of pre-quantized `gguf` models available on Hugging Face.
-
-Note: `convert.py` has been moved to `examples/convert_legacy_llama.py` and shouldn't be used for anything other than `Llama/Llama2/Mistral` models and their derivatives.
-It does not support LLaMA 3, you can use `convert_hf_to_gguf.py` with LLaMA 3 downloaded from Hugging Face.
+By default, the chat template will be taken from the input model. If you want to use another chat template, pass `--chat-template NAME` as a parameter. See the list of [supported templates](https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template)
 
 ```bash
-# obtain the official LLaMA model weights and place them in ./models
-ls ./models
-llama-2-7b tokenizer_checklist.chk tokenizer.model
-# [Optional] for models using BPE tokenizers
-ls ./models
- vocab.json
-# [Optional] for PyTorch .bin models like Mistral-7B
-ls ./models
-
-
-# install Python dependencies
-python3 -m pip install -r requirements.txt
-
-# convert the model to ggml FP16 format
-python3 convert_hf_to_gguf.py models/mymodel/
-
-# quantize the model to 4-bits (using Q4_K_M method)
-./llama-quantize ./models/mymodel/ggml-model-f16.gguf ./models/mymodel/ggml-model-Q4_K_M.gguf Q4_K_M
-
-# update the gguf filetype to current version if older version is now unsupported
-./llama-quantize ./models/mymodel/ggml-model-Q4_K_M.gguf ./models/mymodel/ggml-model-Q4_K_M-v2.gguf COPY
+./llama-cli -m your_model.gguf -p "You are a helpful assistant" -cnv --chat-template chatml
 ```
 
-### Run the quantized model
+You can also use your own template via in-prefix, in-suffix and reverse-prompt parameters:
 
 ```bash
-# start inference on a gguf model
-./llama-cli -m ./models/mymodel/ggml-model-Q4_K_M.gguf -n 128
+./llama-cli -m your_model.gguf -p "You are a helpful assistant" -cnv --in-prefix 'User: ' --reverse-prompt 'User:'
 ```
 
-When running the larger models, make sure you have enough disk space to store all the intermediate files.
-
-### Running on Windows with prebuilt binaries
-
-You will find prebuilt Windows binaries on the release page.
+### Web server
 
-Simply download and extract the latest zip package of choice: (e.g. `llama-b1380-bin-win-avx2-x64.zip`)
+[llama.cpp web server](./examples/server/README.md) is a lightweight [OpenAI API](https://github.com/openai/openai-openapi) compatible HTTP server that can be used to serve local models and easily connect them to existing clients.
 
-From the unzipped folder, open a terminal/cmd window here and place a pre-converted `.gguf` model file. Test out the main example like so:
+Example usage:
 
-```
-.\main -m llama-2-7b.Q4_0.gguf -n 128
-```
-
-### Memory/Disk Requirements
-
-As the models are currently fully loaded into memory, you will need adequate disk space to save them and sufficient RAM to load them. At the moment, memory and disk requirements are the same.
-
-| Model | Original size | Quantized size (Q4_0) |
-|------:|--------------:|----------------------:|
-|    7B |         13 GB |                3.9 GB |
-|   13B |         24 GB |                7.8 GB |
-|   30B |         60 GB |               19.5 GB |
-|   65B |        120 GB |               38.5 GB |
-
-### Quantization
-
-Several quantization methods are supported. They differ in the resulting model disk size and inference speed.
-
-*(outdated)*
-
-| Model | Measure      |    F16 |   Q4_0 |   Q4_1 |   Q5_0 |   Q5_1 |   Q8_0 |
-|------:|--------------|-------:|-------:|-------:|-------:|-------:|-------:|
-|    7B | perplexity   | 5.9066 | 6.1565 | 6.0912 | 5.9862 | 5.9481 | 5.9070 |
-|    7B | file size    |  13.0G |   3.5G |   3.9G |   4.3G |   4.7G |   6.7G |
-|    7B | ms/tok @ 4th |    127 |     55 |     54 |     76 |     83 |     72 |
-|    7B | ms/tok @ 8th |    122 |     43 |     45 |     52 |     56 |     67 |
-|    7B | bits/weight  |   16.0 |    4.5 |    5.0 |    5.5 |    6.0 |    8.5 |
-|   13B | perplexity   | 5.2543 | 5.3860 | 5.3608 | 5.2856 | 5.2706 | 5.2548 |
-|   13B | file size    |  25.0G |   6.8G |   7.6G |   8.3G |   9.1G |    13G |
-|   13B | ms/tok @ 4th |      - |    103 |    105 |    148 |    160 |    131 |
-|   13B | ms/tok @ 8th |      - |     73 |     82 |     98 |    105 |    128 |
-|   13B | bits/weight  |   16.0 |    4.5 |    5.0 |    5.5 |    6.0 |    8.5 |
-
-- [k-quants](https://github.com/ggerganov/llama.cpp/pull/1684)
-- recent k-quants improvements and new i-quants
-  - [#2707](https://github.com/ggerganov/llama.cpp/pull/2707)
-  - [#2807](https://github.com/ggerganov/llama.cpp/pull/2807)
-  - [#4773 - 2-bit i-quants (inference)](https://github.com/ggerganov/llama.cpp/pull/4773)
-  - [#4856 - 2-bit i-quants (inference)](https://github.com/ggerganov/llama.cpp/pull/4856)
-  - [#4861 - importance matrix](https://github.com/ggerganov/llama.cpp/pull/4861)
-  - [#4872 - MoE models](https://github.com/ggerganov/llama.cpp/pull/4872)
-  - [#4897 - 2-bit quantization](https://github.com/ggerganov/llama.cpp/pull/4897)
-  - [#4930 - imatrix for all k-quants](https://github.com/ggerganov/llama.cpp/pull/4930)
-  - [#4951 - imatrix on the GPU](https://github.com/ggerganov/llama.cpp/pull/4957)
-  - [#4969 - imatrix for legacy quants](https://github.com/ggerganov/llama.cpp/pull/4969)
-  - [#4996 - k-qunats tuning](https://github.com/ggerganov/llama.cpp/pull/4996)
-  - [#5060 - Q3_K_XS](https://github.com/ggerganov/llama.cpp/pull/5060)
-  - [#5196 - 3-bit i-quants](https://github.com/ggerganov/llama.cpp/pull/5196)
-  - [quantization tuning](https://github.com/ggerganov/llama.cpp/pull/5320), [another one](https://github.com/ggerganov/llama.cpp/pull/5334), and [another one](https://github.com/ggerganov/llama.cpp/pull/5361)
-
-### Perplexity (measuring model quality)
-
-You can use the `perplexity` example to measure perplexity over a given prompt (lower perplexity is better).
-For more information, see [https://huggingface.co/docs/transformers/perplexity](https://huggingface.co/docs/transformers/perplexity).
-
-The perplexity measurements in table above are done against the `wikitext2` test dataset (https://paperswithcode.com/dataset/wikitext-2), with context length of 512.
-The time per token is measured on a MacBook M1 Pro 32GB RAM using 4 and 8 threads.
-
-#### How to run
+```bash
+./llama-server -m your_model.gguf --port 8080
 
-1. Download/extract: https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
-2. Run `./llama-perplexity -m models/7B/ggml-model-q4_0.gguf -f wiki.test.raw`
-3. Output:
+# Basic web UI can be accessed via browser: http://localhost:8080
+# Chat completion endpoint: http://localhost:8080/v1/chat/completions
 ```
-perplexity : calculating perplexity over 655 chunks
-24.43 seconds per pass - ETA 4.45 hours
-[1]4.5970,[2]5.1807,[3]6.0382,...
-```
-And after 4.45 hours, you will have the final perplexity.
 
 ### Interactive mode
 
-If you want a more ChatGPT-like experience, you can run in interactive mode by passing `-i` as a parameter.
+> [!NOTE]
+> If you prefer basic usage, please consider using conversation mode instead of interactive mode
+
 In this mode, you can always interrupt generation by pressing Ctrl+C and entering one or more lines of text, which will be converted into tokens and appended to the current context. You can also specify a *reverse prompt* with the parameter `-r "reverse prompt string"`. This will result in user input being prompted whenever the exact tokens of the reverse prompt string are encountered in the generation. A typical use is to use a prompt that makes LLaMA emulate a chat between multiple users, say Alice and Bob, and pass `-r "Alice:"`.
 
 Here is an example of a few-shot interaction, invoked with the command
@@ -827,150 +414,28 @@ If your issue is with model generation quality, then please at least scan the fo
     - [Aligning language models to follow instructions](https://openai.com/research/instruction-following)
     - [Training language models to follow instructions with human feedback](https://arxiv.org/abs/2203.02155)
 
-### Android
-
-#### Build on Android using Termux
-[Termux](https://github.com/termux/termux-app#installation) is a method to execute `llama.cpp` on an Android device (no root required).
-```
-apt update && apt upgrade -y
-apt install git make cmake
-```
-
-It's recommended to move your model inside the `~/` directory for best performance:
-```
-cd storage/downloads
-mv model.gguf ~/
-```
-
-[Get the code](https://github.com/ggerganov/llama.cpp#get-the-code) & [follow the Linux build instructions](https://github.com/ggerganov/llama.cpp#build) to build `llama.cpp`.
-
-#### Building the Project using Android NDK
-Obtain the [Android NDK](https://developer.android.com/ndk) and then build with CMake.
-
-Execute the following commands on your computer to avoid downloading the NDK to your mobile. Alternatively, you can also do this in Termux:
-```
-$ mkdir build-android
-$ cd build-android
-$ export NDK=
-$ cmake -DCMAKE_TOOLCHAIN_FILE=$NDK/build/cmake/android.toolchain.cmake -DANDROID_ABI=arm64-v8a -DANDROID_PLATFORM=android-23 -DCMAKE_C_FLAGS=-march=armv8.4a+dotprod ..
-$ make
-```
-
-Install [termux](https://github.com/termux/termux-app#installation) on your device and run `termux-setup-storage` to get access to your SD card (if Android 11+ then run the command twice).
-
-Finally, copy these built `llama` binaries and the model file to your device storage. Because the file permissions in the Android sdcard cannot be changed, you can copy the executable files to the `/data/data/com.termux/files/home/bin` path, and then execute the following commands in Termux to add executable permission:
-
-(Assumed that you have pushed the built executable files to the /sdcard/llama.cpp/bin path using `adb push`)
-```
-$cp -r /sdcard/llama.cpp/bin /data/data/com.termux/files/home/
-$cd /data/data/com.termux/files/home/bin
-$chmod +x ./*
-```
-
-Download model [llama-2-7b-chat.Q4_K_M.gguf](https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGUF/blob/main/llama-2-7b-chat.Q4_K_M.gguf), and push it to `/sdcard/llama.cpp/`, then move it to `/data/data/com.termux/files/home/model/`
-
-```
-$mv /sdcard/llama.cpp/llama-2-7b-chat.Q4_K_M.gguf /data/data/com.termux/files/home/model/
-```
-
-Now, you can start chatting:
-```
-$cd /data/data/com.termux/files/home/bin
-$./llama-cli -m ../model/llama-2-7b-chat.Q4_K_M.gguf -n 128 -cml
-```
-
-Here's a demo of an interactive session running on Pixel 5 phone:
-
-https://user-images.githubusercontent.com/271616/225014776-1d567049-ad71-4ef2-b050-55b0b3b9274c.mp4
-
-### Docker
-
-#### Prerequisites
-* Docker must be installed and running on your system.
-* Create a folder to store big models & intermediate files (ex. /llama/models)
-
-#### Images
-We have three Docker images available for this project:
-
-1. `ghcr.io/ggerganov/llama.cpp:full`: This image includes both the main executable file and the tools to convert LLaMA models into ggml and convert into 4-bit quantization. (platforms: `linux/amd64`, `linux/arm64`)
-2. `ghcr.io/ggerganov/llama.cpp:light`: This image only includes the main executable file. (platforms: `linux/amd64`, `linux/arm64`)
-3. `ghcr.io/ggerganov/llama.cpp:server`: This image only includes the server executable file. (platforms: `linux/amd64`, `linux/arm64`)
+## Tools
 
-Additionally, there the following images, similar to the above:
-
-- `ghcr.io/ggerganov/llama.cpp:full-cuda`: Same as `full` but compiled with CUDA support. (platforms: `linux/amd64`)
-- `ghcr.io/ggerganov/llama.cpp:light-cuda`: Same as `light` but compiled with CUDA support. (platforms: `linux/amd64`)
-- `ghcr.io/ggerganov/llama.cpp:server-cuda`: Same as `server` but compiled with CUDA support. (platforms: `linux/amd64`)
-- `ghcr.io/ggerganov/llama.cpp:full-rocm`: Same as `full` but compiled with ROCm support. (platforms: `linux/amd64`, `linux/arm64`)
-- `ghcr.io/ggerganov/llama.cpp:light-rocm`: Same as `light` but compiled with ROCm support. (platforms: `linux/amd64`, `linux/arm64`)
-- `ghcr.io/ggerganov/llama.cpp:server-rocm`: Same as `server` but compiled with ROCm support. (platforms: `linux/amd64`, `linux/arm64`)
-
-The GPU enabled images are not currently tested by CI beyond being built. They are not built with any variation from the ones in the Dockerfiles defined in [.devops/](.devops/) and the GitHub Action defined in [.github/workflows/docker.yml](.github/workflows/docker.yml). If you need different settings (for example, a different CUDA or ROCm library, you'll need to build the images locally for now).
-
-#### Usage
-
-The easiest way to download the models, convert them to ggml and optimize them is with the --all-in-one command which includes the full docker image.
-
-Replace `/path/to/models` below with the actual path where you downloaded the models.
-
-```bash
-docker run -v /path/to/models:/models ghcr.io/ggerganov/llama.cpp:full --all-in-one "/models/" 7B
-```
-
-On completion, you are ready to play!
-
-```bash
-docker run -v /path/to/models:/models ghcr.io/ggerganov/llama.cpp:full --run -m /models/7B/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 512
-```
-
-or with a light image:
-
-```bash
-docker run -v /path/to/models:/models ghcr.io/ggerganov/llama.cpp:light -m /models/7B/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 512
-```
-
-or with a server image:
-
-```bash
-docker run -v /path/to/models:/models -p 8000:8000 ghcr.io/ggerganov/llama.cpp:server -m /models/7B/ggml-model-q4_0.gguf --port 8000 --host 0.0.0.0 -n 512
-```
-
-### Docker With CUDA
-
-Assuming one has the [nvidia-container-toolkit](https://github.com/NVIDIA/nvidia-container-toolkit) properly installed on Linux, or is using a GPU enabled cloud, `cuBLAS` should be accessible inside the container.
-
-#### Building Locally
-
-```bash
-docker build -t local/llama.cpp:full-cuda -f .devops/full-cuda.Dockerfile .
-docker build -t local/llama.cpp:light-cuda -f .devops/llama-cli-cuda.Dockerfile .
-docker build -t local/llama.cpp:server-cuda -f .devops/llama-server-cuda.Dockerfile .
-```
-
-You may want to pass in some different `ARGS`, depending on the CUDA environment supported by your container host, as well as the GPU architecture.
+### Prepare and Quantize
 
-The defaults are:
+> [!NOTE]
+> You can use the [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space on Hugging Face to quantise your model weights without any setup too. It is synced from `llama.cpp` main every 6 hours.
 
-- `CUDA_VERSION` set to `11.7.1`
-- `CUDA_DOCKER_ARCH` set to `all`
+To obtain the official LLaMA 2 weights please see the Obtaining and using the Facebook LLaMA 2 model section. There is also a large selection of pre-quantized `gguf` models available on Hugging Face.
 
-The resulting images, are essentially the same as the non-CUDA images:
+Note: `convert.py` has been moved to `examples/convert_legacy_llama.py` and shouldn't be used for anything other than `Llama/Llama2/Mistral` models and their derivatives.
+It does not support LLaMA 3, you can use `convert_hf_to_gguf.py` with LLaMA 3 downloaded from Hugging Face.
 
-1. `local/llama.cpp:full-cuda`: This image includes both the main executable file and the tools to convert LLaMA models into ggml and convert into 4-bit quantization.
-2. `local/llama.cpp:light-cuda`: This image only includes the main executable file.
-3. `local/llama.cpp:server-cuda`: This image only includes the server executable file.
+To learn more about quantizing model, [read this documentation](./examples/quantize/README.md)
 
-#### Usage
+### Perplexity (measuring model quality)
 
-After building locally, Usage is similar to the non-CUDA examples, but you'll need to add the `--gpus` flag. You will also want to use the `--n-gpu-layers` flag.
+You can use the `perplexity` example to measure perplexity over a given prompt (lower perplexity is better).
+For more information, see [https://huggingface.co/docs/transformers/perplexity](https://huggingface.co/docs/transformers/perplexity).
 
-```bash
-docker run --gpus all -v /path/to/models:/models local/llama.cpp:full-cuda --run -m /models/7B/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 512 --n-gpu-layers 1
-docker run --gpus all -v /path/to/models:/models local/llama.cpp:light-cuda -m /models/7B/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 512 --n-gpu-layers 1
-docker run --gpus all -v /path/to/models:/models local/llama.cpp:server-cuda -m /models/7B/ggml-model-q4_0.gguf --port 8000 --host 0.0.0.0 -n 512 --n-gpu-layers 1
-```
+To learn more how to measure perplexity using llama.cpp, [read this documentation](./examples/perplexity/README.md)
 
-### Contributing
+## Contributing
 
 - Contributors can open PRs
 - Collaborators can push to branches in the `llama.cpp` repo and merge PRs into the `master` branch
@@ -981,12 +446,17 @@ docker run --gpus all -v /path/to/models:/models local/llama.cpp:server-cuda -m
 - Make sure to read this: [Inference at the edge](https://github.com/ggerganov/llama.cpp/discussions/205)
 - A bit of backstory for those who are interested: [Changelog podcast](https://changelog.com/podcast/532)
 
-### Docs
+## Other documentations
 
 - [main (cli)](./examples/main/README.md)
 - [server](./examples/server/README.md)
 - [jeopardy](./examples/jeopardy/README.md)
-- [BLIS](./docs/BLIS.md)
+- [GBNF grammars](./grammars/README.md)
+
+**Development documentations**
+
+- [How to build](./docs/build.md)
+- [Running on Docker](./docs/docker.md)
+- [Build on Android](./docs/android.md)
 - [Performance troubleshooting](./docs/token_generation_performance_tips.md)
 - [GGML tips & tricks](https://github.com/ggerganov/llama.cpp/wiki/GGML-Tips-&-Tricks)
-- [GBNF grammars](./grammars/README.md)
diff --git a/docs/android.md b/docs/android.md
new file mode 100644
index 0000000000000..cec4358d98a26
--- /dev/null
+++ b/docs/android.md
@@ -0,0 +1,56 @@
+
+# Android
+
+## Build on Android using Termux
+[Termux](https://github.com/termux/termux-app#installation) is a method to execute `llama.cpp` on an Android device (no root required).
+```
+apt update && apt upgrade -y
+apt install git make cmake
+```
+
+It's recommended to move your model inside the `~/` directory for best performance:
+```
+cd storage/downloads
+mv model.gguf ~/
+```
+
+[Get the code](https://github.com/ggerganov/llama.cpp#get-the-code) & [follow the Linux build instructions](https://github.com/ggerganov/llama.cpp#build) to build `llama.cpp`.
+
+## Building the Project using Android NDK
+Obtain the [Android NDK](https://developer.android.com/ndk) and then build with CMake.
+
+Execute the following commands on your computer to avoid downloading the NDK to your mobile. Alternatively, you can also do this in Termux:
+```
+$ mkdir build-android
+$ cd build-android
+$ export NDK=
+$ cmake -DCMAKE_TOOLCHAIN_FILE=$NDK/build/cmake/android.toolchain.cmake -DANDROID_ABI=arm64-v8a -DANDROID_PLATFORM=android-23 -DCMAKE_C_FLAGS=-march=armv8.4a+dotprod ..
+$ make
+```
+
+Install [termux](https://github.com/termux/termux-app#installation) on your device and run `termux-setup-storage` to get access to your SD card (if Android 11+ then run the command twice).
+
+Finally, copy these built `llama` binaries and the model file to your device storage. Because the file permissions in the Android sdcard cannot be changed, you can copy the executable files to the `/data/data/com.termux/files/home/bin` path, and then execute the following commands in Termux to add executable permission:
+
+(Assumed that you have pushed the built executable files to the /sdcard/llama.cpp/bin path using `adb push`)
+```
+$cp -r /sdcard/llama.cpp/bin /data/data/com.termux/files/home/
+$cd /data/data/com.termux/files/home/bin
+$chmod +x ./*
+```
+
+Download model [llama-2-7b-chat.Q4_K_M.gguf](https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGUF/blob/main/llama-2-7b-chat.Q4_K_M.gguf), and push it to `/sdcard/llama.cpp/`, then move it to `/data/data/com.termux/files/home/model/`
+
+```
+$mv /sdcard/llama.cpp/llama-2-7b-chat.Q4_K_M.gguf /data/data/com.termux/files/home/model/
+```
+
+Now, you can start chatting:
+```
+$cd /data/data/com.termux/files/home/bin
+$./llama-cli -m ../model/llama-2-7b-chat.Q4_K_M.gguf -n 128 -cml
+```
+
+Here's a demo of an interactive session running on Pixel 5 phone:
+
+https://user-images.githubusercontent.com/271616/225014776-1d567049-ad71-4ef2-b050-55b0b3b9274c.mp4
diff --git a/docs/BLIS.md b/docs/backend/BLIS.md
similarity index 100%
rename from docs/BLIS.md
rename to docs/backend/BLIS.md
diff --git a/README-sycl.md b/docs/backend/SYCL.md
similarity index 100%
rename from README-sycl.md
rename to docs/backend/SYCL.md
diff --git a/docs/build.md b/docs/build.md
new file mode 100644
index 0000000000000..cf42a4eb93e19
--- /dev/null
+++ b/docs/build.md
@@ -0,0 +1,288 @@
+# Build llama.cpp locally
+
+**To get the Code:**
+
+```bash
+git clone https://github.com/ggerganov/llama.cpp
+cd llama.cpp
+```
+
+In order to build llama.cpp you have four different options.
+
+- Using `make`:
+  - On Linux or MacOS:
+
+      ```bash
+      make
+      ```
+
+  - On Windows:
+
+    1. Download the latest fortran version of [w64devkit](https://github.com/skeeto/w64devkit/releases).
+    2. Extract `w64devkit` on your pc.
+    3. Run `w64devkit.exe`.
+    4. Use the `cd` command to reach the `llama.cpp` folder.
+    5. From here you can run:
+        ```bash
+        make
+        ```
+
+  - Notes:
+    - For faster compilation, add the `-j` argument to run multiple jobs in parallel. For example, `make -j 8` will run 8 jobs in parallel.
+    - For faster repeated compilation, install [ccache](https://ccache.dev/).
+    - For debug builds, run `make LLAMA_DEBUG=1`
+
+- Using `CMake`:
+
+  ```bash
+  cmake -B build
+  cmake --build build --config Release
+  ```
+
+  **Notes**:
+
+    - For faster compilation, add the `-j` argument to run multiple jobs in parallel. For example, `cmake --build build --config Release -j 8` will run 8 jobs in parallel.
+    - For faster repeated compilation, install [ccache](https://ccache.dev/).
+    - For debug builds, there are two cases:
+
+      1. Single-config generators (e.g. default = `Unix Makefiles`; note that they just ignore the `--config` flag):
+
+      ```bash
+      cmake -B build -DCMAKE_BUILD_TYPE=Debug
+      cmake --build build
+      ```
+
+      2. Multi-config generators (`-G` param set to Visual Studio, XCode...):
+
+      ```bash
+      cmake -B build -G "Xcode"
+      cmake --build build --config Debug
+      ```
+
+-   Using `gmake` (FreeBSD):
+
+    1. Install and activate [DRM in FreeBSD](https://wiki.freebsd.org/Graphics)
+    2. Add your user to **video** group
+    3. Install compilation dependencies.
+
+        ```bash
+        sudo pkg install gmake automake autoconf pkgconf llvm15 openblas
+
+        gmake CC=/usr/local/bin/clang15 CXX=/usr/local/bin/clang++15 -j4
+        ```
+
+## Metal Build
+
+On MacOS, Metal is enabled by default. Using Metal makes the computation run on the GPU.
+To disable the Metal build at compile time use the `GGML_NO_METAL=1` flag or the `GGML_METAL=OFF` cmake option.
+
+When built with Metal support, you can explicitly disable GPU inference with the `--n-gpu-layers|-ngl 0` command-line
+argument.
+
+## BLAS Build
+
+Building the program with BLAS support may lead to some performance improvements in prompt processing using batch sizes higher than 32 (the default is 512). Support with CPU-only BLAS implementations doesn't affect the normal generation performance. We may see generation performance improvements with GPU-involved BLAS implementations, e.g. cuBLAS, hipBLAS. There are currently several different BLAS implementations available for build and use:
+
+### Accelerate Framework:
+
+  This is only available on Mac PCs and it's enabled by default. You can just build using the normal instructions.
+
+### OpenBLAS:
+
+This provides BLAS acceleration using only the CPU. Make sure to have OpenBLAS installed on your machine.
+
+- Using `make`:
+  - On Linux:
+    ```bash
+    make GGML_OPENBLAS=1
+    ```
+
+  - On Windows:
+
+    1. Download the latest fortran version of [w64devkit](https://github.com/skeeto/w64devkit/releases).
+    2. Download the latest version of [OpenBLAS for Windows](https://github.com/xianyi/OpenBLAS/releases).
+    3. Extract `w64devkit` on your pc.
+    4. From the OpenBLAS zip that you just downloaded copy `libopenblas.a`, located inside the `lib` folder, inside `w64devkit\x86_64-w64-mingw32\lib`.
+    5. From the same OpenBLAS zip copy the content of the `include` folder inside `w64devkit\x86_64-w64-mingw32\include`.
+    6. Run `w64devkit.exe`.
+    7. Use the `cd` command to reach the `llama.cpp` folder.
+    8. From here you can run:
+
+        ```bash
+        make GGML_OPENBLAS=1
+        ```
+
+- Using `CMake` on Linux:
+
+    ```bash
+    cmake -B build -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
+    cmake --build build --config Release
+    ```
+
+### BLIS
+
+Check [BLIS.md](./backend/BLIS.md) for more information.
+
+### SYCL
+
+SYCL is a higher-level programming model to improve programming productivity on various hardware accelerators.
+
+llama.cpp based on SYCL is used to **support Intel GPU** (Data Center Max series, Flex series, Arc series, Built-in GPU and iGPU).
+
+For detailed info, please refer to [llama.cpp for SYCL](./backend/SYCL.md).
+
+### Intel oneMKL
+
+Building through oneAPI compilers will make avx_vnni instruction set available for intel processors that do not support avx512 and avx512_vnni. Please note that this build config **does not support Intel GPU**. For Intel GPU support, please refer to [llama.cpp for SYCL](./backend/SYCL.md).
+
+- Using manual oneAPI installation:
+  By default, `GGML_BLAS_VENDOR` is set to `Generic`, so if you already sourced intel environment script and assign `-DGGML_BLAS=ON` in cmake, the mkl version of Blas will automatically been selected. Otherwise please install oneAPI and follow the below steps:
+    ```bash
+    source /opt/intel/oneapi/setvars.sh # You can skip this step if  in oneapi-basekit docker image, only required for manual installation
+    cmake -B build -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=Intel10_64lp -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_NATIVE=ON
+    cmake --build build --config Release
+    ```
+
+- Using oneAPI docker image:
+  If you do not want to source the environment vars and install oneAPI manually, you can also build the code using intel docker container: [oneAPI-basekit](https://hub.docker.com/r/intel/oneapi-basekit). Then, you can use the commands given above.
+
+Check [Optimizing and Running LLaMA2 on Intel® CPU](https://www.intel.com/content/www/us/en/content-details/791610/optimizing-and-running-llama2-on-intel-cpu.html) for more information.
+
+### CUDA
+
+This provides GPU acceleration using the CUDA cores of your Nvidia GPU. Make sure to have the CUDA toolkit installed. You can download it from your Linux distro's package manager (e.g. `apt install nvidia-cuda-toolkit`) or from here: [CUDA Toolkit](https://developer.nvidia.com/cuda-downloads).
+
+For Jetson user, if you have Jetson Orin, you can try this: [Offical Support](https://www.jetson-ai-lab.com/tutorial_text-generation.html). If you are using an old model(nano/TX2), need some additional operations before compiling.
+
+- Using `make`:
+  ```bash
+  make GGML_CUDA=1
+  ```
+- Using `CMake`:
+
+  ```bash
+  cmake -B build -DGGML_CUDA=ON
+  cmake --build build --config Release
+  ```
+
+The environment variable [`CUDA_VISIBLE_DEVICES`](https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#env-vars) can be used to specify which GPU(s) will be used. The following compilation options are also available to tweak performance:
+
+| Option                        | Legal values           | Default | Description                                                                                                                                                                                                                                                                             |
+|-------------------------------|------------------------|---------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| GGML_CUDA_FORCE_DMMV          | Boolean                | false   | Force the use of dequantization + matrix vector multiplication kernels instead of using kernels that do matrix vector multiplication on quantized data. By default the decision is made based on compute capability (MMVQ for 6.1/Pascal/GTX 1000 or higher). Does not affect k-quants. |
+| GGML_CUDA_DMMV_X              | Positive integer >= 32 | 32      | Number of values in x direction processed by the CUDA dequantization + matrix vector multiplication kernel per iteration. Increasing this value can improve performance on fast GPUs. Power of 2 heavily recommended. Does not affect k-quants.                                         |
+| GGML_CUDA_MMV_Y               | Positive integer       | 1       | Block size in y direction for the CUDA mul mat vec kernels. Increasing this value can improve performance on fast GPUs. Power of 2 recommended.                                                                                                                                         |
+| GGML_CUDA_FORCE_MMQ           | Boolean                | false   | Force the use of custom matrix multiplication kernels for quantized models instead of FP16 cuBLAS even if there is no int8 tensor core implementation available (affects V100, RDNA3). MMQ kernels are enabled by default on GPUs with int8 tensor core support. With MMQ force enabled, speed for large batch sizes will be worse but VRAM consumption will be lower.                       |
+| GGML_CUDA_FORCE_CUBLAS        | Boolean                | false   | Force the use of FP16 cuBLAS instead of custom matrix multiplication kernels for quantized models                                                                                                                                                                                       |
+| GGML_CUDA_F16                 | Boolean                | false   | If enabled, use half-precision floating point arithmetic for the CUDA dequantization + mul mat vec kernels and for the q4_1 and q5_1 matrix matrix multiplication kernels. Can improve performance on relatively recent GPUs.                                                           |
+| GGML_CUDA_KQUANTS_ITER        | 1 or 2                 | 2       | Number of values processed per iteration and per CUDA thread for Q2_K and Q6_K quantization formats. Setting this value to 1 can improve performance for slow GPUs.                                                                                                                     |
+| GGML_CUDA_PEER_MAX_BATCH_SIZE | Positive integer       | 128     | Maximum batch size for which to enable peer access between multiple GPUs. Peer access requires either Linux or NVLink. When using NVLink enabling peer access for larger batch sizes is potentially beneficial.                                                                         |
+| GGML_CUDA_FA_ALL_QUANTS       | Boolean                | false   | Compile support for all KV cache quantization type (combinations) for the FlashAttention CUDA kernels. More fine-grained control over KV cache size but compilation takes much longer.                                                                                                  |
+
+### hipBLAS
+
+This provides BLAS acceleration on HIP-supported AMD GPUs.
+Make sure to have ROCm installed.
+You can download it from your Linux distro's package manager or from here: [ROCm Quick Start (Linux)](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/tutorial/quick-start.html#rocm-install-quick).
+
+- Using `make`:
+  ```bash
+  make GGML_HIPBLAS=1
+  ```
+- Using `CMake` for Linux (assuming a gfx1030-compatible AMD GPU):
+  ```bash
+  HIPCXX="$(hipconfig -l)/clang" HIP_PATH="$(hipconfig -R)" \
+      cmake -S . -B build -DGGML_HIPBLAS=ON -DAMDGPU_TARGETS=gfx1030 -DCMAKE_BUILD_TYPE=Release \
+      && cmake --build build --config Release -- -j 16
+  ```
+  On Linux it is also possible to use unified memory architecture (UMA) to share main memory between the CPU and integrated GPU by setting `-DGGML_HIP_UMA=ON`.
+  However, this hurts performance for non-integrated GPUs (but enables working with integrated GPUs).
+
+  Note that if you get the following error:
+  ```
+  clang: error: cannot find ROCm device library; provide its path via '--rocm-path' or '--rocm-device-lib-path', or pass '-nogpulib' to build without ROCm device library
+  ```
+  Try searching for a directory under `HIP_PATH` that contains the file
+  `oclc_abi_version_400.bc`. Then, add the following to the start of the
+  command: `HIP_DEVICE_LIB_PATH=`, so something
+  like:
+  ```bash
+  HIPCXX="$(hipconfig -l)/clang" HIP_PATH="$(hipconfig -p)" \
+  HIP_DEVICE_LIB_PATH= \
+      cmake -S . -B build -DGGML_HIPBLAS=ON -DAMDGPU_TARGETS=gfx1030 -DCMAKE_BUILD_TYPE=Release \
+      && cmake --build build -- -j 16
+  ```
+
+- Using `make` (example for target gfx1030, build with 16 CPU threads):
+  ```bash
+  make -j16 GGML_HIPBLAS=1 GGML_HIP_UMA=1 AMDGPU_TARGETS=gfx1030
+  ```
+
+- Using `CMake` for Windows (using x64 Native Tools Command Prompt for VS, and assuming a gfx1100-compatible AMD GPU):
+  ```bash
+  set PATH=%HIP_PATH%\bin;%PATH%
+  cmake -S . -B build -G Ninja -DAMDGPU_TARGETS=gfx1100 -DGGML_HIPBLAS=ON -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_BUILD_TYPE=Release
+  cmake --build build
+  ```
+  Make sure that `AMDGPU_TARGETS` is set to the GPU arch you want to compile for. The above example uses `gfx1100` that corresponds to Radeon RX 7900XTX/XT/GRE. You can find a list of targets [here](https://llvm.org/docs/AMDGPUUsage.html#processors)
+  Find your gpu version string by matching the most significant version information from `rocminfo | grep gfx | head -1 | awk '{print $2}'` with the list of processors, e.g. `gfx1035` maps to `gfx1030`.
+
+
+The environment variable [`HIP_VISIBLE_DEVICES`](https://rocm.docs.amd.com/en/latest/understand/gpu_isolation.html#hip-visible-devices) can be used to specify which GPU(s) will be used.
+If your GPU is not officially supported you can use the environment variable [`HSA_OVERRIDE_GFX_VERSION`] set to a similar GPU, for example 10.3.0 on RDNA2 (e.g. gfx1030, gfx1031, or gfx1035) or 11.0.0 on RDNA3.
+The following compilation options are also available to tweak performance (yes, they refer to CUDA, not HIP, because it uses the same code as the cuBLAS version above):
+
+| Option                 | Legal values           | Default | Description                                                                                                                                                                                                                                    |
+|------------------------|------------------------|---------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| GGML_CUDA_DMMV_X       | Positive integer >= 32 | 32      | Number of values in x direction processed by the HIP dequantization + matrix vector multiplication kernel per iteration. Increasing this value can improve performance on fast GPUs. Power of 2 heavily recommended. Does not affect k-quants. |
+| GGML_CUDA_MMV_Y        | Positive integer       | 1       | Block size in y direction for the HIP mul mat vec kernels. Increasing this value can improve performance on fast GPUs. Power of 2 recommended. Does not affect k-quants.                                                                       |
+| GGML_CUDA_KQUANTS_ITER | 1 or 2                 | 2       | Number of values processed per iteration and per HIP thread for Q2_K and Q6_K quantization formats. Setting this value to 1 can improve performance for slow GPUs.                                                                             |
+
+### Vulkan
+
+**With docker**:
+
+You don't need to install Vulkan SDK. It will be installed inside the container.
+
+```sh
+# Build the image
+docker build -t llama-cpp-vulkan -f .devops/llama-cli-vulkan.Dockerfile .
+
+# Then, use it:
+docker run -it --rm -v "$(pwd):/app:Z" --device /dev/dri/renderD128:/dev/dri/renderD128 --device /dev/dri/card1:/dev/dri/card1 llama-cpp-vulkan -m "/app/models/YOUR_MODEL_FILE" -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 33
+```
+
+**Without docker**:
+
+Firstly, you need to make sure you have installed [Vulkan SDK](https://vulkan.lunarg.com/doc/view/latest/linux/getting_started_ubuntu.html)
+
+For example, on Ubuntu 22.04 (jammy), use the command below:
+
+```bash
+wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add -
+wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list
+apt update -y
+apt-get install -y vulkan-sdk
+# To verify the installation, use the command below:
+vulkaninfo
+```
+
+Alternatively your package manager might be able to provide the appropriate libraries.
+For example for Ubuntu 22.04 you can install `libvulkan-dev` instead.
+For Fedora 40, you can install `vulkan-devel`, `glslc` and `glslang` packages.
+
+Then, build llama.cpp using the cmake command below:
+
+```bash
+cmake -B build -DGGML_VULKAN=1
+cmake --build build --config Release
+# Test the output binary (with "-ngl 33" to offload all layers to GPU)
+./bin/llama-cli -m "PATH_TO_MODEL" -p "Hi you how are you" -n 50 -e -ngl 33 -t 4
+
+# You should see in the output, ggml_vulkan detected your GPU. For example:
+# ggml_vulkan: Using Intel(R) Graphics (ADL GT2) | uma: 1 | fp16: 1 | warp size: 32
+```
+
+### Android
+
+To read documentation for how to build on Android, [click here](./android.md)
diff --git a/docs/HOWTO-add-model.md b/docs/development/HOWTO-add-model.md
similarity index 99%
rename from docs/HOWTO-add-model.md
rename to docs/development/HOWTO-add-model.md
index 87093cedd9ab6..2712b66c17533 100644
--- a/docs/HOWTO-add-model.md
+++ b/docs/development/HOWTO-add-model.md
@@ -1,4 +1,4 @@
-## Add a new model architecture to `llama.cpp`
+# Add a new model architecture to `llama.cpp`
 
 Adding a model requires few steps:
 
diff --git a/docs/debugging-tests.md b/docs/development/debugging-tests.md
similarity index 100%
rename from docs/debugging-tests.md
rename to docs/development/debugging-tests.md
diff --git a/docs/llama-star/idea-arch.key b/docs/development/llama-star/idea-arch.key
similarity index 100%
rename from docs/llama-star/idea-arch.key
rename to docs/development/llama-star/idea-arch.key
diff --git a/docs/llama-star/idea-arch.pdf b/docs/development/llama-star/idea-arch.pdf
similarity index 100%
rename from docs/llama-star/idea-arch.pdf
rename to docs/development/llama-star/idea-arch.pdf
diff --git a/docs/token_generation_performance_tips.md b/docs/development/token_generation_performance_tips.md
similarity index 100%
rename from docs/token_generation_performance_tips.md
rename to docs/development/token_generation_performance_tips.md
diff --git a/docs/docker.md b/docs/docker.md
new file mode 100644
index 0000000000000..d8922d77d9fe5
--- /dev/null
+++ b/docs/docker.md
@@ -0,0 +1,86 @@
+# Docker
+
+## Prerequisites
+* Docker must be installed and running on your system.
+* Create a folder to store big models & intermediate files (ex. /llama/models)
+
+## Images
+We have three Docker images available for this project:
+
+1. `ghcr.io/ggerganov/llama.cpp:full`: This image includes both the main executable file and the tools to convert LLaMA models into ggml and convert into 4-bit quantization. (platforms: `linux/amd64`, `linux/arm64`)
+2. `ghcr.io/ggerganov/llama.cpp:light`: This image only includes the main executable file. (platforms: `linux/amd64`, `linux/arm64`)
+3. `ghcr.io/ggerganov/llama.cpp:server`: This image only includes the server executable file. (platforms: `linux/amd64`, `linux/arm64`)
+
+Additionally, there the following images, similar to the above:
+
+- `ghcr.io/ggerganov/llama.cpp:full-cuda`: Same as `full` but compiled with CUDA support. (platforms: `linux/amd64`)
+- `ghcr.io/ggerganov/llama.cpp:light-cuda`: Same as `light` but compiled with CUDA support. (platforms: `linux/amd64`)
+- `ghcr.io/ggerganov/llama.cpp:server-cuda`: Same as `server` but compiled with CUDA support. (platforms: `linux/amd64`)
+- `ghcr.io/ggerganov/llama.cpp:full-rocm`: Same as `full` but compiled with ROCm support. (platforms: `linux/amd64`, `linux/arm64`)
+- `ghcr.io/ggerganov/llama.cpp:light-rocm`: Same as `light` but compiled with ROCm support. (platforms: `linux/amd64`, `linux/arm64`)
+- `ghcr.io/ggerganov/llama.cpp:server-rocm`: Same as `server` but compiled with ROCm support. (platforms: `linux/amd64`, `linux/arm64`)
+
+The GPU enabled images are not currently tested by CI beyond being built. They are not built with any variation from the ones in the Dockerfiles defined in [.devops/](.devops/) and the GitHub Action defined in [.github/workflows/docker.yml](.github/workflows/docker.yml). If you need different settings (for example, a different CUDA or ROCm library, you'll need to build the images locally for now).
+
+## Usage
+
+The easiest way to download the models, convert them to ggml and optimize them is with the --all-in-one command which includes the full docker image.
+
+Replace `/path/to/models` below with the actual path where you downloaded the models.
+
+```bash
+docker run -v /path/to/models:/models ghcr.io/ggerganov/llama.cpp:full --all-in-one "/models/" 7B
+```
+
+On completion, you are ready to play!
+
+```bash
+docker run -v /path/to/models:/models ghcr.io/ggerganov/llama.cpp:full --run -m /models/7B/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 512
+```
+
+or with a light image:
+
+```bash
+docker run -v /path/to/models:/models ghcr.io/ggerganov/llama.cpp:light -m /models/7B/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 512
+```
+
+or with a server image:
+
+```bash
+docker run -v /path/to/models:/models -p 8000:8000 ghcr.io/ggerganov/llama.cpp:server -m /models/7B/ggml-model-q4_0.gguf --port 8000 --host 0.0.0.0 -n 512
+```
+
+## Docker With CUDA
+
+Assuming one has the [nvidia-container-toolkit](https://github.com/NVIDIA/nvidia-container-toolkit) properly installed on Linux, or is using a GPU enabled cloud, `cuBLAS` should be accessible inside the container.
+
+## Building Docker locally
+
+```bash
+docker build -t local/llama.cpp:full-cuda -f .devops/full-cuda.Dockerfile .
+docker build -t local/llama.cpp:light-cuda -f .devops/llama-cli-cuda.Dockerfile .
+docker build -t local/llama.cpp:server-cuda -f .devops/llama-server-cuda.Dockerfile .
+```
+
+You may want to pass in some different `ARGS`, depending on the CUDA environment supported by your container host, as well as the GPU architecture.
+
+The defaults are:
+
+- `CUDA_VERSION` set to `11.7.1`
+- `CUDA_DOCKER_ARCH` set to `all`
+
+The resulting images, are essentially the same as the non-CUDA images:
+
+1. `local/llama.cpp:full-cuda`: This image includes both the main executable file and the tools to convert LLaMA models into ggml and convert into 4-bit quantization.
+2. `local/llama.cpp:light-cuda`: This image only includes the main executable file.
+3. `local/llama.cpp:server-cuda`: This image only includes the server executable file.
+
+## Usage
+
+After building locally, Usage is similar to the non-CUDA examples, but you'll need to add the `--gpus` flag. You will also want to use the `--n-gpu-layers` flag.
+
+```bash
+docker run --gpus all -v /path/to/models:/models local/llama.cpp:full-cuda --run -m /models/7B/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 512 --n-gpu-layers 1
+docker run --gpus all -v /path/to/models:/models local/llama.cpp:light-cuda -m /models/7B/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 512 --n-gpu-layers 1
+docker run --gpus all -v /path/to/models:/models local/llama.cpp:server-cuda -m /models/7B/ggml-model-q4_0.gguf --port 8000 --host 0.0.0.0 -n 512 --n-gpu-layers 1
+```
diff --git a/docs/install.md b/docs/install.md
new file mode 100644
index 0000000000000..10a568506835b
--- /dev/null
+++ b/docs/install.md
@@ -0,0 +1,39 @@
+# Install pre-built version of llama.cpp
+
+## Homebrew
+
+On Mac and Linux, the homebrew package manager can be used via
+
+```sh
+brew install llama.cpp
+```
+The formula is automatically updated with new `llama.cpp` releases. More info: https://github.com/ggerganov/llama.cpp/discussions/7668
+
+## Nix
+
+On Mac and Linux, the Nix package manager can be used via
+
+```sh
+nix profile install nixpkgs#llama-cpp
+```
+For flake enabled installs.
+
+Or
+
+```sh
+nix-env --file '' --install --attr llama-cpp
+```
+
+For non-flake enabled installs.
+
+This expression is automatically updated within the [nixpkgs repo](https://github.com/NixOS/nixpkgs/blob/nixos-24.05/pkgs/by-name/ll/llama-cpp/package.nix#L164).
+
+## Flox
+
+On Mac and Linux, Flox can be used to install llama.cpp within a Flox environment via
+
+```sh
+flox install llama-cpp
+```
+
+Flox follows the nixpkgs build of llama.cpp.
diff --git a/examples/quantize/README.md b/examples/quantize/README.md
index b78ece4e7f59d..553c2701bced3 100644
--- a/examples/quantize/README.md
+++ b/examples/quantize/README.md
@@ -4,7 +4,89 @@ You can also use the [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-
 
 Note: It is synced from llama.cpp `main` every 6 hours.
 
-## Llama 2 7B
+Example usage:
+
+```bash
+# obtain the official LLaMA model weights and place them in ./models
+ls ./models
+llama-2-7b tokenizer_checklist.chk tokenizer.model
+# [Optional] for models using BPE tokenizers
+ls ./models
+ vocab.json
+# [Optional] for PyTorch .bin models like Mistral-7B
+ls ./models
+
+
+# install Python dependencies
+python3 -m pip install -r requirements.txt
+
+# convert the model to ggml FP16 format
+python3 convert_hf_to_gguf.py models/mymodel/
+
+# quantize the model to 4-bits (using Q4_K_M method)
+./llama-quantize ./models/mymodel/ggml-model-f16.gguf ./models/mymodel/ggml-model-Q4_K_M.gguf Q4_K_M
+
+# update the gguf filetype to current version if older version is now unsupported
+./llama-quantize ./models/mymodel/ggml-model-Q4_K_M.gguf ./models/mymodel/ggml-model-Q4_K_M-v2.gguf COPY
+```
+
+Run the quantized model:
+
+```bash
+# start inference on a gguf model
+./llama-cli -m ./models/mymodel/ggml-model-Q4_K_M.gguf -n 128
+```
+
+When running the larger models, make sure you have enough disk space to store all the intermediate files.
+
+## Memory/Disk Requirements
+
+As the models are currently fully loaded into memory, you will need adequate disk space to save them and sufficient RAM to load them. At the moment, memory and disk requirements are the same.
+
+| Model | Original size | Quantized size (Q4_0) |
+|------:|--------------:|----------------------:|
+|    7B |         13 GB |                3.9 GB |
+|   13B |         24 GB |                7.8 GB |
+|   30B |         60 GB |               19.5 GB |
+|   65B |        120 GB |               38.5 GB |
+
+## Quantization
+
+Several quantization methods are supported. They differ in the resulting model disk size and inference speed.
+
+*(outdated)*
+
+| Model | Measure      |    F16 |   Q4_0 |   Q4_1 |   Q5_0 |   Q5_1 |   Q8_0 |
+|------:|--------------|-------:|-------:|-------:|-------:|-------:|-------:|
+|    7B | perplexity   | 5.9066 | 6.1565 | 6.0912 | 5.9862 | 5.9481 | 5.9070 |
+|    7B | file size    |  13.0G |   3.5G |   3.9G |   4.3G |   4.7G |   6.7G |
+|    7B | ms/tok @ 4th |    127 |     55 |     54 |     76 |     83 |     72 |
+|    7B | ms/tok @ 8th |    122 |     43 |     45 |     52 |     56 |     67 |
+|    7B | bits/weight  |   16.0 |    4.5 |    5.0 |    5.5 |    6.0 |    8.5 |
+|   13B | perplexity   | 5.2543 | 5.3860 | 5.3608 | 5.2856 | 5.2706 | 5.2548 |
+|   13B | file size    |  25.0G |   6.8G |   7.6G |   8.3G |   9.1G |    13G |
+|   13B | ms/tok @ 4th |      - |    103 |    105 |    148 |    160 |    131 |
+|   13B | ms/tok @ 8th |      - |     73 |     82 |     98 |    105 |    128 |
+|   13B | bits/weight  |   16.0 |    4.5 |    5.0 |    5.5 |    6.0 |    8.5 |
+
+- [k-quants](https://github.com/ggerganov/llama.cpp/pull/1684)
+- recent k-quants improvements and new i-quants
+  - [#2707](https://github.com/ggerganov/llama.cpp/pull/2707)
+  - [#2807](https://github.com/ggerganov/llama.cpp/pull/2807)
+  - [#4773 - 2-bit i-quants (inference)](https://github.com/ggerganov/llama.cpp/pull/4773)
+  - [#4856 - 2-bit i-quants (inference)](https://github.com/ggerganov/llama.cpp/pull/4856)
+  - [#4861 - importance matrix](https://github.com/ggerganov/llama.cpp/pull/4861)
+  - [#4872 - MoE models](https://github.com/ggerganov/llama.cpp/pull/4872)
+  - [#4897 - 2-bit quantization](https://github.com/ggerganov/llama.cpp/pull/4897)
+  - [#4930 - imatrix for all k-quants](https://github.com/ggerganov/llama.cpp/pull/4930)
+  - [#4951 - imatrix on the GPU](https://github.com/ggerganov/llama.cpp/pull/4957)
+  - [#4969 - imatrix for legacy quants](https://github.com/ggerganov/llama.cpp/pull/4969)
+  - [#4996 - k-qunats tuning](https://github.com/ggerganov/llama.cpp/pull/4996)
+  - [#5060 - Q3_K_XS](https://github.com/ggerganov/llama.cpp/pull/5060)
+  - [#5196 - 3-bit i-quants](https://github.com/ggerganov/llama.cpp/pull/5196)
+  - [quantization tuning](https://github.com/ggerganov/llama.cpp/pull/5320), [another one](https://github.com/ggerganov/llama.cpp/pull/5334), and [another one](https://github.com/ggerganov/llama.cpp/pull/5361)
+
+**Llama 2 7B**
 
 | Quantization | Bits per Weight (BPW) |
 |--------------|-----------------------|
@@ -18,7 +100,8 @@ Note: It is synced from llama.cpp `main` every 6 hours.
 | Q5_K_M       | 5.68                  |
 | Q6_K         | 6.56                  |
 
-## Llama 2 13B
+**Llama 2 13B**
+
 Quantization | Bits per Weight (BPW)
 -- | --
 Q2_K | 3.34
@@ -31,7 +114,7 @@ Q5_K_S | 5.51
 Q5_K_M | 5.67
 Q6_K | 6.56
 
-# Llama 2 70B
+**Llama 2 70B**
 
 Quantization | Bits per Weight (BPW)
 -- | --

From 213701b51a17175d0d326b566efc03f30ec7fbe6 Mon Sep 17 00:00:00 2001
From: jaime-m-p <167997752+jaime-m-p@users.noreply.github.com>
Date: Fri, 5 Jul 2024 19:01:35 +0200
Subject: [PATCH 115/326] Detokenizer fixes (#8039)

* Add llama_detokenize():
  - Update header files location
  - UNKNOWN and CONTROL are 'special pieces'
  - Remove space after UNKNOWN and CONTROL
  - Refactor llama_token_to_piece()
  - Add flag: clean_up_tokenization_spaces
  - Symmetric params for llama_tokenize() and llama_detokenize()

* Update and fix tokenizer tests:
  - Using llama_detokenize()
  - Unexpected vocab type as test fail instead of error
    - Useful when automating tests:
    - If you don't know in advance the vocab type
    - Differenciate other loading errors
  - Skip unicode surrogaes and undefined
  - Gracefully exit threads
    - Using exit() is throwing random exceptions
  - Clean old known problematic codepoints
  - Minor: confusing hexadecimal codepoint

* Update bruteforce random tests
  - Add detokenizer checks
  - New generator: ascii_lr_strip
  - New generator: apostrophe
  - Add more vocabs files
  - Detokenize special tokens.
  - Replace errors with '\uFFFD' when detokenizing to 'utf-8'
  - More edge cases
  - Better detokenization results check

* Fix add_space_prefix, set false by default
* Better leading space removal
* Do not remove space when decoding special tokens
* Bugfix: custom regexs splits undefined unicode codepoints
* 'viking' detokenizer clean spaces
---
 common/common.cpp                             |  58 ++--
 common/common.h                               |  16 +-
 examples/batched.swift/Sources/main.swift     |   3 +-
 .../llama.cpp.swift/LibLlama.swift            |   4 +-
 include/llama.h                               |  19 +-
 src/llama.cpp                                 | 254 +++++++++-----
 src/unicode.cpp                               |  18 +-
 tests/test-tokenizer-0.cpp                    |  12 +-
 tests/test-tokenizer-1-bpe.cpp                |  35 +-
 tests/test-tokenizer-1-spm.cpp                |  33 +-
 tests/test-tokenizer-random.py                | 316 ++++++++++++------
 11 files changed, 501 insertions(+), 267 deletions(-)

diff --git a/common/common.cpp b/common/common.cpp
index 42ae85f5f11c2..c548bcb2857a8 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -2592,51 +2592,35 @@ std::vector llama_tokenize(
 }
 
 std::string llama_token_to_piece(const struct llama_context * ctx, llama_token token, bool special) {
-    std::vector result(8, 0);
-    const int n_tokens = llama_token_to_piece(llama_get_model(ctx), token, result.data(), result.size(), special);
-    if (n_tokens < 0) {
-        result.resize(-n_tokens);
-        int check = llama_token_to_piece(llama_get_model(ctx), token, result.data(), result.size(), special);
-        GGML_ASSERT(check == -n_tokens);
-    } else {
-        result.resize(n_tokens);
-    }
-
-    return std::string(result.data(), result.size());
-}
-
-std::string llama_detokenize_spm(llama_context * ctx, const std::vector & tokens) {
-    const llama_token bos_id = llama_token_bos(llama_get_model(ctx));
-
     std::string piece;
-    std::string result;
-
-    for (size_t i = 0; i < tokens.size(); ++i) {
-        piece = llama_token_to_piece(ctx, tokens[i]);
-
-        // remove the leading space of the first non-BOS token
-        if (((tokens[0] == bos_id && i == 1) || (tokens[0] != bos_id && i == 0)) && piece[0] == ' ') {
-            piece = piece.substr(1);
-        }
-
-        result += piece;
+    piece.resize(piece.capacity());  // using string internal cache, 15 bytes + '\n'
+    const int n_chars = llama_token_to_piece(llama_get_model(ctx), token, &piece[0], piece.size(), 0, special);
+    if (n_chars < 0) {
+        piece.resize(-n_chars);
+        int check = llama_token_to_piece(llama_get_model(ctx), token, &piece[0], piece.size(), 0, special);
+        GGML_ASSERT(check == -n_chars);
+    }
+    else {
+        piece.resize(n_chars);
     }
 
-    return result;
+    return piece;
 }
 
-std::string llama_detokenize_bpe(llama_context * ctx, const std::vector & tokens) {
-    std::string piece;
-    std::string result;
-
-    for (size_t i = 0; i < tokens.size(); ++i) {
-        piece = llama_token_to_piece(ctx, tokens[i]);
-
-        result += piece;
+std::string llama_detokenize(llama_context * ctx, const std::vector & tokens, bool special) {
+    std::string text;
+    text.resize(std::max(text.capacity(), tokens.size()));
+    int32_t n_chars = llama_detokenize(llama_get_model(ctx), tokens.data(), (int32_t)tokens.size(), &text[0], (int32_t)text.size(), false, special);
+    if (n_chars < 0) {
+        text.resize(-n_chars);
+        n_chars = llama_detokenize(llama_get_model(ctx), tokens.data(), (int32_t)tokens.size(), &text[0], (int32_t)text.size(), false, special);
+        GGML_ASSERT(n_chars <= (int32_t)text.size());  // whitespace trimming is performed after per-token detokenization
     }
 
+    text.resize(n_chars);
+
     // NOTE: the original tokenizer decodes bytes after collecting the pieces.
-    return result;
+    return text;
 }
 
 bool llama_should_add_bos_token(const llama_model * model) {
diff --git a/common/common.h b/common/common.h
index ac86483ffa1c9..dabf02b598b3b 100644
--- a/common/common.h
+++ b/common/common.h
@@ -350,21 +350,13 @@ std::string llama_token_to_piece(
                        llama_token   token,
                        bool          special = true);
 
-// TODO: these should be moved in llama.h C-style API under single `llama_detokenize` function
-//       that takes into account the tokenizer type and decides how to handle the leading space
-//
-// detokenizes a vector of tokens into a string
-// should work similar to Python's `tokenizer.decode`
-// removes the leading space from the first non-BOS token
-std::string llama_detokenize_spm(
-                         llama_context * ctx,
-        const std::vector & tokens);
-
 // detokenizes a vector of tokens into a string
 // should work similar to Python's `tokenizer.decode`
-std::string llama_detokenize_bpe(
+// optionally renders special/control tokens
+std::string llama_detokenize(
                          llama_context * ctx,
-        const std::vector & tokens);
+        const std::vector & tokens,
+                                  bool   special = true);
 
 // Uses the value from the model metadata if possible, otherwise
 // defaults to true when model type is SPM, otherwise false.
diff --git a/examples/batched.swift/Sources/main.swift b/examples/batched.swift/Sources/main.swift
index dbbd06da58183..616494d2d841d 100644
--- a/examples/batched.swift/Sources/main.swift
+++ b/examples/batched.swift/Sources/main.swift
@@ -229,7 +229,7 @@ private func tokenize(text: String, add_bos: Bool) -> [llama_token] {
 
 private func token_to_piece(token: llama_token, buffer: inout [CChar]) -> String? {
     var result = [CChar](repeating: 0, count: 8)
-    let nTokens = llama_token_to_piece(model, token, &result, Int32(result.count), false)
+    let nTokens = llama_token_to_piece(model, token, &result, Int32(result.count), 0, false)
     if nTokens < 0 {
         let actualTokensCount = -Int(nTokens)
         result = .init(repeating: 0, count: actualTokensCount)
@@ -238,6 +238,7 @@ private func token_to_piece(token: llama_token, buffer: inout [CChar]) -> String
             token,
             &result,
             Int32(result.count),
+            0,
             false
         )
         assert(check == actualTokensCount)
diff --git a/examples/llama.swiftui/llama.cpp.swift/LibLlama.swift b/examples/llama.swiftui/llama.cpp.swift/LibLlama.swift
index 737f882fb2d2e..2a3f9f75890fc 100644
--- a/examples/llama.swiftui/llama.cpp.swift/LibLlama.swift
+++ b/examples/llama.swiftui/llama.cpp.swift/LibLlama.swift
@@ -322,7 +322,7 @@ actor LlamaContext {
         defer {
             result.deallocate()
         }
-        let nTokens = llama_token_to_piece(model, token, result, 8, false)
+        let nTokens = llama_token_to_piece(model, token, result, 8, 0, false)
 
         if nTokens < 0 {
             let newResult = UnsafeMutablePointer.allocate(capacity: Int(-nTokens))
@@ -330,7 +330,7 @@ actor LlamaContext {
             defer {
                 newResult.deallocate()
             }
-            let nNewTokens = llama_token_to_piece(model, token, newResult, -nTokens, false)
+            let nNewTokens = llama_token_to_piece(model, token, newResult, -nTokens, 0, false)
             let bufferPointer = UnsafeBufferPointer(start: newResult, count: Int(nNewTokens))
             return Array(bufferPointer)
         } else {
diff --git a/include/llama.h b/include/llama.h
index 7a9a25609c9c1..865ace9944d02 100644
--- a/include/llama.h
+++ b/include/llama.h
@@ -904,6 +904,7 @@ extern "C" {
     /// @param tokens The tokens pointer must be large enough to hold the resulting tokens.
     /// @return Returns the number of tokens on success, no more than n_tokens_max
     /// @return Returns a negative number on failure - the number of tokens that would have been returned
+    /// @param add_special Allow to add BOS and EOS tokens if model is configured to do so.
     /// @param parse_special Allow tokenizing special and/or control tokens which otherwise are not exposed and treated
     ///                      as plaintext. Does not insert a leading space.
     LLAMA_API int32_t llama_tokenize(
@@ -918,15 +919,31 @@ extern "C" {
     // Token Id -> Piece.
     // Uses the vocabulary in the provided context.
     // Does not write null terminator to the buffer.
-    // User code is responsible to remove the leading whitespace of the first non-BOS token when decoding multiple tokens.
+    // User can skip up to 'lstrip' leading spaces before copying (useful when encoding/decoding multiple tokens with 'add_space_prefix')
     // @param special If true, special tokens are rendered in the output.
     LLAMA_API int32_t llama_token_to_piece(
               const struct llama_model * model,
                            llama_token   token,
                                   char * buf,
                                int32_t   length,
+                               int32_t   lstrip,
                                   bool   special);
 
+    /// @details Convert the provided tokens into text (inverse of llama_tokenize()).
+    /// @param text The char pointer must be large enough to hold the resulting text.
+    /// @return Returns the number of chars/bytes on success, no more than text_len_max.
+    /// @return Returns a negative number on failure - the number of chars/bytes that would have been returned.
+    /// @param remove_special Allow to remove BOS and EOS tokens if model is configured to do so.
+    /// @param unparse_special If true, special tokens are rendered in the output.
+    LLAMA_API int32_t llama_detokenize(
+        const struct llama_model * model,
+               const llama_token * tokens,
+                         int32_t   n_tokens,
+                            char * text,
+                         int32_t   text_len_max,
+                            bool   remove_special,
+                            bool   unparse_special);
+
     /// Apply chat template. Inspired by hf apply_chat_template() on python.
     /// Both "model" and "custom_template" are optional, but at least one is required. "custom_template" has higher precedence than "model"
     /// NOTE: This function does not use a jinja parser. It only support a pre-defined list of template. See more: https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template
diff --git a/src/llama.cpp b/src/llama.cpp
index 18956d441409f..b770ca5bc33fc 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -1995,18 +1995,19 @@ using llama_mlocks = std::vector>;
 
 // NOTE: avoid ever using this except for building the token_to_piece caches
 static std::string llama_token_to_piece(const struct llama_model * model, llama_token token, bool special) {
-    std::vector result(8, 0);
-    const int n_tokens = llama_token_to_piece(model, token, result.data(), result.size(), special);
-    if (n_tokens < 0) {
-        result.resize(-n_tokens);
-        int check = llama_token_to_piece(model, token, result.data(), result.size(), special);
-        GGML_ASSERT(check == -n_tokens);
+    std::string piece;
+    piece.resize(piece.capacity());  // using string internal cache
+    const int n_chars = llama_token_to_piece(model, token, &piece[0], piece.size(), 0, special);
+    if (n_chars < 0) {
+        piece.resize(-n_chars);
+        int check = llama_token_to_piece(model, token, &piece[0], piece.size(), 0, special);
+        GGML_ASSERT(check == -n_chars);
     }
     else {
-        result.resize(n_tokens);
+        piece.resize(n_chars);
     }
 
-    return std::string(result.data(), result.size());
+    return piece;
 }
 
 static ggml_backend_buffer_type_t llama_default_buffer_type_cpu(bool host_buffer) {
@@ -2586,10 +2587,11 @@ struct llama_vocab {
     id special_eot_id    = -1; // TODO: move above after "eos_id", and here add "file separator" token
 
     // tokenizer flags
-    bool tokenizer_add_space_prefix = true;
+    bool tokenizer_add_space_prefix = false;
     bool tokenizer_add_bos          = false;
     bool tokenizer_add_eos          = false;
     bool tokenizer_ignore_merges    = false;
+    bool tokenizer_clean_spaces     = false;  // clean_up_tokenization_spaces
     bool tokenizer_remove_extra_whitespaces   = false;
     bool tokenizer_escape_whitespaces         = true;
     bool tokenizer_treat_whitespace_as_suffix = false;
@@ -5230,11 +5232,6 @@ static void llm_load_vocab(
             vocab.special_pad_id  = -1;
             vocab.special_cls_id  = -1;
             vocab.special_mask_id = -1;
-
-            const int add_space_prefix_keyidx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_ADD_PREFIX).c_str());
-            if (add_space_prefix_keyidx != -1) {
-                vocab.tokenizer_add_space_prefix = gguf_get_val_bool(ctx, add_space_prefix_keyidx);
-            } // The default value of add_space_prefix is true.
         } else if (tokenizer_model == "bert") {
             vocab.type = LLAMA_VOCAB_TYPE_WPM;
 
@@ -5246,15 +5243,9 @@ static void llm_load_vocab(
             vocab.special_pad_id  = 0;
             vocab.special_cls_id  = 101;
             vocab.special_mask_id = 103;
-            vocab.tokenizer_add_space_prefix = false;
         } else if (tokenizer_model == "gpt2") {
             vocab.type = LLAMA_VOCAB_TYPE_BPE;
 
-            const int add_space_prefix_keyidx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_ADD_PREFIX).c_str());
-            if (add_space_prefix_keyidx != -1) {
-                vocab.tokenizer_add_space_prefix = gguf_get_val_bool(ctx, add_space_prefix_keyidx);
-            }
-
             // read bpe merges and populate bpe ranks
             const int merges_keyidx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_MERGES).c_str());
             if (merges_keyidx == -1) {
@@ -5333,6 +5324,8 @@ static void llm_load_vocab(
 
         // for now, only BPE models have pre-tokenizers
         if (vocab.type == LLAMA_VOCAB_TYPE_BPE) {
+            vocab.tokenizer_add_space_prefix = false;
+            vocab.tokenizer_clean_spaces = true;
             if (tokenizer_pre.empty()) {
                 LLAMA_LOG_WARN("%s: missing pre-tokenizer type, using: 'default'\n", __func__);
                 LLAMA_LOG_WARN("%s:                                             \n", __func__);
@@ -5354,9 +5347,11 @@ static void llm_load_vocab(
             } else if (
                     tokenizer_pre == "deepseek-llm") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEEPSEEK_LLM;
+                vocab.tokenizer_clean_spaces = false;
             } else if (
                     tokenizer_pre == "deepseek-coder") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEEPSEEK_CODER;
+                vocab.tokenizer_clean_spaces = false;
             } else if (
                     tokenizer_pre == "falcon") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_FALCON;
@@ -5368,6 +5363,7 @@ static void llm_load_vocab(
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_STARCODER;
             } else if (
                     tokenizer_pre == "gpt-2"   ||
+                    tokenizer_pre == "phi-2"   ||
                     tokenizer_pre == "jina-es" ||
                     tokenizer_pre == "jina-de" ||
                     tokenizer_pre == "jina-v2-es" ||
@@ -5383,6 +5379,7 @@ static void llm_load_vocab(
             } else if (
                 tokenizer_pre == "qwen2") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_QWEN2;
+                vocab.tokenizer_clean_spaces = false;
             } else if (
                 tokenizer_pre == "stablelm2") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_STABLELM2;
@@ -5398,9 +5395,11 @@ static void llm_load_vocab(
             } else if (
                 tokenizer_pre == "poro-chat") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_PORO;
+                vocab.tokenizer_clean_spaces = false;
             } else if (
                 tokenizer_pre == "viking") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_VIKING;
+                vocab.tokenizer_clean_spaces = false;
             } else if (
                 tokenizer_pre == "jais") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_JAIS;
@@ -5409,10 +5408,14 @@ static void llm_load_vocab(
             }
         } else if (vocab.type == LLAMA_VOCAB_TYPE_SPM) {
             vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
+            vocab.tokenizer_add_space_prefix = true;
+            vocab.tokenizer_clean_spaces = false;
             vocab.tokenizer_add_bos = true;
             vocab.tokenizer_add_eos = false;
         } else if (vocab.type == LLAMA_VOCAB_TYPE_WPM) {
             vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
+            vocab.tokenizer_add_space_prefix = false;
+            vocab.tokenizer_clean_spaces = true;
             vocab.tokenizer_add_bos = true;
             vocab.tokenizer_add_eos = false;
         } else if (vocab.type == LLAMA_VOCAB_TYPE_UGM) {
@@ -5422,6 +5425,11 @@ static void llm_load_vocab(
         } else {
             vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
         }
+
+        const int add_space_prefix_keyidx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_ADD_PREFIX).c_str());
+        if (add_space_prefix_keyidx != -1) {
+            vocab.tokenizer_add_space_prefix = gguf_get_val_bool(ctx, add_space_prefix_keyidx);
+        }
     }
 
     const int token_idx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_LIST).c_str());
@@ -5603,7 +5611,7 @@ static void llm_load_vocab(
             }
         }
 
-        std::sort( vocab.cache_special_tokens.begin(), vocab.cache_special_tokens.end(),
+        std::sort(vocab.cache_special_tokens.begin(), vocab.cache_special_tokens.end(),
             [&] (const llama_vocab::id a, const llama_vocab::id b) {
                 return vocab.id_to_token[a].text.size() > vocab.id_to_token[b].text.size();
             }
@@ -16098,7 +16106,7 @@ static std::vector llama_tokenize_internal(const llama_vocab &
                 // tokenizer.encode('', add_special_tokens=True)  returns [1]
                 // tokenizer.encode('', add_special_tokens=False) returns []
 
-                bool is_prev_special = false;
+                bool is_prev_special = true;  // prefix with space if first token
 
                 if (add_special && vocab.tokenizer_add_bos) {
                     GGML_ASSERT(vocab.special_bos_id != -1);
@@ -16110,10 +16118,9 @@ static std::vector llama_tokenize_internal(const llama_vocab &
                     if (fragment.type == FRAGMENT_BUFFER_VARIANT_TYPE_RAW_TEXT) {
                         auto raw_text = fragment.raw_text.substr(fragment.offset, fragment.length);
 
-                        if (vocab.tokenizer_add_space_prefix) {
-                            if (!output.size() || is_prev_special) {  // prefix with space if first token
-                                raw_text = " " + raw_text;
-                            }
+                        // prefix with space if previous is special
+                        if (vocab.tokenizer_add_space_prefix && is_prev_special) {
+                            raw_text = " " + raw_text;
                         }
 
 #ifdef PRETOKENIZERDEBUG
@@ -16122,6 +16129,7 @@ static std::vector llama_tokenize_internal(const llama_vocab &
                         llm_tokenizer_spm tokenizer(vocab);
                         llama_escape_whitespace(raw_text);
                         tokenizer.tokenize(raw_text, output);
+                        is_prev_special = false;
                     } else { // if (fragment.type == FRAGMENT_BUFFER_VARIANT_TYPE_TOKEN)
                         output.push_back(fragment.token);
                         is_prev_special = true;
@@ -20904,85 +20912,66 @@ static std::string llama_decode_text(const std::string & text) {
 }
 
 // does not write null-terminator to buf
-int32_t llama_token_to_piece(const struct llama_model * model, llama_token token, char * buf, int32_t length, bool special) {
+int32_t llama_token_to_piece(const struct llama_model * model, llama_token token, char * buf, int32_t length, int32_t lstrip, bool special) {
     // ref: https://github.com/ggerganov/llama.cpp/pull/7587#discussion_r1620983843
-    if (!special && llama_is_control_token(model->vocab, token)) {
+    static const int attr_special = LLAMA_TOKEN_ATTR_UNKNOWN | LLAMA_TOKEN_ATTR_CONTROL;
+    const llama_token_attr attr = llama_token_get_attr(model, token);
+    if (!special && (attr & attr_special)) {
         return 0;
     }
 
+    // copy piece chars to output text buffer
+    // skip up to 'lstrip' leading spaces before copying
+    auto _try_copy = [=] (const char * token, size_t size) -> int32_t {
+        for (int32_t i = 0; i < lstrip && size && *token == ' '; ++i) {
+            token++;
+            size--;
+        }
+        if (length < (int32_t)size) {
+            return (int32_t) -size;
+        }
+        memcpy(buf, token, size);
+        return (int32_t) size;
+    };
+
     // if we have a cache - use it
     {
         const auto & cache = model->vocab.cache_token_to_piece;
 
         if (!cache.empty()) {
-            const auto & res = cache.at(token);
-            if (length < (int) res.size()) {
-                return -(int) res.size();
-            }
-            memcpy(buf, res.c_str(), res.size());
-            return res.size();
+            const auto & result = cache.at(token);
+            return _try_copy(result.data(), result.size());
         }
     }
 
     if (0 <= token && token < llama_n_vocab(model)) {
+        const std::string & token_text = model->vocab.id_to_token[token].text;
         switch (llama_vocab_get_type(model->vocab)) {
             case LLAMA_VOCAB_TYPE_WPM:
             case LLAMA_VOCAB_TYPE_SPM:
             case LLAMA_VOCAB_TYPE_UGM: {
                 // NOTE: we accept all unsupported token types,
                 // suppressing them like CONTROL tokens.
-                if (llama_is_normal_token(model->vocab, token)) {
-                    std::string result = model->vocab.id_to_token[token].text;
+                if (attr & (attr_special | LLAMA_TOKEN_ATTR_USER_DEFINED)) {
+                    return _try_copy(token_text.data(), token_text.size());
+                } else if (attr & LLAMA_TOKEN_ATTR_NORMAL) {
+                    std::string result = token_text;
                     llama_unescape_whitespace(result);
-                    if (length < (int) result.length()) {
-                        return -(int) result.length();
-                    }
-                    memcpy(buf, result.c_str(), result.length());
-                    return result.length();
-                } else if (
-                        (llama_is_user_defined_token(model->vocab, token)) ||
-                        (llama_is_control_token     (model->vocab, token) && special)) {
-                    std::string result = model->vocab.id_to_token[token].text;
-                    if (length < (int) result.length()) {
-                        return -(int) result.length();
-                    }
-                    memcpy(buf, result.c_str(), result.length());
-                    return result.length();
-                } else if (llama_is_unknown_token(model->vocab, token)) { // NOLINT
-                    if (length < 3) {
-                        return -3;
-                    }
-                    memcpy(buf, "\xe2\x96\x85", 3);
-                    return 3;
-                } else if (llama_is_byte_token(model->vocab, token)) {
-                    if (length < 1) {
-                        return -1;
-                    }
-                    buf[0] = llama_token_to_byte(model->vocab, token);
-                    return 1;
+                    return _try_copy(result.data(), result.size());
+                } else if (attr & LLAMA_TOKEN_ATTR_BYTE) {
+                    char byte = (char) llama_token_to_byte(model->vocab, token);
+                    return _try_copy((char*) &byte, 1);
                 }
                 break;
             }
             case LLAMA_VOCAB_TYPE_BPE: {
                 // NOTE: we accept all unsupported token types,
                 // suppressing them like CONTROL tokens.
-                if (llama_is_normal_token(model->vocab, token)) {
-                    std::string result = model->vocab.id_to_token[token].text;
-                    result = llama_decode_text(result);
-                    if (length < (int) result.length()) {
-                        return -(int) result.length();
-                    }
-                    memcpy(buf, result.c_str(), result.length());
-                    return result.length();
-                } else if (
-                        (llama_is_user_defined_token(model->vocab, token)) ||
-                        (llama_is_control_token     (model->vocab, token) && special)) {
-                    std::string result = model->vocab.id_to_token[token].text;
-                    if (length < (int) result.length()) {
-                        return -(int) result.length();
-                    }
-                    memcpy(buf, result.c_str(), result.length());
-                    return result.length();
+                if (attr & (attr_special | LLAMA_TOKEN_ATTR_USER_DEFINED)) {
+                    return _try_copy(token_text.data(), token_text.size());
+                } else if (attr & LLAMA_TOKEN_ATTR_NORMAL) {
+                    std::string result = llama_decode_text(token_text);
+                    return _try_copy(result.data(), result.size());
                 }
                 break;
             }
@@ -20993,6 +20982,113 @@ int32_t llama_token_to_piece(const struct llama_model * model, llama_token token
     return 0;
 }
 
+int32_t llama_detokenize(
+        const struct llama_model * model,
+               const llama_token * tokens,
+                         int32_t   n_tokens,
+                            char * text,
+                         int32_t   text_len_max,
+                            bool   remove_special,
+                            bool   unparse_special) {
+    int32_t avail = text_len_max;
+    int32_t total = 0;
+
+    // remove the leading space
+    bool remove_space = model->vocab.tokenizer_add_space_prefix;
+
+    if (remove_special && model->vocab.tokenizer_add_bos) {
+        if (n_tokens > 0 && tokens[0] == model->vocab.special_bos_id) {
+            remove_space = false;
+            n_tokens--;
+            tokens++;
+        }
+    }
+
+    if (remove_special && model->vocab.tokenizer_add_eos) {
+        if (n_tokens > 0 && tokens[n_tokens-1] == model->vocab.special_eos_id) {
+            n_tokens--;
+        }
+    }
+
+    for (int32_t i = 0; i < n_tokens; ++i) {
+        GGML_ASSERT(avail >= 0);
+        int32_t n_chars = llama_token_to_piece(model, tokens[i], text, avail, remove_space, unparse_special);
+        remove_space = false;
+        if (n_chars < 0) {
+            avail = 0;
+            total -= n_chars;
+        } else if (n_chars > 0) {
+            avail -= n_chars;
+            text  += n_chars;
+            total += n_chars;
+        }
+    }
+
+    if (total > text_len_max) {
+        return -total;
+    }
+
+    if (model->vocab.tokenizer_clean_spaces) {
+        text -= total;  // restart text
+
+        // first pass: characters ?!.,  //TODO: where do these characters come from?
+        const int32_t total1 = total;
+        total = total ? 1 : 0;
+        for (int32_t i = 1; i < total1; ++i) {
+            const char x = text[i];
+            if (text[i - 1] == ' ') {
+                if (x == '?' || x == '!' || x == '.' || x == ',') {  // " ?", " !", " .", " ,"
+                    total--;  // remove space
+                }
+            }
+            text[total++] = x;
+        }
+
+        // second pass: strip single apostrophe between spaces
+        const int32_t total2 = total;
+        total = total ? 1 : 0;
+        for (int32_t i = 1; i < total2; ++i) {
+            const char x = text[i];
+            if (x == '\'' && i + 1 < total2 && text[i - 1] == ' ' && text[i + 1] == ' ') {  // " ' "
+                total--;           // remove prev space
+                text[++i] = '\0';  // remove next space
+            }
+            text[total++] = x;
+        }
+
+        // third pass: apostrophe contractions  //NOTE: this makes sense?
+        const int32_t total3 = total;
+        total = total ? 1 : 0;
+        for (int32_t i = 1; i < total3; ++i) {
+            const char x = text[i];
+            if (text[i - 1] == ' ') {
+                if (x == '\'' && i + 1 < total3) {
+                    const char x1 = text[i + 1];
+                    if (x1 == 't' || x1 == 'd') {  // " 't", " 'd"
+                        //total--;  // remove space
+                    } else if (x1 == 's' || x1 == 'm') {  // " 's", " 'm"
+                        total--;  // remove space
+                    } else if (i + 2 < total3) {
+                        const char x2 = text[i + 2];
+                        if ((x1 == 'l' && x2 == 'l')) {  // " 'll"
+                            //total--;  // remove space
+                        } else if ((x1 == 'r' && x2 == 'e') || (x1 == 'v' && x2 == 'e')) {  // " 're", " 've"
+                            total--;  // remove space
+                        } else {
+                            //total--;  // remove space
+                        }
+                    } else {
+                        //total--;  // remove space
+                    }
+                }
+            }
+            text[total++] = x;
+        }
+    }
+
+    return total <= text_len_max ? total : -total;
+}
+
 // trim whitespace from the beginning and end of a string
 static std::string trim(const std::string & str) {
     size_t start = 0;
diff --git a/src/unicode.cpp b/src/unicode.cpp
index 8692924b957cc..51daa15afa669 100644
--- a/src/unicode.cpp
+++ b/src/unicode.cpp
@@ -232,8 +232,7 @@ static std::vector unicode_regex_split_custom_gpt2(const std::string & t
         };
 
         auto _get_flags = [&] (const size_t pos) -> codepoint_flags {
-            static const codepoint_flags undef(codepoint_flags::UNDEFINED);
-            return (offset_ini <= pos && pos < offset_end) ? unicode_cpt_flags(cpts[pos]) : undef;
+            return (offset_ini <= pos && pos < offset_end) ? unicode_cpt_flags(cpts[pos]) : codepoint_flags{};
         };
 
         size_t _prev_end = offset_ini;
@@ -295,9 +294,9 @@ static std::vector unicode_regex_split_custom_gpt2(const std::string & t
                 continue;
             }
             // regex: ?[^\s\p{L}\p{N}]+
-            if (!(flags2.is_whitespace || flags2.is_letter || flags2.is_number || flags2.is_undefined)) {
+            if (!(flags2.is_whitespace | flags2.is_letter | flags2.is_number) && flags2.as_uint()) {
                 pos += (cpt == ' ');
-                while (!(flags2.is_whitespace || flags2.is_letter || flags2.is_number || flags2.is_undefined)) {
+                while (!(flags2.is_whitespace | flags2.is_letter | flags2.is_number) && flags2.as_uint()) {
                     flags2 = _get_flags(++pos);
                 }
                 _add_token(pos);
@@ -351,8 +350,7 @@ static std::vector unicode_regex_split_custom_llama3(const std::string &
         };
 
         auto _get_flags = [&] (const size_t pos) -> codepoint_flags {
-            static const codepoint_flags undef(codepoint_flags::UNDEFINED);
-            return (offset_ini <= pos && pos < offset_end) ? unicode_cpt_flags(cpts[pos]) : undef;
+            return (offset_ini <= pos && pos < offset_end) ? unicode_cpt_flags(cpts[pos]) : codepoint_flags{};
         };
 
         size_t _prev_end = offset_ini;
@@ -394,8 +392,8 @@ static std::vector unicode_regex_split_custom_llama3(const std::string &
                 }
             }
 
-            // regex: [^\r\n\p{L}\p{N}]?\p{L}+  //####FIXME: the first \p{L} is correct?
-            if (!(cpt == '\r' || cpt == '\n' || /*flags.is_letter |*/ flags.is_number)) {
+            // regex: [^\r\n\p{L}\p{N}]?\p{L}+
+            if (!(cpt == '\r' || cpt == '\n' || flags.is_number)) {
                 if (flags.is_letter || _get_flags(pos+1).is_letter) {  // one or more letters
                     pos++;
                     while (_get_flags(pos).is_letter) {
@@ -421,9 +419,9 @@ static std::vector unicode_regex_split_custom_llama3(const std::string &
 
             // regex: ?[^\s\p{L}\p{N}]+[\r\n]*
             auto flags2 = (cpt == ' ' ? _get_flags(pos+1) : flags);
-            if (!(flags2.is_whitespace || flags2.is_letter || flags2.is_number || flags2.is_undefined)) {
+            if (!(flags2.is_whitespace | flags2.is_letter | flags2.is_number) && flags.as_uint()) {
                 pos += (cpt == ' ');
-                while (!(flags2.is_whitespace || flags2.is_letter || flags2.is_number || flags2.is_undefined)) {
+                while (!(flags2.is_whitespace | flags2.is_letter | flags2.is_number) && flags2.as_uint()) {
                     flags2 = _get_flags(++pos);
                 }
                 uint32_t cpt2 = _get_cpt(pos);
diff --git a/tests/test-tokenizer-0.cpp b/tests/test-tokenizer-0.cpp
index d478f104148a6..1f04b6f34ad7e 100644
--- a/tests/test-tokenizer-0.cpp
+++ b/tests/test-tokenizer-0.cpp
@@ -195,11 +195,11 @@ int main(int argc, char **argv) {
     const bool add_special = false;
 
     for (const auto & test_kv : k_tests) {
-        const std::vector res = llama_tokenize(ctx, test_kv.first, add_special);
+        const std::vector res = llama_tokenize(ctx, test_kv.first, add_special, true);
 
         printf("\n");
         printf("src: '%s'\n", test_kv.first.c_str());
-        printf("res: '%s'\n", llama_detokenize_bpe(ctx, res).c_str());
+        printf("res: '%s'\n", llama_detokenize(ctx, res).c_str());
         printf("tok: ");
         for (const auto & tok : res) {
             printf("%d ", tok);
@@ -216,8 +216,8 @@ int main(int argc, char **argv) {
         if (!correct) {
             fprintf(stderr, "%s : failed test:    '%s'\n", __func__, test_kv.first.c_str());
             fprintf(stderr, "%s : detokenized to: '%s' instead of '%s'\n", __func__,
-                llama_detokenize_bpe(ctx, res).c_str(),
-                llama_detokenize_bpe(ctx, test_kv.second).c_str());
+                llama_detokenize(ctx, res).c_str(),
+                llama_detokenize(ctx, test_kv.second).c_str());
             fprintf(stderr, "%s : expected tokens: ", __func__);
             for (const auto & t : test_kv.second) {
                 fprintf(stderr, "%6d '%s', ", t, llama_token_to_piece(ctx, t).c_str());
@@ -253,7 +253,7 @@ int main(int argc, char **argv) {
         {
             const auto t_start = ggml_time_us();
 
-            res = llama_tokenize(ctx, text, add_special);
+            res = llama_tokenize(ctx, text, add_special, true);
 
             const auto t_end = ggml_time_us();
 
@@ -272,7 +272,7 @@ int main(int argc, char **argv) {
             }
 
             for (const auto & tok : res) {
-                //ofs << tok << " '" << string_strip(llama_detokenize_bpe(ctx, std::vector{tok})) << "'" << std::endl;
+                //ofs << tok << " '" << string_strip(llama_detokenize(ctx, std::vector{tok})) << "'" << std::endl;
                 ofs << tok << "\n";
             }
         }
diff --git a/tests/test-tokenizer-1-bpe.cpp b/tests/test-tokenizer-1-bpe.cpp
index 209a04ad6f77a..9498387e0f212 100644
--- a/tests/test-tokenizer-1-bpe.cpp
+++ b/tests/test-tokenizer-1-bpe.cpp
@@ -11,6 +11,7 @@
 #include 
 #include 
 #include 
+#include 
 
 int main(int argc, char **argv) {
     if (argc < 2 || argc > 3) {
@@ -63,7 +64,10 @@ int main(int argc, char **argv) {
         }
     }
 
-    GGML_ASSERT(llama_vocab_type(model) == LLAMA_VOCAB_TYPE_BPE);
+    //GGML_ASSERT(llama_vocab_type(model) == LLAMA_VOCAB_TYPE_BPE);
+    if (llama_vocab_type(model) != LLAMA_VOCAB_TYPE_BPE) {
+        return 99;
+    }
 
 #ifdef _WIN32
     // We need this for unicode console support
@@ -74,7 +78,7 @@ int main(int argc, char **argv) {
     const int n_vocab = llama_n_vocab(model);
 
     for (int i = 0; i < n_vocab; ++i) {
-        std::string str = llama_detokenize_bpe(ctx, std::vector(1, i));
+        std::string str = llama_detokenize(ctx, std::vector(1, i));
         try {
             auto cps = unicode_cpts_from_utf8(str);
             std::vector tokens = llama_tokenize(ctx, str, false, true);
@@ -90,7 +94,7 @@ int main(int argc, char **argv) {
                 fprintf(stderr, "]\n");
                 return 2;
             }
-            std::string check = llama_detokenize_bpe(ctx, tokens);
+            std::string check = llama_detokenize(ctx, tokens);
             if (check != str) {
                 fprintf(stderr, "%s : error: token %d detokenizes to '%s'(%zu) but tokenization of this detokenizes to '%s'(%zu)\n",
                     __func__, i, str.c_str(), str.length(), check.c_str(), check.length());
@@ -108,26 +112,23 @@ int main(int argc, char **argv) {
 
         std::vector threads(nthread);
 
+        std::atomic_int errcode = {};
+
         for (int i = 0; i < nthread; ++i) {
-            threads[i] = std::thread([i, nthread, ctx]() {
-                for (uint32_t cp = i; cp < 0x0010ffff; cp += nthread) {
-                    if (!( // NOLINT
-                                (cp < 0x03       || cp >  0x05)   && cp != 0x0b && cp != 0x11 &&
-                                (cp < 0x13       || cp >  0x17)   && cp != 0x19 &&
-                                (cp < 0x1c       || cp >  0x1e)   &&
-                                (cp < 0xd800     || cp >  0xdfff) &&
-                                (cp < 0x00040000 || cp >= 0x000e0000)
-                        )) {
+            threads[i] = std::thread([i, nthread, ctx, &errcode]() {
+                for (uint32_t cp = i; !errcode && cp < 0x00110000; cp += nthread) {
+                    if ((0x0000D800 <= cp && cp <= 0x0000DFFF) ||  // surrogates \p{Cs}
+                        (0x00040000 <= cp && cp <= 0x000E0000)) {  // undefined  \p{Cn}
                         continue;
                     }
 
                     std::string str = unicode_cpt_to_utf8(cp);
                     std::vector tokens = llama_tokenize(ctx, str, false);
-                    std::string check = llama_detokenize_bpe(ctx, tokens);
+                    std::string check = llama_detokenize(ctx, tokens);
                     if (cp != 9601 && str != check) {
-                        fprintf(stderr, "error: codepoint %x detokenizes to '%s'(%zu) instead of '%s'(%zu)\n",
+                        fprintf(stderr, "error: codepoint 0x%x detokenizes to '%s'(%zu) instead of '%s'(%zu)\n",
                                 cp, check.c_str(), check.length(), str.c_str(), str.length());
-                        std::exit(3);
+                        errcode = 3;
                     }
                 }
             });
@@ -136,6 +137,10 @@ int main(int argc, char **argv) {
         for (auto & t : threads) {
             t.join();
         }
+
+        if (errcode) {
+            return errcode;
+        }
     }
 
     llama_free_model(model);
diff --git a/tests/test-tokenizer-1-spm.cpp b/tests/test-tokenizer-1-spm.cpp
index ac2333ddaf886..7ca9e2ca6a671 100644
--- a/tests/test-tokenizer-1-spm.cpp
+++ b/tests/test-tokenizer-1-spm.cpp
@@ -11,6 +11,7 @@
 #include 
 #include 
 #include 
+#include 
 
 int main(int argc, char ** argv) {
     if (argc < 2) {
@@ -51,7 +52,10 @@ int main(int argc, char ** argv) {
         }
     }
 
-    GGML_ASSERT(llama_vocab_type(model) == LLAMA_VOCAB_TYPE_SPM);
+    //GGML_ASSERT(llama_vocab_type(model) == LLAMA_VOCAB_TYPE_SPM);
+    if (llama_vocab_type(model) != LLAMA_VOCAB_TYPE_SPM) {
+        return 99;
+    }
 
 #ifdef _WIN32
     // We need this for unicode console support
@@ -62,9 +66,9 @@ int main(int argc, char ** argv) {
     const int n_vocab = llama_n_vocab(model);
 
     for (int i = 0; i < n_vocab; ++i) {
-        std::string str = llama_detokenize_spm(ctx, std::vector(1, i));
-        std::vector tokens = llama_tokenize(ctx, str, false);
-        std::string check = llama_detokenize_spm(ctx, tokens);
+        std::string str = llama_detokenize(ctx, std::vector(1, i), true);
+        std::vector tokens = llama_tokenize(ctx, str, false, true);
+        std::string check = llama_detokenize(ctx, tokens);
         if (check != str) {
             fprintf(stderr, "%s : error: token %d detokenizes to '%s'(%zu) but tokenization of this detokenizes to '%s'(%zu)\n",
                 __func__, i, str.c_str(), str.length(), check.c_str(), check.length());
@@ -78,20 +82,23 @@ int main(int argc, char ** argv) {
 
         std::vector threads(nthread);
 
+        std::atomic_int errcode = {};
+
         for (int i = 0; i < nthread; ++i) {
-            threads[i] = std::thread([i, nthread, ctx]() {
-                for (uint32_t cp = i; cp < 0x0010ffff; cp += nthread) {
-                    if (cp >= 0xd800 && cp <= 0xdfff) {
+            threads[i] = std::thread([i, nthread, ctx, &errcode]() {
+                for (uint32_t cp = i; !errcode && cp < 0x00110000; cp += nthread) {
+                    if ((0x0000D800 <= cp && cp <= 0x0000DFFF) ||  // surrogates \p{Cs}
+                        (0x00040000 <= cp && cp <= 0x000E0000)) {  // undefined \p{Cn}
                         continue;
                     }
 
                     std::string str = unicode_cpt_to_utf8(cp);
-                    std::vector tokens = llama_tokenize(ctx, str, false);
-                    std::string check = llama_detokenize_spm(ctx, tokens);
+                    std::vector tokens = llama_tokenize(ctx, str, false, true);
+                    std::string check = llama_detokenize(ctx, tokens);
                     if (cp != 9601 && str != check) {
-                        fprintf(stderr, "error: codepoint %x detokenizes to '%s'(%zu) instead of '%s'(%zu)\n",
+                        fprintf(stderr, "error: codepoint 0x%x detokenizes to '%s'(%zu) instead of '%s'(%zu)\n",
                                 cp, check.c_str(), check.length(), str.c_str(), str.length());
-                        std::exit(3);
+                        errcode = 3;
                     }
                 }
             });
@@ -100,6 +107,10 @@ int main(int argc, char ** argv) {
         for (auto & t : threads) {
             t.join();
         }
+
+        if(errcode) {
+            return errcode;
+        }
     }
 
     llama_free_model(model);
diff --git a/tests/test-tokenizer-random.py b/tests/test-tokenizer-random.py
index a07c52fb3fc60..48cab8a1e0859 100644
--- a/tests/test-tokenizer-random.py
+++ b/tests/test-tokenizer-random.py
@@ -13,7 +13,7 @@
 import random
 import unicodedata
 
-from typing import Callable, Iterator
+from typing import Iterator
 
 import cffi
 from transformers import AutoTokenizer
@@ -24,17 +24,20 @@
 
 class LibLlama:
 
-    DEFAULT_PATH_LLAMA_H = "./llama.h"
-    DEFAULT_PATH_LIBLLAMA = "./build/libllama.so"  # CMakeLists.txt: BUILD_SHARED_LIBS ON
+    DEFAULT_PATH_LLAMA_H = "./include/llama.h"
+    DEFAULT_PATH_INCLUDES = ["./ggml/include/", "./include/"]
+    DEFAULT_PATH_LIBLLAMA = "./build/src/libllama.so"  # CMakeLists.txt: BUILD_SHARED_LIBS ON
 
-    def __init__(self, path_llama_h: str = None, path_libllama: str = None):
+    def __init__(self, path_llama_h: str = None, path_includes: list[str] = [], path_libllama: str = None):
         path_llama_h = path_llama_h or self.DEFAULT_PATH_LLAMA_H
+        path_includes = path_includes or self.DEFAULT_PATH_INCLUDES
         path_libllama = path_libllama or self.DEFAULT_PATH_LIBLLAMA
-        (self.ffi, self.lib) = self._load_libllama_cffi(path_llama_h, path_libllama)
+        (self.ffi, self.lib) = self._load_libllama_cffi(path_llama_h, path_includes, path_libllama)
         self.lib.llama_backend_init()
 
-    def _load_libllama_cffi(self, path_llama_h: str, path_libllama: str):
-        cmd = ["gcc", "-E", "-P", "-D__restrict=", "-D__attribute__(x)=", "-D__asm__(x)=", path_llama_h]
+    def _load_libllama_cffi(self, path_llama_h: str, path_includes: list[str], path_libllama: str):
+        cmd = ["gcc", "-E", "-P", "-D__restrict=", "-D__attribute__(x)=", "-D__asm__(x)="]
+        cmd += ["-I" + path for path in path_includes] + [path_llama_h]
         res = subprocess.run(cmd, stdout=subprocess.PIPE)
         assert (res.returncode == 0)
         source = res.stdout.decode()
@@ -79,6 +82,7 @@ def __init__(self, libllama: LibLlama, path_model: str, mparams={}, cparams={}):
             raise RuntimeError("error: failed to create context for model '%s'" % path_model)
         n_tokens_max = self.lib.llama_n_ctx(self.ctx)
         self.token_ids = self.ffi.new("llama_token[]", n_tokens_max)
+        self.text_buff = self.ffi.new("uint8_t[]", 1024)
 
     def free(self):
         if self.ctx:
@@ -89,14 +93,78 @@ def free(self):
         self.model = None
         self.lib = None
 
-    def tokenize(self, text: str, n_tokens_max: int = 0, add_special: bool = False, parse_special: bool = False) -> list[int]:
-        n_tokens_max = n_tokens_max if n_tokens_max > 0 else len(self.token_ids)
+    def tokenize(self, text: str, add_special: bool = False, parse_special: bool = False) -> list[int]:
         text = text.encode("utf-8")
-        num = self.lib.llama_tokenize(self.model, text, len(text), self.token_ids, n_tokens_max, add_special, parse_special)
-        if num < 0:
-            return []
+        num = self.lib.llama_tokenize(self.model, text, len(text), self.token_ids, len(self.token_ids), add_special, parse_special)
+        while num < 0 and len(self.token_ids) < (16 << 20):
+            self.token_ids = self.ffi.new("llama_token[]", -2 * num)
+            num = self.lib.llama_tokenize(self.model, text, len(text), self.token_ids, len(self.token_ids), add_special, parse_special)
         return list(self.token_ids[0:num])
 
+    def detokenize(self, ids: list[int], remove_special: bool = False, unparse_special: bool = False) -> str:
+        if len(self.token_ids) < len(ids):
+            self.token_ids = self.ffi.new("llama_token[]", 2 * len(ids))
+        for i, id in enumerate(ids):
+            self.token_ids[i] = id
+        num = self.lib.llama_detokenize(self.model, self.token_ids, len(ids), self.text_buff, len(self.text_buff), remove_special, unparse_special)
+        while num < 0 and len(self.text_buff) < (16 << 20):
+            self.text_buff = self.ffi.new("uint8_t[]", -2 * num)
+            num = self.lib.llama_detokenize(self.model, self.token_ids, len(ids), self.text_buff, len(self.text_buff), remove_special, unparse_special)
+        return str(self.ffi.buffer(self.text_buff, num), encoding="utf-8", errors="replace")  # replace errors with '\uFFFD'
+
+
+class Tokenizer:
+
+    def encode(self, text: str) -> list[int]:
+        raise NotImplementedError
+
+    def decode(self, ids: list[int]) -> str:
+        raise NotImplementedError
+
+
+class TokenizerGroundtruth (Tokenizer):
+
+    def __init__(self, dir_tokenizer: str):
+        self.model = AutoTokenizer.from_pretrained(dir_tokenizer)
+        # guess BOS and EOS
+        ids = self.encode("a")
+        assert 1 <= len(ids) <= 3
+        add_bos_token = len(ids) > 1 and self.model.bos_token_id == ids[0]
+        add_eos_token = len(ids) > 1 and self.model.eos_token_id == ids[-1]
+        self.add_bos_token = getattr(self.model, "add_bos_token", add_bos_token)
+        self.add_eos_token = getattr(self.model, "add_eos_token", add_eos_token)
+        # build vocab
+        tokens = list(self.model.get_vocab().values())
+        self.vocab = self.model.batch_decode(tokens, skip_special_tokens=True)
+        self.vocab = list(sorted(self.vocab))
+        # tokens and lists
+        self.special_tokens = list(self.model.all_special_tokens)
+        self.added_tokens   = list(self.model.added_tokens_encoder)
+        self.bos_token = self.model.bos_token
+        self.eos_token = self.model.eos_token
+
+    def encode(self, text: str) -> list[int]:
+        return self.model.encode(text, add_special_tokens=True)
+
+    def decode(self, ids: list[int]) -> str:
+        return self.model.decode(ids, skip_special_tokens=False)
+
+
+class TokenizerLlamaCpp (Tokenizer):
+
+    libllama: LibLlama = None
+
+    def __init__(self, vocab_file: str):
+        if not self.libllama:
+            self.libllama = LibLlama()
+        self.model = LibLlamaModel(self.libllama, vocab_file, mparams=dict(vocab_only=True), cparams=dict(n_ctx=4096))
+
+    def encode(self, text: str) -> list[int]:
+        return self.model.tokenize(text, add_special=True, parse_special=True)
+
+    def decode(self, ids: list[int]) -> str:
+        return self.model.detokenize(ids, remove_special=False, unparse_special=True)
+
 
 def generator_custom_text() -> Iterator[str]:
     """General tests"""
@@ -165,19 +233,48 @@ def generator_custom_text_edge_cases() -> Iterator[str]:
         'a  b',        # rstrip phi-3
         'a  b',      # lstrip jina-v2
         '\xa0aC',          # deepseek
+        '\u2029 \uA3E4',   # deepseek-llm
+        "a ?",
+        'å',               # mpt
+        '\U000ac517',      # utf-8 encode error, falcon
+        '\U000522f4',      # utf-8 encode error, starcoder
+        "abcd",
+        "  abcd",
     ]
 
 
-def generator_vocab_words(vocab: list[str]) -> Iterator[str]:
+def generator_vocab_words(tokenizer: TokenizerGroundtruth) -> Iterator[str]:
     """Brute force check all vocab words"""
-    yield from vocab
-
-
-def generator_added_lr_strip(tokenizer) -> Iterator[str]:
-    WHITESPACES = ["", " ", "  ", "    "]
-    special_tokens = list(tokenizer.all_special_tokens)
-    added_tokens   = list(tokenizer.added_tokens_encoder)
-    all_tokens     = list(sorted(set(special_tokens + added_tokens)))
+    yield from tokenizer.vocab
+
+
+def generator_ascii_lr_strip() -> Iterator[str]:
+    WHITESPACES = ["", " ", "  "]
+    CHARACTERS = list(chr(i) for i in range(1, 0x80)) + [""]
+    for char1 in CHARACTERS:
+        for char2 in CHARACTERS:
+            for lstrip in WHITESPACES:
+                for rstrip in WHITESPACES:
+                    yield lstrip + char1 + char2 + rstrip
+                    yield lstrip + char1 + rstrip + char2
+                    yield char1 + lstrip + char2 + rstrip
+
+
+def generator_apostrophe() -> Iterator[str]:
+    WHITESPACES = ["", " ", "  "]
+    CHARACTERS = list(chr(i) for i in range(1, 0x80)) + [""]
+    for char1 in CHARACTERS:
+        for char2 in CHARACTERS:
+            for lstrip in WHITESPACES:
+                for rstrip in WHITESPACES:
+                    yield char1 + lstrip + "'" + rstrip + char2
+                    yield char1 + char2 + lstrip + "'" + rstrip + "z"
+                    yield "a" + lstrip + "'" + rstrip + char1 + char2
+
+
+def generator_added_lr_strip(tokenizer: TokenizerGroundtruth) -> Iterator[str]:
+    WHITESPACES = ["", " ", "  ", "\n", "\r\n", "\n\n", "\t", "\t\t"]
+    all_tokens = list(sorted(set(tokenizer.special_tokens + tokenizer.added_tokens)))
     for token in all_tokens:
         for lstrip in WHITESPACES:
             for rstrip in WHITESPACES:
@@ -187,11 +284,9 @@ def generator_added_lr_strip(tokenizer) -> Iterator[str]:
                 yield "a" + lstrip + token + rstrip + "z"
 
 
-def generator_random_added_tokens(tokenizer, iterations=100) -> Iterator[str]:
-    special_tokens = list(tokenizer.all_special_tokens)
-    added_tokens   = list(tokenizer.added_tokens_encoder)
-    separations    = [" ", "\n", "\t", "-", "!", "one", "1", "", ""]
-    all_tokens     = list(sorted(set(special_tokens + added_tokens + separations)))
+def generator_random_added_tokens(tokenizer: TokenizerGroundtruth, iterations=100) -> Iterator[str]:
+    separations = [" ", "\n", "\t", "-", "!", "one", "1", "", ""]
+    all_tokens  = list(sorted(set(tokenizer.special_tokens + tokenizer.added_tokens + separations)))
     rand = random.Random()
     for m in range(iterations):
         rand.seed(m)
@@ -242,13 +337,13 @@ def generator_unicodes() -> Iterator[str]:
     def _valid(cpt):
         if cpt >= 0x30000:  # unassigned and supplement­ary
             return False
-        if 0x00D800 <= cpt <= 0x00F8FF:  # Surrogates
-            return False
-        if unicodedata.category(chr(cpt)) == "Cn":
+        # if cpt == 0x2029:  # deepseek-llm
+        #    return False
+        if unicodedata.category(chr(cpt)) in ("Cn", "Cs", "Co"):  # undefined, surrogates, private
             return False
         return True
 
-    characters = [chr(cpt) for cpt in range(1, MAX_CODEPOINTS) if _valid(cpt)]
+    characters = [chr(cpt) for cpt in range(0, MAX_CODEPOINTS) if _valid(cpt)]
 
     yield from characters
 
@@ -273,11 +368,11 @@ def generator_random_unicodes(iterations=100) -> Iterator[str]:
         yield "".join(text)
 
 
-def generator_random_vocab_chars(vocab: list[str], iterations=100) -> Iterator[str]:
+def generator_random_vocab_chars(tokenizer: TokenizerGroundtruth, iterations=100) -> Iterator[str]:
     """Brute force random text with vocab characters"""
 
     vocab_chars = set()
-    for word in vocab:
+    for word in tokenizer.vocab:
         vocab_chars.update(word)
     vocab_chars = list(sorted(vocab_chars))
 
@@ -288,10 +383,10 @@ def generator_random_vocab_chars(vocab: list[str], iterations=100) -> Iterator[s
         yield "".join(text)
 
 
-def generator_random_vocab_words(vocab: list[str], iterations=100) -> Iterator[str]:
+def generator_random_vocab_words(tokenizer: TokenizerGroundtruth, iterations=100) -> Iterator[str]:
     """Brute force random text from vocab words"""
 
-    vocab = [w.strip() for w in vocab]
+    vocab = [w.strip() for w in tokenizer.vocab]
     yield from vocab
 
     rand = random.Random()
@@ -307,7 +402,7 @@ def generator_random_vocab_words(vocab: list[str], iterations=100) -> Iterator[s
         yield "".join(text)
 
 
-def compare_tokenizers(func_tokenize1: Callable, func_tokenize2: Callable, generator: Iterator[str]):
+def compare_tokenizers(tokenizer1: TokenizerGroundtruth, tokenizer2: TokenizerLlamaCpp, generator: Iterator[str]):
 
     def find_first_mismatch(ids1: list[int], ids2: list[int]):
         for i, (a, b) in enumerate(zip(ids1, ids2)):
@@ -317,34 +412,67 @@ def find_first_mismatch(ids1: list[int], ids2: list[int]):
             return -1
         return min(len(ids1), len(ids2))
 
-    t_tokenizer1 = 0
-    t_tokenizer2 = 0
+    def check_detokenizer(text: str, text1: str, text2: str) -> bool:
+        if text1 == text2:  # equal to TokenizerGroundtruth?
+            return True
+        # equal to source text?
+        if tokenizer1.add_bos_token:  # remove BOS
+            if text2.startswith(tokenizer1.bos_token):
+                text2 = text2[len(tokenizer1.bos_token):]
+        if tokenizer1.add_eos_token:  # remove EOS
+            if text2.endswith(tokenizer1.eos_token):
+                text2 = text2[:-len(tokenizer1.eos_token)]
+        return text == text2
+
+    t_encode1 = 0
+    t_encode2 = 0
+    t_decode1 = 0
+    t_decode2 = 0
     t_start = time.perf_counter()
-    num_errors = 10
+    encode_errors = 0
+    decode_errors = 0
+    MAX_ERRORS = 10
 
     logger.info("%s: %s" % (generator.__name__, "ini"))
     for text in generator:
+        # print(repr(text), text.encode())
         # print(repr(text), hex(ord(text[0])), text.encode())
         t0 = time.perf_counter()
-        ids1 = func_tokenize1(text)
+        ids1 = tokenizer1.encode(text)
         t1 = time.perf_counter()
-        ids2 = func_tokenize2(text)
+        ids2 = tokenizer2.encode(text)
         t2 = time.perf_counter()
-        t_tokenizer1 += t1 - t0
-        t_tokenizer2 += t2 - t1
-        if ids1 != ids2:
+        text1 = tokenizer1.decode(ids1)
+        t3 = time.perf_counter()
+        text2 = tokenizer2.decode(ids1)
+        t4 = time.perf_counter()
+        t_encode1 += t1 - t0
+        t_encode2 += t2 - t1
+        t_decode1 += t3 - t2
+        t_decode2 += t4 - t3
+        if encode_errors < MAX_ERRORS and ids1 != ids2:
             i = find_first_mismatch(ids1, ids2)
             ids1 = list(ids1)[max(0, i - 2) : i + 5 + 1]
             ids2 = list(ids2)[max(0, i - 2) : i + 5 + 1]
-            logger.error(" TokenIDs: " + str(ids1))
-            logger.error(" Expected: " + str(ids2))
+            logger.error(" Expected: " + str(ids1))
+            logger.error("   Result: " + str(ids2))
+            encode_errors += 1
+            logger.error(f" {encode_errors=}")
+        if decode_errors < MAX_ERRORS and not check_detokenizer(text, text1, text2):
+            i = find_first_mismatch(text1, text2)
+            text1 = list(text1[max(0, i - 2) : i + 5 + 1])
+            text2 = list(text2[max(0, i - 2) : i + 5 + 1])
+            logger.error(" Expected: " + " ".join(hex(ord(x)) for x in text1))
+            logger.error("   Result: " + " ".join(hex(ord(x)) for x in text2))
+            decode_errors += 1
+            logger.error(f" {decode_errors=}")
+        if encode_errors >= MAX_ERRORS and decode_errors >= MAX_ERRORS:
+            logger.error(f" EXIT: {encode_errors=} {decode_errors=}")
             # raise Exception()
-            num_errors += 1
-            if num_errors > 10:
-                break
+            break
 
     t_total = time.perf_counter() - t_start
-    logger.info("%s: end,  tok1: %.3f  tok2: %.3f  total: %.3f" % (generator.__name__, t_tokenizer1, t_tokenizer2, t_total))
+    logger.info(f"{generator.__name__}: end,  {t_encode1=:.3f} {t_encode2=:.3f}  {t_decode1=:.3f} {t_decode2=:.3f}  {t_total=:.3f}")
 
 
 def main(argv: list[str] = None):
@@ -357,74 +485,76 @@ def main(argv: list[str] = None):
     logging.basicConfig(level = logging.DEBUG if args.verbose else logging.INFO)
     logger.info(f"VOCABFILE: '{args.vocab_file}'")
 
-    model = LibLlamaModel(LibLlama(), args.vocab_file, mparams=dict(vocab_only=True), cparams=dict(n_ctx=4096))
-    tokenizer = AutoTokenizer.from_pretrained(args.dir_tokenizer)
-
-    def func_tokenize1(text: str):
-        return model.tokenize(text, add_special=True, parse_special=True)
-
-    def func_tokenize2(text: str):
-        return tokenizer.encode(text, add_special_tokens=True)
+    tokenizer1 = TokenizerGroundtruth(args.dir_tokenizer)
+    tokenizer2 = TokenizerLlamaCpp(args.vocab_file)
 
-    ids = func_tokenize2("a")
-    assert 1 <= len(ids) <= 3
-    add_bos_token = len(ids) > 1 and tokenizer.bos_token_id == ids[0]
-    add_eos_token = len(ids) > 1 and tokenizer.eos_token_id == ids[-1]
-    tokenizer.add_bos_token = getattr(tokenizer, "add_bos_token", add_bos_token)
-    tokenizer.add_eos_token = getattr(tokenizer, "add_eos_token", add_eos_token)
+    # compare_tokenizers(tokenizer1, tokenizer2, generator_custom_text())
+    # compare_tokenizers(tokenizer1, tokenizer2, generator_custom_text_edge_cases())
+    compare_tokenizers(tokenizer1, tokenizer2, generator_ascii_lr_strip())
+    compare_tokenizers(tokenizer1, tokenizer2, generator_apostrophe())
+    compare_tokenizers(tokenizer1, tokenizer2, generator_unicodes())
+    compare_tokenizers(tokenizer1, tokenizer2, generator_vocab_words(tokenizer1))
+    compare_tokenizers(tokenizer1, tokenizer2, generator_added_lr_strip(tokenizer1))
+    # compare_tokenizers(tokenizer1, tokenizer2, generator_random_added_tokens(tokenizer1, 10_000))
+    # compare_tokenizers(tokenizer1, tokenizer2, generator_random_chars(10_000))
+    # compare_tokenizers(tokenizer1, tokenizer2, generator_random_unicodes(10_000))
+    # compare_tokenizers(tokenizer1, tokenizer2, generator_random_vocab_chars(tokenizer1, 10_000))
+    # compare_tokenizers(tokenizer1, tokenizer2, generator_random_vocab_words(tokenizer1, 5_000))
 
-    vocab = list(sorted(tokenizer.batch_decode(list(tokenizer.get_vocab().values()), skip_special_tokens=True)))
-
-    compare_tokenizers(func_tokenize1, func_tokenize2, generator_custom_text())
-    compare_tokenizers(func_tokenize1, func_tokenize2, generator_custom_text_edge_cases())
-    compare_tokenizers(func_tokenize1, func_tokenize2, generator_unicodes())
-    compare_tokenizers(func_tokenize1, func_tokenize2, generator_vocab_words(vocab))
-    compare_tokenizers(func_tokenize1, func_tokenize2, generator_added_lr_strip(tokenizer))
-    compare_tokenizers(func_tokenize1, func_tokenize2, generator_random_added_tokens(tokenizer, 10_000))
-    compare_tokenizers(func_tokenize1, func_tokenize2, generator_random_chars(10_000))
-    compare_tokenizers(func_tokenize1, func_tokenize2, generator_random_unicodes(10_000))
-    compare_tokenizers(func_tokenize1, func_tokenize2, generator_random_vocab_chars(vocab, 10_000))
-    compare_tokenizers(func_tokenize1, func_tokenize2, generator_random_vocab_words(vocab, 5_000))
-
-    model.free()
+    tokenizer2.model.free()
 
 
 if __name__ == "__main__":
     # main()
 
+    if True:
+        logging.basicConfig(
+            level    = logging.DEBUG,
+            format   = "%(asctime)s.%(msecs)03d %(name)s %(levelname)s %(message)s",
+            datefmt  = "%Y-%m-%d %H:%M:%S",
+            filename = logger.name + ".log",
+            filemode = "a"
+        )
     logging.basicConfig(
         level    = logging.DEBUG,
-        format   = "%(asctime)s.%(msecs)03d %(name)s %(levelname)s %(message)s",
-        datefmt  = "%Y-%m-%d %H:%M:%S",
-        filename = logger.name + ".log",
-        filemode = "a"
+        format   = "%(levelname)s %(message)s",
     )
 
     path_tokenizers   = "./models/tokenizers/"
     path_vocab_format = "./models/ggml-vocab-%s.gguf"
 
-    # import os
-    # tokenizers = os.listdir(path_tokenizers)
     tokenizers = [
-        # "llama-spm",   # SPM
-        # "phi-3",       # SPM
-        # "bert-bge",    # WPM
-        # "jina-v2-en",  # WPM
-        "gpt-2",          # BPE
+        "llama-spm",      # SPM
+        "phi-3",          # SPM
+        "gemma",          # SPM
+        "gemma-2",        # SPM
+        "baichuan",       # SPM
+        "bert-bge",       # WPM
+        "jina-v2-en",     # WPM
         "llama-bpe",      # BPE
+        "phi-2",          # BPE
+        "deepseek-llm",   # BPE
+        "deepseek-coder", # BPE
         "falcon",         # BPE
+        "mpt",            # BPE
         "starcoder",      # BPE
+        "gpt-2",          # BPE
+        "stablelm2",      # BPE
+        "refact",         # BPE
+        "qwen2",          # BPE
+        "olmo",           # BPE
         "jina-v2-es",     # BPE
         "jina-v2-de",     # BPE
-        "jina-v2-code",   # BPE
         "smaug-bpe",      # BPE
-        "phi-2",          # BPE
-        "deepseek-coder", # BPE
-        "deepseek-llm",   # BPE
+        "poro-chat",      # BPE
+        "jina-v2-code",   # BPE
+        "viking",         # BPE
+        "jais",           # BPE
     ]
 
+    logger.info("=" * 50)
     for tokenizer in tokenizers:
-        logger.info("=" * 50)
+        logger.info("-" * 50)
         logger.info(f"TOKENIZER: '{tokenizer}'")
         vocab_file = path_vocab_format % tokenizer
         dir_tokenizer = path_tokenizers + "/" + tokenizer

From 87e25a1d1bd26eb06d1cab9e2ee4e14a7a0be33c Mon Sep 17 00:00:00 2001
From: Daniel Bevenius 
Date: Sat, 6 Jul 2024 09:22:16 +0200
Subject: [PATCH 116/326] llama : add early return for empty range (#8327)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

* llama : add early return for empty range

This commit adds an early return to the llama_kv_cache_seq_add and
llama_kv_cache_seq_div functions.

The motivation for adding this is to avoid looping over the cache
when the range is empty. I ran into this when using the self-extend
feature in main.cpp.

Signed-off-by: Daniel Bevenius 

* llama : add static_cast to fix CI warning/error

This commit attempts to fix the following warning/error:

```console
src/llama.cpp:7271:31: error:
comparison of integer expressions of different signedness:
‘int’ and ‘uint32_t’ {aka ‘unsigned int’} [-Werror=sign-compare]
 7271 |                         if (i < hparams.n_layer_dense_lead) {
      |                             ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
This can be reproduced locally by setting -Wsign-compare in the
Makefile.

Signed-off-by: Daniel Bevenius 

* squash! llama : add early return for empty range

Remove the setting of cache.head to 0 when the range is empty.

Signed-off-by: Daniel Bevenius 

* Update src/llama.cpp

---------

Signed-off-by: Daniel Bevenius 
Co-authored-by: Georgi Gerganov 
---
 src/llama.cpp | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/src/llama.cpp b/src/llama.cpp
index b770ca5bc33fc..b39906fd53b6f 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -3260,6 +3260,8 @@ static void llama_kv_cache_seq_add(
 
     if (p0 < 0) p0 = 0;
     if (p1 < 0) p1 = std::numeric_limits::max();
+    // If there is no range then return early to avoid looping over the cache.
+    if (p0 == p1) return;
 
     if (cache.recurrent) {
         // for Mamba-like models, only the pos needs to be shifted
@@ -3304,6 +3306,8 @@ static void llama_kv_cache_seq_div(
                           int   d) {
     if (p0 < 0) p0 = 0;
     if (p1 < 0) p1 = std::numeric_limits::max();
+    // If there is no range then return early to avoid looping over the cache.
+    if (p0 == p1) return;
 
     if (cache.recurrent) {
         // for Mamba-like models, only the pos needs to be changed

From 60d83a0149849e9217e4b8ae26e277a41aea906e Mon Sep 17 00:00:00 2001
From: Xuan Son Nguyen 
Date: Sat, 6 Jul 2024 19:01:23 +0200
Subject: [PATCH 117/326] update main readme (#8333)

---
 README.md     | 43 ++++++++++++++++++++++++-------------------
 docs/build.md |  2 +-
 2 files changed, 25 insertions(+), 20 deletions(-)

diff --git a/README.md b/README.md
index a4bbf00bdae94..800b499e9d516 100644
--- a/README.md
+++ b/README.md
@@ -391,28 +391,21 @@ The `grammars/` folder contains a handful of sample grammars. To write your own,
 
 For authoring more complex JSON grammars, you can also check out https://grammar.intrinsiclabs.ai/, a browser app that lets you write TypeScript interfaces which it compiles to GBNF grammars that you can save for local use. Note that the app is built and maintained by members of the community, please file any issues or FRs on [its repo](http://github.com/intrinsiclabsai/gbnfgen) and not this one.
 
-### Obtaining and using the Facebook LLaMA 2 model
+## Build
 
-- Refer to [Facebook's LLaMA download page](https://ai.meta.com/resources/models-and-libraries/llama-downloads/) if you want to access the model data.
-- Alternatively, if you want to save time and space, you can download already converted and quantized models from [TheBloke](https://huggingface.co/TheBloke), including:
-  - [LLaMA 2 7B base](https://huggingface.co/TheBloke/Llama-2-7B-GGUF)
-  - [LLaMA 2 13B base](https://huggingface.co/TheBloke/Llama-2-13B-GGUF)
-  - [LLaMA 2 70B base](https://huggingface.co/TheBloke/Llama-2-70B-GGUF)
-  - [LLaMA 2 7B chat](https://huggingface.co/TheBloke/Llama-2-7B-chat-GGUF)
-  - [LLaMA 2 13B chat](https://huggingface.co/TheBloke/Llama-2-13B-chat-GGUF)
-  - [LLaMA 2 70B chat](https://huggingface.co/TheBloke/Llama-2-70B-chat-GGUF)
+Please refer to [Build llama.cpp locally](./docs/build.md)
 
-### Seminal papers and background on the models
+## Supported backends
 
-If your issue is with model generation quality, then please at least scan the following links and papers to understand the limitations of LLaMA models. This is especially important when choosing an appropriate model size and appreciating both the significant and subtle differences between LLaMA models and ChatGPT:
-- LLaMA:
-    - [Introducing LLaMA: A foundational, 65-billion-parameter large language model](https://ai.facebook.com/blog/large-language-model-llama-meta-ai/)
-    - [LLaMA: Open and Efficient Foundation Language Models](https://arxiv.org/abs/2302.13971)
-- GPT-3
-    - [Language Models are Few-Shot Learners](https://arxiv.org/abs/2005.14165)
-- GPT-3.5 / InstructGPT / ChatGPT:
-    - [Aligning language models to follow instructions](https://openai.com/research/instruction-following)
-    - [Training language models to follow instructions with human feedback](https://arxiv.org/abs/2203.02155)
+| Backend | Target devices |
+| --- | --- |
+| [Metal](./docs/build.md#metal-build) | Apple Silicon |
+| [BLAS](./docs/build.md#blas-build) | All |
+| [BLIS](./docs/backend/BLIS.md) | All |
+| [SYCL](./docs/backend/SYCL.md) | Intel and Nvidia GPU |
+| [CUDA](./docs/build.md#cuda) | Nvidia GPU |
+| [hipBLAS](./docs/build.md#hipblas) | AMD GPU |
+| [Vulkan](./docs/build.md#vulkan) | GPU |
 
 ## Tools
 
@@ -460,3 +453,15 @@ To learn more how to measure perplexity using llama.cpp, [read this documentatio
 - [Build on Android](./docs/android.md)
 - [Performance troubleshooting](./docs/token_generation_performance_tips.md)
 - [GGML tips & tricks](https://github.com/ggerganov/llama.cpp/wiki/GGML-Tips-&-Tricks)
+
+**Seminal papers and background on the models**
+
+If your issue is with model generation quality, then please at least scan the following links and papers to understand the limitations of LLaMA models. This is especially important when choosing an appropriate model size and appreciating both the significant and subtle differences between LLaMA models and ChatGPT:
+- LLaMA:
+    - [Introducing LLaMA: A foundational, 65-billion-parameter large language model](https://ai.facebook.com/blog/large-language-model-llama-meta-ai/)
+    - [LLaMA: Open and Efficient Foundation Language Models](https://arxiv.org/abs/2302.13971)
+- GPT-3
+    - [Language Models are Few-Shot Learners](https://arxiv.org/abs/2005.14165)
+- GPT-3.5 / InstructGPT / ChatGPT:
+    - [Aligning language models to follow instructions](https://openai.com/research/instruction-following)
+    - [Training language models to follow instructions with human feedback](https://arxiv.org/abs/2203.02155)
diff --git a/docs/build.md b/docs/build.md
index cf42a4eb93e19..bf41bfdf9c2f8 100644
--- a/docs/build.md
+++ b/docs/build.md
@@ -85,7 +85,7 @@ Building the program with BLAS support may lead to some performance improvements
 
 ### Accelerate Framework:
 
-  This is only available on Mac PCs and it's enabled by default. You can just build using the normal instructions.
+This is only available on Mac PCs and it's enabled by default. You can just build using the normal instructions.
 
 ### OpenBLAS:
 

From 86e7299ef5dff0f388922dc6fcbce009e99d8005 Mon Sep 17 00:00:00 2001
From: "Derrick T. Woolworth" 
Date: Sat, 6 Jul 2024 15:32:04 -0500
Subject: [PATCH 118/326] added support for Authorization Bearer tokens when
 downloading model (#8307)

* added support for Authorization Bearer tokens

* removed auth_token, removed set_ function, other small fixes

* Update common/common.cpp

---------

Co-authored-by: Xuan Son Nguyen 
---
 common/common.cpp | 44 +++++++++++++++++++++++++++++++++++++-------
 common/common.h   |  6 ++++--
 2 files changed, 41 insertions(+), 9 deletions(-)

diff --git a/common/common.cpp b/common/common.cpp
index c548bcb2857a8..fc0f3b350ec6e 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -190,6 +190,12 @@ int32_t cpu_get_num_math() {
 // CLI argument parsing
 //
 
+void gpt_params_handle_hf_token(gpt_params & params) {
+    if (params.hf_token.empty() && std::getenv("HF_TOKEN")) {
+        params.hf_token = std::getenv("HF_TOKEN");
+    }
+}
+
 void gpt_params_handle_model_default(gpt_params & params) {
     if (!params.hf_repo.empty()) {
         // short-hand to avoid specifying --hf-file -> default it to --model
@@ -237,6 +243,8 @@ bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params) {
 
     gpt_params_handle_model_default(params);
 
+    gpt_params_handle_hf_token(params);
+
     if (params.escape) {
         string_process_escapes(params.prompt);
         string_process_escapes(params.input_prefix);
@@ -652,6 +660,14 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
         params.model_url = argv[i];
         return true;
     }
+    if (arg == "-hft" || arg == "--hf-token") {
+        if (++i >= argc) {
+          invalid_param = true;
+          return true;
+        }
+        params.hf_token = argv[i];
+        return true;
+    }
     if (arg == "-hfr" || arg == "--hf-repo") {
         CHECK_ARG
         params.hf_repo = argv[i];
@@ -1576,6 +1592,7 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
     options.push_back({ "*",           "-mu,   --model-url MODEL_URL",  "model download url (default: unused)" });
     options.push_back({ "*",           "-hfr,  --hf-repo REPO",         "Hugging Face model repository (default: unused)" });
     options.push_back({ "*",           "-hff,  --hf-file FILE",         "Hugging Face model file (default: unused)" });
+    options.push_back({ "*",           "-hft,  --hf-token TOKEN",       "Hugging Face access token (default: value from HF_TOKEN environment variable)" });
 
     options.push_back({ "retrieval" });
     options.push_back({ "retrieval",   "       --context-file FNAME",   "file to load context from (repeat to specify multiple files)" });
@@ -2015,9 +2032,9 @@ std::tuple llama_init_from_gpt_par
     llama_model * model = nullptr;
 
     if (!params.hf_repo.empty() && !params.hf_file.empty()) {
-        model = llama_load_model_from_hf(params.hf_repo.c_str(), params.hf_file.c_str(), params.model.c_str(), mparams);
+        model = llama_load_model_from_hf(params.hf_repo.c_str(), params.hf_file.c_str(), params.model.c_str(), params.hf_token.c_str(), mparams);
     } else if (!params.model_url.empty()) {
-        model = llama_load_model_from_url(params.model_url.c_str(), params.model.c_str(), mparams);
+        model = llama_load_model_from_url(params.model_url.c_str(), params.model.c_str(), params.hf_token.c_str(), mparams);
     } else {
         model = llama_load_model_from_file(params.model.c_str(), mparams);
     }
@@ -2205,7 +2222,7 @@ static bool starts_with(const std::string & str, const std::string & prefix) {
     return str.rfind(prefix, 0) == 0;
 }
 
-static bool llama_download_file(const std::string & url, const std::string & path) {
+static bool llama_download_file(const std::string & url, const std::string & path, const std::string & hf_token) {
 
     // Initialize libcurl
     std::unique_ptr curl(curl_easy_init(), &curl_easy_cleanup);
@@ -2220,6 +2237,15 @@ static bool llama_download_file(const std::string & url, const std::string & pat
     curl_easy_setopt(curl.get(), CURLOPT_URL, url.c_str());
     curl_easy_setopt(curl.get(), CURLOPT_FOLLOWLOCATION, 1L);
 
+    // Check if hf-token or bearer-token was specified
+    if (!hf_token.empty()) {
+      std::string auth_header = "Authorization: Bearer ";
+      auth_header += hf_token.c_str();
+      struct curl_slist *http_headers = NULL;
+      http_headers = curl_slist_append(http_headers, auth_header.c_str());
+      curl_easy_setopt(curl.get(), CURLOPT_HTTPHEADER, http_headers);
+    }
+
 #if defined(_WIN32)
     // CURLSSLOPT_NATIVE_CA tells libcurl to use standard certificate store of
     //   operating system. Currently implemented under MS-Windows.
@@ -2415,6 +2441,7 @@ static bool llama_download_file(const std::string & url, const std::string & pat
 struct llama_model * llama_load_model_from_url(
         const char * model_url,
         const char * path_model,
+        const char * hf_token,
         const struct llama_model_params & params) {
     // Basic validation of the model_url
     if (!model_url || strlen(model_url) == 0) {
@@ -2422,7 +2449,7 @@ struct llama_model * llama_load_model_from_url(
         return NULL;
     }
 
-    if (!llama_download_file(model_url, path_model)) {
+    if (!llama_download_file(model_url, path_model, hf_token)) {
         return NULL;
     }
 
@@ -2470,14 +2497,14 @@ struct llama_model * llama_load_model_from_url(
         // Prepare download in parallel
         std::vector> futures_download;
         for (int idx = 1; idx < n_split; idx++) {
-            futures_download.push_back(std::async(std::launch::async, [&split_prefix, &split_url_prefix, &n_split](int download_idx) -> bool {
+            futures_download.push_back(std::async(std::launch::async, [&split_prefix, &split_url_prefix, &n_split, hf_token](int download_idx) -> bool {
                 char split_path[PATH_MAX] = {0};
                 llama_split_path(split_path, sizeof(split_path), split_prefix, download_idx, n_split);
 
                 char split_url[LLAMA_CURL_MAX_URL_LENGTH] = {0};
                 llama_split_path(split_url, sizeof(split_url), split_url_prefix, download_idx, n_split);
 
-                return llama_download_file(split_url, split_path);
+                return llama_download_file(split_url, split_path, hf_token);
             }, idx));
         }
 
@@ -2496,6 +2523,7 @@ struct llama_model * llama_load_model_from_hf(
         const char * repo,
         const char * model,
         const char * path_model,
+        const char * hf_token,
         const struct llama_model_params & params) {
     // construct hugging face model url:
     //
@@ -2511,7 +2539,7 @@ struct llama_model * llama_load_model_from_hf(
     model_url += "/resolve/main/";
     model_url += model;
 
-    return llama_load_model_from_url(model_url.c_str(), path_model, params);
+    return llama_load_model_from_url(model_url.c_str(), path_model, hf_token, params);
 }
 
 #else
@@ -2519,6 +2547,7 @@ struct llama_model * llama_load_model_from_hf(
 struct llama_model * llama_load_model_from_url(
         const char * /*model_url*/,
         const char * /*path_model*/,
+        const char * /*hf_token*/,
         const struct llama_model_params & /*params*/) {
     fprintf(stderr, "%s: llama.cpp built without libcurl, downloading from an url not supported.\n", __func__);
     return nullptr;
@@ -2528,6 +2557,7 @@ struct llama_model * llama_load_model_from_hf(
         const char * /*repo*/,
         const char * /*model*/,
         const char * /*path_model*/,
+        const char * /*hf_token*/,
         const struct llama_model_params & /*params*/) {
     fprintf(stderr, "%s: llama.cpp built without libcurl, downloading from Hugging Face not supported.\n", __func__);
     return nullptr;
diff --git a/common/common.h b/common/common.h
index dabf02b598b3b..184a53dc09064 100644
--- a/common/common.h
+++ b/common/common.h
@@ -108,6 +108,7 @@ struct gpt_params {
     std::string model_draft          = ""; // draft model for speculative decoding
     std::string model_alias          = "unknown"; // model alias
     std::string model_url            = ""; // model url to download
+    std::string hf_token             = ""; // HF token
     std::string hf_repo              = ""; // HF repo
     std::string hf_file              = ""; // HF file
     std::string prompt               = "";
@@ -256,6 +257,7 @@ struct gpt_params {
     bool spm_infill = false; // suffix/prefix/middle pattern for infill
 };
 
+void gpt_params_handle_hf_token(gpt_params & params);
 void gpt_params_handle_model_default(gpt_params & params);
 
 bool gpt_params_parse_ex   (int argc, char ** argv, gpt_params & params);
@@ -311,8 +313,8 @@ std::tuple llama_init_from_gpt_par
 struct llama_model_params   llama_model_params_from_gpt_params  (const gpt_params & params);
 struct llama_context_params llama_context_params_from_gpt_params(const gpt_params & params);
 
-struct llama_model * llama_load_model_from_url(const char * model_url, const char * path_model, const struct llama_model_params & params);
-struct llama_model * llama_load_model_from_hf(const char * repo, const char * file, const char * path_model, const struct llama_model_params & params);
+struct llama_model * llama_load_model_from_url(const char * model_url, const char * path_model, const char * hf_token, const struct llama_model_params & params);
+struct llama_model * llama_load_model_from_hf(const char * repo, const char * file, const char * path_model, const char * hf_token, const struct llama_model_params & params);
 
 // Batch utils
 

From cb4d86c4d723af87d3d7e3177e9485f200391384 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Bjarke=20Viks=C3=B8e?=
 <164612031+bviksoe@users.noreply.github.com>
Date: Sun, 7 Jul 2024 11:10:38 +0200
Subject: [PATCH 119/326] server: Retrieve prompt template in /props (#8337)

* server: Retrieve prompt template in /props

This PR adds the following:
- Expose the model's Jinja2 prompt template from the model in the /props endpoint.
- Change log-level from Error to Warning for warning about template mismatch.

The front-end stands a better chance of actually executing the Jinja template format correctly. Server is currently just guessing it.

Ideally this should have been inside a JSON block that expose the same key/value pairs as listed during startup in "llm_load_print_meta" function.

* Make string buffer dynamic

* Add doc and better string handling

* Using chat_template naming convention

* Use intermediate vector for string assignment
---
 examples/server/README.md  |  4 +++-
 examples/server/server.cpp | 13 +++++++++++--
 2 files changed, 14 insertions(+), 3 deletions(-)

diff --git a/examples/server/README.md b/examples/server/README.md
index aa4cbbe63907b..cb45ee06dd0a0 100644
--- a/examples/server/README.md
+++ b/examples/server/README.md
@@ -366,7 +366,8 @@ Notice that each `probs` is an array of length `n_probs`.
   "assistant_name": "",
   "user_name": "",
   "default_generation_settings": { ... },
-  "total_slots": 1
+  "total_slots": 1,
+  "chat_template": ""
 }
 ```
 
@@ -374,6 +375,7 @@ Notice that each `probs` is an array of length `n_probs`.
 - `user_name` - the required anti-prompt to generate the prompt in case you have specified a system prompt for all slots.
 - `default_generation_settings` - the default generation settings for the `/completion` endpoint, which has the same fields as the `generation_settings` response object from the `/completion` endpoint.
 - `total_slots` - the total number of slots for process requests (defined by `--parallel` option)
+- `chat_template` - the model's original Jinja2 prompt template
 
 - **POST** `/v1/chat/completions`: OpenAI-compatible Chat Completions API. Given a ChatML-formatted json description in `messages`, it returns the predicted completion. Both synchronous and streaming mode are supported, so scripted and interactive applications work fine. While no strong claims of compatibility with OpenAI API spec is being made, in our experience it suffices to support many apps. Only models with a [supported chat template](https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template) can be used optimally with this endpoint. By default, the ChatML template will be used.
 
diff --git a/examples/server/server.cpp b/examples/server/server.cpp
index d7fb61812aa3e..47bea15913600 100644
--- a/examples/server/server.cpp
+++ b/examples/server/server.cpp
@@ -2605,7 +2605,7 @@ int main(int argc, char ** argv) {
     // if a custom chat template is not supplied, we will use the one that comes with the model (if any)
     if (params.chat_template.empty()) {
         if (!ctx_server.validate_model_chat_template()) {
-            LOG_ERROR("The chat template that comes with this model is not yet supported, falling back to chatml. This may cause the model to output suboptimal responses", {});
+            LOG_WARNING("The chat template that comes with this model is not yet supported, falling back to chatml. This may cause the model to output suboptimal responses", {});
             params.chat_template = "chatml";
         }
     }
@@ -2967,11 +2967,20 @@ int main(int argc, char ** argv) {
     };
 
     const auto handle_props = [&ctx_server](const httplib::Request & req, httplib::Response & res) {
+        std::string template_key = "tokenizer.chat_template", curr_tmpl;
+        int32_t tlen = llama_model_meta_val_str(ctx_server.model, template_key.c_str(), nullptr, 0);
+        if (tlen > 0) {
+            std::vector curr_tmpl_buf(tlen + 1, 0);
+            if (llama_model_meta_val_str(ctx_server.model, template_key.c_str(), curr_tmpl_buf.data(), curr_tmpl_buf.size()) == tlen) {
+                curr_tmpl = std::string(curr_tmpl_buf.data(), tlen);
+            }
+        }
         res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
         json data = {
             { "system_prompt",               ctx_server.system_prompt.c_str() },
             { "default_generation_settings", ctx_server.default_generation_settings_for_props },
-            { "total_slots",                 ctx_server.params.n_parallel }
+            { "total_slots",                 ctx_server.params.n_parallel },
+            { "chat_template",               curr_tmpl.c_str() }
         };
 
         res.set_content(data.dump(), "application/json; charset=utf-8");

From 210eb9ed0ac3979a93e37568d96447ec3e95ad05 Mon Sep 17 00:00:00 2001
From: standby24x7 
Date: Sun, 7 Jul 2024 19:37:47 +0900
Subject: [PATCH 120/326] finetune: Rename an old command name in finetune.sh
 (#8344)

This patch replaces an old commad "main" with "llama-cli"
in finetune.sh.
The part that I fixed is comment, so it doesn't change
the script.

Signed-off-by: Masanari Iida 
---
 examples/finetune/finetune.sh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/finetune/finetune.sh b/examples/finetune/finetune.sh
index d7f2165e5cb3a..e3cc7f2712f17 100644
--- a/examples/finetune/finetune.sh
+++ b/examples/finetune/finetune.sh
@@ -8,7 +8,7 @@ if [[ ! $LLAMA_MODEL_DIR ]]; then LLAMA_MODEL_DIR="./models"; fi
 if [[ ! $LLAMA_TRAINING_DIR ]]; then LLAMA_TRAINING_DIR="."; fi
 
 # MODEL="$LLAMA_MODEL_DIR/openllama-3b-v2-q8_0.gguf" # This is the model the readme uses.
-MODEL="$LLAMA_MODEL_DIR/openllama-3b-v2.gguf" # An f16 model. Note in this case with "-g", you get an f32-format .BIN file that isn't yet supported if you use it with "main --lora" with GPU inferencing.
+MODEL="$LLAMA_MODEL_DIR/openllama-3b-v2.gguf" # An f16 model. Note in this case with "-g", you get an f32-format .BIN file that isn't yet supported if you use it with "llama-cli --lora" with GPU inferencing.
 
 while getopts "dg" opt; do
   case $opt in

From b81ba1f96b06c691020429a2d2dfcbada899ca86 Mon Sep 17 00:00:00 2001
From: standby24x7 
Date: Sun, 7 Jul 2024 19:38:02 +0900
Subject: [PATCH 121/326] finetune: Rename command name in README.md (#8343)

Rename an old command name "finetune" to "llama-finetune"
in README.md

Signed-off-by: Masanari Iida 
---
 examples/finetune/README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/finetune/README.md b/examples/finetune/README.md
index a6ae64983bc0a..1c27df053bc04 100644
--- a/examples/finetune/README.md
+++ b/examples/finetune/README.md
@@ -87,4 +87,4 @@ The LORA rank can be configured for each model tensor type separately with these
 
 The LORA rank of 'norm' tensors should always be 1.
 
-To see all available options use `finetune --help`.
+To see all available options use `llama-finetune --help`.

From d39130a3985ce0747d7229a6b7ebebb6376b5abf Mon Sep 17 00:00:00 2001
From: compilade 
Date: Sun, 7 Jul 2024 07:23:38 -0400
Subject: [PATCH 122/326] py : use cpu-only torch in requirements.txt (#8335)

---
 examples/llava/requirements.txt                         | 1 +
 requirements/requirements-convert_hf_to_gguf.txt        | 1 +
 requirements/requirements-convert_hf_to_gguf_update.txt | 1 +
 3 files changed, 3 insertions(+)

diff --git a/examples/llava/requirements.txt b/examples/llava/requirements.txt
index 4713f0a3460f4..fbfd0cdd722e1 100644
--- a/examples/llava/requirements.txt
+++ b/examples/llava/requirements.txt
@@ -1,3 +1,4 @@
 -r ../../requirements/requirements-convert_legacy_llama.txt
+--extra-index-url https://download.pytorch.org/whl/cpu
 pillow~=10.2.0
 torch~=2.2.1
diff --git a/requirements/requirements-convert_hf_to_gguf.txt b/requirements/requirements-convert_hf_to_gguf.txt
index 653355c07d68c..8cb9c354f0152 100644
--- a/requirements/requirements-convert_hf_to_gguf.txt
+++ b/requirements/requirements-convert_hf_to_gguf.txt
@@ -1,2 +1,3 @@
 -r ./requirements-convert_legacy_llama.txt
+--extra-index-url https://download.pytorch.org/whl/cpu
 torch~=2.2.1
diff --git a/requirements/requirements-convert_hf_to_gguf_update.txt b/requirements/requirements-convert_hf_to_gguf_update.txt
index 653355c07d68c..8cb9c354f0152 100644
--- a/requirements/requirements-convert_hf_to_gguf_update.txt
+++ b/requirements/requirements-convert_hf_to_gguf_update.txt
@@ -1,2 +1,3 @@
 -r ./requirements-convert_legacy_llama.txt
+--extra-index-url https://download.pytorch.org/whl/cpu
 torch~=2.2.1

From b5040086d436e7345e4fa33a5b9558060c75603f Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Sun, 7 Jul 2024 14:59:02 +0300
Subject: [PATCH 123/326] llama : fix n_rot default (#8348)

ggml-ci
---
 src/llama.cpp | 29 +++++++++++++++--------------
 1 file changed, 15 insertions(+), 14 deletions(-)

diff --git a/src/llama.cpp b/src/llama.cpp
index b39906fd53b6f..1a65faef9bedc 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -4625,16 +4625,6 @@ static void llm_load_hparams(
 
     // non-transformer models do not have attention heads
     if (hparams.n_head() > 0) {
-        // sanity check for n_rot (optional)
-        hparams.n_rot = hparams.n_embd / hparams.n_head();
-
-        ml.get_key(LLM_KV_ROPE_DIMENSION_COUNT, hparams.n_rot, false);
-
-        if (model.arch == LLM_ARCH_LLAMA || model.arch == LLM_ARCH_FALCON) {
-            if (hparams.n_rot != hparams.n_embd / hparams.n_head()) {
-                throw std::runtime_error(format("invalid n_rot: %u, expected %u", hparams.n_rot, hparams.n_embd / hparams.n_head()));
-            }
-        }
         // gpt-neox n_rot = rotary_pct * (n_embd / n_head)
         // gpt-j n_rot = rotary_dim
 
@@ -4643,6 +4633,17 @@ static void llm_load_hparams(
 
         hparams.n_embd_head_v = hparams.n_embd / hparams.n_head();
         ml.get_key(LLM_KV_ATTENTION_VALUE_LENGTH, hparams.n_embd_head_v, false);
+
+        // sanity check for n_rot (optional)
+        hparams.n_rot = hparams.n_embd_head_k;
+
+        ml.get_key(LLM_KV_ROPE_DIMENSION_COUNT, hparams.n_rot, false);
+
+        if (model.arch == LLM_ARCH_LLAMA || model.arch == LLM_ARCH_FALCON) {
+            if (hparams.n_rot != hparams.n_embd_head_k) {
+                throw std::runtime_error(format("invalid n_rot: %u, expected %u", hparams.n_rot, hparams.n_embd_head_k));
+            }
+        }
     } else {
         hparams.n_rot = 0;
         hparams.n_embd_head_k = 0;
@@ -11490,7 +11491,7 @@ struct llm_build_context {
 
                 Qcur = ggml_rope_ext(
                         ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head_k, n_head,    n_tokens), inp_pos, nullptr,
-                        n_embd_head_k, rope_type, n_ctx_orig, freq_base, freq_scale,
+                        n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
                         ext_factor, attn_factor, beta_fast, beta_slow);
                 cb(Qcur, "Qcur", il);
 
@@ -11499,7 +11500,7 @@ struct llm_build_context {
 
                 Kcur = ggml_rope_ext(
                         ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head_k, n_head_kv, n_tokens), inp_pos, nullptr,
-                        n_embd_head_k, rope_type, n_ctx_orig, freq_base, freq_scale,
+                        n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
                         ext_factor, attn_factor, beta_fast, beta_slow);
                 cb(Kcur, "Kcur", il);
 
@@ -11603,7 +11604,7 @@ struct llm_build_context {
 
                 Qcur = ggml_rope_ext(
                         ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head_k, n_head,    n_tokens), inp_pos, nullptr,
-                        n_embd_head_k, rope_type, n_ctx_orig, freq_base, freq_scale,
+                        n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
                         ext_factor, attn_factor, beta_fast, beta_slow);
                 cb(Qcur, "Qcur", il);
 
@@ -11612,7 +11613,7 @@ struct llm_build_context {
 
                 Kcur = ggml_rope_ext(
                         ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head_k, n_head_kv, n_tokens), inp_pos, nullptr,
-                        n_embd_head_k, rope_type, n_ctx_orig, freq_base, freq_scale,
+                        n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
                         ext_factor, attn_factor, beta_fast, beta_slow);
                 cb(Kcur, "Kcur", il);
 

From 905942abdba5ba0b28a1b0805e51e4f818c54bc9 Mon Sep 17 00:00:00 2001
From: toyer <2042519524@qq.com>
Date: Sun, 7 Jul 2024 20:52:10 +0800
Subject: [PATCH 124/326] llama : support glm3 and glm4 (#8031)

* add chatglm3-6b model support huggingface model:
 https://hf-mirror.com/THUDM/chatglm3-6b

Signed-off-by: XingXing Qiao 

* remove .rotary_pos_emb.inv_freq and unuse code for chatglm3 model

Signed-off-by: XingXing Qiao 

* fix lint error

Signed-off-by: XingXing Qiao 

* optimize convert-hf-to-gguf.py for chatglm model

Signed-off-by: XingXing Qiao 

* support glm-4-9b-chat

Signed-off-by: XingXing Qiao 

* fix eos tokens to glm4

* remove unused log

* add preprocess to chatglm3 and chatglm4

* add eos_id_list to llama.cpp

* fix code style

* fix code style

* fix conflicts

* fix conflicts

* Revert "add eos_id_list to llama.cpp"

This reverts commit 3a4d5790bfdc205c5b658204239f168fc21cc1a8.

* set <|endoftext|> as eos and <|user|> as eot

* fix chat template bug

* add comment to glm prefix and suffix

* fix conflicts and add rope_ratio & ChatGLMForConditionalGeneration

* fix chat template bug

* fix codestyle

* fix conflicts

* modified the general name of glm model

* fix conflicts

* remove prefix and suffix

* use normal glm4 chattempalte & use LLM_FFN_SWIGLU in phi3

* fix: resolve Flake8 errors in `convert-hf-to-gguf.py`

- Fix E302 by adding two blank lines before top-level function definitions
- Replace print statements to fix NP100
- Fix E303 by ensuring only one blank line between lines of code

* fix rope ratio to solve incorrect answers

* fix by comments

---------

Signed-off-by: XingXing Qiao 
Co-authored-by: XingXing Qiao 
Co-authored-by: Umpire2018 <138990495+Umpire2018@users.noreply.github.com>
---
 convert_hf_to_gguf.py          | 187 +++++++++++++++++++++++++
 gguf-py/gguf/constants.py      |  18 ++-
 gguf-py/gguf/tensor_mapping.py |  14 +-
 include/llama.h                |   6 +-
 src/llama.cpp                  | 247 ++++++++++++++++++++++++++++++---
 tests/test-chat-template.cpp   |   8 ++
 6 files changed, 455 insertions(+), 25 deletions(-)

diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py
index 455eea883b93b..6ee41d3a118e5 100755
--- a/convert_hf_to_gguf.py
+++ b/convert_hf_to_gguf.py
@@ -487,6 +487,9 @@ def get_vocab_base_pre(self, tokenizer) -> str:
         if chkhsh == "7967bfa498ade6b757b064f31e964dddbb80f8f9a4d68d4ba7998fcf281c531a":
             # ref: https://huggingface.co/jinaai/jina-embeddings-v2-base-code
             res = "jina-v2-code"
+        if chkhsh == "b6e8e1518dc4305be2fe39c313ed643381c4da5db34a98f6a04c093f8afbe99b":
+            # ref: https://huggingface.co/THUDM/glm-4-9b-chat
+            res = "chatglm-bpe"
         if chkhsh == "7fc505bd3104ca1083b150b17d088b59534ede9bde81f0dd2090967d7fe52cee":
             # ref: https://huggingface.co/LumiOpen/Viking-7B
             res = "viking"
@@ -3176,6 +3179,190 @@ def write_tensors(self):
         self.gguf_writer.add_max_alibi_bias(self.max_alibi_bias)
 
 
+@Model.register("ChatGLMModel", "ChatGLMForConditionalGeneration")
+class ChatGLMModel(Model):
+    model_arch = gguf.MODEL_ARCH.CHATGLM
+
+    def set_vocab_chatglm3(self):
+        dir_model = self.dir_model
+        hparams = self.hparams
+        tokens: list[bytearray] = []
+        toktypes: list[int] = []
+        scores: list[float] = []
+
+        from transformers import AutoTokenizer
+        tokenizer = AutoTokenizer.from_pretrained(dir_model, trust_remote_code=True)
+        vocab_size = hparams.get("padded_vocab_size", len(tokenizer.get_vocab()))
+        assert max(tokenizer.get_vocab().values()) < vocab_size
+        role_special_tokens = ["<|system|>", "<|user|>", "<|assistant|>", "<|observation|>"]
+        special_tokens = ["[MASK]", "[gMASK]", "[sMASK]", "sop", "eop"] + role_special_tokens
+        for token_id in range(vocab_size):
+            piece = tokenizer._convert_id_to_token(token_id)
+            if token_id == 0:
+                piece = ""
+            elif token_id == 1:
+                piece = ""
+            elif token_id == 2:
+                piece = ""
+
+            text = piece.encode("utf-8")
+            score = 0.0
+            # Referencing the tokenizer Python implementation(https://huggingface.co/THUDM/chatglm3-6b/blob/main/tokenization_chatglm.py),
+            # it is only valid if it is less than tokenizer.tokenizer.sp_model.vocab_size()
+            if len(piece) != 0 and token_id < tokenizer.tokenizer.sp_model.vocab_size():
+                score = tokenizer.tokenizer.sp_model.get_score(token_id)
+
+            if len(piece) == 0:
+                text = f"[PAD{token_id}]".encode("utf-8")
+
+            if token_id >= tokenizer.tokenizer.sp_model.vocab_size():
+                if piece in special_tokens:
+                    # show special tokens in prompt
+                    toktype = SentencePieceTokenTypes.USER_DEFINED
+                else:
+                    toktype = SentencePieceTokenTypes.UNKNOWN
+                tokens.append(text)
+                scores.append(score)
+                toktypes.append(toktype)
+                continue
+
+            toktype = SentencePieceTokenTypes.NORMAL
+            if tokenizer.tokenizer.sp_model.is_unknown(token_id):
+                toktype = SentencePieceTokenTypes.UNKNOWN
+            elif tokenizer.tokenizer.sp_model.is_control(token_id):
+                toktype = SentencePieceTokenTypes.CONTROL
+            elif tokenizer.tokenizer.sp_model.is_unused(token_id):
+                toktype = SentencePieceTokenTypes.UNUSED
+            elif tokenizer.tokenizer.sp_model.is_byte(token_id):
+                toktype = SentencePieceTokenTypes.BYTE
+
+            tokens.append(text)
+            scores.append(score)
+            toktypes.append(toktype)
+
+        self.gguf_writer.add_tokenizer_model("llama")
+        # glm3 needs prefix and suffix formatted as:
+        # prompt = "[gMASK]sop<|user|>\n" + prompt + "<|assistant|>"
+        self.gguf_writer.add_tokenizer_pre("chatglm-spm")
+        self.gguf_writer.add_token_list(tokens)
+        self.gguf_writer.add_token_scores(scores)
+        self.gguf_writer.add_token_types(toktypes)
+
+        special_vocab = gguf.SpecialVocab(self.dir_model, n_vocab=len(tokens))
+        special_vocab.add_to_gguf(self.gguf_writer)
+
+    @staticmethod
+    def token_bytes_to_string(b):
+        from transformers.models.gpt2.tokenization_gpt2 import bytes_to_unicode
+        byte_encoder = bytes_to_unicode()
+        return ''.join([byte_encoder[ord(char)] for char in b.decode('latin-1')])
+
+    @staticmethod
+    def bpe(mergeable_ranks: dict[bytes, int], token: bytes, max_rank: int | None = None) -> list[bytes]:
+        parts = [bytes([b]) for b in token]
+        while True:
+            min_idx = None
+            min_rank = None
+            for i, pair in enumerate(zip(parts[:-1], parts[1:])):
+                rank = mergeable_ranks.get(pair[0] + pair[1])
+                if rank is not None and (min_rank is None or rank < min_rank):
+                    min_idx = i
+                    min_rank = rank
+            if min_rank is None or (max_rank is not None and min_rank >= max_rank):
+                break
+            assert min_idx is not None
+            parts = parts[:min_idx] + [parts[min_idx] + parts[min_idx + 1]] + parts[min_idx + 2:]
+        return parts
+
+    def set_vocab(self):
+        if "THUDM/chatglm3-6b" in self.hparams.get("_name_or_path", ""):
+            self.set_vocab_chatglm3()
+            return
+
+        dir_model = self.dir_model
+        hparams = self.hparams
+        tokens: list[str] = []
+        toktypes: list[int] = []
+
+        from transformers import AutoTokenizer
+        tokenizer = AutoTokenizer.from_pretrained(dir_model, trust_remote_code=True)
+        vocab_size = hparams["padded_vocab_size"]
+        assert max(tokenizer.get_vocab().values()) < vocab_size
+
+        tokpre = self.get_vocab_base_pre(tokenizer)
+
+        merges = []
+        vocab = {}
+        mergeable_ranks = tokenizer.mergeable_ranks
+        for token, rank in mergeable_ranks.items():
+            vocab[ChatGLMModel.token_bytes_to_string(token)] = rank
+            if len(token) == 1:
+                continue
+            merged = ChatGLMModel.bpe(mergeable_ranks, token, max_rank=rank)
+            assert len(merged) >= 2 and len(merged) <= 7
+            merges.append(' '.join(map(ChatGLMModel.token_bytes_to_string, merged)))
+
+        # for this kind of tokenizer, added_vocab is not a subset of vocab, so they need to be combined
+        added_vocab = tokenizer.get_added_vocab()
+        reverse_vocab = {id_ : encoded_tok for encoded_tok, id_ in {**vocab, **added_vocab}.items()}
+
+        for i in range(vocab_size):
+            if i not in reverse_vocab:
+                tokens.append(f"[PAD{i}]")
+                toktypes.append(gguf.TokenType.USER_DEFINED)
+            elif reverse_vocab[i] in added_vocab:
+                tokens.append(reverse_vocab[i])
+                if tokenizer.added_tokens_decoder[i].special:
+                    toktypes.append(gguf.TokenType.CONTROL)
+                else:
+                    toktypes.append(gguf.TokenType.USER_DEFINED)
+            else:
+                tokens.append(reverse_vocab[i])
+                toktypes.append(gguf.TokenType.NORMAL)
+
+        self.gguf_writer.add_tokenizer_model("gpt2")
+        self.gguf_writer.add_tokenizer_pre(tokpre)
+        self.gguf_writer.add_token_list(tokens)
+        self.gguf_writer.add_token_types(toktypes)
+
+        special_vocab = gguf.SpecialVocab(dir_model, load_merges=False)
+        special_vocab.merges = merges
+        # only add special tokens when they were not already loaded from config.json
+        special_vocab._set_special_token("eos", tokenizer.get_added_vocab()["<|endoftext|>"])
+        special_vocab._set_special_token("eot", tokenizer.get_added_vocab()["<|user|>"])
+        # this one is usually not in config.json anyway
+        special_vocab._set_special_token("unk", tokenizer.get_added_vocab()["<|endoftext|>"])
+        special_vocab.add_to_gguf(self.gguf_writer)
+
+    def set_gguf_parameters(self):
+        self.gguf_writer.add_name(self.hparams.get("_name_or_path").split("/")[1]) # THUDM/glm4-9b-chat or THUDM/chatglm3-6b
+        n_embed = self.hparams.get("hidden_size", self.hparams.get("n_embed"))
+        n_head = self.hparams.get("n_head", self.hparams.get("num_attention_heads"))
+        n_head_kv = self.hparams.get("multi_query_group_num", n_head)
+        self.gguf_writer.add_context_length(self.hparams.get("seq_length", n_embed))
+        self.gguf_writer.add_embedding_length(n_embed)
+        self.gguf_writer.add_feed_forward_length(self.hparams.get("ffn_hidden_size", 4 * n_embed))
+        self.gguf_writer.add_block_count(self.hparams["num_layers"])
+        self.gguf_writer.add_head_count(n_head)
+        self.gguf_writer.add_head_count_kv(n_head_kv)
+        self.gguf_writer.add_layer_norm_rms_eps(self.hparams["layernorm_epsilon"])
+        self.gguf_writer.add_file_type(self.ftype)
+        self.gguf_writer.add_rope_dimension_count(64)
+        self.gguf_writer.add_add_bos_token(False)
+        rope_freq = 10000
+        if "rope_ratio" in self.hparams:
+            rope_freq = rope_freq * self.hparams["rope_ratio"]
+        self.gguf_writer.add_rope_freq_base(rope_freq)
+
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        del bid  # unused
+
+        if name.endswith(".rotary_pos_emb.inv_freq"):
+            return []
+
+        name = name.removeprefix("transformer.")
+        return [(self.map_tensor_name(name), data_torch)]
+
 ###### CONVERSION LOGIC ######
 
 
diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py
index d78fb1e44b29e..a95a44237e348 100644
--- a/gguf-py/gguf/constants.py
+++ b/gguf-py/gguf/constants.py
@@ -120,7 +120,6 @@ class Tokenizer:
         MIDDLE_ID            = "tokenizer.ggml.middle_token_id"
         EOT_ID               = "tokenizer.ggml.eot_token_id"
 
-
 #
 # recommended mapping of model tensor names for storage in gguf
 #
@@ -163,6 +162,7 @@ class MODEL_ARCH(IntEnum):
     OPENELM      = auto()
     ARCTIC       = auto()
     DEEPSEEK2    = auto()
+    CHATGLM      = auto()
     BITNET       = auto()
     T5           = auto()
     JAIS         = auto()
@@ -289,6 +289,7 @@ class MODEL_TENSOR(IntEnum):
     MODEL_ARCH.OPENELM:        "openelm",
     MODEL_ARCH.ARCTIC:         "arctic",
     MODEL_ARCH.DEEPSEEK2:      "deepseek2",
+    MODEL_ARCH.CHATGLM:        "chatglm",
     MODEL_ARCH.BITNET:         "bitnet",
     MODEL_ARCH.T5:             "t5",
     MODEL_ARCH.JAIS:           "jais",
@@ -924,6 +925,18 @@ class MODEL_TENSOR(IntEnum):
         MODEL_TENSOR.FFN_DOWN_SHEXP,
         MODEL_TENSOR.FFN_UP_SHEXP,
     ],
+    MODEL_ARCH.CHATGLM : [
+        MODEL_TENSOR.TOKEN_EMBD,
+        MODEL_TENSOR.ROPE_FREQS,
+        MODEL_TENSOR.OUTPUT_NORM,
+        MODEL_TENSOR.OUTPUT,
+        MODEL_TENSOR.ATTN_NORM,
+        MODEL_TENSOR.ATTN_QKV,
+        MODEL_TENSOR.ATTN_OUT,
+        MODEL_TENSOR.FFN_NORM,
+        MODEL_TENSOR.FFN_DOWN,
+        MODEL_TENSOR.FFN_UP,
+    ],
     MODEL_ARCH.BITNET: [
         MODEL_TENSOR.ATTN_Q,
         MODEL_TENSOR.ATTN_K,
@@ -1020,6 +1033,9 @@ class MODEL_TENSOR(IntEnum):
         MODEL_TENSOR.ROPE_FREQS,
         MODEL_TENSOR.ATTN_ROT_EMBD,
     ],
+    MODEL_ARCH.CHATGLM: [
+        MODEL_TENSOR.ROPE_FREQS,
+    ],
 }
 
 #
diff --git a/gguf-py/gguf/tensor_mapping.py b/gguf-py/gguf/tensor_mapping.py
index 6054f61595e13..7264240f5e17a 100644
--- a/gguf-py/gguf/tensor_mapping.py
+++ b/gguf-py/gguf/tensor_mapping.py
@@ -24,6 +24,7 @@ class TensorNameMap:
             "backbone.embedding",                        # mamba
             "backbone.embeddings",                       # mamba-hf
             "transformer.in_out_embed",                  # Grok
+            "embedding.word_embeddings",                 # chatglm
             "transformer.token_embeddings",              # openelm
             "shared",                                    # t5
         ),
@@ -55,6 +56,7 @@ class TensorNameMap:
             "output",                    # llama-pth bloom internlm2
             "word_embeddings_for_head",  # persimmon
             "lm_head.linear",            # phi2
+            "output_layer",              # chatglm
         ),
 
         # Output norm
@@ -71,12 +73,14 @@ class TensorNameMap:
             "model.norm_f",                            # mamba-qbert
             "backbone.norm_f",                         # mamba
             "transformer.rms_norm",                    # Grok
+            "encoder.final_layernorm",                 # chatglm
             "transformer.norm",                        # openelm
         ),
 
         # Rope frequencies
         MODEL_TENSOR.ROPE_FREQS: (
             "rope.freqs",  # llama-pth
+            "rotary_pos_emb.inv_freq",  # chatglm
         ),
     }
 
@@ -101,6 +105,7 @@ class TensorNameMap:
             "backbone.layers.{bid}.norm",                           # mamba
             "transformer.decoder_layer.{bid}.rms_norm",             # Grok
             "transformer.blocks.{bid}.norm_attn_norm.norm_1",       # dbrx
+            "encoder.layers.{bid}.input_layernorm",                 # chatglm
             "transformer.layers.{bid}.attn_norm",                   # openelm
         ),
 
@@ -124,6 +129,7 @@ class TensorNameMap:
             "transformer.h.{bid}.mixer.Wqkv",                                      # phi2
             "encoder.layers.{bid}.attn.Wqkv",                                      # nomic-bert
             "model.layers.{bid}.self_attn.qkv_proj",                               # phi3
+            "encoder.layers.{bid}.self_attention.query_key_value",                 # chatglm
             "transformer.layers.{bid}.attn.qkv_proj",                              # openelm
         ),
 
@@ -135,7 +141,7 @@ class TensorNameMap:
             "transformer.h.{bid}.attn.q_proj",                           # gpt-j
             "model.layers.layers.{bid}.self_attn.q_proj",                # plamo
             "model.layers.{bid}.attention.wq",                           # internlm2
-            "transformer.decoder_layer.{bid}.multi_head_attention.query" # Grok
+            "transformer.decoder_layer.{bid}.multi_head_attention.query",# Grok
         ),
 
         # Attention key
@@ -147,7 +153,7 @@ class TensorNameMap:
             "transformer.h.{bid}.attn.k",                              # refact
             "model.layers.layers.{bid}.self_attn.k_proj",              # plamo
             "model.layers.{bid}.attention.wk",                         # internlm2
-            "transformer.decoder_layer.{bid}.multi_head_attention.key" # Grok
+            "transformer.decoder_layer.{bid}.multi_head_attention.key",# Grok
         ),
 
         # Attention value
@@ -182,6 +188,7 @@ class TensorNameMap:
             "encoder.layers.{bid}.attn.out_proj",                           # nomic-bert
             "transformer.decoder_layer.{bid}.multi_head_attention.linear",  # Grok
             "transformer.blocks.{bid}.norm_attn_norm.attn.out_proj",        # dbrx
+            "encoder.layers.{bid}.self_attention.dense",                    # chatglm
             "transformer.layers.{bid}.attn.out_proj",                       # openelm
         ),
 
@@ -218,6 +225,7 @@ class TensorNameMap:
             "h.{bid}.ln_2",                                                  # gpt2
             "model.layers.{bid}.ffn_norm",                                   # internlm2
             "transformer.decoder_layer.{bid}.rms_norm_2",                    # Grok
+            "encoder.layers.{bid}.post_attention_layernorm",                 # chatglm
             "transformer.layers.{bid}.ffn_norm",                             # openelm
         ),
 
@@ -268,6 +276,7 @@ class TensorNameMap:
             "model.layers.{bid}.mlp.c_fc",                            # starcoder2
             "encoder.layer.{bid}.mlp.gated_layers_v",                 # jina-bert-v2
             "model.layers.{bid}.residual_mlp.w3",                     # arctic
+            "encoder.layers.{bid}.mlp.dense_h_to_4h",                 # chatglm
         ),
 
         MODEL_TENSOR.FFN_UP_EXP: (
@@ -337,6 +346,7 @@ class TensorNameMap:
             "transformer.layers.{bid}.ffn.proj_2",                    # openelm
             "model.layers.{bid}.residual_mlp.w2",                     # arctic
             "encoder.layer.{bid}.mlp.down_layer",                     # jina-bert-v2
+            "encoder.layers.{bid}.mlp.dense_4h_to_h",                 # chatglm
         ),
 
         MODEL_TENSOR.FFN_DOWN_EXP: (
diff --git a/include/llama.h b/include/llama.h
index 865ace9944d02..bb4b05ba63671 100644
--- a/include/llama.h
+++ b/include/llama.h
@@ -88,8 +88,10 @@ extern "C" {
         LLAMA_VOCAB_PRE_TYPE_DBRX           = 13,
         LLAMA_VOCAB_PRE_TYPE_SMAUG          = 14,
         LLAMA_VOCAB_PRE_TYPE_PORO           = 15,
-        LLAMA_VOCAB_PRE_TYPE_VIKING         = 16,
-        LLAMA_VOCAB_PRE_TYPE_JAIS           = 17,
+        LLAMA_VOCAB_PRE_TYPE_CHATGLM3       = 16,
+        LLAMA_VOCAB_PRE_TYPE_CHATGLM4       = 17,
+        LLAMA_VOCAB_PRE_TYPE_VIKING         = 18,
+        LLAMA_VOCAB_PRE_TYPE_JAIS           = 19,
     };
 
     // note: these values should be synchronized with ggml_rope
diff --git a/src/llama.cpp b/src/llama.cpp
index 1a65faef9bedc..2b9ace2858457 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -229,6 +229,7 @@ enum llm_arch {
     LLM_ARCH_OPENELM,
     LLM_ARCH_ARCTIC,
     LLM_ARCH_DEEPSEEK2,
+    LLM_ARCH_CHATGLM,
     LLM_ARCH_BITNET,
     LLM_ARCH_T5,
     LLM_ARCH_JAIS,
@@ -272,6 +273,7 @@ static const std::map LLM_ARCH_NAMES = {
     { LLM_ARCH_OPENELM,         "openelm"      },
     { LLM_ARCH_ARCTIC,          "arctic"       },
     { LLM_ARCH_DEEPSEEK2,       "deepseek2"    },
+    { LLM_ARCH_CHATGLM,         "chatglm"      },
     { LLM_ARCH_BITNET,          "bitnet"       },
     { LLM_ARCH_T5,              "t5"           },
     { LLM_ARCH_JAIS,            "jais"         },
@@ -1205,6 +1207,21 @@ static const std::map> LLM_TENSOR_NA
             { LLM_TENSOR_FFN_UP_SHEXP,       "blk.%d.ffn_up_shexp" },
         },
     },
+    {
+        LLM_ARCH_CHATGLM,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,      "token_embd" },
+            { LLM_TENSOR_ROPE_FREQS,      "rope_freqs" },
+            { LLM_TENSOR_OUTPUT_NORM,     "output_norm" },
+            { LLM_TENSOR_OUTPUT,          "output" },
+            { LLM_TENSOR_ATTN_NORM,       "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_QKV,        "blk.%d.attn_qkv" },
+            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output" },
+            { LLM_TENSOR_FFN_NORM,        "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
+            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
+        },
+    },
     {
         LLM_ARCH_BITNET,
         {
@@ -2087,9 +2104,11 @@ enum e_model {
     MODEL_2_8B,
     MODEL_3B,
     MODEL_4B,
+    MODEL_6B,
     MODEL_6_9B,
     MODEL_7B,
     MODEL_8B,
+    MODEL_9B,
     MODEL_11B,
     MODEL_12B,
     MODEL_13B,
@@ -2115,7 +2134,6 @@ enum e_model {
     MODEL_16x12B,
     MODEL_10B_128x3_66B,
     MODEL_57B_A14B,
-    MODEL_9B,
     MODEL_27B,
 };
 
@@ -4490,9 +4508,11 @@ static const char * llama_model_type_name(e_model type) {
         case MODEL_2_8B:          return "2.8B";
         case MODEL_3B:            return "3B";
         case MODEL_4B:            return "4B";
+        case MODEL_6B:            return "6B";
         case MODEL_6_9B:          return "6.9B";
         case MODEL_7B:            return "7B";
         case MODEL_8B:            return "8B";
+        case MODEL_9B:            return "9B";
         case MODEL_11B:           return "11B";
         case MODEL_12B:           return "12B";
         case MODEL_13B:           return "13B";
@@ -4518,7 +4538,6 @@ static const char * llama_model_type_name(e_model type) {
         case MODEL_16x12B:        return "16x12B";
         case MODEL_10B_128x3_66B: return "10B+128x3.66B";
         case MODEL_57B_A14B:      return "57B.A14B";
-        case MODEL_9B:            return "9B";
         case MODEL_27B:           return "27B";
         default:                  return "?B";
     }
@@ -5124,6 +5143,15 @@ static void llm_load_hparams(
                     default: model.type = e_model::MODEL_UNKNOWN;
                 }
             } break;
+        case LLM_ARCH_CHATGLM:
+            {
+                ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
+                switch (hparams.n_layer) {
+                    case 28: model.type = e_model::MODEL_6B; break;
+                    case 40: model.type = e_model::MODEL_9B; break;
+                    default: model.type = e_model::MODEL_UNKNOWN;
+                }
+            } break;
         case LLM_ARCH_BITNET:
             {
                 ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
@@ -5256,9 +5284,7 @@ static void llm_load_vocab(
             if (merges_keyidx == -1) {
                 throw std::runtime_error("cannot find tokenizer merges in model file\n");
             }
-
             const int n_merges = gguf_get_arr_n(ctx, merges_keyidx);
-
             for (int i = 0; i < n_merges; i++) {
                 const std::string word = gguf_get_arr_str(ctx, merges_keyidx, i);
                 GGML_ASSERT(unicode_cpts_from_utf8(word).size() > 0);
@@ -5401,6 +5427,10 @@ static void llm_load_vocab(
                 tokenizer_pre == "poro-chat") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_PORO;
                 vocab.tokenizer_clean_spaces = false;
+            } else if (
+                tokenizer_pre == "chatglm-bpe") {
+                vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_CHATGLM4;
+                vocab.special_bos_id  = -1;
             } else if (
                 tokenizer_pre == "viking") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_VIKING;
@@ -5525,7 +5555,6 @@ static void llm_load_vocab(
                 vocab.special_eot_id    = 107;
             }
         }
-
         try {
             vocab.linefeed_id = llama_byte_to_token(vocab, '\n');
         } catch (const std::exception & e) {
@@ -7433,6 +7462,36 @@ static bool llm_load_tensors(
                         layer.ffn_up_b   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP,   "bias", i),   {n_ff});
                     }
                 } break;
+            case LLM_ARCH_CHATGLM:
+                {
+                    model.tok_embd   = ml.create_tensor(ctx_input,  tn(LLM_TENSOR_TOKEN_EMBD,      "weight"), {n_embd, n_vocab});
+
+                    // output
+                    {
+                        model.output_norm   = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
+                        model.output        = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab});
+                    }
+
+                    for (int i = 0; i < n_layer; ++i) {
+                        ggml_context * ctx_layer = ctx_for_layer(i);
+                        ggml_context * ctx_split = ctx_for_layer_split(i);
+
+                        auto & layer = model.layers[i];
+
+                        layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
+
+                        layer.wqkv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_embd + (hparams.n_embd_head_k << 2)});
+                        layer.bqkv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_QKV, "bias", i),   {n_embd + (hparams.n_embd_head_k << 2)});
+
+                        layer.wo   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
+
+                        layer.ffn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
+
+                        layer.ffn_up     = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd, n_ff * 2});
+
+                        layer.ffn_down   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd});
+                    }
+                } break;
             default:
                 throw std::runtime_error("unknown architecture");
         }
@@ -7657,6 +7716,7 @@ enum llm_ffn_op_type {
     LLM_FFN_GELU,
     LLM_FFN_RELU,
     LLM_FFN_RELU_SQR,
+    LLM_FFN_SWIGLU,
 };
 
 enum llm_ffn_gate_type {
@@ -7861,6 +7921,19 @@ static struct ggml_tensor * llm_build_ffn(
                 cur = ggml_sqr(ctx, cur);
                 cb(cur, "ffn_sqr(relu)", il);
             } break;
+        case LLM_FFN_SWIGLU:
+            {
+                // Project to 4h. If using swiglu double the output width, see https://arxiv.org/pdf/2002.05202.pdf
+                int64_t split_point = cur->ne[0] / 2;
+                struct ggml_tensor * x0 = ggml_cont(ctx, ggml_view_2d(ctx, cur, split_point, cur->ne[1], cur->nb[1], 0));
+                struct ggml_tensor * x1 = ggml_cont(ctx, ggml_view_2d(ctx, cur, split_point, cur->ne[1], cur->nb[1], split_point * ggml_element_size(cur)));
+
+                x0 = ggml_silu(ctx, x0);
+                cb(cur, "ffn_silu", il);
+
+                cur = ggml_mul(ctx, x0, x1);
+                cb(cur, "ffn_mul", il);
+            } break;
     }
 
     if (type_gate == LLM_FFN_PAR) {
@@ -10709,19 +10782,12 @@ struct llm_build_context {
             // special-case: the up and gate tensors are merged into a single tensor
             // TOOD: support into llm_build_ffn
             {
-                struct ggml_tensor* up = ggml_mul_mat(ctx0, model.layers[il].ffn_up, cur);
-                cb(up, "ffn_up", il);
-
-                auto g = ggml_cont(ctx0, ggml_view_2d(ctx0, up, up->ne[0] / 2, up->ne[1], ggml_row_size(up->type, up->ne[0]), 0));
-                auto y = ggml_cont(ctx0, ggml_view_2d(ctx0, up, up->ne[0] / 2, up->ne[1], ggml_row_size(up->type, up->ne[0]), up->nb[1] / 2));
-
-                y = ggml_mul(ctx0, y, ggml_silu(ctx0, g));
-                cb(y, "ffn_gate", il);
-
-                auto down = ggml_mul_mat(ctx0, model.layers[il].ffn_down, y);
-                cb(down, "ffn_down", il);
-
-                cur = down;
+                cur = llm_build_ffn(ctx0, cur,
+                        model.layers[il].ffn_up,   NULL, NULL,
+                        NULL,                      NULL, NULL,
+                        model.layers[il].ffn_down, NULL, NULL,
+                        NULL,
+                        LLM_FFN_SWIGLU, LLM_FFN_SEQ, cb, il);
                 cb(cur, "ffn_out", il);
             }
 
@@ -13413,6 +13479,120 @@ struct llm_build_context {
 
         return gf;
     }
+
+    struct ggml_cgraph * build_chatglm() {
+        struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
+
+        const int64_t n_embd_head = hparams.n_embd_head_v;
+        const int64_t n_embd_gqa  = hparams.n_embd_v_gqa();
+        GGML_ASSERT(n_embd_head == hparams.n_embd_head_k);
+
+        struct ggml_tensor * cur;
+        struct ggml_tensor * inpL;
+
+        inpL = llm_build_inp_embd(ctx0, lctx, hparams, batch, model.tok_embd, cb);
+
+        // inp_pos - contains the positions
+        struct ggml_tensor * inp_pos = build_inp_pos();
+
+        // KQ_mask (mask for 1 head, it will be broadcasted to all heads)
+        struct ggml_tensor * KQ_mask = build_inp_KQ_mask();
+
+        for (int il = 0; il < n_layer; ++il) {
+            struct ggml_tensor * inpSA = inpL;
+
+            cur = llm_build_norm(ctx0, inpL, hparams,
+                    model.layers[il].attn_norm,
+                    NULL,
+                    LLM_NORM_RMS, cb, il);
+            cb(cur, "attn_norm", il);
+
+            // self-attention
+            {
+                struct ggml_tensor * Qcur = nullptr;
+                struct ggml_tensor * Kcur = nullptr;
+                struct ggml_tensor * Vcur = nullptr;
+
+                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
+                cb(cur, "wqkv", il);
+
+                cur = ggml_add(ctx0, cur, model.layers[il].bqkv);
+                cb(cur, "bqkv", il);
+
+                Qcur = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, n_embd,     n_tokens, cur->nb[1], 0*sizeof(float)*(n_embd)));
+                Kcur = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, n_embd_gqa, n_tokens, cur->nb[1], 1*sizeof(float)*(n_embd)));
+                Vcur = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, n_embd_gqa, n_tokens, cur->nb[1], 1*sizeof(float)*(n_embd + n_embd_gqa)));
+
+                cb(Qcur, "Qcur", il);
+                cb(Kcur, "Kcur", il);
+                cb(Vcur, "Vcur", il);
+                //printf("freq_base: %f freq_scale: %f ext_factor: %f attn_factor: %f\n", freq_base, freq_scale, ext_factor, attn_factor);
+                Qcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos, nullptr,
+                    n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
+                    ext_factor, attn_factor, beta_fast, beta_slow
+                );
+                cb(Qcur, "Qcur_rope", il);
+
+                Kcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
+                    n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
+                    ext_factor, attn_factor, beta_fast, beta_slow
+                );
+                cb(Kcur, "Kcur_rope", il);
+
+                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                        model.layers[il].wo, NULL,
+                        Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
+
+            }
+
+            if (il == n_layer - 1) {
+                // skip computing output for unused tokens
+                struct ggml_tensor * inp_out_ids = build_inp_out_ids();
+                cur   = ggml_get_rows(ctx0,   cur, inp_out_ids);
+                inpSA = ggml_get_rows(ctx0, inpSA, inp_out_ids);
+            }
+
+            // Add the input
+            struct ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpSA);
+            cb(ffn_inp, "ffn_inp", il);
+
+            // FF
+            {
+                cur = llm_build_norm(ctx0, ffn_inp, hparams,
+                        model.layers[il].ffn_norm,
+                        NULL,
+                        LLM_NORM_RMS, cb, il);
+                cb(cur, "ffn_norm", il);
+
+                cur = llm_build_ffn(ctx0, cur,
+                        model.layers[il].ffn_up,   NULL, NULL,
+                        NULL,                      NULL, NULL,
+                        model.layers[il].ffn_down, NULL, NULL,
+                        NULL,
+                        LLM_FFN_SWIGLU, LLM_FFN_SEQ, cb, il);
+                cb(cur, "ffn_out", il);
+
+            }
+
+            inpL = ggml_add(ctx0, cur, ffn_inp);
+            cb(inpL, "l_out", il);
+        }
+
+        cur = llm_build_norm(ctx0, inpL, hparams,
+                model.output_norm,
+                NULL,
+                LLM_NORM_RMS, cb, -1);
+        cb(cur, "result_norm", -1);
+
+        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cb(cur, "result_output", -1);
+
+        ggml_build_forward_expand(gf, cur);
+
+        return gf;
+    }
 };
 
 static struct ggml_cgraph * llama_build_graph_defrag(llama_context & lctx, const std::vector & ids) {
@@ -13644,6 +13824,10 @@ static struct ggml_cgraph * llama_build_graph(
             {
                 result = llm.build_deepseek2();
             } break;
+        case LLM_ARCH_CHATGLM:
+            {
+                result = llm.build_chatglm();
+            } break;
         case LLM_ARCH_BITNET:
             {
                 result = llm.build_bitnet();
@@ -15259,6 +15443,11 @@ struct llm_tokenizer_bpe {
                     " ?[^(\\s|.,!?…。，、।۔،)]+",
                 };
                 break;
+            case LLAMA_VOCAB_PRE_TYPE_CHATGLM4:
+                regex_exprs = {
+                    "(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
+                };
+                break;
             case LLAMA_VOCAB_PRE_TYPE_VIKING:
                 regex_exprs = {
                     "\\p{N}",
@@ -16160,7 +16349,6 @@ static std::vector llama_tokenize_internal(const llama_vocab &
                 if (add_special) {
                     tokenizer.append_bos(output);
                 }
-
                 for (const auto & fragment : fragment_buffer) {
                     if (fragment.type == FRAGMENT_BUFFER_VARIANT_TYPE_RAW_TEXT) {
                         auto raw_text = fragment.raw_text.substr(fragment.offset, fragment.length);
@@ -19151,6 +19339,7 @@ enum llama_rope_type llama_rope_type(const struct llama_model * model) {
         case LLM_ARCH_OLMO:
         case LLM_ARCH_ARCTIC:
         case LLM_ARCH_DEEPSEEK2:
+        case LLM_ARCH_CHATGLM:
             return LLAMA_ROPE_TYPE_NORM;
 
         // the pairs of head values are offset by n_rot/2
@@ -20883,7 +21072,6 @@ int32_t llama_tokenize(
                         bool   add_special,
                         bool   parse_special) {
     auto res = llama_tokenize_internal(model->vocab, std::string(text, text_len), add_special, parse_special);
-
     if (n_tokens_max < (int) res.size()) {
         // LLAMA_LOG_ERROR("%s: too many tokens\n", __func__);
         return -((int) res.size());
@@ -21302,6 +21490,25 @@ static int32_t llama_chat_apply_template_internal(
         if (add_ass) {
             ss << "<|start_header_id|>assistant<|end_header_id|>\n\n";
         }
+    } else if (tmpl == "chatglm3" || tmpl_contains("[gMASK]sop")) {
+        // chatglm3-6b
+        ss << "[gMASK]" << "sop";
+        for (auto message : chat) {
+            std::string role(message->role);
+            ss << "<|" << role << "|>" << "\n " << message->content;
+        }
+        if (add_ass) {
+            ss << "<|assistant|>";
+        }
+    } else if (tmpl == "chaglm4" || tmpl_contains("[gMASK]")) {
+        ss << "[gMASK]" << "";
+        for (auto message : chat) {
+            std::string role(message->role);
+            ss << "<|" << role << "|>" << "\n" << message->content;
+        }
+        if (add_ass) {
+            ss << "<|assistant|>";
+        }
     } else if (tmpl == "minicpm" || tmpl_contains(u8"<用户>")) {
         // MiniCPM-3B-OpenHermes-2.5-v2-GGUF
         for (auto message : chat) {
diff --git a/tests/test-chat-template.cpp b/tests/test-chat-template.cpp
index 03f5369109716..6583dd0b2b39b 100644
--- a/tests/test-chat-template.cpp
+++ b/tests/test-chat-template.cpp
@@ -58,6 +58,10 @@ int main(void) {
         "{% for message in messages %}{% if (message['role'] == 'user') %}{{'<|user|>' + '\n' + message['content'] + '<|end|>' + '\n' + '<|assistant|>' + '\n'}}{% elif (message['role'] == 'assistant') %}{{message['content'] + '<|end|>' + '\n'}}{% endif %}{% endfor %}",
         //Phi-3-vision
         "{% for message in messages %}{{'<|' + message['role'] + '|>' + '\n' + message['content'] + '<|end|>\n' }}{% endfor %}{% if add_generation_prompt and messages[-1]['role'] != 'assistant' %}{{- '<|assistant|>\n' -}}{% endif %}",
+        // ChatGLM3
+        "{% for message in messages %}{% if loop.first %}[gMASK]sop<|{{ message['role'] }}|>\n {{ message['content'] }}{% else %}<|{{ message['role'] }}|>\n {{ message['content'] }}{% endif %}{% endfor %}{% if add_generation_prompt %}<|assistant|>{% endif %}",
+        // ChatGLM4
+        u8"[gMASK]{% for item in messages %}{% if item['tools'] is defined %}<|system|>\n你是一个名为 ChatGLM 的人工智能助手。你是基于智谱AI训练的语言模型 GLM-4 模型开发的，你的任务是针对用户的问题和要求提供适当的答复和支持。\n\n# 可用工具{% set tools = item['tools'] %}{% for tool in tools %}{% if tool['type'] == 'function' %}\n\n## {{ tool['function']['name'] }}\n\n{{ tool['function'] | tojson(indent=4) }}\n......{% endif %}{% endfor %}{% endif %}{% if item['content'] %}<|{{ item['role'] }}|>{{ item['metadata'] }}\n{{ item['content'] }}{% endif %}{% endfor %}{% if add_generation_prompt %}<|assistant|>{% endif %}",
         // MiniCPM-3B-OpenHermes-2.5-v2-GGUF
         u8"{% for message in messages %}{% if message['role'] == 'user' %}{{'<用户>' + message['content'].strip() + ''}}{% else %}{{message['content'].strip()}}{% endif %}{% endfor %}",
         // DeepSeek-V2
@@ -98,6 +102,10 @@ int main(void) {
         "<|system|>\nYou are a helpful assistant<|end|>\n<|user|>\nHello<|end|>\n<|assistant|>\nHi there<|end|>\n<|user|>\nWho are you<|end|>\n<|assistant|>\n   I am an assistant   <|end|>\n<|user|>\nAnother question<|end|>\n<|assistant|>\n",
         //Phi-3-vision
         "<|system|>\nYou are a helpful assistant<|end|>\n<|user|>\nHello<|end|>\n<|assistant|>\nHi there<|end|>\n<|user|>\nWho are you<|end|>\n<|assistant|>\n   I am an assistant   <|end|>\n<|user|>\nAnother question<|end|>\n<|assistant|>\n",
+        // ChatGLM3
+        "[gMASK]sop<|system|>\n You are a helpful assistant<|user|>\n Hello<|assistant|>\n Hi there<|user|>\n Who are you<|assistant|>\n    I am an assistant   <|user|>\n Another question<|assistant|>",
+        // ChatGLM4
+        "[gMASK]<|system|>\nYou are a helpful assistant<|user|>\nHello<|assistant|>\nHi there<|user|>\nWho are you<|assistant|>\n   I am an assistant   <|user|>\nAnother question<|assistant|>",
         // MiniCPM-3B-OpenHermes-2.5-v2-GGUF
         u8"You are a helpful assistant<用户>HelloHi there<用户>Who are youI am an assistant<用户>Another question",
         // DeepSeek-V2

From f7cab35ef9e66c57b4a416d09eb6c814e0ba4e4c Mon Sep 17 00:00:00 2001
From: Brian 
Date: Sun, 7 Jul 2024 22:58:43 +1000
Subject: [PATCH 125/326] gguf-hash: model wide and per tensor hashing using
 xxhash and sha1 (#8048)

CLI to hash GGUF files to detect difference on a per model and per tensor level

The hash type we support is:

- `--xxh64`: use xhash 64bit hash mode (default)
- `--sha1`: use sha1
- `--uuid`: use uuid
- `--sha256`: use sha256

While most POSIX systems already have hash checking programs like sha256sum, it
is designed to check entire files. This is not ideal for our purpose if we want
to check for consistency of the tensor data even if the metadata content of the
gguf KV store has been updated.

This program is designed to hash a gguf tensor payload on a 'per tensor layer'
in addition to a 'entire tensor model' hash. The intent is that the entire
tensor layer can be checked first but if there is any detected inconsistencies,
then the per tensor hash can be used to narrow down the specific tensor layer
that has inconsistencies.

Co-authored-by: Georgi Gerganov 
---
 Makefile                                      |   18 +
 examples/CMakeLists.txt                       |    1 +
 examples/gguf-hash/CMakeLists.txt             |   15 +
 examples/gguf-hash/README.md                  |  206 +
 .../gguf-hash/deps/rotate-bits/package.json   |   13 +
 .../gguf-hash/deps/rotate-bits/rotate-bits.h  |   46 +
 examples/gguf-hash/deps/sha1/package.json     |    9 +
 examples/gguf-hash/deps/sha1/sha1.c           |  295 +
 examples/gguf-hash/deps/sha1/sha1.h           |   52 +
 examples/gguf-hash/deps/sha256/package.json   |   15 +
 examples/gguf-hash/deps/sha256/sha256.c       |  221 +
 examples/gguf-hash/deps/sha256/sha256.h       |   24 +
 examples/gguf-hash/deps/xxhash/clib.json      |   12 +
 examples/gguf-hash/deps/xxhash/xxhash.c       |   42 +
 examples/gguf-hash/deps/xxhash/xxhash.h       | 7093 +++++++++++++++++
 examples/gguf-hash/gguf-hash.cpp              |  693 ++
 gguf-py/scripts/gguf_hash.py                  |   91 +
 17 files changed, 8846 insertions(+)
 create mode 100644 examples/gguf-hash/CMakeLists.txt
 create mode 100644 examples/gguf-hash/README.md
 create mode 100644 examples/gguf-hash/deps/rotate-bits/package.json
 create mode 100644 examples/gguf-hash/deps/rotate-bits/rotate-bits.h
 create mode 100644 examples/gguf-hash/deps/sha1/package.json
 create mode 100644 examples/gguf-hash/deps/sha1/sha1.c
 create mode 100644 examples/gguf-hash/deps/sha1/sha1.h
 create mode 100644 examples/gguf-hash/deps/sha256/package.json
 create mode 100644 examples/gguf-hash/deps/sha256/sha256.c
 create mode 100644 examples/gguf-hash/deps/sha256/sha256.h
 create mode 100644 examples/gguf-hash/deps/xxhash/clib.json
 create mode 100644 examples/gguf-hash/deps/xxhash/xxhash.c
 create mode 100644 examples/gguf-hash/deps/xxhash/xxhash.h
 create mode 100644 examples/gguf-hash/gguf-hash.cpp
 create mode 100755 gguf-py/scripts/gguf_hash.py

diff --git a/Makefile b/Makefile
index 2730d8b602093..bb6e2f968cf0f 100644
--- a/Makefile
+++ b/Makefile
@@ -14,6 +14,7 @@ BUILD_TARGETS = \
 	llama-finetune \
 	llama-gbnf-validator \
 	llama-gguf \
+	llama-gguf-hash \
 	llama-gguf-split \
 	llama-gritlm \
 	llama-imatrix \
@@ -1178,6 +1179,23 @@ llama-gguf: examples/gguf/gguf.cpp \
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
 	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
 
+examples/gguf-hash/deps/sha1/sha1.o: \
+	examples/gguf-hash/deps/sha1/sha1.c
+	$(CC) $(CFLAGS) -Iexamples/gguf-hash/deps -c $< -o $@
+
+examples/gguf-hash/deps/xxhash/xxhash.o: \
+	examples/gguf-hash/deps/xxhash/xxhash.c
+	$(CC) $(CFLAGS) -Iexamples/gguf-hash/deps -c $< -o $@
+
+examples/gguf-hash/deps/sha256/sha256.o: \
+	examples/gguf-hash/deps/sha256/sha256.c
+	$(CC) $(CFLAGS) -Iexamples/gguf-hash/deps -c $< -o $@
+
+llama-gguf-hash: examples/gguf-hash/gguf-hash.cpp examples/gguf-hash/deps/sha1/sha1.o examples/gguf-hash/deps/xxhash/xxhash.o examples/gguf-hash/deps/sha256/sha256.o\
+	$(OBJ_ALL)
+	$(CXX) $(CXXFLAGS) -Iexamples/gguf-hash/deps -c $< -o $(call GET_OBJ_FILE, $<)
+	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+
 llama-gguf-split: examples/gguf-split/gguf-split.cpp \
 	$(OBJ_ALL)
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
diff --git a/examples/CMakeLists.txt b/examples/CMakeLists.txt
index 7d9ab34572b74..155743639adfd 100644
--- a/examples/CMakeLists.txt
+++ b/examples/CMakeLists.txt
@@ -23,6 +23,7 @@ else()
     add_subdirectory(export-lora)
     add_subdirectory(finetune)
     add_subdirectory(gbnf-validator)
+    add_subdirectory(gguf-hash)
     add_subdirectory(gguf-split)
     add_subdirectory(gguf)
     add_subdirectory(gritlm)
diff --git a/examples/gguf-hash/CMakeLists.txt b/examples/gguf-hash/CMakeLists.txt
new file mode 100644
index 0000000000000..633f4553594bb
--- /dev/null
+++ b/examples/gguf-hash/CMakeLists.txt
@@ -0,0 +1,15 @@
+set(TARGET llama-gguf-hash)
+add_executable(${TARGET} gguf-hash.cpp)
+install(TARGETS ${TARGET} RUNTIME)
+
+# clibs dependencies
+include_directories(deps/)
+add_library(xxhash OBJECT deps/xxhash/xxhash.c deps/xxhash/xxhash.h)
+target_link_libraries(${TARGET} PRIVATE xxhash)
+add_library(sha1 OBJECT deps/sha1/sha1.c deps/sha1/sha1.h)
+target_link_libraries(${TARGET} PRIVATE sha1)
+add_library(sha256 OBJECT deps/sha256/sha256.c deps/sha256/sha256.h)
+target_link_libraries(${TARGET} PRIVATE sha256)
+
+target_link_libraries(${TARGET} PRIVATE ggml ${CMAKE_THREAD_LIBS_INIT})
+target_compile_features(${TARGET} PRIVATE cxx_std_11)
diff --git a/examples/gguf-hash/README.md b/examples/gguf-hash/README.md
new file mode 100644
index 0000000000000..2320ffd8181b3
--- /dev/null
+++ b/examples/gguf-hash/README.md
@@ -0,0 +1,206 @@
+
+# llama-gguf-hash
+
+CLI to hash GGUF files to detect difference on a per model and per tensor level.
+
+**Command line options:**
+
+- `--help`: display help message
+- `--xxh64`: use xhash 64bit hash mode (default)
+- `--sha1`: use sha1
+- `--uuid`: use uuid
+- `--sha256`: use sha256
+- `--all`: use all hash
+- `--no-layer`: exclude per layer hash
+- `--uuid`: generate UUIDv5 ID
+- `-c`, `--check `:  verify against a manifest
+
+## About
+
+While most POSIX systems already have hash checking programs like sha256sum, it
+is designed to check entire files. This is not ideal for our purpose if we want
+to check for consistency of the tensor data even if the metadata content of the
+gguf KV store has been updated.
+
+This program is designed to hash a gguf tensor payload on a 'per tensor layer'
+in addition to a 'entire tensor model' hash. The intent is that the entire
+tensor layer can be checked first but if there is any detected inconsistencies,
+then the per tensor hash can be used to narrow down the specific tensor layer
+that has inconsistencies.
+
+For Maintainers:
+- Detection of tensor inconsistency during development and automated tests
+    - This is served by xxh64 which is fast
+    - This is also served by having per tensor layer to assist in narrowing down
+      the location of the faulty tensor layer
+    - This is also served by sha1 which is much slower but more widely supported
+
+For Model Creators:
+- Optional consistent UUID generation based on model tensor content
+    - This is served by UUIDv5 which is useful for databases keys
+        - llama.cpp UUIDv5 Namespace: `ef001206-dadc-5f6d-a15f-3359e577d4e5`
+            - Made via UUIDv5 URL namespace of `en.wikipedia.org/wiki/Llama.cpp`
+
+For Model Users:
+- Assurance of tensor layer integrity even if metadata was updated
+    - This is served by sha256 which is still considered very secure as of 2024
+
+### Design Note
+
+- The default behavior of this program if no arguments is provided is to hash
+  using xxhash's xxh32 mode because it is very fast and is primarily targeted
+  towards maintainers who may want to use this in automated tests.
+- xxhash support xxh32 and xxh128 for 32bit hash and 128bit hash respectively
+  however we picked 64bit xxhash as most computers are 64bit as of 2024 and thus
+  would have a better affinity to calculating hash that is 64bit in size.
+
+## Compile Example
+
+```bash
+cmake -B build -DCMAKE_BUILD_TYPE=Debug -DLLAMA_FATAL_WARNINGS=ON
+make -C build clean
+make -C build llama-gguf-hash VERBOSE=1
+./build/bin/llama-gguf-hash test.gguf
+./build/bin/llama-gguf-hash --xxh64 test.gguf
+./build/bin/llama-gguf-hash --sha1 test.gguf
+./build/bin/llama-gguf-hash --uuid test.gguf
+./build/bin/llama-gguf-hash --sha256 test.gguf
+```
+
+## Generation and Verification Example
+
+To generate we may use this command
+
+```bash
+./llama-gguf-hash --all test.gguf > test.gguf.manifest
+```
+
+Which would generate a manifest that looks like below, which contains multiple hash type and per tensor layer hashes as well
+(This excludes UUID as that is an ID not a hash)
+
+```bash
+xxh64     f66e9cd66a4396a0  test.gguf:tensor_0
+sha1      59f79ecefd8125a996fdf419239051a7e99e5f20  test.gguf:tensor_0
+sha256    c0510d38fa060c46265e0160a85c7243096b01dd31c2f355bdbb5516b20de1bd  test.gguf:tensor_0
+xxh64     7d3a1f9ac04d0537  test.gguf:tensor_1
+sha1      4765f592eacf096df4628ba59476af94d767080a  test.gguf:tensor_1
+sha256    8514cbcc73692a2c56bd7a33a022edd5ff819614bd23b19915d7224387f397a7  test.gguf:tensor_1
+xxh64     a0af5d700049693b  test.gguf:tensor_2
+sha1      25cbfbad4513cc348e2c95ebdee69d6ff2fd8753  test.gguf:tensor_2
+sha256    947e6b36e20f2cc95e1d2ce1c1669d813d574657ac6b5ac5196158d454d35180  test.gguf:tensor_2
+xxh64     e83fddf559d7b6a6  test.gguf:tensor_3
+sha1      a9cba73e2d90f2ee3dae2548caa42bef3fe6a96c  test.gguf:tensor_3
+sha256    423b044e016d8ac73c39f23f60bf01bedef5ecb03c0230accd824c91fe86f1a1  test.gguf:tensor_3
+xxh64     1257733306b7992d  test.gguf:tensor_4
+sha1      d7bc61db93bb685ce9d598da89717c66729b7543  test.gguf:tensor_4
+sha256    79737cb3912d4201384cf7f16a1a37ff7823f23ea796cb205b6ca361ab9e3ebf  test.gguf:tensor_4
+xxh64     d238d16ba4711e58  test.gguf:tensor_5
+sha1      0706566c198fe1072f37e0a5135b4b5f23654c52  test.gguf:tensor_5
+sha256    60949be8298eced0ecdde64487643d018407bd261691e061d9e9c3dbc9fd358b  test.gguf:tensor_5
+xxh64     3fbc3b65ab8c7f39  test.gguf:tensor_6
+sha1      73922a0727226a409049f6fc3172a52219ca6f00  test.gguf:tensor_6
+sha256    574f4c46ff384a3b9a225eb955d2a871847a2e8b3fa59387a8252832e92ef7b0  test.gguf:tensor_6
+xxh64     c22021c29854f093  test.gguf:tensor_7
+sha1      efc39cece6a951188fc41e354c73bbfe6813d447  test.gguf:tensor_7
+sha256    4c0410cd3c500f078ae5b21e8dc9eb79e29112713b2ab58a882f82a3868d4d75  test.gguf:tensor_7
+xxh64     936df61f5d64261f  test.gguf:tensor_8
+sha1      c2490296d789a4f34398a337fed8377d943d9f06  test.gguf:tensor_8
+sha256    c4401313feeba0261275c3b25bd2d8fe40ce04e0f440c2980ed0e9674c30ff01  test.gguf:tensor_8
+xxh64     93fd20c64421c081  test.gguf:tensor_9
+sha1      7047ce1e78437a6884337a3751c7ee0421918a65  test.gguf:tensor_9
+sha256    23d57cf0d7a6e90b0b3616b41300e0cd354781e812add854a5f95aa55f2bc514  test.gguf:tensor_9
+xxh64     5a54d3aad816f302  test.gguf
+sha1      d15be52c4ff213e823cb6dd13af7ee2f978e7042  test.gguf
+sha256    7dd641b32f59b60dbd4b5420c4b0f6321ccf48f58f6ae201a3dbc4a58a27c6e4  test.gguf
+```
+
+We can then use the normal check command which will by default check for the highest security strength hash and verify against that:
+
+```bash
+$ ./llama-gguf-hash --check test.gguf.manifest test.gguf
+manifest  test.gguf.manifest  sha256  sha1  xxh64
+sha256    c0510d38fa060c46265e0160a85c7243096b01dd31c2f355bdbb5516b20de1bd  test.gguf:tensor_0  -  Ok
+sha256    8514cbcc73692a2c56bd7a33a022edd5ff819614bd23b19915d7224387f397a7  test.gguf:tensor_1  -  Ok
+sha256    947e6b36e20f2cc95e1d2ce1c1669d813d574657ac6b5ac5196158d454d35180  test.gguf:tensor_2  -  Ok
+sha256    423b044e016d8ac73c39f23f60bf01bedef5ecb03c0230accd824c91fe86f1a1  test.gguf:tensor_3  -  Ok
+sha256    79737cb3912d4201384cf7f16a1a37ff7823f23ea796cb205b6ca361ab9e3ebf  test.gguf:tensor_4  -  Ok
+sha256    60949be8298eced0ecdde64487643d018407bd261691e061d9e9c3dbc9fd358b  test.gguf:tensor_5  -  Ok
+sha256    574f4c46ff384a3b9a225eb955d2a871847a2e8b3fa59387a8252832e92ef7b0  test.gguf:tensor_6  -  Ok
+sha256    4c0410cd3c500f078ae5b21e8dc9eb79e29112713b2ab58a882f82a3868d4d75  test.gguf:tensor_7  -  Ok
+sha256    c4401313feeba0261275c3b25bd2d8fe40ce04e0f440c2980ed0e9674c30ff01  test.gguf:tensor_8  -  Ok
+sha256    23d57cf0d7a6e90b0b3616b41300e0cd354781e812add854a5f95aa55f2bc514  test.gguf:tensor_9  -  Ok
+sha256    7dd641b32f59b60dbd4b5420c4b0f6321ccf48f58f6ae201a3dbc4a58a27c6e4  test.gguf  -  Ok
+
+Verification results for test.gguf.manifest - Success
+```
+
+Or we may explicitly ask for a faster hash like:
+
+```bash
+$ ./llama-gguf-hash --check test.gguf.manifest --xxh64 test.gguf
+manifest  test.gguf.manifest  sha256  sha1  xxh64
+xxh64     f66e9cd66a4396a0  test.gguf:tensor_0  -  Ok
+xxh64     7d3a1f9ac04d0537  test.gguf:tensor_1  -  Ok
+xxh64     a0af5d700049693b  test.gguf:tensor_2  -  Ok
+xxh64     e83fddf559d7b6a6  test.gguf:tensor_3  -  Ok
+xxh64     1257733306b7992d  test.gguf:tensor_4  -  Ok
+xxh64     d238d16ba4711e58  test.gguf:tensor_5  -  Ok
+xxh64     3fbc3b65ab8c7f39  test.gguf:tensor_6  -  Ok
+xxh64     c22021c29854f093  test.gguf:tensor_7  -  Ok
+xxh64     936df61f5d64261f  test.gguf:tensor_8  -  Ok
+xxh64     93fd20c64421c081  test.gguf:tensor_9  -  Ok
+xxh64     5a54d3aad816f302  test.gguf  -  Ok
+
+Verification results for test.gguf.manifest - Success
+```
+
+Or maybe we want to just check that all the hash is valid:
+
+```bash
+$./llama-gguf-hash --check test.gguf.manifest --all test.gguf.manifest
+manifest  test.gguf.manifest  sha256  sha1  xxh64
+xxh64     f66e9cd66a4396a0  test.gguf:tensor_0  -  Ok
+sha1      59f79ecefd8125a996fdf419239051a7e99e5f20  test.gguf:tensor_0  -  Ok
+sha256    c0510d38fa060c46265e0160a85c7243096b01dd31c2f355bdbb5516b20de1bd  test.gguf:tensor_0  -  Ok
+xxh64     7d3a1f9ac04d0537  test.gguf:tensor_1  -  Ok
+sha1      4765f592eacf096df4628ba59476af94d767080a  test.gguf:tensor_1  -  Ok
+sha256    8514cbcc73692a2c56bd7a33a022edd5ff819614bd23b19915d7224387f397a7  test.gguf:tensor_1  -  Ok
+xxh64     a0af5d700049693b  test.gguf:tensor_2  -  Ok
+sha1      25cbfbad4513cc348e2c95ebdee69d6ff2fd8753  test.gguf:tensor_2  -  Ok
+sha256    947e6b36e20f2cc95e1d2ce1c1669d813d574657ac6b5ac5196158d454d35180  test.gguf:tensor_2  -  Ok
+xxh64     e83fddf559d7b6a6  test.gguf:tensor_3  -  Ok
+sha1      a9cba73e2d90f2ee3dae2548caa42bef3fe6a96c  test.gguf:tensor_3  -  Ok
+sha256    423b044e016d8ac73c39f23f60bf01bedef5ecb03c0230accd824c91fe86f1a1  test.gguf:tensor_3  -  Ok
+xxh64     1257733306b7992d  test.gguf:tensor_4  -  Ok
+sha1      d7bc61db93bb685ce9d598da89717c66729b7543  test.gguf:tensor_4  -  Ok
+sha256    79737cb3912d4201384cf7f16a1a37ff7823f23ea796cb205b6ca361ab9e3ebf  test.gguf:tensor_4  -  Ok
+xxh64     d238d16ba4711e58  test.gguf:tensor_5  -  Ok
+sha1      0706566c198fe1072f37e0a5135b4b5f23654c52  test.gguf:tensor_5  -  Ok
+sha256    60949be8298eced0ecdde64487643d018407bd261691e061d9e9c3dbc9fd358b  test.gguf:tensor_5  -  Ok
+xxh64     3fbc3b65ab8c7f39  test.gguf:tensor_6  -  Ok
+sha1      73922a0727226a409049f6fc3172a52219ca6f00  test.gguf:tensor_6  -  Ok
+sha256    574f4c46ff384a3b9a225eb955d2a871847a2e8b3fa59387a8252832e92ef7b0  test.gguf:tensor_6  -  Ok
+xxh64     c22021c29854f093  test.gguf:tensor_7  -  Ok
+sha1      efc39cece6a951188fc41e354c73bbfe6813d447  test.gguf:tensor_7  -  Ok
+sha256    4c0410cd3c500f078ae5b21e8dc9eb79e29112713b2ab58a882f82a3868d4d75  test.gguf:tensor_7  -  Ok
+xxh64     936df61f5d64261f  test.gguf:tensor_8  -  Ok
+sha1      c2490296d789a4f34398a337fed8377d943d9f06  test.gguf:tensor_8  -  Ok
+sha256    c4401313feeba0261275c3b25bd2d8fe40ce04e0f440c2980ed0e9674c30ff01  test.gguf:tensor_8  -  Ok
+xxh64     93fd20c64421c081  test.gguf:tensor_9  -  Ok
+sha1      7047ce1e78437a6884337a3751c7ee0421918a65  test.gguf:tensor_9  -  Ok
+sha256    23d57cf0d7a6e90b0b3616b41300e0cd354781e812add854a5f95aa55f2bc514  test.gguf:tensor_9  -  Ok
+xxh64     5a54d3aad816f302  test.gguf  -  Ok
+sha1      d15be52c4ff213e823cb6dd13af7ee2f978e7042  test.gguf  -  Ok
+sha256    7dd641b32f59b60dbd4b5420c4b0f6321ccf48f58f6ae201a3dbc4a58a27c6e4  test.gguf  -  Ok
+
+Verification results for test.gguf.manifest - Success
+```
+
+
+## Crypto/Hash Libraries Used
+
+These micro c libraries dependencies was installed via the [clib c package manager](https://github.com/clibs)
+
+- https://github.com/mofosyne/xxHash (From: https://github.com/Cyan4973/xxHash)
+- https://github.com/clibs/sha1/
+- https://github.com/jb55/sha256.c
diff --git a/examples/gguf-hash/deps/rotate-bits/package.json b/examples/gguf-hash/deps/rotate-bits/package.json
new file mode 100644
index 0000000000000..74c0bef68d8bd
--- /dev/null
+++ b/examples/gguf-hash/deps/rotate-bits/package.json
@@ -0,0 +1,13 @@
+{
+  "name": "rotate-bits",
+  "version": "0.1.1",
+  "repo": "jb55/rotate-bits.h",
+  "description": "rotate bits",
+  "keywords": ["rotl", "rotr"],
+  "src": ["rotate-bits.h"],
+  "license": "Public Domain",
+  "development": {
+    "thlorenz/tap.c": "*"
+  }
+}
+
diff --git a/examples/gguf-hash/deps/rotate-bits/rotate-bits.h b/examples/gguf-hash/deps/rotate-bits/rotate-bits.h
new file mode 100644
index 0000000000000..75c4881fc322f
--- /dev/null
+++ b/examples/gguf-hash/deps/rotate-bits/rotate-bits.h
@@ -0,0 +1,46 @@
+
+
+#ifndef __ROTATE_DEFS_H
+#define __ROTATE_DEFS_H
+
+#ifdef _MSC_VER
+
+#include 
+
+#define ROTL32(v, n) _rotl((v), (n))
+#define ROTL64(v, n) _rotl64((v), (n))
+
+#define ROTR32(v, n) _rotr((v), (n))
+#define ROTR64(v, n) _rotr64((v), (n))
+
+#else
+
+#include 
+
+#define U8V(v) ((uint8_t)(v) & 0xFFU)
+#define U16V(v) ((uint16_t)(v) & 0xFFFFU)
+#define U32V(v) ((uint32_t)(v) & 0xFFFFFFFFU)
+#define U64V(v) ((uint64_t)(v) & 0xFFFFFFFFFFFFFFFFU)
+
+#define ROTL32(v, n) \
+  (U32V((uint32_t)(v) << (n)) | ((uint32_t)(v) >> (32 - (n))))
+
+// tests fail if we don't have this cast...
+#define ROTL64(v, n) \
+  (U64V((uint64_t)(v) << (n)) | ((uint64_t)(v) >> (64 - (n))))
+
+#define ROTR32(v, n) ROTL32(v, 32 - (n))
+#define ROTR64(v, n) ROTL64(v, 64 - (n))
+
+#endif
+
+#define ROTL8(v, n) \
+  (U8V((uint8_t)(v) << (n)) | ((uint8_t)(v) >> (8 - (n))))
+
+#define ROTL16(v, n) \
+  (U16V((uint16_t)(v) << (n)) | ((uint16_t)(v) >> (16 - (n))))
+
+#define ROTR8(v, n) ROTL8(v, 8 - (n))
+#define ROTR16(v, n) ROTL16(v, 16 - (n))
+
+#endif
diff --git a/examples/gguf-hash/deps/sha1/package.json b/examples/gguf-hash/deps/sha1/package.json
new file mode 100644
index 0000000000000..6a5843dd1ef46
--- /dev/null
+++ b/examples/gguf-hash/deps/sha1/package.json
@@ -0,0 +1,9 @@
+{
+  "name": "sha1",
+  "version": "0.0.1",
+  "repo": "clibs/sha1",
+  "description": "sha1 hash algorithm",
+  "keywords": ["sha1", "hash"],
+  "license": "public domain",
+  "src": ["sha1.c", "sha1.h"]
+}
diff --git a/examples/gguf-hash/deps/sha1/sha1.c b/examples/gguf-hash/deps/sha1/sha1.c
new file mode 100644
index 0000000000000..76cd6ca3381d5
--- /dev/null
+++ b/examples/gguf-hash/deps/sha1/sha1.c
@@ -0,0 +1,295 @@
+/*
+SHA-1 in C
+By Steve Reid 
+100% Public Domain
+
+Test Vectors (from FIPS PUB 180-1)
+"abc"
+  A9993E36 4706816A BA3E2571 7850C26C 9CD0D89D
+"abcdbcdecdefdefgefghfghighijhijkijkljklmklmnlmnomnopnopq"
+  84983E44 1C3BD26E BAAE4AA1 F95129E5 E54670F1
+A million repetitions of "a"
+  34AA973C D4C4DAA4 F61EEB2B DBAD2731 6534016F
+*/
+
+/* #define LITTLE_ENDIAN * This should be #define'd already, if true. */
+/* #define SHA1HANDSOFF * Copies data before messing with it. */
+
+#define SHA1HANDSOFF
+
+#include 
+#include 
+
+/* for uint32_t */
+#include 
+
+#include "sha1.h"
+
+
+#define rol(value, bits) (((value) << (bits)) | ((value) >> (32 - (bits))))
+
+/* blk0() and blk() perform the initial expand. */
+/* I got the idea of expanding during the round function from SSLeay */
+#if BYTE_ORDER == LITTLE_ENDIAN
+#define blk0(i) (block->l[i] = (rol(block->l[i],24)&0xFF00FF00) \
+    |(rol(block->l[i],8)&0x00FF00FF))
+#elif BYTE_ORDER == BIG_ENDIAN
+#define blk0(i) block->l[i]
+#else
+#error "Endianness not defined!"
+#endif
+#define blk(i) (block->l[i&15] = rol(block->l[(i+13)&15]^block->l[(i+8)&15] \
+    ^block->l[(i+2)&15]^block->l[i&15],1))
+
+/* (R0+R1), R2, R3, R4 are the different operations used in SHA1 */
+#define R0(v,w,x,y,z,i) z+=((w&(x^y))^y)+blk0(i)+0x5A827999+rol(v,5);w=rol(w,30);
+#define R1(v,w,x,y,z,i) z+=((w&(x^y))^y)+blk(i)+0x5A827999+rol(v,5);w=rol(w,30);
+#define R2(v,w,x,y,z,i) z+=(w^x^y)+blk(i)+0x6ED9EBA1+rol(v,5);w=rol(w,30);
+#define R3(v,w,x,y,z,i) z+=(((w|x)&y)|(w&x))+blk(i)+0x8F1BBCDC+rol(v,5);w=rol(w,30);
+#define R4(v,w,x,y,z,i) z+=(w^x^y)+blk(i)+0xCA62C1D6+rol(v,5);w=rol(w,30);
+
+
+/* Hash a single 512-bit block. This is the core of the algorithm. */
+
+void SHA1Transform(
+    uint32_t state[5],
+    const unsigned char buffer[64]
+)
+{
+    uint32_t a, b, c, d, e;
+
+    typedef union
+    {
+        unsigned char c[64];
+        uint32_t l[16];
+    } CHAR64LONG16;
+
+#ifdef SHA1HANDSOFF
+    CHAR64LONG16 block[1];      /* use array to appear as a pointer */
+
+    memcpy(block, buffer, 64);
+#else
+    /* The following had better never be used because it causes the
+     * pointer-to-const buffer to be cast into a pointer to non-const.
+     * And the result is written through.  I threw a "const" in, hoping
+     * this will cause a diagnostic.
+     */
+    CHAR64LONG16 *block = (const CHAR64LONG16 *) buffer;
+#endif
+    /* Copy context->state[] to working vars */
+    a = state[0];
+    b = state[1];
+    c = state[2];
+    d = state[3];
+    e = state[4];
+    /* 4 rounds of 20 operations each. Loop unrolled. */
+    R0(a, b, c, d, e, 0);
+    R0(e, a, b, c, d, 1);
+    R0(d, e, a, b, c, 2);
+    R0(c, d, e, a, b, 3);
+    R0(b, c, d, e, a, 4);
+    R0(a, b, c, d, e, 5);
+    R0(e, a, b, c, d, 6);
+    R0(d, e, a, b, c, 7);
+    R0(c, d, e, a, b, 8);
+    R0(b, c, d, e, a, 9);
+    R0(a, b, c, d, e, 10);
+    R0(e, a, b, c, d, 11);
+    R0(d, e, a, b, c, 12);
+    R0(c, d, e, a, b, 13);
+    R0(b, c, d, e, a, 14);
+    R0(a, b, c, d, e, 15);
+    R1(e, a, b, c, d, 16);
+    R1(d, e, a, b, c, 17);
+    R1(c, d, e, a, b, 18);
+    R1(b, c, d, e, a, 19);
+    R2(a, b, c, d, e, 20);
+    R2(e, a, b, c, d, 21);
+    R2(d, e, a, b, c, 22);
+    R2(c, d, e, a, b, 23);
+    R2(b, c, d, e, a, 24);
+    R2(a, b, c, d, e, 25);
+    R2(e, a, b, c, d, 26);
+    R2(d, e, a, b, c, 27);
+    R2(c, d, e, a, b, 28);
+    R2(b, c, d, e, a, 29);
+    R2(a, b, c, d, e, 30);
+    R2(e, a, b, c, d, 31);
+    R2(d, e, a, b, c, 32);
+    R2(c, d, e, a, b, 33);
+    R2(b, c, d, e, a, 34);
+    R2(a, b, c, d, e, 35);
+    R2(e, a, b, c, d, 36);
+    R2(d, e, a, b, c, 37);
+    R2(c, d, e, a, b, 38);
+    R2(b, c, d, e, a, 39);
+    R3(a, b, c, d, e, 40);
+    R3(e, a, b, c, d, 41);
+    R3(d, e, a, b, c, 42);
+    R3(c, d, e, a, b, 43);
+    R3(b, c, d, e, a, 44);
+    R3(a, b, c, d, e, 45);
+    R3(e, a, b, c, d, 46);
+    R3(d, e, a, b, c, 47);
+    R3(c, d, e, a, b, 48);
+    R3(b, c, d, e, a, 49);
+    R3(a, b, c, d, e, 50);
+    R3(e, a, b, c, d, 51);
+    R3(d, e, a, b, c, 52);
+    R3(c, d, e, a, b, 53);
+    R3(b, c, d, e, a, 54);
+    R3(a, b, c, d, e, 55);
+    R3(e, a, b, c, d, 56);
+    R3(d, e, a, b, c, 57);
+    R3(c, d, e, a, b, 58);
+    R3(b, c, d, e, a, 59);
+    R4(a, b, c, d, e, 60);
+    R4(e, a, b, c, d, 61);
+    R4(d, e, a, b, c, 62);
+    R4(c, d, e, a, b, 63);
+    R4(b, c, d, e, a, 64);
+    R4(a, b, c, d, e, 65);
+    R4(e, a, b, c, d, 66);
+    R4(d, e, a, b, c, 67);
+    R4(c, d, e, a, b, 68);
+    R4(b, c, d, e, a, 69);
+    R4(a, b, c, d, e, 70);
+    R4(e, a, b, c, d, 71);
+    R4(d, e, a, b, c, 72);
+    R4(c, d, e, a, b, 73);
+    R4(b, c, d, e, a, 74);
+    R4(a, b, c, d, e, 75);
+    R4(e, a, b, c, d, 76);
+    R4(d, e, a, b, c, 77);
+    R4(c, d, e, a, b, 78);
+    R4(b, c, d, e, a, 79);
+    /* Add the working vars back into context.state[] */
+    state[0] += a;
+    state[1] += b;
+    state[2] += c;
+    state[3] += d;
+    state[4] += e;
+    /* Wipe variables */
+    a = b = c = d = e = 0;
+#ifdef SHA1HANDSOFF
+    memset(block, '\0', sizeof(block));
+#endif
+}
+
+
+/* SHA1Init - Initialize new context */
+
+void SHA1Init(
+    SHA1_CTX * context
+)
+{
+    /* SHA1 initialization constants */
+    context->state[0] = 0x67452301;
+    context->state[1] = 0xEFCDAB89;
+    context->state[2] = 0x98BADCFE;
+    context->state[3] = 0x10325476;
+    context->state[4] = 0xC3D2E1F0;
+    context->count[0] = context->count[1] = 0;
+}
+
+
+/* Run your data through this. */
+
+void SHA1Update(
+    SHA1_CTX * context,
+    const unsigned char *data,
+    uint32_t len
+)
+{
+    uint32_t i;
+
+    uint32_t j;
+
+    j = context->count[0];
+    if ((context->count[0] += len << 3) < j)
+        context->count[1]++;
+    context->count[1] += (len >> 29);
+    j = (j >> 3) & 63;
+    if ((j + len) > 63)
+    {
+        memcpy(&context->buffer[j], data, (i = 64 - j));
+        SHA1Transform(context->state, context->buffer);
+        for (; i + 63 < len; i += 64)
+        {
+            SHA1Transform(context->state, &data[i]);
+        }
+        j = 0;
+    }
+    else
+        i = 0;
+    memcpy(&context->buffer[j], &data[i], len - i);
+}
+
+
+/* Add padding and return the message digest. */
+
+void SHA1Final(
+    unsigned char digest[20],
+    SHA1_CTX * context
+)
+{
+    unsigned i;
+
+    unsigned char finalcount[8];
+
+    unsigned char c;
+
+#if 0    /* untested "improvement" by DHR */
+    /* Convert context->count to a sequence of bytes
+     * in finalcount.  Second element first, but
+     * big-endian order within element.
+     * But we do it all backwards.
+     */
+    unsigned char *fcp = &finalcount[8];
+
+    for (i = 0; i < 2; i++)
+    {
+        uint32_t t = context->count[i];
+
+        int j;
+
+        for (j = 0; j < 4; t >>= 8, j++)
+            *--fcp = (unsigned char) t}
+#else
+    for (i = 0; i < 8; i++)
+    {
+        finalcount[i] = (unsigned char) ((context->count[(i >= 4 ? 0 : 1)] >> ((3 - (i & 3)) * 8)) & 255);      /* Endian independent */
+    }
+#endif
+    c = 0200;
+    SHA1Update(context, &c, 1);
+    while ((context->count[0] & 504) != 448)
+    {
+        c = 0000;
+        SHA1Update(context, &c, 1);
+    }
+    SHA1Update(context, finalcount, 8); /* Should cause a SHA1Transform() */
+    for (i = 0; i < 20; i++)
+    {
+        digest[i] = (unsigned char)
+            ((context->state[i >> 2] >> ((3 - (i & 3)) * 8)) & 255);
+    }
+    /* Wipe variables */
+    memset(context, '\0', sizeof(*context));
+    memset(&finalcount, '\0', sizeof(finalcount));
+}
+
+void SHA1(
+    char *hash_out,
+    const char *str,
+    uint32_t len)
+{
+    SHA1_CTX ctx;
+    unsigned int ii;
+
+    SHA1Init(&ctx);
+    for (ii=0; ii
+   100% Public Domain
+ */
+
+#include "stdint.h"
+
+#if defined(__cplusplus)
+extern "C" {
+#endif
+
+typedef struct
+{
+    uint32_t state[5];
+    uint32_t count[2];
+    unsigned char buffer[64];
+} SHA1_CTX;
+
+void SHA1Transform(
+    uint32_t state[5],
+    const unsigned char buffer[64]
+    );
+
+void SHA1Init(
+    SHA1_CTX * context
+    );
+
+void SHA1Update(
+    SHA1_CTX * context,
+    const unsigned char *data,
+    uint32_t len
+    );
+
+void SHA1Final(
+    unsigned char digest[20],
+    SHA1_CTX * context
+    );
+
+void SHA1(
+    char *hash_out,
+    const char *str,
+    uint32_t len);
+
+#if defined(__cplusplus)
+}
+#endif
+
+#endif /* SHA1_H */
diff --git a/examples/gguf-hash/deps/sha256/package.json b/examples/gguf-hash/deps/sha256/package.json
new file mode 100644
index 0000000000000..b92a0412738df
--- /dev/null
+++ b/examples/gguf-hash/deps/sha256/package.json
@@ -0,0 +1,15 @@
+{
+  "name": "sha256",
+  "version": "0.0.2",
+  "repo": "jb55/sha256.c",
+  "description": "sha256 in c",
+  "keywords": ["sha256", "sha2"],
+  "src": ["sha256.c", "sha256.h"],
+  "dependencies": {
+    "jb55/rotate-bits.h": "0.1.1"
+  },
+  "development": {
+    "thlorenz/tap.c": "*"
+  }
+}
+
diff --git a/examples/gguf-hash/deps/sha256/sha256.c b/examples/gguf-hash/deps/sha256/sha256.c
new file mode 100644
index 0000000000000..a7a87aeb20032
--- /dev/null
+++ b/examples/gguf-hash/deps/sha256/sha256.c
@@ -0,0 +1,221 @@
+/* Crypto/Sha256.c -- SHA-256 Hash
+2010-06-11 : Igor Pavlov : Public domain
+This code is based on public domain code from Wei Dai's Crypto++ library. */
+
+#include "rotate-bits/rotate-bits.h"
+#include "sha256.h"
+
+/* define it for speed optimization */
+#define _SHA256_UNROLL
+#define _SHA256_UNROLL2
+
+void
+sha256_init(sha256_t *p)
+{
+  p->state[0] = 0x6a09e667;
+  p->state[1] = 0xbb67ae85;
+  p->state[2] = 0x3c6ef372;
+  p->state[3] = 0xa54ff53a;
+  p->state[4] = 0x510e527f;
+  p->state[5] = 0x9b05688c;
+  p->state[6] = 0x1f83d9ab;
+  p->state[7] = 0x5be0cd19;
+  p->count = 0;
+}
+
+#define S0(x) (ROTR32(x, 2) ^ ROTR32(x,13) ^ ROTR32(x, 22))
+#define S1(x) (ROTR32(x, 6) ^ ROTR32(x,11) ^ ROTR32(x, 25))
+#define s0(x) (ROTR32(x, 7) ^ ROTR32(x,18) ^ (x >> 3))
+#define s1(x) (ROTR32(x,17) ^ ROTR32(x,19) ^ (x >> 10))
+
+#define blk0(i) (W[i] = data[i])
+#define blk2(i) (W[i&15] += s1(W[(i-2)&15]) + W[(i-7)&15] + s0(W[(i-15)&15]))
+
+#define Ch(x,y,z) (z^(x&(y^z)))
+#define Maj(x,y,z) ((x&y)|(z&(x|y)))
+
+#define a(i) T[(0-(i))&7]
+#define b(i) T[(1-(i))&7]
+#define c(i) T[(2-(i))&7]
+#define d(i) T[(3-(i))&7]
+#define e(i) T[(4-(i))&7]
+#define f(i) T[(5-(i))&7]
+#define g(i) T[(6-(i))&7]
+#define h(i) T[(7-(i))&7]
+
+
+#ifdef _SHA256_UNROLL2
+
+#define R(a,b,c,d,e,f,g,h, i) h += S1(e) + Ch(e,f,g) + K[i+j] + (j?blk2(i):blk0(i));\
+  d += h; h += S0(a) + Maj(a, b, c)
+
+#define RX_8(i) \
+  R(a,b,c,d,e,f,g,h, i); \
+  R(h,a,b,c,d,e,f,g, (i+1)); \
+  R(g,h,a,b,c,d,e,f, (i+2)); \
+  R(f,g,h,a,b,c,d,e, (i+3)); \
+  R(e,f,g,h,a,b,c,d, (i+4)); \
+  R(d,e,f,g,h,a,b,c, (i+5)); \
+  R(c,d,e,f,g,h,a,b, (i+6)); \
+  R(b,c,d,e,f,g,h,a, (i+7))
+
+#else
+
+#define R(i) h(i) += S1(e(i)) + Ch(e(i),f(i),g(i)) + K[i+j] + (j?blk2(i):blk0(i));\
+  d(i) += h(i); h(i) += S0(a(i)) + Maj(a(i), b(i), c(i))
+
+#ifdef _SHA256_UNROLL
+
+#define RX_8(i) R(i+0); R(i+1); R(i+2); R(i+3); R(i+4); R(i+5); R(i+6); R(i+7);
+
+#endif
+
+#endif
+
+static const uint32_t K[64] = {
+  0x428a2f98, 0x71374491, 0xb5c0fbcf, 0xe9b5dba5,
+  0x3956c25b, 0x59f111f1, 0x923f82a4, 0xab1c5ed5,
+  0xd807aa98, 0x12835b01, 0x243185be, 0x550c7dc3,
+  0x72be5d74, 0x80deb1fe, 0x9bdc06a7, 0xc19bf174,
+  0xe49b69c1, 0xefbe4786, 0x0fc19dc6, 0x240ca1cc,
+  0x2de92c6f, 0x4a7484aa, 0x5cb0a9dc, 0x76f988da,
+  0x983e5152, 0xa831c66d, 0xb00327c8, 0xbf597fc7,
+  0xc6e00bf3, 0xd5a79147, 0x06ca6351, 0x14292967,
+  0x27b70a85, 0x2e1b2138, 0x4d2c6dfc, 0x53380d13,
+  0x650a7354, 0x766a0abb, 0x81c2c92e, 0x92722c85,
+  0xa2bfe8a1, 0xa81a664b, 0xc24b8b70, 0xc76c51a3,
+  0xd192e819, 0xd6990624, 0xf40e3585, 0x106aa070,
+  0x19a4c116, 0x1e376c08, 0x2748774c, 0x34b0bcb5,
+  0x391c0cb3, 0x4ed8aa4a, 0x5b9cca4f, 0x682e6ff3,
+  0x748f82ee, 0x78a5636f, 0x84c87814, 0x8cc70208,
+  0x90befffa, 0xa4506ceb, 0xbef9a3f7, 0xc67178f2
+};
+
+static void
+sha256_transform(uint32_t *state, const uint32_t *data)
+{
+  uint32_t W[16] = {0};
+  unsigned j;
+  #ifdef _SHA256_UNROLL2
+  uint32_t a,b,c,d,e,f,g,h;
+  a = state[0];
+  b = state[1];
+  c = state[2];
+  d = state[3];
+  e = state[4];
+  f = state[5];
+  g = state[6];
+  h = state[7];
+  #else
+  uint32_t T[8];
+  for (j = 0; j < 8; j++)
+    T[j] = state[j];
+  #endif
+
+  for (j = 0; j < 64; j += 16)
+  {
+    #if defined(_SHA256_UNROLL) || defined(_SHA256_UNROLL2)
+    RX_8(0); RX_8(8);
+    #else
+    unsigned i;
+    for (i = 0; i < 16; i++) { R(i); }
+    #endif
+  }
+
+  #ifdef _SHA256_UNROLL2
+  state[0] += a;
+  state[1] += b;
+  state[2] += c;
+  state[3] += d;
+  state[4] += e;
+  state[5] += f;
+  state[6] += g;
+  state[7] += h;
+  #else
+  for (j = 0; j < 8; j++)
+    state[j] += T[j];
+  #endif
+
+  /* Wipe variables */
+  /* memset(W, 0, sizeof(W)); */
+  /* memset(T, 0, sizeof(T)); */
+}
+
+#undef S0
+#undef S1
+#undef s0
+#undef s1
+
+static void
+sha256_write_byte_block(sha256_t *p)
+{
+  uint32_t data32[16];
+  unsigned i;
+  for (i = 0; i < 16; i++)
+    data32[i] =
+      ((uint32_t)(p->buffer[i * 4    ]) << 24) +
+      ((uint32_t)(p->buffer[i * 4 + 1]) << 16) +
+      ((uint32_t)(p->buffer[i * 4 + 2]) <<  8) +
+      ((uint32_t)(p->buffer[i * 4 + 3]));
+  sha256_transform(p->state, data32);
+}
+
+
+void
+sha256_hash(unsigned char *buf, const unsigned char *data, size_t size)
+{
+  sha256_t hash;
+  sha256_init(&hash);
+  sha256_update(&hash, data, size);
+  sha256_final(&hash, buf);
+}
+
+
+void
+sha256_update(sha256_t *p, const unsigned char *data, size_t size)
+{
+  uint32_t curBufferPos = (uint32_t)p->count & 0x3F;
+  while (size > 0)
+  {
+    p->buffer[curBufferPos++] = *data++;
+    p->count++;
+    size--;
+    if (curBufferPos == 64)
+    {
+      curBufferPos = 0;
+      sha256_write_byte_block(p);
+    }
+  }
+}
+
+
+void
+sha256_final(sha256_t *p, unsigned char *digest)
+{
+  uint64_t lenInBits = (p->count << 3);
+  uint32_t curBufferPos = (uint32_t)p->count & 0x3F;
+  unsigned i;
+  p->buffer[curBufferPos++] = 0x80;
+  while (curBufferPos != (64 - 8))
+  {
+    curBufferPos &= 0x3F;
+    if (curBufferPos == 0)
+      sha256_write_byte_block(p);
+    p->buffer[curBufferPos++] = 0;
+  }
+  for (i = 0; i < 8; i++)
+  {
+    p->buffer[curBufferPos++] = (unsigned char)(lenInBits >> 56);
+    lenInBits <<= 8;
+  }
+  sha256_write_byte_block(p);
+
+  for (i = 0; i < 8; i++)
+  {
+    *digest++ = (unsigned char)(p->state[i] >> 24);
+    *digest++ = (unsigned char)(p->state[i] >> 16);
+    *digest++ = (unsigned char)(p->state[i] >> 8);
+    *digest++ = (unsigned char)(p->state[i]);
+  }
+  sha256_init(p);
+}
diff --git a/examples/gguf-hash/deps/sha256/sha256.h b/examples/gguf-hash/deps/sha256/sha256.h
new file mode 100644
index 0000000000000..21657e66b602d
--- /dev/null
+++ b/examples/gguf-hash/deps/sha256/sha256.h
@@ -0,0 +1,24 @@
+/* Sha256.h -- SHA-256 Hash
+2010-06-11 : Igor Pavlov : Public domain */
+
+#ifndef __CRYPTO_SHA256_H
+#define __CRYPTO_SHA256_H
+
+#include 
+#include 
+
+#define SHA256_DIGEST_SIZE 32
+
+typedef struct sha256_t
+{
+  uint32_t state[8];
+  uint64_t count;
+  unsigned char buffer[64];
+} sha256_t;
+
+void sha256_init(sha256_t *p);
+void sha256_update(sha256_t *p, const unsigned char *data, size_t size);
+void sha256_final(sha256_t *p, unsigned char *digest);
+void sha256_hash(unsigned char *buf, const unsigned char *data, size_t size);
+
+#endif
diff --git a/examples/gguf-hash/deps/xxhash/clib.json b/examples/gguf-hash/deps/xxhash/clib.json
new file mode 100644
index 0000000000000..0048c74dc2741
--- /dev/null
+++ b/examples/gguf-hash/deps/xxhash/clib.json
@@ -0,0 +1,12 @@
+{
+  "name": "xxhash",
+  "version": "0.8.2",
+  "repo": "mofosyne/xxhash",
+  "description": "Extremely fast non-cryptographic hash algorithm",
+  "keywords": ["xxhash", "hashing"],
+  "license": "BSD-2-Clause",
+  "src": [
+    "xxhash.c",
+    "xxhash.h"
+  ]
+}
diff --git a/examples/gguf-hash/deps/xxhash/xxhash.c b/examples/gguf-hash/deps/xxhash/xxhash.c
new file mode 100644
index 0000000000000..e60cc37f13c27
--- /dev/null
+++ b/examples/gguf-hash/deps/xxhash/xxhash.c
@@ -0,0 +1,42 @@
+/*
+ * xxHash - Extremely Fast Hash algorithm
+ * Copyright (C) 2012-2023 Yann Collet
+ *
+ * BSD 2-Clause License (https://www.opensource.org/licenses/bsd-license.php)
+ *
+ * Redistribution and use in source and binary forms, with or without
+ * modification, are permitted provided that the following conditions are
+ * met:
+ *
+ *    * Redistributions of source code must retain the above copyright
+ *      notice, this list of conditions and the following disclaimer.
+ *    * Redistributions in binary form must reproduce the above
+ *      copyright notice, this list of conditions and the following disclaimer
+ *      in the documentation and/or other materials provided with the
+ *      distribution.
+ *
+ * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+ * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+ * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+ * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+ * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+ * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+ * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+ * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+ * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+ * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+ *
+ * You can contact the author at:
+ *   - xxHash homepage: https://www.xxhash.com
+ *   - xxHash source repository: https://github.com/Cyan4973/xxHash
+ */
+
+/*
+ * xxhash.c instantiates functions defined in xxhash.h
+ */
+
+#define XXH_STATIC_LINKING_ONLY /* access advanced declarations */
+#define XXH_IMPLEMENTATION      /* access definitions */
+
+#include "xxhash.h"
diff --git a/examples/gguf-hash/deps/xxhash/xxhash.h b/examples/gguf-hash/deps/xxhash/xxhash.h
new file mode 100644
index 0000000000000..c0fafe20d54ad
--- /dev/null
+++ b/examples/gguf-hash/deps/xxhash/xxhash.h
@@ -0,0 +1,7093 @@
+/*
+ * xxHash - Extremely Fast Hash algorithm
+ * Header File
+ * Copyright (C) 2012-2023 Yann Collet
+ *
+ * BSD 2-Clause License (https://www.opensource.org/licenses/bsd-license.php)
+ *
+ * Redistribution and use in source and binary forms, with or without
+ * modification, are permitted provided that the following conditions are
+ * met:
+ *
+ *    * Redistributions of source code must retain the above copyright
+ *      notice, this list of conditions and the following disclaimer.
+ *    * Redistributions in binary form must reproduce the above
+ *      copyright notice, this list of conditions and the following disclaimer
+ *      in the documentation and/or other materials provided with the
+ *      distribution.
+ *
+ * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+ * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+ * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+ * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+ * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+ * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+ * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+ * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+ * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+ * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+ *
+ * You can contact the author at:
+ *   - xxHash homepage: https://www.xxhash.com
+ *   - xxHash source repository: https://github.com/Cyan4973/xxHash
+ */
+
+/*!
+ * @mainpage xxHash
+ *
+ * xxHash is an extremely fast non-cryptographic hash algorithm, working at RAM speed
+ * limits.
+ *
+ * It is proposed in four flavors, in three families:
+ * 1. @ref XXH32_family
+ *   - Classic 32-bit hash function. Simple, compact, and runs on almost all
+ *     32-bit and 64-bit systems.
+ * 2. @ref XXH64_family
+ *   - Classic 64-bit adaptation of XXH32. Just as simple, and runs well on most
+ *     64-bit systems (but _not_ 32-bit systems).
+ * 3. @ref XXH3_family
+ *   - Modern 64-bit and 128-bit hash function family which features improved
+ *     strength and performance across the board, especially on smaller data.
+ *     It benefits greatly from SIMD and 64-bit without requiring it.
+ *
+ * Benchmarks
+ * ---
+ * The reference system uses an Intel i7-9700K CPU, and runs Ubuntu x64 20.04.
+ * The open source benchmark program is compiled with clang v10.0 using -O3 flag.
+ *
+ * | Hash Name            | ISA ext | Width | Large Data Speed | Small Data Velocity |
+ * | -------------------- | ------- | ----: | ---------------: | ------------------: |
+ * | XXH3_64bits()        | @b AVX2 |    64 |        59.4 GB/s |               133.1 |
+ * | MeowHash             | AES-NI  |   128 |        58.2 GB/s |                52.5 |
+ * | XXH3_128bits()       | @b AVX2 |   128 |        57.9 GB/s |               118.1 |
+ * | CLHash               | PCLMUL  |    64 |        37.1 GB/s |                58.1 |
+ * | XXH3_64bits()        | @b SSE2 |    64 |        31.5 GB/s |               133.1 |
+ * | XXH3_128bits()       | @b SSE2 |   128 |        29.6 GB/s |               118.1 |
+ * | RAM sequential read  |         |   N/A |        28.0 GB/s |                 N/A |
+ * | ahash                | AES-NI  |    64 |        22.5 GB/s |               107.2 |
+ * | City64               |         |    64 |        22.0 GB/s |                76.6 |
+ * | T1ha2                |         |    64 |        22.0 GB/s |                99.0 |
+ * | City128              |         |   128 |        21.7 GB/s |                57.7 |
+ * | FarmHash             | AES-NI  |    64 |        21.3 GB/s |                71.9 |
+ * | XXH64()              |         |    64 |        19.4 GB/s |                71.0 |
+ * | SpookyHash           |         |    64 |        19.3 GB/s |                53.2 |
+ * | Mum                  |         |    64 |        18.0 GB/s |                67.0 |
+ * | CRC32C               | SSE4.2  |    32 |        13.0 GB/s |                57.9 |
+ * | XXH32()              |         |    32 |         9.7 GB/s |                71.9 |
+ * | City32               |         |    32 |         9.1 GB/s |                66.0 |
+ * | Blake3*              | @b AVX2 |   256 |         4.4 GB/s |                 8.1 |
+ * | Murmur3              |         |    32 |         3.9 GB/s |                56.1 |
+ * | SipHash*             |         |    64 |         3.0 GB/s |                43.2 |
+ * | Blake3*              | @b SSE2 |   256 |         2.4 GB/s |                 8.1 |
+ * | HighwayHash          |         |    64 |         1.4 GB/s |                 6.0 |
+ * | FNV64                |         |    64 |         1.2 GB/s |                62.7 |
+ * | Blake2*              |         |   256 |         1.1 GB/s |                 5.1 |
+ * | SHA1*                |         |   160 |         0.8 GB/s |                 5.6 |
+ * | MD5*                 |         |   128 |         0.6 GB/s |                 7.8 |
+ * @note
+ *   - Hashes which require a specific ISA extension are noted. SSE2 is also noted,
+ *     even though it is mandatory on x64.
+ *   - Hashes with an asterisk are cryptographic. Note that MD5 is non-cryptographic
+ *     by modern standards.
+ *   - Small data velocity is a rough average of algorithm's efficiency for small
+ *     data. For more accurate information, see the wiki.
+ *   - More benchmarks and strength tests are found on the wiki:
+ *         https://github.com/Cyan4973/xxHash/wiki
+ *
+ * Usage
+ * ------
+ * All xxHash variants use a similar API. Changing the algorithm is a trivial
+ * substitution.
+ *
+ * @pre
+ *    For functions which take an input and length parameter, the following
+ *    requirements are assumed:
+ *    - The range from [`input`, `input + length`) is valid, readable memory.
+ *      - The only exception is if the `length` is `0`, `input` may be `NULL`.
+ *    - For C++, the objects must have the *TriviallyCopyable* property, as the
+ *      functions access bytes directly as if it was an array of `unsigned char`.
+ *
+ * @anchor single_shot_example
+ * **Single Shot**
+ *
+ * These functions are stateless functions which hash a contiguous block of memory,
+ * immediately returning the result. They are the easiest and usually the fastest
+ * option.
+ *
+ * XXH32(), XXH64(), XXH3_64bits(), XXH3_128bits()
+ *
+ * @code{.c}
+ *   #include 
+ *   #include "xxhash.h"
+ *
+ *   // Example for a function which hashes a null terminated string with XXH32().
+ *   XXH32_hash_t hash_string(const char* string, XXH32_hash_t seed)
+ *   {
+ *       // NULL pointers are only valid if the length is zero
+ *       size_t length = (string == NULL) ? 0 : strlen(string);
+ *       return XXH32(string, length, seed);
+ *   }
+ * @endcode
+ *
+ *
+ * @anchor streaming_example
+ * **Streaming**
+ *
+ * These groups of functions allow incremental hashing of unknown size, even
+ * more than what would fit in a size_t.
+ *
+ * XXH32_reset(), XXH64_reset(), XXH3_64bits_reset(), XXH3_128bits_reset()
+ *
+ * @code{.c}
+ *   #include 
+ *   #include 
+ *   #include "xxhash.h"
+ *   // Example for a function which hashes a FILE incrementally with XXH3_64bits().
+ *   XXH64_hash_t hashFile(FILE* f)
+ *   {
+ *       // Allocate a state struct. Do not just use malloc() or new.
+ *       XXH3_state_t* state = XXH3_createState();
+ *       assert(state != NULL && "Out of memory!");
+ *       // Reset the state to start a new hashing session.
+ *       XXH3_64bits_reset(state);
+ *       char buffer[4096];
+ *       size_t count;
+ *       // Read the file in chunks
+ *       while ((count = fread(buffer, 1, sizeof(buffer), f)) != 0) {
+ *           // Run update() as many times as necessary to process the data
+ *           XXH3_64bits_update(state, buffer, count);
+ *       }
+ *       // Retrieve the finalized hash. This will not change the state.
+ *       XXH64_hash_t result = XXH3_64bits_digest(state);
+ *       // Free the state. Do not use free().
+ *       XXH3_freeState(state);
+ *       return result;
+ *   }
+ * @endcode
+ *
+ * Streaming functions generate the xxHash value from an incremental input.
+ * This method is slower than single-call functions, due to state management.
+ * For small inputs, prefer `XXH32()` and `XXH64()`, which are better optimized.
+ *
+ * An XXH state must first be allocated using `XXH*_createState()`.
+ *
+ * Start a new hash by initializing the state with a seed using `XXH*_reset()`.
+ *
+ * Then, feed the hash state by calling `XXH*_update()` as many times as necessary.
+ *
+ * The function returns an error code, with 0 meaning OK, and any other value
+ * meaning there is an error.
+ *
+ * Finally, a hash value can be produced anytime, by using `XXH*_digest()`.
+ * This function returns the nn-bits hash as an int or long long.
+ *
+ * It's still possible to continue inserting input into the hash state after a
+ * digest, and generate new hash values later on by invoking `XXH*_digest()`.
+ *
+ * When done, release the state using `XXH*_freeState()`.
+ *
+ *
+ * @anchor canonical_representation_example
+ * **Canonical Representation**
+ *
+ * The default return values from XXH functions are unsigned 32, 64 and 128 bit
+ * integers.
+ * This the simplest and fastest format for further post-processing.
+ *
+ * However, this leaves open the question of what is the order on the byte level,
+ * since little and big endian conventions will store the same number differently.
+ *
+ * The canonical representation settles this issue by mandating big-endian
+ * convention, the same convention as human-readable numbers (large digits first).
+ *
+ * When writing hash values to storage, sending them over a network, or printing
+ * them, it's highly recommended to use the canonical representation to ensure
+ * portability across a wider range of systems, present and future.
+ *
+ * The following functions allow transformation of hash values to and from
+ * canonical format.
+ *
+ * XXH32_canonicalFromHash(), XXH32_hashFromCanonical(),
+ * XXH64_canonicalFromHash(), XXH64_hashFromCanonical(),
+ * XXH128_canonicalFromHash(), XXH128_hashFromCanonical(),
+ *
+ * @code{.c}
+ *   #include 
+ *   #include "xxhash.h"
+ *
+ *   // Example for a function which prints XXH32_hash_t in human readable format
+ *   void printXxh32(XXH32_hash_t hash)
+ *   {
+ *       XXH32_canonical_t cano;
+ *       XXH32_canonicalFromHash(&cano, hash);
+ *       size_t i;
+ *       for(i = 0; i < sizeof(cano.digest); ++i) {
+ *           printf("%02x", cano.digest[i]);
+ *       }
+ *       printf("\n");
+ *   }
+ *
+ *   // Example for a function which converts XXH32_canonical_t to XXH32_hash_t
+ *   XXH32_hash_t convertCanonicalToXxh32(XXH32_canonical_t cano)
+ *   {
+ *       XXH32_hash_t hash = XXH32_hashFromCanonical(&cano);
+ *       return hash;
+ *   }
+ * @endcode
+ *
+ *
+ * @file xxhash.h
+ * xxHash prototypes and implementation
+ */
+
+#if defined (__cplusplus)
+extern "C" {
+#endif
+
+/* ****************************
+ *  INLINE mode
+ ******************************/
+/*!
+ * @defgroup public Public API
+ * Contains details on the public xxHash functions.
+ * @{
+ */
+#ifdef XXH_DOXYGEN
+/*!
+ * @brief Gives access to internal state declaration, required for static allocation.
+ *
+ * Incompatible with dynamic linking, due to risks of ABI changes.
+ *
+ * Usage:
+ * @code{.c}
+ *     #define XXH_STATIC_LINKING_ONLY
+ *     #include "xxhash.h"
+ * @endcode
+ */
+#  define XXH_STATIC_LINKING_ONLY
+/* Do not undef XXH_STATIC_LINKING_ONLY for Doxygen */
+
+/*!
+ * @brief Gives access to internal definitions.
+ *
+ * Usage:
+ * @code{.c}
+ *     #define XXH_STATIC_LINKING_ONLY
+ *     #define XXH_IMPLEMENTATION
+ *     #include "xxhash.h"
+ * @endcode
+ */
+#  define XXH_IMPLEMENTATION
+/* Do not undef XXH_IMPLEMENTATION for Doxygen */
+
+/*!
+ * @brief Exposes the implementation and marks all functions as `inline`.
+ *
+ * Use these build macros to inline xxhash into the target unit.
+ * Inlining improves performance on small inputs, especially when the length is
+ * expressed as a compile-time constant:
+ *
+ *  https://fastcompression.blogspot.com/2018/03/xxhash-for-small-keys-impressive-power.html
+ *
+ * It also keeps xxHash symbols private to the unit, so they are not exported.
+ *
+ * Usage:
+ * @code{.c}
+ *     #define XXH_INLINE_ALL
+ *     #include "xxhash.h"
+ * @endcode
+ * Do not compile and link xxhash.o as a separate object, as it is not useful.
+ */
+#  define XXH_INLINE_ALL
+#  undef XXH_INLINE_ALL
+/*!
+ * @brief Exposes the implementation without marking functions as inline.
+ */
+#  define XXH_PRIVATE_API
+#  undef XXH_PRIVATE_API
+/*!
+ * @brief Emulate a namespace by transparently prefixing all symbols.
+ *
+ * If you want to include _and expose_ xxHash functions from within your own
+ * library, but also want to avoid symbol collisions with other libraries which
+ * may also include xxHash, you can use @ref XXH_NAMESPACE to automatically prefix
+ * any public symbol from xxhash library with the value of @ref XXH_NAMESPACE
+ * (therefore, avoid empty or numeric values).
+ *
+ * Note that no change is required within the calling program as long as it
+ * includes `xxhash.h`: Regular symbol names will be automatically translated
+ * by this header.
+ */
+#  define XXH_NAMESPACE /* YOUR NAME HERE */
+#  undef XXH_NAMESPACE
+#endif
+
+#if (defined(XXH_INLINE_ALL) || defined(XXH_PRIVATE_API)) \
+    && !defined(XXH_INLINE_ALL_31684351384)
+   /* this section should be traversed only once */
+#  define XXH_INLINE_ALL_31684351384
+   /* give access to the advanced API, required to compile implementations */
+#  undef XXH_STATIC_LINKING_ONLY   /* avoid macro redef */
+#  define XXH_STATIC_LINKING_ONLY
+   /* make all functions private */
+#  undef XXH_PUBLIC_API
+#  if defined(__GNUC__)
+#    define XXH_PUBLIC_API static __inline __attribute__((__unused__))
+#  elif defined (__cplusplus) || (defined (__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L) /* C99 */)
+#    define XXH_PUBLIC_API static inline
+#  elif defined(_MSC_VER)
+#    define XXH_PUBLIC_API static __inline
+#  else
+     /* note: this version may generate warnings for unused static functions */
+#    define XXH_PUBLIC_API static
+#  endif
+
+   /*
+    * This part deals with the special case where a unit wants to inline xxHash,
+    * but "xxhash.h" has previously been included without XXH_INLINE_ALL,
+    * such as part of some previously included *.h header file.
+    * Without further action, the new include would just be ignored,
+    * and functions would effectively _not_ be inlined (silent failure).
+    * The following macros solve this situation by prefixing all inlined names,
+    * avoiding naming collision with previous inclusions.
+    */
+   /* Before that, we unconditionally #undef all symbols,
+    * in case they were already defined with XXH_NAMESPACE.
+    * They will then be redefined for XXH_INLINE_ALL
+    */
+#  undef XXH_versionNumber
+    /* XXH32 */
+#  undef XXH32
+#  undef XXH32_createState
+#  undef XXH32_freeState
+#  undef XXH32_reset
+#  undef XXH32_update
+#  undef XXH32_digest
+#  undef XXH32_copyState
+#  undef XXH32_canonicalFromHash
+#  undef XXH32_hashFromCanonical
+    /* XXH64 */
+#  undef XXH64
+#  undef XXH64_createState
+#  undef XXH64_freeState
+#  undef XXH64_reset
+#  undef XXH64_update
+#  undef XXH64_digest
+#  undef XXH64_copyState
+#  undef XXH64_canonicalFromHash
+#  undef XXH64_hashFromCanonical
+    /* XXH3_64bits */
+#  undef XXH3_64bits
+#  undef XXH3_64bits_withSecret
+#  undef XXH3_64bits_withSeed
+#  undef XXH3_64bits_withSecretandSeed
+#  undef XXH3_createState
+#  undef XXH3_freeState
+#  undef XXH3_copyState
+#  undef XXH3_64bits_reset
+#  undef XXH3_64bits_reset_withSeed
+#  undef XXH3_64bits_reset_withSecret
+#  undef XXH3_64bits_update
+#  undef XXH3_64bits_digest
+#  undef XXH3_generateSecret
+    /* XXH3_128bits */
+#  undef XXH128
+#  undef XXH3_128bits
+#  undef XXH3_128bits_withSeed
+#  undef XXH3_128bits_withSecret
+#  undef XXH3_128bits_reset
+#  undef XXH3_128bits_reset_withSeed
+#  undef XXH3_128bits_reset_withSecret
+#  undef XXH3_128bits_reset_withSecretandSeed
+#  undef XXH3_128bits_update
+#  undef XXH3_128bits_digest
+#  undef XXH128_isEqual
+#  undef XXH128_cmp
+#  undef XXH128_canonicalFromHash
+#  undef XXH128_hashFromCanonical
+    /* Finally, free the namespace itself */
+#  undef XXH_NAMESPACE
+
+    /* employ the namespace for XXH_INLINE_ALL */
+#  define XXH_NAMESPACE XXH_INLINE_
+   /*
+    * Some identifiers (enums, type names) are not symbols,
+    * but they must nonetheless be renamed to avoid redeclaration.
+    * Alternative solution: do not redeclare them.
+    * However, this requires some #ifdefs, and has a more dispersed impact.
+    * Meanwhile, renaming can be achieved in a single place.
+    */
+#  define XXH_IPREF(Id)   XXH_NAMESPACE ## Id
+#  define XXH_OK XXH_IPREF(XXH_OK)
+#  define XXH_ERROR XXH_IPREF(XXH_ERROR)
+#  define XXH_errorcode XXH_IPREF(XXH_errorcode)
+#  define XXH32_canonical_t  XXH_IPREF(XXH32_canonical_t)
+#  define XXH64_canonical_t  XXH_IPREF(XXH64_canonical_t)
+#  define XXH128_canonical_t XXH_IPREF(XXH128_canonical_t)
+#  define XXH32_state_s XXH_IPREF(XXH32_state_s)
+#  define XXH32_state_t XXH_IPREF(XXH32_state_t)
+#  define XXH64_state_s XXH_IPREF(XXH64_state_s)
+#  define XXH64_state_t XXH_IPREF(XXH64_state_t)
+#  define XXH3_state_s  XXH_IPREF(XXH3_state_s)
+#  define XXH3_state_t  XXH_IPREF(XXH3_state_t)
+#  define XXH128_hash_t XXH_IPREF(XXH128_hash_t)
+   /* Ensure the header is parsed again, even if it was previously included */
+#  undef XXHASH_H_5627135585666179
+#  undef XXHASH_H_STATIC_13879238742
+#endif /* XXH_INLINE_ALL || XXH_PRIVATE_API */
+
+/* ****************************************************************
+ *  Stable API
+ *****************************************************************/
+#ifndef XXHASH_H_5627135585666179
+#define XXHASH_H_5627135585666179 1
+
+/*! @brief Marks a global symbol. */
+#if !defined(XXH_INLINE_ALL) && !defined(XXH_PRIVATE_API)
+#  if defined(_WIN32) && defined(_MSC_VER) && (defined(XXH_IMPORT) || defined(XXH_EXPORT))
+#    ifdef XXH_EXPORT
+#      define XXH_PUBLIC_API __declspec(dllexport)
+#    elif XXH_IMPORT
+#      define XXH_PUBLIC_API __declspec(dllimport)
+#    endif
+#  else
+#    define XXH_PUBLIC_API   /* do nothing */
+#  endif
+#endif
+
+#ifdef XXH_NAMESPACE
+#  define XXH_CAT(A,B) A##B
+#  define XXH_NAME2(A,B) XXH_CAT(A,B)
+#  define XXH_versionNumber XXH_NAME2(XXH_NAMESPACE, XXH_versionNumber)
+/* XXH32 */
+#  define XXH32 XXH_NAME2(XXH_NAMESPACE, XXH32)
+#  define XXH32_createState XXH_NAME2(XXH_NAMESPACE, XXH32_createState)
+#  define XXH32_freeState XXH_NAME2(XXH_NAMESPACE, XXH32_freeState)
+#  define XXH32_reset XXH_NAME2(XXH_NAMESPACE, XXH32_reset)
+#  define XXH32_update XXH_NAME2(XXH_NAMESPACE, XXH32_update)
+#  define XXH32_digest XXH_NAME2(XXH_NAMESPACE, XXH32_digest)
+#  define XXH32_copyState XXH_NAME2(XXH_NAMESPACE, XXH32_copyState)
+#  define XXH32_canonicalFromHash XXH_NAME2(XXH_NAMESPACE, XXH32_canonicalFromHash)
+#  define XXH32_hashFromCanonical XXH_NAME2(XXH_NAMESPACE, XXH32_hashFromCanonical)
+/* XXH64 */
+#  define XXH64 XXH_NAME2(XXH_NAMESPACE, XXH64)
+#  define XXH64_createState XXH_NAME2(XXH_NAMESPACE, XXH64_createState)
+#  define XXH64_freeState XXH_NAME2(XXH_NAMESPACE, XXH64_freeState)
+#  define XXH64_reset XXH_NAME2(XXH_NAMESPACE, XXH64_reset)
+#  define XXH64_update XXH_NAME2(XXH_NAMESPACE, XXH64_update)
+#  define XXH64_digest XXH_NAME2(XXH_NAMESPACE, XXH64_digest)
+#  define XXH64_copyState XXH_NAME2(XXH_NAMESPACE, XXH64_copyState)
+#  define XXH64_canonicalFromHash XXH_NAME2(XXH_NAMESPACE, XXH64_canonicalFromHash)
+#  define XXH64_hashFromCanonical XXH_NAME2(XXH_NAMESPACE, XXH64_hashFromCanonical)
+/* XXH3_64bits */
+#  define XXH3_64bits XXH_NAME2(XXH_NAMESPACE, XXH3_64bits)
+#  define XXH3_64bits_withSecret XXH_NAME2(XXH_NAMESPACE, XXH3_64bits_withSecret)
+#  define XXH3_64bits_withSeed XXH_NAME2(XXH_NAMESPACE, XXH3_64bits_withSeed)
+#  define XXH3_64bits_withSecretandSeed XXH_NAME2(XXH_NAMESPACE, XXH3_64bits_withSecretandSeed)
+#  define XXH3_createState XXH_NAME2(XXH_NAMESPACE, XXH3_createState)
+#  define XXH3_freeState XXH_NAME2(XXH_NAMESPACE, XXH3_freeState)
+#  define XXH3_copyState XXH_NAME2(XXH_NAMESPACE, XXH3_copyState)
+#  define XXH3_64bits_reset XXH_NAME2(XXH_NAMESPACE, XXH3_64bits_reset)
+#  define XXH3_64bits_reset_withSeed XXH_NAME2(XXH_NAMESPACE, XXH3_64bits_reset_withSeed)
+#  define XXH3_64bits_reset_withSecret XXH_NAME2(XXH_NAMESPACE, XXH3_64bits_reset_withSecret)
+#  define XXH3_64bits_reset_withSecretandSeed XXH_NAME2(XXH_NAMESPACE, XXH3_64bits_reset_withSecretandSeed)
+#  define XXH3_64bits_update XXH_NAME2(XXH_NAMESPACE, XXH3_64bits_update)
+#  define XXH3_64bits_digest XXH_NAME2(XXH_NAMESPACE, XXH3_64bits_digest)
+#  define XXH3_generateSecret XXH_NAME2(XXH_NAMESPACE, XXH3_generateSecret)
+#  define XXH3_generateSecret_fromSeed XXH_NAME2(XXH_NAMESPACE, XXH3_generateSecret_fromSeed)
+/* XXH3_128bits */
+#  define XXH128 XXH_NAME2(XXH_NAMESPACE, XXH128)
+#  define XXH3_128bits XXH_NAME2(XXH_NAMESPACE, XXH3_128bits)
+#  define XXH3_128bits_withSeed XXH_NAME2(XXH_NAMESPACE, XXH3_128bits_withSeed)
+#  define XXH3_128bits_withSecret XXH_NAME2(XXH_NAMESPACE, XXH3_128bits_withSecret)
+#  define XXH3_128bits_withSecretandSeed XXH_NAME2(XXH_NAMESPACE, XXH3_128bits_withSecretandSeed)
+#  define XXH3_128bits_reset XXH_NAME2(XXH_NAMESPACE, XXH3_128bits_reset)
+#  define XXH3_128bits_reset_withSeed XXH_NAME2(XXH_NAMESPACE, XXH3_128bits_reset_withSeed)
+#  define XXH3_128bits_reset_withSecret XXH_NAME2(XXH_NAMESPACE, XXH3_128bits_reset_withSecret)
+#  define XXH3_128bits_reset_withSecretandSeed XXH_NAME2(XXH_NAMESPACE, XXH3_128bits_reset_withSecretandSeed)
+#  define XXH3_128bits_update XXH_NAME2(XXH_NAMESPACE, XXH3_128bits_update)
+#  define XXH3_128bits_digest XXH_NAME2(XXH_NAMESPACE, XXH3_128bits_digest)
+#  define XXH128_isEqual XXH_NAME2(XXH_NAMESPACE, XXH128_isEqual)
+#  define XXH128_cmp     XXH_NAME2(XXH_NAMESPACE, XXH128_cmp)
+#  define XXH128_canonicalFromHash XXH_NAME2(XXH_NAMESPACE, XXH128_canonicalFromHash)
+#  define XXH128_hashFromCanonical XXH_NAME2(XXH_NAMESPACE, XXH128_hashFromCanonical)
+#endif
+
+
+/* *************************************
+*  Compiler specifics
+***************************************/
+
+/* specific declaration modes for Windows */
+#if !defined(XXH_INLINE_ALL) && !defined(XXH_PRIVATE_API)
+#  if defined(_WIN32) && defined(_MSC_VER) && (defined(XXH_IMPORT) || defined(XXH_EXPORT))
+#    ifdef XXH_EXPORT
+#      define XXH_PUBLIC_API __declspec(dllexport)
+#    elif XXH_IMPORT
+#      define XXH_PUBLIC_API __declspec(dllimport)
+#    endif
+#  else
+#    define XXH_PUBLIC_API   /* do nothing */
+#  endif
+#endif
+
+#if defined (__GNUC__)
+# define XXH_CONSTF  __attribute__((__const__))
+# define XXH_PUREF   __attribute__((__pure__))
+# define XXH_MALLOCF __attribute__((__malloc__))
+#else
+# define XXH_CONSTF  /* disable */
+# define XXH_PUREF
+# define XXH_MALLOCF
+#endif
+
+/* *************************************
+*  Version
+***************************************/
+#define XXH_VERSION_MAJOR    0
+#define XXH_VERSION_MINOR    8
+#define XXH_VERSION_RELEASE  3
+/*! @brief Version number, encoded as two digits each */
+#define XXH_VERSION_NUMBER  (XXH_VERSION_MAJOR *100*100 + XXH_VERSION_MINOR *100 + XXH_VERSION_RELEASE)
+
+/*!
+ * @brief Obtains the xxHash version.
+ *
+ * This is mostly useful when xxHash is compiled as a shared library,
+ * since the returned value comes from the library, as opposed to header file.
+ *
+ * @return @ref XXH_VERSION_NUMBER of the invoked library.
+ */
+XXH_PUBLIC_API XXH_CONSTF unsigned XXH_versionNumber (void);
+
+
+/* ****************************
+*  Common basic types
+******************************/
+#include    /* size_t */
+/*!
+ * @brief Exit code for the streaming API.
+ */
+typedef enum {
+    XXH_OK = 0, /*!< OK */
+    XXH_ERROR   /*!< Error */
+} XXH_errorcode;
+
+
+/*-**********************************************************************
+*  32-bit hash
+************************************************************************/
+#if defined(XXH_DOXYGEN) /* Don't show  include */
+/*!
+ * @brief An unsigned 32-bit integer.
+ *
+ * Not necessarily defined to `uint32_t` but functionally equivalent.
+ */
+typedef uint32_t XXH32_hash_t;
+
+#elif !defined (__VMS) \
+  && (defined (__cplusplus) \
+  || (defined (__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L) /* C99 */) )
+#   ifdef _AIX
+#     include 
+#   else
+#     include 
+#   endif
+    typedef uint32_t XXH32_hash_t;
+
+#else
+#   include 
+#   if UINT_MAX == 0xFFFFFFFFUL
+      typedef unsigned int XXH32_hash_t;
+#   elif ULONG_MAX == 0xFFFFFFFFUL
+      typedef unsigned long XXH32_hash_t;
+#   else
+#     error "unsupported platform: need a 32-bit type"
+#   endif
+#endif
+
+/*!
+ * @}
+ *
+ * @defgroup XXH32_family XXH32 family
+ * @ingroup public
+ * Contains functions used in the classic 32-bit xxHash algorithm.
+ *
+ * @note
+ *   XXH32 is useful for older platforms, with no or poor 64-bit performance.
+ *   Note that the @ref XXH3_family provides competitive speed for both 32-bit
+ *   and 64-bit systems, and offers true 64/128 bit hash results.
+ *
+ * @see @ref XXH64_family, @ref XXH3_family : Other xxHash families
+ * @see @ref XXH32_impl for implementation details
+ * @{
+ */
+
+/*!
+ * @brief Calculates the 32-bit hash of @p input using xxHash32.
+ *
+ * @param input The block of data to be hashed, at least @p length bytes in size.
+ * @param length The length of @p input, in bytes.
+ * @param seed The 32-bit seed to alter the hash's output predictably.
+ *
+ * @pre
+ *   The memory between @p input and @p input + @p length must be valid,
+ *   readable, contiguous memory. However, if @p length is `0`, @p input may be
+ *   `NULL`. In C++, this also must be *TriviallyCopyable*.
+ *
+ * @return The calculated 32-bit xxHash32 value.
+ *
+ * @see @ref single_shot_example "Single Shot Example" for an example.
+ */
+XXH_PUBLIC_API XXH_PUREF XXH32_hash_t XXH32 (const void* input, size_t length, XXH32_hash_t seed);
+
+#ifndef XXH_NO_STREAM
+/*!
+ * @typedef struct XXH32_state_s XXH32_state_t
+ * @brief The opaque state struct for the XXH32 streaming API.
+ *
+ * @see XXH32_state_s for details.
+ * @see @ref streaming_example "Streaming Example"
+ */
+typedef struct XXH32_state_s XXH32_state_t;
+
+/*!
+ * @brief Allocates an @ref XXH32_state_t.
+ *
+ * @return An allocated pointer of @ref XXH32_state_t on success.
+ * @return `NULL` on failure.
+ *
+ * @note Must be freed with XXH32_freeState().
+ *
+ * @see @ref streaming_example "Streaming Example"
+ */
+XXH_PUBLIC_API XXH_MALLOCF XXH32_state_t* XXH32_createState(void);
+/*!
+ * @brief Frees an @ref XXH32_state_t.
+ *
+ * @param statePtr A pointer to an @ref XXH32_state_t allocated with @ref XXH32_createState().
+ *
+ * @return @ref XXH_OK.
+ *
+ * @note @p statePtr must be allocated with XXH32_createState().
+ *
+ * @see @ref streaming_example "Streaming Example"
+ *
+ */
+XXH_PUBLIC_API XXH_errorcode  XXH32_freeState(XXH32_state_t* statePtr);
+/*!
+ * @brief Copies one @ref XXH32_state_t to another.
+ *
+ * @param dst_state The state to copy to.
+ * @param src_state The state to copy from.
+ * @pre
+ *   @p dst_state and @p src_state must not be `NULL` and must not overlap.
+ */
+XXH_PUBLIC_API void XXH32_copyState(XXH32_state_t* dst_state, const XXH32_state_t* src_state);
+
+/*!
+ * @brief Resets an @ref XXH32_state_t to begin a new hash.
+ *
+ * @param statePtr The state struct to reset.
+ * @param seed The 32-bit seed to alter the hash result predictably.
+ *
+ * @pre
+ *   @p statePtr must not be `NULL`.
+ *
+ * @return @ref XXH_OK on success.
+ * @return @ref XXH_ERROR on failure.
+ *
+ * @note This function resets and seeds a state. Call it before @ref XXH32_update().
+ *
+ * @see @ref streaming_example "Streaming Example"
+ */
+XXH_PUBLIC_API XXH_errorcode XXH32_reset  (XXH32_state_t* statePtr, XXH32_hash_t seed);
+
+/*!
+ * @brief Consumes a block of @p input to an @ref XXH32_state_t.
+ *
+ * @param statePtr The state struct to update.
+ * @param input The block of data to be hashed, at least @p length bytes in size.
+ * @param length The length of @p input, in bytes.
+ *
+ * @pre
+ *   @p statePtr must not be `NULL`.
+ * @pre
+ *   The memory between @p input and @p input + @p length must be valid,
+ *   readable, contiguous memory. However, if @p length is `0`, @p input may be
+ *   `NULL`. In C++, this also must be *TriviallyCopyable*.
+ *
+ * @return @ref XXH_OK on success.
+ * @return @ref XXH_ERROR on failure.
+ *
+ * @note Call this to incrementally consume blocks of data.
+ *
+ * @see @ref streaming_example "Streaming Example"
+ */
+XXH_PUBLIC_API XXH_errorcode XXH32_update (XXH32_state_t* statePtr, const void* input, size_t length);
+
+/*!
+ * @brief Returns the calculated hash value from an @ref XXH32_state_t.
+ *
+ * @param statePtr The state struct to calculate the hash from.
+ *
+ * @pre
+ *  @p statePtr must not be `NULL`.
+ *
+ * @return The calculated 32-bit xxHash32 value from that state.
+ *
+ * @note
+ *   Calling XXH32_digest() will not affect @p statePtr, so you can update,
+ *   digest, and update again.
+ *
+ * @see @ref streaming_example "Streaming Example"
+ */
+XXH_PUBLIC_API XXH_PUREF XXH32_hash_t XXH32_digest (const XXH32_state_t* statePtr);
+#endif /* !XXH_NO_STREAM */
+
+/*******   Canonical representation   *******/
+
+/*!
+ * @brief Canonical (big endian) representation of @ref XXH32_hash_t.
+ */
+typedef struct {
+    unsigned char digest[4]; /*!< Hash bytes, big endian */
+} XXH32_canonical_t;
+
+/*!
+ * @brief Converts an @ref XXH32_hash_t to a big endian @ref XXH32_canonical_t.
+ *
+ * @param dst  The @ref XXH32_canonical_t pointer to be stored to.
+ * @param hash The @ref XXH32_hash_t to be converted.
+ *
+ * @pre
+ *   @p dst must not be `NULL`.
+ *
+ * @see @ref canonical_representation_example "Canonical Representation Example"
+ */
+XXH_PUBLIC_API void XXH32_canonicalFromHash(XXH32_canonical_t* dst, XXH32_hash_t hash);
+
+/*!
+ * @brief Converts an @ref XXH32_canonical_t to a native @ref XXH32_hash_t.
+ *
+ * @param src The @ref XXH32_canonical_t to convert.
+ *
+ * @pre
+ *   @p src must not be `NULL`.
+ *
+ * @return The converted hash.
+ *
+ * @see @ref canonical_representation_example "Canonical Representation Example"
+ */
+XXH_PUBLIC_API XXH_PUREF XXH32_hash_t XXH32_hashFromCanonical(const XXH32_canonical_t* src);
+
+
+/*! @cond Doxygen ignores this part */
+#ifdef __has_attribute
+# define XXH_HAS_ATTRIBUTE(x) __has_attribute(x)
+#else
+# define XXH_HAS_ATTRIBUTE(x) 0
+#endif
+/*! @endcond */
+
+/*! @cond Doxygen ignores this part */
+/*
+ * C23 __STDC_VERSION__ number hasn't been specified yet. For now
+ * leave as `201711L` (C17 + 1).
+ * TODO: Update to correct value when its been specified.
+ */
+#define XXH_C23_VN 201711L
+/*! @endcond */
+
+/*! @cond Doxygen ignores this part */
+/* C-language Attributes are added in C23. */
+#if defined(__STDC_VERSION__) && (__STDC_VERSION__ >= XXH_C23_VN) && defined(__has_c_attribute)
+# define XXH_HAS_C_ATTRIBUTE(x) __has_c_attribute(x)
+#else
+# define XXH_HAS_C_ATTRIBUTE(x) 0
+#endif
+/*! @endcond */
+
+/*! @cond Doxygen ignores this part */
+#if defined(__cplusplus) && defined(__has_cpp_attribute)
+# define XXH_HAS_CPP_ATTRIBUTE(x) __has_cpp_attribute(x)
+#else
+# define XXH_HAS_CPP_ATTRIBUTE(x) 0
+#endif
+/*! @endcond */
+
+/*! @cond Doxygen ignores this part */
+/*
+ * Define XXH_FALLTHROUGH macro for annotating switch case with the 'fallthrough' attribute
+ * introduced in CPP17 and C23.
+ * CPP17 : https://en.cppreference.com/w/cpp/language/attributes/fallthrough
+ * C23   : https://en.cppreference.com/w/c/language/attributes/fallthrough
+ */
+#if XXH_HAS_C_ATTRIBUTE(fallthrough) || XXH_HAS_CPP_ATTRIBUTE(fallthrough)
+# define XXH_FALLTHROUGH [[fallthrough]]
+#elif XXH_HAS_ATTRIBUTE(__fallthrough__)
+# define XXH_FALLTHROUGH __attribute__ ((__fallthrough__))
+#else
+# define XXH_FALLTHROUGH /* fallthrough */
+#endif
+/*! @endcond */
+
+/*! @cond Doxygen ignores this part */
+/*
+ * Define XXH_NOESCAPE for annotated pointers in public API.
+ * https://clang.llvm.org/docs/AttributeReference.html#noescape
+ * As of writing this, only supported by clang.
+ */
+#if XXH_HAS_ATTRIBUTE(noescape)
+# define XXH_NOESCAPE __attribute__((__noescape__))
+#else
+# define XXH_NOESCAPE
+#endif
+/*! @endcond */
+
+
+/*!
+ * @}
+ * @ingroup public
+ * @{
+ */
+
+#ifndef XXH_NO_LONG_LONG
+/*-**********************************************************************
+*  64-bit hash
+************************************************************************/
+#if defined(XXH_DOXYGEN) /* don't include  */
+/*!
+ * @brief An unsigned 64-bit integer.
+ *
+ * Not necessarily defined to `uint64_t` but functionally equivalent.
+ */
+typedef uint64_t XXH64_hash_t;
+#elif !defined (__VMS) \
+  && (defined (__cplusplus) \
+  || (defined (__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L) /* C99 */) )
+#   ifdef _AIX
+#     include 
+#   else
+#     include 
+#   endif
+   typedef uint64_t XXH64_hash_t;
+#else
+#  include 
+#  if defined(__LP64__) && ULONG_MAX == 0xFFFFFFFFFFFFFFFFULL
+     /* LP64 ABI says uint64_t is unsigned long */
+     typedef unsigned long XXH64_hash_t;
+#  else
+     /* the following type must have a width of 64-bit */
+     typedef unsigned long long XXH64_hash_t;
+#  endif
+#endif
+
+/*!
+ * @}
+ *
+ * @defgroup XXH64_family XXH64 family
+ * @ingroup public
+ * @{
+ * Contains functions used in the classic 64-bit xxHash algorithm.
+ *
+ * @note
+ *   XXH3 provides competitive speed for both 32-bit and 64-bit systems,
+ *   and offers true 64/128 bit hash results.
+ *   It provides better speed for systems with vector processing capabilities.
+ */
+
+/*!
+ * @brief Calculates the 64-bit hash of @p input using xxHash64.
+ *
+ * @param input The block of data to be hashed, at least @p length bytes in size.
+ * @param length The length of @p input, in bytes.
+ * @param seed The 64-bit seed to alter the hash's output predictably.
+ *
+ * @pre
+ *   The memory between @p input and @p input + @p length must be valid,
+ *   readable, contiguous memory. However, if @p length is `0`, @p input may be
+ *   `NULL`. In C++, this also must be *TriviallyCopyable*.
+ *
+ * @return The calculated 64-bit xxHash64 value.
+ *
+ * @see @ref single_shot_example "Single Shot Example" for an example.
+ */
+XXH_PUBLIC_API XXH_PUREF XXH64_hash_t XXH64(XXH_NOESCAPE const void* input, size_t length, XXH64_hash_t seed);
+
+/*******   Streaming   *******/
+#ifndef XXH_NO_STREAM
+/*!
+ * @brief The opaque state struct for the XXH64 streaming API.
+ *
+ * @see XXH64_state_s for details.
+ * @see @ref streaming_example "Streaming Example"
+ */
+typedef struct XXH64_state_s XXH64_state_t;   /* incomplete type */
+
+/*!
+ * @brief Allocates an @ref XXH64_state_t.
+ *
+ * @return An allocated pointer of @ref XXH64_state_t on success.
+ * @return `NULL` on failure.
+ *
+ * @note Must be freed with XXH64_freeState().
+ *
+ * @see @ref streaming_example "Streaming Example"
+ */
+XXH_PUBLIC_API XXH_MALLOCF XXH64_state_t* XXH64_createState(void);
+
+/*!
+ * @brief Frees an @ref XXH64_state_t.
+ *
+ * @param statePtr A pointer to an @ref XXH64_state_t allocated with @ref XXH64_createState().
+ *
+ * @return @ref XXH_OK.
+ *
+ * @note @p statePtr must be allocated with XXH64_createState().
+ *
+ * @see @ref streaming_example "Streaming Example"
+ */
+XXH_PUBLIC_API XXH_errorcode  XXH64_freeState(XXH64_state_t* statePtr);
+
+/*!
+ * @brief Copies one @ref XXH64_state_t to another.
+ *
+ * @param dst_state The state to copy to.
+ * @param src_state The state to copy from.
+ * @pre
+ *   @p dst_state and @p src_state must not be `NULL` and must not overlap.
+ */
+XXH_PUBLIC_API void XXH64_copyState(XXH_NOESCAPE XXH64_state_t* dst_state, const XXH64_state_t* src_state);
+
+/*!
+ * @brief Resets an @ref XXH64_state_t to begin a new hash.
+ *
+ * @param statePtr The state struct to reset.
+ * @param seed The 64-bit seed to alter the hash result predictably.
+ *
+ * @pre
+ *   @p statePtr must not be `NULL`.
+ *
+ * @return @ref XXH_OK on success.
+ * @return @ref XXH_ERROR on failure.
+ *
+ * @note This function resets and seeds a state. Call it before @ref XXH64_update().
+ *
+ * @see @ref streaming_example "Streaming Example"
+ */
+XXH_PUBLIC_API XXH_errorcode XXH64_reset  (XXH_NOESCAPE XXH64_state_t* statePtr, XXH64_hash_t seed);
+
+/*!
+ * @brief Consumes a block of @p input to an @ref XXH64_state_t.
+ *
+ * @param statePtr The state struct to update.
+ * @param input The block of data to be hashed, at least @p length bytes in size.
+ * @param length The length of @p input, in bytes.
+ *
+ * @pre
+ *   @p statePtr must not be `NULL`.
+ * @pre
+ *   The memory between @p input and @p input + @p length must be valid,
+ *   readable, contiguous memory. However, if @p length is `0`, @p input may be
+ *   `NULL`. In C++, this also must be *TriviallyCopyable*.
+ *
+ * @return @ref XXH_OK on success.
+ * @return @ref XXH_ERROR on failure.
+ *
+ * @note Call this to incrementally consume blocks of data.
+ *
+ * @see @ref streaming_example "Streaming Example"
+ */
+XXH_PUBLIC_API XXH_errorcode XXH64_update (XXH_NOESCAPE XXH64_state_t* statePtr, XXH_NOESCAPE const void* input, size_t length);
+
+/*!
+ * @brief Returns the calculated hash value from an @ref XXH64_state_t.
+ *
+ * @param statePtr The state struct to calculate the hash from.
+ *
+ * @pre
+ *  @p statePtr must not be `NULL`.
+ *
+ * @return The calculated 64-bit xxHash64 value from that state.
+ *
+ * @note
+ *   Calling XXH64_digest() will not affect @p statePtr, so you can update,
+ *   digest, and update again.
+ *
+ * @see @ref streaming_example "Streaming Example"
+ */
+XXH_PUBLIC_API XXH_PUREF XXH64_hash_t XXH64_digest (XXH_NOESCAPE const XXH64_state_t* statePtr);
+#endif /* !XXH_NO_STREAM */
+/*******   Canonical representation   *******/
+
+/*!
+ * @brief Canonical (big endian) representation of @ref XXH64_hash_t.
+ */
+typedef struct { unsigned char digest[sizeof(XXH64_hash_t)]; } XXH64_canonical_t;
+
+/*!
+ * @brief Converts an @ref XXH64_hash_t to a big endian @ref XXH64_canonical_t.
+ *
+ * @param dst The @ref XXH64_canonical_t pointer to be stored to.
+ * @param hash The @ref XXH64_hash_t to be converted.
+ *
+ * @pre
+ *   @p dst must not be `NULL`.
+ *
+ * @see @ref canonical_representation_example "Canonical Representation Example"
+ */
+XXH_PUBLIC_API void XXH64_canonicalFromHash(XXH_NOESCAPE XXH64_canonical_t* dst, XXH64_hash_t hash);
+
+/*!
+ * @brief Converts an @ref XXH64_canonical_t to a native @ref XXH64_hash_t.
+ *
+ * @param src The @ref XXH64_canonical_t to convert.
+ *
+ * @pre
+ *   @p src must not be `NULL`.
+ *
+ * @return The converted hash.
+ *
+ * @see @ref canonical_representation_example "Canonical Representation Example"
+ */
+XXH_PUBLIC_API XXH_PUREF XXH64_hash_t XXH64_hashFromCanonical(XXH_NOESCAPE const XXH64_canonical_t* src);
+
+#ifndef XXH_NO_XXH3
+
+/*!
+ * @}
+ * ************************************************************************
+ * @defgroup XXH3_family XXH3 family
+ * @ingroup public
+ * @{
+ *
+ * XXH3 is a more recent hash algorithm featuring:
+ *  - Improved speed for both small and large inputs
+ *  - True 64-bit and 128-bit outputs
+ *  - SIMD acceleration
+ *  - Improved 32-bit viability
+ *
+ * Speed analysis methodology is explained here:
+ *
+ *    https://fastcompression.blogspot.com/2019/03/presenting-xxh3.html
+ *
+ * Compared to XXH64, expect XXH3 to run approximately
+ * ~2x faster on large inputs and >3x faster on small ones,
+ * exact differences vary depending on platform.
+ *
+ * XXH3's speed benefits greatly from SIMD and 64-bit arithmetic,
+ * but does not require it.
+ * Most 32-bit and 64-bit targets that can run XXH32 smoothly can run XXH3
+ * at competitive speeds, even without vector support. Further details are
+ * explained in the implementation.
+ *
+ * XXH3 has a fast scalar implementation, but it also includes accelerated SIMD
+ * implementations for many common platforms:
+ *   - AVX512
+ *   - AVX2
+ *   - SSE2
+ *   - ARM NEON
+ *   - WebAssembly SIMD128
+ *   - POWER8 VSX
+ *   - s390x ZVector
+ * This can be controlled via the @ref XXH_VECTOR macro, but it automatically
+ * selects the best version according to predefined macros. For the x86 family, an
+ * automatic runtime dispatcher is included separately in @ref xxh_x86dispatch.c.
+ *
+ * XXH3 implementation is portable:
+ * it has a generic C90 formulation that can be compiled on any platform,
+ * all implementations generate exactly the same hash value on all platforms.
+ * Starting from v0.8.0, it's also labelled "stable", meaning that
+ * any future version will also generate the same hash value.
+ *
+ * XXH3 offers 2 variants, _64bits and _128bits.
+ *
+ * When only 64 bits are needed, prefer invoking the _64bits variant, as it
+ * reduces the amount of mixing, resulting in faster speed on small inputs.
+ * It's also generally simpler to manipulate a scalar return type than a struct.
+ *
+ * The API supports one-shot hashing, streaming mode, and custom secrets.
+ */
+/*-**********************************************************************
+*  XXH3 64-bit variant
+************************************************************************/
+
+/*!
+ * @brief Calculates 64-bit unseeded variant of XXH3 hash of @p input.
+ *
+ * @param input  The block of data to be hashed, at least @p length bytes in size.
+ * @param length The length of @p input, in bytes.
+ *
+ * @pre
+ *   The memory between @p input and @p input + @p length must be valid,
+ *   readable, contiguous memory. However, if @p length is `0`, @p input may be
+ *   `NULL`. In C++, this also must be *TriviallyCopyable*.
+ *
+ * @return The calculated 64-bit XXH3 hash value.
+ *
+ * @note
+ *   This is equivalent to @ref XXH3_64bits_withSeed() with a seed of `0`, however
+ *   it may have slightly better performance due to constant propagation of the
+ *   defaults.
+ *
+ * @see
+ *    XXH3_64bits_withSeed(), XXH3_64bits_withSecret(): other seeding variants
+ * @see @ref single_shot_example "Single Shot Example" for an example.
+ */
+XXH_PUBLIC_API XXH_PUREF XXH64_hash_t XXH3_64bits(XXH_NOESCAPE const void* input, size_t length);
+
+/*!
+ * @brief Calculates 64-bit seeded variant of XXH3 hash of @p input.
+ *
+ * @param input  The block of data to be hashed, at least @p length bytes in size.
+ * @param length The length of @p input, in bytes.
+ * @param seed   The 64-bit seed to alter the hash result predictably.
+ *
+ * @pre
+ *   The memory between @p input and @p input + @p length must be valid,
+ *   readable, contiguous memory. However, if @p length is `0`, @p input may be
+ *   `NULL`. In C++, this also must be *TriviallyCopyable*.
+ *
+ * @return The calculated 64-bit XXH3 hash value.
+ *
+ * @note
+ *    seed == 0 produces the same results as @ref XXH3_64bits().
+ *
+ * This variant generates a custom secret on the fly based on default secret
+ * altered using the @p seed value.
+ *
+ * While this operation is decently fast, note that it's not completely free.
+ *
+ * @see @ref single_shot_example "Single Shot Example" for an example.
+ */
+XXH_PUBLIC_API XXH_PUREF XXH64_hash_t XXH3_64bits_withSeed(XXH_NOESCAPE const void* input, size_t length, XXH64_hash_t seed);
+
+/*!
+ * The bare minimum size for a custom secret.
+ *
+ * @see
+ *  XXH3_64bits_withSecret(), XXH3_64bits_reset_withSecret(),
+ *  XXH3_128bits_withSecret(), XXH3_128bits_reset_withSecret().
+ */
+#define XXH3_SECRET_SIZE_MIN 136
+
+/*!
+ * @brief Calculates 64-bit variant of XXH3 with a custom "secret".
+ *
+ * @param data       The block of data to be hashed, at least @p len bytes in size.
+ * @param len        The length of @p data, in bytes.
+ * @param secret     The secret data.
+ * @param secretSize The length of @p secret, in bytes.
+ *
+ * @return The calculated 64-bit XXH3 hash value.
+ *
+ * @pre
+ *   The memory between @p data and @p data + @p len must be valid,
+ *   readable, contiguous memory. However, if @p length is `0`, @p data may be
+ *   `NULL`. In C++, this also must be *TriviallyCopyable*.
+ *
+ * It's possible to provide any blob of bytes as a "secret" to generate the hash.
+ * This makes it more difficult for an external actor to prepare an intentional collision.
+ * The main condition is that @p secretSize *must* be large enough (>= @ref XXH3_SECRET_SIZE_MIN).
+ * However, the quality of the secret impacts the dispersion of the hash algorithm.
+ * Therefore, the secret _must_ look like a bunch of random bytes.
+ * Avoid "trivial" or structured data such as repeated sequences or a text document.
+ * Whenever in doubt about the "randomness" of the blob of bytes,
+ * consider employing @ref XXH3_generateSecret() instead (see below).
+ * It will generate a proper high entropy secret derived from the blob of bytes.
+ * Another advantage of using XXH3_generateSecret() is that
+ * it guarantees that all bits within the initial blob of bytes
+ * will impact every bit of the output.
+ * This is not necessarily the case when using the blob of bytes directly
+ * because, when hashing _small_ inputs, only a portion of the secret is employed.
+ *
+ * @see @ref single_shot_example "Single Shot Example" for an example.
+ */
+XXH_PUBLIC_API XXH_PUREF XXH64_hash_t XXH3_64bits_withSecret(XXH_NOESCAPE const void* data, size_t len, XXH_NOESCAPE const void* secret, size_t secretSize);
+
+
+/*******   Streaming   *******/
+#ifndef XXH_NO_STREAM
+/*
+ * Streaming requires state maintenance.
+ * This operation costs memory and CPU.
+ * As a consequence, streaming is slower than one-shot hashing.
+ * For better performance, prefer one-shot functions whenever applicable.
+ */
+
+/*!
+ * @brief The opaque state struct for the XXH3 streaming API.
+ *
+ * @see XXH3_state_s for details.
+ * @see @ref streaming_example "Streaming Example"
+ */
+typedef struct XXH3_state_s XXH3_state_t;
+XXH_PUBLIC_API XXH_MALLOCF XXH3_state_t* XXH3_createState(void);
+XXH_PUBLIC_API XXH_errorcode XXH3_freeState(XXH3_state_t* statePtr);
+
+/*!
+ * @brief Copies one @ref XXH3_state_t to another.
+ *
+ * @param dst_state The state to copy to.
+ * @param src_state The state to copy from.
+ * @pre
+ *   @p dst_state and @p src_state must not be `NULL` and must not overlap.
+ */
+XXH_PUBLIC_API void XXH3_copyState(XXH_NOESCAPE XXH3_state_t* dst_state, XXH_NOESCAPE const XXH3_state_t* src_state);
+
+/*!
+ * @brief Resets an @ref XXH3_state_t to begin a new hash.
+ *
+ * @param statePtr The state struct to reset.
+ *
+ * @pre
+ *   @p statePtr must not be `NULL`.
+ *
+ * @return @ref XXH_OK on success.
+ * @return @ref XXH_ERROR on failure.
+ *
+ * @note
+ *   - This function resets `statePtr` and generate a secret with default parameters.
+ *   - Call this function before @ref XXH3_64bits_update().
+ *   - Digest will be equivalent to `XXH3_64bits()`.
+ *
+ * @see @ref streaming_example "Streaming Example"
+ *
+ */
+XXH_PUBLIC_API XXH_errorcode XXH3_64bits_reset(XXH_NOESCAPE XXH3_state_t* statePtr);
+
+/*!
+ * @brief Resets an @ref XXH3_state_t with 64-bit seed to begin a new hash.
+ *
+ * @param statePtr The state struct to reset.
+ * @param seed     The 64-bit seed to alter the hash result predictably.
+ *
+ * @pre
+ *   @p statePtr must not be `NULL`.
+ *
+ * @return @ref XXH_OK on success.
+ * @return @ref XXH_ERROR on failure.
+ *
+ * @note
+ *   - This function resets `statePtr` and generate a secret from `seed`.
+ *   - Call this function before @ref XXH3_64bits_update().
+ *   - Digest will be equivalent to `XXH3_64bits_withSeed()`.
+ *
+ * @see @ref streaming_example "Streaming Example"
+ *
+ */
+XXH_PUBLIC_API XXH_errorcode XXH3_64bits_reset_withSeed(XXH_NOESCAPE XXH3_state_t* statePtr, XXH64_hash_t seed);
+
+/*!
+ * @brief Resets an @ref XXH3_state_t with secret data to begin a new hash.
+ *
+ * @param statePtr The state struct to reset.
+ * @param secret     The secret data.
+ * @param secretSize The length of @p secret, in bytes.
+ *
+ * @pre
+ *   @p statePtr must not be `NULL`.
+ *
+ * @return @ref XXH_OK on success.
+ * @return @ref XXH_ERROR on failure.
+ *
+ * @note
+ *   `secret` is referenced, it _must outlive_ the hash streaming session.
+ *
+ * Similar to one-shot API, `secretSize` must be >= @ref XXH3_SECRET_SIZE_MIN,
+ * and the quality of produced hash values depends on secret's entropy
+ * (secret's content should look like a bunch of random bytes).
+ * When in doubt about the randomness of a candidate `secret`,
+ * consider employing `XXH3_generateSecret()` instead (see below).
+ *
+ * @see @ref streaming_example "Streaming Example"
+ */
+XXH_PUBLIC_API XXH_errorcode XXH3_64bits_reset_withSecret(XXH_NOESCAPE XXH3_state_t* statePtr, XXH_NOESCAPE const void* secret, size_t secretSize);
+
+/*!
+ * @brief Consumes a block of @p input to an @ref XXH3_state_t.
+ *
+ * @param statePtr The state struct to update.
+ * @param input The block of data to be hashed, at least @p length bytes in size.
+ * @param length The length of @p input, in bytes.
+ *
+ * @pre
+ *   @p statePtr must not be `NULL`.
+ * @pre
+ *   The memory between @p input and @p input + @p length must be valid,
+ *   readable, contiguous memory. However, if @p length is `0`, @p input may be
+ *   `NULL`. In C++, this also must be *TriviallyCopyable*.
+ *
+ * @return @ref XXH_OK on success.
+ * @return @ref XXH_ERROR on failure.
+ *
+ * @note Call this to incrementally consume blocks of data.
+ *
+ * @see @ref streaming_example "Streaming Example"
+ */
+XXH_PUBLIC_API XXH_errorcode XXH3_64bits_update (XXH_NOESCAPE XXH3_state_t* statePtr, XXH_NOESCAPE const void* input, size_t length);
+
+/*!
+ * @brief Returns the calculated XXH3 64-bit hash value from an @ref XXH3_state_t.
+ *
+ * @param statePtr The state struct to calculate the hash from.
+ *
+ * @pre
+ *  @p statePtr must not be `NULL`.
+ *
+ * @return The calculated XXH3 64-bit hash value from that state.
+ *
+ * @note
+ *   Calling XXH3_64bits_digest() will not affect @p statePtr, so you can update,
+ *   digest, and update again.
+ *
+ * @see @ref streaming_example "Streaming Example"
+ */
+XXH_PUBLIC_API XXH_PUREF XXH64_hash_t  XXH3_64bits_digest (XXH_NOESCAPE const XXH3_state_t* statePtr);
+#endif /* !XXH_NO_STREAM */
+
+/* note : canonical representation of XXH3 is the same as XXH64
+ * since they both produce XXH64_hash_t values */
+
+
+/*-**********************************************************************
+*  XXH3 128-bit variant
+************************************************************************/
+
+/*!
+ * @brief The return value from 128-bit hashes.
+ *
+ * Stored in little endian order, although the fields themselves are in native
+ * endianness.
+ */
+typedef struct {
+    XXH64_hash_t low64;   /*!< `value & 0xFFFFFFFFFFFFFFFF` */
+    XXH64_hash_t high64;  /*!< `value >> 64` */
+} XXH128_hash_t;
+
+/*!
+ * @brief Calculates 128-bit unseeded variant of XXH3 of @p data.
+ *
+ * @param data The block of data to be hashed, at least @p length bytes in size.
+ * @param len  The length of @p data, in bytes.
+ *
+ * @return The calculated 128-bit variant of XXH3 value.
+ *
+ * The 128-bit variant of XXH3 has more strength, but it has a bit of overhead
+ * for shorter inputs.
+ *
+ * This is equivalent to @ref XXH3_128bits_withSeed() with a seed of `0`, however
+ * it may have slightly better performance due to constant propagation of the
+ * defaults.
+ *
+ * @see XXH3_128bits_withSeed(), XXH3_128bits_withSecret(): other seeding variants
+ * @see @ref single_shot_example "Single Shot Example" for an example.
+ */
+XXH_PUBLIC_API XXH_PUREF XXH128_hash_t XXH3_128bits(XXH_NOESCAPE const void* data, size_t len);
+/*! @brief Calculates 128-bit seeded variant of XXH3 hash of @p data.
+ *
+ * @param data The block of data to be hashed, at least @p length bytes in size.
+ * @param len  The length of @p data, in bytes.
+ * @param seed The 64-bit seed to alter the hash result predictably.
+ *
+ * @return The calculated 128-bit variant of XXH3 value.
+ *
+ * @note
+ *    seed == 0 produces the same results as @ref XXH3_64bits().
+ *
+ * This variant generates a custom secret on the fly based on default secret
+ * altered using the @p seed value.
+ *
+ * While this operation is decently fast, note that it's not completely free.
+ *
+ * @see XXH3_128bits(), XXH3_128bits_withSecret(): other seeding variants
+ * @see @ref single_shot_example "Single Shot Example" for an example.
+ */
+XXH_PUBLIC_API XXH_PUREF XXH128_hash_t XXH3_128bits_withSeed(XXH_NOESCAPE const void* data, size_t len, XXH64_hash_t seed);
+/*!
+ * @brief Calculates 128-bit variant of XXH3 with a custom "secret".
+ *
+ * @param data       The block of data to be hashed, at least @p len bytes in size.
+ * @param len        The length of @p data, in bytes.
+ * @param secret     The secret data.
+ * @param secretSize The length of @p secret, in bytes.
+ *
+ * @return The calculated 128-bit variant of XXH3 value.
+ *
+ * It's possible to provide any blob of bytes as a "secret" to generate the hash.
+ * This makes it more difficult for an external actor to prepare an intentional collision.
+ * The main condition is that @p secretSize *must* be large enough (>= @ref XXH3_SECRET_SIZE_MIN).
+ * However, the quality of the secret impacts the dispersion of the hash algorithm.
+ * Therefore, the secret _must_ look like a bunch of random bytes.
+ * Avoid "trivial" or structured data such as repeated sequences or a text document.
+ * Whenever in doubt about the "randomness" of the blob of bytes,
+ * consider employing @ref XXH3_generateSecret() instead (see below).
+ * It will generate a proper high entropy secret derived from the blob of bytes.
+ * Another advantage of using XXH3_generateSecret() is that
+ * it guarantees that all bits within the initial blob of bytes
+ * will impact every bit of the output.
+ * This is not necessarily the case when using the blob of bytes directly
+ * because, when hashing _small_ inputs, only a portion of the secret is employed.
+ *
+ * @see @ref single_shot_example "Single Shot Example" for an example.
+ */
+XXH_PUBLIC_API XXH_PUREF XXH128_hash_t XXH3_128bits_withSecret(XXH_NOESCAPE const void* data, size_t len, XXH_NOESCAPE const void* secret, size_t secretSize);
+
+/*******   Streaming   *******/
+#ifndef XXH_NO_STREAM
+/*
+ * Streaming requires state maintenance.
+ * This operation costs memory and CPU.
+ * As a consequence, streaming is slower than one-shot hashing.
+ * For better performance, prefer one-shot functions whenever applicable.
+ *
+ * XXH3_128bits uses the same XXH3_state_t as XXH3_64bits().
+ * Use already declared XXH3_createState() and XXH3_freeState().
+ *
+ * All reset and streaming functions have same meaning as their 64-bit counterpart.
+ */
+
+/*!
+ * @brief Resets an @ref XXH3_state_t to begin a new hash.
+ *
+ * @param statePtr The state struct to reset.
+ *
+ * @pre
+ *   @p statePtr must not be `NULL`.
+ *
+ * @return @ref XXH_OK on success.
+ * @return @ref XXH_ERROR on failure.
+ *
+ * @note
+ *   - This function resets `statePtr` and generate a secret with default parameters.
+ *   - Call it before @ref XXH3_128bits_update().
+ *   - Digest will be equivalent to `XXH3_128bits()`.
+ *
+ * @see @ref streaming_example "Streaming Example"
+ */
+XXH_PUBLIC_API XXH_errorcode XXH3_128bits_reset(XXH_NOESCAPE XXH3_state_t* statePtr);
+
+/*!
+ * @brief Resets an @ref XXH3_state_t with 64-bit seed to begin a new hash.
+ *
+ * @param statePtr The state struct to reset.
+ * @param seed     The 64-bit seed to alter the hash result predictably.
+ *
+ * @pre
+ *   @p statePtr must not be `NULL`.
+ *
+ * @return @ref XXH_OK on success.
+ * @return @ref XXH_ERROR on failure.
+ *
+ * @note
+ *   - This function resets `statePtr` and generate a secret from `seed`.
+ *   - Call it before @ref XXH3_128bits_update().
+ *   - Digest will be equivalent to `XXH3_128bits_withSeed()`.
+ *
+ * @see @ref streaming_example "Streaming Example"
+ */
+XXH_PUBLIC_API XXH_errorcode XXH3_128bits_reset_withSeed(XXH_NOESCAPE XXH3_state_t* statePtr, XXH64_hash_t seed);
+/*!
+ * @brief Resets an @ref XXH3_state_t with secret data to begin a new hash.
+ *
+ * @param statePtr   The state struct to reset.
+ * @param secret     The secret data.
+ * @param secretSize The length of @p secret, in bytes.
+ *
+ * @pre
+ *   @p statePtr must not be `NULL`.
+ *
+ * @return @ref XXH_OK on success.
+ * @return @ref XXH_ERROR on failure.
+ *
+ * `secret` is referenced, it _must outlive_ the hash streaming session.
+ * Similar to one-shot API, `secretSize` must be >= @ref XXH3_SECRET_SIZE_MIN,
+ * and the quality of produced hash values depends on secret's entropy
+ * (secret's content should look like a bunch of random bytes).
+ * When in doubt about the randomness of a candidate `secret`,
+ * consider employing `XXH3_generateSecret()` instead (see below).
+ *
+ * @see @ref streaming_example "Streaming Example"
+ */
+XXH_PUBLIC_API XXH_errorcode XXH3_128bits_reset_withSecret(XXH_NOESCAPE XXH3_state_t* statePtr, XXH_NOESCAPE const void* secret, size_t secretSize);
+
+/*!
+ * @brief Consumes a block of @p input to an @ref XXH3_state_t.
+ *
+ * Call this to incrementally consume blocks of data.
+ *
+ * @param statePtr The state struct to update.
+ * @param input The block of data to be hashed, at least @p length bytes in size.
+ * @param length The length of @p input, in bytes.
+ *
+ * @pre
+ *   @p statePtr must not be `NULL`.
+ *
+ * @return @ref XXH_OK on success.
+ * @return @ref XXH_ERROR on failure.
+ *
+ * @note
+ *   The memory between @p input and @p input + @p length must be valid,
+ *   readable, contiguous memory. However, if @p length is `0`, @p input may be
+ *   `NULL`. In C++, this also must be *TriviallyCopyable*.
+ *
+ */
+XXH_PUBLIC_API XXH_errorcode XXH3_128bits_update (XXH_NOESCAPE XXH3_state_t* statePtr, XXH_NOESCAPE const void* input, size_t length);
+
+/*!
+ * @brief Returns the calculated XXH3 128-bit hash value from an @ref XXH3_state_t.
+ *
+ * @param statePtr The state struct to calculate the hash from.
+ *
+ * @pre
+ *  @p statePtr must not be `NULL`.
+ *
+ * @return The calculated XXH3 128-bit hash value from that state.
+ *
+ * @note
+ *   Calling XXH3_128bits_digest() will not affect @p statePtr, so you can update,
+ *   digest, and update again.
+ *
+ */
+XXH_PUBLIC_API XXH_PUREF XXH128_hash_t XXH3_128bits_digest (XXH_NOESCAPE const XXH3_state_t* statePtr);
+#endif /* !XXH_NO_STREAM */
+
+/* Following helper functions make it possible to compare XXH128_hast_t values.
+ * Since XXH128_hash_t is a structure, this capability is not offered by the language.
+ * Note: For better performance, these functions can be inlined using XXH_INLINE_ALL */
+
+/*!
+ * @brief Check equality of two XXH128_hash_t values
+ *
+ * @param h1 The 128-bit hash value.
+ * @param h2 Another 128-bit hash value.
+ *
+ * @return `1` if `h1` and `h2` are equal.
+ * @return `0` if they are not.
+ */
+XXH_PUBLIC_API XXH_PUREF int XXH128_isEqual(XXH128_hash_t h1, XXH128_hash_t h2);
+
+/*!
+ * @brief Compares two @ref XXH128_hash_t
+ *
+ * This comparator is compatible with stdlib's `qsort()`/`bsearch()`.
+ *
+ * @param h128_1 Left-hand side value
+ * @param h128_2 Right-hand side value
+ *
+ * @return >0 if @p h128_1  > @p h128_2
+ * @return =0 if @p h128_1 == @p h128_2
+ * @return <0 if @p h128_1  < @p h128_2
+ */
+XXH_PUBLIC_API XXH_PUREF int XXH128_cmp(XXH_NOESCAPE const void* h128_1, XXH_NOESCAPE const void* h128_2);
+
+
+/*******   Canonical representation   *******/
+typedef struct { unsigned char digest[sizeof(XXH128_hash_t)]; } XXH128_canonical_t;
+
+
+/*!
+ * @brief Converts an @ref XXH128_hash_t to a big endian @ref XXH128_canonical_t.
+ *
+ * @param dst  The @ref XXH128_canonical_t pointer to be stored to.
+ * @param hash The @ref XXH128_hash_t to be converted.
+ *
+ * @pre
+ *   @p dst must not be `NULL`.
+ * @see @ref canonical_representation_example "Canonical Representation Example"
+ */
+XXH_PUBLIC_API void XXH128_canonicalFromHash(XXH_NOESCAPE XXH128_canonical_t* dst, XXH128_hash_t hash);
+
+/*!
+ * @brief Converts an @ref XXH128_canonical_t to a native @ref XXH128_hash_t.
+ *
+ * @param src The @ref XXH128_canonical_t to convert.
+ *
+ * @pre
+ *   @p src must not be `NULL`.
+ *
+ * @return The converted hash.
+ * @see @ref canonical_representation_example "Canonical Representation Example"
+ */
+XXH_PUBLIC_API XXH_PUREF XXH128_hash_t XXH128_hashFromCanonical(XXH_NOESCAPE const XXH128_canonical_t* src);
+
+
+#endif  /* !XXH_NO_XXH3 */
+#endif  /* XXH_NO_LONG_LONG */
+
+/*!
+ * @}
+ */
+#endif /* XXHASH_H_5627135585666179 */
+
+
+
+#if defined(XXH_STATIC_LINKING_ONLY) && !defined(XXHASH_H_STATIC_13879238742)
+#define XXHASH_H_STATIC_13879238742
+/* ****************************************************************************
+ * This section contains declarations which are not guaranteed to remain stable.
+ * They may change in future versions, becoming incompatible with a different
+ * version of the library.
+ * These declarations should only be used with static linking.
+ * Never use them in association with dynamic linking!
+ ***************************************************************************** */
+
+/*
+ * These definitions are only present to allow static allocation
+ * of XXH states, on stack or in a struct, for example.
+ * Never **ever** access their members directly.
+ */
+
+/*!
+ * @internal
+ * @brief Structure for XXH32 streaming API.
+ *
+ * @note This is only defined when @ref XXH_STATIC_LINKING_ONLY,
+ * @ref XXH_INLINE_ALL, or @ref XXH_IMPLEMENTATION is defined. Otherwise it is
+ * an opaque type. This allows fields to safely be changed.
+ *
+ * Typedef'd to @ref XXH32_state_t.
+ * Do not access the members of this struct directly.
+ * @see XXH64_state_s, XXH3_state_s
+ */
+struct XXH32_state_s {
+   XXH32_hash_t total_len_32; /*!< Total length hashed, modulo 2^32 */
+   XXH32_hash_t large_len;    /*!< Whether the hash is >= 16 (handles @ref total_len_32 overflow) */
+   XXH32_hash_t v[4];         /*!< Accumulator lanes */
+   XXH32_hash_t mem32[4];     /*!< Internal buffer for partial reads. Treated as unsigned char[16]. */
+   XXH32_hash_t memsize;      /*!< Amount of data in @ref mem32 */
+   XXH32_hash_t reserved;     /*!< Reserved field. Do not read nor write to it. */
+};   /* typedef'd to XXH32_state_t */
+
+
+#ifndef XXH_NO_LONG_LONG  /* defined when there is no 64-bit support */
+
+/*!
+ * @internal
+ * @brief Structure for XXH64 streaming API.
+ *
+ * @note This is only defined when @ref XXH_STATIC_LINKING_ONLY,
+ * @ref XXH_INLINE_ALL, or @ref XXH_IMPLEMENTATION is defined. Otherwise it is
+ * an opaque type. This allows fields to safely be changed.
+ *
+ * Typedef'd to @ref XXH64_state_t.
+ * Do not access the members of this struct directly.
+ * @see XXH32_state_s, XXH3_state_s
+ */
+struct XXH64_state_s {
+   XXH64_hash_t total_len;    /*!< Total length hashed. This is always 64-bit. */
+   XXH64_hash_t v[4];         /*!< Accumulator lanes */
+   XXH64_hash_t mem64[4];     /*!< Internal buffer for partial reads. Treated as unsigned char[32]. */
+   XXH32_hash_t memsize;      /*!< Amount of data in @ref mem64 */
+   XXH32_hash_t reserved32;   /*!< Reserved field, needed for padding anyways*/
+   XXH64_hash_t reserved64;   /*!< Reserved field. Do not read or write to it. */
+};   /* typedef'd to XXH64_state_t */
+
+#ifndef XXH_NO_XXH3
+
+/* Windows SDK under 10.0.22000 is missing stdalign.h so we add a check
+   before allowing the windows compiler to use the C11 form.
+   Reference: https://github.com/Cyan4973/xxHash/issues/955 */
+#if defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 201112L) \
+    && (defined(_MSC_VER) && (_MSC_VER >= 1000) || !defined(_MSC_VER)) /* >= C11 */
+#  include 
+#  define XXH_ALIGN(n)      alignas(n)
+#elif defined(__cplusplus) && (__cplusplus >= 201103L) /* >= C++11 */
+/* In C++ alignas() is a keyword */
+#  define XXH_ALIGN(n)      alignas(n)
+#elif defined(__GNUC__)
+#  define XXH_ALIGN(n)      __attribute__ ((aligned(n)))
+#elif defined(_MSC_VER)
+#  define XXH_ALIGN(n)      __declspec(align(n))
+#else
+#  define XXH_ALIGN(n)   /* disabled */
+#endif
+
+/* Old GCC versions only accept the attribute after the type in structures. */
+#if !(defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 201112L))   /* C11+ */ \
+    && ! (defined(__cplusplus) && (__cplusplus >= 201103L)) /* >= C++11 */ \
+    && defined(__GNUC__)
+#   define XXH_ALIGN_MEMBER(align, type) type XXH_ALIGN(align)
+#else
+#   define XXH_ALIGN_MEMBER(align, type) XXH_ALIGN(align) type
+#endif
+
+/*!
+ * @brief The size of the internal XXH3 buffer.
+ *
+ * This is the optimal update size for incremental hashing.
+ *
+ * @see XXH3_64b_update(), XXH3_128b_update().
+ */
+#define XXH3_INTERNALBUFFER_SIZE 256
+
+/*!
+ * @internal
+ * @brief Default size of the secret buffer (and @ref XXH3_kSecret).
+ *
+ * This is the size used in @ref XXH3_kSecret and the seeded functions.
+ *
+ * Not to be confused with @ref XXH3_SECRET_SIZE_MIN.
+ */
+#define XXH3_SECRET_DEFAULT_SIZE 192
+
+/*!
+ * @internal
+ * @brief Structure for XXH3 streaming API.
+ *
+ * @note This is only defined when @ref XXH_STATIC_LINKING_ONLY,
+ * @ref XXH_INLINE_ALL, or @ref XXH_IMPLEMENTATION is defined.
+ * Otherwise it is an opaque type.
+ * Never use this definition in combination with dynamic library.
+ * This allows fields to safely be changed in the future.
+ *
+ * @note ** This structure has a strict alignment requirement of 64 bytes!! **
+ * Do not allocate this with `malloc()` or `new`,
+ * it will not be sufficiently aligned.
+ * Use @ref XXH3_createState() and @ref XXH3_freeState(), or stack allocation.
+ *
+ * Typedef'd to @ref XXH3_state_t.
+ * Do never access the members of this struct directly.
+ *
+ * @see XXH3_INITSTATE() for stack initialization.
+ * @see XXH3_createState(), XXH3_freeState().
+ * @see XXH32_state_s, XXH64_state_s
+ */
+struct XXH3_state_s {
+   XXH_ALIGN_MEMBER(64, XXH64_hash_t acc[8]);
+       /*!< The 8 accumulators. See @ref XXH32_state_s::v and @ref XXH64_state_s::v */
+   XXH_ALIGN_MEMBER(64, unsigned char customSecret[XXH3_SECRET_DEFAULT_SIZE]);
+       /*!< Used to store a custom secret generated from a seed. */
+   XXH_ALIGN_MEMBER(64, unsigned char buffer[XXH3_INTERNALBUFFER_SIZE]);
+       /*!< The internal buffer. @see XXH32_state_s::mem32 */
+   XXH32_hash_t bufferedSize;
+       /*!< The amount of memory in @ref buffer, @see XXH32_state_s::memsize */
+   XXH32_hash_t useSeed;
+       /*!< Reserved field. Needed for padding on 64-bit. */
+   size_t nbStripesSoFar;
+       /*!< Number or stripes processed. */
+   XXH64_hash_t totalLen;
+       /*!< Total length hashed. 64-bit even on 32-bit targets. */
+   size_t nbStripesPerBlock;
+       /*!< Number of stripes per block. */
+   size_t secretLimit;
+       /*!< Size of @ref customSecret or @ref extSecret */
+   XXH64_hash_t seed;
+       /*!< Seed for _withSeed variants. Must be zero otherwise, @see XXH3_INITSTATE() */
+   XXH64_hash_t reserved64;
+       /*!< Reserved field. */
+   const unsigned char* extSecret;
+       /*!< Reference to an external secret for the _withSecret variants, NULL
+        *   for other variants. */
+   /* note: there may be some padding at the end due to alignment on 64 bytes */
+}; /* typedef'd to XXH3_state_t */
+
+#undef XXH_ALIGN_MEMBER
+
+/*!
+ * @brief Initializes a stack-allocated `XXH3_state_s`.
+ *
+ * When the @ref XXH3_state_t structure is merely emplaced on stack,
+ * it should be initialized with XXH3_INITSTATE() or a memset()
+ * in case its first reset uses XXH3_NNbits_reset_withSeed().
+ * This init can be omitted if the first reset uses default or _withSecret mode.
+ * This operation isn't necessary when the state is created with XXH3_createState().
+ * Note that this doesn't prepare the state for a streaming operation,
+ * it's still necessary to use XXH3_NNbits_reset*() afterwards.
+ */
+#define XXH3_INITSTATE(XXH3_state_ptr)                       \
+    do {                                                     \
+        XXH3_state_t* tmp_xxh3_state_ptr = (XXH3_state_ptr); \
+        tmp_xxh3_state_ptr->seed = 0;                        \
+        tmp_xxh3_state_ptr->extSecret = NULL;                \
+    } while(0)
+
+
+/*!
+ * @brief Calculates the 128-bit hash of @p data using XXH3.
+ *
+ * @param data The block of data to be hashed, at least @p len bytes in size.
+ * @param len  The length of @p data, in bytes.
+ * @param seed The 64-bit seed to alter the hash's output predictably.
+ *
+ * @pre
+ *   The memory between @p data and @p data + @p len must be valid,
+ *   readable, contiguous memory. However, if @p len is `0`, @p data may be
+ *   `NULL`. In C++, this also must be *TriviallyCopyable*.
+ *
+ * @return The calculated 128-bit XXH3 value.
+ *
+ * @see @ref single_shot_example "Single Shot Example" for an example.
+ */
+XXH_PUBLIC_API XXH_PUREF XXH128_hash_t XXH128(XXH_NOESCAPE const void* data, size_t len, XXH64_hash_t seed);
+
+
+/* ===   Experimental API   === */
+/* Symbols defined below must be considered tied to a specific library version. */
+
+/*!
+ * @brief Derive a high-entropy secret from any user-defined content, named customSeed.
+ *
+ * @param secretBuffer    A writable buffer for derived high-entropy secret data.
+ * @param secretSize      Size of secretBuffer, in bytes.  Must be >= XXH3_SECRET_SIZE_MIN.
+ * @param customSeed      A user-defined content.
+ * @param customSeedSize  Size of customSeed, in bytes.
+ *
+ * @return @ref XXH_OK on success.
+ * @return @ref XXH_ERROR on failure.
+ *
+ * The generated secret can be used in combination with `*_withSecret()` functions.
+ * The `_withSecret()` variants are useful to provide a higher level of protection
+ * than 64-bit seed, as it becomes much more difficult for an external actor to
+ * guess how to impact the calculation logic.
+ *
+ * The function accepts as input a custom seed of any length and any content,
+ * and derives from it a high-entropy secret of length @p secretSize into an
+ * already allocated buffer @p secretBuffer.
+ *
+ * The generated secret can then be used with any `*_withSecret()` variant.
+ * The functions @ref XXH3_128bits_withSecret(), @ref XXH3_64bits_withSecret(),
+ * @ref XXH3_128bits_reset_withSecret() and @ref XXH3_64bits_reset_withSecret()
+ * are part of this list. They all accept a `secret` parameter
+ * which must be large enough for implementation reasons (>= @ref XXH3_SECRET_SIZE_MIN)
+ * _and_ feature very high entropy (consist of random-looking bytes).
+ * These conditions can be a high bar to meet, so @ref XXH3_generateSecret() can
+ * be employed to ensure proper quality.
+ *
+ * @p customSeed can be anything. It can have any size, even small ones,
+ * and its content can be anything, even "poor entropy" sources such as a bunch
+ * of zeroes. The resulting `secret` will nonetheless provide all required qualities.
+ *
+ * @pre
+ *   - @p secretSize must be >= @ref XXH3_SECRET_SIZE_MIN
+ *   - When @p customSeedSize > 0, supplying NULL as customSeed is undefined behavior.
+ *
+ * Example code:
+ * @code{.c}
+ *    #include 
+ *    #include 
+ *    #include 
+ *    #define XXH_STATIC_LINKING_ONLY // expose unstable API
+ *    #include "xxhash.h"
+ *    // Hashes argv[2] using the entropy from argv[1].
+ *    int main(int argc, char* argv[])
+ *    {
+ *        char secret[XXH3_SECRET_SIZE_MIN];
+ *        if (argv != 3) { return 1; }
+ *        XXH3_generateSecret(secret, sizeof(secret), argv[1], strlen(argv[1]));
+ *        XXH64_hash_t h = XXH3_64bits_withSecret(
+ *             argv[2], strlen(argv[2]),
+ *             secret, sizeof(secret)
+ *        );
+ *        printf("%016llx\n", (unsigned long long) h);
+ *    }
+ * @endcode
+ */
+XXH_PUBLIC_API XXH_errorcode XXH3_generateSecret(XXH_NOESCAPE void* secretBuffer, size_t secretSize, XXH_NOESCAPE const void* customSeed, size_t customSeedSize);
+
+/*!
+ * @brief Generate the same secret as the _withSeed() variants.
+ *
+ * @param secretBuffer A writable buffer of @ref XXH3_SECRET_DEFAULT_SIZE bytes
+ * @param seed         The 64-bit seed to alter the hash result predictably.
+ *
+ * The generated secret can be used in combination with
+ *`*_withSecret()` and `_withSecretandSeed()` variants.
+ *
+ * Example C++ `std::string` hash class:
+ * @code{.cpp}
+ *    #include 
+ *    #define XXH_STATIC_LINKING_ONLY // expose unstable API
+ *    #include "xxhash.h"
+ *    // Slow, seeds each time
+ *    class HashSlow {
+ *        XXH64_hash_t seed;
+ *    public:
+ *        HashSlow(XXH64_hash_t s) : seed{s} {}
+ *        size_t operator()(const std::string& x) const {
+ *            return size_t{XXH3_64bits_withSeed(x.c_str(), x.length(), seed)};
+ *        }
+ *    };
+ *    // Fast, caches the seeded secret for future uses.
+ *    class HashFast {
+ *        unsigned char secret[XXH3_SECRET_DEFAULT_SIZE];
+ *    public:
+ *        HashFast(XXH64_hash_t s) {
+ *            XXH3_generateSecret_fromSeed(secret, seed);
+ *        }
+ *        size_t operator()(const std::string& x) const {
+ *            return size_t{
+ *                XXH3_64bits_withSecret(x.c_str(), x.length(), secret, sizeof(secret))
+ *            };
+ *        }
+ *    };
+ * @endcode
+ */
+XXH_PUBLIC_API void XXH3_generateSecret_fromSeed(XXH_NOESCAPE void* secretBuffer, XXH64_hash_t seed);
+
+/*!
+ * @brief Maximum size of "short" key in bytes.
+ */
+#define XXH3_MIDSIZE_MAX 240
+
+/*!
+ * @brief Calculates 64/128-bit seeded variant of XXH3 hash of @p data.
+ *
+ * @param data       The block of data to be hashed, at least @p len bytes in size.
+ * @param len        The length of @p data, in bytes.
+ * @param secret     The secret data.
+ * @param secretSize The length of @p secret, in bytes.
+ * @param seed       The 64-bit seed to alter the hash result predictably.
+ *
+ * These variants generate hash values using either:
+ * - @p seed for "short" keys (< @ref XXH3_MIDSIZE_MAX = 240 bytes)
+ * - @p secret for "large" keys (>= @ref XXH3_MIDSIZE_MAX).
+ *
+ * This generally benefits speed, compared to `_withSeed()` or `_withSecret()`.
+ * `_withSeed()` has to generate the secret on the fly for "large" keys.
+ * It's fast, but can be perceptible for "not so large" keys (< 1 KB).
+ * `_withSecret()` has to generate the masks on the fly for "small" keys,
+ * which requires more instructions than _withSeed() variants.
+ * Therefore, _withSecretandSeed variant combines the best of both worlds.
+ *
+ * When @p secret has been generated by XXH3_generateSecret_fromSeed(),
+ * this variant produces *exactly* the same results as `_withSeed()` variant,
+ * hence offering only a pure speed benefit on "large" input,
+ * by skipping the need to regenerate the secret for every large input.
+ *
+ * Another usage scenario is to hash the secret to a 64-bit hash value,
+ * for example with XXH3_64bits(), which then becomes the seed,
+ * and then employ both the seed and the secret in _withSecretandSeed().
+ * On top of speed, an added benefit is that each bit in the secret
+ * has a 50% chance to swap each bit in the output, via its impact to the seed.
+ *
+ * This is not guaranteed when using the secret directly in "small data" scenarios,
+ * because only portions of the secret are employed for small data.
+ */
+XXH_PUBLIC_API XXH_PUREF XXH64_hash_t
+XXH3_64bits_withSecretandSeed(XXH_NOESCAPE const void* data, size_t len,
+                              XXH_NOESCAPE const void* secret, size_t secretSize,
+                              XXH64_hash_t seed);
+
+/*!
+ * @brief Calculates 128-bit seeded variant of XXH3 hash of @p data.
+ *
+ * @param data       The memory segment to be hashed, at least @p len bytes in size.
+ * @param length     The length of @p data, in bytes.
+ * @param secret     The secret used to alter hash result predictably.
+ * @param secretSize The length of @p secret, in bytes (must be >= XXH3_SECRET_SIZE_MIN)
+ * @param seed64     The 64-bit seed to alter the hash result predictably.
+ *
+ * @return @ref XXH_OK on success.
+ * @return @ref XXH_ERROR on failure.
+ *
+ * @see XXH3_64bits_withSecretandSeed(): contract is the same.
+ */
+XXH_PUBLIC_API XXH_PUREF XXH128_hash_t
+XXH3_128bits_withSecretandSeed(XXH_NOESCAPE const void* input, size_t length,
+                               XXH_NOESCAPE const void* secret, size_t secretSize,
+                               XXH64_hash_t seed64);
+
+#ifndef XXH_NO_STREAM
+/*!
+ * @brief Resets an @ref XXH3_state_t with secret data to begin a new hash.
+ *
+ * @param statePtr   A pointer to an @ref XXH3_state_t allocated with @ref XXH3_createState().
+ * @param secret     The secret data.
+ * @param secretSize The length of @p secret, in bytes.
+ * @param seed64     The 64-bit seed to alter the hash result predictably.
+ *
+ * @return @ref XXH_OK on success.
+ * @return @ref XXH_ERROR on failure.
+ *
+ * @see XXH3_64bits_withSecretandSeed(). Contract is identical.
+ */
+XXH_PUBLIC_API XXH_errorcode
+XXH3_64bits_reset_withSecretandSeed(XXH_NOESCAPE XXH3_state_t* statePtr,
+                                    XXH_NOESCAPE const void* secret, size_t secretSize,
+                                    XXH64_hash_t seed64);
+
+/*!
+ * @brief Resets an @ref XXH3_state_t with secret data to begin a new hash.
+ *
+ * @param statePtr   A pointer to an @ref XXH3_state_t allocated with @ref XXH3_createState().
+ * @param secret     The secret data.
+ * @param secretSize The length of @p secret, in bytes.
+ * @param seed64     The 64-bit seed to alter the hash result predictably.
+ *
+ * @return @ref XXH_OK on success.
+ * @return @ref XXH_ERROR on failure.
+ *
+ * @see XXH3_64bits_withSecretandSeed(). Contract is identical.
+ *
+ * Note: there was a bug in an earlier version of this function (<= v0.8.2)
+ * that would make it generate an incorrect hash value
+ * when @p seed == 0 and @p length < XXH3_MIDSIZE_MAX
+ * and @p secret is different from XXH3_generateSecret_fromSeed().
+ * As stated in the contract, the correct hash result must be
+ * the same as XXH3_128bits_withSeed() when @p length <= XXH3_MIDSIZE_MAX.
+ * Results generated by this older version are wrong, hence not comparable.
+ */
+XXH_PUBLIC_API XXH_errorcode
+XXH3_128bits_reset_withSecretandSeed(XXH_NOESCAPE XXH3_state_t* statePtr,
+                                     XXH_NOESCAPE const void* secret, size_t secretSize,
+                                     XXH64_hash_t seed64);
+
+#endif /* !XXH_NO_STREAM */
+
+#endif  /* !XXH_NO_XXH3 */
+#endif  /* XXH_NO_LONG_LONG */
+#if defined(XXH_INLINE_ALL) || defined(XXH_PRIVATE_API)
+#  define XXH_IMPLEMENTATION
+#endif
+
+#endif  /* defined(XXH_STATIC_LINKING_ONLY) && !defined(XXHASH_H_STATIC_13879238742) */
+
+
+/* ======================================================================== */
+/* ======================================================================== */
+/* ======================================================================== */
+
+
+/*-**********************************************************************
+ * xxHash implementation
+ *-**********************************************************************
+ * xxHash's implementation used to be hosted inside xxhash.c.
+ *
+ * However, inlining requires implementation to be visible to the compiler,
+ * hence be included alongside the header.
+ * Previously, implementation was hosted inside xxhash.c,
+ * which was then #included when inlining was activated.
+ * This construction created issues with a few build and install systems,
+ * as it required xxhash.c to be stored in /include directory.
+ *
+ * xxHash implementation is now directly integrated within xxhash.h.
+ * As a consequence, xxhash.c is no longer needed in /include.
+ *
+ * xxhash.c is still available and is still useful.
+ * In a "normal" setup, when xxhash is not inlined,
+ * xxhash.h only exposes the prototypes and public symbols,
+ * while xxhash.c can be built into an object file xxhash.o
+ * which can then be linked into the final binary.
+ ************************************************************************/
+
+#if ( defined(XXH_INLINE_ALL) || defined(XXH_PRIVATE_API) \
+   || defined(XXH_IMPLEMENTATION) ) && !defined(XXH_IMPLEM_13a8737387)
+#  define XXH_IMPLEM_13a8737387
+
+/* *************************************
+*  Tuning parameters
+***************************************/
+
+/*!
+ * @defgroup tuning Tuning parameters
+ * @{
+ *
+ * Various macros to control xxHash's behavior.
+ */
+#ifdef XXH_DOXYGEN
+/*!
+ * @brief Define this to disable 64-bit code.
+ *
+ * Useful if only using the @ref XXH32_family and you have a strict C90 compiler.
+ */
+#  define XXH_NO_LONG_LONG
+#  undef XXH_NO_LONG_LONG /* don't actually */
+/*!
+ * @brief Controls how unaligned memory is accessed.
+ *
+ * By default, access to unaligned memory is controlled by `memcpy()`, which is
+ * safe and portable.
+ *
+ * Unfortunately, on some target/compiler combinations, the generated assembly
+ * is sub-optimal.
+ *
+ * The below switch allow selection of a different access method
+ * in the search for improved performance.
+ *
+ * @par Possible options:
+ *
+ *  - `XXH_FORCE_MEMORY_ACCESS=0` (default): `memcpy`
+ *   @par
+ *     Use `memcpy()`. Safe and portable. Note that most modern compilers will
+ *     eliminate the function call and treat it as an unaligned access.
+ *
+ *  - `XXH_FORCE_MEMORY_ACCESS=1`: `__attribute__((aligned(1)))`
+ *   @par
+ *     Depends on compiler extensions and is therefore not portable.
+ *     This method is safe _if_ your compiler supports it,
+ *     and *generally* as fast or faster than `memcpy`.
+ *
+ *  - `XXH_FORCE_MEMORY_ACCESS=2`: Direct cast
+ *  @par
+ *     Casts directly and dereferences. This method doesn't depend on the
+ *     compiler, but it violates the C standard as it directly dereferences an
+ *     unaligned pointer. It can generate buggy code on targets which do not
+ *     support unaligned memory accesses, but in some circumstances, it's the
+ *     only known way to get the most performance.
+ *
+ *  - `XXH_FORCE_MEMORY_ACCESS=3`: Byteshift
+ *  @par
+ *     Also portable. This can generate the best code on old compilers which don't
+ *     inline small `memcpy()` calls, and it might also be faster on big-endian
+ *     systems which lack a native byteswap instruction. However, some compilers
+ *     will emit literal byteshifts even if the target supports unaligned access.
+ *
+ *
+ * @warning
+ *   Methods 1 and 2 rely on implementation-defined behavior. Use these with
+ *   care, as what works on one compiler/platform/optimization level may cause
+ *   another to read garbage data or even crash.
+ *
+ * See https://fastcompression.blogspot.com/2015/08/accessing-unaligned-memory.html for details.
+ *
+ * Prefer these methods in priority order (0 > 3 > 1 > 2)
+ */
+#  define XXH_FORCE_MEMORY_ACCESS 0
+
+/*!
+ * @def XXH_SIZE_OPT
+ * @brief Controls how much xxHash optimizes for size.
+ *
+ * xxHash, when compiled, tends to result in a rather large binary size. This
+ * is mostly due to heavy usage to forced inlining and constant folding of the
+ * @ref XXH3_family to increase performance.
+ *
+ * However, some developers prefer size over speed. This option can
+ * significantly reduce the size of the generated code. When using the `-Os`
+ * or `-Oz` options on GCC or Clang, this is defined to 1 by default,
+ * otherwise it is defined to 0.
+ *
+ * Most of these size optimizations can be controlled manually.
+ *
+ * This is a number from 0-2.
+ *  - `XXH_SIZE_OPT` == 0: Default. xxHash makes no size optimizations. Speed
+ *    comes first.
+ *  - `XXH_SIZE_OPT` == 1: Default for `-Os` and `-Oz`. xxHash is more
+ *    conservative and disables hacks that increase code size. It implies the
+ *    options @ref XXH_NO_INLINE_HINTS == 1, @ref XXH_FORCE_ALIGN_CHECK == 0,
+ *    and @ref XXH3_NEON_LANES == 8 if they are not already defined.
+ *  - `XXH_SIZE_OPT` == 2: xxHash tries to make itself as small as possible.
+ *    Performance may cry. For example, the single shot functions just use the
+ *    streaming API.
+ */
+#  define XXH_SIZE_OPT 0
+
+/*!
+ * @def XXH_FORCE_ALIGN_CHECK
+ * @brief If defined to non-zero, adds a special path for aligned inputs (XXH32()
+ * and XXH64() only).
+ *
+ * This is an important performance trick for architectures without decent
+ * unaligned memory access performance.
+ *
+ * It checks for input alignment, and when conditions are met, uses a "fast
+ * path" employing direct 32-bit/64-bit reads, resulting in _dramatically
+ * faster_ read speed.
+ *
+ * The check costs one initial branch per hash, which is generally negligible,
+ * but not zero.
+ *
+ * Moreover, it's not useful to generate an additional code path if memory
+ * access uses the same instruction for both aligned and unaligned
+ * addresses (e.g. x86 and aarch64).
+ *
+ * In these cases, the alignment check can be removed by setting this macro to 0.
+ * Then the code will always use unaligned memory access.
+ * Align check is automatically disabled on x86, x64, ARM64, and some ARM chips
+ * which are platforms known to offer good unaligned memory accesses performance.
+ *
+ * It is also disabled by default when @ref XXH_SIZE_OPT >= 1.
+ *
+ * This option does not affect XXH3 (only XXH32 and XXH64).
+ */
+#  define XXH_FORCE_ALIGN_CHECK 0
+
+/*!
+ * @def XXH_NO_INLINE_HINTS
+ * @brief When non-zero, sets all functions to `static`.
+ *
+ * By default, xxHash tries to force the compiler to inline almost all internal
+ * functions.
+ *
+ * This can usually improve performance due to reduced jumping and improved
+ * constant folding, but significantly increases the size of the binary which
+ * might not be favorable.
+ *
+ * Additionally, sometimes the forced inlining can be detrimental to performance,
+ * depending on the architecture.
+ *
+ * XXH_NO_INLINE_HINTS marks all internal functions as static, giving the
+ * compiler full control on whether to inline or not.
+ *
+ * When not optimizing (-O0), using `-fno-inline` with GCC or Clang, or if
+ * @ref XXH_SIZE_OPT >= 1, this will automatically be defined.
+ */
+#  define XXH_NO_INLINE_HINTS 0
+
+/*!
+ * @def XXH3_INLINE_SECRET
+ * @brief Determines whether to inline the XXH3 withSecret code.
+ *
+ * When the secret size is known, the compiler can improve the performance
+ * of XXH3_64bits_withSecret() and XXH3_128bits_withSecret().
+ *
+ * However, if the secret size is not known, it doesn't have any benefit. This
+ * happens when xxHash is compiled into a global symbol. Therefore, if
+ * @ref XXH_INLINE_ALL is *not* defined, this will be defined to 0.
+ *
+ * Additionally, this defaults to 0 on GCC 12+, which has an issue with function pointers
+ * that are *sometimes* force inline on -Og, and it is impossible to automatically
+ * detect this optimization level.
+ */
+#  define XXH3_INLINE_SECRET 0
+
+/*!
+ * @def XXH32_ENDJMP
+ * @brief Whether to use a jump for `XXH32_finalize`.
+ *
+ * For performance, `XXH32_finalize` uses multiple branches in the finalizer.
+ * This is generally preferable for performance,
+ * but depending on exact architecture, a jmp may be preferable.
+ *
+ * This setting is only possibly making a difference for very small inputs.
+ */
+#  define XXH32_ENDJMP 0
+
+/*!
+ * @internal
+ * @brief Redefines old internal names.
+ *
+ * For compatibility with code that uses xxHash's internals before the names
+ * were changed to improve namespacing. There is no other reason to use this.
+ */
+#  define XXH_OLD_NAMES
+#  undef XXH_OLD_NAMES /* don't actually use, it is ugly. */
+
+/*!
+ * @def XXH_NO_STREAM
+ * @brief Disables the streaming API.
+ *
+ * When xxHash is not inlined and the streaming functions are not used, disabling
+ * the streaming functions can improve code size significantly, especially with
+ * the @ref XXH3_family which tends to make constant folded copies of itself.
+ */
+#  define XXH_NO_STREAM
+#  undef XXH_NO_STREAM /* don't actually */
+#endif /* XXH_DOXYGEN */
+/*!
+ * @}
+ */
+
+#ifndef XXH_FORCE_MEMORY_ACCESS   /* can be defined externally, on command line for example */
+   /* prefer __packed__ structures (method 1) for GCC
+    * < ARMv7 with unaligned access (e.g. Raspbian armhf) still uses byte shifting, so we use memcpy
+    * which for some reason does unaligned loads. */
+#  if defined(__GNUC__) && !(defined(__ARM_ARCH) && __ARM_ARCH < 7 && defined(__ARM_FEATURE_UNALIGNED))
+#    define XXH_FORCE_MEMORY_ACCESS 1
+#  endif
+#endif
+
+#ifndef XXH_SIZE_OPT
+   /* default to 1 for -Os or -Oz */
+#  if (defined(__GNUC__) || defined(__clang__)) && defined(__OPTIMIZE_SIZE__)
+#    define XXH_SIZE_OPT 1
+#  else
+#    define XXH_SIZE_OPT 0
+#  endif
+#endif
+
+#ifndef XXH_FORCE_ALIGN_CHECK  /* can be defined externally */
+   /* don't check on sizeopt, x86, aarch64, or arm when unaligned access is available */
+#  if XXH_SIZE_OPT >= 1 || \
+      defined(__i386)  || defined(__x86_64__) || defined(__aarch64__) || defined(__ARM_FEATURE_UNALIGNED) \
+   || defined(_M_IX86) || defined(_M_X64)     || defined(_M_ARM64)    || defined(_M_ARM) /* visual */
+#    define XXH_FORCE_ALIGN_CHECK 0
+#  else
+#    define XXH_FORCE_ALIGN_CHECK 1
+#  endif
+#endif
+
+#ifndef XXH_NO_INLINE_HINTS
+#  if XXH_SIZE_OPT >= 1 || defined(__NO_INLINE__)  /* -O0, -fno-inline */
+#    define XXH_NO_INLINE_HINTS 1
+#  else
+#    define XXH_NO_INLINE_HINTS 0
+#  endif
+#endif
+
+#ifndef XXH3_INLINE_SECRET
+#  if (defined(__GNUC__) && !defined(__clang__) && __GNUC__ >= 12) \
+     || !defined(XXH_INLINE_ALL)
+#    define XXH3_INLINE_SECRET 0
+#  else
+#    define XXH3_INLINE_SECRET 1
+#  endif
+#endif
+
+#ifndef XXH32_ENDJMP
+/* generally preferable for performance */
+#  define XXH32_ENDJMP 0
+#endif
+
+/*!
+ * @defgroup impl Implementation
+ * @{
+ */
+
+
+/* *************************************
+*  Includes & Memory related functions
+***************************************/
+#if defined(XXH_NO_STREAM)
+/* nothing */
+#elif defined(XXH_NO_STDLIB)
+
+/* When requesting to disable any mention of stdlib,
+ * the library loses the ability to invoked malloc / free.
+ * In practice, it means that functions like `XXH*_createState()`
+ * will always fail, and return NULL.
+ * This flag is useful in situations where
+ * xxhash.h is integrated into some kernel, embedded or limited environment
+ * without access to dynamic allocation.
+ */
+
+static XXH_CONSTF void* XXH_malloc(size_t s) { (void)s; return NULL; }
+static void XXH_free(void* p) { (void)p; }
+
+#else
+
+/*
+ * Modify the local functions below should you wish to use
+ * different memory routines for malloc() and free()
+ */
+#include 
+
+/*!
+ * @internal
+ * @brief Modify this function to use a different routine than malloc().
+ */
+static XXH_MALLOCF void* XXH_malloc(size_t s) { return malloc(s); }
+
+/*!
+ * @internal
+ * @brief Modify this function to use a different routine than free().
+ */
+static void XXH_free(void* p) { free(p); }
+
+#endif  /* XXH_NO_STDLIB */
+
+#include 
+
+/*!
+ * @internal
+ * @brief Modify this function to use a different routine than memcpy().
+ */
+static void* XXH_memcpy(void* dest, const void* src, size_t size)
+{
+    return memcpy(dest,src,size);
+}
+
+#include    /* ULLONG_MAX */
+
+
+/* *************************************
+*  Compiler Specific Options
+***************************************/
+#ifdef _MSC_VER /* Visual Studio warning fix */
+#  pragma warning(disable : 4127) /* disable: C4127: conditional expression is constant */
+#endif
+
+#if XXH_NO_INLINE_HINTS  /* disable inlining hints */
+#  if defined(__GNUC__) || defined(__clang__)
+#    define XXH_FORCE_INLINE static __attribute__((__unused__))
+#  else
+#    define XXH_FORCE_INLINE static
+#  endif
+#  define XXH_NO_INLINE static
+/* enable inlining hints */
+#elif defined(__GNUC__) || defined(__clang__)
+#  define XXH_FORCE_INLINE static __inline__ __attribute__((__always_inline__, __unused__))
+#  define XXH_NO_INLINE static __attribute__((__noinline__))
+#elif defined(_MSC_VER)  /* Visual Studio */
+#  define XXH_FORCE_INLINE static __forceinline
+#  define XXH_NO_INLINE static __declspec(noinline)
+#elif defined (__cplusplus) \
+  || (defined (__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L))   /* C99 */
+#  define XXH_FORCE_INLINE static inline
+#  define XXH_NO_INLINE static
+#else
+#  define XXH_FORCE_INLINE static
+#  define XXH_NO_INLINE static
+#endif
+
+#if XXH3_INLINE_SECRET
+#  define XXH3_WITH_SECRET_INLINE XXH_FORCE_INLINE
+#else
+#  define XXH3_WITH_SECRET_INLINE XXH_NO_INLINE
+#endif
+
+
+/* *************************************
+*  Debug
+***************************************/
+/*!
+ * @ingroup tuning
+ * @def XXH_DEBUGLEVEL
+ * @brief Sets the debugging level.
+ *
+ * XXH_DEBUGLEVEL is expected to be defined externally, typically via the
+ * compiler's command line options. The value must be a number.
+ */
+#ifndef XXH_DEBUGLEVEL
+#  ifdef DEBUGLEVEL /* backwards compat */
+#    define XXH_DEBUGLEVEL DEBUGLEVEL
+#  else
+#    define XXH_DEBUGLEVEL 0
+#  endif
+#endif
+
+#if (XXH_DEBUGLEVEL>=1)
+#  include    /* note: can still be disabled with NDEBUG */
+#  define XXH_ASSERT(c)   assert(c)
+#else
+#  if defined(__INTEL_COMPILER)
+#    define XXH_ASSERT(c)   XXH_ASSUME((unsigned char) (c))
+#  else
+#    define XXH_ASSERT(c)   XXH_ASSUME(c)
+#  endif
+#endif
+
+/* note: use after variable declarations */
+#ifndef XXH_STATIC_ASSERT
+#  if defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 201112L)    /* C11 */
+#    define XXH_STATIC_ASSERT_WITH_MESSAGE(c,m) do { _Static_assert((c),m); } while(0)
+#  elif defined(__cplusplus) && (__cplusplus >= 201103L)            /* C++11 */
+#    define XXH_STATIC_ASSERT_WITH_MESSAGE(c,m) do { static_assert((c),m); } while(0)
+#  else
+#    define XXH_STATIC_ASSERT_WITH_MESSAGE(c,m) do { struct xxh_sa { char x[(c) ? 1 : -1]; }; } while(0)
+#  endif
+#  define XXH_STATIC_ASSERT(c) XXH_STATIC_ASSERT_WITH_MESSAGE((c),#c)
+#endif
+
+/*!
+ * @internal
+ * @def XXH_COMPILER_GUARD(var)
+ * @brief Used to prevent unwanted optimizations for @p var.
+ *
+ * It uses an empty GCC inline assembly statement with a register constraint
+ * which forces @p var into a general purpose register (eg eax, ebx, ecx
+ * on x86) and marks it as modified.
+ *
+ * This is used in a few places to avoid unwanted autovectorization (e.g.
+ * XXH32_round()). All vectorization we want is explicit via intrinsics,
+ * and _usually_ isn't wanted elsewhere.
+ *
+ * We also use it to prevent unwanted constant folding for AArch64 in
+ * XXH3_initCustomSecret_scalar().
+ */
+#if defined(__GNUC__) || defined(__clang__)
+#  define XXH_COMPILER_GUARD(var) __asm__("" : "+r" (var))
+#else
+#  define XXH_COMPILER_GUARD(var) ((void)0)
+#endif
+
+/* Specifically for NEON vectors which use the "w" constraint, on
+ * Clang. */
+#if defined(__clang__) && defined(__ARM_ARCH) && !defined(__wasm__)
+#  define XXH_COMPILER_GUARD_CLANG_NEON(var) __asm__("" : "+w" (var))
+#else
+#  define XXH_COMPILER_GUARD_CLANG_NEON(var) ((void)0)
+#endif
+
+/* *************************************
+*  Basic Types
+***************************************/
+#if !defined (__VMS) \
+ && (defined (__cplusplus) \
+ || (defined (__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L) /* C99 */) )
+#   ifdef _AIX
+#     include 
+#   else
+#     include 
+#   endif
+    typedef uint8_t xxh_u8;
+#else
+    typedef unsigned char xxh_u8;
+#endif
+typedef XXH32_hash_t xxh_u32;
+
+#ifdef XXH_OLD_NAMES
+#  warning "XXH_OLD_NAMES is planned to be removed starting v0.9. If the program depends on it, consider moving away from it by employing newer type names directly"
+#  define BYTE xxh_u8
+#  define U8   xxh_u8
+#  define U32  xxh_u32
+#endif
+
+/* ***   Memory access   *** */
+
+/*!
+ * @internal
+ * @fn xxh_u32 XXH_read32(const void* ptr)
+ * @brief Reads an unaligned 32-bit integer from @p ptr in native endianness.
+ *
+ * Affected by @ref XXH_FORCE_MEMORY_ACCESS.
+ *
+ * @param ptr The pointer to read from.
+ * @return The 32-bit native endian integer from the bytes at @p ptr.
+ */
+
+/*!
+ * @internal
+ * @fn xxh_u32 XXH_readLE32(const void* ptr)
+ * @brief Reads an unaligned 32-bit little endian integer from @p ptr.
+ *
+ * Affected by @ref XXH_FORCE_MEMORY_ACCESS.
+ *
+ * @param ptr The pointer to read from.
+ * @return The 32-bit little endian integer from the bytes at @p ptr.
+ */
+
+/*!
+ * @internal
+ * @fn xxh_u32 XXH_readBE32(const void* ptr)
+ * @brief Reads an unaligned 32-bit big endian integer from @p ptr.
+ *
+ * Affected by @ref XXH_FORCE_MEMORY_ACCESS.
+ *
+ * @param ptr The pointer to read from.
+ * @return The 32-bit big endian integer from the bytes at @p ptr.
+ */
+
+/*!
+ * @internal
+ * @fn xxh_u32 XXH_readLE32_align(const void* ptr, XXH_alignment align)
+ * @brief Like @ref XXH_readLE32(), but has an option for aligned reads.
+ *
+ * Affected by @ref XXH_FORCE_MEMORY_ACCESS.
+ * Note that when @ref XXH_FORCE_ALIGN_CHECK == 0, the @p align parameter is
+ * always @ref XXH_alignment::XXH_unaligned.
+ *
+ * @param ptr The pointer to read from.
+ * @param align Whether @p ptr is aligned.
+ * @pre
+ *   If @p align == @ref XXH_alignment::XXH_aligned, @p ptr must be 4 byte
+ *   aligned.
+ * @return The 32-bit little endian integer from the bytes at @p ptr.
+ */
+
+#if (defined(XXH_FORCE_MEMORY_ACCESS) && (XXH_FORCE_MEMORY_ACCESS==3))
+/*
+ * Manual byteshift. Best for old compilers which don't inline memcpy.
+ * We actually directly use XXH_readLE32 and XXH_readBE32.
+ */
+#elif (defined(XXH_FORCE_MEMORY_ACCESS) && (XXH_FORCE_MEMORY_ACCESS==2))
+
+/*
+ * Force direct memory access. Only works on CPU which support unaligned memory
+ * access in hardware.
+ */
+static xxh_u32 XXH_read32(const void* memPtr) { return *(const xxh_u32*) memPtr; }
+
+#elif (defined(XXH_FORCE_MEMORY_ACCESS) && (XXH_FORCE_MEMORY_ACCESS==1))
+
+/*
+ * __attribute__((aligned(1))) is supported by gcc and clang. Originally the
+ * documentation claimed that it only increased the alignment, but actually it
+ * can decrease it on gcc, clang, and icc:
+ * https://gcc.gnu.org/bugzilla/show_bug.cgi?id=69502,
+ * https://gcc.godbolt.org/z/xYez1j67Y.
+ */
+#ifdef XXH_OLD_NAMES
+typedef union { xxh_u32 u32; } __attribute__((__packed__)) unalign;
+#endif
+static xxh_u32 XXH_read32(const void* ptr)
+{
+    typedef __attribute__((__aligned__(1))) xxh_u32 xxh_unalign32;
+    return *((const xxh_unalign32*)ptr);
+}
+
+#else
+
+/*
+ * Portable and safe solution. Generally efficient.
+ * see: https://fastcompression.blogspot.com/2015/08/accessing-unaligned-memory.html
+ */
+static xxh_u32 XXH_read32(const void* memPtr)
+{
+    xxh_u32 val;
+    XXH_memcpy(&val, memPtr, sizeof(val));
+    return val;
+}
+
+#endif   /* XXH_FORCE_DIRECT_MEMORY_ACCESS */
+
+
+/* ***   Endianness   *** */
+
+/*!
+ * @ingroup tuning
+ * @def XXH_CPU_LITTLE_ENDIAN
+ * @brief Whether the target is little endian.
+ *
+ * Defined to 1 if the target is little endian, or 0 if it is big endian.
+ * It can be defined externally, for example on the compiler command line.
+ *
+ * If it is not defined,
+ * a runtime check (which is usually constant folded) is used instead.
+ *
+ * @note
+ *   This is not necessarily defined to an integer constant.
+ *
+ * @see XXH_isLittleEndian() for the runtime check.
+ */
+#ifndef XXH_CPU_LITTLE_ENDIAN
+/*
+ * Try to detect endianness automatically, to avoid the nonstandard behavior
+ * in `XXH_isLittleEndian()`
+ */
+#  if defined(_WIN32) /* Windows is always little endian */ \
+     || defined(__LITTLE_ENDIAN__) \
+     || (defined(__BYTE_ORDER__) && __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__)
+#    define XXH_CPU_LITTLE_ENDIAN 1
+#  elif defined(__BIG_ENDIAN__) \
+     || (defined(__BYTE_ORDER__) && __BYTE_ORDER__ == __ORDER_BIG_ENDIAN__)
+#    define XXH_CPU_LITTLE_ENDIAN 0
+#  else
+/*!
+ * @internal
+ * @brief Runtime check for @ref XXH_CPU_LITTLE_ENDIAN.
+ *
+ * Most compilers will constant fold this.
+ */
+static int XXH_isLittleEndian(void)
+{
+    /*
+     * Portable and well-defined behavior.
+     * Don't use static: it is detrimental to performance.
+     */
+    const union { xxh_u32 u; xxh_u8 c[4]; } one = { 1 };
+    return one.c[0];
+}
+#   define XXH_CPU_LITTLE_ENDIAN   XXH_isLittleEndian()
+#  endif
+#endif
+
+
+
+
+/* ****************************************
+*  Compiler-specific Functions and Macros
+******************************************/
+#define XXH_GCC_VERSION (__GNUC__ * 100 + __GNUC_MINOR__)
+
+#ifdef __has_builtin
+#  define XXH_HAS_BUILTIN(x) __has_builtin(x)
+#else
+#  define XXH_HAS_BUILTIN(x) 0
+#endif
+
+
+
+/*
+ * C23 and future versions have standard "unreachable()".
+ * Once it has been implemented reliably we can add it as an
+ * additional case:
+ *
+ * ```
+ * #if defined(__STDC_VERSION__) && (__STDC_VERSION__ >= XXH_C23_VN)
+ * #  include 
+ * #  ifdef unreachable
+ * #    define XXH_UNREACHABLE() unreachable()
+ * #  endif
+ * #endif
+ * ```
+ *
+ * Note C++23 also has std::unreachable() which can be detected
+ * as follows:
+ * ```
+ * #if defined(__cpp_lib_unreachable) && (__cpp_lib_unreachable >= 202202L)
+ * #  include 
+ * #  define XXH_UNREACHABLE() std::unreachable()
+ * #endif
+ * ```
+ * NB: `__cpp_lib_unreachable` is defined in the `` header.
+ * We don't use that as including `` in `extern "C"` blocks
+ * doesn't work on GCC12
+ */
+
+#if XXH_HAS_BUILTIN(__builtin_unreachable)
+#  define XXH_UNREACHABLE() __builtin_unreachable()
+
+#elif defined(_MSC_VER)
+#  define XXH_UNREACHABLE() __assume(0)
+
+#else
+#  define XXH_UNREACHABLE()
+#endif
+
+#if XXH_HAS_BUILTIN(__builtin_assume)
+#  define XXH_ASSUME(c) __builtin_assume(c)
+#else
+#  define XXH_ASSUME(c) if (!(c)) { XXH_UNREACHABLE(); }
+#endif
+
+/*!
+ * @internal
+ * @def XXH_rotl32(x,r)
+ * @brief 32-bit rotate left.
+ *
+ * @param x The 32-bit integer to be rotated.
+ * @param r The number of bits to rotate.
+ * @pre
+ *   @p r > 0 && @p r < 32
+ * @note
+ *   @p x and @p r may be evaluated multiple times.
+ * @return The rotated result.
+ */
+#if !defined(NO_CLANG_BUILTIN) && XXH_HAS_BUILTIN(__builtin_rotateleft32) \
+                               && XXH_HAS_BUILTIN(__builtin_rotateleft64)
+#  define XXH_rotl32 __builtin_rotateleft32
+#  define XXH_rotl64 __builtin_rotateleft64
+/* Note: although _rotl exists for minGW (GCC under windows), performance seems poor */
+#elif defined(_MSC_VER)
+#  define XXH_rotl32(x,r) _rotl(x,r)
+#  define XXH_rotl64(x,r) _rotl64(x,r)
+#else
+#  define XXH_rotl32(x,r) (((x) << (r)) | ((x) >> (32 - (r))))
+#  define XXH_rotl64(x,r) (((x) << (r)) | ((x) >> (64 - (r))))
+#endif
+
+/*!
+ * @internal
+ * @fn xxh_u32 XXH_swap32(xxh_u32 x)
+ * @brief A 32-bit byteswap.
+ *
+ * @param x The 32-bit integer to byteswap.
+ * @return @p x, byteswapped.
+ */
+#if defined(_MSC_VER)     /* Visual Studio */
+#  define XXH_swap32 _byteswap_ulong
+#elif XXH_GCC_VERSION >= 403
+#  define XXH_swap32 __builtin_bswap32
+#else
+static xxh_u32 XXH_swap32 (xxh_u32 x)
+{
+    return  ((x << 24) & 0xff000000 ) |
+            ((x <<  8) & 0x00ff0000 ) |
+            ((x >>  8) & 0x0000ff00 ) |
+            ((x >> 24) & 0x000000ff );
+}
+#endif
+
+
+/* ***************************
+*  Memory reads
+*****************************/
+
+/*!
+ * @internal
+ * @brief Enum to indicate whether a pointer is aligned.
+ */
+typedef enum {
+    XXH_aligned,  /*!< Aligned */
+    XXH_unaligned /*!< Possibly unaligned */
+} XXH_alignment;
+
+/*
+ * XXH_FORCE_MEMORY_ACCESS==3 is an endian-independent byteshift load.
+ *
+ * This is ideal for older compilers which don't inline memcpy.
+ */
+#if (defined(XXH_FORCE_MEMORY_ACCESS) && (XXH_FORCE_MEMORY_ACCESS==3))
+
+XXH_FORCE_INLINE xxh_u32 XXH_readLE32(const void* memPtr)
+{
+    const xxh_u8* bytePtr = (const xxh_u8 *)memPtr;
+    return bytePtr[0]
+         | ((xxh_u32)bytePtr[1] << 8)
+         | ((xxh_u32)bytePtr[2] << 16)
+         | ((xxh_u32)bytePtr[3] << 24);
+}
+
+XXH_FORCE_INLINE xxh_u32 XXH_readBE32(const void* memPtr)
+{
+    const xxh_u8* bytePtr = (const xxh_u8 *)memPtr;
+    return bytePtr[3]
+         | ((xxh_u32)bytePtr[2] << 8)
+         | ((xxh_u32)bytePtr[1] << 16)
+         | ((xxh_u32)bytePtr[0] << 24);
+}
+
+#else
+XXH_FORCE_INLINE xxh_u32 XXH_readLE32(const void* ptr)
+{
+    return XXH_CPU_LITTLE_ENDIAN ? XXH_read32(ptr) : XXH_swap32(XXH_read32(ptr));
+}
+
+static xxh_u32 XXH_readBE32(const void* ptr)
+{
+    return XXH_CPU_LITTLE_ENDIAN ? XXH_swap32(XXH_read32(ptr)) : XXH_read32(ptr);
+}
+#endif
+
+XXH_FORCE_INLINE xxh_u32
+XXH_readLE32_align(const void* ptr, XXH_alignment align)
+{
+    if (align==XXH_unaligned) {
+        return XXH_readLE32(ptr);
+    } else {
+        return XXH_CPU_LITTLE_ENDIAN ? *(const xxh_u32*)ptr : XXH_swap32(*(const xxh_u32*)ptr);
+    }
+}
+
+
+/* *************************************
+*  Misc
+***************************************/
+/*! @ingroup public */
+XXH_PUBLIC_API unsigned XXH_versionNumber (void) { return XXH_VERSION_NUMBER; }
+
+
+/* *******************************************************************
+*  32-bit hash functions
+*********************************************************************/
+/*!
+ * @}
+ * @defgroup XXH32_impl XXH32 implementation
+ * @ingroup impl
+ *
+ * Details on the XXH32 implementation.
+ * @{
+ */
+ /* #define instead of static const, to be used as initializers */
+#define XXH_PRIME32_1  0x9E3779B1U  /*!< 0b10011110001101110111100110110001 */
+#define XXH_PRIME32_2  0x85EBCA77U  /*!< 0b10000101111010111100101001110111 */
+#define XXH_PRIME32_3  0xC2B2AE3DU  /*!< 0b11000010101100101010111000111101 */
+#define XXH_PRIME32_4  0x27D4EB2FU  /*!< 0b00100111110101001110101100101111 */
+#define XXH_PRIME32_5  0x165667B1U  /*!< 0b00010110010101100110011110110001 */
+
+#ifdef XXH_OLD_NAMES
+#  define PRIME32_1 XXH_PRIME32_1
+#  define PRIME32_2 XXH_PRIME32_2
+#  define PRIME32_3 XXH_PRIME32_3
+#  define PRIME32_4 XXH_PRIME32_4
+#  define PRIME32_5 XXH_PRIME32_5
+#endif
+
+/*!
+ * @internal
+ * @brief Normal stripe processing routine.
+ *
+ * This shuffles the bits so that any bit from @p input impacts several bits in
+ * @p acc.
+ *
+ * @param acc The accumulator lane.
+ * @param input The stripe of input to mix.
+ * @return The mixed accumulator lane.
+ */
+static xxh_u32 XXH32_round(xxh_u32 acc, xxh_u32 input)
+{
+    acc += input * XXH_PRIME32_2;
+    acc  = XXH_rotl32(acc, 13);
+    acc *= XXH_PRIME32_1;
+#if (defined(__SSE4_1__) || defined(__aarch64__) || defined(__wasm_simd128__)) && !defined(XXH_ENABLE_AUTOVECTORIZE)
+    /*
+     * UGLY HACK:
+     * A compiler fence is used to prevent GCC and Clang from
+     * autovectorizing the XXH32 loop (pragmas and attributes don't work for some
+     * reason) without globally disabling SSE4.1.
+     *
+     * The reason we want to avoid vectorization is because despite working on
+     * 4 integers at a time, there are multiple factors slowing XXH32 down on
+     * SSE4:
+     * - There's a ridiculous amount of lag from pmulld (10 cycles of latency on
+     *   newer chips!) making it slightly slower to multiply four integers at
+     *   once compared to four integers independently. Even when pmulld was
+     *   fastest, Sandy/Ivy Bridge, it is still not worth it to go into SSE
+     *   just to multiply unless doing a long operation.
+     *
+     * - Four instructions are required to rotate,
+     *      movqda tmp,  v // not required with VEX encoding
+     *      pslld  tmp, 13 // tmp <<= 13
+     *      psrld  v,   19 // x >>= 19
+     *      por    v,  tmp // x |= tmp
+     *   compared to one for scalar:
+     *      roll   v, 13    // reliably fast across the board
+     *      shldl  v, v, 13 // Sandy Bridge and later prefer this for some reason
+     *
+     * - Instruction level parallelism is actually more beneficial here because
+     *   the SIMD actually serializes this operation: While v1 is rotating, v2
+     *   can load data, while v3 can multiply. SSE forces them to operate
+     *   together.
+     *
+     * This is also enabled on AArch64, as Clang is *very aggressive* in vectorizing
+     * the loop. NEON is only faster on the A53, and with the newer cores, it is less
+     * than half the speed.
+     *
+     * Additionally, this is used on WASM SIMD128 because it JITs to the same
+     * SIMD instructions and has the same issue.
+     */
+    XXH_COMPILER_GUARD(acc);
+#endif
+    return acc;
+}
+
+/*!
+ * @internal
+ * @brief Mixes all bits to finalize the hash.
+ *
+ * The final mix ensures that all input bits have a chance to impact any bit in
+ * the output digest, resulting in an unbiased distribution.
+ *
+ * @param hash The hash to avalanche.
+ * @return The avalanched hash.
+ */
+static xxh_u32 XXH32_avalanche(xxh_u32 hash)
+{
+    hash ^= hash >> 15;
+    hash *= XXH_PRIME32_2;
+    hash ^= hash >> 13;
+    hash *= XXH_PRIME32_3;
+    hash ^= hash >> 16;
+    return hash;
+}
+
+#define XXH_get32bits(p) XXH_readLE32_align(p, align)
+
+/*!
+ * @internal
+ * @brief Processes the last 0-15 bytes of @p ptr.
+ *
+ * There may be up to 15 bytes remaining to consume from the input.
+ * This final stage will digest them to ensure that all input bytes are present
+ * in the final mix.
+ *
+ * @param hash The hash to finalize.
+ * @param ptr The pointer to the remaining input.
+ * @param len The remaining length, modulo 16.
+ * @param align Whether @p ptr is aligned.
+ * @return The finalized hash.
+ * @see XXH64_finalize().
+ */
+static XXH_PUREF xxh_u32
+XXH32_finalize(xxh_u32 hash, const xxh_u8* ptr, size_t len, XXH_alignment align)
+{
+#define XXH_PROCESS1 do {                             \
+    hash += (*ptr++) * XXH_PRIME32_5;                 \
+    hash = XXH_rotl32(hash, 11) * XXH_PRIME32_1;      \
+} while (0)
+
+#define XXH_PROCESS4 do {                             \
+    hash += XXH_get32bits(ptr) * XXH_PRIME32_3;       \
+    ptr += 4;                                         \
+    hash  = XXH_rotl32(hash, 17) * XXH_PRIME32_4;     \
+} while (0)
+
+    if (ptr==NULL) XXH_ASSERT(len == 0);
+
+    /* Compact rerolled version; generally faster */
+    if (!XXH32_ENDJMP) {
+        len &= 15;
+        while (len >= 4) {
+            XXH_PROCESS4;
+            len -= 4;
+        }
+        while (len > 0) {
+            XXH_PROCESS1;
+            --len;
+        }
+        return XXH32_avalanche(hash);
+    } else {
+         switch(len&15) /* or switch(bEnd - p) */ {
+           case 12:      XXH_PROCESS4;
+                         XXH_FALLTHROUGH;  /* fallthrough */
+           case 8:       XXH_PROCESS4;
+                         XXH_FALLTHROUGH;  /* fallthrough */
+           case 4:       XXH_PROCESS4;
+                         return XXH32_avalanche(hash);
+
+           case 13:      XXH_PROCESS4;
+                         XXH_FALLTHROUGH;  /* fallthrough */
+           case 9:       XXH_PROCESS4;
+                         XXH_FALLTHROUGH;  /* fallthrough */
+           case 5:       XXH_PROCESS4;
+                         XXH_PROCESS1;
+                         return XXH32_avalanche(hash);
+
+           case 14:      XXH_PROCESS4;
+                         XXH_FALLTHROUGH;  /* fallthrough */
+           case 10:      XXH_PROCESS4;
+                         XXH_FALLTHROUGH;  /* fallthrough */
+           case 6:       XXH_PROCESS4;
+                         XXH_PROCESS1;
+                         XXH_PROCESS1;
+                         return XXH32_avalanche(hash);
+
+           case 15:      XXH_PROCESS4;
+                         XXH_FALLTHROUGH;  /* fallthrough */
+           case 11:      XXH_PROCESS4;
+                         XXH_FALLTHROUGH;  /* fallthrough */
+           case 7:       XXH_PROCESS4;
+                         XXH_FALLTHROUGH;  /* fallthrough */
+           case 3:       XXH_PROCESS1;
+                         XXH_FALLTHROUGH;  /* fallthrough */
+           case 2:       XXH_PROCESS1;
+                         XXH_FALLTHROUGH;  /* fallthrough */
+           case 1:       XXH_PROCESS1;
+                         XXH_FALLTHROUGH;  /* fallthrough */
+           case 0:       return XXH32_avalanche(hash);
+        }
+        XXH_ASSERT(0);
+        return hash;   /* reaching this point is deemed impossible */
+    }
+}
+
+#ifdef XXH_OLD_NAMES
+#  define PROCESS1 XXH_PROCESS1
+#  define PROCESS4 XXH_PROCESS4
+#else
+#  undef XXH_PROCESS1
+#  undef XXH_PROCESS4
+#endif
+
+/*!
+ * @internal
+ * @brief The implementation for @ref XXH32().
+ *
+ * @param input , len , seed Directly passed from @ref XXH32().
+ * @param align Whether @p input is aligned.
+ * @return The calculated hash.
+ */
+XXH_FORCE_INLINE XXH_PUREF xxh_u32
+XXH32_endian_align(const xxh_u8* input, size_t len, xxh_u32 seed, XXH_alignment align)
+{
+    xxh_u32 h32;
+
+    if (input==NULL) XXH_ASSERT(len == 0);
+
+    if (len>=16) {
+        const xxh_u8* const bEnd = input + len;
+        const xxh_u8* const limit = bEnd - 15;
+        xxh_u32 v1 = seed + XXH_PRIME32_1 + XXH_PRIME32_2;
+        xxh_u32 v2 = seed + XXH_PRIME32_2;
+        xxh_u32 v3 = seed + 0;
+        xxh_u32 v4 = seed - XXH_PRIME32_1;
+
+        do {
+            v1 = XXH32_round(v1, XXH_get32bits(input)); input += 4;
+            v2 = XXH32_round(v2, XXH_get32bits(input)); input += 4;
+            v3 = XXH32_round(v3, XXH_get32bits(input)); input += 4;
+            v4 = XXH32_round(v4, XXH_get32bits(input)); input += 4;
+        } while (input < limit);
+
+        h32 = XXH_rotl32(v1, 1)  + XXH_rotl32(v2, 7)
+            + XXH_rotl32(v3, 12) + XXH_rotl32(v4, 18);
+    } else {
+        h32  = seed + XXH_PRIME32_5;
+    }
+
+    h32 += (xxh_u32)len;
+
+    return XXH32_finalize(h32, input, len&15, align);
+}
+
+/*! @ingroup XXH32_family */
+XXH_PUBLIC_API XXH32_hash_t XXH32 (const void* input, size_t len, XXH32_hash_t seed)
+{
+#if !defined(XXH_NO_STREAM) && XXH_SIZE_OPT >= 2
+    /* Simple version, good for code maintenance, but unfortunately slow for small inputs */
+    XXH32_state_t state;
+    XXH32_reset(&state, seed);
+    XXH32_update(&state, (const xxh_u8*)input, len);
+    return XXH32_digest(&state);
+#else
+    if (XXH_FORCE_ALIGN_CHECK) {
+        if ((((size_t)input) & 3) == 0) {   /* Input is 4-bytes aligned, leverage the speed benefit */
+            return XXH32_endian_align((const xxh_u8*)input, len, seed, XXH_aligned);
+    }   }
+
+    return XXH32_endian_align((const xxh_u8*)input, len, seed, XXH_unaligned);
+#endif
+}
+
+
+
+/*******   Hash streaming   *******/
+#ifndef XXH_NO_STREAM
+/*! @ingroup XXH32_family */
+XXH_PUBLIC_API XXH32_state_t* XXH32_createState(void)
+{
+    return (XXH32_state_t*)XXH_malloc(sizeof(XXH32_state_t));
+}
+/*! @ingroup XXH32_family */
+XXH_PUBLIC_API XXH_errorcode XXH32_freeState(XXH32_state_t* statePtr)
+{
+    XXH_free(statePtr);
+    return XXH_OK;
+}
+
+/*! @ingroup XXH32_family */
+XXH_PUBLIC_API void XXH32_copyState(XXH32_state_t* dstState, const XXH32_state_t* srcState)
+{
+    XXH_memcpy(dstState, srcState, sizeof(*dstState));
+}
+
+/*! @ingroup XXH32_family */
+XXH_PUBLIC_API XXH_errorcode XXH32_reset(XXH32_state_t* statePtr, XXH32_hash_t seed)
+{
+    XXH_ASSERT(statePtr != NULL);
+    memset(statePtr, 0, sizeof(*statePtr));
+    statePtr->v[0] = seed + XXH_PRIME32_1 + XXH_PRIME32_2;
+    statePtr->v[1] = seed + XXH_PRIME32_2;
+    statePtr->v[2] = seed + 0;
+    statePtr->v[3] = seed - XXH_PRIME32_1;
+    return XXH_OK;
+}
+
+
+/*! @ingroup XXH32_family */
+XXH_PUBLIC_API XXH_errorcode
+XXH32_update(XXH32_state_t* state, const void* input, size_t len)
+{
+    if (input==NULL) {
+        XXH_ASSERT(len == 0);
+        return XXH_OK;
+    }
+
+    {   const xxh_u8* p = (const xxh_u8*)input;
+        const xxh_u8* const bEnd = p + len;
+
+        state->total_len_32 += (XXH32_hash_t)len;
+        state->large_len |= (XXH32_hash_t)((len>=16) | (state->total_len_32>=16));
+
+        if (state->memsize + len < 16)  {   /* fill in tmp buffer */
+            XXH_memcpy((xxh_u8*)(state->mem32) + state->memsize, input, len);
+            state->memsize += (XXH32_hash_t)len;
+            return XXH_OK;
+        }
+
+        if (state->memsize) {   /* some data left from previous update */
+            XXH_memcpy((xxh_u8*)(state->mem32) + state->memsize, input, 16-state->memsize);
+            {   const xxh_u32* p32 = state->mem32;
+                state->v[0] = XXH32_round(state->v[0], XXH_readLE32(p32)); p32++;
+                state->v[1] = XXH32_round(state->v[1], XXH_readLE32(p32)); p32++;
+                state->v[2] = XXH32_round(state->v[2], XXH_readLE32(p32)); p32++;
+                state->v[3] = XXH32_round(state->v[3], XXH_readLE32(p32));
+            }
+            p += 16-state->memsize;
+            state->memsize = 0;
+        }
+
+        if (p <= bEnd-16) {
+            const xxh_u8* const limit = bEnd - 16;
+
+            do {
+                state->v[0] = XXH32_round(state->v[0], XXH_readLE32(p)); p+=4;
+                state->v[1] = XXH32_round(state->v[1], XXH_readLE32(p)); p+=4;
+                state->v[2] = XXH32_round(state->v[2], XXH_readLE32(p)); p+=4;
+                state->v[3] = XXH32_round(state->v[3], XXH_readLE32(p)); p+=4;
+            } while (p<=limit);
+
+        }
+
+        if (p < bEnd) {
+            XXH_memcpy(state->mem32, p, (size_t)(bEnd-p));
+            state->memsize = (unsigned)(bEnd-p);
+        }
+    }
+
+    return XXH_OK;
+}
+
+
+/*! @ingroup XXH32_family */
+XXH_PUBLIC_API XXH32_hash_t XXH32_digest(const XXH32_state_t* state)
+{
+    xxh_u32 h32;
+
+    if (state->large_len) {
+        h32 = XXH_rotl32(state->v[0], 1)
+            + XXH_rotl32(state->v[1], 7)
+            + XXH_rotl32(state->v[2], 12)
+            + XXH_rotl32(state->v[3], 18);
+    } else {
+        h32 = state->v[2] /* == seed */ + XXH_PRIME32_5;
+    }
+
+    h32 += state->total_len_32;
+
+    return XXH32_finalize(h32, (const xxh_u8*)state->mem32, state->memsize, XXH_aligned);
+}
+#endif /* !XXH_NO_STREAM */
+
+/*******   Canonical representation   *******/
+
+/*! @ingroup XXH32_family */
+XXH_PUBLIC_API void XXH32_canonicalFromHash(XXH32_canonical_t* dst, XXH32_hash_t hash)
+{
+    XXH_STATIC_ASSERT(sizeof(XXH32_canonical_t) == sizeof(XXH32_hash_t));
+    if (XXH_CPU_LITTLE_ENDIAN) hash = XXH_swap32(hash);
+    XXH_memcpy(dst, &hash, sizeof(*dst));
+}
+/*! @ingroup XXH32_family */
+XXH_PUBLIC_API XXH32_hash_t XXH32_hashFromCanonical(const XXH32_canonical_t* src)
+{
+    return XXH_readBE32(src);
+}
+
+
+#ifndef XXH_NO_LONG_LONG
+
+/* *******************************************************************
+*  64-bit hash functions
+*********************************************************************/
+/*!
+ * @}
+ * @ingroup impl
+ * @{
+ */
+/*******   Memory access   *******/
+
+typedef XXH64_hash_t xxh_u64;
+
+#ifdef XXH_OLD_NAMES
+#  define U64 xxh_u64
+#endif
+
+#if (defined(XXH_FORCE_MEMORY_ACCESS) && (XXH_FORCE_MEMORY_ACCESS==3))
+/*
+ * Manual byteshift. Best for old compilers which don't inline memcpy.
+ * We actually directly use XXH_readLE64 and XXH_readBE64.
+ */
+#elif (defined(XXH_FORCE_MEMORY_ACCESS) && (XXH_FORCE_MEMORY_ACCESS==2))
+
+/* Force direct memory access. Only works on CPU which support unaligned memory access in hardware */
+static xxh_u64 XXH_read64(const void* memPtr)
+{
+    return *(const xxh_u64*) memPtr;
+}
+
+#elif (defined(XXH_FORCE_MEMORY_ACCESS) && (XXH_FORCE_MEMORY_ACCESS==1))
+
+/*
+ * __attribute__((aligned(1))) is supported by gcc and clang. Originally the
+ * documentation claimed that it only increased the alignment, but actually it
+ * can decrease it on gcc, clang, and icc:
+ * https://gcc.gnu.org/bugzilla/show_bug.cgi?id=69502,
+ * https://gcc.godbolt.org/z/xYez1j67Y.
+ */
+#ifdef XXH_OLD_NAMES
+typedef union { xxh_u32 u32; xxh_u64 u64; } __attribute__((__packed__)) unalign64;
+#endif
+static xxh_u64 XXH_read64(const void* ptr)
+{
+    typedef __attribute__((__aligned__(1))) xxh_u64 xxh_unalign64;
+    return *((const xxh_unalign64*)ptr);
+}
+
+#else
+
+/*
+ * Portable and safe solution. Generally efficient.
+ * see: https://fastcompression.blogspot.com/2015/08/accessing-unaligned-memory.html
+ */
+static xxh_u64 XXH_read64(const void* memPtr)
+{
+    xxh_u64 val;
+    XXH_memcpy(&val, memPtr, sizeof(val));
+    return val;
+}
+
+#endif   /* XXH_FORCE_DIRECT_MEMORY_ACCESS */
+
+#if defined(_MSC_VER)     /* Visual Studio */
+#  define XXH_swap64 _byteswap_uint64
+#elif XXH_GCC_VERSION >= 403
+#  define XXH_swap64 __builtin_bswap64
+#else
+static xxh_u64 XXH_swap64(xxh_u64 x)
+{
+    return  ((x << 56) & 0xff00000000000000ULL) |
+            ((x << 40) & 0x00ff000000000000ULL) |
+            ((x << 24) & 0x0000ff0000000000ULL) |
+            ((x << 8)  & 0x000000ff00000000ULL) |
+            ((x >> 8)  & 0x00000000ff000000ULL) |
+            ((x >> 24) & 0x0000000000ff0000ULL) |
+            ((x >> 40) & 0x000000000000ff00ULL) |
+            ((x >> 56) & 0x00000000000000ffULL);
+}
+#endif
+
+
+/* XXH_FORCE_MEMORY_ACCESS==3 is an endian-independent byteshift load. */
+#if (defined(XXH_FORCE_MEMORY_ACCESS) && (XXH_FORCE_MEMORY_ACCESS==3))
+
+XXH_FORCE_INLINE xxh_u64 XXH_readLE64(const void* memPtr)
+{
+    const xxh_u8* bytePtr = (const xxh_u8 *)memPtr;
+    return bytePtr[0]
+         | ((xxh_u64)bytePtr[1] << 8)
+         | ((xxh_u64)bytePtr[2] << 16)
+         | ((xxh_u64)bytePtr[3] << 24)
+         | ((xxh_u64)bytePtr[4] << 32)
+         | ((xxh_u64)bytePtr[5] << 40)
+         | ((xxh_u64)bytePtr[6] << 48)
+         | ((xxh_u64)bytePtr[7] << 56);
+}
+
+XXH_FORCE_INLINE xxh_u64 XXH_readBE64(const void* memPtr)
+{
+    const xxh_u8* bytePtr = (const xxh_u8 *)memPtr;
+    return bytePtr[7]
+         | ((xxh_u64)bytePtr[6] << 8)
+         | ((xxh_u64)bytePtr[5] << 16)
+         | ((xxh_u64)bytePtr[4] << 24)
+         | ((xxh_u64)bytePtr[3] << 32)
+         | ((xxh_u64)bytePtr[2] << 40)
+         | ((xxh_u64)bytePtr[1] << 48)
+         | ((xxh_u64)bytePtr[0] << 56);
+}
+
+#else
+XXH_FORCE_INLINE xxh_u64 XXH_readLE64(const void* ptr)
+{
+    return XXH_CPU_LITTLE_ENDIAN ? XXH_read64(ptr) : XXH_swap64(XXH_read64(ptr));
+}
+
+static xxh_u64 XXH_readBE64(const void* ptr)
+{
+    return XXH_CPU_LITTLE_ENDIAN ? XXH_swap64(XXH_read64(ptr)) : XXH_read64(ptr);
+}
+#endif
+
+XXH_FORCE_INLINE xxh_u64
+XXH_readLE64_align(const void* ptr, XXH_alignment align)
+{
+    if (align==XXH_unaligned)
+        return XXH_readLE64(ptr);
+    else
+        return XXH_CPU_LITTLE_ENDIAN ? *(const xxh_u64*)ptr : XXH_swap64(*(const xxh_u64*)ptr);
+}
+
+
+/*******   xxh64   *******/
+/*!
+ * @}
+ * @defgroup XXH64_impl XXH64 implementation
+ * @ingroup impl
+ *
+ * Details on the XXH64 implementation.
+ * @{
+ */
+/* #define rather that static const, to be used as initializers */
+#define XXH_PRIME64_1  0x9E3779B185EBCA87ULL  /*!< 0b1001111000110111011110011011000110000101111010111100101010000111 */
+#define XXH_PRIME64_2  0xC2B2AE3D27D4EB4FULL  /*!< 0b1100001010110010101011100011110100100111110101001110101101001111 */
+#define XXH_PRIME64_3  0x165667B19E3779F9ULL  /*!< 0b0001011001010110011001111011000110011110001101110111100111111001 */
+#define XXH_PRIME64_4  0x85EBCA77C2B2AE63ULL  /*!< 0b1000010111101011110010100111011111000010101100101010111001100011 */
+#define XXH_PRIME64_5  0x27D4EB2F165667C5ULL  /*!< 0b0010011111010100111010110010111100010110010101100110011111000101 */
+
+#ifdef XXH_OLD_NAMES
+#  define PRIME64_1 XXH_PRIME64_1
+#  define PRIME64_2 XXH_PRIME64_2
+#  define PRIME64_3 XXH_PRIME64_3
+#  define PRIME64_4 XXH_PRIME64_4
+#  define PRIME64_5 XXH_PRIME64_5
+#endif
+
+/*! @copydoc XXH32_round */
+static xxh_u64 XXH64_round(xxh_u64 acc, xxh_u64 input)
+{
+    acc += input * XXH_PRIME64_2;
+    acc  = XXH_rotl64(acc, 31);
+    acc *= XXH_PRIME64_1;
+#if (defined(__AVX512F__)) && !defined(XXH_ENABLE_AUTOVECTORIZE)
+    /*
+     * DISABLE AUTOVECTORIZATION:
+     * A compiler fence is used to prevent GCC and Clang from
+     * autovectorizing the XXH64 loop (pragmas and attributes don't work for some
+     * reason) without globally disabling AVX512.
+     *
+     * Autovectorization of XXH64 tends to be detrimental,
+     * though the exact outcome may change depending on exact cpu and compiler version.
+     * For information, it has been reported as detrimental for Skylake-X,
+     * but possibly beneficial for Zen4.
+     *
+     * The default is to disable auto-vectorization,
+     * but you can select to enable it instead using `XXH_ENABLE_AUTOVECTORIZE` build variable.
+     */
+    XXH_COMPILER_GUARD(acc);
+#endif
+    return acc;
+}
+
+static xxh_u64 XXH64_mergeRound(xxh_u64 acc, xxh_u64 val)
+{
+    val  = XXH64_round(0, val);
+    acc ^= val;
+    acc  = acc * XXH_PRIME64_1 + XXH_PRIME64_4;
+    return acc;
+}
+
+/*! @copydoc XXH32_avalanche */
+static xxh_u64 XXH64_avalanche(xxh_u64 hash)
+{
+    hash ^= hash >> 33;
+    hash *= XXH_PRIME64_2;
+    hash ^= hash >> 29;
+    hash *= XXH_PRIME64_3;
+    hash ^= hash >> 32;
+    return hash;
+}
+
+
+#define XXH_get64bits(p) XXH_readLE64_align(p, align)
+
+/*!
+ * @internal
+ * @brief Processes the last 0-31 bytes of @p ptr.
+ *
+ * There may be up to 31 bytes remaining to consume from the input.
+ * This final stage will digest them to ensure that all input bytes are present
+ * in the final mix.
+ *
+ * @param hash The hash to finalize.
+ * @param ptr The pointer to the remaining input.
+ * @param len The remaining length, modulo 32.
+ * @param align Whether @p ptr is aligned.
+ * @return The finalized hash
+ * @see XXH32_finalize().
+ */
+static XXH_PUREF xxh_u64
+XXH64_finalize(xxh_u64 hash, const xxh_u8* ptr, size_t len, XXH_alignment align)
+{
+    if (ptr==NULL) XXH_ASSERT(len == 0);
+    len &= 31;
+    while (len >= 8) {
+        xxh_u64 const k1 = XXH64_round(0, XXH_get64bits(ptr));
+        ptr += 8;
+        hash ^= k1;
+        hash  = XXH_rotl64(hash,27) * XXH_PRIME64_1 + XXH_PRIME64_4;
+        len -= 8;
+    }
+    if (len >= 4) {
+        hash ^= (xxh_u64)(XXH_get32bits(ptr)) * XXH_PRIME64_1;
+        ptr += 4;
+        hash = XXH_rotl64(hash, 23) * XXH_PRIME64_2 + XXH_PRIME64_3;
+        len -= 4;
+    }
+    while (len > 0) {
+        hash ^= (*ptr++) * XXH_PRIME64_5;
+        hash = XXH_rotl64(hash, 11) * XXH_PRIME64_1;
+        --len;
+    }
+    return  XXH64_avalanche(hash);
+}
+
+#ifdef XXH_OLD_NAMES
+#  define PROCESS1_64 XXH_PROCESS1_64
+#  define PROCESS4_64 XXH_PROCESS4_64
+#  define PROCESS8_64 XXH_PROCESS8_64
+#else
+#  undef XXH_PROCESS1_64
+#  undef XXH_PROCESS4_64
+#  undef XXH_PROCESS8_64
+#endif
+
+/*!
+ * @internal
+ * @brief The implementation for @ref XXH64().
+ *
+ * @param input , len , seed Directly passed from @ref XXH64().
+ * @param align Whether @p input is aligned.
+ * @return The calculated hash.
+ */
+XXH_FORCE_INLINE XXH_PUREF xxh_u64
+XXH64_endian_align(const xxh_u8* input, size_t len, xxh_u64 seed, XXH_alignment align)
+{
+    xxh_u64 h64;
+    if (input==NULL) XXH_ASSERT(len == 0);
+
+    if (len>=32) {
+        const xxh_u8* const bEnd = input + len;
+        const xxh_u8* const limit = bEnd - 31;
+        xxh_u64 v1 = seed + XXH_PRIME64_1 + XXH_PRIME64_2;
+        xxh_u64 v2 = seed + XXH_PRIME64_2;
+        xxh_u64 v3 = seed + 0;
+        xxh_u64 v4 = seed - XXH_PRIME64_1;
+
+        do {
+            v1 = XXH64_round(v1, XXH_get64bits(input)); input+=8;
+            v2 = XXH64_round(v2, XXH_get64bits(input)); input+=8;
+            v3 = XXH64_round(v3, XXH_get64bits(input)); input+=8;
+            v4 = XXH64_round(v4, XXH_get64bits(input)); input+=8;
+        } while (input= 2
+    /* Simple version, good for code maintenance, but unfortunately slow for small inputs */
+    XXH64_state_t state;
+    XXH64_reset(&state, seed);
+    XXH64_update(&state, (const xxh_u8*)input, len);
+    return XXH64_digest(&state);
+#else
+    if (XXH_FORCE_ALIGN_CHECK) {
+        if ((((size_t)input) & 7)==0) {  /* Input is aligned, let's leverage the speed advantage */
+            return XXH64_endian_align((const xxh_u8*)input, len, seed, XXH_aligned);
+    }   }
+
+    return XXH64_endian_align((const xxh_u8*)input, len, seed, XXH_unaligned);
+
+#endif
+}
+
+/*******   Hash Streaming   *******/
+#ifndef XXH_NO_STREAM
+/*! @ingroup XXH64_family*/
+XXH_PUBLIC_API XXH64_state_t* XXH64_createState(void)
+{
+    return (XXH64_state_t*)XXH_malloc(sizeof(XXH64_state_t));
+}
+/*! @ingroup XXH64_family */
+XXH_PUBLIC_API XXH_errorcode XXH64_freeState(XXH64_state_t* statePtr)
+{
+    XXH_free(statePtr);
+    return XXH_OK;
+}
+
+/*! @ingroup XXH64_family */
+XXH_PUBLIC_API void XXH64_copyState(XXH_NOESCAPE XXH64_state_t* dstState, const XXH64_state_t* srcState)
+{
+    XXH_memcpy(dstState, srcState, sizeof(*dstState));
+}
+
+/*! @ingroup XXH64_family */
+XXH_PUBLIC_API XXH_errorcode XXH64_reset(XXH_NOESCAPE XXH64_state_t* statePtr, XXH64_hash_t seed)
+{
+    XXH_ASSERT(statePtr != NULL);
+    memset(statePtr, 0, sizeof(*statePtr));
+    statePtr->v[0] = seed + XXH_PRIME64_1 + XXH_PRIME64_2;
+    statePtr->v[1] = seed + XXH_PRIME64_2;
+    statePtr->v[2] = seed + 0;
+    statePtr->v[3] = seed - XXH_PRIME64_1;
+    return XXH_OK;
+}
+
+/*! @ingroup XXH64_family */
+XXH_PUBLIC_API XXH_errorcode
+XXH64_update (XXH_NOESCAPE XXH64_state_t* state, XXH_NOESCAPE const void* input, size_t len)
+{
+    if (input==NULL) {
+        XXH_ASSERT(len == 0);
+        return XXH_OK;
+    }
+
+    {   const xxh_u8* p = (const xxh_u8*)input;
+        const xxh_u8* const bEnd = p + len;
+
+        state->total_len += len;
+
+        if (state->memsize + len < 32) {  /* fill in tmp buffer */
+            XXH_memcpy(((xxh_u8*)state->mem64) + state->memsize, input, len);
+            state->memsize += (xxh_u32)len;
+            return XXH_OK;
+        }
+
+        if (state->memsize) {   /* tmp buffer is full */
+            XXH_memcpy(((xxh_u8*)state->mem64) + state->memsize, input, 32-state->memsize);
+            state->v[0] = XXH64_round(state->v[0], XXH_readLE64(state->mem64+0));
+            state->v[1] = XXH64_round(state->v[1], XXH_readLE64(state->mem64+1));
+            state->v[2] = XXH64_round(state->v[2], XXH_readLE64(state->mem64+2));
+            state->v[3] = XXH64_round(state->v[3], XXH_readLE64(state->mem64+3));
+            p += 32 - state->memsize;
+            state->memsize = 0;
+        }
+
+        if (p+32 <= bEnd) {
+            const xxh_u8* const limit = bEnd - 32;
+
+            do {
+                state->v[0] = XXH64_round(state->v[0], XXH_readLE64(p)); p+=8;
+                state->v[1] = XXH64_round(state->v[1], XXH_readLE64(p)); p+=8;
+                state->v[2] = XXH64_round(state->v[2], XXH_readLE64(p)); p+=8;
+                state->v[3] = XXH64_round(state->v[3], XXH_readLE64(p)); p+=8;
+            } while (p<=limit);
+
+        }
+
+        if (p < bEnd) {
+            XXH_memcpy(state->mem64, p, (size_t)(bEnd-p));
+            state->memsize = (unsigned)(bEnd-p);
+        }
+    }
+
+    return XXH_OK;
+}
+
+
+/*! @ingroup XXH64_family */
+XXH_PUBLIC_API XXH64_hash_t XXH64_digest(XXH_NOESCAPE const XXH64_state_t* state)
+{
+    xxh_u64 h64;
+
+    if (state->total_len >= 32) {
+        h64 = XXH_rotl64(state->v[0], 1) + XXH_rotl64(state->v[1], 7) + XXH_rotl64(state->v[2], 12) + XXH_rotl64(state->v[3], 18);
+        h64 = XXH64_mergeRound(h64, state->v[0]);
+        h64 = XXH64_mergeRound(h64, state->v[1]);
+        h64 = XXH64_mergeRound(h64, state->v[2]);
+        h64 = XXH64_mergeRound(h64, state->v[3]);
+    } else {
+        h64  = state->v[2] /*seed*/ + XXH_PRIME64_5;
+    }
+
+    h64 += (xxh_u64) state->total_len;
+
+    return XXH64_finalize(h64, (const xxh_u8*)state->mem64, (size_t)state->total_len, XXH_aligned);
+}
+#endif /* !XXH_NO_STREAM */
+
+/******* Canonical representation   *******/
+
+/*! @ingroup XXH64_family */
+XXH_PUBLIC_API void XXH64_canonicalFromHash(XXH_NOESCAPE XXH64_canonical_t* dst, XXH64_hash_t hash)
+{
+    XXH_STATIC_ASSERT(sizeof(XXH64_canonical_t) == sizeof(XXH64_hash_t));
+    if (XXH_CPU_LITTLE_ENDIAN) hash = XXH_swap64(hash);
+    XXH_memcpy(dst, &hash, sizeof(*dst));
+}
+
+/*! @ingroup XXH64_family */
+XXH_PUBLIC_API XXH64_hash_t XXH64_hashFromCanonical(XXH_NOESCAPE const XXH64_canonical_t* src)
+{
+    return XXH_readBE64(src);
+}
+
+#ifndef XXH_NO_XXH3
+
+/* *********************************************************************
+*  XXH3
+*  New generation hash designed for speed on small keys and vectorization
+************************************************************************ */
+/*!
+ * @}
+ * @defgroup XXH3_impl XXH3 implementation
+ * @ingroup impl
+ * @{
+ */
+
+/* ===   Compiler specifics   === */
+
+#if ((defined(sun) || defined(__sun)) && __cplusplus) /* Solaris includes __STDC_VERSION__ with C++. Tested with GCC 5.5 */
+#  define XXH_RESTRICT   /* disable */
+#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L   /* >= C99 */
+#  define XXH_RESTRICT   restrict
+#elif (defined (__GNUC__) && ((__GNUC__ > 3) || (__GNUC__ == 3 && __GNUC_MINOR__ >= 1))) \
+   || (defined (__clang__)) \
+   || (defined (_MSC_VER) && (_MSC_VER >= 1400)) \
+   || (defined (__INTEL_COMPILER) && (__INTEL_COMPILER >= 1300))
+/*
+ * There are a LOT more compilers that recognize __restrict but this
+ * covers the major ones.
+ */
+#  define XXH_RESTRICT   __restrict
+#else
+#  define XXH_RESTRICT   /* disable */
+#endif
+
+#if (defined(__GNUC__) && (__GNUC__ >= 3))  \
+  || (defined(__INTEL_COMPILER) && (__INTEL_COMPILER >= 800)) \
+  || defined(__clang__)
+#    define XXH_likely(x) __builtin_expect(x, 1)
+#    define XXH_unlikely(x) __builtin_expect(x, 0)
+#else
+#    define XXH_likely(x) (x)
+#    define XXH_unlikely(x) (x)
+#endif
+
+#ifndef XXH_HAS_INCLUDE
+#  ifdef __has_include
+/*
+ * Not defined as XXH_HAS_INCLUDE(x) (function-like) because
+ * this causes segfaults in Apple Clang 4.2 (on Mac OS X 10.7 Lion)
+ */
+#    define XXH_HAS_INCLUDE __has_include
+#  else
+#    define XXH_HAS_INCLUDE(x) 0
+#  endif
+#endif
+
+#if defined(__GNUC__) || defined(__clang__)
+#  if defined(__ARM_FEATURE_SVE)
+#    include 
+#  endif
+#  if defined(__ARM_NEON__) || defined(__ARM_NEON) \
+   || (defined(_M_ARM) && _M_ARM >= 7) \
+   || defined(_M_ARM64) || defined(_M_ARM64EC) \
+   || (defined(__wasm_simd128__) && XXH_HAS_INCLUDE()) /* WASM SIMD128 via SIMDe */
+#    define inline __inline__  /* circumvent a clang bug */
+#    include 
+#    undef inline
+#  elif defined(__AVX2__)
+#    include 
+#  elif defined(__SSE2__)
+#    include 
+#  endif
+#endif
+
+#if defined(_MSC_VER)
+#  include 
+#endif
+
+/*
+ * One goal of XXH3 is to make it fast on both 32-bit and 64-bit, while
+ * remaining a true 64-bit/128-bit hash function.
+ *
+ * This is done by prioritizing a subset of 64-bit operations that can be
+ * emulated without too many steps on the average 32-bit machine.
+ *
+ * For example, these two lines seem similar, and run equally fast on 64-bit:
+ *
+ *   xxh_u64 x;
+ *   x ^= (x >> 47); // good
+ *   x ^= (x >> 13); // bad
+ *
+ * However, to a 32-bit machine, there is a major difference.
+ *
+ * x ^= (x >> 47) looks like this:
+ *
+ *   x.lo ^= (x.hi >> (47 - 32));
+ *
+ * while x ^= (x >> 13) looks like this:
+ *
+ *   // note: funnel shifts are not usually cheap.
+ *   x.lo ^= (x.lo >> 13) | (x.hi << (32 - 13));
+ *   x.hi ^= (x.hi >> 13);
+ *
+ * The first one is significantly faster than the second, simply because the
+ * shift is larger than 32. This means:
+ *  - All the bits we need are in the upper 32 bits, so we can ignore the lower
+ *    32 bits in the shift.
+ *  - The shift result will always fit in the lower 32 bits, and therefore,
+ *    we can ignore the upper 32 bits in the xor.
+ *
+ * Thanks to this optimization, XXH3 only requires these features to be efficient:
+ *
+ *  - Usable unaligned access
+ *  - A 32-bit or 64-bit ALU
+ *      - If 32-bit, a decent ADC instruction
+ *  - A 32 or 64-bit multiply with a 64-bit result
+ *  - For the 128-bit variant, a decent byteswap helps short inputs.
+ *
+ * The first two are already required by XXH32, and almost all 32-bit and 64-bit
+ * platforms which can run XXH32 can run XXH3 efficiently.
+ *
+ * Thumb-1, the classic 16-bit only subset of ARM's instruction set, is one
+ * notable exception.
+ *
+ * First of all, Thumb-1 lacks support for the UMULL instruction which
+ * performs the important long multiply. This means numerous __aeabi_lmul
+ * calls.
+ *
+ * Second of all, the 8 functional registers are just not enough.
+ * Setup for __aeabi_lmul, byteshift loads, pointers, and all arithmetic need
+ * Lo registers, and this shuffling results in thousands more MOVs than A32.
+ *
+ * A32 and T32 don't have this limitation. They can access all 14 registers,
+ * do a 32->64 multiply with UMULL, and the flexible operand allowing free
+ * shifts is helpful, too.
+ *
+ * Therefore, we do a quick sanity check.
+ *
+ * If compiling Thumb-1 for a target which supports ARM instructions, we will
+ * emit a warning, as it is not a "sane" platform to compile for.
+ *
+ * Usually, if this happens, it is because of an accident and you probably need
+ * to specify -march, as you likely meant to compile for a newer architecture.
+ *
+ * Credit: large sections of the vectorial and asm source code paths
+ *         have been contributed by @easyaspi314
+ */
+#if defined(__thumb__) && !defined(__thumb2__) && defined(__ARM_ARCH_ISA_ARM)
+#   warning "XXH3 is highly inefficient without ARM or Thumb-2."
+#endif
+
+/* ==========================================
+ * Vectorization detection
+ * ========================================== */
+
+#ifdef XXH_DOXYGEN
+/*!
+ * @ingroup tuning
+ * @brief Overrides the vectorization implementation chosen for XXH3.
+ *
+ * Can be defined to 0 to disable SIMD or any of the values mentioned in
+ * @ref XXH_VECTOR_TYPE.
+ *
+ * If this is not defined, it uses predefined macros to determine the best
+ * implementation.
+ */
+#  define XXH_VECTOR XXH_SCALAR
+/*!
+ * @ingroup tuning
+ * @brief Possible values for @ref XXH_VECTOR.
+ *
+ * Note that these are actually implemented as macros.
+ *
+ * If this is not defined, it is detected automatically.
+ * internal macro XXH_X86DISPATCH overrides this.
+ */
+enum XXH_VECTOR_TYPE /* fake enum */ {
+    XXH_SCALAR = 0,  /*!< Portable scalar version */
+    XXH_SSE2   = 1,  /*!<
+                      * SSE2 for Pentium 4, Opteron, all x86_64.
+                      *
+                      * @note SSE2 is also guaranteed on Windows 10, macOS, and
+                      * Android x86.
+                      */
+    XXH_AVX2   = 2,  /*!< AVX2 for Haswell and Bulldozer */
+    XXH_AVX512 = 3,  /*!< AVX512 for Skylake and Icelake */
+    XXH_NEON   = 4,  /*!<
+                       * NEON for most ARMv7-A, all AArch64, and WASM SIMD128
+                       * via the SIMDeverywhere polyfill provided with the
+                       * Emscripten SDK.
+                       */
+    XXH_VSX    = 5,  /*!< VSX and ZVector for POWER8/z13 (64-bit) */
+    XXH_SVE    = 6,  /*!< SVE for some ARMv8-A and ARMv9-A */
+};
+/*!
+ * @ingroup tuning
+ * @brief Selects the minimum alignment for XXH3's accumulators.
+ *
+ * When using SIMD, this should match the alignment required for said vector
+ * type, so, for example, 32 for AVX2.
+ *
+ * Default: Auto detected.
+ */
+#  define XXH_ACC_ALIGN 8
+#endif
+
+/* Actual definition */
+#ifndef XXH_DOXYGEN
+#  define XXH_SCALAR 0
+#  define XXH_SSE2   1
+#  define XXH_AVX2   2
+#  define XXH_AVX512 3
+#  define XXH_NEON   4
+#  define XXH_VSX    5
+#  define XXH_SVE    6
+#endif
+
+#ifndef XXH_VECTOR    /* can be defined on command line */
+#  if defined(__ARM_FEATURE_SVE)
+#    define XXH_VECTOR XXH_SVE
+#  elif ( \
+        defined(__ARM_NEON__) || defined(__ARM_NEON) /* gcc */ \
+     || defined(_M_ARM) || defined(_M_ARM64) || defined(_M_ARM64EC) /* msvc */ \
+     || (defined(__wasm_simd128__) && XXH_HAS_INCLUDE()) /* wasm simd128 via SIMDe */ \
+   ) && ( \
+        defined(_WIN32) || defined(__LITTLE_ENDIAN__) /* little endian only */ \
+    || (defined(__BYTE_ORDER__) && __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__) \
+   )
+#    define XXH_VECTOR XXH_NEON
+#  elif defined(__AVX512F__)
+#    define XXH_VECTOR XXH_AVX512
+#  elif defined(__AVX2__)
+#    define XXH_VECTOR XXH_AVX2
+#  elif defined(__SSE2__) || defined(_M_AMD64) || defined(_M_X64) || (defined(_M_IX86_FP) && (_M_IX86_FP == 2))
+#    define XXH_VECTOR XXH_SSE2
+#  elif (defined(__PPC64__) && defined(__POWER8_VECTOR__)) \
+     || (defined(__s390x__) && defined(__VEC__)) \
+     && defined(__GNUC__) /* TODO: IBM XL */
+#    define XXH_VECTOR XXH_VSX
+#  else
+#    define XXH_VECTOR XXH_SCALAR
+#  endif
+#endif
+
+/* __ARM_FEATURE_SVE is only supported by GCC & Clang. */
+#if (XXH_VECTOR == XXH_SVE) && !defined(__ARM_FEATURE_SVE)
+#  ifdef _MSC_VER
+#    pragma warning(once : 4606)
+#  else
+#    warning "__ARM_FEATURE_SVE isn't supported. Use SCALAR instead."
+#  endif
+#  undef XXH_VECTOR
+#  define XXH_VECTOR XXH_SCALAR
+#endif
+
+/*
+ * Controls the alignment of the accumulator,
+ * for compatibility with aligned vector loads, which are usually faster.
+ */
+#ifndef XXH_ACC_ALIGN
+#  if defined(XXH_X86DISPATCH)
+#     define XXH_ACC_ALIGN 64  /* for compatibility with avx512 */
+#  elif XXH_VECTOR == XXH_SCALAR  /* scalar */
+#     define XXH_ACC_ALIGN 8
+#  elif XXH_VECTOR == XXH_SSE2  /* sse2 */
+#     define XXH_ACC_ALIGN 16
+#  elif XXH_VECTOR == XXH_AVX2  /* avx2 */
+#     define XXH_ACC_ALIGN 32
+#  elif XXH_VECTOR == XXH_NEON  /* neon */
+#     define XXH_ACC_ALIGN 16
+#  elif XXH_VECTOR == XXH_VSX   /* vsx */
+#     define XXH_ACC_ALIGN 16
+#  elif XXH_VECTOR == XXH_AVX512  /* avx512 */
+#     define XXH_ACC_ALIGN 64
+#  elif XXH_VECTOR == XXH_SVE   /* sve */
+#     define XXH_ACC_ALIGN 64
+#  endif
+#endif
+
+#if defined(XXH_X86DISPATCH) || XXH_VECTOR == XXH_SSE2 \
+    || XXH_VECTOR == XXH_AVX2 || XXH_VECTOR == XXH_AVX512
+#  define XXH_SEC_ALIGN XXH_ACC_ALIGN
+#elif XXH_VECTOR == XXH_SVE
+#  define XXH_SEC_ALIGN XXH_ACC_ALIGN
+#else
+#  define XXH_SEC_ALIGN 8
+#endif
+
+#if defined(__GNUC__) || defined(__clang__)
+#  define XXH_ALIASING __attribute__((__may_alias__))
+#else
+#  define XXH_ALIASING /* nothing */
+#endif
+
+/*
+ * UGLY HACK:
+ * GCC usually generates the best code with -O3 for xxHash.
+ *
+ * However, when targeting AVX2, it is overzealous in its unrolling resulting
+ * in code roughly 3/4 the speed of Clang.
+ *
+ * There are other issues, such as GCC splitting _mm256_loadu_si256 into
+ * _mm_loadu_si128 + _mm256_inserti128_si256. This is an optimization which
+ * only applies to Sandy and Ivy Bridge... which don't even support AVX2.
+ *
+ * That is why when compiling the AVX2 version, it is recommended to use either
+ *   -O2 -mavx2 -march=haswell
+ * or
+ *   -O2 -mavx2 -mno-avx256-split-unaligned-load
+ * for decent performance, or to use Clang instead.
+ *
+ * Fortunately, we can control the first one with a pragma that forces GCC into
+ * -O2, but the other one we can't control without "failed to inline always
+ * inline function due to target mismatch" warnings.
+ */
+#if XXH_VECTOR == XXH_AVX2 /* AVX2 */ \
+  && defined(__GNUC__) && !defined(__clang__) /* GCC, not Clang */ \
+  && defined(__OPTIMIZE__) && XXH_SIZE_OPT <= 0 /* respect -O0 and -Os */
+#  pragma GCC push_options
+#  pragma GCC optimize("-O2")
+#endif
+
+#if XXH_VECTOR == XXH_NEON
+
+/*
+ * UGLY HACK: While AArch64 GCC on Linux does not seem to care, on macOS, GCC -O3
+ * optimizes out the entire hashLong loop because of the aliasing violation.
+ *
+ * However, GCC is also inefficient at load-store optimization with vld1q/vst1q,
+ * so the only option is to mark it as aliasing.
+ */
+typedef uint64x2_t xxh_aliasing_uint64x2_t XXH_ALIASING;
+
+/*!
+ * @internal
+ * @brief `vld1q_u64` but faster and alignment-safe.
+ *
+ * On AArch64, unaligned access is always safe, but on ARMv7-a, it is only
+ * *conditionally* safe (`vld1` has an alignment bit like `movdq[ua]` in x86).
+ *
+ * GCC for AArch64 sees `vld1q_u8` as an intrinsic instead of a load, so it
+ * prohibits load-store optimizations. Therefore, a direct dereference is used.
+ *
+ * Otherwise, `vld1q_u8` is used with `vreinterpretq_u8_u64` to do a safe
+ * unaligned load.
+ */
+#if defined(__aarch64__) && defined(__GNUC__) && !defined(__clang__)
+XXH_FORCE_INLINE uint64x2_t XXH_vld1q_u64(void const* ptr) /* silence -Wcast-align */
+{
+    return *(xxh_aliasing_uint64x2_t const *)ptr;
+}
+#else
+XXH_FORCE_INLINE uint64x2_t XXH_vld1q_u64(void const* ptr)
+{
+    return vreinterpretq_u64_u8(vld1q_u8((uint8_t const*)ptr));
+}
+#endif
+
+/*!
+ * @internal
+ * @brief `vmlal_u32` on low and high halves of a vector.
+ *
+ * This is a workaround for AArch64 GCC < 11 which implemented arm_neon.h with
+ * inline assembly and were therefore incapable of merging the `vget_{low, high}_u32`
+ * with `vmlal_u32`.
+ */
+#if defined(__aarch64__) && defined(__GNUC__) && !defined(__clang__) && __GNUC__ < 11
+XXH_FORCE_INLINE uint64x2_t
+XXH_vmlal_low_u32(uint64x2_t acc, uint32x4_t lhs, uint32x4_t rhs)
+{
+    /* Inline assembly is the only way */
+    __asm__("umlal   %0.2d, %1.2s, %2.2s" : "+w" (acc) : "w" (lhs), "w" (rhs));
+    return acc;
+}
+XXH_FORCE_INLINE uint64x2_t
+XXH_vmlal_high_u32(uint64x2_t acc, uint32x4_t lhs, uint32x4_t rhs)
+{
+    /* This intrinsic works as expected */
+    return vmlal_high_u32(acc, lhs, rhs);
+}
+#else
+/* Portable intrinsic versions */
+XXH_FORCE_INLINE uint64x2_t
+XXH_vmlal_low_u32(uint64x2_t acc, uint32x4_t lhs, uint32x4_t rhs)
+{
+    return vmlal_u32(acc, vget_low_u32(lhs), vget_low_u32(rhs));
+}
+/*! @copydoc XXH_vmlal_low_u32
+ * Assume the compiler converts this to vmlal_high_u32 on aarch64 */
+XXH_FORCE_INLINE uint64x2_t
+XXH_vmlal_high_u32(uint64x2_t acc, uint32x4_t lhs, uint32x4_t rhs)
+{
+    return vmlal_u32(acc, vget_high_u32(lhs), vget_high_u32(rhs));
+}
+#endif
+
+/*!
+ * @ingroup tuning
+ * @brief Controls the NEON to scalar ratio for XXH3
+ *
+ * This can be set to 2, 4, 6, or 8.
+ *
+ * ARM Cortex CPUs are _very_ sensitive to how their pipelines are used.
+ *
+ * For example, the Cortex-A73 can dispatch 3 micro-ops per cycle, but only 2 of those
+ * can be NEON. If you are only using NEON instructions, you are only using 2/3 of the CPU
+ * bandwidth.
+ *
+ * This is even more noticeable on the more advanced cores like the Cortex-A76 which
+ * can dispatch 8 micro-ops per cycle, but still only 2 NEON micro-ops at once.
+ *
+ * Therefore, to make the most out of the pipeline, it is beneficial to run 6 NEON lanes
+ * and 2 scalar lanes, which is chosen by default.
+ *
+ * This does not apply to Apple processors or 32-bit processors, which run better with
+ * full NEON. These will default to 8. Additionally, size-optimized builds run 8 lanes.
+ *
+ * This change benefits CPUs with large micro-op buffers without negatively affecting
+ * most other CPUs:
+ *
+ *  | Chipset               | Dispatch type       | NEON only | 6:2 hybrid | Diff. |
+ *  |:----------------------|:--------------------|----------:|-----------:|------:|
+ *  | Snapdragon 730 (A76)  | 2 NEON/8 micro-ops  |  8.8 GB/s |  10.1 GB/s |  ~16% |
+ *  | Snapdragon 835 (A73)  | 2 NEON/3 micro-ops  |  5.1 GB/s |   5.3 GB/s |   ~5% |
+ *  | Marvell PXA1928 (A53) | In-order dual-issue |  1.9 GB/s |   1.9 GB/s |    0% |
+ *  | Apple M1              | 4 NEON/8 micro-ops  | 37.3 GB/s |  36.1 GB/s |  ~-3% |
+ *
+ * It also seems to fix some bad codegen on GCC, making it almost as fast as clang.
+ *
+ * When using WASM SIMD128, if this is 2 or 6, SIMDe will scalarize 2 of the lanes meaning
+ * it effectively becomes worse 4.
+ *
+ * @see XXH3_accumulate_512_neon()
+ */
+# ifndef XXH3_NEON_LANES
+#  if (defined(__aarch64__) || defined(__arm64__) || defined(_M_ARM64) || defined(_M_ARM64EC)) \
+   && !defined(__APPLE__) && XXH_SIZE_OPT <= 0
+#   define XXH3_NEON_LANES 6
+#  else
+#   define XXH3_NEON_LANES XXH_ACC_NB
+#  endif
+# endif
+#endif  /* XXH_VECTOR == XXH_NEON */
+
+/*
+ * VSX and Z Vector helpers.
+ *
+ * This is very messy, and any pull requests to clean this up are welcome.
+ *
+ * There are a lot of problems with supporting VSX and s390x, due to
+ * inconsistent intrinsics, spotty coverage, and multiple endiannesses.
+ */
+#if XXH_VECTOR == XXH_VSX
+/* Annoyingly, these headers _may_ define three macros: `bool`, `vector`,
+ * and `pixel`. This is a problem for obvious reasons.
+ *
+ * These keywords are unnecessary; the spec literally says they are
+ * equivalent to `__bool`, `__vector`, and `__pixel` and may be undef'd
+ * after including the header.
+ *
+ * We use pragma push_macro/pop_macro to keep the namespace clean. */
+#  pragma push_macro("bool")
+#  pragma push_macro("vector")
+#  pragma push_macro("pixel")
+/* silence potential macro redefined warnings */
+#  undef bool
+#  undef vector
+#  undef pixel
+
+#  if defined(__s390x__)
+#    include 
+#  else
+#    include 
+#  endif
+
+/* Restore the original macro values, if applicable. */
+#  pragma pop_macro("pixel")
+#  pragma pop_macro("vector")
+#  pragma pop_macro("bool")
+
+typedef __vector unsigned long long xxh_u64x2;
+typedef __vector unsigned char xxh_u8x16;
+typedef __vector unsigned xxh_u32x4;
+
+/*
+ * UGLY HACK: Similar to aarch64 macOS GCC, s390x GCC has the same aliasing issue.
+ */
+typedef xxh_u64x2 xxh_aliasing_u64x2 XXH_ALIASING;
+
+# ifndef XXH_VSX_BE
+#  if defined(__BIG_ENDIAN__) \
+  || (defined(__BYTE_ORDER__) && __BYTE_ORDER__ == __ORDER_BIG_ENDIAN__)
+#    define XXH_VSX_BE 1
+#  elif defined(__VEC_ELEMENT_REG_ORDER__) && __VEC_ELEMENT_REG_ORDER__ == __ORDER_BIG_ENDIAN__
+#    warning "-maltivec=be is not recommended. Please use native endianness."
+#    define XXH_VSX_BE 1
+#  else
+#    define XXH_VSX_BE 0
+#  endif
+# endif /* !defined(XXH_VSX_BE) */
+
+# if XXH_VSX_BE
+#  if defined(__POWER9_VECTOR__) || (defined(__clang__) && defined(__s390x__))
+#    define XXH_vec_revb vec_revb
+#  else
+/*!
+ * A polyfill for POWER9's vec_revb().
+ */
+XXH_FORCE_INLINE xxh_u64x2 XXH_vec_revb(xxh_u64x2 val)
+{
+    xxh_u8x16 const vByteSwap = { 0x07, 0x06, 0x05, 0x04, 0x03, 0x02, 0x01, 0x00,
+                                  0x0F, 0x0E, 0x0D, 0x0C, 0x0B, 0x0A, 0x09, 0x08 };
+    return vec_perm(val, val, vByteSwap);
+}
+#  endif
+# endif /* XXH_VSX_BE */
+
+/*!
+ * Performs an unaligned vector load and byte swaps it on big endian.
+ */
+XXH_FORCE_INLINE xxh_u64x2 XXH_vec_loadu(const void *ptr)
+{
+    xxh_u64x2 ret;
+    XXH_memcpy(&ret, ptr, sizeof(xxh_u64x2));
+# if XXH_VSX_BE
+    ret = XXH_vec_revb(ret);
+# endif
+    return ret;
+}
+
+/*
+ * vec_mulo and vec_mule are very problematic intrinsics on PowerPC
+ *
+ * These intrinsics weren't added until GCC 8, despite existing for a while,
+ * and they are endian dependent. Also, their meaning swap depending on version.
+ * */
+# if defined(__s390x__)
+ /* s390x is always big endian, no issue on this platform */
+#  define XXH_vec_mulo vec_mulo
+#  define XXH_vec_mule vec_mule
+# elif defined(__clang__) && XXH_HAS_BUILTIN(__builtin_altivec_vmuleuw) && !defined(__ibmxl__)
+/* Clang has a better way to control this, we can just use the builtin which doesn't swap. */
+ /* The IBM XL Compiler (which defined __clang__) only implements the vec_* operations */
+#  define XXH_vec_mulo __builtin_altivec_vmulouw
+#  define XXH_vec_mule __builtin_altivec_vmuleuw
+# else
+/* gcc needs inline assembly */
+/* Adapted from https://github.com/google/highwayhash/blob/master/highwayhash/hh_vsx.h. */
+XXH_FORCE_INLINE xxh_u64x2 XXH_vec_mulo(xxh_u32x4 a, xxh_u32x4 b)
+{
+    xxh_u64x2 result;
+    __asm__("vmulouw %0, %1, %2" : "=v" (result) : "v" (a), "v" (b));
+    return result;
+}
+XXH_FORCE_INLINE xxh_u64x2 XXH_vec_mule(xxh_u32x4 a, xxh_u32x4 b)
+{
+    xxh_u64x2 result;
+    __asm__("vmuleuw %0, %1, %2" : "=v" (result) : "v" (a), "v" (b));
+    return result;
+}
+# endif /* XXH_vec_mulo, XXH_vec_mule */
+#endif /* XXH_VECTOR == XXH_VSX */
+
+#if XXH_VECTOR == XXH_SVE
+#define ACCRND(acc, offset) \
+do { \
+    svuint64_t input_vec = svld1_u64(mask, xinput + offset);         \
+    svuint64_t secret_vec = svld1_u64(mask, xsecret + offset);       \
+    svuint64_t mixed = sveor_u64_x(mask, secret_vec, input_vec);     \
+    svuint64_t swapped = svtbl_u64(input_vec, kSwap);                \
+    svuint64_t mixed_lo = svextw_u64_x(mask, mixed);                 \
+    svuint64_t mixed_hi = svlsr_n_u64_x(mask, mixed, 32);            \
+    svuint64_t mul = svmad_u64_x(mask, mixed_lo, mixed_hi, swapped); \
+    acc = svadd_u64_x(mask, acc, mul);                               \
+} while (0)
+#endif /* XXH_VECTOR == XXH_SVE */
+
+/* prefetch
+ * can be disabled, by declaring XXH_NO_PREFETCH build macro */
+#if defined(XXH_NO_PREFETCH)
+#  define XXH_PREFETCH(ptr)  (void)(ptr)  /* disabled */
+#else
+#  if XXH_SIZE_OPT >= 1
+#    define XXH_PREFETCH(ptr) (void)(ptr)
+#  elif defined(_MSC_VER) && (defined(_M_X64) || defined(_M_IX86))  /* _mm_prefetch() not defined outside of x86/x64 */
+#    include    /* https://msdn.microsoft.com/fr-fr/library/84szxsww(v=vs.90).aspx */
+#    define XXH_PREFETCH(ptr)  _mm_prefetch((const char*)(ptr), _MM_HINT_T0)
+#  elif defined(__GNUC__) && ( (__GNUC__ >= 4) || ( (__GNUC__ == 3) && (__GNUC_MINOR__ >= 1) ) )
+#    define XXH_PREFETCH(ptr)  __builtin_prefetch((ptr), 0 /* rw==read */, 3 /* locality */)
+#  else
+#    define XXH_PREFETCH(ptr) (void)(ptr)  /* disabled */
+#  endif
+#endif  /* XXH_NO_PREFETCH */
+
+
+/* ==========================================
+ * XXH3 default settings
+ * ========================================== */
+
+#define XXH_SECRET_DEFAULT_SIZE 192   /* minimum XXH3_SECRET_SIZE_MIN */
+
+#if (XXH_SECRET_DEFAULT_SIZE < XXH3_SECRET_SIZE_MIN)
+#  error "default keyset is not large enough"
+#endif
+
+/*! Pseudorandom secret taken directly from FARSH. */
+XXH_ALIGN(64) static const xxh_u8 XXH3_kSecret[XXH_SECRET_DEFAULT_SIZE] = {
+    0xb8, 0xfe, 0x6c, 0x39, 0x23, 0xa4, 0x4b, 0xbe, 0x7c, 0x01, 0x81, 0x2c, 0xf7, 0x21, 0xad, 0x1c,
+    0xde, 0xd4, 0x6d, 0xe9, 0x83, 0x90, 0x97, 0xdb, 0x72, 0x40, 0xa4, 0xa4, 0xb7, 0xb3, 0x67, 0x1f,
+    0xcb, 0x79, 0xe6, 0x4e, 0xcc, 0xc0, 0xe5, 0x78, 0x82, 0x5a, 0xd0, 0x7d, 0xcc, 0xff, 0x72, 0x21,
+    0xb8, 0x08, 0x46, 0x74, 0xf7, 0x43, 0x24, 0x8e, 0xe0, 0x35, 0x90, 0xe6, 0x81, 0x3a, 0x26, 0x4c,
+    0x3c, 0x28, 0x52, 0xbb, 0x91, 0xc3, 0x00, 0xcb, 0x88, 0xd0, 0x65, 0x8b, 0x1b, 0x53, 0x2e, 0xa3,
+    0x71, 0x64, 0x48, 0x97, 0xa2, 0x0d, 0xf9, 0x4e, 0x38, 0x19, 0xef, 0x46, 0xa9, 0xde, 0xac, 0xd8,
+    0xa8, 0xfa, 0x76, 0x3f, 0xe3, 0x9c, 0x34, 0x3f, 0xf9, 0xdc, 0xbb, 0xc7, 0xc7, 0x0b, 0x4f, 0x1d,
+    0x8a, 0x51, 0xe0, 0x4b, 0xcd, 0xb4, 0x59, 0x31, 0xc8, 0x9f, 0x7e, 0xc9, 0xd9, 0x78, 0x73, 0x64,
+    0xea, 0xc5, 0xac, 0x83, 0x34, 0xd3, 0xeb, 0xc3, 0xc5, 0x81, 0xa0, 0xff, 0xfa, 0x13, 0x63, 0xeb,
+    0x17, 0x0d, 0xdd, 0x51, 0xb7, 0xf0, 0xda, 0x49, 0xd3, 0x16, 0x55, 0x26, 0x29, 0xd4, 0x68, 0x9e,
+    0x2b, 0x16, 0xbe, 0x58, 0x7d, 0x47, 0xa1, 0xfc, 0x8f, 0xf8, 0xb8, 0xd1, 0x7a, 0xd0, 0x31, 0xce,
+    0x45, 0xcb, 0x3a, 0x8f, 0x95, 0x16, 0x04, 0x28, 0xaf, 0xd7, 0xfb, 0xca, 0xbb, 0x4b, 0x40, 0x7e,
+};
+
+static const xxh_u64 PRIME_MX1 = 0x165667919E3779F9ULL;  /*!< 0b0001011001010110011001111001000110011110001101110111100111111001 */
+static const xxh_u64 PRIME_MX2 = 0x9FB21C651E98DF25ULL;  /*!< 0b1001111110110010000111000110010100011110100110001101111100100101 */
+
+#ifdef XXH_OLD_NAMES
+#  define kSecret XXH3_kSecret
+#endif
+
+#ifdef XXH_DOXYGEN
+/*!
+ * @brief Calculates a 32-bit to 64-bit long multiply.
+ *
+ * Implemented as a macro.
+ *
+ * Wraps `__emulu` on MSVC x86 because it tends to call `__allmul` when it doesn't
+ * need to (but it shouldn't need to anyways, it is about 7 instructions to do
+ * a 64x64 multiply...). Since we know that this will _always_ emit `MULL`, we
+ * use that instead of the normal method.
+ *
+ * If you are compiling for platforms like Thumb-1 and don't have a better option,
+ * you may also want to write your own long multiply routine here.
+ *
+ * @param x, y Numbers to be multiplied
+ * @return 64-bit product of the low 32 bits of @p x and @p y.
+ */
+XXH_FORCE_INLINE xxh_u64
+XXH_mult32to64(xxh_u64 x, xxh_u64 y)
+{
+   return (x & 0xFFFFFFFF) * (y & 0xFFFFFFFF);
+}
+#elif defined(_MSC_VER) && defined(_M_IX86)
+#    define XXH_mult32to64(x, y) __emulu((unsigned)(x), (unsigned)(y))
+#else
+/*
+ * Downcast + upcast is usually better than masking on older compilers like
+ * GCC 4.2 (especially 32-bit ones), all without affecting newer compilers.
+ *
+ * The other method, (x & 0xFFFFFFFF) * (y & 0xFFFFFFFF), will AND both operands
+ * and perform a full 64x64 multiply -- entirely redundant on 32-bit.
+ */
+#    define XXH_mult32to64(x, y) ((xxh_u64)(xxh_u32)(x) * (xxh_u64)(xxh_u32)(y))
+#endif
+
+/*!
+ * @brief Calculates a 64->128-bit long multiply.
+ *
+ * Uses `__uint128_t` and `_umul128` if available, otherwise uses a scalar
+ * version.
+ *
+ * @param lhs , rhs The 64-bit integers to be multiplied
+ * @return The 128-bit result represented in an @ref XXH128_hash_t.
+ */
+static XXH128_hash_t
+XXH_mult64to128(xxh_u64 lhs, xxh_u64 rhs)
+{
+    /*
+     * GCC/Clang __uint128_t method.
+     *
+     * On most 64-bit targets, GCC and Clang define a __uint128_t type.
+     * This is usually the best way as it usually uses a native long 64-bit
+     * multiply, such as MULQ on x86_64 or MUL + UMULH on aarch64.
+     *
+     * Usually.
+     *
+     * Despite being a 32-bit platform, Clang (and emscripten) define this type
+     * despite not having the arithmetic for it. This results in a laggy
+     * compiler builtin call which calculates a full 128-bit multiply.
+     * In that case it is best to use the portable one.
+     * https://github.com/Cyan4973/xxHash/issues/211#issuecomment-515575677
+     */
+#if (defined(__GNUC__) || defined(__clang__)) && !defined(__wasm__) \
+    && defined(__SIZEOF_INT128__) \
+    || (defined(_INTEGRAL_MAX_BITS) && _INTEGRAL_MAX_BITS >= 128)
+
+    __uint128_t const product = (__uint128_t)lhs * (__uint128_t)rhs;
+    XXH128_hash_t r128;
+    r128.low64  = (xxh_u64)(product);
+    r128.high64 = (xxh_u64)(product >> 64);
+    return r128;
+
+    /*
+     * MSVC for x64's _umul128 method.
+     *
+     * xxh_u64 _umul128(xxh_u64 Multiplier, xxh_u64 Multiplicand, xxh_u64 *HighProduct);
+     *
+     * This compiles to single operand MUL on x64.
+     */
+#elif (defined(_M_X64) || defined(_M_IA64)) && !defined(_M_ARM64EC)
+
+#ifndef _MSC_VER
+#   pragma intrinsic(_umul128)
+#endif
+    xxh_u64 product_high;
+    xxh_u64 const product_low = _umul128(lhs, rhs, &product_high);
+    XXH128_hash_t r128;
+    r128.low64  = product_low;
+    r128.high64 = product_high;
+    return r128;
+
+    /*
+     * MSVC for ARM64's __umulh method.
+     *
+     * This compiles to the same MUL + UMULH as GCC/Clang's __uint128_t method.
+     */
+#elif defined(_M_ARM64) || defined(_M_ARM64EC)
+
+#ifndef _MSC_VER
+#   pragma intrinsic(__umulh)
+#endif
+    XXH128_hash_t r128;
+    r128.low64  = lhs * rhs;
+    r128.high64 = __umulh(lhs, rhs);
+    return r128;
+
+#else
+    /*
+     * Portable scalar method. Optimized for 32-bit and 64-bit ALUs.
+     *
+     * This is a fast and simple grade school multiply, which is shown below
+     * with base 10 arithmetic instead of base 0x100000000.
+     *
+     *           9 3 // D2 lhs = 93
+     *         x 7 5 // D2 rhs = 75
+     *     ----------
+     *           1 5 // D2 lo_lo = (93 % 10) * (75 % 10) = 15
+     *         4 5 | // D2 hi_lo = (93 / 10) * (75 % 10) = 45
+     *         2 1 | // D2 lo_hi = (93 % 10) * (75 / 10) = 21
+     *     + 6 3 | | // D2 hi_hi = (93 / 10) * (75 / 10) = 63
+     *     ---------
+     *         2 7 | // D2 cross = (15 / 10) + (45 % 10) + 21 = 27
+     *     + 6 7 | | // D2 upper = (27 / 10) + (45 / 10) + 63 = 67
+     *     ---------
+     *       6 9 7 5 // D4 res = (27 * 10) + (15 % 10) + (67 * 100) = 6975
+     *
+     * The reasons for adding the products like this are:
+     *  1. It avoids manual carry tracking. Just like how
+     *     (9 * 9) + 9 + 9 = 99, the same applies with this for UINT64_MAX.
+     *     This avoids a lot of complexity.
+     *
+     *  2. It hints for, and on Clang, compiles to, the powerful UMAAL
+     *     instruction available in ARM's Digital Signal Processing extension
+     *     in 32-bit ARMv6 and later, which is shown below:
+     *
+     *         void UMAAL(xxh_u32 *RdLo, xxh_u32 *RdHi, xxh_u32 Rn, xxh_u32 Rm)
+     *         {
+     *             xxh_u64 product = (xxh_u64)*RdLo * (xxh_u64)*RdHi + Rn + Rm;
+     *             *RdLo = (xxh_u32)(product & 0xFFFFFFFF);
+     *             *RdHi = (xxh_u32)(product >> 32);
+     *         }
+     *
+     *     This instruction was designed for efficient long multiplication, and
+     *     allows this to be calculated in only 4 instructions at speeds
+     *     comparable to some 64-bit ALUs.
+     *
+     *  3. It isn't terrible on other platforms. Usually this will be a couple
+     *     of 32-bit ADD/ADCs.
+     */
+
+    /* First calculate all of the cross products. */
+    xxh_u64 const lo_lo = XXH_mult32to64(lhs & 0xFFFFFFFF, rhs & 0xFFFFFFFF);
+    xxh_u64 const hi_lo = XXH_mult32to64(lhs >> 32,        rhs & 0xFFFFFFFF);
+    xxh_u64 const lo_hi = XXH_mult32to64(lhs & 0xFFFFFFFF, rhs >> 32);
+    xxh_u64 const hi_hi = XXH_mult32to64(lhs >> 32,        rhs >> 32);
+
+    /* Now add the products together. These will never overflow. */
+    xxh_u64 const cross = (lo_lo >> 32) + (hi_lo & 0xFFFFFFFF) + lo_hi;
+    xxh_u64 const upper = (hi_lo >> 32) + (cross >> 32)        + hi_hi;
+    xxh_u64 const lower = (cross << 32) | (lo_lo & 0xFFFFFFFF);
+
+    XXH128_hash_t r128;
+    r128.low64  = lower;
+    r128.high64 = upper;
+    return r128;
+#endif
+}
+
+/*!
+ * @brief Calculates a 64-bit to 128-bit multiply, then XOR folds it.
+ *
+ * The reason for the separate function is to prevent passing too many structs
+ * around by value. This will hopefully inline the multiply, but we don't force it.
+ *
+ * @param lhs , rhs The 64-bit integers to multiply
+ * @return The low 64 bits of the product XOR'd by the high 64 bits.
+ * @see XXH_mult64to128()
+ */
+static xxh_u64
+XXH3_mul128_fold64(xxh_u64 lhs, xxh_u64 rhs)
+{
+    XXH128_hash_t product = XXH_mult64to128(lhs, rhs);
+    return product.low64 ^ product.high64;
+}
+
+/*! Seems to produce slightly better code on GCC for some reason. */
+XXH_FORCE_INLINE XXH_CONSTF xxh_u64 XXH_xorshift64(xxh_u64 v64, int shift)
+{
+    XXH_ASSERT(0 <= shift && shift < 64);
+    return v64 ^ (v64 >> shift);
+}
+
+/*
+ * This is a fast avalanche stage,
+ * suitable when input bits are already partially mixed
+ */
+static XXH64_hash_t XXH3_avalanche(xxh_u64 h64)
+{
+    h64 = XXH_xorshift64(h64, 37);
+    h64 *= PRIME_MX1;
+    h64 = XXH_xorshift64(h64, 32);
+    return h64;
+}
+
+/*
+ * This is a stronger avalanche,
+ * inspired by Pelle Evensen's rrmxmx
+ * preferable when input has not been previously mixed
+ */
+static XXH64_hash_t XXH3_rrmxmx(xxh_u64 h64, xxh_u64 len)
+{
+    /* this mix is inspired by Pelle Evensen's rrmxmx */
+    h64 ^= XXH_rotl64(h64, 49) ^ XXH_rotl64(h64, 24);
+    h64 *= PRIME_MX2;
+    h64 ^= (h64 >> 35) + len ;
+    h64 *= PRIME_MX2;
+    return XXH_xorshift64(h64, 28);
+}
+
+
+/* ==========================================
+ * Short keys
+ * ==========================================
+ * One of the shortcomings of XXH32 and XXH64 was that their performance was
+ * sub-optimal on short lengths. It used an iterative algorithm which strongly
+ * favored lengths that were a multiple of 4 or 8.
+ *
+ * Instead of iterating over individual inputs, we use a set of single shot
+ * functions which piece together a range of lengths and operate in constant time.
+ *
+ * Additionally, the number of multiplies has been significantly reduced. This
+ * reduces latency, especially when emulating 64-bit multiplies on 32-bit.
+ *
+ * Depending on the platform, this may or may not be faster than XXH32, but it
+ * is almost guaranteed to be faster than XXH64.
+ */
+
+/*
+ * At very short lengths, there isn't enough input to fully hide secrets, or use
+ * the entire secret.
+ *
+ * There is also only a limited amount of mixing we can do before significantly
+ * impacting performance.
+ *
+ * Therefore, we use different sections of the secret and always mix two secret
+ * samples with an XOR. This should have no effect on performance on the
+ * seedless or withSeed variants because everything _should_ be constant folded
+ * by modern compilers.
+ *
+ * The XOR mixing hides individual parts of the secret and increases entropy.
+ *
+ * This adds an extra layer of strength for custom secrets.
+ */
+XXH_FORCE_INLINE XXH_PUREF XXH64_hash_t
+XXH3_len_1to3_64b(const xxh_u8* input, size_t len, const xxh_u8* secret, XXH64_hash_t seed)
+{
+    XXH_ASSERT(input != NULL);
+    XXH_ASSERT(1 <= len && len <= 3);
+    XXH_ASSERT(secret != NULL);
+    /*
+     * len = 1: combined = { input[0], 0x01, input[0], input[0] }
+     * len = 2: combined = { input[1], 0x02, input[0], input[1] }
+     * len = 3: combined = { input[2], 0x03, input[0], input[1] }
+     */
+    {   xxh_u8  const c1 = input[0];
+        xxh_u8  const c2 = input[len >> 1];
+        xxh_u8  const c3 = input[len - 1];
+        xxh_u32 const combined = ((xxh_u32)c1 << 16) | ((xxh_u32)c2  << 24)
+                               | ((xxh_u32)c3 <<  0) | ((xxh_u32)len << 8);
+        xxh_u64 const bitflip = (XXH_readLE32(secret) ^ XXH_readLE32(secret+4)) + seed;
+        xxh_u64 const keyed = (xxh_u64)combined ^ bitflip;
+        return XXH64_avalanche(keyed);
+    }
+}
+
+XXH_FORCE_INLINE XXH_PUREF XXH64_hash_t
+XXH3_len_4to8_64b(const xxh_u8* input, size_t len, const xxh_u8* secret, XXH64_hash_t seed)
+{
+    XXH_ASSERT(input != NULL);
+    XXH_ASSERT(secret != NULL);
+    XXH_ASSERT(4 <= len && len <= 8);
+    seed ^= (xxh_u64)XXH_swap32((xxh_u32)seed) << 32;
+    {   xxh_u32 const input1 = XXH_readLE32(input);
+        xxh_u32 const input2 = XXH_readLE32(input + len - 4);
+        xxh_u64 const bitflip = (XXH_readLE64(secret+8) ^ XXH_readLE64(secret+16)) - seed;
+        xxh_u64 const input64 = input2 + (((xxh_u64)input1) << 32);
+        xxh_u64 const keyed = input64 ^ bitflip;
+        return XXH3_rrmxmx(keyed, len);
+    }
+}
+
+XXH_FORCE_INLINE XXH_PUREF XXH64_hash_t
+XXH3_len_9to16_64b(const xxh_u8* input, size_t len, const xxh_u8* secret, XXH64_hash_t seed)
+{
+    XXH_ASSERT(input != NULL);
+    XXH_ASSERT(secret != NULL);
+    XXH_ASSERT(9 <= len && len <= 16);
+    {   xxh_u64 const bitflip1 = (XXH_readLE64(secret+24) ^ XXH_readLE64(secret+32)) + seed;
+        xxh_u64 const bitflip2 = (XXH_readLE64(secret+40) ^ XXH_readLE64(secret+48)) - seed;
+        xxh_u64 const input_lo = XXH_readLE64(input)           ^ bitflip1;
+        xxh_u64 const input_hi = XXH_readLE64(input + len - 8) ^ bitflip2;
+        xxh_u64 const acc = len
+                          + XXH_swap64(input_lo) + input_hi
+                          + XXH3_mul128_fold64(input_lo, input_hi);
+        return XXH3_avalanche(acc);
+    }
+}
+
+XXH_FORCE_INLINE XXH_PUREF XXH64_hash_t
+XXH3_len_0to16_64b(const xxh_u8* input, size_t len, const xxh_u8* secret, XXH64_hash_t seed)
+{
+    XXH_ASSERT(len <= 16);
+    {   if (XXH_likely(len >  8)) return XXH3_len_9to16_64b(input, len, secret, seed);
+        if (XXH_likely(len >= 4)) return XXH3_len_4to8_64b(input, len, secret, seed);
+        if (len) return XXH3_len_1to3_64b(input, len, secret, seed);
+        return XXH64_avalanche(seed ^ (XXH_readLE64(secret+56) ^ XXH_readLE64(secret+64)));
+    }
+}
+
+/*
+ * DISCLAIMER: There are known *seed-dependent* multicollisions here due to
+ * multiplication by zero, affecting hashes of lengths 17 to 240.
+ *
+ * However, they are very unlikely.
+ *
+ * Keep this in mind when using the unseeded XXH3_64bits() variant: As with all
+ * unseeded non-cryptographic hashes, it does not attempt to defend itself
+ * against specially crafted inputs, only random inputs.
+ *
+ * Compared to classic UMAC where a 1 in 2^31 chance of 4 consecutive bytes
+ * cancelling out the secret is taken an arbitrary number of times (addressed
+ * in XXH3_accumulate_512), this collision is very unlikely with random inputs
+ * and/or proper seeding:
+ *
+ * This only has a 1 in 2^63 chance of 8 consecutive bytes cancelling out, in a
+ * function that is only called up to 16 times per hash with up to 240 bytes of
+ * input.
+ *
+ * This is not too bad for a non-cryptographic hash function, especially with
+ * only 64 bit outputs.
+ *
+ * The 128-bit variant (which trades some speed for strength) is NOT affected
+ * by this, although it is always a good idea to use a proper seed if you care
+ * about strength.
+ */
+XXH_FORCE_INLINE xxh_u64 XXH3_mix16B(const xxh_u8* XXH_RESTRICT input,
+                                     const xxh_u8* XXH_RESTRICT secret, xxh_u64 seed64)
+{
+#if defined(__GNUC__) && !defined(__clang__) /* GCC, not Clang */ \
+  && defined(__i386__) && defined(__SSE2__)  /* x86 + SSE2 */ \
+  && !defined(XXH_ENABLE_AUTOVECTORIZE)      /* Define to disable like XXH32 hack */
+    /*
+     * UGLY HACK:
+     * GCC for x86 tends to autovectorize the 128-bit multiply, resulting in
+     * slower code.
+     *
+     * By forcing seed64 into a register, we disrupt the cost model and
+     * cause it to scalarize. See `XXH32_round()`
+     *
+     * FIXME: Clang's output is still _much_ faster -- On an AMD Ryzen 3600,
+     * XXH3_64bits @ len=240 runs at 4.6 GB/s with Clang 9, but 3.3 GB/s on
+     * GCC 9.2, despite both emitting scalar code.
+     *
+     * GCC generates much better scalar code than Clang for the rest of XXH3,
+     * which is why finding a more optimal codepath is an interest.
+     */
+    XXH_COMPILER_GUARD(seed64);
+#endif
+    {   xxh_u64 const input_lo = XXH_readLE64(input);
+        xxh_u64 const input_hi = XXH_readLE64(input+8);
+        return XXH3_mul128_fold64(
+            input_lo ^ (XXH_readLE64(secret)   + seed64),
+            input_hi ^ (XXH_readLE64(secret+8) - seed64)
+        );
+    }
+}
+
+/* For mid range keys, XXH3 uses a Mum-hash variant. */
+XXH_FORCE_INLINE XXH_PUREF XXH64_hash_t
+XXH3_len_17to128_64b(const xxh_u8* XXH_RESTRICT input, size_t len,
+                     const xxh_u8* XXH_RESTRICT secret, size_t secretSize,
+                     XXH64_hash_t seed)
+{
+    XXH_ASSERT(secretSize >= XXH3_SECRET_SIZE_MIN); (void)secretSize;
+    XXH_ASSERT(16 < len && len <= 128);
+
+    {   xxh_u64 acc = len * XXH_PRIME64_1;
+#if XXH_SIZE_OPT >= 1
+        /* Smaller and cleaner, but slightly slower. */
+        unsigned int i = (unsigned int)(len - 1) / 32;
+        do {
+            acc += XXH3_mix16B(input+16 * i, secret+32*i, seed);
+            acc += XXH3_mix16B(input+len-16*(i+1), secret+32*i+16, seed);
+        } while (i-- != 0);
+#else
+        if (len > 32) {
+            if (len > 64) {
+                if (len > 96) {
+                    acc += XXH3_mix16B(input+48, secret+96, seed);
+                    acc += XXH3_mix16B(input+len-64, secret+112, seed);
+                }
+                acc += XXH3_mix16B(input+32, secret+64, seed);
+                acc += XXH3_mix16B(input+len-48, secret+80, seed);
+            }
+            acc += XXH3_mix16B(input+16, secret+32, seed);
+            acc += XXH3_mix16B(input+len-32, secret+48, seed);
+        }
+        acc += XXH3_mix16B(input+0, secret+0, seed);
+        acc += XXH3_mix16B(input+len-16, secret+16, seed);
+#endif
+        return XXH3_avalanche(acc);
+    }
+}
+
+XXH_NO_INLINE XXH_PUREF XXH64_hash_t
+XXH3_len_129to240_64b(const xxh_u8* XXH_RESTRICT input, size_t len,
+                      const xxh_u8* XXH_RESTRICT secret, size_t secretSize,
+                      XXH64_hash_t seed)
+{
+    XXH_ASSERT(secretSize >= XXH3_SECRET_SIZE_MIN); (void)secretSize;
+    XXH_ASSERT(128 < len && len <= XXH3_MIDSIZE_MAX);
+
+    #define XXH3_MIDSIZE_STARTOFFSET 3
+    #define XXH3_MIDSIZE_LASTOFFSET  17
+
+    {   xxh_u64 acc = len * XXH_PRIME64_1;
+        xxh_u64 acc_end;
+        unsigned int const nbRounds = (unsigned int)len / 16;
+        unsigned int i;
+        XXH_ASSERT(128 < len && len <= XXH3_MIDSIZE_MAX);
+        for (i=0; i<8; i++) {
+            acc += XXH3_mix16B(input+(16*i), secret+(16*i), seed);
+        }
+        /* last bytes */
+        acc_end = XXH3_mix16B(input + len - 16, secret + XXH3_SECRET_SIZE_MIN - XXH3_MIDSIZE_LASTOFFSET, seed);
+        XXH_ASSERT(nbRounds >= 8);
+        acc = XXH3_avalanche(acc);
+#if defined(__clang__)                                /* Clang */ \
+    && (defined(__ARM_NEON) || defined(__ARM_NEON__)) /* NEON */ \
+    && !defined(XXH_ENABLE_AUTOVECTORIZE)             /* Define to disable */
+        /*
+         * UGLY HACK:
+         * Clang for ARMv7-A tries to vectorize this loop, similar to GCC x86.
+         * In everywhere else, it uses scalar code.
+         *
+         * For 64->128-bit multiplies, even if the NEON was 100% optimal, it
+         * would still be slower than UMAAL (see XXH_mult64to128).
+         *
+         * Unfortunately, Clang doesn't handle the long multiplies properly and
+         * converts them to the nonexistent "vmulq_u64" intrinsic, which is then
+         * scalarized into an ugly mess of VMOV.32 instructions.
+         *
+         * This mess is difficult to avoid without turning autovectorization
+         * off completely, but they are usually relatively minor and/or not
+         * worth it to fix.
+         *
+         * This loop is the easiest to fix, as unlike XXH32, this pragma
+         * _actually works_ because it is a loop vectorization instead of an
+         * SLP vectorization.
+         */
+        #pragma clang loop vectorize(disable)
+#endif
+        for (i=8 ; i < nbRounds; i++) {
+            /*
+             * Prevents clang for unrolling the acc loop and interleaving with this one.
+             */
+            XXH_COMPILER_GUARD(acc);
+            acc_end += XXH3_mix16B(input+(16*i), secret+(16*(i-8)) + XXH3_MIDSIZE_STARTOFFSET, seed);
+        }
+        return XXH3_avalanche(acc + acc_end);
+    }
+}
+
+
+/* =======     Long Keys     ======= */
+
+#define XXH_STRIPE_LEN 64
+#define XXH_SECRET_CONSUME_RATE 8   /* nb of secret bytes consumed at each accumulation */
+#define XXH_ACC_NB (XXH_STRIPE_LEN / sizeof(xxh_u64))
+
+#ifdef XXH_OLD_NAMES
+#  define STRIPE_LEN XXH_STRIPE_LEN
+#  define ACC_NB XXH_ACC_NB
+#endif
+
+#ifndef XXH_PREFETCH_DIST
+#  ifdef __clang__
+#    define XXH_PREFETCH_DIST 320
+#  else
+#    if (XXH_VECTOR == XXH_AVX512)
+#      define XXH_PREFETCH_DIST 512
+#    else
+#      define XXH_PREFETCH_DIST 384
+#    endif
+#  endif  /* __clang__ */
+#endif  /* XXH_PREFETCH_DIST */
+
+/*
+ * These macros are to generate an XXH3_accumulate() function.
+ * The two arguments select the name suffix and target attribute.
+ *
+ * The name of this symbol is XXH3_accumulate_() and it calls
+ * XXH3_accumulate_512_().
+ *
+ * It may be useful to hand implement this function if the compiler fails to
+ * optimize the inline function.
+ */
+#define XXH3_ACCUMULATE_TEMPLATE(name)                      \
+void                                                        \
+XXH3_accumulate_##name(xxh_u64* XXH_RESTRICT acc,           \
+                       const xxh_u8* XXH_RESTRICT input,    \
+                       const xxh_u8* XXH_RESTRICT secret,   \
+                       size_t nbStripes)                    \
+{                                                           \
+    size_t n;                                               \
+    for (n = 0; n < nbStripes; n++ ) {                      \
+        const xxh_u8* const in = input + n*XXH_STRIPE_LEN;  \
+        XXH_PREFETCH(in + XXH_PREFETCH_DIST);               \
+        XXH3_accumulate_512_##name(                         \
+                 acc,                                       \
+                 in,                                        \
+                 secret + n*XXH_SECRET_CONSUME_RATE);       \
+    }                                                       \
+}
+
+
+XXH_FORCE_INLINE void XXH_writeLE64(void* dst, xxh_u64 v64)
+{
+    if (!XXH_CPU_LITTLE_ENDIAN) v64 = XXH_swap64(v64);
+    XXH_memcpy(dst, &v64, sizeof(v64));
+}
+
+/* Several intrinsic functions below are supposed to accept __int64 as argument,
+ * as documented in https://software.intel.com/sites/landingpage/IntrinsicsGuide/ .
+ * However, several environments do not define __int64 type,
+ * requiring a workaround.
+ */
+#if !defined (__VMS) \
+  && (defined (__cplusplus) \
+  || (defined (__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L) /* C99 */) )
+    typedef int64_t xxh_i64;
+#else
+    /* the following type must have a width of 64-bit */
+    typedef long long xxh_i64;
+#endif
+
+
+/*
+ * XXH3_accumulate_512 is the tightest loop for long inputs, and it is the most optimized.
+ *
+ * It is a hardened version of UMAC, based off of FARSH's implementation.
+ *
+ * This was chosen because it adapts quite well to 32-bit, 64-bit, and SIMD
+ * implementations, and it is ridiculously fast.
+ *
+ * We harden it by mixing the original input to the accumulators as well as the product.
+ *
+ * This means that in the (relatively likely) case of a multiply by zero, the
+ * original input is preserved.
+ *
+ * On 128-bit inputs, we swap 64-bit pairs when we add the input to improve
+ * cross-pollination, as otherwise the upper and lower halves would be
+ * essentially independent.
+ *
+ * This doesn't matter on 64-bit hashes since they all get merged together in
+ * the end, so we skip the extra step.
+ *
+ * Both XXH3_64bits and XXH3_128bits use this subroutine.
+ */
+
+#if (XXH_VECTOR == XXH_AVX512) \
+     || (defined(XXH_DISPATCH_AVX512) && XXH_DISPATCH_AVX512 != 0)
+
+#ifndef XXH_TARGET_AVX512
+# define XXH_TARGET_AVX512  /* disable attribute target */
+#endif
+
+XXH_FORCE_INLINE XXH_TARGET_AVX512 void
+XXH3_accumulate_512_avx512(void* XXH_RESTRICT acc,
+                     const void* XXH_RESTRICT input,
+                     const void* XXH_RESTRICT secret)
+{
+    __m512i* const xacc = (__m512i *) acc;
+    XXH_ASSERT((((size_t)acc) & 63) == 0);
+    XXH_STATIC_ASSERT(XXH_STRIPE_LEN == sizeof(__m512i));
+
+    {
+        /* data_vec    = input[0]; */
+        __m512i const data_vec    = _mm512_loadu_si512   (input);
+        /* key_vec     = secret[0]; */
+        __m512i const key_vec     = _mm512_loadu_si512   (secret);
+        /* data_key    = data_vec ^ key_vec; */
+        __m512i const data_key    = _mm512_xor_si512     (data_vec, key_vec);
+        /* data_key_lo = data_key >> 32; */
+        __m512i const data_key_lo = _mm512_srli_epi64 (data_key, 32);
+        /* product     = (data_key & 0xffffffff) * (data_key_lo & 0xffffffff); */
+        __m512i const product     = _mm512_mul_epu32     (data_key, data_key_lo);
+        /* xacc[0] += swap(data_vec); */
+        __m512i const data_swap = _mm512_shuffle_epi32(data_vec, (_MM_PERM_ENUM)_MM_SHUFFLE(1, 0, 3, 2));
+        __m512i const sum       = _mm512_add_epi64(*xacc, data_swap);
+        /* xacc[0] += product; */
+        *xacc = _mm512_add_epi64(product, sum);
+    }
+}
+XXH_FORCE_INLINE XXH_TARGET_AVX512 XXH3_ACCUMULATE_TEMPLATE(avx512)
+
+/*
+ * XXH3_scrambleAcc: Scrambles the accumulators to improve mixing.
+ *
+ * Multiplication isn't perfect, as explained by Google in HighwayHash:
+ *
+ *  // Multiplication mixes/scrambles bytes 0-7 of the 64-bit result to
+ *  // varying degrees. In descending order of goodness, bytes
+ *  // 3 4 2 5 1 6 0 7 have quality 228 224 164 160 100 96 36 32.
+ *  // As expected, the upper and lower bytes are much worse.
+ *
+ * Source: https://github.com/google/highwayhash/blob/0aaf66b/highwayhash/hh_avx2.h#L291
+ *
+ * Since our algorithm uses a pseudorandom secret to add some variance into the
+ * mix, we don't need to (or want to) mix as often or as much as HighwayHash does.
+ *
+ * This isn't as tight as XXH3_accumulate, but still written in SIMD to avoid
+ * extraction.
+ *
+ * Both XXH3_64bits and XXH3_128bits use this subroutine.
+ */
+
+XXH_FORCE_INLINE XXH_TARGET_AVX512 void
+XXH3_scrambleAcc_avx512(void* XXH_RESTRICT acc, const void* XXH_RESTRICT secret)
+{
+    XXH_ASSERT((((size_t)acc) & 63) == 0);
+    XXH_STATIC_ASSERT(XXH_STRIPE_LEN == sizeof(__m512i));
+    {   __m512i* const xacc = (__m512i*) acc;
+        const __m512i prime32 = _mm512_set1_epi32((int)XXH_PRIME32_1);
+
+        /* xacc[0] ^= (xacc[0] >> 47) */
+        __m512i const acc_vec     = *xacc;
+        __m512i const shifted     = _mm512_srli_epi64    (acc_vec, 47);
+        /* xacc[0] ^= secret; */
+        __m512i const key_vec     = _mm512_loadu_si512   (secret);
+        __m512i const data_key    = _mm512_ternarylogic_epi32(key_vec, acc_vec, shifted, 0x96 /* key_vec ^ acc_vec ^ shifted */);
+
+        /* xacc[0] *= XXH_PRIME32_1; */
+        __m512i const data_key_hi = _mm512_srli_epi64 (data_key, 32);
+        __m512i const prod_lo     = _mm512_mul_epu32     (data_key, prime32);
+        __m512i const prod_hi     = _mm512_mul_epu32     (data_key_hi, prime32);
+        *xacc = _mm512_add_epi64(prod_lo, _mm512_slli_epi64(prod_hi, 32));
+    }
+}
+
+XXH_FORCE_INLINE XXH_TARGET_AVX512 void
+XXH3_initCustomSecret_avx512(void* XXH_RESTRICT customSecret, xxh_u64 seed64)
+{
+    XXH_STATIC_ASSERT((XXH_SECRET_DEFAULT_SIZE & 63) == 0);
+    XXH_STATIC_ASSERT(XXH_SEC_ALIGN == 64);
+    XXH_ASSERT(((size_t)customSecret & 63) == 0);
+    (void)(&XXH_writeLE64);
+    {   int const nbRounds = XXH_SECRET_DEFAULT_SIZE / sizeof(__m512i);
+        __m512i const seed_pos = _mm512_set1_epi64((xxh_i64)seed64);
+        __m512i const seed     = _mm512_mask_sub_epi64(seed_pos, 0xAA, _mm512_set1_epi8(0), seed_pos);
+
+        const __m512i* const src  = (const __m512i*) ((const void*) XXH3_kSecret);
+              __m512i* const dest = (      __m512i*) customSecret;
+        int i;
+        XXH_ASSERT(((size_t)src & 63) == 0); /* control alignment */
+        XXH_ASSERT(((size_t)dest & 63) == 0);
+        for (i=0; i < nbRounds; ++i) {
+            dest[i] = _mm512_add_epi64(_mm512_load_si512(src + i), seed);
+    }   }
+}
+
+#endif
+
+#if (XXH_VECTOR == XXH_AVX2) \
+    || (defined(XXH_DISPATCH_AVX2) && XXH_DISPATCH_AVX2 != 0)
+
+#ifndef XXH_TARGET_AVX2
+# define XXH_TARGET_AVX2  /* disable attribute target */
+#endif
+
+XXH_FORCE_INLINE XXH_TARGET_AVX2 void
+XXH3_accumulate_512_avx2( void* XXH_RESTRICT acc,
+                    const void* XXH_RESTRICT input,
+                    const void* XXH_RESTRICT secret)
+{
+    XXH_ASSERT((((size_t)acc) & 31) == 0);
+    {   __m256i* const xacc    =       (__m256i *) acc;
+        /* Unaligned. This is mainly for pointer arithmetic, and because
+         * _mm256_loadu_si256 requires  a const __m256i * pointer for some reason. */
+        const         __m256i* const xinput  = (const __m256i *) input;
+        /* Unaligned. This is mainly for pointer arithmetic, and because
+         * _mm256_loadu_si256 requires a const __m256i * pointer for some reason. */
+        const         __m256i* const xsecret = (const __m256i *) secret;
+
+        size_t i;
+        for (i=0; i < XXH_STRIPE_LEN/sizeof(__m256i); i++) {
+            /* data_vec    = xinput[i]; */
+            __m256i const data_vec    = _mm256_loadu_si256    (xinput+i);
+            /* key_vec     = xsecret[i]; */
+            __m256i const key_vec     = _mm256_loadu_si256   (xsecret+i);
+            /* data_key    = data_vec ^ key_vec; */
+            __m256i const data_key    = _mm256_xor_si256     (data_vec, key_vec);
+            /* data_key_lo = data_key >> 32; */
+            __m256i const data_key_lo = _mm256_srli_epi64 (data_key, 32);
+            /* product     = (data_key & 0xffffffff) * (data_key_lo & 0xffffffff); */
+            __m256i const product     = _mm256_mul_epu32     (data_key, data_key_lo);
+            /* xacc[i] += swap(data_vec); */
+            __m256i const data_swap = _mm256_shuffle_epi32(data_vec, _MM_SHUFFLE(1, 0, 3, 2));
+            __m256i const sum       = _mm256_add_epi64(xacc[i], data_swap);
+            /* xacc[i] += product; */
+            xacc[i] = _mm256_add_epi64(product, sum);
+    }   }
+}
+XXH_FORCE_INLINE XXH_TARGET_AVX2 XXH3_ACCUMULATE_TEMPLATE(avx2)
+
+XXH_FORCE_INLINE XXH_TARGET_AVX2 void
+XXH3_scrambleAcc_avx2(void* XXH_RESTRICT acc, const void* XXH_RESTRICT secret)
+{
+    XXH_ASSERT((((size_t)acc) & 31) == 0);
+    {   __m256i* const xacc = (__m256i*) acc;
+        /* Unaligned. This is mainly for pointer arithmetic, and because
+         * _mm256_loadu_si256 requires a const __m256i * pointer for some reason. */
+        const         __m256i* const xsecret = (const __m256i *) secret;
+        const __m256i prime32 = _mm256_set1_epi32((int)XXH_PRIME32_1);
+
+        size_t i;
+        for (i=0; i < XXH_STRIPE_LEN/sizeof(__m256i); i++) {
+            /* xacc[i] ^= (xacc[i] >> 47) */
+            __m256i const acc_vec     = xacc[i];
+            __m256i const shifted     = _mm256_srli_epi64    (acc_vec, 47);
+            __m256i const data_vec    = _mm256_xor_si256     (acc_vec, shifted);
+            /* xacc[i] ^= xsecret; */
+            __m256i const key_vec     = _mm256_loadu_si256   (xsecret+i);
+            __m256i const data_key    = _mm256_xor_si256     (data_vec, key_vec);
+
+            /* xacc[i] *= XXH_PRIME32_1; */
+            __m256i const data_key_hi = _mm256_srli_epi64 (data_key, 32);
+            __m256i const prod_lo     = _mm256_mul_epu32     (data_key, prime32);
+            __m256i const prod_hi     = _mm256_mul_epu32     (data_key_hi, prime32);
+            xacc[i] = _mm256_add_epi64(prod_lo, _mm256_slli_epi64(prod_hi, 32));
+        }
+    }
+}
+
+XXH_FORCE_INLINE XXH_TARGET_AVX2 void XXH3_initCustomSecret_avx2(void* XXH_RESTRICT customSecret, xxh_u64 seed64)
+{
+    XXH_STATIC_ASSERT((XXH_SECRET_DEFAULT_SIZE & 31) == 0);
+    XXH_STATIC_ASSERT((XXH_SECRET_DEFAULT_SIZE / sizeof(__m256i)) == 6);
+    XXH_STATIC_ASSERT(XXH_SEC_ALIGN <= 64);
+    (void)(&XXH_writeLE64);
+    XXH_PREFETCH(customSecret);
+    {   __m256i const seed = _mm256_set_epi64x((xxh_i64)(0U - seed64), (xxh_i64)seed64, (xxh_i64)(0U - seed64), (xxh_i64)seed64);
+
+        const __m256i* const src  = (const __m256i*) ((const void*) XXH3_kSecret);
+              __m256i*       dest = (      __m256i*) customSecret;
+
+#       if defined(__GNUC__) || defined(__clang__)
+        /*
+         * On GCC & Clang, marking 'dest' as modified will cause the compiler:
+         *   - do not extract the secret from sse registers in the internal loop
+         *   - use less common registers, and avoid pushing these reg into stack
+         */
+        XXH_COMPILER_GUARD(dest);
+#       endif
+        XXH_ASSERT(((size_t)src & 31) == 0); /* control alignment */
+        XXH_ASSERT(((size_t)dest & 31) == 0);
+
+        /* GCC -O2 need unroll loop manually */
+        dest[0] = _mm256_add_epi64(_mm256_load_si256(src+0), seed);
+        dest[1] = _mm256_add_epi64(_mm256_load_si256(src+1), seed);
+        dest[2] = _mm256_add_epi64(_mm256_load_si256(src+2), seed);
+        dest[3] = _mm256_add_epi64(_mm256_load_si256(src+3), seed);
+        dest[4] = _mm256_add_epi64(_mm256_load_si256(src+4), seed);
+        dest[5] = _mm256_add_epi64(_mm256_load_si256(src+5), seed);
+    }
+}
+
+#endif
+
+/* x86dispatch always generates SSE2 */
+#if (XXH_VECTOR == XXH_SSE2) || defined(XXH_X86DISPATCH)
+
+#ifndef XXH_TARGET_SSE2
+# define XXH_TARGET_SSE2  /* disable attribute target */
+#endif
+
+XXH_FORCE_INLINE XXH_TARGET_SSE2 void
+XXH3_accumulate_512_sse2( void* XXH_RESTRICT acc,
+                    const void* XXH_RESTRICT input,
+                    const void* XXH_RESTRICT secret)
+{
+    /* SSE2 is just a half-scale version of the AVX2 version. */
+    XXH_ASSERT((((size_t)acc) & 15) == 0);
+    {   __m128i* const xacc    =       (__m128i *) acc;
+        /* Unaligned. This is mainly for pointer arithmetic, and because
+         * _mm_loadu_si128 requires a const __m128i * pointer for some reason. */
+        const         __m128i* const xinput  = (const __m128i *) input;
+        /* Unaligned. This is mainly for pointer arithmetic, and because
+         * _mm_loadu_si128 requires a const __m128i * pointer for some reason. */
+        const         __m128i* const xsecret = (const __m128i *) secret;
+
+        size_t i;
+        for (i=0; i < XXH_STRIPE_LEN/sizeof(__m128i); i++) {
+            /* data_vec    = xinput[i]; */
+            __m128i const data_vec    = _mm_loadu_si128   (xinput+i);
+            /* key_vec     = xsecret[i]; */
+            __m128i const key_vec     = _mm_loadu_si128   (xsecret+i);
+            /* data_key    = data_vec ^ key_vec; */
+            __m128i const data_key    = _mm_xor_si128     (data_vec, key_vec);
+            /* data_key_lo = data_key >> 32; */
+            __m128i const data_key_lo = _mm_shuffle_epi32 (data_key, _MM_SHUFFLE(0, 3, 0, 1));
+            /* product     = (data_key & 0xffffffff) * (data_key_lo & 0xffffffff); */
+            __m128i const product     = _mm_mul_epu32     (data_key, data_key_lo);
+            /* xacc[i] += swap(data_vec); */
+            __m128i const data_swap = _mm_shuffle_epi32(data_vec, _MM_SHUFFLE(1,0,3,2));
+            __m128i const sum       = _mm_add_epi64(xacc[i], data_swap);
+            /* xacc[i] += product; */
+            xacc[i] = _mm_add_epi64(product, sum);
+    }   }
+}
+XXH_FORCE_INLINE XXH_TARGET_SSE2 XXH3_ACCUMULATE_TEMPLATE(sse2)
+
+XXH_FORCE_INLINE XXH_TARGET_SSE2 void
+XXH3_scrambleAcc_sse2(void* XXH_RESTRICT acc, const void* XXH_RESTRICT secret)
+{
+    XXH_ASSERT((((size_t)acc) & 15) == 0);
+    {   __m128i* const xacc = (__m128i*) acc;
+        /* Unaligned. This is mainly for pointer arithmetic, and because
+         * _mm_loadu_si128 requires a const __m128i * pointer for some reason. */
+        const         __m128i* const xsecret = (const __m128i *) secret;
+        const __m128i prime32 = _mm_set1_epi32((int)XXH_PRIME32_1);
+
+        size_t i;
+        for (i=0; i < XXH_STRIPE_LEN/sizeof(__m128i); i++) {
+            /* xacc[i] ^= (xacc[i] >> 47) */
+            __m128i const acc_vec     = xacc[i];
+            __m128i const shifted     = _mm_srli_epi64    (acc_vec, 47);
+            __m128i const data_vec    = _mm_xor_si128     (acc_vec, shifted);
+            /* xacc[i] ^= xsecret[i]; */
+            __m128i const key_vec     = _mm_loadu_si128   (xsecret+i);
+            __m128i const data_key    = _mm_xor_si128     (data_vec, key_vec);
+
+            /* xacc[i] *= XXH_PRIME32_1; */
+            __m128i const data_key_hi = _mm_shuffle_epi32 (data_key, _MM_SHUFFLE(0, 3, 0, 1));
+            __m128i const prod_lo     = _mm_mul_epu32     (data_key, prime32);
+            __m128i const prod_hi     = _mm_mul_epu32     (data_key_hi, prime32);
+            xacc[i] = _mm_add_epi64(prod_lo, _mm_slli_epi64(prod_hi, 32));
+        }
+    }
+}
+
+XXH_FORCE_INLINE XXH_TARGET_SSE2 void XXH3_initCustomSecret_sse2(void* XXH_RESTRICT customSecret, xxh_u64 seed64)
+{
+    XXH_STATIC_ASSERT((XXH_SECRET_DEFAULT_SIZE & 15) == 0);
+    (void)(&XXH_writeLE64);
+    {   int const nbRounds = XXH_SECRET_DEFAULT_SIZE / sizeof(__m128i);
+
+#       if defined(_MSC_VER) && defined(_M_IX86) && _MSC_VER < 1900
+        /* MSVC 32bit mode does not support _mm_set_epi64x before 2015 */
+        XXH_ALIGN(16) const xxh_i64 seed64x2[2] = { (xxh_i64)seed64, (xxh_i64)(0U - seed64) };
+        __m128i const seed = _mm_load_si128((__m128i const*)seed64x2);
+#       else
+        __m128i const seed = _mm_set_epi64x((xxh_i64)(0U - seed64), (xxh_i64)seed64);
+#       endif
+        int i;
+
+        const void* const src16 = XXH3_kSecret;
+        __m128i* dst16 = (__m128i*) customSecret;
+#       if defined(__GNUC__) || defined(__clang__)
+        /*
+         * On GCC & Clang, marking 'dest' as modified will cause the compiler:
+         *   - do not extract the secret from sse registers in the internal loop
+         *   - use less common registers, and avoid pushing these reg into stack
+         */
+        XXH_COMPILER_GUARD(dst16);
+#       endif
+        XXH_ASSERT(((size_t)src16 & 15) == 0); /* control alignment */
+        XXH_ASSERT(((size_t)dst16 & 15) == 0);
+
+        for (i=0; i < nbRounds; ++i) {
+            dst16[i] = _mm_add_epi64(_mm_load_si128((const __m128i *)src16+i), seed);
+    }   }
+}
+
+#endif
+
+#if (XXH_VECTOR == XXH_NEON)
+
+/* forward declarations for the scalar routines */
+XXH_FORCE_INLINE void
+XXH3_scalarRound(void* XXH_RESTRICT acc, void const* XXH_RESTRICT input,
+                 void const* XXH_RESTRICT secret, size_t lane);
+
+XXH_FORCE_INLINE void
+XXH3_scalarScrambleRound(void* XXH_RESTRICT acc,
+                         void const* XXH_RESTRICT secret, size_t lane);
+
+/*!
+ * @internal
+ * @brief The bulk processing loop for NEON and WASM SIMD128.
+ *
+ * The NEON code path is actually partially scalar when running on AArch64. This
+ * is to optimize the pipelining and can have up to 15% speedup depending on the
+ * CPU, and it also mitigates some GCC codegen issues.
+ *
+ * @see XXH3_NEON_LANES for configuring this and details about this optimization.
+ *
+ * NEON's 32-bit to 64-bit long multiply takes a half vector of 32-bit
+ * integers instead of the other platforms which mask full 64-bit vectors,
+ * so the setup is more complicated than just shifting right.
+ *
+ * Additionally, there is an optimization for 4 lanes at once noted below.
+ *
+ * Since, as stated, the most optimal amount of lanes for Cortexes is 6,
+ * there needs to be *three* versions of the accumulate operation used
+ * for the remaining 2 lanes.
+ *
+ * WASM's SIMD128 uses SIMDe's arm_neon.h polyfill because the intrinsics overlap
+ * nearly perfectly.
+ */
+
+XXH_FORCE_INLINE void
+XXH3_accumulate_512_neon( void* XXH_RESTRICT acc,
+                    const void* XXH_RESTRICT input,
+                    const void* XXH_RESTRICT secret)
+{
+    XXH_ASSERT((((size_t)acc) & 15) == 0);
+    XXH_STATIC_ASSERT(XXH3_NEON_LANES > 0 && XXH3_NEON_LANES <= XXH_ACC_NB && XXH3_NEON_LANES % 2 == 0);
+    {   /* GCC for darwin arm64 does not like aliasing here */
+        xxh_aliasing_uint64x2_t* const xacc = (xxh_aliasing_uint64x2_t*) acc;
+        /* We don't use a uint32x4_t pointer because it causes bus errors on ARMv7. */
+        uint8_t const* xinput = (const uint8_t *) input;
+        uint8_t const* xsecret  = (const uint8_t *) secret;
+
+        size_t i;
+#ifdef __wasm_simd128__
+        /*
+         * On WASM SIMD128, Clang emits direct address loads when XXH3_kSecret
+         * is constant propagated, which results in it converting it to this
+         * inside the loop:
+         *
+         *    a = v128.load(XXH3_kSecret +  0 + $secret_offset, offset = 0)
+         *    b = v128.load(XXH3_kSecret + 16 + $secret_offset, offset = 0)
+         *    ...
+         *
+         * This requires a full 32-bit address immediate (and therefore a 6 byte
+         * instruction) as well as an add for each offset.
+         *
+         * Putting an asm guard prevents it from folding (at the cost of losing
+         * the alignment hint), and uses the free offset in `v128.load` instead
+         * of adding secret_offset each time which overall reduces code size by
+         * about a kilobyte and improves performance.
+         */
+        XXH_COMPILER_GUARD(xsecret);
+#endif
+        /* Scalar lanes use the normal scalarRound routine */
+        for (i = XXH3_NEON_LANES; i < XXH_ACC_NB; i++) {
+            XXH3_scalarRound(acc, input, secret, i);
+        }
+        i = 0;
+        /* 4 NEON lanes at a time. */
+        for (; i+1 < XXH3_NEON_LANES / 2; i+=2) {
+            /* data_vec = xinput[i]; */
+            uint64x2_t data_vec_1 = XXH_vld1q_u64(xinput  + (i * 16));
+            uint64x2_t data_vec_2 = XXH_vld1q_u64(xinput  + ((i+1) * 16));
+            /* key_vec  = xsecret[i];  */
+            uint64x2_t key_vec_1  = XXH_vld1q_u64(xsecret + (i * 16));
+            uint64x2_t key_vec_2  = XXH_vld1q_u64(xsecret + ((i+1) * 16));
+            /* data_swap = swap(data_vec) */
+            uint64x2_t data_swap_1 = vextq_u64(data_vec_1, data_vec_1, 1);
+            uint64x2_t data_swap_2 = vextq_u64(data_vec_2, data_vec_2, 1);
+            /* data_key = data_vec ^ key_vec; */
+            uint64x2_t data_key_1 = veorq_u64(data_vec_1, key_vec_1);
+            uint64x2_t data_key_2 = veorq_u64(data_vec_2, key_vec_2);
+
+            /*
+             * If we reinterpret the 64x2 vectors as 32x4 vectors, we can use a
+             * de-interleave operation for 4 lanes in 1 step with `vuzpq_u32` to
+             * get one vector with the low 32 bits of each lane, and one vector
+             * with the high 32 bits of each lane.
+             *
+             * The intrinsic returns a double vector because the original ARMv7-a
+             * instruction modified both arguments in place. AArch64 and SIMD128 emit
+             * two instructions from this intrinsic.
+             *
+             *  [ dk11L | dk11H | dk12L | dk12H ] -> [ dk11L | dk12L | dk21L | dk22L ]
+             *  [ dk21L | dk21H | dk22L | dk22H ] -> [ dk11H | dk12H | dk21H | dk22H ]
+             */
+            uint32x4x2_t unzipped = vuzpq_u32(
+                vreinterpretq_u32_u64(data_key_1),
+                vreinterpretq_u32_u64(data_key_2)
+            );
+            /* data_key_lo = data_key & 0xFFFFFFFF */
+            uint32x4_t data_key_lo = unzipped.val[0];
+            /* data_key_hi = data_key >> 32 */
+            uint32x4_t data_key_hi = unzipped.val[1];
+            /*
+             * Then, we can split the vectors horizontally and multiply which, as for most
+             * widening intrinsics, have a variant that works on both high half vectors
+             * for free on AArch64. A similar instruction is available on SIMD128.
+             *
+             * sum = data_swap + (u64x2) data_key_lo * (u64x2) data_key_hi
+             */
+            uint64x2_t sum_1 = XXH_vmlal_low_u32(data_swap_1, data_key_lo, data_key_hi);
+            uint64x2_t sum_2 = XXH_vmlal_high_u32(data_swap_2, data_key_lo, data_key_hi);
+            /*
+             * Clang reorders
+             *    a += b * c;     // umlal   swap.2d, dkl.2s, dkh.2s
+             *    c += a;         // add     acc.2d, acc.2d, swap.2d
+             * to
+             *    c += a;         // add     acc.2d, acc.2d, swap.2d
+             *    c += b * c;     // umlal   acc.2d, dkl.2s, dkh.2s
+             *
+             * While it would make sense in theory since the addition is faster,
+             * for reasons likely related to umlal being limited to certain NEON
+             * pipelines, this is worse. A compiler guard fixes this.
+             */
+            XXH_COMPILER_GUARD_CLANG_NEON(sum_1);
+            XXH_COMPILER_GUARD_CLANG_NEON(sum_2);
+            /* xacc[i] = acc_vec + sum; */
+            xacc[i]   = vaddq_u64(xacc[i], sum_1);
+            xacc[i+1] = vaddq_u64(xacc[i+1], sum_2);
+        }
+        /* Operate on the remaining NEON lanes 2 at a time. */
+        for (; i < XXH3_NEON_LANES / 2; i++) {
+            /* data_vec = xinput[i]; */
+            uint64x2_t data_vec = XXH_vld1q_u64(xinput  + (i * 16));
+            /* key_vec  = xsecret[i];  */
+            uint64x2_t key_vec  = XXH_vld1q_u64(xsecret + (i * 16));
+            /* acc_vec_2 = swap(data_vec) */
+            uint64x2_t data_swap = vextq_u64(data_vec, data_vec, 1);
+            /* data_key = data_vec ^ key_vec; */
+            uint64x2_t data_key = veorq_u64(data_vec, key_vec);
+            /* For two lanes, just use VMOVN and VSHRN. */
+            /* data_key_lo = data_key & 0xFFFFFFFF; */
+            uint32x2_t data_key_lo = vmovn_u64(data_key);
+            /* data_key_hi = data_key >> 32; */
+            uint32x2_t data_key_hi = vshrn_n_u64(data_key, 32);
+            /* sum = data_swap + (u64x2) data_key_lo * (u64x2) data_key_hi; */
+            uint64x2_t sum = vmlal_u32(data_swap, data_key_lo, data_key_hi);
+            /* Same Clang workaround as before */
+            XXH_COMPILER_GUARD_CLANG_NEON(sum);
+            /* xacc[i] = acc_vec + sum; */
+            xacc[i] = vaddq_u64 (xacc[i], sum);
+        }
+    }
+}
+XXH_FORCE_INLINE XXH3_ACCUMULATE_TEMPLATE(neon)
+
+XXH_FORCE_INLINE void
+XXH3_scrambleAcc_neon(void* XXH_RESTRICT acc, const void* XXH_RESTRICT secret)
+{
+    XXH_ASSERT((((size_t)acc) & 15) == 0);
+
+    {   xxh_aliasing_uint64x2_t* xacc       = (xxh_aliasing_uint64x2_t*) acc;
+        uint8_t const* xsecret = (uint8_t const*) secret;
+
+        size_t i;
+        /* WASM uses operator overloads and doesn't need these. */
+#ifndef __wasm_simd128__
+        /* { prime32_1, prime32_1 } */
+        uint32x2_t const kPrimeLo = vdup_n_u32(XXH_PRIME32_1);
+        /* { 0, prime32_1, 0, prime32_1 } */
+        uint32x4_t const kPrimeHi = vreinterpretq_u32_u64(vdupq_n_u64((xxh_u64)XXH_PRIME32_1 << 32));
+#endif
+
+        /* AArch64 uses both scalar and neon at the same time */
+        for (i = XXH3_NEON_LANES; i < XXH_ACC_NB; i++) {
+            XXH3_scalarScrambleRound(acc, secret, i);
+        }
+        for (i=0; i < XXH3_NEON_LANES / 2; i++) {
+            /* xacc[i] ^= (xacc[i] >> 47); */
+            uint64x2_t acc_vec  = xacc[i];
+            uint64x2_t shifted  = vshrq_n_u64(acc_vec, 47);
+            uint64x2_t data_vec = veorq_u64(acc_vec, shifted);
+
+            /* xacc[i] ^= xsecret[i]; */
+            uint64x2_t key_vec  = XXH_vld1q_u64(xsecret + (i * 16));
+            uint64x2_t data_key = veorq_u64(data_vec, key_vec);
+            /* xacc[i] *= XXH_PRIME32_1 */
+#ifdef __wasm_simd128__
+            /* SIMD128 has multiply by u64x2, use it instead of expanding and scalarizing */
+            xacc[i] = data_key * XXH_PRIME32_1;
+#else
+            /*
+             * Expanded version with portable NEON intrinsics
+             *
+             *    lo(x) * lo(y) + (hi(x) * lo(y) << 32)
+             *
+             * prod_hi = hi(data_key) * lo(prime) << 32
+             *
+             * Since we only need 32 bits of this multiply a trick can be used, reinterpreting the vector
+             * as a uint32x4_t and multiplying by { 0, prime, 0, prime } to cancel out the unwanted bits
+             * and avoid the shift.
+             */
+            uint32x4_t prod_hi = vmulq_u32 (vreinterpretq_u32_u64(data_key), kPrimeHi);
+            /* Extract low bits for vmlal_u32  */
+            uint32x2_t data_key_lo = vmovn_u64(data_key);
+            /* xacc[i] = prod_hi + lo(data_key) * XXH_PRIME32_1; */
+            xacc[i] = vmlal_u32(vreinterpretq_u64_u32(prod_hi), data_key_lo, kPrimeLo);
+#endif
+        }
+    }
+}
+#endif
+
+#if (XXH_VECTOR == XXH_VSX)
+
+XXH_FORCE_INLINE void
+XXH3_accumulate_512_vsx(  void* XXH_RESTRICT acc,
+                    const void* XXH_RESTRICT input,
+                    const void* XXH_RESTRICT secret)
+{
+    /* presumed aligned */
+    xxh_aliasing_u64x2* const xacc = (xxh_aliasing_u64x2*) acc;
+    xxh_u8 const* const xinput   = (xxh_u8 const*) input;   /* no alignment restriction */
+    xxh_u8 const* const xsecret  = (xxh_u8 const*) secret;    /* no alignment restriction */
+    xxh_u64x2 const v32 = { 32, 32 };
+    size_t i;
+    for (i = 0; i < XXH_STRIPE_LEN / sizeof(xxh_u64x2); i++) {
+        /* data_vec = xinput[i]; */
+        xxh_u64x2 const data_vec = XXH_vec_loadu(xinput + 16*i);
+        /* key_vec = xsecret[i]; */
+        xxh_u64x2 const key_vec  = XXH_vec_loadu(xsecret + 16*i);
+        xxh_u64x2 const data_key = data_vec ^ key_vec;
+        /* shuffled = (data_key << 32) | (data_key >> 32); */
+        xxh_u32x4 const shuffled = (xxh_u32x4)vec_rl(data_key, v32);
+        /* product = ((xxh_u64x2)data_key & 0xFFFFFFFF) * ((xxh_u64x2)shuffled & 0xFFFFFFFF); */
+        xxh_u64x2 const product  = XXH_vec_mulo((xxh_u32x4)data_key, shuffled);
+        /* acc_vec = xacc[i]; */
+        xxh_u64x2 acc_vec        = xacc[i];
+        acc_vec += product;
+
+        /* swap high and low halves */
+#ifdef __s390x__
+        acc_vec += vec_permi(data_vec, data_vec, 2);
+#else
+        acc_vec += vec_xxpermdi(data_vec, data_vec, 2);
+#endif
+        xacc[i] = acc_vec;
+    }
+}
+XXH_FORCE_INLINE XXH3_ACCUMULATE_TEMPLATE(vsx)
+
+XXH_FORCE_INLINE void
+XXH3_scrambleAcc_vsx(void* XXH_RESTRICT acc, const void* XXH_RESTRICT secret)
+{
+    XXH_ASSERT((((size_t)acc) & 15) == 0);
+
+    {   xxh_aliasing_u64x2* const xacc = (xxh_aliasing_u64x2*) acc;
+        const xxh_u8* const xsecret = (const xxh_u8*) secret;
+        /* constants */
+        xxh_u64x2 const v32  = { 32, 32 };
+        xxh_u64x2 const v47 = { 47, 47 };
+        xxh_u32x4 const prime = { XXH_PRIME32_1, XXH_PRIME32_1, XXH_PRIME32_1, XXH_PRIME32_1 };
+        size_t i;
+        for (i = 0; i < XXH_STRIPE_LEN / sizeof(xxh_u64x2); i++) {
+            /* xacc[i] ^= (xacc[i] >> 47); */
+            xxh_u64x2 const acc_vec  = xacc[i];
+            xxh_u64x2 const data_vec = acc_vec ^ (acc_vec >> v47);
+
+            /* xacc[i] ^= xsecret[i]; */
+            xxh_u64x2 const key_vec  = XXH_vec_loadu(xsecret + 16*i);
+            xxh_u64x2 const data_key = data_vec ^ key_vec;
+
+            /* xacc[i] *= XXH_PRIME32_1 */
+            /* prod_lo = ((xxh_u64x2)data_key & 0xFFFFFFFF) * ((xxh_u64x2)prime & 0xFFFFFFFF);  */
+            xxh_u64x2 const prod_even  = XXH_vec_mule((xxh_u32x4)data_key, prime);
+            /* prod_hi = ((xxh_u64x2)data_key >> 32) * ((xxh_u64x2)prime >> 32);  */
+            xxh_u64x2 const prod_odd  = XXH_vec_mulo((xxh_u32x4)data_key, prime);
+            xacc[i] = prod_odd + (prod_even << v32);
+    }   }
+}
+
+#endif
+
+#if (XXH_VECTOR == XXH_SVE)
+
+XXH_FORCE_INLINE void
+XXH3_accumulate_512_sve( void* XXH_RESTRICT acc,
+                   const void* XXH_RESTRICT input,
+                   const void* XXH_RESTRICT secret)
+{
+    uint64_t *xacc = (uint64_t *)acc;
+    const uint64_t *xinput = (const uint64_t *)(const void *)input;
+    const uint64_t *xsecret = (const uint64_t *)(const void *)secret;
+    svuint64_t kSwap = sveor_n_u64_z(svptrue_b64(), svindex_u64(0, 1), 1);
+    uint64_t element_count = svcntd();
+    if (element_count >= 8) {
+        svbool_t mask = svptrue_pat_b64(SV_VL8);
+        svuint64_t vacc = svld1_u64(mask, xacc);
+        ACCRND(vacc, 0);
+        svst1_u64(mask, xacc, vacc);
+    } else if (element_count == 2) {   /* sve128 */
+        svbool_t mask = svptrue_pat_b64(SV_VL2);
+        svuint64_t acc0 = svld1_u64(mask, xacc + 0);
+        svuint64_t acc1 = svld1_u64(mask, xacc + 2);
+        svuint64_t acc2 = svld1_u64(mask, xacc + 4);
+        svuint64_t acc3 = svld1_u64(mask, xacc + 6);
+        ACCRND(acc0, 0);
+        ACCRND(acc1, 2);
+        ACCRND(acc2, 4);
+        ACCRND(acc3, 6);
+        svst1_u64(mask, xacc + 0, acc0);
+        svst1_u64(mask, xacc + 2, acc1);
+        svst1_u64(mask, xacc + 4, acc2);
+        svst1_u64(mask, xacc + 6, acc3);
+    } else {
+        svbool_t mask = svptrue_pat_b64(SV_VL4);
+        svuint64_t acc0 = svld1_u64(mask, xacc + 0);
+        svuint64_t acc1 = svld1_u64(mask, xacc + 4);
+        ACCRND(acc0, 0);
+        ACCRND(acc1, 4);
+        svst1_u64(mask, xacc + 0, acc0);
+        svst1_u64(mask, xacc + 4, acc1);
+    }
+}
+
+XXH_FORCE_INLINE void
+XXH3_accumulate_sve(xxh_u64* XXH_RESTRICT acc,
+               const xxh_u8* XXH_RESTRICT input,
+               const xxh_u8* XXH_RESTRICT secret,
+               size_t nbStripes)
+{
+    if (nbStripes != 0) {
+        uint64_t *xacc = (uint64_t *)acc;
+        const uint64_t *xinput = (const uint64_t *)(const void *)input;
+        const uint64_t *xsecret = (const uint64_t *)(const void *)secret;
+        svuint64_t kSwap = sveor_n_u64_z(svptrue_b64(), svindex_u64(0, 1), 1);
+        uint64_t element_count = svcntd();
+        if (element_count >= 8) {
+            svbool_t mask = svptrue_pat_b64(SV_VL8);
+            svuint64_t vacc = svld1_u64(mask, xacc + 0);
+            do {
+                /* svprfd(svbool_t, void *, enum svfprop); */
+                svprfd(mask, xinput + 128, SV_PLDL1STRM);
+                ACCRND(vacc, 0);
+                xinput += 8;
+                xsecret += 1;
+                nbStripes--;
+           } while (nbStripes != 0);
+
+           svst1_u64(mask, xacc + 0, vacc);
+        } else if (element_count == 2) { /* sve128 */
+            svbool_t mask = svptrue_pat_b64(SV_VL2);
+            svuint64_t acc0 = svld1_u64(mask, xacc + 0);
+            svuint64_t acc1 = svld1_u64(mask, xacc + 2);
+            svuint64_t acc2 = svld1_u64(mask, xacc + 4);
+            svuint64_t acc3 = svld1_u64(mask, xacc + 6);
+            do {
+                svprfd(mask, xinput + 128, SV_PLDL1STRM);
+                ACCRND(acc0, 0);
+                ACCRND(acc1, 2);
+                ACCRND(acc2, 4);
+                ACCRND(acc3, 6);
+                xinput += 8;
+                xsecret += 1;
+                nbStripes--;
+           } while (nbStripes != 0);
+
+           svst1_u64(mask, xacc + 0, acc0);
+           svst1_u64(mask, xacc + 2, acc1);
+           svst1_u64(mask, xacc + 4, acc2);
+           svst1_u64(mask, xacc + 6, acc3);
+        } else {
+            svbool_t mask = svptrue_pat_b64(SV_VL4);
+            svuint64_t acc0 = svld1_u64(mask, xacc + 0);
+            svuint64_t acc1 = svld1_u64(mask, xacc + 4);
+            do {
+                svprfd(mask, xinput + 128, SV_PLDL1STRM);
+                ACCRND(acc0, 0);
+                ACCRND(acc1, 4);
+                xinput += 8;
+                xsecret += 1;
+                nbStripes--;
+           } while (nbStripes != 0);
+
+           svst1_u64(mask, xacc + 0, acc0);
+           svst1_u64(mask, xacc + 4, acc1);
+       }
+    }
+}
+
+#endif
+
+/* scalar variants - universal */
+
+#if defined(__aarch64__) && (defined(__GNUC__) || defined(__clang__))
+/*
+ * In XXH3_scalarRound(), GCC and Clang have a similar codegen issue, where they
+ * emit an excess mask and a full 64-bit multiply-add (MADD X-form).
+ *
+ * While this might not seem like much, as AArch64 is a 64-bit architecture, only
+ * big Cortex designs have a full 64-bit multiplier.
+ *
+ * On the little cores, the smaller 32-bit multiplier is used, and full 64-bit
+ * multiplies expand to 2-3 multiplies in microcode. This has a major penalty
+ * of up to 4 latency cycles and 2 stall cycles in the multiply pipeline.
+ *
+ * Thankfully, AArch64 still provides the 32-bit long multiply-add (UMADDL) which does
+ * not have this penalty and does the mask automatically.
+ */
+XXH_FORCE_INLINE xxh_u64
+XXH_mult32to64_add64(xxh_u64 lhs, xxh_u64 rhs, xxh_u64 acc)
+{
+    xxh_u64 ret;
+    /* note: %x = 64-bit register, %w = 32-bit register */
+    __asm__("umaddl %x0, %w1, %w2, %x3" : "=r" (ret) : "r" (lhs), "r" (rhs), "r" (acc));
+    return ret;
+}
+#else
+XXH_FORCE_INLINE xxh_u64
+XXH_mult32to64_add64(xxh_u64 lhs, xxh_u64 rhs, xxh_u64 acc)
+{
+    return XXH_mult32to64((xxh_u32)lhs, (xxh_u32)rhs) + acc;
+}
+#endif
+
+/*!
+ * @internal
+ * @brief Scalar round for @ref XXH3_accumulate_512_scalar().
+ *
+ * This is extracted to its own function because the NEON path uses a combination
+ * of NEON and scalar.
+ */
+XXH_FORCE_INLINE void
+XXH3_scalarRound(void* XXH_RESTRICT acc,
+                 void const* XXH_RESTRICT input,
+                 void const* XXH_RESTRICT secret,
+                 size_t lane)
+{
+    xxh_u64* xacc = (xxh_u64*) acc;
+    xxh_u8 const* xinput  = (xxh_u8 const*) input;
+    xxh_u8 const* xsecret = (xxh_u8 const*) secret;
+    XXH_ASSERT(lane < XXH_ACC_NB);
+    XXH_ASSERT(((size_t)acc & (XXH_ACC_ALIGN-1)) == 0);
+    {
+        xxh_u64 const data_val = XXH_readLE64(xinput + lane * 8);
+        xxh_u64 const data_key = data_val ^ XXH_readLE64(xsecret + lane * 8);
+        xacc[lane ^ 1] += data_val; /* swap adjacent lanes */
+        xacc[lane] = XXH_mult32to64_add64(data_key /* & 0xFFFFFFFF */, data_key >> 32, xacc[lane]);
+    }
+}
+
+/*!
+ * @internal
+ * @brief Processes a 64 byte block of data using the scalar path.
+ */
+XXH_FORCE_INLINE void
+XXH3_accumulate_512_scalar(void* XXH_RESTRICT acc,
+                     const void* XXH_RESTRICT input,
+                     const void* XXH_RESTRICT secret)
+{
+    size_t i;
+    /* ARM GCC refuses to unroll this loop, resulting in a 24% slowdown on ARMv6. */
+#if defined(__GNUC__) && !defined(__clang__) \
+  && (defined(__arm__) || defined(__thumb2__)) \
+  && defined(__ARM_FEATURE_UNALIGNED) /* no unaligned access just wastes bytes */ \
+  && XXH_SIZE_OPT <= 0
+#  pragma GCC unroll 8
+#endif
+    for (i=0; i < XXH_ACC_NB; i++) {
+        XXH3_scalarRound(acc, input, secret, i);
+    }
+}
+XXH_FORCE_INLINE XXH3_ACCUMULATE_TEMPLATE(scalar)
+
+/*!
+ * @internal
+ * @brief Scalar scramble step for @ref XXH3_scrambleAcc_scalar().
+ *
+ * This is extracted to its own function because the NEON path uses a combination
+ * of NEON and scalar.
+ */
+XXH_FORCE_INLINE void
+XXH3_scalarScrambleRound(void* XXH_RESTRICT acc,
+                         void const* XXH_RESTRICT secret,
+                         size_t lane)
+{
+    xxh_u64* const xacc = (xxh_u64*) acc;   /* presumed aligned */
+    const xxh_u8* const xsecret = (const xxh_u8*) secret;   /* no alignment restriction */
+    XXH_ASSERT((((size_t)acc) & (XXH_ACC_ALIGN-1)) == 0);
+    XXH_ASSERT(lane < XXH_ACC_NB);
+    {
+        xxh_u64 const key64 = XXH_readLE64(xsecret + lane * 8);
+        xxh_u64 acc64 = xacc[lane];
+        acc64 = XXH_xorshift64(acc64, 47);
+        acc64 ^= key64;
+        acc64 *= XXH_PRIME32_1;
+        xacc[lane] = acc64;
+    }
+}
+
+/*!
+ * @internal
+ * @brief Scrambles the accumulators after a large chunk has been read
+ */
+XXH_FORCE_INLINE void
+XXH3_scrambleAcc_scalar(void* XXH_RESTRICT acc, const void* XXH_RESTRICT secret)
+{
+    size_t i;
+    for (i=0; i < XXH_ACC_NB; i++) {
+        XXH3_scalarScrambleRound(acc, secret, i);
+    }
+}
+
+XXH_FORCE_INLINE void
+XXH3_initCustomSecret_scalar(void* XXH_RESTRICT customSecret, xxh_u64 seed64)
+{
+    /*
+     * We need a separate pointer for the hack below,
+     * which requires a non-const pointer.
+     * Any decent compiler will optimize this out otherwise.
+     */
+    const xxh_u8* kSecretPtr = XXH3_kSecret;
+    XXH_STATIC_ASSERT((XXH_SECRET_DEFAULT_SIZE & 15) == 0);
+
+#if defined(__GNUC__) && defined(__aarch64__)
+    /*
+     * UGLY HACK:
+     * GCC and Clang generate a bunch of MOV/MOVK pairs for aarch64, and they are
+     * placed sequentially, in order, at the top of the unrolled loop.
+     *
+     * While MOVK is great for generating constants (2 cycles for a 64-bit
+     * constant compared to 4 cycles for LDR), it fights for bandwidth with
+     * the arithmetic instructions.
+     *
+     *   I   L   S
+     * MOVK
+     * MOVK
+     * MOVK
+     * MOVK
+     * ADD
+     * SUB      STR
+     *          STR
+     * By forcing loads from memory (as the asm line causes the compiler to assume
+     * that XXH3_kSecretPtr has been changed), the pipelines are used more
+     * efficiently:
+     *   I   L   S
+     *      LDR
+     *  ADD LDR
+     *  SUB     STR
+     *          STR
+     *
+     * See XXH3_NEON_LANES for details on the pipsline.
+     *
+     * XXH3_64bits_withSeed, len == 256, Snapdragon 835
+     *   without hack: 2654.4 MB/s
+     *   with hack:    3202.9 MB/s
+     */
+    XXH_COMPILER_GUARD(kSecretPtr);
+#endif
+    {   int const nbRounds = XXH_SECRET_DEFAULT_SIZE / 16;
+        int i;
+        for (i=0; i < nbRounds; i++) {
+            /*
+             * The asm hack causes the compiler to assume that kSecretPtr aliases with
+             * customSecret, and on aarch64, this prevented LDP from merging two
+             * loads together for free. Putting the loads together before the stores
+             * properly generates LDP.
+             */
+            xxh_u64 lo = XXH_readLE64(kSecretPtr + 16*i)     + seed64;
+            xxh_u64 hi = XXH_readLE64(kSecretPtr + 16*i + 8) - seed64;
+            XXH_writeLE64((xxh_u8*)customSecret + 16*i,     lo);
+            XXH_writeLE64((xxh_u8*)customSecret + 16*i + 8, hi);
+    }   }
+}
+
+
+typedef void (*XXH3_f_accumulate)(xxh_u64* XXH_RESTRICT, const xxh_u8* XXH_RESTRICT, const xxh_u8* XXH_RESTRICT, size_t);
+typedef void (*XXH3_f_scrambleAcc)(void* XXH_RESTRICT, const void*);
+typedef void (*XXH3_f_initCustomSecret)(void* XXH_RESTRICT, xxh_u64);
+
+
+#if (XXH_VECTOR == XXH_AVX512)
+
+#define XXH3_accumulate_512 XXH3_accumulate_512_avx512
+#define XXH3_accumulate     XXH3_accumulate_avx512
+#define XXH3_scrambleAcc    XXH3_scrambleAcc_avx512
+#define XXH3_initCustomSecret XXH3_initCustomSecret_avx512
+
+#elif (XXH_VECTOR == XXH_AVX2)
+
+#define XXH3_accumulate_512 XXH3_accumulate_512_avx2
+#define XXH3_accumulate     XXH3_accumulate_avx2
+#define XXH3_scrambleAcc    XXH3_scrambleAcc_avx2
+#define XXH3_initCustomSecret XXH3_initCustomSecret_avx2
+
+#elif (XXH_VECTOR == XXH_SSE2)
+
+#define XXH3_accumulate_512 XXH3_accumulate_512_sse2
+#define XXH3_accumulate     XXH3_accumulate_sse2
+#define XXH3_scrambleAcc    XXH3_scrambleAcc_sse2
+#define XXH3_initCustomSecret XXH3_initCustomSecret_sse2
+
+#elif (XXH_VECTOR == XXH_NEON)
+
+#define XXH3_accumulate_512 XXH3_accumulate_512_neon
+#define XXH3_accumulate     XXH3_accumulate_neon
+#define XXH3_scrambleAcc    XXH3_scrambleAcc_neon
+#define XXH3_initCustomSecret XXH3_initCustomSecret_scalar
+
+#elif (XXH_VECTOR == XXH_VSX)
+
+#define XXH3_accumulate_512 XXH3_accumulate_512_vsx
+#define XXH3_accumulate     XXH3_accumulate_vsx
+#define XXH3_scrambleAcc    XXH3_scrambleAcc_vsx
+#define XXH3_initCustomSecret XXH3_initCustomSecret_scalar
+
+#elif (XXH_VECTOR == XXH_SVE)
+#define XXH3_accumulate_512 XXH3_accumulate_512_sve
+#define XXH3_accumulate     XXH3_accumulate_sve
+#define XXH3_scrambleAcc    XXH3_scrambleAcc_scalar
+#define XXH3_initCustomSecret XXH3_initCustomSecret_scalar
+
+#else /* scalar */
+
+#define XXH3_accumulate_512 XXH3_accumulate_512_scalar
+#define XXH3_accumulate     XXH3_accumulate_scalar
+#define XXH3_scrambleAcc    XXH3_scrambleAcc_scalar
+#define XXH3_initCustomSecret XXH3_initCustomSecret_scalar
+
+#endif
+
+#if XXH_SIZE_OPT >= 1 /* don't do SIMD for initialization */
+#  undef XXH3_initCustomSecret
+#  define XXH3_initCustomSecret XXH3_initCustomSecret_scalar
+#endif
+
+XXH_FORCE_INLINE void
+XXH3_hashLong_internal_loop(xxh_u64* XXH_RESTRICT acc,
+                      const xxh_u8* XXH_RESTRICT input, size_t len,
+                      const xxh_u8* XXH_RESTRICT secret, size_t secretSize,
+                            XXH3_f_accumulate f_acc,
+                            XXH3_f_scrambleAcc f_scramble)
+{
+    size_t const nbStripesPerBlock = (secretSize - XXH_STRIPE_LEN) / XXH_SECRET_CONSUME_RATE;
+    size_t const block_len = XXH_STRIPE_LEN * nbStripesPerBlock;
+    size_t const nb_blocks = (len - 1) / block_len;
+
+    size_t n;
+
+    XXH_ASSERT(secretSize >= XXH3_SECRET_SIZE_MIN);
+
+    for (n = 0; n < nb_blocks; n++) {
+        f_acc(acc, input + n*block_len, secret, nbStripesPerBlock);
+        f_scramble(acc, secret + secretSize - XXH_STRIPE_LEN);
+    }
+
+    /* last partial block */
+    XXH_ASSERT(len > XXH_STRIPE_LEN);
+    {   size_t const nbStripes = ((len - 1) - (block_len * nb_blocks)) / XXH_STRIPE_LEN;
+        XXH_ASSERT(nbStripes <= (secretSize / XXH_SECRET_CONSUME_RATE));
+        f_acc(acc, input + nb_blocks*block_len, secret, nbStripes);
+
+        /* last stripe */
+        {   const xxh_u8* const p = input + len - XXH_STRIPE_LEN;
+#define XXH_SECRET_LASTACC_START 7  /* not aligned on 8, last secret is different from acc & scrambler */
+            XXH3_accumulate_512(acc, p, secret + secretSize - XXH_STRIPE_LEN - XXH_SECRET_LASTACC_START);
+    }   }
+}
+
+XXH_FORCE_INLINE xxh_u64
+XXH3_mix2Accs(const xxh_u64* XXH_RESTRICT acc, const xxh_u8* XXH_RESTRICT secret)
+{
+    return XXH3_mul128_fold64(
+               acc[0] ^ XXH_readLE64(secret),
+               acc[1] ^ XXH_readLE64(secret+8) );
+}
+
+static XXH64_hash_t
+XXH3_mergeAccs(const xxh_u64* XXH_RESTRICT acc, const xxh_u8* XXH_RESTRICT secret, xxh_u64 start)
+{
+    xxh_u64 result64 = start;
+    size_t i = 0;
+
+    for (i = 0; i < 4; i++) {
+        result64 += XXH3_mix2Accs(acc+2*i, secret + 16*i);
+#if defined(__clang__)                                /* Clang */ \
+    && (defined(__arm__) || defined(__thumb__))       /* ARMv7 */ \
+    && (defined(__ARM_NEON) || defined(__ARM_NEON__)) /* NEON */  \
+    && !defined(XXH_ENABLE_AUTOVECTORIZE)             /* Define to disable */
+        /*
+         * UGLY HACK:
+         * Prevent autovectorization on Clang ARMv7-a. Exact same problem as
+         * the one in XXH3_len_129to240_64b. Speeds up shorter keys > 240b.
+         * XXH3_64bits, len == 256, Snapdragon 835:
+         *   without hack: 2063.7 MB/s
+         *   with hack:    2560.7 MB/s
+         */
+        XXH_COMPILER_GUARD(result64);
+#endif
+    }
+
+    return XXH3_avalanche(result64);
+}
+
+#define XXH3_INIT_ACC { XXH_PRIME32_3, XXH_PRIME64_1, XXH_PRIME64_2, XXH_PRIME64_3, \
+                        XXH_PRIME64_4, XXH_PRIME32_2, XXH_PRIME64_5, XXH_PRIME32_1 }
+
+XXH_FORCE_INLINE XXH64_hash_t
+XXH3_hashLong_64b_internal(const void* XXH_RESTRICT input, size_t len,
+                           const void* XXH_RESTRICT secret, size_t secretSize,
+                           XXH3_f_accumulate f_acc,
+                           XXH3_f_scrambleAcc f_scramble)
+{
+    XXH_ALIGN(XXH_ACC_ALIGN) xxh_u64 acc[XXH_ACC_NB] = XXH3_INIT_ACC;
+
+    XXH3_hashLong_internal_loop(acc, (const xxh_u8*)input, len, (const xxh_u8*)secret, secretSize, f_acc, f_scramble);
+
+    /* converge into final hash */
+    XXH_STATIC_ASSERT(sizeof(acc) == 64);
+    /* do not align on 8, so that the secret is different from the accumulator */
+#define XXH_SECRET_MERGEACCS_START 11
+    XXH_ASSERT(secretSize >= sizeof(acc) + XXH_SECRET_MERGEACCS_START);
+    return XXH3_mergeAccs(acc, (const xxh_u8*)secret + XXH_SECRET_MERGEACCS_START, (xxh_u64)len * XXH_PRIME64_1);
+}
+
+/*
+ * It's important for performance to transmit secret's size (when it's static)
+ * so that the compiler can properly optimize the vectorized loop.
+ * This makes a big performance difference for "medium" keys (<1 KB) when using AVX instruction set.
+ * When the secret size is unknown, or on GCC 12 where the mix of NO_INLINE and FORCE_INLINE
+ * breaks -Og, this is XXH_NO_INLINE.
+ */
+XXH3_WITH_SECRET_INLINE XXH64_hash_t
+XXH3_hashLong_64b_withSecret(const void* XXH_RESTRICT input, size_t len,
+                             XXH64_hash_t seed64, const xxh_u8* XXH_RESTRICT secret, size_t secretLen)
+{
+    (void)seed64;
+    return XXH3_hashLong_64b_internal(input, len, secret, secretLen, XXH3_accumulate, XXH3_scrambleAcc);
+}
+
+/*
+ * It's preferable for performance that XXH3_hashLong is not inlined,
+ * as it results in a smaller function for small data, easier to the instruction cache.
+ * Note that inside this no_inline function, we do inline the internal loop,
+ * and provide a statically defined secret size to allow optimization of vector loop.
+ */
+XXH_NO_INLINE XXH_PUREF XXH64_hash_t
+XXH3_hashLong_64b_default(const void* XXH_RESTRICT input, size_t len,
+                          XXH64_hash_t seed64, const xxh_u8* XXH_RESTRICT secret, size_t secretLen)
+{
+    (void)seed64; (void)secret; (void)secretLen;
+    return XXH3_hashLong_64b_internal(input, len, XXH3_kSecret, sizeof(XXH3_kSecret), XXH3_accumulate, XXH3_scrambleAcc);
+}
+
+/*
+ * XXH3_hashLong_64b_withSeed():
+ * Generate a custom key based on alteration of default XXH3_kSecret with the seed,
+ * and then use this key for long mode hashing.
+ *
+ * This operation is decently fast but nonetheless costs a little bit of time.
+ * Try to avoid it whenever possible (typically when seed==0).
+ *
+ * It's important for performance that XXH3_hashLong is not inlined. Not sure
+ * why (uop cache maybe?), but the difference is large and easily measurable.
+ */
+XXH_FORCE_INLINE XXH64_hash_t
+XXH3_hashLong_64b_withSeed_internal(const void* input, size_t len,
+                                    XXH64_hash_t seed,
+                                    XXH3_f_accumulate f_acc,
+                                    XXH3_f_scrambleAcc f_scramble,
+                                    XXH3_f_initCustomSecret f_initSec)
+{
+#if XXH_SIZE_OPT <= 0
+    if (seed == 0)
+        return XXH3_hashLong_64b_internal(input, len,
+                                          XXH3_kSecret, sizeof(XXH3_kSecret),
+                                          f_acc, f_scramble);
+#endif
+    {   XXH_ALIGN(XXH_SEC_ALIGN) xxh_u8 secret[XXH_SECRET_DEFAULT_SIZE];
+        f_initSec(secret, seed);
+        return XXH3_hashLong_64b_internal(input, len, secret, sizeof(secret),
+                                          f_acc, f_scramble);
+    }
+}
+
+/*
+ * It's important for performance that XXH3_hashLong is not inlined.
+ */
+XXH_NO_INLINE XXH64_hash_t
+XXH3_hashLong_64b_withSeed(const void* XXH_RESTRICT input, size_t len,
+                           XXH64_hash_t seed, const xxh_u8* XXH_RESTRICT secret, size_t secretLen)
+{
+    (void)secret; (void)secretLen;
+    return XXH3_hashLong_64b_withSeed_internal(input, len, seed,
+                XXH3_accumulate, XXH3_scrambleAcc, XXH3_initCustomSecret);
+}
+
+
+typedef XXH64_hash_t (*XXH3_hashLong64_f)(const void* XXH_RESTRICT, size_t,
+                                          XXH64_hash_t, const xxh_u8* XXH_RESTRICT, size_t);
+
+XXH_FORCE_INLINE XXH64_hash_t
+XXH3_64bits_internal(const void* XXH_RESTRICT input, size_t len,
+                     XXH64_hash_t seed64, const void* XXH_RESTRICT secret, size_t secretLen,
+                     XXH3_hashLong64_f f_hashLong)
+{
+    XXH_ASSERT(secretLen >= XXH3_SECRET_SIZE_MIN);
+    /*
+     * If an action is to be taken if `secretLen` condition is not respected,
+     * it should be done here.
+     * For now, it's a contract pre-condition.
+     * Adding a check and a branch here would cost performance at every hash.
+     * Also, note that function signature doesn't offer room to return an error.
+     */
+    if (len <= 16)
+        return XXH3_len_0to16_64b((const xxh_u8*)input, len, (const xxh_u8*)secret, seed64);
+    if (len <= 128)
+        return XXH3_len_17to128_64b((const xxh_u8*)input, len, (const xxh_u8*)secret, secretLen, seed64);
+    if (len <= XXH3_MIDSIZE_MAX)
+        return XXH3_len_129to240_64b((const xxh_u8*)input, len, (const xxh_u8*)secret, secretLen, seed64);
+    return f_hashLong(input, len, seed64, (const xxh_u8*)secret, secretLen);
+}
+
+
+/* ===   Public entry point   === */
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH64_hash_t XXH3_64bits(XXH_NOESCAPE const void* input, size_t length)
+{
+    return XXH3_64bits_internal(input, length, 0, XXH3_kSecret, sizeof(XXH3_kSecret), XXH3_hashLong_64b_default);
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH64_hash_t
+XXH3_64bits_withSecret(XXH_NOESCAPE const void* input, size_t length, XXH_NOESCAPE const void* secret, size_t secretSize)
+{
+    return XXH3_64bits_internal(input, length, 0, secret, secretSize, XXH3_hashLong_64b_withSecret);
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH64_hash_t
+XXH3_64bits_withSeed(XXH_NOESCAPE const void* input, size_t length, XXH64_hash_t seed)
+{
+    return XXH3_64bits_internal(input, length, seed, XXH3_kSecret, sizeof(XXH3_kSecret), XXH3_hashLong_64b_withSeed);
+}
+
+XXH_PUBLIC_API XXH64_hash_t
+XXH3_64bits_withSecretandSeed(XXH_NOESCAPE const void* input, size_t length, XXH_NOESCAPE const void* secret, size_t secretSize, XXH64_hash_t seed)
+{
+    if (length <= XXH3_MIDSIZE_MAX)
+        return XXH3_64bits_internal(input, length, seed, XXH3_kSecret, sizeof(XXH3_kSecret), NULL);
+    return XXH3_hashLong_64b_withSecret(input, length, seed, (const xxh_u8*)secret, secretSize);
+}
+
+
+/* ===   XXH3 streaming   === */
+#ifndef XXH_NO_STREAM
+/*
+ * Malloc's a pointer that is always aligned to align.
+ *
+ * This must be freed with `XXH_alignedFree()`.
+ *
+ * malloc typically guarantees 16 byte alignment on 64-bit systems and 8 byte
+ * alignment on 32-bit. This isn't enough for the 32 byte aligned loads in AVX2
+ * or on 32-bit, the 16 byte aligned loads in SSE2 and NEON.
+ *
+ * This underalignment previously caused a rather obvious crash which went
+ * completely unnoticed due to XXH3_createState() not actually being tested.
+ * Credit to RedSpah for noticing this bug.
+ *
+ * The alignment is done manually: Functions like posix_memalign or _mm_malloc
+ * are avoided: To maintain portability, we would have to write a fallback
+ * like this anyways, and besides, testing for the existence of library
+ * functions without relying on external build tools is impossible.
+ *
+ * The method is simple: Overallocate, manually align, and store the offset
+ * to the original behind the returned pointer.
+ *
+ * Align must be a power of 2 and 8 <= align <= 128.
+ */
+static XXH_MALLOCF void* XXH_alignedMalloc(size_t s, size_t align)
+{
+    XXH_ASSERT(align <= 128 && align >= 8); /* range check */
+    XXH_ASSERT((align & (align-1)) == 0);   /* power of 2 */
+    XXH_ASSERT(s != 0 && s < (s + align));  /* empty/overflow */
+    {   /* Overallocate to make room for manual realignment and an offset byte */
+        xxh_u8* base = (xxh_u8*)XXH_malloc(s + align);
+        if (base != NULL) {
+            /*
+             * Get the offset needed to align this pointer.
+             *
+             * Even if the returned pointer is aligned, there will always be
+             * at least one byte to store the offset to the original pointer.
+             */
+            size_t offset = align - ((size_t)base & (align - 1)); /* base % align */
+            /* Add the offset for the now-aligned pointer */
+            xxh_u8* ptr = base + offset;
+
+            XXH_ASSERT((size_t)ptr % align == 0);
+
+            /* Store the offset immediately before the returned pointer. */
+            ptr[-1] = (xxh_u8)offset;
+            return ptr;
+        }
+        return NULL;
+    }
+}
+/*
+ * Frees an aligned pointer allocated by XXH_alignedMalloc(). Don't pass
+ * normal malloc'd pointers, XXH_alignedMalloc has a specific data layout.
+ */
+static void XXH_alignedFree(void* p)
+{
+    if (p != NULL) {
+        xxh_u8* ptr = (xxh_u8*)p;
+        /* Get the offset byte we added in XXH_malloc. */
+        xxh_u8 offset = ptr[-1];
+        /* Free the original malloc'd pointer */
+        xxh_u8* base = ptr - offset;
+        XXH_free(base);
+    }
+}
+/*! @ingroup XXH3_family */
+/*!
+ * @brief Allocate an @ref XXH3_state_t.
+ *
+ * @return An allocated pointer of @ref XXH3_state_t on success.
+ * @return `NULL` on failure.
+ *
+ * @note Must be freed with XXH3_freeState().
+ *
+ * @see @ref streaming_example "Streaming Example"
+ */
+XXH_PUBLIC_API XXH3_state_t* XXH3_createState(void)
+{
+    XXH3_state_t* const state = (XXH3_state_t*)XXH_alignedMalloc(sizeof(XXH3_state_t), 64);
+    if (state==NULL) return NULL;
+    XXH3_INITSTATE(state);
+    return state;
+}
+
+/*! @ingroup XXH3_family */
+/*!
+ * @brief Frees an @ref XXH3_state_t.
+ *
+ * @param statePtr A pointer to an @ref XXH3_state_t allocated with @ref XXH3_createState().
+ *
+ * @return @ref XXH_OK.
+ *
+ * @note Must be allocated with XXH3_createState().
+ *
+ * @see @ref streaming_example "Streaming Example"
+ */
+XXH_PUBLIC_API XXH_errorcode XXH3_freeState(XXH3_state_t* statePtr)
+{
+    XXH_alignedFree(statePtr);
+    return XXH_OK;
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API void
+XXH3_copyState(XXH_NOESCAPE XXH3_state_t* dst_state, XXH_NOESCAPE const XXH3_state_t* src_state)
+{
+    XXH_memcpy(dst_state, src_state, sizeof(*dst_state));
+}
+
+static void
+XXH3_reset_internal(XXH3_state_t* statePtr,
+                    XXH64_hash_t seed,
+                    const void* secret, size_t secretSize)
+{
+    size_t const initStart = offsetof(XXH3_state_t, bufferedSize);
+    size_t const initLength = offsetof(XXH3_state_t, nbStripesPerBlock) - initStart;
+    XXH_ASSERT(offsetof(XXH3_state_t, nbStripesPerBlock) > initStart);
+    XXH_ASSERT(statePtr != NULL);
+    /* set members from bufferedSize to nbStripesPerBlock (excluded) to 0 */
+    memset((char*)statePtr + initStart, 0, initLength);
+    statePtr->acc[0] = XXH_PRIME32_3;
+    statePtr->acc[1] = XXH_PRIME64_1;
+    statePtr->acc[2] = XXH_PRIME64_2;
+    statePtr->acc[3] = XXH_PRIME64_3;
+    statePtr->acc[4] = XXH_PRIME64_4;
+    statePtr->acc[5] = XXH_PRIME32_2;
+    statePtr->acc[6] = XXH_PRIME64_5;
+    statePtr->acc[7] = XXH_PRIME32_1;
+    statePtr->seed = seed;
+    statePtr->useSeed = (seed != 0);
+    statePtr->extSecret = (const unsigned char*)secret;
+    XXH_ASSERT(secretSize >= XXH3_SECRET_SIZE_MIN);
+    statePtr->secretLimit = secretSize - XXH_STRIPE_LEN;
+    statePtr->nbStripesPerBlock = statePtr->secretLimit / XXH_SECRET_CONSUME_RATE;
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH_errorcode
+XXH3_64bits_reset(XXH_NOESCAPE XXH3_state_t* statePtr)
+{
+    if (statePtr == NULL) return XXH_ERROR;
+    XXH3_reset_internal(statePtr, 0, XXH3_kSecret, XXH_SECRET_DEFAULT_SIZE);
+    return XXH_OK;
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH_errorcode
+XXH3_64bits_reset_withSecret(XXH_NOESCAPE XXH3_state_t* statePtr, XXH_NOESCAPE const void* secret, size_t secretSize)
+{
+    if (statePtr == NULL) return XXH_ERROR;
+    XXH3_reset_internal(statePtr, 0, secret, secretSize);
+    if (secret == NULL) return XXH_ERROR;
+    if (secretSize < XXH3_SECRET_SIZE_MIN) return XXH_ERROR;
+    return XXH_OK;
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH_errorcode
+XXH3_64bits_reset_withSeed(XXH_NOESCAPE XXH3_state_t* statePtr, XXH64_hash_t seed)
+{
+    if (statePtr == NULL) return XXH_ERROR;
+    if (seed==0) return XXH3_64bits_reset(statePtr);
+    if ((seed != statePtr->seed) || (statePtr->extSecret != NULL))
+        XXH3_initCustomSecret(statePtr->customSecret, seed);
+    XXH3_reset_internal(statePtr, seed, NULL, XXH_SECRET_DEFAULT_SIZE);
+    return XXH_OK;
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH_errorcode
+XXH3_64bits_reset_withSecretandSeed(XXH_NOESCAPE XXH3_state_t* statePtr, XXH_NOESCAPE const void* secret, size_t secretSize, XXH64_hash_t seed64)
+{
+    if (statePtr == NULL) return XXH_ERROR;
+    if (secret == NULL) return XXH_ERROR;
+    if (secretSize < XXH3_SECRET_SIZE_MIN) return XXH_ERROR;
+    XXH3_reset_internal(statePtr, seed64, secret, secretSize);
+    statePtr->useSeed = 1; /* always, even if seed64==0 */
+    return XXH_OK;
+}
+
+/*!
+ * @internal
+ * @brief Processes a large input for XXH3_update() and XXH3_digest_long().
+ *
+ * Unlike XXH3_hashLong_internal_loop(), this can process data that overlaps a block.
+ *
+ * @param acc                Pointer to the 8 accumulator lanes
+ * @param nbStripesSoFarPtr  In/out pointer to the number of leftover stripes in the block*
+ * @param nbStripesPerBlock  Number of stripes in a block
+ * @param input              Input pointer
+ * @param nbStripes          Number of stripes to process
+ * @param secret             Secret pointer
+ * @param secretLimit        Offset of the last block in @p secret
+ * @param f_acc              Pointer to an XXH3_accumulate implementation
+ * @param f_scramble         Pointer to an XXH3_scrambleAcc implementation
+ * @return                   Pointer past the end of @p input after processing
+ */
+XXH_FORCE_INLINE const xxh_u8 *
+XXH3_consumeStripes(xxh_u64* XXH_RESTRICT acc,
+                    size_t* XXH_RESTRICT nbStripesSoFarPtr, size_t nbStripesPerBlock,
+                    const xxh_u8* XXH_RESTRICT input, size_t nbStripes,
+                    const xxh_u8* XXH_RESTRICT secret, size_t secretLimit,
+                    XXH3_f_accumulate f_acc,
+                    XXH3_f_scrambleAcc f_scramble)
+{
+    const xxh_u8* initialSecret = secret + *nbStripesSoFarPtr * XXH_SECRET_CONSUME_RATE;
+    /* Process full blocks */
+    if (nbStripes >= (nbStripesPerBlock - *nbStripesSoFarPtr)) {
+        /* Process the initial partial block... */
+        size_t nbStripesThisIter = nbStripesPerBlock - *nbStripesSoFarPtr;
+
+        do {
+            /* Accumulate and scramble */
+            f_acc(acc, input, initialSecret, nbStripesThisIter);
+            f_scramble(acc, secret + secretLimit);
+            input += nbStripesThisIter * XXH_STRIPE_LEN;
+            nbStripes -= nbStripesThisIter;
+            /* Then continue the loop with the full block size */
+            nbStripesThisIter = nbStripesPerBlock;
+            initialSecret = secret;
+        } while (nbStripes >= nbStripesPerBlock);
+        *nbStripesSoFarPtr = 0;
+    }
+    /* Process a partial block */
+    if (nbStripes > 0) {
+        f_acc(acc, input, initialSecret, nbStripes);
+        input += nbStripes * XXH_STRIPE_LEN;
+        *nbStripesSoFarPtr += nbStripes;
+    }
+    /* Return end pointer */
+    return input;
+}
+
+#ifndef XXH3_STREAM_USE_STACK
+# if XXH_SIZE_OPT <= 0 && !defined(__clang__) /* clang doesn't need additional stack space */
+#   define XXH3_STREAM_USE_STACK 1
+# endif
+#endif
+/*
+ * Both XXH3_64bits_update and XXH3_128bits_update use this routine.
+ */
+XXH_FORCE_INLINE XXH_errorcode
+XXH3_update(XXH3_state_t* XXH_RESTRICT const state,
+            const xxh_u8* XXH_RESTRICT input, size_t len,
+            XXH3_f_accumulate f_acc,
+            XXH3_f_scrambleAcc f_scramble)
+{
+    if (input==NULL) {
+        XXH_ASSERT(len == 0);
+        return XXH_OK;
+    }
+
+    XXH_ASSERT(state != NULL);
+    {   const xxh_u8* const bEnd = input + len;
+        const unsigned char* const secret = (state->extSecret == NULL) ? state->customSecret : state->extSecret;
+#if defined(XXH3_STREAM_USE_STACK) && XXH3_STREAM_USE_STACK >= 1
+        /* For some reason, gcc and MSVC seem to suffer greatly
+         * when operating accumulators directly into state.
+         * Operating into stack space seems to enable proper optimization.
+         * clang, on the other hand, doesn't seem to need this trick */
+        XXH_ALIGN(XXH_ACC_ALIGN) xxh_u64 acc[8];
+        XXH_memcpy(acc, state->acc, sizeof(acc));
+#else
+        xxh_u64* XXH_RESTRICT const acc = state->acc;
+#endif
+        state->totalLen += len;
+        XXH_ASSERT(state->bufferedSize <= XXH3_INTERNALBUFFER_SIZE);
+
+        /* small input : just fill in tmp buffer */
+        if (len <= XXH3_INTERNALBUFFER_SIZE - state->bufferedSize) {
+            XXH_memcpy(state->buffer + state->bufferedSize, input, len);
+            state->bufferedSize += (XXH32_hash_t)len;
+            return XXH_OK;
+        }
+
+        /* total input is now > XXH3_INTERNALBUFFER_SIZE */
+        #define XXH3_INTERNALBUFFER_STRIPES (XXH3_INTERNALBUFFER_SIZE / XXH_STRIPE_LEN)
+        XXH_STATIC_ASSERT(XXH3_INTERNALBUFFER_SIZE % XXH_STRIPE_LEN == 0);   /* clean multiple */
+
+        /*
+         * Internal buffer is partially filled (always, except at beginning)
+         * Complete it, then consume it.
+         */
+        if (state->bufferedSize) {
+            size_t const loadSize = XXH3_INTERNALBUFFER_SIZE - state->bufferedSize;
+            XXH_memcpy(state->buffer + state->bufferedSize, input, loadSize);
+            input += loadSize;
+            XXH3_consumeStripes(acc,
+                               &state->nbStripesSoFar, state->nbStripesPerBlock,
+                                state->buffer, XXH3_INTERNALBUFFER_STRIPES,
+                                secret, state->secretLimit,
+                                f_acc, f_scramble);
+            state->bufferedSize = 0;
+        }
+        XXH_ASSERT(input < bEnd);
+        if (bEnd - input > XXH3_INTERNALBUFFER_SIZE) {
+            size_t nbStripes = (size_t)(bEnd - 1 - input) / XXH_STRIPE_LEN;
+            input = XXH3_consumeStripes(acc,
+                                       &state->nbStripesSoFar, state->nbStripesPerBlock,
+                                       input, nbStripes,
+                                       secret, state->secretLimit,
+                                       f_acc, f_scramble);
+            XXH_memcpy(state->buffer + sizeof(state->buffer) - XXH_STRIPE_LEN, input - XXH_STRIPE_LEN, XXH_STRIPE_LEN);
+
+        }
+        /* Some remaining input (always) : buffer it */
+        XXH_ASSERT(input < bEnd);
+        XXH_ASSERT(bEnd - input <= XXH3_INTERNALBUFFER_SIZE);
+        XXH_ASSERT(state->bufferedSize == 0);
+        XXH_memcpy(state->buffer, input, (size_t)(bEnd-input));
+        state->bufferedSize = (XXH32_hash_t)(bEnd-input);
+#if defined(XXH3_STREAM_USE_STACK) && XXH3_STREAM_USE_STACK >= 1
+        /* save stack accumulators into state */
+        XXH_memcpy(state->acc, acc, sizeof(acc));
+#endif
+    }
+
+    return XXH_OK;
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH_errorcode
+XXH3_64bits_update(XXH_NOESCAPE XXH3_state_t* state, XXH_NOESCAPE const void* input, size_t len)
+{
+    return XXH3_update(state, (const xxh_u8*)input, len,
+                       XXH3_accumulate, XXH3_scrambleAcc);
+}
+
+
+XXH_FORCE_INLINE void
+XXH3_digest_long (XXH64_hash_t* acc,
+                  const XXH3_state_t* state,
+                  const unsigned char* secret)
+{
+    xxh_u8 lastStripe[XXH_STRIPE_LEN];
+    const xxh_u8* lastStripePtr;
+
+    /*
+     * Digest on a local copy. This way, the state remains unaltered, and it can
+     * continue ingesting more input afterwards.
+     */
+    XXH_memcpy(acc, state->acc, sizeof(state->acc));
+    if (state->bufferedSize >= XXH_STRIPE_LEN) {
+        /* Consume remaining stripes then point to remaining data in buffer */
+        size_t const nbStripes = (state->bufferedSize - 1) / XXH_STRIPE_LEN;
+        size_t nbStripesSoFar = state->nbStripesSoFar;
+        XXH3_consumeStripes(acc,
+                           &nbStripesSoFar, state->nbStripesPerBlock,
+                            state->buffer, nbStripes,
+                            secret, state->secretLimit,
+                            XXH3_accumulate, XXH3_scrambleAcc);
+        lastStripePtr = state->buffer + state->bufferedSize - XXH_STRIPE_LEN;
+    } else {  /* bufferedSize < XXH_STRIPE_LEN */
+        /* Copy to temp buffer */
+        size_t const catchupSize = XXH_STRIPE_LEN - state->bufferedSize;
+        XXH_ASSERT(state->bufferedSize > 0);  /* there is always some input buffered */
+        XXH_memcpy(lastStripe, state->buffer + sizeof(state->buffer) - catchupSize, catchupSize);
+        XXH_memcpy(lastStripe + catchupSize, state->buffer, state->bufferedSize);
+        lastStripePtr = lastStripe;
+    }
+    /* Last stripe */
+    XXH3_accumulate_512(acc,
+                        lastStripePtr,
+                        secret + state->secretLimit - XXH_SECRET_LASTACC_START);
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH64_hash_t XXH3_64bits_digest (XXH_NOESCAPE const XXH3_state_t* state)
+{
+    const unsigned char* const secret = (state->extSecret == NULL) ? state->customSecret : state->extSecret;
+    if (state->totalLen > XXH3_MIDSIZE_MAX) {
+        XXH_ALIGN(XXH_ACC_ALIGN) XXH64_hash_t acc[XXH_ACC_NB];
+        XXH3_digest_long(acc, state, secret);
+        return XXH3_mergeAccs(acc,
+                              secret + XXH_SECRET_MERGEACCS_START,
+                              (xxh_u64)state->totalLen * XXH_PRIME64_1);
+    }
+    /* totalLen <= XXH3_MIDSIZE_MAX: digesting a short input */
+    if (state->useSeed)
+        return XXH3_64bits_withSeed(state->buffer, (size_t)state->totalLen, state->seed);
+    return XXH3_64bits_withSecret(state->buffer, (size_t)(state->totalLen),
+                                  secret, state->secretLimit + XXH_STRIPE_LEN);
+}
+#endif /* !XXH_NO_STREAM */
+
+
+/* ==========================================
+ * XXH3 128 bits (a.k.a XXH128)
+ * ==========================================
+ * XXH3's 128-bit variant has better mixing and strength than the 64-bit variant,
+ * even without counting the significantly larger output size.
+ *
+ * For example, extra steps are taken to avoid the seed-dependent collisions
+ * in 17-240 byte inputs (See XXH3_mix16B and XXH128_mix32B).
+ *
+ * This strength naturally comes at the cost of some speed, especially on short
+ * lengths. Note that longer hashes are about as fast as the 64-bit version
+ * due to it using only a slight modification of the 64-bit loop.
+ *
+ * XXH128 is also more oriented towards 64-bit machines. It is still extremely
+ * fast for a _128-bit_ hash on 32-bit (it usually clears XXH64).
+ */
+
+XXH_FORCE_INLINE XXH_PUREF XXH128_hash_t
+XXH3_len_1to3_128b(const xxh_u8* input, size_t len, const xxh_u8* secret, XXH64_hash_t seed)
+{
+    /* A doubled version of 1to3_64b with different constants. */
+    XXH_ASSERT(input != NULL);
+    XXH_ASSERT(1 <= len && len <= 3);
+    XXH_ASSERT(secret != NULL);
+    /*
+     * len = 1: combinedl = { input[0], 0x01, input[0], input[0] }
+     * len = 2: combinedl = { input[1], 0x02, input[0], input[1] }
+     * len = 3: combinedl = { input[2], 0x03, input[0], input[1] }
+     */
+    {   xxh_u8 const c1 = input[0];
+        xxh_u8 const c2 = input[len >> 1];
+        xxh_u8 const c3 = input[len - 1];
+        xxh_u32 const combinedl = ((xxh_u32)c1 <<16) | ((xxh_u32)c2 << 24)
+                                | ((xxh_u32)c3 << 0) | ((xxh_u32)len << 8);
+        xxh_u32 const combinedh = XXH_rotl32(XXH_swap32(combinedl), 13);
+        xxh_u64 const bitflipl = (XXH_readLE32(secret) ^ XXH_readLE32(secret+4)) + seed;
+        xxh_u64 const bitfliph = (XXH_readLE32(secret+8) ^ XXH_readLE32(secret+12)) - seed;
+        xxh_u64 const keyed_lo = (xxh_u64)combinedl ^ bitflipl;
+        xxh_u64 const keyed_hi = (xxh_u64)combinedh ^ bitfliph;
+        XXH128_hash_t h128;
+        h128.low64  = XXH64_avalanche(keyed_lo);
+        h128.high64 = XXH64_avalanche(keyed_hi);
+        return h128;
+    }
+}
+
+XXH_FORCE_INLINE XXH_PUREF XXH128_hash_t
+XXH3_len_4to8_128b(const xxh_u8* input, size_t len, const xxh_u8* secret, XXH64_hash_t seed)
+{
+    XXH_ASSERT(input != NULL);
+    XXH_ASSERT(secret != NULL);
+    XXH_ASSERT(4 <= len && len <= 8);
+    seed ^= (xxh_u64)XXH_swap32((xxh_u32)seed) << 32;
+    {   xxh_u32 const input_lo = XXH_readLE32(input);
+        xxh_u32 const input_hi = XXH_readLE32(input + len - 4);
+        xxh_u64 const input_64 = input_lo + ((xxh_u64)input_hi << 32);
+        xxh_u64 const bitflip = (XXH_readLE64(secret+16) ^ XXH_readLE64(secret+24)) + seed;
+        xxh_u64 const keyed = input_64 ^ bitflip;
+
+        /* Shift len to the left to ensure it is even, this avoids even multiplies. */
+        XXH128_hash_t m128 = XXH_mult64to128(keyed, XXH_PRIME64_1 + (len << 2));
+
+        m128.high64 += (m128.low64 << 1);
+        m128.low64  ^= (m128.high64 >> 3);
+
+        m128.low64   = XXH_xorshift64(m128.low64, 35);
+        m128.low64  *= PRIME_MX2;
+        m128.low64   = XXH_xorshift64(m128.low64, 28);
+        m128.high64  = XXH3_avalanche(m128.high64);
+        return m128;
+    }
+}
+
+XXH_FORCE_INLINE XXH_PUREF XXH128_hash_t
+XXH3_len_9to16_128b(const xxh_u8* input, size_t len, const xxh_u8* secret, XXH64_hash_t seed)
+{
+    XXH_ASSERT(input != NULL);
+    XXH_ASSERT(secret != NULL);
+    XXH_ASSERT(9 <= len && len <= 16);
+    {   xxh_u64 const bitflipl = (XXH_readLE64(secret+32) ^ XXH_readLE64(secret+40)) - seed;
+        xxh_u64 const bitfliph = (XXH_readLE64(secret+48) ^ XXH_readLE64(secret+56)) + seed;
+        xxh_u64 const input_lo = XXH_readLE64(input);
+        xxh_u64       input_hi = XXH_readLE64(input + len - 8);
+        XXH128_hash_t m128 = XXH_mult64to128(input_lo ^ input_hi ^ bitflipl, XXH_PRIME64_1);
+        /*
+         * Put len in the middle of m128 to ensure that the length gets mixed to
+         * both the low and high bits in the 128x64 multiply below.
+         */
+        m128.low64 += (xxh_u64)(len - 1) << 54;
+        input_hi   ^= bitfliph;
+        /*
+         * Add the high 32 bits of input_hi to the high 32 bits of m128, then
+         * add the long product of the low 32 bits of input_hi and XXH_PRIME32_2 to
+         * the high 64 bits of m128.
+         *
+         * The best approach to this operation is different on 32-bit and 64-bit.
+         */
+        if (sizeof(void *) < sizeof(xxh_u64)) { /* 32-bit */
+            /*
+             * 32-bit optimized version, which is more readable.
+             *
+             * On 32-bit, it removes an ADC and delays a dependency between the two
+             * halves of m128.high64, but it generates an extra mask on 64-bit.
+             */
+            m128.high64 += (input_hi & 0xFFFFFFFF00000000ULL) + XXH_mult32to64((xxh_u32)input_hi, XXH_PRIME32_2);
+        } else {
+            /*
+             * 64-bit optimized (albeit more confusing) version.
+             *
+             * Uses some properties of addition and multiplication to remove the mask:
+             *
+             * Let:
+             *    a = input_hi.lo = (input_hi & 0x00000000FFFFFFFF)
+             *    b = input_hi.hi = (input_hi & 0xFFFFFFFF00000000)
+             *    c = XXH_PRIME32_2
+             *
+             *    a + (b * c)
+             * Inverse Property: x + y - x == y
+             *    a + (b * (1 + c - 1))
+             * Distributive Property: x * (y + z) == (x * y) + (x * z)
+             *    a + (b * 1) + (b * (c - 1))
+             * Identity Property: x * 1 == x
+             *    a + b + (b * (c - 1))
+             *
+             * Substitute a, b, and c:
+             *    input_hi.hi + input_hi.lo + ((xxh_u64)input_hi.lo * (XXH_PRIME32_2 - 1))
+             *
+             * Since input_hi.hi + input_hi.lo == input_hi, we get this:
+             *    input_hi + ((xxh_u64)input_hi.lo * (XXH_PRIME32_2 - 1))
+             */
+            m128.high64 += input_hi + XXH_mult32to64((xxh_u32)input_hi, XXH_PRIME32_2 - 1);
+        }
+        /* m128 ^= XXH_swap64(m128 >> 64); */
+        m128.low64  ^= XXH_swap64(m128.high64);
+
+        {   /* 128x64 multiply: h128 = m128 * XXH_PRIME64_2; */
+            XXH128_hash_t h128 = XXH_mult64to128(m128.low64, XXH_PRIME64_2);
+            h128.high64 += m128.high64 * XXH_PRIME64_2;
+
+            h128.low64   = XXH3_avalanche(h128.low64);
+            h128.high64  = XXH3_avalanche(h128.high64);
+            return h128;
+    }   }
+}
+
+/*
+ * Assumption: `secret` size is >= XXH3_SECRET_SIZE_MIN
+ */
+XXH_FORCE_INLINE XXH_PUREF XXH128_hash_t
+XXH3_len_0to16_128b(const xxh_u8* input, size_t len, const xxh_u8* secret, XXH64_hash_t seed)
+{
+    XXH_ASSERT(len <= 16);
+    {   if (len > 8) return XXH3_len_9to16_128b(input, len, secret, seed);
+        if (len >= 4) return XXH3_len_4to8_128b(input, len, secret, seed);
+        if (len) return XXH3_len_1to3_128b(input, len, secret, seed);
+        {   XXH128_hash_t h128;
+            xxh_u64 const bitflipl = XXH_readLE64(secret+64) ^ XXH_readLE64(secret+72);
+            xxh_u64 const bitfliph = XXH_readLE64(secret+80) ^ XXH_readLE64(secret+88);
+            h128.low64 = XXH64_avalanche(seed ^ bitflipl);
+            h128.high64 = XXH64_avalanche( seed ^ bitfliph);
+            return h128;
+    }   }
+}
+
+/*
+ * A bit slower than XXH3_mix16B, but handles multiply by zero better.
+ */
+XXH_FORCE_INLINE XXH128_hash_t
+XXH128_mix32B(XXH128_hash_t acc, const xxh_u8* input_1, const xxh_u8* input_2,
+              const xxh_u8* secret, XXH64_hash_t seed)
+{
+    acc.low64  += XXH3_mix16B (input_1, secret+0, seed);
+    acc.low64  ^= XXH_readLE64(input_2) + XXH_readLE64(input_2 + 8);
+    acc.high64 += XXH3_mix16B (input_2, secret+16, seed);
+    acc.high64 ^= XXH_readLE64(input_1) + XXH_readLE64(input_1 + 8);
+    return acc;
+}
+
+
+XXH_FORCE_INLINE XXH_PUREF XXH128_hash_t
+XXH3_len_17to128_128b(const xxh_u8* XXH_RESTRICT input, size_t len,
+                      const xxh_u8* XXH_RESTRICT secret, size_t secretSize,
+                      XXH64_hash_t seed)
+{
+    XXH_ASSERT(secretSize >= XXH3_SECRET_SIZE_MIN); (void)secretSize;
+    XXH_ASSERT(16 < len && len <= 128);
+
+    {   XXH128_hash_t acc;
+        acc.low64 = len * XXH_PRIME64_1;
+        acc.high64 = 0;
+
+#if XXH_SIZE_OPT >= 1
+        {
+            /* Smaller, but slightly slower. */
+            unsigned int i = (unsigned int)(len - 1) / 32;
+            do {
+                acc = XXH128_mix32B(acc, input+16*i, input+len-16*(i+1), secret+32*i, seed);
+            } while (i-- != 0);
+        }
+#else
+        if (len > 32) {
+            if (len > 64) {
+                if (len > 96) {
+                    acc = XXH128_mix32B(acc, input+48, input+len-64, secret+96, seed);
+                }
+                acc = XXH128_mix32B(acc, input+32, input+len-48, secret+64, seed);
+            }
+            acc = XXH128_mix32B(acc, input+16, input+len-32, secret+32, seed);
+        }
+        acc = XXH128_mix32B(acc, input, input+len-16, secret, seed);
+#endif
+        {   XXH128_hash_t h128;
+            h128.low64  = acc.low64 + acc.high64;
+            h128.high64 = (acc.low64    * XXH_PRIME64_1)
+                        + (acc.high64   * XXH_PRIME64_4)
+                        + ((len - seed) * XXH_PRIME64_2);
+            h128.low64  = XXH3_avalanche(h128.low64);
+            h128.high64 = (XXH64_hash_t)0 - XXH3_avalanche(h128.high64);
+            return h128;
+        }
+    }
+}
+
+XXH_NO_INLINE XXH_PUREF XXH128_hash_t
+XXH3_len_129to240_128b(const xxh_u8* XXH_RESTRICT input, size_t len,
+                       const xxh_u8* XXH_RESTRICT secret, size_t secretSize,
+                       XXH64_hash_t seed)
+{
+    XXH_ASSERT(secretSize >= XXH3_SECRET_SIZE_MIN); (void)secretSize;
+    XXH_ASSERT(128 < len && len <= XXH3_MIDSIZE_MAX);
+
+    {   XXH128_hash_t acc;
+        unsigned i;
+        acc.low64 = len * XXH_PRIME64_1;
+        acc.high64 = 0;
+        /*
+         *  We set as `i` as offset + 32. We do this so that unchanged
+         * `len` can be used as upper bound. This reaches a sweet spot
+         * where both x86 and aarch64 get simple agen and good codegen
+         * for the loop.
+         */
+        for (i = 32; i < 160; i += 32) {
+            acc = XXH128_mix32B(acc,
+                                input  + i - 32,
+                                input  + i - 16,
+                                secret + i - 32,
+                                seed);
+        }
+        acc.low64 = XXH3_avalanche(acc.low64);
+        acc.high64 = XXH3_avalanche(acc.high64);
+        /*
+         * NB: `i <= len` will duplicate the last 32-bytes if
+         * len % 32 was zero. This is an unfortunate necessity to keep
+         * the hash result stable.
+         */
+        for (i=160; i <= len; i += 32) {
+            acc = XXH128_mix32B(acc,
+                                input + i - 32,
+                                input + i - 16,
+                                secret + XXH3_MIDSIZE_STARTOFFSET + i - 160,
+                                seed);
+        }
+        /* last bytes */
+        acc = XXH128_mix32B(acc,
+                            input + len - 16,
+                            input + len - 32,
+                            secret + XXH3_SECRET_SIZE_MIN - XXH3_MIDSIZE_LASTOFFSET - 16,
+                            (XXH64_hash_t)0 - seed);
+
+        {   XXH128_hash_t h128;
+            h128.low64  = acc.low64 + acc.high64;
+            h128.high64 = (acc.low64    * XXH_PRIME64_1)
+                        + (acc.high64   * XXH_PRIME64_4)
+                        + ((len - seed) * XXH_PRIME64_2);
+            h128.low64  = XXH3_avalanche(h128.low64);
+            h128.high64 = (XXH64_hash_t)0 - XXH3_avalanche(h128.high64);
+            return h128;
+        }
+    }
+}
+
+XXH_FORCE_INLINE XXH128_hash_t
+XXH3_hashLong_128b_internal(const void* XXH_RESTRICT input, size_t len,
+                            const xxh_u8* XXH_RESTRICT secret, size_t secretSize,
+                            XXH3_f_accumulate f_acc,
+                            XXH3_f_scrambleAcc f_scramble)
+{
+    XXH_ALIGN(XXH_ACC_ALIGN) xxh_u64 acc[XXH_ACC_NB] = XXH3_INIT_ACC;
+
+    XXH3_hashLong_internal_loop(acc, (const xxh_u8*)input, len, secret, secretSize, f_acc, f_scramble);
+
+    /* converge into final hash */
+    XXH_STATIC_ASSERT(sizeof(acc) == 64);
+    XXH_ASSERT(secretSize >= sizeof(acc) + XXH_SECRET_MERGEACCS_START);
+    {   XXH128_hash_t h128;
+        h128.low64  = XXH3_mergeAccs(acc,
+                                     secret + XXH_SECRET_MERGEACCS_START,
+                                     (xxh_u64)len * XXH_PRIME64_1);
+        h128.high64 = XXH3_mergeAccs(acc,
+                                     secret + secretSize
+                                            - sizeof(acc) - XXH_SECRET_MERGEACCS_START,
+                                     ~((xxh_u64)len * XXH_PRIME64_2));
+        return h128;
+    }
+}
+
+/*
+ * It's important for performance that XXH3_hashLong() is not inlined.
+ */
+XXH_NO_INLINE XXH_PUREF XXH128_hash_t
+XXH3_hashLong_128b_default(const void* XXH_RESTRICT input, size_t len,
+                           XXH64_hash_t seed64,
+                           const void* XXH_RESTRICT secret, size_t secretLen)
+{
+    (void)seed64; (void)secret; (void)secretLen;
+    return XXH3_hashLong_128b_internal(input, len, XXH3_kSecret, sizeof(XXH3_kSecret),
+                                       XXH3_accumulate, XXH3_scrambleAcc);
+}
+
+/*
+ * It's important for performance to pass @p secretLen (when it's static)
+ * to the compiler, so that it can properly optimize the vectorized loop.
+ *
+ * When the secret size is unknown, or on GCC 12 where the mix of NO_INLINE and FORCE_INLINE
+ * breaks -Og, this is XXH_NO_INLINE.
+ */
+XXH3_WITH_SECRET_INLINE XXH128_hash_t
+XXH3_hashLong_128b_withSecret(const void* XXH_RESTRICT input, size_t len,
+                              XXH64_hash_t seed64,
+                              const void* XXH_RESTRICT secret, size_t secretLen)
+{
+    (void)seed64;
+    return XXH3_hashLong_128b_internal(input, len, (const xxh_u8*)secret, secretLen,
+                                       XXH3_accumulate, XXH3_scrambleAcc);
+}
+
+XXH_FORCE_INLINE XXH128_hash_t
+XXH3_hashLong_128b_withSeed_internal(const void* XXH_RESTRICT input, size_t len,
+                                XXH64_hash_t seed64,
+                                XXH3_f_accumulate f_acc,
+                                XXH3_f_scrambleAcc f_scramble,
+                                XXH3_f_initCustomSecret f_initSec)
+{
+    if (seed64 == 0)
+        return XXH3_hashLong_128b_internal(input, len,
+                                           XXH3_kSecret, sizeof(XXH3_kSecret),
+                                           f_acc, f_scramble);
+    {   XXH_ALIGN(XXH_SEC_ALIGN) xxh_u8 secret[XXH_SECRET_DEFAULT_SIZE];
+        f_initSec(secret, seed64);
+        return XXH3_hashLong_128b_internal(input, len, (const xxh_u8*)secret, sizeof(secret),
+                                           f_acc, f_scramble);
+    }
+}
+
+/*
+ * It's important for performance that XXH3_hashLong is not inlined.
+ */
+XXH_NO_INLINE XXH128_hash_t
+XXH3_hashLong_128b_withSeed(const void* input, size_t len,
+                            XXH64_hash_t seed64, const void* XXH_RESTRICT secret, size_t secretLen)
+{
+    (void)secret; (void)secretLen;
+    return XXH3_hashLong_128b_withSeed_internal(input, len, seed64,
+                XXH3_accumulate, XXH3_scrambleAcc, XXH3_initCustomSecret);
+}
+
+typedef XXH128_hash_t (*XXH3_hashLong128_f)(const void* XXH_RESTRICT, size_t,
+                                            XXH64_hash_t, const void* XXH_RESTRICT, size_t);
+
+XXH_FORCE_INLINE XXH128_hash_t
+XXH3_128bits_internal(const void* input, size_t len,
+                      XXH64_hash_t seed64, const void* XXH_RESTRICT secret, size_t secretLen,
+                      XXH3_hashLong128_f f_hl128)
+{
+    XXH_ASSERT(secretLen >= XXH3_SECRET_SIZE_MIN);
+    /*
+     * If an action is to be taken if `secret` conditions are not respected,
+     * it should be done here.
+     * For now, it's a contract pre-condition.
+     * Adding a check and a branch here would cost performance at every hash.
+     */
+    if (len <= 16)
+        return XXH3_len_0to16_128b((const xxh_u8*)input, len, (const xxh_u8*)secret, seed64);
+    if (len <= 128)
+        return XXH3_len_17to128_128b((const xxh_u8*)input, len, (const xxh_u8*)secret, secretLen, seed64);
+    if (len <= XXH3_MIDSIZE_MAX)
+        return XXH3_len_129to240_128b((const xxh_u8*)input, len, (const xxh_u8*)secret, secretLen, seed64);
+    return f_hl128(input, len, seed64, secret, secretLen);
+}
+
+
+/* ===   Public XXH128 API   === */
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH128_hash_t XXH3_128bits(XXH_NOESCAPE const void* input, size_t len)
+{
+    return XXH3_128bits_internal(input, len, 0,
+                                 XXH3_kSecret, sizeof(XXH3_kSecret),
+                                 XXH3_hashLong_128b_default);
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH128_hash_t
+XXH3_128bits_withSecret(XXH_NOESCAPE const void* input, size_t len, XXH_NOESCAPE const void* secret, size_t secretSize)
+{
+    return XXH3_128bits_internal(input, len, 0,
+                                 (const xxh_u8*)secret, secretSize,
+                                 XXH3_hashLong_128b_withSecret);
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH128_hash_t
+XXH3_128bits_withSeed(XXH_NOESCAPE const void* input, size_t len, XXH64_hash_t seed)
+{
+    return XXH3_128bits_internal(input, len, seed,
+                                 XXH3_kSecret, sizeof(XXH3_kSecret),
+                                 XXH3_hashLong_128b_withSeed);
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH128_hash_t
+XXH3_128bits_withSecretandSeed(XXH_NOESCAPE const void* input, size_t len, XXH_NOESCAPE const void* secret, size_t secretSize, XXH64_hash_t seed)
+{
+    if (len <= XXH3_MIDSIZE_MAX)
+        return XXH3_128bits_internal(input, len, seed, XXH3_kSecret, sizeof(XXH3_kSecret), NULL);
+    return XXH3_hashLong_128b_withSecret(input, len, seed, secret, secretSize);
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH128_hash_t
+XXH128(XXH_NOESCAPE const void* input, size_t len, XXH64_hash_t seed)
+{
+    return XXH3_128bits_withSeed(input, len, seed);
+}
+
+
+/* ===   XXH3 128-bit streaming   === */
+#ifndef XXH_NO_STREAM
+/*
+ * All initialization and update functions are identical to 64-bit streaming variant.
+ * The only difference is the finalization routine.
+ */
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH_errorcode
+XXH3_128bits_reset(XXH_NOESCAPE XXH3_state_t* statePtr)
+{
+    return XXH3_64bits_reset(statePtr);
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH_errorcode
+XXH3_128bits_reset_withSecret(XXH_NOESCAPE XXH3_state_t* statePtr, XXH_NOESCAPE const void* secret, size_t secretSize)
+{
+    return XXH3_64bits_reset_withSecret(statePtr, secret, secretSize);
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH_errorcode
+XXH3_128bits_reset_withSeed(XXH_NOESCAPE XXH3_state_t* statePtr, XXH64_hash_t seed)
+{
+    return XXH3_64bits_reset_withSeed(statePtr, seed);
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH_errorcode
+XXH3_128bits_reset_withSecretandSeed(XXH_NOESCAPE XXH3_state_t* statePtr, XXH_NOESCAPE const void* secret, size_t secretSize, XXH64_hash_t seed)
+{
+    return XXH3_64bits_reset_withSecretandSeed(statePtr, secret, secretSize, seed);
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH_errorcode
+XXH3_128bits_update(XXH_NOESCAPE XXH3_state_t* state, XXH_NOESCAPE const void* input, size_t len)
+{
+    return XXH3_64bits_update(state, input, len);
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH128_hash_t XXH3_128bits_digest (XXH_NOESCAPE const XXH3_state_t* state)
+{
+    const unsigned char* const secret = (state->extSecret == NULL) ? state->customSecret : state->extSecret;
+    if (state->totalLen > XXH3_MIDSIZE_MAX) {
+        XXH_ALIGN(XXH_ACC_ALIGN) XXH64_hash_t acc[XXH_ACC_NB];
+        XXH3_digest_long(acc, state, secret);
+        XXH_ASSERT(state->secretLimit + XXH_STRIPE_LEN >= sizeof(acc) + XXH_SECRET_MERGEACCS_START);
+        {   XXH128_hash_t h128;
+            h128.low64  = XXH3_mergeAccs(acc,
+                                         secret + XXH_SECRET_MERGEACCS_START,
+                                         (xxh_u64)state->totalLen * XXH_PRIME64_1);
+            h128.high64 = XXH3_mergeAccs(acc,
+                                         secret + state->secretLimit + XXH_STRIPE_LEN
+                                                - sizeof(acc) - XXH_SECRET_MERGEACCS_START,
+                                         ~((xxh_u64)state->totalLen * XXH_PRIME64_2));
+            return h128;
+        }
+    }
+    /* len <= XXH3_MIDSIZE_MAX : short code */
+    if (state->useSeed)
+        return XXH3_128bits_withSeed(state->buffer, (size_t)state->totalLen, state->seed);
+    return XXH3_128bits_withSecret(state->buffer, (size_t)(state->totalLen),
+                                   secret, state->secretLimit + XXH_STRIPE_LEN);
+}
+#endif /* !XXH_NO_STREAM */
+/* 128-bit utility functions */
+
+#include    /* memcmp, memcpy */
+
+/* return : 1 is equal, 0 if different */
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API int XXH128_isEqual(XXH128_hash_t h1, XXH128_hash_t h2)
+{
+    /* note : XXH128_hash_t is compact, it has no padding byte */
+    return !(memcmp(&h1, &h2, sizeof(h1)));
+}
+
+/* This prototype is compatible with stdlib's qsort().
+ * @return : >0 if *h128_1  > *h128_2
+ *           <0 if *h128_1  < *h128_2
+ *           =0 if *h128_1 == *h128_2  */
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API int XXH128_cmp(XXH_NOESCAPE const void* h128_1, XXH_NOESCAPE const void* h128_2)
+{
+    XXH128_hash_t const h1 = *(const XXH128_hash_t*)h128_1;
+    XXH128_hash_t const h2 = *(const XXH128_hash_t*)h128_2;
+    int const hcmp = (h1.high64 > h2.high64) - (h2.high64 > h1.high64);
+    /* note : bets that, in most cases, hash values are different */
+    if (hcmp) return hcmp;
+    return (h1.low64 > h2.low64) - (h2.low64 > h1.low64);
+}
+
+
+/*======   Canonical representation   ======*/
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API void
+XXH128_canonicalFromHash(XXH_NOESCAPE XXH128_canonical_t* dst, XXH128_hash_t hash)
+{
+    XXH_STATIC_ASSERT(sizeof(XXH128_canonical_t) == sizeof(XXH128_hash_t));
+    if (XXH_CPU_LITTLE_ENDIAN) {
+        hash.high64 = XXH_swap64(hash.high64);
+        hash.low64  = XXH_swap64(hash.low64);
+    }
+    XXH_memcpy(dst, &hash.high64, sizeof(hash.high64));
+    XXH_memcpy((char*)dst + sizeof(hash.high64), &hash.low64, sizeof(hash.low64));
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH128_hash_t
+XXH128_hashFromCanonical(XXH_NOESCAPE const XXH128_canonical_t* src)
+{
+    XXH128_hash_t h;
+    h.high64 = XXH_readBE64(src);
+    h.low64  = XXH_readBE64(src->digest + 8);
+    return h;
+}
+
+
+
+/* ==========================================
+ * Secret generators
+ * ==========================================
+ */
+#define XXH_MIN(x, y) (((x) > (y)) ? (y) : (x))
+
+XXH_FORCE_INLINE void XXH3_combine16(void* dst, XXH128_hash_t h128)
+{
+    XXH_writeLE64( dst, XXH_readLE64(dst) ^ h128.low64 );
+    XXH_writeLE64( (char*)dst+8, XXH_readLE64((char*)dst+8) ^ h128.high64 );
+}
+
+/*! @ingroup XXH3_family */
+XXH_PUBLIC_API XXH_errorcode
+XXH3_generateSecret(XXH_NOESCAPE void* secretBuffer, size_t secretSize, XXH_NOESCAPE const void* customSeed, size_t customSeedSize)
+{
+#if (XXH_DEBUGLEVEL >= 1)
+    XXH_ASSERT(secretBuffer != NULL);
+    XXH_ASSERT(secretSize >= XXH3_SECRET_SIZE_MIN);
+#else
+    /* production mode, assert() are disabled */
+    if (secretBuffer == NULL) return XXH_ERROR;
+    if (secretSize < XXH3_SECRET_SIZE_MIN) return XXH_ERROR;
+#endif
+
+    if (customSeedSize == 0) {
+        customSeed = XXH3_kSecret;
+        customSeedSize = XXH_SECRET_DEFAULT_SIZE;
+    }
+#if (XXH_DEBUGLEVEL >= 1)
+    XXH_ASSERT(customSeed != NULL);
+#else
+    if (customSeed == NULL) return XXH_ERROR;
+#endif
+
+    /* Fill secretBuffer with a copy of customSeed - repeat as needed */
+    {   size_t pos = 0;
+        while (pos < secretSize) {
+            size_t const toCopy = XXH_MIN((secretSize - pos), customSeedSize);
+            memcpy((char*)secretBuffer + pos, customSeed, toCopy);
+            pos += toCopy;
+    }   }
+
+    {   size_t const nbSeg16 = secretSize / 16;
+        size_t n;
+        XXH128_canonical_t scrambler;
+        XXH128_canonicalFromHash(&scrambler, XXH128(customSeed, customSeedSize, 0));
+        for (n=0; n   /* abort() */
+#include 
+#include 
+#include 
+#include 
+#include 
+#include 
+
+#include 
+#include 
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+#include "xxhash/xxhash.h"
+#include "sha1/sha1.h"
+#include "sha256/sha256.h"
+
+#ifdef __cplusplus
+}
+#endif
+
+
+// uuid.uuid5(uuid.NAMESPACE_URL, 'en.wikipedia.org/wiki/Llama.cpp')
+#define UUID_NAMESPACE_LLAMA_CPP "ef001206-dadc-5f6d-a15f-3359e577d4e5"
+#define UUID_NAMESPACE_LLAMA_CPP_HEX 0xef, 0x00, 0x12, 0x06, 0xda, 0xdc, 0x5f, 0x6d, 0xa1, 0x5f, 0x33, 0x59, 0xe5, 0x77, 0xd4, 0xe5
+
+
+#define HASH_TYPE_SHA256_STR "sha256"
+#define HASH_TYPE_SHA1_STR   "sha1"
+#define HASH_TYPE_XXH64_STR  "xxh64"
+#define HASH_TYPE_UUID_STR   "uuid"
+
+
+typedef enum {
+    HASH_EXIT_SUCCESS = 0, // All hash has been generated or validated
+    HASH_EXIT_FAILURE = 1, // Generic Failure
+    HASH_EXIT_MISMATCH = 2, // Hash mismatched during validation
+    HASH_EXIT_MANIFEST_MISSING_ENTRY = 3, // Hash attempted validation but missing entry in manifest
+    HASH_EXIT_MANIFEST_UNKNOWN_HASH = 4, // Manifest is present, but we do not know any hash format within it
+    HASH_EXIT_MANIFEST_FILE_ERROR = 5 // Manifest is either missing or not a known format
+} hash_exit_code_t;
+
+
+typedef enum {
+    HASH_MANIFEST_NOT_FOUND,
+    HASH_MANIFEST_MISMATCH,
+    HASH_MANIFEST_OK,
+} hash_manifest_result_t;
+
+
+struct hash_params {
+    std::string input;
+    bool xxh64 = false;
+    bool sha1 = false;
+    bool sha256 = false;
+    bool uuid = false;
+
+    bool no_layer = false;
+
+    bool manifest_is_usable = false;
+    std::string manifest_file;
+};
+
+struct manifest_check_params {
+    bool xxh64 = false;
+    bool sha1 = false;
+    bool sha256 = false;
+    bool uuid = false;
+};
+
+static char const * hash_manifest_result_to_str(hash_manifest_result_t value) {
+    switch (value) {
+        case HASH_MANIFEST_NOT_FOUND: return "Not Found";
+        case HASH_MANIFEST_MISMATCH: return "Mismatch";
+        case HASH_MANIFEST_OK: return "Ok";
+    }
+    return "?";
+}
+
+static char const * hash_exit_code_to_str(hash_exit_code_t value) {
+    switch (value) {
+        case HASH_EXIT_SUCCESS: return "Success";
+        case HASH_EXIT_FAILURE: return "Failure";
+        case HASH_EXIT_MISMATCH: return "Mismatch";
+        case HASH_EXIT_MANIFEST_MISSING_ENTRY: return "Manifest Missing Entry";
+        case HASH_EXIT_MANIFEST_UNKNOWN_HASH: return "Manifest Unknown Hash";
+        case HASH_EXIT_MANIFEST_FILE_ERROR: return "Manifest File Error";
+    }
+    return "?";
+}
+
+static void hash_print_usage(const char * executable) {
+    const hash_params default_params;
+    printf("\n");
+    printf("usage: %s [options] GGUF_IN\n", executable);
+    printf("\n");
+    printf("Hash a GGUF file");
+    printf("\n");
+    printf("options:\n");
+    printf("  -h, --help              show this help message and exit\n");
+    printf("      --xxh64             use xxh64 hash\n");
+    printf("      --sha1              use sha1 hash\n");
+    printf("      --sha256            use sha256 hash\n");
+    printf("      --all               use all hash\n");
+    printf("      --no-layer          exclude per layer hash\n");
+    printf("      --uuid              generate UUIDv5 ID\n");
+    printf("  -c, --check   verify against a manifest\n");
+    printf("\n");
+}
+
+static void hash_params_parse_ex(int argc, const char ** argv, hash_params & params) {
+    std::string arg;
+    bool invalid_param = false;
+    const std::string arg_prefix = "--";
+
+    int arg_idx = 1;
+    for (; arg_idx < argc && strncmp(argv[arg_idx], "--", 2) == 0; arg_idx++) {
+        arg = argv[arg_idx];
+        if (arg.compare(0, arg_prefix.size(), arg_prefix) == 0) {
+            std::replace(arg.begin(), arg.end(), '_', '-');
+        }
+
+        bool arg_found = false;
+        if (arg == "-h" || arg == "--help") {
+            hash_print_usage(argv[0]);
+            exit(0);
+        }
+
+        if (arg == "--xxh64") {
+            arg_found = true;
+            params.xxh64 = true;
+        }
+
+        if (arg == "--sha1") {
+            arg_found = true;
+            params.sha1 = true;
+        }
+
+        if (arg == "--uuid") {
+            arg_found = true;
+            params.uuid = true;
+        }
+
+        if (arg == "--sha256") {
+            arg_found = true;
+            params.sha256 = true;
+        }
+
+        if (arg == "--all") {
+            arg_found = true;
+            params.sha256 = true;
+            params.sha1 = true;
+            params.xxh64 = true;
+        }
+
+        if (arg == "--no-layer") {
+            arg_found = true;
+            params.no_layer = true;
+        }
+
+        if (arg == "-c" || arg == "--check") {
+            if (++arg_idx >= argc) {
+                invalid_param = true;
+                break;
+            }
+            arg_found = true;
+            params.manifest_file = argv[arg_idx];
+        }
+
+        if (!arg_found) {
+            throw std::invalid_argument("error: unknown argument: " + arg);
+        }
+    }
+
+    if (invalid_param) {
+        throw std::invalid_argument("error: invalid parameter for argument:" + arg);
+    }
+
+    if (argc - arg_idx < 1) {
+        throw std::invalid_argument("error: bad arguments");
+    }
+
+    params.input = argv[arg_idx++];
+}
+
+static bool hash_params_parse(int argc, const char ** argv, hash_params & params) {
+    bool result = true;
+    try {
+        hash_params_parse_ex(argc, argv, params);
+    }
+    catch (const std::invalid_argument & ex) {
+        fprintf(stderr, "%s\n", ex.what());
+        hash_print_usage(argv[0]);
+        exit(EXIT_FAILURE);
+    }
+    return result;
+}
+
+static bool manifest_type(const std::string & manifest_file, manifest_check_params & manifest_check) {
+    if (manifest_file.empty()) {
+        return false;
+    }
+
+    std::ifstream file(manifest_file);
+    if (!file.is_open()) {
+        return false;
+    }
+
+    std::string manifest_entry_line;
+    while (getline(file, manifest_entry_line)) {
+        // hash_type_str hash_str tensor_name
+        // e.g. 'xxh64     f66e9cd66a4396a0  test.gguf:tensor_0'
+        std::istringstream line_stream(manifest_entry_line);
+        std::string file_hash_type;
+        if (line_stream >> file_hash_type) {
+            if (file_hash_type == HASH_TYPE_SHA256_STR) {
+                manifest_check.sha256 = true;
+            } else if (file_hash_type == HASH_TYPE_SHA1_STR) {
+                manifest_check.sha1 = true;
+            } else if (file_hash_type == HASH_TYPE_XXH64_STR) {
+                manifest_check.xxh64 = true;
+            } else if (file_hash_type == HASH_TYPE_UUID_STR) {
+                manifest_check.uuid = true;
+            }
+        }
+    }
+
+    return true;
+}
+
+static hash_manifest_result_t manifest_verify(const std::string& manifest_file, const std::string& hash_type_str, const std::string& hash_str, const std::string& tensor_name) {
+    if (manifest_file.empty()) {
+        return HASH_MANIFEST_NOT_FOUND;
+    }
+
+    std::ifstream file(manifest_file);
+    if (!file.is_open()) {
+        return HASH_MANIFEST_NOT_FOUND;
+    }
+
+    std::string manifest_entry_line;
+    while (getline(file, manifest_entry_line)) {
+        std::istringstream line_stream(manifest_entry_line);
+        std::string file_hash_type;
+        std::string file_hash;
+        std::string file_tensor_name;
+        if (line_stream >> file_hash_type >> file_hash >> file_tensor_name) {
+            // Line parsed. Check hash validity
+
+            if (file_hash_type != hash_type_str) {
+                continue;
+            }
+
+            if (file_tensor_name != tensor_name) {
+                continue;
+            }
+
+            return (file_hash == hash_str) ? HASH_MANIFEST_OK : HASH_MANIFEST_MISMATCH;
+        }
+    }
+
+    return HASH_MANIFEST_NOT_FOUND;
+}
+
+static void generate_uuidv5(const unsigned char sha1_digest[20], unsigned char uuid[16]) {
+    // Ref: https://www.rfc-editor.org/rfc/rfc9562.html#section-5.5
+    // Assumes that digest was processed correctly with the expected namespace
+    for (int i = 0; i < 16; i++) {
+        uuid[i] = sha1_digest[i];
+    }
+
+    // Set bits corresponding to UUID ver 5
+    uuid[ 6] &= ~(0xF << 4);
+    uuid[ 6] |= (5 << 4);
+
+    // Set bits corresponding to UUID variant 0b10XX
+    uuid[ 8] &= ~(0xc << 4);
+    uuid[ 8] |= (0x8 << 4);
+}
+
+static hash_exit_code_t gguf_hash(const hash_params & hash_params) {
+    const std::string & fname = hash_params.input;
+    struct ggml_context * ctx_data = NULL;
+
+    struct gguf_init_params params = {
+        /*.no_alloc = */ false,
+        /*.ctx      = */ &ctx_data,
+    };
+
+    // xxh64 init
+    XXH64_state_t* xxh64_model_hash_state = NULL;
+    if (hash_params.xxh64) {
+        xxh64_model_hash_state = XXH64_createState();
+        if (xxh64_model_hash_state==NULL) {
+            abort();
+        }
+
+        XXH64_hash_t const seed = 0;
+        if (XXH64_reset(xxh64_model_hash_state, seed) == XXH_ERROR) {
+            abort();
+        }
+    }
+
+    // sha1 init
+    SHA1_CTX sha1_model_hash_ctx;
+    if (hash_params.sha1) {
+        SHA1Init(&sha1_model_hash_ctx);
+    }
+
+    // sha256 init
+    sha256_t sha256_model_hash_ctx;
+    if (hash_params.sha256) {
+        sha256_init(&sha256_model_hash_ctx);
+    }
+
+    // sha1 for uuid init
+    SHA1_CTX sha1_for_uuid_ctx;
+    if (hash_params.uuid) {
+        unsigned char const uuidv5_namespace[] = {UUID_NAMESPACE_LLAMA_CPP_HEX};
+        SHA1Init(&sha1_for_uuid_ctx);
+        SHA1Update( &sha1_for_uuid_ctx, (unsigned char const *)uuidv5_namespace, sizeof(uuidv5_namespace));
+    }
+
+    struct gguf_context * ctx = gguf_init_from_file(fname.c_str(), params);
+    const int n_tensors = gguf_get_n_tensors(ctx);
+    bool tensor_layer_in_manifest = false;
+    bool model_in_manifest = false;
+    bool tensor_layer_has_mismatch = false;
+    bool model_has_mismatch = false;
+    for (int i = 0; i < n_tensors; ++i) {
+        const char * name = gguf_get_tensor_name(ctx, i);
+        struct ggml_tensor * cur = ggml_get_tensor(ctx_data, name);
+        auto n_bytes = ggml_nbytes(cur);
+        auto *raw_data = cur->data;
+        const std::string tensor_layer_name = fname + ":" + name;
+
+        if (hash_params.xxh64) {
+
+            if (!hash_params.no_layer) {
+                // Per Layer Hash
+                XXH64_hash_t hash = XXH64(raw_data, n_bytes, 0);
+
+                char hex_result[17];
+                for (int  offset = 0; offset < 8; offset++) {
+                    unsigned int shift_bits_by = (8 * (8 - offset - 1));
+                    sprintf( ( hex_result + (2*offset)), "%02x", (unsigned char) (hash >> shift_bits_by)&0xff);
+                }
+
+                if (hash_params.manifest_is_usable) {
+                    hash_manifest_result_t verify_result = manifest_verify(hash_params.manifest_file, HASH_TYPE_XXH64_STR, hex_result, tensor_layer_name);
+
+                    switch (verify_result) {
+                        case HASH_MANIFEST_NOT_FOUND:
+                            break;
+                        case HASH_MANIFEST_MISMATCH:
+                            tensor_layer_in_manifest = true;
+                            tensor_layer_has_mismatch = true;
+                            break;
+                        case HASH_MANIFEST_OK:
+                            tensor_layer_in_manifest = true;
+                            break;
+                    }
+
+                    printf("%-8s  %-s  %s  -  %s\n", HASH_TYPE_XXH64_STR, hex_result, tensor_layer_name.c_str(), hash_manifest_result_to_str(verify_result));
+                } else {
+                    printf("%-8s  %-s  %s\n", HASH_TYPE_XXH64_STR, hex_result, tensor_layer_name.c_str());
+                }
+            }
+
+            // Overall Model Hash
+            if (XXH64_update(xxh64_model_hash_state, raw_data, n_bytes) == XXH_ERROR) abort();
+        }
+
+        if (hash_params.sha1) {
+
+            if (!hash_params.no_layer) {
+                // Per Layer Hash
+                char result[21]; // sha1 outputs 20 bytes
+                SHA1( result, (const char *)raw_data, n_bytes);
+
+                char hex_result[41] = {0};
+                for (int  offset = 0; offset < 20; offset++) {
+                    sprintf( ( hex_result + (2*offset)), "%02x", result[offset]&0xff);
+                }
+
+                if (hash_params.manifest_is_usable) {
+                    hash_manifest_result_t verify_result = manifest_verify(hash_params.manifest_file, HASH_TYPE_SHA1_STR, hex_result, tensor_layer_name);
+
+                    switch (verify_result) {
+                        case HASH_MANIFEST_NOT_FOUND:
+                            break;
+                        case HASH_MANIFEST_MISMATCH:
+                            tensor_layer_in_manifest = true;
+                            tensor_layer_has_mismatch = true;
+                            break;
+                        case HASH_MANIFEST_OK:
+                            tensor_layer_in_manifest = true;
+                            break;
+                    }
+
+                    printf("%-8s  %-s  %s  -  %s\n", HASH_TYPE_SHA1_STR, hex_result, tensor_layer_name.c_str(), hash_manifest_result_to_str(verify_result));
+                } else {
+                    printf("%-8s  %-s  %s\n", HASH_TYPE_SHA1_STR, hex_result, tensor_layer_name.c_str());
+                }
+            }
+
+            // Overall Model Hash
+            SHA1Update( &sha1_model_hash_ctx, (unsigned char const *)raw_data, n_bytes);
+        }
+
+        if (hash_params.sha256) {
+
+            if (!hash_params.no_layer) {
+                // Per Layer Hash
+                unsigned char result[SHA256_DIGEST_SIZE]; // sha256 outputs 32 bytes
+                sha256_hash((unsigned char*) result, (const unsigned char *)raw_data, n_bytes);
+
+                char hex_result[SHA256_DIGEST_SIZE * 2 + 1] = {0};
+                for (int  offset = 0; offset < SHA256_DIGEST_SIZE; offset++) {
+                    sprintf( ( hex_result + (2*offset)), "%02x", result[offset]&0xff);
+                }
+
+                if (hash_params.manifest_is_usable) {
+                    hash_manifest_result_t verify_result = manifest_verify(hash_params.manifest_file, HASH_TYPE_SHA256_STR, hex_result, tensor_layer_name);
+
+                    switch (verify_result) {
+                        case HASH_MANIFEST_NOT_FOUND:
+                            break;
+                        case HASH_MANIFEST_MISMATCH:
+                            tensor_layer_in_manifest = true;
+                            tensor_layer_has_mismatch = true;
+                            break;
+                        case HASH_MANIFEST_OK:
+                            tensor_layer_in_manifest = true;
+                            break;
+                    }
+
+                    printf("%-8s  %-s  %s  -  %s\n", HASH_TYPE_SHA256_STR, hex_result, tensor_layer_name.c_str(), hash_manifest_result_to_str(verify_result));
+                } else {
+                    printf("%-8s  %-s  %s\n", HASH_TYPE_SHA256_STR, hex_result, tensor_layer_name.c_str());
+                }
+            }
+
+            // Overall Model Hash
+            sha256_update( &sha256_model_hash_ctx, (unsigned char const *)raw_data, n_bytes);
+        }
+
+        if (hash_params.uuid) {
+            SHA1Update( &sha1_for_uuid_ctx, (unsigned char const *)raw_data, n_bytes);
+        }
+    }
+
+    if (hash_params.xxh64) {
+        XXH64_hash_t const hash = XXH64_digest(xxh64_model_hash_state);
+
+        char hex_result[17];
+        for (int  offset = 0; offset < 8; offset++) {
+            unsigned int shift_bits_by = (8 * (8 - offset - 1));
+            sprintf( ( hex_result + (2*offset)), "%02x", (unsigned char) (hash >> shift_bits_by)&0xff);
+        }
+
+        if (hash_params.manifest_is_usable) {
+            hash_manifest_result_t verify_result = manifest_verify(hash_params.manifest_file, HASH_TYPE_XXH64_STR, hex_result, fname);
+
+            switch (verify_result) {
+                case HASH_MANIFEST_NOT_FOUND:
+                    break;
+                case HASH_MANIFEST_MISMATCH:
+                    model_in_manifest = true;
+                    model_has_mismatch = true;
+                    break;
+                case HASH_MANIFEST_OK:
+                    model_in_manifest = true;
+                    break;
+            }
+
+            printf("%-8s  %-s  %s  -  %s\n", HASH_TYPE_XXH64_STR, hex_result, fname.c_str(), hash_manifest_result_to_str(verify_result));
+        } else {
+            printf("%-8s  %-s  %s\n", HASH_TYPE_XXH64_STR, hex_result, fname.c_str());
+        }
+    }
+
+    if (hash_params.sha1) {
+        unsigned char result[21];
+        SHA1Final(result, &sha1_model_hash_ctx);
+
+        char hex_result[41];
+        for (int  offset = 0; offset < 20; offset++) {
+            sprintf( ( hex_result + (2*offset)), "%02x", result[offset]&0xff);
+        }
+
+        if (hash_params.manifest_is_usable) {
+            hash_manifest_result_t verify_result = manifest_verify(hash_params.manifest_file, HASH_TYPE_SHA1_STR, hex_result, fname);
+
+            switch (verify_result) {
+                case HASH_MANIFEST_NOT_FOUND:
+                    break;
+                case HASH_MANIFEST_MISMATCH:
+                    model_in_manifest = true;
+                    model_has_mismatch = true;
+                    break;
+                case HASH_MANIFEST_OK:
+                    model_in_manifest = true;
+                    break;
+            }
+
+            printf("%-8s  %-s  %s  -  %s\n", HASH_TYPE_SHA1_STR, hex_result, fname.c_str(), hash_manifest_result_to_str(verify_result));
+        } else {
+            printf("%-8s  %-s  %s\n", HASH_TYPE_SHA1_STR, hex_result, fname.c_str());
+        }
+    }
+
+    if (hash_params.sha256) {
+        unsigned char result[SHA256_DIGEST_SIZE]; // sha256 outputs 32 bytes
+        sha256_final( &sha256_model_hash_ctx,  result);
+
+        char hex_result[SHA256_DIGEST_SIZE * 2 + 1] = {0};
+        for (int  offset = 0; offset < SHA256_DIGEST_SIZE; offset++) {
+            sprintf( ( hex_result + (2*offset)), "%02x", result[offset]&0xff);
+        }
+
+        if (hash_params.manifest_is_usable) {
+            hash_manifest_result_t verify_result = manifest_verify(hash_params.manifest_file, HASH_TYPE_SHA256_STR, hex_result, fname);
+
+            switch (verify_result) {
+                case HASH_MANIFEST_NOT_FOUND:
+                    break;
+                case HASH_MANIFEST_MISMATCH:
+                    model_in_manifest = true;
+                    model_has_mismatch = true;
+                    break;
+                case HASH_MANIFEST_OK:
+                    model_in_manifest = true;
+                    break;
+            }
+
+            printf("%-8s  %-s  %s  -  %s\n", HASH_TYPE_SHA256_STR, hex_result, fname.c_str(), hash_manifest_result_to_str(verify_result));
+        } else {
+            printf("%-8s  %-s  %s\n", HASH_TYPE_SHA256_STR, hex_result, fname.c_str());
+        }
+    }
+
+    if (hash_params.uuid) {
+        unsigned char result[21];
+        SHA1Final(result, &sha1_for_uuid_ctx);
+
+        unsigned char uuid[16];
+        generate_uuidv5(result, uuid);
+
+        char string_buffer[37] = {0};
+        sprintf(string_buffer, "%02x%02x%02x%02x-%02x%02x-%02x%02x-%02x%02x-%02x%02x%02x%02x%02x%02x",
+            uuid[0], uuid[1], uuid[2], uuid[3],
+            uuid[4], uuid[5], uuid[6], uuid[7],
+            uuid[8], uuid[9], uuid[10], uuid[11],
+            uuid[12], uuid[13], uuid[14], uuid[15]);
+
+        if (hash_params.manifest_is_usable) {
+            hash_manifest_result_t verify_result = manifest_verify(hash_params.manifest_file, HASH_TYPE_SHA256_STR, string_buffer, fname);
+
+            switch (verify_result) {
+                case HASH_MANIFEST_NOT_FOUND:
+                    break;
+                case HASH_MANIFEST_MISMATCH:
+                    model_in_manifest = true;
+                    model_has_mismatch = true;
+                    break;
+                case HASH_MANIFEST_OK:
+                    model_in_manifest = true;
+                    break;
+            }
+
+            printf("%-8s  %-s  %s  -  %s\n", HASH_TYPE_UUID_STR, string_buffer, fname.c_str(), hash_manifest_result_to_str(verify_result));
+        } else {
+            printf("%-8s  %-s  %s\n", HASH_TYPE_UUID_STR, string_buffer, fname.c_str());
+        }
+    }
+
+
+    ggml_free(ctx_data);
+    gguf_free(ctx);
+
+
+    if (hash_params.manifest_is_usable) {
+        // In hash verification mode
+
+        if (!model_in_manifest) {
+            // model missing in manifest?
+
+            // Check tensor layer...
+            if (!tensor_layer_in_manifest) {
+                // Still missing? Maybe we are reading the wrong manifest.
+                return HASH_EXIT_MANIFEST_MISSING_ENTRY;
+            }
+
+            if (tensor_layer_has_mismatch) {
+                // Per tensor check found error
+                return HASH_EXIT_FAILURE;
+            }
+
+            // All per tensor layer checks passed? Sounds good enough.
+            return HASH_EXIT_SUCCESS;
+        }
+
+        // Overall model check passed, but let's check per layer just in case
+        // If missing, we don't care too much as the overall model checked
+        if (tensor_layer_in_manifest && tensor_layer_has_mismatch) {
+            return HASH_EXIT_FAILURE;
+        }
+
+        if (model_has_mismatch) {
+            // model has failed hash somewhere in the model
+            return HASH_EXIT_FAILURE;
+        }
+
+        // All checks appears to be fine
+        return HASH_EXIT_SUCCESS;
+    }
+
+    // In hash generation mode
+    return HASH_EXIT_SUCCESS;
+}
+
+int main(int argc, const char ** argv) {
+    hash_params params;
+    manifest_check_params manifest_check;
+    hash_params_parse(argc, argv, params);
+
+    if (!params.manifest_file.empty()) {
+        if (!manifest_type(params.manifest_file, manifest_check)) {
+            printf("ERROR cannot open manifest %s", params.manifest_file.c_str());
+            return HASH_EXIT_MANIFEST_FILE_ERROR;
+        }
+
+        if (!manifest_check.sha256 && !manifest_check.sha1 && !manifest_check.xxh64 && !manifest_check.uuid) {
+            printf("ERROR manifest does not have any known hash format in %s", params.manifest_file.c_str());
+            return HASH_EXIT_MANIFEST_UNKNOWN_HASH;
+        }
+
+        printf("manifest  %s", params.manifest_file.c_str());
+
+        if (manifest_check.sha256) {
+            printf("  sha256");
+        }
+
+        if (manifest_check.sha1) {
+            printf("  sha1");
+        }
+
+        if (manifest_check.xxh64) {
+            printf("  xxh64");
+        }
+
+        if (manifest_check.uuid) {
+            printf("  uuid");
+        }
+
+        printf("\n");
+
+        // Autoselect the highest security hash if manifest is provided but
+        // the user has not specifically defined the hash they care about
+        if (!params.xxh64 && !params.sha1 && !params.uuid && !params.sha256) {
+            // User has not selected a specific value, pick most secure hash
+            if (manifest_check.sha256) {
+                params.sha256 = true;
+            } else if (manifest_check.sha1) {
+                params.sha1 = true;
+            } else if (manifest_check.xxh64) {
+                params.xxh64 = true;
+            } else if (manifest_check.uuid) {
+                params.uuid = true;
+            }
+        }
+
+        params.manifest_is_usable = true;
+    }
+
+    // By default if no swich argument provided, assume xxh64
+    if (!params.xxh64 && !params.sha1 && !params.uuid && !params.sha256) {
+        params.xxh64 = true;
+    }
+
+    hash_exit_code_t exit_code = gguf_hash(params);
+
+    if (params.manifest_is_usable) {
+        printf("\nVerification results for %s - %s\n", params.manifest_file.c_str(), hash_exit_code_to_str(exit_code));
+    }
+
+    return exit_code;
+}
diff --git a/gguf-py/scripts/gguf_hash.py b/gguf-py/scripts/gguf_hash.py
new file mode 100755
index 0000000000000..95677518209ed
--- /dev/null
+++ b/gguf-py/scripts/gguf_hash.py
@@ -0,0 +1,91 @@
+#!/usr/bin/env python3
+from __future__ import annotations
+
+import uuid
+import hashlib
+
+import logging
+import argparse
+import os
+import sys
+from pathlib import Path
+
+from tqdm import tqdm
+
+# Necessary to load the local gguf package
+if "NO_LOCAL_GGUF" not in os.environ and (Path(__file__).parent.parent.parent / 'gguf-py').exists():
+    sys.path.insert(0, str(Path(__file__).parent.parent))
+
+from gguf import GGUFReader  # noqa: E402
+
+
+logger = logging.getLogger("gguf-hash")
+
+# UUID_NAMESPACE_LLAMA_CPP = uuid.uuid5(uuid.NAMESPACE_URL, 'en.wikipedia.org/wiki/Llama.cpp')
+UUID_NAMESPACE_LLAMA_CPP = uuid.UUID('ef001206-dadc-5f6d-a15f-3359e577d4e5')
+
+
+# For more information about what field.parts and field.data represent,
+# please see the comments in the modify_gguf.py example.
+def gguf_hash(reader: GGUFReader, filename: str, disable_progress_bar) -> None:
+    sha1 = hashlib.sha1()
+    uuidv5_sha1 = hashlib.sha1()
+    uuidv5_sha1.update(UUID_NAMESPACE_LLAMA_CPP.bytes)
+
+    # Total Weight Calculation For Progress Bar
+    total_weights = 0
+    for n, tensor in enumerate(reader.tensors, 1):
+
+        # We don't need these
+        if tensor.name.endswith((".attention.masked_bias", ".attention.bias", ".rotary_emb.inv_freq")):
+            continue
+
+        # Calculate Tensor Volume
+        sum_weights_in_tensor = 1
+        for dim in tensor.shape:
+            sum_weights_in_tensor *= dim
+        total_weights += sum_weights_in_tensor
+
+    # Hash Progress Bar
+    bar = tqdm(desc="Hashing", total=total_weights, unit="weights", unit_scale=True, disable=disable_progress_bar)
+
+    # Hashing Process
+    for n, tensor in enumerate(reader.tensors, 1):
+
+        # We don't need these
+        if tensor.name.endswith((".attention.masked_bias", ".attention.bias", ".rotary_emb.inv_freq")):
+            continue
+
+        # Progressbar
+        sum_weights_in_tensor = 1
+        for dim in tensor.shape:
+            sum_weights_in_tensor *= dim
+        bar.update(sum_weights_in_tensor)
+
+        sha1_layer = hashlib.sha1()
+        sha1_layer.update(tensor.data)
+        sha1.update(tensor.data)
+        uuidv5_sha1.update(tensor.data)
+        print("sha1    {0}  {1}:{2}".format(sha1_layer.hexdigest(), filename, tensor.name)) # noqa: NP100
+
+    # Flush Hash Progress Bar
+    bar.close()
+
+    # Display Hash Output
+    print("sha1    {0}  {1}".format(sha1.hexdigest(), filename)) # noqa: NP100
+    print("UUIDv5  {0}  {1}".format(uuid.UUID(bytes=uuidv5_sha1.digest()[:16], version=5), filename)) # noqa: NP100
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Dump GGUF file metadata")
+    parser.add_argument("model",         type=str,            help="GGUF format model filename")
+    parser.add_argument("--verbose",     action="store_true", help="increase output verbosity")
+    parser.add_argument("--progressbar", action="store_true", help="enable progressbar")
+    args = parser.parse_args(None if len(sys.argv) > 1 else ["--help"])
+    logging.basicConfig(level=logging.DEBUG if args.verbose else logging.INFO)
+    reader = GGUFReader(args.model, 'r')
+    gguf_hash(reader, args.model, not args.progressbar)
+
+
+if __name__ == '__main__':
+    main()

From f1948f1e108157d5e7eb60fc8f24a10412e5d4ff Mon Sep 17 00:00:00 2001
From: Andy Tai 
Date: Sun, 7 Jul 2024 06:21:37 -0700
Subject: [PATCH 126/326] readme : update bindings list (#8222)

* adding guile_llama_cpp  to binding list

* fix formatting

* fix formatting
---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 800b499e9d516..aba6a4c59ada0 100644
--- a/README.md
+++ b/README.md
@@ -131,6 +131,7 @@ Typically finetunes of the base models below are supported as well.
 - Zig: [deins/llama.cpp.zig](https://github.com/Deins/llama.cpp.zig)
 - Flutter/Dart: [netdur/llama_cpp_dart](https://github.com/netdur/llama_cpp_dart)
 - PHP (API bindings and features built on top of llama.cpp): [distantmagic/resonance](https://github.com/distantmagic/resonance) [(more info)](https://github.com/ggerganov/llama.cpp/pull/6326)
+- Guile Scheme: [guile_llama_cpp](https://savannah.nongnu.org/projects/guile-llama-cpp)
 
 **UI:**
 

From 4090ea5501c702cd858095c394ba068919c56cc8 Mon Sep 17 00:00:00 2001
From: Alex Tuddenham <61622354+AlexsCode@users.noreply.github.com>
Date: Sun, 7 Jul 2024 15:59:14 +0100
Subject: [PATCH 127/326] ci : add checks for cmake,make and ctest in ci/run.sh
 (#8200)

* Added checks for cmake,make and ctest

* Removed erroneous whitespace
---
 ci/run.sh | 20 ++++++++++++++++++++
 1 file changed, 20 insertions(+)

diff --git a/ci/run.sh b/ci/run.sh
index 9703b77ce51db..58022c7dc37e0 100755
--- a/ci/run.sh
+++ b/ci/run.sh
@@ -103,6 +103,9 @@ function gg_run_ctest_debug {
 
     set -e
 
+    # Check cmake, make and ctest are installed
+    gg_check_build_requirements
+
     (time cmake -DCMAKE_BUILD_TYPE=Debug ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
     (time make -j                                          ) 2>&1 | tee -a $OUT/${ci}-make.log
 
@@ -131,6 +134,9 @@ function gg_run_ctest_release {
 
     set -e
 
+    # Check cmake, make and ctest are installed
+    gg_check_build_requirements
+
     (time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
     (time make -j                                            ) 2>&1 | tee -a $OUT/${ci}-make.log
 
@@ -701,6 +707,20 @@ function gg_run_embd_bge_small {
     set +e
 }
 
+function gg_check_build_requirements {
+    if ! command -v cmake &> /dev/null; then
+        gg_printf 'cmake not found, please install'
+    fi
+
+    if ! command -v make &> /dev/null; then
+        gg_printf 'make not found, please install'
+    fi
+
+    if ! command -v ctest &> /dev/null; then
+        gg_printf 'ctest not found, please install'
+    fi
+}
+
 function gg_sum_embd_bge_small {
     gg_printf '### %s\n\n' "${ci}"
 

From a8db2a9ce64cd4417f6a312ab61858f17f0f8584 Mon Sep 17 00:00:00 2001
From: Denis Spasyuk <34203011+dspasyuk@users.noreply.github.com>
Date: Sun, 7 Jul 2024 09:08:28 -0600
Subject: [PATCH 128/326] Update llama-cli documentation (#8315)

* Update README.md

* Update README.md

* Update README.md

fixed llama-cli/main, templates on some cmds added chat template sections and fixed typos in some areas

* Update README.md

* Update README.md

* Update README.md
---
 examples/main/README.md | 93 +++++++++++++++++++++--------------------
 1 file changed, 48 insertions(+), 45 deletions(-)

diff --git a/examples/main/README.md b/examples/main/README.md
index 61e4a42f7e02c..9396a34fa5a31 100644
--- a/examples/main/README.md
+++ b/examples/main/README.md
@@ -1,6 +1,6 @@
 # llama.cpp/examples/main
 
-This example program allows you to use various LLaMA language models in an easy and efficient way. It is specifically designed to work with the [llama.cpp](https://github.com/ggerganov/llama.cpp) project, which provides a plain C/C++ implementation with optional 4-bit quantization support for faster, lower memory inference, and is optimized for desktop CPUs. This program can be used to perform various inference tasks with LLaMA models, including generating text based on user-provided prompts and chat-like interactions with reverse prompts.
+This example program allows you to use various LLaMA language models easily and efficiently. It is specifically designed to work with the [llama.cpp](https://github.com/ggerganov/llama.cpp) project, which provides a plain C/C++ implementation with optional 4-bit quantization support for faster, lower memory inference, and is optimized for desktop CPUs. This program can be used to perform various inference tasks with LLaMA models, including generating text based on user-provided prompts and chat-like interactions with reverse prompts.
 
 ## Table of Contents
 
@@ -17,60 +17,59 @@ This example program allows you to use various LLaMA language models in an easy
 
 To get started right away, run the following command, making sure to use the correct path for the model you have:
 
-#### Unix-based systems (Linux, macOS, etc.):
+First, we will need to download a model. In these examples, we will use the Gemma model from the ggml-org repo on Hugging Face.
+[https://huggingface.co/ggml-org/gemma-1.1-7b-it-Q4_K_M-GGUF/resolve/main/gemma-1.1-7b-it.Q4_K_M.gguf?download=true](https://huggingface.co/ggml-org/gemma-1.1-7b-it-Q4_K_M-GGUF/resolve/main/gemma-1.1-7b-it.Q4_K_M.gguf?download=true)
 
-```bash
-./llama-cli -m models/7B/ggml-model.bin --prompt "Once upon a time"
-```
+Once downloaded, place your model in the models folder in llama.cpp.
 
-#### Windows:
+### Unix-based systems (Linux, macOS, etc.):
 
-```powershell
-llama-cli.exe -m models\7B\ggml-model.bin --prompt "Once upon a time"
-```
+##### Input prompt (One-and-done)
 
-For an interactive experience, try this command:
+```bash
+./llama-cli -m models/gemma-1.1-7b-it.Q4_K_M.gguf --prompt "Once upon a time"
+```
+##### Conversation mode (Allow for continuous interaction with the model)
 
-#### Unix-based systems (Linux, macOS, etc.):
+```bash
+./llama-cli -m models/gemma-1.1-7b-it.Q4_K_M.gguf -cnv --chat-template gemma
+```
 
+##### Infinite text from a starting prompt (you can use `Ctrl-C` to stop it):
 ```bash
-./llama-cli -m models/7B/ggml-model.bin -n -1 --color -r "User:" --in-prefix " " -i -p \
-'User: Hi
-AI: Hello. I am an AI chatbot. Would you like to talk?
-User: Sure!
-AI: What would you like to talk about?
-User:'
+./llama-cli -m models\gemma-1.1-7b-it.Q4_K_M.gguf --ignore-eos -n -1
 ```
 
-#### Windows:
+### Windows:
 
+##### Input prompt (One-and-done)
 ```powershell
-llama-cli.exe -m models\7B\ggml-model.bin -n -1 --color -r "User:" --in-prefix " " -i -e -p "User: Hi\nAI: Hello. I am an AI chatbot. Would you like to talk?\nUser: Sure!\nAI: What would you like to talk about?\nUser:"
+./llama-cli.exe -m models\gemma-1.1-7b-it.Q4_K_M.gguf --prompt "Once upon a time"
 ```
+##### Conversation mode (Allow for continuous interaction with the model)
 
-The following command generates "infinite" text from a starting prompt (you can use `Ctrl-C` to stop it):
-
-#### Unix-based systems (Linux, macOS, etc.):
-
-```bash
-./llama-cli -m models/7B/ggml-model.bin --ignore-eos -n -1
+```powershell
+./llama-cli.exe -m models\gemma-1.1-7b-it.Q4_K_M.gguf -cnv --chat-template gemma
 ```
 
-#### Windows:
+#### Infinite text from a starting prompt (you can use `Ctrl-C` to stop it):
 
 ```powershell
-llama-cli.exe -m models\7B\ggml-model.bin --ignore-eos -n -1
+llama-cli.exe -m models\gemma-1.1-7b-it.Q4_K_M.gguf --ignore-eos -n -1
 ```
 
 ## Common Options
 
 In this section, we cover the most commonly used options for running the `llama-cli` program with the LLaMA models:
 
--   `-m FNAME, --model FNAME`: Specify the path to the LLaMA model file (e.g., `models/7B/ggml-model.gguf`; inferred from `--model-url` if set).
--   `-mu MODEL_URL --model-url MODEL_URL`: Specify a remote http url to download the file (e.g https://huggingface.co/ggml-org/models/resolve/main/phi-2/ggml-model-q4_0.gguf).
+-   `-m FNAME, --model FNAME`: Specify the path to the LLaMA model file (e.g., `models/gemma-1.1-7b-it.Q4_K_M.gguf`; inferred from `--model-url` if set).
+-   `-mu MODEL_URL --model-url MODEL_URL`: Specify a remote http url to download the file (e.g [https://huggingface.co/ggml-org/gemma-1.1-7b-it-Q4_K_M-GGUF/resolve/main/gemma-1.1-7b-it.Q4_K_M.gguf?download=true](https://huggingface.co/ggml-org/gemma-1.1-7b-it-Q4_K_M-GGUF/resolve/main/gemma-1.1-7b-it.Q4_K_M.gguf?download=true)).
 -   `-i, --interactive`: Run the program in interactive mode, allowing you to provide input directly and receive real-time responses.
 -   `-n N, --n-predict N`: Set the number of tokens to predict when generating text. Adjusting this value can influence the length of the generated text.
 -   `-c N, --ctx-size N`: Set the size of the prompt context. The default is 512, but LLaMA models were built with a context of 2048, which will provide better results for longer input/inference.
+-   `-mli, --multiline-input`: Allows you to write or paste multiple lines without ending each in '\'
+-   `-t N, --threads N`: Set the number of threads to use during generation. For optimal performance, it is recommended to set this value to the number of physical CPU cores your system has.
+-   -   `-ngl N, --n-gpu-layers N`: When compiled with GPU support, this option allows offloading some layers to the GPU for computation. Generally results in increased performance.
 
 ## Input Prompts
 
@@ -90,6 +89,7 @@ In interactive mode, users can participate in text generation by injecting their
 
 -   `-i, --interactive`: Run the program in interactive mode, allowing users to engage in real-time conversations or provide specific instructions to the model.
 -   `--interactive-first`: Run the program in interactive mode and immediately wait for user input before starting the text generation.
+-   `-cnv,  --conversation`:  Run the program in conversation mode (does not print special tokens and suffix/prefix, use default chat template) (default: false)
 -   `--color`: Enable colorized output to differentiate visually distinguishing between prompts, user input, and generated text.
 
 By understanding and utilizing these interaction options, you can create engaging and dynamic experiences with the LLaMA models, tailoring the text generation process to your specific needs.
@@ -117,6 +117,13 @@ The `--in-suffix` flag is used to add a suffix after your input. This is useful
 ```sh
 ./llama-cli -r "User:" --in-prefix " " --in-suffix "Assistant:"
 ```
+When --in-prefix or --in-suffix options are enabled the chat template ( --chat-template ) is disabled
+
+### Chat templates
+
+ `--chat-template JINJA_TEMPLATE`: This option sets a custom jinja chat template. It accepts a string, not a file name.  Default: template taken from model's metadata. Llama.cpp only supports [some pre-defined templates](https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template). These include llama2, llama3, gemma, monarch, chatml, orion, vicuna, vicuna-orca, deepseek, command-r, zephyr. When --in-prefix or --in-suffix options are enabled the chat template ( --chat-template ) is disabled.
+
+ Example usage: `--chat-template gemma`
 
 ## Context Management
 
@@ -124,9 +131,7 @@ During text generation, LLaMA models have a limited context size, which means th
 
 ### Context Size
 
-The `--ctx-size` option allows you to set the size of the prompt context used by the LLaMA models during text generation. A larger context size helps the model to better comprehend and generate responses for longer input or conversations.
-
--   `-c N, --ctx-size N`: Set the size of the prompt context (default: 512). The LLaMA models were built with a context of 2048, which will yield the best results on longer input/inference. However, increasing the context size beyond 2048 may lead to unpredictable results.
+- `-c N, --ctx-size N`: Set the size of the prompt context (default: 0, 0 = loaded from model). The LLaMA models were built with a context of 2048-8192, which will yield the best results on longer input/inference.
 
 ### Extended Context Size
 
@@ -148,15 +153,15 @@ The following options allow you to control the text generation process and fine-
 
 ### Number of Tokens to Predict
 
--   `-n N, --n-predict N`: Set the number of tokens to predict when generating text (default: 128, -1 = infinity, -2 = until context filled)
+-   `-n N, --predict N`: Set the number of tokens to predict when generating text (default: -1, -1 = infinity, -2 = until context filled)
 
-The `--n-predict` option controls the number of tokens the model generates in response to the input prompt. By adjusting this value, you can influence the length of the generated text. A higher value will result in longer text, while a lower value will produce shorter text.
+The `--predict` option controls the number of tokens the model generates in response to the input prompt. By adjusting this value, you can influence the length of the generated text. A higher value will result in longer text, while a lower value will produce shorter text.
 
-A value of -1 will enable infinite text generation, even though we have a finite context window. When the context window is full, some of the earlier tokens (half of the tokens after `--n-keep`) will be discarded. The context must then be re-evaluated before generation can resume. On large models and/or large context windows, this will result in significant pause in output.
+A value of -1 will enable infinite text generation, even though we have a finite context window. When the context window is full, some of the earlier tokens (half of the tokens after `--keep`) will be discarded. The context must then be re-evaluated before generation can resume. On large models and/or large context windows, this will result in a significant pause in output.
 
 If the pause is undesirable, a value of -2 will stop generation immediately when the context is filled.
 
-It is important to note that the generated text may be shorter than the specified number of tokens if an End-of-Sequence (EOS) token or a reverse prompt is encountered. In interactive mode text generation will pause and control will be returned to the user. In non-interactive mode, the program will end. In both cases, the text generation may stop before reaching the specified `n-predict` value. If you want the model to keep going without ever producing End-of-Sequence on its own, you can use the `--ignore-eos` parameter.
+It is important to note that the generated text may be shorter than the specified number of tokens if an End-of-Sequence (EOS) token or a reverse prompt is encountered. In interactive mode, text generation will pause and control will be returned to the user. In non-interactive mode, the program will end. In both cases, the text generation may stop before reaching the specified `--predict` value. If you want the model to keep going without ever producing End-of-Sequence on its own, you can use the `--ignore-eos` parameter.
 
 ### Temperature
 
@@ -164,15 +169,15 @@ It is important to note that the generated text may be shorter than the specifie
 
 Temperature is a hyperparameter that controls the randomness of the generated text. It affects the probability distribution of the model's output tokens. A higher temperature (e.g., 1.5) makes the output more random and creative, while a lower temperature (e.g., 0.5) makes the output more focused, deterministic, and conservative. The default value is 0.8, which provides a balance between randomness and determinism. At the extreme, a temperature of 0 will always pick the most likely next token, leading to identical outputs in each run.
 
-Example usage: `--temp 0.5`
+Example usage: `--temp 0`
 
 ### Repeat Penalty
 
--   `--repeat-penalty N`: Control the repetition of token sequences in the generated text (default: 1.1).
+-   `--repeat-penalty N`: Control the repetition of token sequences in the generated text default: 1.0, 1.0 = disabled).
 -   `--repeat-last-n N`: Last n tokens to consider for penalizing repetition (default: 64, 0 = disabled, -1 = ctx-size).
 -   `--no-penalize-nl`: Disable penalization for newline tokens when applying the repeat penalty.
 
-The `repeat-penalty` option helps prevent the model from generating repetitive or monotonous text. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. The default value is 1.1.
+The `repeat-penalty` option helps prevent the model from generating repetitive or monotonous text. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. The default value is 1.
 
 The `repeat-last-n` option controls the number of tokens in the history to consider for penalizing repetition. A larger value will look further back in the generated text to prevent repetitions, while a smaller value will only consider recent tokens. A value of 0 disables the penalty, and a value of -1 sets the number of tokens considered equal to the context size (`ctx-size`).
 
@@ -196,19 +201,19 @@ Top-p sampling, also known as nucleus sampling, is another text generation metho
 
 Example usage: `--top-p 0.95`
 
-### Min P Sampling
+### Min-P Sampling
 
--   `--min-p N`: Sets a minimum base probability threshold for token selection (default: 0.05).
+-   `--min-p N`: Sets a minimum base probability threshold for token selection (default: 0.1).
 
 The Min-P sampling method was designed as an alternative to Top-P, and aims to ensure a balance of quality and variety. The parameter *p* represents the minimum probability for a token to be considered, relative to the probability of the most likely token. For example, with *p*=0.05 and the most likely token having a probability of 0.9, logits with a value less than 0.045 are filtered out.
 
 Example usage: `--min-p 0.05`
 
-### Tail Free Sampling (TFS)
+### Tail-Free Sampling (TFS)
 
 -   `--tfs N`: Enable tail free sampling with parameter z (default: 1.0, 1.0 = disabled).
 
-Tail free sampling (TFS) is a text generation technique that aims to reduce the impact of less likely tokens, which may be less relevant, less coherent, or nonsensical, on the output. Similar to Top-P it tries to determine the bulk of the most likely tokens dynamically. But TFS filters out logits based on the second derivative of their probabilities. Adding tokens is stopped after the sum of the second derivatives reaches the parameter z. In short: TFS looks how quickly the probabilities of the tokens decrease and cuts off the tail of unlikely tokens using the parameter z. Typical values for z are in the range of 0.9 to 0.95. A value of 1.0 would include all tokens, and thus disables the effect of TFS.
+Tail-free sampling (TFS) is a text generation technique that aims to reduce the impact of less likely tokens, which may be less relevant, less coherent, or nonsensical, on the output. Similar to Top-P it tries to determine the bulk of the most likely tokens dynamically. But TFS filters out logits based on the second derivative of their probabilities. Adding tokens is stopped after the sum of the second derivatives reaches the parameter z. In short: TFS looks at how quickly the probabilities of the tokens decrease and cuts off the tail of unlikely tokens using the parameter z. Typical values for z are in the range of 0.9 to 0.95. A value of 1.0 would include all tokens and thus disables the effect of TFS.
 
 Example usage: `--tfs 0.95`
 
@@ -307,10 +312,8 @@ These options provide extra functionality and customization when running the LLa
 
 -   `-h, --help`: Display a help message showing all available options and their default values. This is particularly useful for checking the latest options and default values, as they can change frequently, and the information in this document may become outdated.
 -   `--verbose-prompt`: Print the prompt before generating text.
--   `-ngl N, --n-gpu-layers N`: When compiled with GPU support, this option allows offloading some layers to the GPU for computation. Generally results in increased performance.
 -   `-mg i, --main-gpu i`: When using multiple GPUs this option controls which GPU is used for small tensors for which the overhead of splitting the computation across all GPUs is not worthwhile. The GPU in question will use slightly more VRAM to store a scratch buffer for temporary results. By default GPU 0 is used.
 -   `-ts SPLIT, --tensor-split SPLIT`: When using multiple GPUs this option controls how large tensors should be split across all GPUs. `SPLIT` is a comma-separated list of non-negative values that assigns the proportion of data that each GPU should get in order. For example, "3,2" will assign 60% of the data to GPU 0 and 40% to GPU 1. By default the data is split in proportion to VRAM but this may not be optimal for performance.
 -   `--lora FNAME`: Apply a LoRA (Low-Rank Adaptation) adapter to the model (implies --no-mmap). This allows you to adapt the pretrained model to specific tasks or domains.
 -   `--lora-base FNAME`: Optional model to use as a base for the layers modified by the LoRA adapter. This flag is used in conjunction with the `--lora` flag, and specifies the base model for the adaptation.
-
 -   `-hfr URL --hf-repo URL`: The url to the Hugging Face model repository. Used in conjunction with `--hf-file` or `-hff`. The model is downloaded and stored in the file provided by `-m` or `--model`. If `-m` is not provided, the model is auto-stored in the path specified by the `LLAMA_CACHE` environment variable  or in an OS-specific local cache.

From 3fd62a6b1c9ca7b7c0093e984cc9c133c6f2726d Mon Sep 17 00:00:00 2001
From: compilade 
Date: Sun, 7 Jul 2024 15:04:39 -0400
Subject: [PATCH 129/326] py : type-check all Python scripts with Pyright
 (#8341)

* py : type-check all Python scripts with Pyright

* server-tests : use trailing slash in openai base_url

* server-tests : add more type annotations

* server-tests : strip "chat" from base_url in oai_chat_completions

* server-tests : model metadata is a dict

* ci : disable pip cache in type-check workflow

The cache is not shared between branches, and it's 250MB in size,
so it would become quite a big part of the 10GB cache limit of the repo.

* py : fix new type errors from master branch

* tests : fix test-tokenizer-random.py

Apparently, gcc applies optimisations even when pre-processing,
which confuses pycparser.

* ci : only show warnings and errors in python type-check

The "information" level otherwise has entries
from 'examples/pydantic_models_to_grammar.py',
which could be confusing for someone trying to figure out what failed,
considering that these messages can safely be ignored
even though they look like errors.
---
 .devops/nix/package.nix                       |  16 +++
 .github/workflows/python-type-check.yml       |  38 +++++++
 convert_hf_to_gguf.py                         |  20 ++--
 convert_llama_ggml_to_gguf.py                 |   3 +-
 examples/convert_legacy_llama.py              |  21 ++--
 .../convert_finetune_checkpoint_to_gguf.py    |   2 +-
 examples/json_schema_pydantic_example.py      |   5 +-
 examples/json_schema_to_grammar.py            |  12 ++-
 .../llava/convert_image_encoder_to_gguf.py    |  10 +-
 examples/llava/llava_surgery_v2.py            |  10 +-
 examples/pydantic_models_to_grammar.py        |  35 +++---
 .../pydantic_models_to_grammar_examples.py    |   7 +-
 examples/server/bench/bench.py                |  11 +-
 examples/server/tests/features/steps/steps.py | 100 +++++++++---------
 examples/server/tests/requirements.txt        |   4 +-
 examples/server_embd.py                       |   4 +-
 .../convert_train_checkpoint_to_gguf.py       |   2 +-
 ggml/ggml_vk_generate_shaders.py              |   4 +-
 gguf-py/gguf/gguf_reader.py                   |   6 +-
 gguf-py/gguf/lazy.py                          |  31 +++---
 gguf-py/scripts/__init__.py                   |   2 +
 gguf-py/scripts/gguf_hash.py                  |   6 +-
 gguf-py/scripts/gguf_new_metadata.py          |   2 +
 gguf-py/tests/test_gguf.py                    |   2 +-
 pyrightconfig.json                            |  20 +++-
 requirements/requirements-all.txt             |  12 +++
 .../requirements-compare-llama-bench.txt      |   2 +
 requirements/requirements-pydantic.txt        |   2 +
 .../requirements-test-tokenizer-random.txt    |   1 +
 scripts/check-requirements.sh                 |  12 +--
 scripts/compare-llama-bench.py                |   8 +-
 scripts/gen-unicode-data.py                   |  16 +--
 tests/test-tokenizer-random.py                |  44 ++++----
 33 files changed, 297 insertions(+), 173 deletions(-)
 create mode 100644 .github/workflows/python-type-check.yml
 create mode 100644 requirements/requirements-all.txt
 create mode 100644 requirements/requirements-compare-llama-bench.txt
 create mode 100644 requirements/requirements-pydantic.txt
 create mode 100644 requirements/requirements-test-tokenizer-random.txt

diff --git a/.devops/nix/package.nix b/.devops/nix/package.nix
index 49e9b75287b33..00be596ce3fb7 100644
--- a/.devops/nix/package.nix
+++ b/.devops/nix/package.nix
@@ -89,6 +89,22 @@ let
       ps.tiktoken
       ps.torchWithoutCuda
       ps.transformers
+
+      # server bench
+      ps.matplotlib
+
+      # server tests
+      ps.openai
+      ps.behave
+      ps.prometheus-client
+
+      # for examples/pydantic-models-to-grammar-examples.py
+      ps.docstring-parser
+      ps.pydantic
+
+      # for scripts/compare-llama-bench.py
+      ps.gitpython
+      ps.tabulate
     ]
   );
 
diff --git a/.github/workflows/python-type-check.yml b/.github/workflows/python-type-check.yml
new file mode 100644
index 0000000000000..e5ff5e6d792cb
--- /dev/null
+++ b/.github/workflows/python-type-check.yml
@@ -0,0 +1,38 @@
+name: Python Type-Check
+
+on:
+  push:
+    paths:
+      - '.github/workflows/python-type-check.yml'
+      - '**.py'
+      - '**/requirements*.txt'
+  pull_request:
+    paths:
+      - '.github/workflows/python-type-check.yml'
+      - '**.py'
+      - '**/requirements*.txt'
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
+  cancel-in-progress: true
+
+jobs:
+  python-type-check:
+    runs-on: ubuntu-latest
+    name: pyright type-check
+    steps:
+      - name: Check out source repository
+        uses: actions/checkout@v4
+      - name: Set up Python environment
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+      - name: Install Python dependencies
+        # TODO: use a venv
+        run: pip install -r requirements/requirements-all.txt
+      - name: Type-check with Pyright
+        uses: jakebailey/pyright-action@v2
+        with:
+          version: 1.1.370
+          level: warning
+          warnings: true
diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py
index 6ee41d3a118e5..6cea73f08b743 100755
--- a/convert_hf_to_gguf.py
+++ b/convert_hf_to_gguf.py
@@ -265,7 +265,7 @@ def write_tensors(self):
                     break
 
             for new_name, data in ((n, d.squeeze().numpy()) for n, d in self.modify_tensors(data_torch, name, bid)):
-                data: np.ndarray = data  # type hint
+                data: np.ndarray  # type hint
                 n_dims = len(data.shape)
                 data_dtype = data.dtype
                 data_qtype: gguf.GGMLQuantizationType | None = None
@@ -599,10 +599,6 @@ def _create_vocab_sentencepiece(self):
 
         tokenizer_path = self.dir_model / 'tokenizer.model'
 
-        tokens: list[bytes] = []
-        scores: list[float] = []
-        toktypes: list[int] = []
-
         if not tokenizer_path.is_file():
             raise FileNotFoundError(f"File not found: {tokenizer_path}")
 
@@ -2120,7 +2116,7 @@ def set_vocab(self):
             logger.error(f'Error: Missing {tokenizer_path}')
             sys.exit(1)
 
-        sentencepiece_model = model.ModelProto()
+        sentencepiece_model = model.ModelProto()  # pyright: ignore[reportAttributeAccessIssue]
         sentencepiece_model.ParseFromString(open(tokenizer_path, "rb").read())
         add_prefix = sentencepiece_model.normalizer_spec.add_dummy_prefix
 
@@ -2972,16 +2968,16 @@ def set_vocab(self):
         if not tokenizer_path.is_file():
             raise FileNotFoundError(f"File not found: {tokenizer_path}")
 
-        sentencepiece_model = model.ModelProto()
+        sentencepiece_model = model.ModelProto()  # pyright: ignore[reportAttributeAccessIssue]
         sentencepiece_model.ParseFromString(open(tokenizer_path, "rb").read())
 
         # some models like Pile-T5 family use BPE tokenizer instead of Unigram
-        if sentencepiece_model.trainer_spec.model_type == 2: # BPE
+        if sentencepiece_model.trainer_spec.model_type == 2:  # BPE
             # assure the tokenizer model file name is correct
             assert tokenizer_path.name == 'tokenizer.model'
             return self._set_vocab_sentencepiece()
         else:
-            assert sentencepiece_model.trainer_spec.model_type == 1 # UNIGRAM
+            assert sentencepiece_model.trainer_spec.model_type == 1  # UNIGRAM
 
         add_prefix = sentencepiece_model.normalizer_spec.add_dummy_prefix
         remove_whitespaces = sentencepiece_model.normalizer_spec.remove_extra_whitespaces
@@ -3152,7 +3148,7 @@ def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iter
             # but Jais's PyTorch model simply precalculates the slope values and places them
             # in relative_pes.slopes
             n_head_closest_log2 = 2 ** math.floor(math.log2(self.hparams["n_head"]))
-            first_val = float(data_torch._data[0])
+            first_val = float(data_torch[0].item())
             self.max_alibi_bias = -round(math.log2(first_val) * n_head_closest_log2)
 
             return tensors
@@ -3186,7 +3182,7 @@ class ChatGLMModel(Model):
     def set_vocab_chatglm3(self):
         dir_model = self.dir_model
         hparams = self.hparams
-        tokens: list[bytearray] = []
+        tokens: list[bytes] = []
         toktypes: list[int] = []
         scores: list[float] = []
 
@@ -3335,7 +3331,7 @@ def set_vocab(self):
         special_vocab.add_to_gguf(self.gguf_writer)
 
     def set_gguf_parameters(self):
-        self.gguf_writer.add_name(self.hparams.get("_name_or_path").split("/")[1]) # THUDM/glm4-9b-chat or THUDM/chatglm3-6b
+        self.gguf_writer.add_name(self.hparams["_name_or_path"].split("/")[1]) # THUDM/glm4-9b-chat or THUDM/chatglm3-6b
         n_embed = self.hparams.get("hidden_size", self.hparams.get("n_embed"))
         n_head = self.hparams.get("n_head", self.hparams.get("num_attention_heads"))
         n_head_kv = self.hparams.get("multi_query_group_num", n_head)
diff --git a/convert_llama_ggml_to_gguf.py b/convert_llama_ggml_to_gguf.py
index 9349de3b3b498..95ea831a50a9c 100755
--- a/convert_llama_ggml_to_gguf.py
+++ b/convert_llama_ggml_to_gguf.py
@@ -354,7 +354,8 @@ def add_tensors(self, gguf_writer):
 
 
 def handle_metadata(cfg, hp):
-    import convert
+    import examples.convert_legacy_llama as convert
+
     assert cfg.model_metadata_dir.is_dir(), 'Metadata dir is not a directory'
     hf_config_path   = cfg.model_metadata_dir / "config.json"
     orig_config_path = cfg.model_metadata_dir / "params.json"
diff --git a/examples/convert_legacy_llama.py b/examples/convert_legacy_llama.py
index 721a57c00299b..c2c73e8ad39ec 100755
--- a/examples/convert_legacy_llama.py
+++ b/examples/convert_legacy_llama.py
@@ -353,7 +353,7 @@ class Metadata:
     version: Optional[str] = None
     url: Optional[str] = None
     description: Optional[str] = None
-    licence: Optional[str] = None
+    license: Optional[str] = None
     source_url: Optional[str] = None
     source_hf_repo: Optional[str] = None
 
@@ -492,12 +492,13 @@ def validate_conversion_to(self, data_type: DataType) -> None:
 
 LazyModel: TypeAlias = 'dict[str, LazyTensor]'
 
+ModelFormat: TypeAlias = Literal['ggml', 'torch', 'safetensors', 'none']
 
 @dataclass
 class ModelPlus:
     model: LazyModel
     paths: list[Path]  # Where this was read from.
-    format: Literal['ggml', 'torch', 'safetensors', 'none']
+    format: ModelFormat
     vocab: BaseVocab | None  # For GGML models (which have vocab built in), the vocab.
 
 
@@ -536,7 +537,7 @@ def load() -> UnquantizedTensor:
 
 
 def merge_multifile_models(models_plus: list[ModelPlus]) -> ModelPlus:
-    formats = set(mp.format for mp in models_plus)
+    formats: set[ModelFormat] = set(mp.format for mp in models_plus)
     assert len(formats) == 1, "different formats?"
     format = formats.pop()
     paths = [path for mp in models_plus for path in mp.paths]
@@ -555,7 +556,7 @@ def merge_multifile_models(models_plus: list[ModelPlus]) -> ModelPlus:
     else:
         model = merge_sharded([mp.model for mp in models_plus])
 
-    return ModelPlus(model, paths, format, vocab)  # pytype: disable=wrong-arg-types
+    return ModelPlus(model, paths, format, vocab)
 
 
 def permute_lazy(lazy_tensor: LazyTensor, n_head: int, n_head_kv: int) -> LazyTensor:
@@ -805,7 +806,7 @@ class OutputFile:
     def __init__(self, fname_out: Path, endianess:gguf.GGUFEndian = gguf.GGUFEndian.LITTLE):
         self.gguf = gguf.GGUFWriter(fname_out, gguf.MODEL_ARCH_NAMES[ARCH], endianess=endianess)
 
-    def add_meta_model(self, params: Params, metadata: Metadata) -> None:
+    def add_meta_model(self, params: Params, metadata: Metadata | None) -> None:
         # Metadata About The Model And Its Provenence
         name = "LLaMA"
         if metadata is not None and metadata.name is not None:
@@ -827,8 +828,8 @@ def add_meta_model(self, params: Params, metadata: Metadata) -> None:
                 self.gguf.add_url(metadata.url)
             if metadata.description is not None:
                 self.gguf.add_description(metadata.description)
-            if metadata.licence is not None:
-                self.gguf.add_licence(metadata.licence)
+            if metadata.license is not None:
+                self.gguf.add_licence(metadata.license)
             if metadata.source_url is not None:
                 self.gguf.add_source_url(metadata.source_url)
             if metadata.source_hf_repo is not None:
@@ -943,7 +944,7 @@ def close(self) -> None:
     @staticmethod
     def write_vocab_only(
         fname_out: Path, params: Params, vocab: Vocab, svocab: gguf.SpecialVocab,
-        endianess: gguf.GGUFEndian = gguf.GGUFEndian.LITTLE, pad_vocab: bool = False, metadata: Metadata = None,
+        endianess: gguf.GGUFEndian = gguf.GGUFEndian.LITTLE, pad_vocab: bool = False, metadata: Metadata | None = None,
     ) -> None:
         check_vocab_size(params, vocab, pad_vocab=pad_vocab)
 
@@ -977,7 +978,7 @@ def write_all(
         fname_out: Path, ftype: GGMLFileType, params: Params, model: LazyModel, vocab: BaseVocab, svocab: gguf.SpecialVocab,
         concurrency: int = DEFAULT_CONCURRENCY, endianess: gguf.GGUFEndian = gguf.GGUFEndian.LITTLE,
         pad_vocab: bool = False,
-        metadata: Metadata = None,
+        metadata: Metadata | None = None,
     ) -> None:
         check_vocab_size(params, vocab, pad_vocab=pad_vocab)
 
@@ -1396,6 +1397,8 @@ def main(args_in: list[str] | None = None) -> None:
     if model_plus.vocab is not None and args.vocab_dir is None and not args.no_vocab:
         vocab = model_plus.vocab
 
+    assert params is not None
+
     logger.info(f"Vocab info: {vocab}")
     logger.info(f"Special vocab info: {special_vocab}")
     model   = model_plus.model
diff --git a/examples/finetune/convert_finetune_checkpoint_to_gguf.py b/examples/finetune/convert_finetune_checkpoint_to_gguf.py
index c89090918da97..1b79d6995d92a 100644
--- a/examples/finetune/convert_finetune_checkpoint_to_gguf.py
+++ b/examples/finetune/convert_finetune_checkpoint_to_gguf.py
@@ -74,7 +74,7 @@ def __init__(self, dtype='f', ne=None):
             if len(self.ne) == 0:
                 self.nbytes = 0
             else:
-                self.nbytes = int(np.product(self.ne)) * 4
+                self.nbytes = int(np.prod(self.ne)) * 4
         else:
             raise ValueError(f"Unhandled data type '{self.dtype}'")
 
diff --git a/examples/json_schema_pydantic_example.py b/examples/json_schema_pydantic_example.py
index c7ca7b8d9041a..19c0bdb5b6770 100644
--- a/examples/json_schema_pydantic_example.py
+++ b/examples/json_schema_pydantic_example.py
@@ -3,7 +3,7 @@
 #! pip install pydantic
 #! python json_schema_pydantic_example.py
 
-from pydantic import BaseModel, Extra, TypeAdapter
+from pydantic import BaseModel, Field, TypeAdapter
 from annotated_types import MinLen
 from typing import Annotated, List, Optional
 import json, requests
@@ -17,6 +17,9 @@ def create_completion(*, response_model=None, endpoint="http://localhost:8080/v1
 
         The response_model param takes a type (+ supports Pydantic) and behaves just as w/ Instructor (see below)
         '''
+        response_format = None
+        type_adapter = None
+
         if response_model:
             type_adapter = TypeAdapter(response_model)
             schema = type_adapter.json_schema()
diff --git a/examples/json_schema_to_grammar.py b/examples/json_schema_to_grammar.py
index 072a230f72408..a8779bf3bca38 100755
--- a/examples/json_schema_to_grammar.py
+++ b/examples/json_schema_to_grammar.py
@@ -1,4 +1,6 @@
 #!/usr/bin/env python3
+from __future__ import annotations
+
 import argparse
 import itertools
 import json
@@ -188,7 +190,7 @@ def uniform_range(from_str: str, to_str: str):
     raise RuntimeError("At least one of min_value or max_value must be set")
 
 class BuiltinRule:
-    def __init__(self, content: str, deps: list = None):
+    def __init__(self, content: str, deps: list | None = None):
         self.content = content
         self.deps = deps or []
 
@@ -248,7 +250,7 @@ def __init__(self, *, prop_order, allow_fetch, dotall, raw_pattern):
 
     def _format_literal(self, literal):
         escaped = GRAMMAR_LITERAL_ESCAPE_RE.sub(
-            lambda m: GRAMMAR_LITERAL_ESCAPES.get(m.group(0)), literal
+            lambda m: GRAMMAR_LITERAL_ESCAPES.get(m.group(0)) or m.group(0), literal
         )
         return f'"{escaped}"'
 
@@ -403,11 +405,11 @@ def _visit_pattern(self, pattern, name):
         i = 0
         length = len(pattern)
 
-        def to_rule(s: Tuple[str, bool]) -> str:
+        def to_rule(s: tuple[str, bool]) -> str:
             (txt, is_literal) = s
             return "\"" + txt + "\"" if is_literal else txt
 
-        def transform() -> Tuple[str, bool]:
+        def transform() -> tuple[str, bool]:
             '''
                 Parse a unit at index i (advancing it), and return its string representation + whether it's a literal.
             '''
@@ -420,7 +422,7 @@ def transform() -> Tuple[str, bool]:
             # We only need a flat structure here to apply repetition operators to the last item, and
             # to merge literals at the and (we're parsing grouped ( sequences ) recursively and don't treat '|' specially
             # (GBNF's syntax is luckily very close to regular expressions!)
-            seq: list[Tuple[str, bool]] = []
+            seq: list[tuple[str, bool]] = []
 
             def get_dot():
                 if self._dotall:
diff --git a/examples/llava/convert_image_encoder_to_gguf.py b/examples/llava/convert_image_encoder_to_gguf.py
index b00bf7c6d0b59..36f6b92fbd46e 100644
--- a/examples/llava/convert_image_encoder_to_gguf.py
+++ b/examples/llava/convert_image_encoder_to_gguf.py
@@ -185,6 +185,8 @@ def bytes_to_unicode():
     fout.add_description("two-tower CLIP model")
 
 if has_text_encoder:
+    assert t_hparams is not None
+    assert tokens is not None
     # text_model hparams
     fout.add_uint32(k(KEY_CONTEXT_LENGTH, TEXT), t_hparams["max_position_embeddings"])
     fout.add_uint32(k(KEY_EMBEDDING_LENGTH, TEXT), t_hparams["hidden_size"])
@@ -259,8 +261,8 @@ def bytes_to_unicode():
 
 
     if processor is not None:
-        image_mean = processor.image_processor.image_mean if args.image_mean is None or args.image_mean == default_image_mean else args.image_mean
-        image_std = processor.image_processor.image_std if args.image_std is None or args.image_std == default_image_std else args.image_std
+        image_mean = processor.image_processor.image_mean if args.image_mean is None or args.image_mean == default_image_mean else args.image_mean  # pyright: ignore[reportAttributeAccessIssue]
+        image_std = processor.image_processor.image_std if args.image_std is None or args.image_std == default_image_std else args.image_std  # pyright: ignore[reportAttributeAccessIssue]
     else:
         image_mean = args.image_mean if args.image_mean is not None else default_image_mean
         image_std = args.image_std if args.image_std is not None else default_image_std
@@ -272,7 +274,7 @@ def bytes_to_unicode():
 
 
 if has_llava_projector:
-    model.vision_model.encoder.layers.pop(-1)
+    model.vision_model.encoder.layers.pop(-1)  # pyright: ignore[reportAttributeAccessIssue]
     projector = torch.load(args.llava_projector)
     for name, data in projector.items():
         name = get_tensor_name(name)
@@ -286,7 +288,7 @@ def bytes_to_unicode():
 
     print("Projector tensors added\n")
 
-state_dict = model.state_dict()
+state_dict = model.state_dict()  # pyright: ignore[reportAttributeAccessIssue]
 for name, data in state_dict.items():
     if should_skip_tensor(name, has_text_encoder, has_vision_encoder, has_llava_projector):
         # we don't need this
diff --git a/examples/llava/llava_surgery_v2.py b/examples/llava/llava_surgery_v2.py
index eb56d6988ac26..2d5b32fe6b236 100644
--- a/examples/llava/llava_surgery_v2.py
+++ b/examples/llava/llava_surgery_v2.py
@@ -2,7 +2,9 @@
 import glob
 import os
 import torch
-from safetensors.torch import load as safe_load, save as safe_save, safe_open, save_file
+from safetensors import safe_open
+from safetensors.torch import save_file
+from typing import Any, ContextManager, cast
 
 # Function to determine if file is a SafeTensor file
 def is_safetensor_file(file_path):
@@ -13,7 +15,7 @@ def is_safetensor_file(file_path):
 def load_model(file_path):
     if is_safetensor_file(file_path):
         tensors = {}
-        with safe_open(file_path, framework="pt", device="cpu") as f:
+        with cast(ContextManager[Any], safe_open(file_path, framework="pt", device="cpu")) as f:
             for key in f.keys():
                 tensors[key] = f.get_tensor(key).clone()
                 # output shape
@@ -134,7 +136,7 @@ def proj_criteria(checkpoint):
     if last_checkpoint is not None:
         for k, v in last_checkpoint.items():
             print(k)
-    print(f"Found {len(mm_tensors)} tensors to extract out of {len(last_checkpoint)} tensors.")
+    print(f"Found {len(mm_tensors)} tensors to extract out of {len(last_checkpoint) if last_checkpoint is not None else 0} tensors.")
     print("No tensors found. Is this a LLaVA model?")
     exit()
 
@@ -143,8 +145,10 @@ def proj_criteria(checkpoint):
 # projector = {name: checkpoint.[name].float() for name in mm_tensors}
 projector = {}
 for name in mm_tensors:
+    assert last_checkpoint is not None
     projector[name] = last_checkpoint[name].float()
 for name in first_mm_tensors:
+    assert first_checkpoint is not None
     projector[name] = first_checkpoint[name].float()
 
 if len(projector) > 0:
diff --git a/examples/pydantic_models_to_grammar.py b/examples/pydantic_models_to_grammar.py
index f029c73a2582d..d8145710ce250 100644
--- a/examples/pydantic_models_to_grammar.py
+++ b/examples/pydantic_models_to_grammar.py
@@ -6,10 +6,10 @@
 from copy import copy
 from enum import Enum
 from inspect import getdoc, isclass
-from typing import TYPE_CHECKING, Any, Callable, List, Optional, Union, get_args, get_origin, get_type_hints
+from typing import TYPE_CHECKING, Any, Callable, List, Optional, Union, get_args, get_origin
 
 from docstring_parser import parse
-from pydantic import BaseModel, Field, create_model
+from pydantic import BaseModel, create_model
 
 if TYPE_CHECKING:
     from types import GenericAlias
@@ -17,6 +17,9 @@
     # python 3.8 compat
     from typing import _GenericAlias as GenericAlias
 
+# TODO: fix this
+# pyright: reportAttributeAccessIssue=information
+
 
 class PydanticDataType(Enum):
     """
@@ -234,8 +237,9 @@ def generate_gbnf_float_rules(max_digit=None, min_digit=None, max_precision=None
 
     # Define the integer part rule
     integer_part_rule = (
-        "integer-part" + (f"-max{max_digit}" if max_digit is not None else "") + (
-        f"-min{min_digit}" if min_digit is not None else "")
+        "integer-part"
+        + (f"-max{max_digit}" if max_digit is not None else "")
+        + (f"-min{min_digit}" if min_digit is not None else "")
     )
 
     # Define the fractional part rule based on precision constraints
@@ -458,7 +462,7 @@ def generate_gbnf_grammar(model: type[BaseModel], processed_models: set[type[Bas
     if not issubclass(model, BaseModel):
         # For non-Pydantic classes, generate model_fields from __annotations__ or __init__
         if hasattr(model, "__annotations__") and model.__annotations__:
-            model_fields = {name: (typ, ...) for name, typ in model.__annotations__.items()}
+            model_fields = {name: (typ, ...) for name, typ in model.__annotations__.items()}  # pyright: ignore[reportGeneralTypeIssues]
         else:
             init_signature = inspect.signature(model.__init__)
             parameters = init_signature.parameters
@@ -680,7 +684,7 @@ def generate_markdown_documentation(
         str: Generated text documentation.
     """
     documentation = ""
-    pyd_models = [(model, True) for model in pydantic_models]
+    pyd_models: list[tuple[type[BaseModel], bool]] = [(model, True) for model in pydantic_models]
     for model, add_prefix in pyd_models:
         if add_prefix:
             documentation += f"{model_prefix}: {model.__name__}\n"
@@ -700,7 +704,7 @@ def generate_markdown_documentation(
             # Indenting the fields section
             documentation += f"  {fields_prefix}:\n"
         else:
-            documentation += f"  Fields:\n"
+            documentation += f"  Fields:\n"  # noqa: F541
         if isclass(model) and issubclass(model, BaseModel):
             for name, field_type in model.__annotations__.items():
                 # if name == "markdown_code_block":
@@ -778,7 +782,7 @@ def generate_field_markdown(
         return field_text
 
     if field_description != "":
-        field_text += f"        Description: " + field_description + "\n"
+        field_text += f"        Description: {field_description}\n"
 
     # Check for and include field-specific examples if available
     if hasattr(model, "Config") and hasattr(model.Config,
@@ -833,7 +837,7 @@ def generate_text_documentation(
         str: Generated text documentation.
     """
     documentation = ""
-    pyd_models = [(model, True) for model in pydantic_models]
+    pyd_models: list[tuple[type[BaseModel], bool]] = [(model, True) for model in pydantic_models]
     for model, add_prefix in pyd_models:
         if add_prefix:
             documentation += f"{model_prefix}: {model.__name__}\n"
@@ -1164,7 +1168,7 @@ def create_dynamic_model_from_function(func: Callable[..., Any]):
         dynamic_fields[param.name] = (
             param.annotation if param.annotation != inspect.Parameter.empty else str, default_value)
     # Creating the dynamic model
-    dynamic_model = create_model(f"{func.__name__}", **dynamic_fields)  # type: ignore[call-overload]
+    dynamic_model = create_model(f"{func.__name__}", **dynamic_fields)
 
     for name, param_doc in param_docs:
         dynamic_model.model_fields[name].description = param_doc.description
@@ -1228,9 +1232,6 @@ def map_grammar_names_to_pydantic_model_class(pydantic_model_list):
     return output
 
 
-from enum import Enum
-
-
 def json_schema_to_python_types(schema):
     type_map = {
         "any": Any,
@@ -1275,7 +1276,7 @@ def convert_dictionary_to_pydantic_model(dictionary: dict[str, Any], model_name:
                     if items != {}:
                         array = {"properties": items}
                         array_type = convert_dictionary_to_pydantic_model(array, f"{model_name}_{field_name}_items")
-                        fields[field_name] = (List[array_type], ...)  # type: ignore[valid-type]
+                        fields[field_name] = (List[array_type], ...)
                     else:
                         fields[field_name] = (list, ...)
                 elif field_type == "object":
@@ -1285,7 +1286,8 @@ def convert_dictionary_to_pydantic_model(dictionary: dict[str, Any], model_name:
                     required = field_data.get("enum", [])
                     for key, field in fields.items():
                         if key not in required:
-                            fields[key] = (Optional[fields[key][0]], ...)
+                            optional_type = fields[key][0]
+                            fields[key] = (Optional[optional_type], ...)
                 else:
                     field_type = json_schema_to_python_types(field_type)
                     fields[field_name] = (field_type, ...)
@@ -1305,6 +1307,7 @@ def convert_dictionary_to_pydantic_model(dictionary: dict[str, Any], model_name:
         required = dictionary.get("required", [])
         for key, field in fields.items():
             if key not in required:
-                fields[key] = (Optional[fields[key][0]], ...)
+                optional_type = fields[key][0]
+                fields[key] = (Optional[optional_type], ...)
     custom_model = create_model(model_name, **fields)
     return custom_model
diff --git a/examples/pydantic_models_to_grammar_examples.py b/examples/pydantic_models_to_grammar_examples.py
index 160966649b05d..8e7f46cf99a43 100644
--- a/examples/pydantic_models_to_grammar_examples.py
+++ b/examples/pydantic_models_to_grammar_examples.py
@@ -1,6 +1,7 @@
 # Function calling example using pydantic models.
+from __future__ import annotations
+
 import datetime
-import importlib
 import json
 from enum import Enum
 from typing import Optional, Union
@@ -215,9 +216,9 @@ def get_current_weather(location, unit):
     if call["function"] == "Calculator":
         print(Calculator(**call["params"]).run())
     elif call["function"] == "get_current_datetime":
-        print(current_datetime_model(**call["params"]).run())
+        print(current_datetime_model(**call["params"]).run())  # pyright: ignore[reportAttributeAccessIssue]
     elif call["function"] == "get_current_weather":
-        print(current_weather_tool_model(**call["params"]).run())
+        print(current_weather_tool_model(**call["params"]).run())  # pyright: ignore[reportAttributeAccessIssue]
 # Should output something like this:
 # 2024-01-14 13:36:06
 # {"location": "London", "temperature": "42", "unit": "celsius"}
diff --git a/examples/server/bench/bench.py b/examples/server/bench/bench.py
index 4fbbb203267f4..2daac08847d65 100644
--- a/examples/server/bench/bench.py
+++ b/examples/server/bench/bench.py
@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import argparse
 import json
 import os
@@ -59,10 +61,11 @@ def main(args_in: list[str] | None = None) -> None:
         sys.exit(1)
 
     # start the benchmark
+    iterations = 0
+    data = {}
     try:
         start_benchmark(args)
 
-        iterations = 0
         with open("results.github.env", 'w') as github_env:
             # parse output
             with open('k6-results.json', 'r') as bench_results:
@@ -129,7 +132,7 @@ def main(args_in: list[str] | None = None) -> None:
                 timestamps, metric_values = zip(*values)
                 metric_values = [float(value) for value in metric_values]
                 prometheus_metrics[metric] = metric_values
-                timestamps_dt = [datetime.fromtimestamp(int(ts)) for ts in timestamps]
+                timestamps_dt = [str(datetime.fromtimestamp(int(ts))) for ts in timestamps]
                 plt.figure(figsize=(16, 10), dpi=80)
                 plt.plot(timestamps_dt, metric_values, label=metric)
                 plt.xticks(rotation=0, fontsize=14, horizontalalignment='center', alpha=.7)
@@ -156,7 +159,7 @@ def main(args_in: list[str] | None = None) -> None:
                 plt.close()
 
                 # Mermaid format in case images upload failed
-                with (open(f"{metric}.mermaid", 'w') as mermaid_f):
+                with open(f"{metric}.mermaid", 'w') as mermaid_f:
                     mermaid = (
                     f"""---
 config:
@@ -278,7 +281,7 @@ def start_server_background(args):
     }
     server_process = subprocess.Popen(
         args,
-        **pkwargs)
+        **pkwargs)  # pyright: ignore[reportArgumentType, reportCallIssue]
 
     def server_log(in_stream, out_stream):
         for line in iter(in_stream.readline, b''):
diff --git a/examples/server/tests/features/steps/steps.py b/examples/server/tests/features/steps/steps.py
index 7b5dabb019e75..df0814cc99bd1 100644
--- a/examples/server/tests/features/steps/steps.py
+++ b/examples/server/tests/features/steps/steps.py
@@ -1,5 +1,4 @@
 import asyncio
-import collections
 import json
 import os
 import re
@@ -8,19 +7,23 @@
 import sys
 import threading
 import time
+from collections.abc import Sequence
 from contextlib import closing
 from re import RegexFlag
+from typing import Any, Literal, cast
 
 import aiohttp
 import numpy as np
 import openai
-from behave import step
+from openai.types.chat import ChatCompletionChunk
+from behave import step  # pyright: ignore[reportAttributeAccessIssue]
 from behave.api.async_step import async_run_until_complete
 from prometheus_client import parser
 
+# pyright: reportRedeclaration=false
 
 @step("a server listening on {server_fqdn}:{server_port}")
-def step_server_config(context, server_fqdn, server_port):
+def step_server_config(context, server_fqdn: str, server_port: str):
     context.server_fqdn = server_fqdn
     context.server_port = int(server_port)
     context.n_threads = None
@@ -74,34 +77,34 @@ def step_server_config(context, server_fqdn, server_port):
 
 
 @step('a model file {hf_file} from HF repo {hf_repo}')
-def step_download_hf_model(context, hf_file, hf_repo):
+def step_download_hf_model(context, hf_file: str, hf_repo: str):
     context.model_hf_repo = hf_repo
     context.model_hf_file = hf_file
     context.model_file = os.path.basename(hf_file)
 
 
 @step('a model file {model_file}')
-def step_model_file(context, model_file):
+def step_model_file(context, model_file: str):
     context.model_file = model_file
 
 
 @step('a model url {model_url}')
-def step_model_url(context, model_url):
+def step_model_url(context, model_url: str):
     context.model_url = model_url
 
 
 @step('a model alias {model_alias}')
-def step_model_alias(context, model_alias):
+def step_model_alias(context, model_alias: str):
     context.model_alias = model_alias
 
 
 @step('{seed:d} as server seed')
-def step_seed(context, seed):
+def step_seed(context, seed: int):
     context.server_seed = seed
 
 
 @step('{ngl:d} GPU offloaded layers')
-def step_n_gpu_layer(context, ngl):
+def step_n_gpu_layer(context, ngl: int):
     if 'N_GPU_LAYERS' in os.environ:
         new_ngl = int(os.environ['N_GPU_LAYERS'])
         if context.debug:
@@ -111,37 +114,37 @@ def step_n_gpu_layer(context, ngl):
 
 
 @step('{n_threads:d} threads')
-def step_n_threads(context, n_threads):
+def step_n_threads(context, n_threads: int):
     context.n_thread = n_threads
 
 
 @step('{draft:d} as draft')
-def step_draft(context, draft):
+def step_draft(context, draft: int):
     context.draft = draft
 
 
 @step('{n_ctx:d} KV cache size')
-def step_n_ctx(context, n_ctx):
+def step_n_ctx(context, n_ctx: int):
     context.n_ctx = n_ctx
 
 
 @step('{n_slots:d} slots')
-def step_n_slots(context, n_slots):
+def step_n_slots(context, n_slots: int):
     context.n_slots = n_slots
 
 
 @step('{n_predict:d} server max tokens to predict')
-def step_server_n_predict(context, n_predict):
+def step_server_n_predict(context, n_predict: int):
     context.n_server_predict = n_predict
 
 
 @step('{slot_save_path} as slot save path')
-def step_slot_save_path(context, slot_save_path):
+def step_slot_save_path(context, slot_save_path: str):
     context.slot_save_path = slot_save_path
 
 
 @step('using slot id {id_slot:d}')
-def step_id_slot(context, id_slot):
+def step_id_slot(context, id_slot: int):
     context.id_slot = id_slot
 
 
@@ -191,7 +194,7 @@ def step_start_server(context):
 
 @step("the server is {expecting_status}")
 @async_run_until_complete
-async def step_wait_for_the_server_to_be_started(context, expecting_status):
+async def step_wait_for_the_server_to_be_started(context, expecting_status: Literal['healthy', 'ready', 'idle', 'busy'] | str):
     match expecting_status:
         case 'healthy':
             await wait_for_health_status(context, context.base_url, 200, 'ok',
@@ -221,7 +224,7 @@ async def step_wait_for_the_server_to_be_started(context, expecting_status):
 
 @step('all slots are {expected_slot_status_string}')
 @async_run_until_complete
-async def step_all_slots_status(context, expected_slot_status_string):
+async def step_all_slots_status(context, expected_slot_status_string: Literal['idle', 'busy'] | str):
     match expected_slot_status_string:
         case 'idle':
             expected_slot_status = 0
@@ -237,7 +240,7 @@ async def step_all_slots_status(context, expected_slot_status_string):
 
 @step('a completion request with {api_error} api error')
 @async_run_until_complete
-async def step_request_completion(context, api_error):
+async def step_request_completion(context, api_error: Literal['raised'] | str):
     expect_api_error = api_error == 'raised'
     seeds = await completions_seed(context, num_seeds=1)
     completion = await request_completion(context.prompts.pop(),
@@ -777,8 +780,8 @@ def step_assert_metric_value(context, metric_name, metric_value):
 def step_available_models(context):
     # openai client always expects an api_key
     openai.api_key = context.user_api_key if context.user_api_key is not None else 'nope'
-    openai.api_base = f'{context.base_url}/v1'
-    context.models = openai.Model.list().data
+    openai.base_url = f'{context.base_url}/v1/'
+    context.models = openai.models.list().data
 
 
 @step('{n_model:d} models are supported')
@@ -789,7 +792,7 @@ def step_supported_models(context, n_model):
 
 
 @step('model {i_model:d} is {param} {preposition} {param_value}')
-def step_supported_models(context, i_model, param, preposition, param_value):
+def step_supported_models(context, i_model: int, param: Literal['identified', 'trained'] | str, preposition: str, param_value: str):
     assert i_model < len(context.models)
     model = context.models[i_model]
 
@@ -798,7 +801,7 @@ def step_supported_models(context, i_model, param, preposition, param_value):
         case 'identified':
             value = model.id
         case 'trained':
-            value = str(model.meta.n_ctx_train)
+            value = str(model.meta["n_ctx_train"])
         case _:
             assert False, "param {param} not supported"
     assert param_value == value, f"model param {param} {value} != {param_value}"
@@ -810,6 +813,7 @@ async def concurrent_requests(context, f_completion, *args, **kwargs):
         print(f"starting {context.n_prompts} concurrent completion requests...")
     assert context.n_prompts > 0
     seeds = await completions_seed(context)
+    assert seeds is not None
     for prompt_no in range(context.n_prompts):
         shifted_args = [context.prompts.pop(), seeds[prompt_no], *args]
         context.concurrent_tasks.append(asyncio.create_task(f_completion(*shifted_args, **kwargs)))
@@ -861,7 +865,7 @@ async def request_completion(prompt,
                              id_slot=None,
                              expect_api_error=None,
                              user_api_key=None,
-                             temperature=None):
+                             temperature=None) -> int | dict[str, Any]:
     if debug:
         print(f"Sending completion request: {prompt}")
     origin = "my.super.domain"
@@ -899,8 +903,8 @@ async def request_completion(prompt,
 async def oai_chat_completions(user_prompt,
                                seed,
                                system_prompt,
-                               base_url,
-                               base_path,
+                               base_url: str,
+                               base_path: str,
                                async_client,
                                debug=False,
                                temperature=None,
@@ -909,7 +913,7 @@ async def oai_chat_completions(user_prompt,
                                enable_streaming=None,
                                response_format=None,
                                user_api_key=None,
-                               expect_api_error=None):
+                               expect_api_error=None) -> int | dict[str, Any]:
     if debug:
         print(f"Sending OAI Chat completions request: {user_prompt}")
     # openai client always expects an api key
@@ -989,32 +993,35 @@ async def oai_chat_completions(user_prompt,
     else:
         try:
             openai.api_key = user_api_key
-            openai.api_base = f'{base_url}{base_path}'
-            chat_completion = openai.Completion.create(
+            openai.base_url = f'{base_url}{base_path.removesuffix("chat")}'
+            assert model is not None
+            chat_completion = openai.chat.completions.create(
                 messages=payload['messages'],
                 model=model,
                 max_tokens=n_predict,
                 stream=enable_streaming,
-                response_format=payload.get('response_format'),
+                response_format=payload.get('response_format') or openai.NOT_GIVEN,
                 seed=seed,
                 temperature=payload['temperature']
             )
-        except openai.error.AuthenticationError as e:
+        except openai.AuthenticationError as e:
             if expect_api_error is not None and expect_api_error:
                 return 401
             else:
                 assert False, f'error raised: {e}'
 
         if enable_streaming:
+            chat_completion = cast(openai.Stream[ChatCompletionChunk], chat_completion)
             for chunk in chat_completion:
                 assert len(chunk.choices) == 1
                 delta = chunk.choices[0].delta
-                if 'content' in delta:
-                    completion_response['content'] += delta['content']
+                if delta.content is not None:
+                    completion_response['content'] += delta.content
                     completion_response['timings']['predicted_n'] += 1
                 completion_response['truncated'] = chunk.choices[0].finish_reason != 'stop'
         else:
             assert len(chat_completion.choices) == 1
+            assert chat_completion.usage is not None
             completion_response = {
                 'content': chat_completion.choices[0].message.content,
                 'timings': {
@@ -1028,7 +1035,7 @@ async def oai_chat_completions(user_prompt,
     return completion_response
 
 
-async def request_embedding(content, seed, base_url=None):
+async def request_embedding(content, seed, base_url=None) -> list[list[float]]:
     async with aiohttp.ClientSession() as session:
         async with session.post(f'{base_url}/embedding',
                                 json={
@@ -1041,7 +1048,7 @@ async def request_embedding(content, seed, base_url=None):
 
 async def request_oai_embeddings(input, seed,
                                  base_url=None, user_api_key=None,
-                                 model=None, async_client=False):
+                                 model=None, async_client=False) -> list[list[float]]:
     # openai client always expects an api_key
     user_api_key = user_api_key if user_api_key is not None else 'nope'
     if async_client:
@@ -1063,7 +1070,7 @@ async def request_oai_embeddings(input, seed,
                 response_json = await response.json()
                 assert response_json['model'] == model, f"invalid model received: {response_json['model']}"
                 assert response_json['object'] == 'list'
-                if isinstance(input, collections.abc.Sequence):
+                if isinstance(input, Sequence):
                     embeddings = []
                     for an_oai_embeddings in response_json['data']:
                         embeddings.append(an_oai_embeddings['embedding'])
@@ -1072,19 +1079,14 @@ async def request_oai_embeddings(input, seed,
                 return embeddings
     else:
         openai.api_key = user_api_key
-        openai.api_base = f'{base_url}/v1'
-        oai_embeddings = openai.Embedding.create(
+        openai.base_url = f'{base_url}/v1/'
+        assert model is not None
+        oai_embeddings = openai.embeddings.create(
             model=model,
             input=input,
         )
 
-        if isinstance(input, collections.abc.Sequence):
-            embeddings = []
-            for an_oai_embeddings in oai_embeddings.data:
-                embeddings.append(an_oai_embeddings.embedding)
-        else:
-            embeddings = [oai_embeddings.data.embedding]
-        return embeddings
+        return [e.embedding for e in oai_embeddings.data]
 
 
 def assert_n_tokens_predicted(completion_response, expected_predicted_n=None, re_content=None):
@@ -1122,7 +1124,7 @@ def assert_all_predictions_equal(completion_responses):
             if i == j:
                 continue
             content_j = response_j['content']
-        assert content_i == content_j, "contents not equal"
+            assert content_i == content_j, "contents not equal"
 
 
 def assert_all_predictions_different(completion_responses):
@@ -1136,7 +1138,7 @@ def assert_all_predictions_different(completion_responses):
             if i == j:
                 continue
             content_j = response_j['content']
-        assert content_i != content_j, "contents not different"
+            assert content_i != content_j, "contents not different"
 
 
 def assert_all_token_probabilities_equal(completion_responses):
@@ -1153,7 +1155,7 @@ def assert_all_token_probabilities_equal(completion_responses):
                 if i == j:
                     continue
                 probs_j = response_j['completion_probabilities'][pos]['probs']
-            assert probs_i == probs_j, "contents not equal"
+                assert probs_i == probs_j, "contents not equal"
 
 
 async def gather_tasks_results(context):
@@ -1343,7 +1345,7 @@ def start_server_background(context):
     }
     context.server_process = subprocess.Popen(
         [str(arg) for arg in [context.server_path, *server_args]],
-        **pkwargs)
+        **pkwargs)  # pyright: ignore[reportArgumentType, reportCallIssue]
 
     def server_log(in_stream, out_stream):
         for line in iter(in_stream.readline, b''):
diff --git a/examples/server/tests/requirements.txt b/examples/server/tests/requirements.txt
index 2e4f42ad28c23..2c741ea1081c4 100644
--- a/examples/server/tests/requirements.txt
+++ b/examples/server/tests/requirements.txt
@@ -1,6 +1,6 @@
 aiohttp~=3.9.3
 behave~=1.2.6
 huggingface_hub~=0.20.3
-numpy~=1.24.4
-openai~=0.25.0
+numpy~=1.26.4
+openai~=1.30.3
 prometheus-client~=0.20.0
diff --git a/examples/server_embd.py b/examples/server_embd.py
index a9a36a44ccac5..0e34c6ceab9ca 100644
--- a/examples/server_embd.py
+++ b/examples/server_embd.py
@@ -1,13 +1,15 @@
 import asyncio
+import asyncio.threads
 import requests
 import numpy as np
 
+
 n = 8
 
 result = []
 
 async def requests_post_async(*args, **kwargs):
-    return await asyncio.to_thread(requests.post, *args, **kwargs)
+    return await asyncio.threads.to_thread(requests.post, *args, **kwargs)
 
 async def main():
     model_url = "http://127.0.0.1:6900"
diff --git a/examples/train-text-from-scratch/convert_train_checkpoint_to_gguf.py b/examples/train-text-from-scratch/convert_train_checkpoint_to_gguf.py
index ed93673bcf306..e045beb7281fd 100644
--- a/examples/train-text-from-scratch/convert_train_checkpoint_to_gguf.py
+++ b/examples/train-text-from-scratch/convert_train_checkpoint_to_gguf.py
@@ -66,7 +66,7 @@ def __init__(self, dtype='f', ne=None):
             if len(self.ne) == 0:
                 self.nbytes = 0
             else:
-                self.nbytes = int(np.product(self.ne)) * 4
+                self.nbytes = int(np.prod(self.ne)) * 4
         else:
             raise ValueError(f"Unhandled data type '{self.dtype}'")
 
diff --git a/ggml/ggml_vk_generate_shaders.py b/ggml/ggml_vk_generate_shaders.py
index 38914eedb7976..41d5d9b8cf4c9 100644
--- a/ggml/ggml_vk_generate_shaders.py
+++ b/ggml/ggml_vk_generate_shaders.py
@@ -99,6 +99,8 @@ async def main():
 
     tasks = []
 
+    base_dict = {"FLOAT_TYPE": "float"}
+
     for fp16 in (False, True):
         # MUL_MAT
         matmul_shaders(tasks, fp16, False)
@@ -106,8 +108,6 @@ async def main():
         matmul_shaders(tasks, fp16, True)
 
     for tname in type_names:
-        base_dict = {"FLOAT_TYPE": "float"}
-
         # mul mat vec
         data_a_key = f"DATA_A_{tname.upper()}"
         shader = f"mul_mat_vec_{tname}.comp" if tname.endswith("_k") else "mul_mat_vec.comp"
diff --git a/gguf-py/gguf/gguf_reader.py b/gguf-py/gguf/gguf_reader.py
index 20432bd258458..e8e61abf86ae4 100644
--- a/gguf-py/gguf/gguf_reader.py
+++ b/gguf-py/gguf/gguf_reader.py
@@ -67,7 +67,7 @@ class ReaderTensor(NamedTuple):
 
 class GGUFReader:
     # I - same as host, S - swapped
-    byte_order: Literal['I'] | Literal['S'] = 'I'
+    byte_order: Literal['I', 'S'] = 'I'
     alignment: int = GGUF_DEFAULT_ALIGNMENT
     data_offset: int
 
@@ -86,7 +86,7 @@ class GGUFReader:
         GGUFValueType.BOOL:    np.bool_,
     }
 
-    def __init__(self, path: os.PathLike[str] | str, mode: Literal['r'] | Literal['r+'] | Literal['c'] = 'r'):
+    def __init__(self, path: os.PathLike[str] | str, mode: Literal['r', 'r+', 'c'] = 'r'):
         self.data = np.memmap(path, mode = mode)
         offs = 0
 
@@ -140,7 +140,7 @@ def get_tensor(self, idx: int) -> ReaderTensor:
         return self.tensors[idx]
 
     def _get(
-        self, offset: int, dtype: npt.DTypeLike, count: int = 1, override_order: None | Literal['I'] | Literal['S'] | Literal['<'] = None,
+        self, offset: int, dtype: npt.DTypeLike, count: int = 1, override_order: None | Literal['I', 'S', '<'] = None,
     ) -> npt.NDArray[Any]:
         count = int(count)
         itemsize = int(np.empty([], dtype = dtype).itemsize)
diff --git a/gguf-py/gguf/lazy.py b/gguf-py/gguf/lazy.py
index 1167335b83ab3..c50124cd912d4 100644
--- a/gguf-py/gguf/lazy.py
+++ b/gguf-py/gguf/lazy.py
@@ -16,16 +16,16 @@
 class LazyMeta(ABCMeta):
 
     def __new__(cls, name: str, bases: tuple[type, ...], namespace: dict[str, Any], **kwargs):
-        def __getattr__(self, __name: str) -> Any:
-            meta_attr = getattr(self._meta, __name)
+        def __getattr__(self, name: str) -> Any:
+            meta_attr = getattr(self._meta, name)
             if callable(meta_attr):
                 return type(self)._wrap_fn(
-                    (lambda s, *args, **kwargs: getattr(s, __name)(*args, **kwargs)),
+                    (lambda s, *args, **kwargs: getattr(s, name)(*args, **kwargs)),
                     use_self=self,
                 )
             elif isinstance(meta_attr, self._tensor_type):
                 # e.g. self.T with torch.Tensor should still be wrapped
-                return type(self)._wrap_fn(lambda s: getattr(s, __name))(self)
+                return type(self)._wrap_fn(lambda s: getattr(s, name))(self)
             else:
                 # no need to wrap non-tensor properties,
                 # and they likely don't depend on the actual contents of the tensor
@@ -141,19 +141,21 @@ def wrapped_fn(*args, **kwargs):
                         res = cls.meta_with_dtype_and_shape(meta_noop, res.shape)
 
             if isinstance(res, cls._tensor_type):
-                def collect_replace(t: LazyBase):
-                    if collect_replace.shared_lazy is None:
-                        collect_replace.shared_lazy = t._lazy
-                    else:
-                        collect_replace.shared_lazy.extend(t._lazy)
-                        t._lazy = collect_replace.shared_lazy
+                class CollectSharedLazy:
+                    # emulating a static variable
+                    shared_lazy: None | deque[LazyBase] = None
 
-                # emulating a static variable
-                collect_replace.shared_lazy = None
+                    @staticmethod
+                    def collect_replace(t: LazyBase):
+                        if CollectSharedLazy.shared_lazy is None:
+                            CollectSharedLazy.shared_lazy = t._lazy
+                        else:
+                            CollectSharedLazy.shared_lazy.extend(t._lazy)
+                            t._lazy = CollectSharedLazy.shared_lazy
 
-                LazyBase._recurse_apply(args, collect_replace)
+                LazyBase._recurse_apply(args, CollectSharedLazy.collect_replace)
 
-                shared_lazy = collect_replace.shared_lazy
+                shared_lazy = CollectSharedLazy.shared_lazy
 
                 return cls(meta=cls.eager_to_meta(res), lazy=shared_lazy, args=args, func=lambda a: fn(*a, **kwargs))
             else:
@@ -184,6 +186,7 @@ def already_eager_to_eager(_t: LazyBase) -> Any:
                 lt._args = cls._recurse_apply(lt._args, already_eager_to_eager)
                 lt._data = lt._func(lt._args)
                 # sanity check
+                assert lt._data is not None
                 assert lt._data.dtype == lt._meta.dtype
                 assert lt._data.shape == lt._meta.shape
 
diff --git a/gguf-py/scripts/__init__.py b/gguf-py/scripts/__init__.py
index f9d29cb691d62..e77f2e9c97c31 100644
--- a/gguf-py/scripts/__init__.py
+++ b/gguf-py/scripts/__init__.py
@@ -1,3 +1,5 @@
+# pyright: reportUnusedImport=false
+
 from .gguf_convert_endian import main as gguf_convert_endian_entrypoint
 from .gguf_dump import main as gguf_dump_entrypoint
 from .gguf_set_metadata import main as gguf_set_metadata_entrypoint
diff --git a/gguf-py/scripts/gguf_hash.py b/gguf-py/scripts/gguf_hash.py
index 95677518209ed..770b79a93471c 100755
--- a/gguf-py/scripts/gguf_hash.py
+++ b/gguf-py/scripts/gguf_hash.py
@@ -63,9 +63,9 @@ def gguf_hash(reader: GGUFReader, filename: str, disable_progress_bar) -> None:
         bar.update(sum_weights_in_tensor)
 
         sha1_layer = hashlib.sha1()
-        sha1_layer.update(tensor.data)
-        sha1.update(tensor.data)
-        uuidv5_sha1.update(tensor.data)
+        sha1_layer.update(tensor.data.data)
+        sha1.update(tensor.data.data)
+        uuidv5_sha1.update(tensor.data.data)
         print("sha1    {0}  {1}:{2}".format(sha1_layer.hexdigest(), filename, tensor.name)) # noqa: NP100
 
     # Flush Hash Progress Bar
diff --git a/gguf-py/scripts/gguf_new_metadata.py b/gguf-py/scripts/gguf_new_metadata.py
index c4b90d5810a65..fce52a8c1164e 100755
--- a/gguf-py/scripts/gguf_new_metadata.py
+++ b/gguf-py/scripts/gguf_new_metadata.py
@@ -1,4 +1,6 @@
 #!/usr/bin/env python3
+from __future__ import annotations
+
 import logging
 import argparse
 import os
diff --git a/gguf-py/tests/test_gguf.py b/gguf-py/tests/test_gguf.py
index 0adeb7d55731a..76b52181e0391 100644
--- a/gguf-py/tests/test_gguf.py
+++ b/gguf-py/tests/test_gguf.py
@@ -1,4 +1,4 @@
-import gguf  # noqa: F401
+import gguf  # noqa: F401  # pyright: ignore[reportUnusedImport]
 
 # TODO: add tests
 
diff --git a/pyrightconfig.json b/pyrightconfig.json
index 020a71a4ec214..6016f4b6d0120 100644
--- a/pyrightconfig.json
+++ b/pyrightconfig.json
@@ -1,3 +1,21 @@
 {
   "extraPaths": ["gguf-py"],
-}
+  "pythonVersion": "3.9",
+  "pythonPlatform": "All",
+  "reportUnusedImport": "warning",
+  "reportDuplicateImport": "error",
+  "reportDeprecated": "warning",
+  "reportUnnecessaryTypeIgnoreComment": "warning",
+  "executionEnvironments": [
+    {
+      // TODO: make this version override work correctly
+      "root": "gguf-py",
+      "pythonVersion": "3.8",
+    },
+    {
+      // uses match expressions in steps.py
+      "root": "examples/server/tests",
+      "pythonVersion": "3.10",
+    },
+  ],
+ }
diff --git a/requirements/requirements-all.txt b/requirements/requirements-all.txt
new file mode 100644
index 0000000000000..94de59d7e1860
--- /dev/null
+++ b/requirements/requirements-all.txt
@@ -0,0 +1,12 @@
+-r ../examples/llava/requirements.txt
+-r ../examples/server/bench/requirements.txt
+-r ../examples/server/tests/requirements.txt
+
+-r ./requirements-compare-llama-bench.txt
+-r ./requirements-pydantic.txt
+-r ./requirements-test-tokenizer-random.txt
+
+-r ./requirements-convert_hf_to_gguf.txt
+-r ./requirements-convert_hf_to_gguf_update.txt
+-r ./requirements-convert_legacy_llama.txt
+-r ./requirements-convert_llama_ggml_to_gguf.txt
diff --git a/requirements/requirements-compare-llama-bench.txt b/requirements/requirements-compare-llama-bench.txt
new file mode 100644
index 0000000000000..e0aaa32043ce2
--- /dev/null
+++ b/requirements/requirements-compare-llama-bench.txt
@@ -0,0 +1,2 @@
+tabulate~=0.9.0
+GitPython~=3.1.43
diff --git a/requirements/requirements-pydantic.txt b/requirements/requirements-pydantic.txt
new file mode 100644
index 0000000000000..2f9455b147d68
--- /dev/null
+++ b/requirements/requirements-pydantic.txt
@@ -0,0 +1,2 @@
+docstring_parser~=0.15
+pydantic~=2.6.3
diff --git a/requirements/requirements-test-tokenizer-random.txt b/requirements/requirements-test-tokenizer-random.txt
new file mode 100644
index 0000000000000..2785e71a25718
--- /dev/null
+++ b/requirements/requirements-test-tokenizer-random.txt
@@ -0,0 +1 @@
+cffi~=1.16.0
diff --git a/scripts/check-requirements.sh b/scripts/check-requirements.sh
index 48f924c02d32c..d3bbded130daf 100755
--- a/scripts/check-requirements.sh
+++ b/scripts/check-requirements.sh
@@ -108,6 +108,11 @@ check_convert_script() {
         fatal "$py missing requirements. Expected: $reqs"
     fi
 
+    # Check that all sub-requirements are added to top-level requirements.txt
+    if ! grep -qF "$reqs" requirements.txt; then
+        fatal "$reqs needs to be added to requirements.txt"
+    fi
+
     local venv="$workdir/$pyname-venv"
     python3 -m venv "$venv"
 
@@ -134,12 +139,7 @@ EOF
 
 readonly ignore_eq_eq='check_requirements: ignore "=="'
 
-for req in "$reqs_dir"/*; do
-    # Check that all sub-requirements are added to top-level requirements.txt
-    if ! grep -qF "$req" requirements.txt; then
-        fatal "$req needs to be added to requirements.txt"
-    fi
-
+for req in */**/requirements*.txt; do
     # Make sure exact release versions aren't being pinned in the requirements
     # Filters out the ignore string
     if grep -vF "$ignore_eq_eq" "$req" | grep -q '=='; then
diff --git a/scripts/compare-llama-bench.py b/scripts/compare-llama-bench.py
index 513dde5e13f93..92b9e682a9f20 100755
--- a/scripts/compare-llama-bench.py
+++ b/scripts/compare-llama-bench.py
@@ -123,13 +123,13 @@
 
 try:
     repo = git.Repo(".", search_parent_directories=True)
-except git.exc.InvalidGitRepositoryError:
+except git.InvalidGitRepositoryError:
     repo = None
 
 
-def find_parent_in_data(commit):
+def find_parent_in_data(commit: git.Commit):
     """Helper function to find the most recent parent measured in number of commits for which there is data."""
-    heap = [(0, commit)]
+    heap: list[tuple[int, git.Commit]] = [(0, commit)]
     seen_hexsha8 = set()
     while heap:
         depth, current_commit = heapq.heappop(heap)
@@ -144,7 +144,7 @@ def find_parent_in_data(commit):
     return None
 
 
-def get_all_parent_hexsha8s(commit):
+def get_all_parent_hexsha8s(commit: git.Commit):
     """Helper function to recursively get hexsha8 values for all parents of a commit."""
     unvisited = [commit]
     visited   = []
diff --git a/scripts/gen-unicode-data.py b/scripts/gen-unicode-data.py
index 890e4d7c24eeb..2d9bde01c3ca7 100644
--- a/scripts/gen-unicode-data.py
+++ b/scripts/gen-unicode-data.py
@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import array
 import unicodedata
 import requests
@@ -133,7 +135,7 @@ def unicode_data_iter():
 
 
 # group ranges with same flags
-ranges_flags = [(0, codepoint_flags[0])]  # start, flags
+ranges_flags: list[tuple[int, int]] = [(0, codepoint_flags[0])]  # start, flags
 for codepoint, flags in enumerate(codepoint_flags):
     if flags != ranges_flags[-1][1]:
         ranges_flags.append((codepoint, flags))
@@ -141,11 +143,11 @@ def unicode_data_iter():
 
 
 # group ranges with same nfd
-ranges_nfd = [(0, 0, 0)]  # start, last, nfd
+ranges_nfd: list[tuple[int, int, int]] = [(0, 0, 0)]  # start, last, nfd
 for codepoint, norm in table_nfd:
     start = ranges_nfd[-1][0]
     if ranges_nfd[-1] != (start, codepoint - 1, norm):
-        ranges_nfd.append(None)
+        ranges_nfd.append(None)  # type: ignore[arg-type]  # dummy, will be replaced below
         start = codepoint
     ranges_nfd[-1] = (start, codepoint, norm)
 
@@ -179,13 +181,13 @@ def out(line=""):
 out("};\n")
 
 out("const std::unordered_map unicode_map_lowercase = {")
-for tuple in table_lowercase:
-    out("{0x%06X, 0x%06X}," % tuple)
+for tuple_lw in table_lowercase:
+    out("{0x%06X, 0x%06X}," % tuple_lw)
 out("};\n")
 
 out("const std::unordered_map unicode_map_uppercase = {")
-for tuple in table_uppercase:
-    out("{0x%06X, 0x%06X}," % tuple)
+for tuple_up in table_uppercase:
+    out("{0x%06X, 0x%06X}," % tuple_up)
 out("};\n")
 
 out("const std::vector unicode_ranges_nfd = {  // start, last, nfd")
diff --git a/tests/test-tokenizer-random.py b/tests/test-tokenizer-random.py
index 48cab8a1e0859..c50a8ca32f657 100644
--- a/tests/test-tokenizer-random.py
+++ b/tests/test-tokenizer-random.py
@@ -6,6 +6,8 @@
 #   python3 tests/test-tokenizer-random.py ./models/ggml-vocab-llama-bpe.gguf ./models/tokenizers/llama-bpe
 #
 
+from __future__ import annotations
+
 import time
 import logging
 import argparse
@@ -13,7 +15,9 @@
 import random
 import unicodedata
 
-from typing import Iterator
+from pathlib import Path
+from typing import Any, Iterator, cast
+from typing_extensions import Buffer
 
 import cffi
 from transformers import AutoTokenizer
@@ -28,15 +32,15 @@ class LibLlama:
     DEFAULT_PATH_INCLUDES = ["./ggml/include/", "./include/"]
     DEFAULT_PATH_LIBLLAMA = "./build/src/libllama.so"  # CMakeLists.txt: BUILD_SHARED_LIBS ON
 
-    def __init__(self, path_llama_h: str = None, path_includes: list[str] = [], path_libllama: str = None):
+    def __init__(self, path_llama_h: str | None = None, path_includes: list[str] = [], path_libllama: str | None = None):
         path_llama_h = path_llama_h or self.DEFAULT_PATH_LLAMA_H
         path_includes = path_includes or self.DEFAULT_PATH_INCLUDES
         path_libllama = path_libllama or self.DEFAULT_PATH_LIBLLAMA
         (self.ffi, self.lib) = self._load_libllama_cffi(path_llama_h, path_includes, path_libllama)
         self.lib.llama_backend_init()
 
-    def _load_libllama_cffi(self, path_llama_h: str, path_includes: list[str], path_libllama: str):
-        cmd = ["gcc", "-E", "-P", "-D__restrict=", "-D__attribute__(x)=", "-D__asm__(x)="]
+    def _load_libllama_cffi(self, path_llama_h: str, path_includes: list[str], path_libllama: str) -> tuple[cffi.FFI, Any]:
+        cmd = ["gcc", "-O0", "-E", "-P", "-D__restrict=", "-D__attribute__(x)=", "-D__asm__(x)="]
         cmd += ["-I" + path for path in path_includes] + [path_llama_h]
         res = subprocess.run(cmd, stdout=subprocess.PIPE)
         assert (res.returncode == 0)
@@ -68,7 +72,7 @@ def context_default_params(self, **kwargs):
 class LibLlamaModel:
 
     def __init__(self, libllama: LibLlama, path_model: str, mparams={}, cparams={}):
-        self.lib = libllama.lib
+        self.lib: Any = libllama.lib
         self.ffi = libllama.ffi
         if isinstance(mparams, dict):
             mparams = libllama.model_default_params(**mparams)
@@ -94,11 +98,11 @@ def free(self):
         self.lib = None
 
     def tokenize(self, text: str, add_special: bool = False, parse_special: bool = False) -> list[int]:
-        text = text.encode("utf-8")
-        num = self.lib.llama_tokenize(self.model, text, len(text), self.token_ids, len(self.token_ids), add_special, parse_special)
+        encoded_text: bytes = text.encode("utf-8")
+        num = self.lib.llama_tokenize(self.model, encoded_text, len(encoded_text), self.token_ids, len(self.token_ids), add_special, parse_special)
         while num < 0 and len(self.token_ids) < (16 << 20):
             self.token_ids = self.ffi.new("llama_token[]", -2 * num)
-            num = self.lib.llama_tokenize(self.model, text, len(text), self.token_ids, len(self.token_ids), add_special, parse_special)
+            num = self.lib.llama_tokenize(self.model, encoded_text, len(encoded_text), self.token_ids, len(self.token_ids), add_special, parse_special)
         return list(self.token_ids[0:num])
 
     def detokenize(self, ids: list[int], remove_special: bool = False, unparse_special: bool = False) -> str:
@@ -110,7 +114,7 @@ def detokenize(self, ids: list[int], remove_special: bool = False, unparse_speci
         while num < 0 and len(self.text_buff) < (16 << 20):
             self.text_buff = self.ffi.new("uint8_t[]", -2 * num)
             num = self.lib.llama_detokenize(self.model, self.token_ids, len(ids), self.text_buff, len(self.text_buff), remove_special, unparse_special)
-        return str(self.ffi.buffer(self.text_buff, num), encoding="utf-8", errors="replace")  # replace errors with '\uFFFD'
+        return str(cast(Buffer, self.ffi.buffer(self.text_buff, num)), encoding="utf-8", errors="replace")  # replace errors with '\uFFFD'
 
 
 class Tokenizer:
@@ -152,7 +156,7 @@ def decode(self, ids: list[int]) -> str:
 
 class TokenizerLlamaCpp (Tokenizer):
 
-    libllama: LibLlama = None
+    libllama: LibLlama | None = None
 
     def __init__(self, vocab_file: str):
         if not self.libllama:
@@ -404,7 +408,7 @@ def generator_random_vocab_words(tokenizer: TokenizerGroundtruth, iterations=100
 
 def compare_tokenizers(tokenizer1: TokenizerGroundtruth, tokenizer2: TokenizerLlamaCpp, generator: Iterator[str]):
 
-    def find_first_mismatch(ids1: list[int], ids2: list[int]):
+    def find_first_mismatch(ids1: list[int] | str, ids2: list[int] | str):
         for i, (a, b) in enumerate(zip(ids1, ids2)):
             if a != b:
                 return i
@@ -433,7 +437,7 @@ def check_detokenizer(text: str, text1: str, text2: str) -> bool:
     decode_errors = 0
     MAX_ERRORS = 10
 
-    logger.info("%s: %s" % (generator.__name__, "ini"))
+    logger.info("%s: %s" % (generator.__qualname__, "ini"))
     for text in generator:
         # print(repr(text), text.encode())
         # print(repr(text), hex(ord(text[0])), text.encode())
@@ -472,13 +476,13 @@ def check_detokenizer(text: str, text1: str, text2: str) -> bool:
             break
 
     t_total = time.perf_counter() - t_start
-    logger.info(f"{generator.__name__}: end,  {t_encode1=:.3f} {t_encode2=:.3f}  {t_decode1=:.3f} {t_decode2=:.3f}  {t_total=:.3f}")
+    logger.info(f"{generator.__qualname__}: end,  {t_encode1=:.3f} {t_encode2=:.3f}  {t_decode1=:.3f} {t_decode2=:.3f}  {t_total=:.3f}")
 
 
-def main(argv: list[str] = None):
+def main(argv: list[str] | None = None):
     parser = argparse.ArgumentParser()
-    parser.add_argument("vocab_file", help="path to vocab 'gguf' file")
-    parser.add_argument("dir_tokenizer", help="directory containing 'tokenizer.model' file")
+    parser.add_argument("vocab_file", type=str, help="path to vocab 'gguf' file")
+    parser.add_argument("dir_tokenizer", type=str, help="directory containing 'tokenizer.model' file")
     parser.add_argument("--verbose", action="store_true", help="increase output verbosity")
     args = parser.parse_args(argv)
 
@@ -520,7 +524,7 @@ def main(argv: list[str] = None):
         format   = "%(levelname)s %(message)s",
     )
 
-    path_tokenizers   = "./models/tokenizers/"
+    path_tokenizers   = Path("./models/tokenizers/")
     path_vocab_format = "./models/ggml-vocab-%s.gguf"
 
     tokenizers = [
@@ -556,6 +560,6 @@ def main(argv: list[str] = None):
     for tokenizer in tokenizers:
         logger.info("-" * 50)
         logger.info(f"TOKENIZER: '{tokenizer}'")
-        vocab_file = path_vocab_format % tokenizer
-        dir_tokenizer = path_tokenizers + "/" + tokenizer
-        main([vocab_file, dir_tokenizer, "--verbose"])
+        vocab_file = Path(path_vocab_format % tokenizer)
+        dir_tokenizer = path_tokenizers / tokenizer
+        main([str(vocab_file), str(dir_tokenizer), "--verbose"])

From 04ce3a8b19256a155aea4d14eaa87edf274c93c3 Mon Sep 17 00:00:00 2001
From: toyer <2042519524@qq.com>
Date: Mon, 8 Jul 2024 13:57:19 +0800
Subject: [PATCH 130/326] readme : add supported glm models (#8360)

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index aba6a4c59ada0..5498d5fc6755a 100644
--- a/README.md
+++ b/README.md
@@ -96,6 +96,7 @@ Typically finetunes of the base models below are supported as well.
 - [x] [GritLM-7B](https://huggingface.co/GritLM/GritLM-7B) + [GritLM-8x7B](https://huggingface.co/GritLM/GritLM-8x7B)
 - [x] [OLMo](https://allenai.org/olmo)
 - [x] [GPT-NeoX](https://github.com/EleutherAI/gpt-neox) + [Pythia](https://github.com/EleutherAI/pythia)
+- [x] [ChatGLM3-6b](https://huggingface.co/THUDM/chatglm3-6b) + [ChatGLM4-9b](https://huggingface.co/THUDM/glm-4-9b)
 
 (instructions for supporting more models: [HOWTO-add-model.md](./docs/HOWTO-add-model.md))
 

From ffd00797d81ef7db1528b9e10adbdc333ade6495 Mon Sep 17 00:00:00 2001
From: Kevin Wang 
Date: Mon, 8 Jul 2024 02:31:55 -0400
Subject: [PATCH 131/326] common : avoid unnecessary logits fetch (#8358)

---
 common/sampling.cpp | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/common/sampling.cpp b/common/sampling.cpp
index 9f332fe573683..e9db2715f2649 100644
--- a/common/sampling.cpp
+++ b/common/sampling.cpp
@@ -282,8 +282,6 @@ static llama_token llama_sampling_sample_impl(
         GGML_ASSERT(!original_logits.empty());
     }
     llama_token id = 0;
-    // Get a pointer to the logits
-    float * logits = llama_get_logits_ith(ctx_main, idx);
 
     if (temp < 0.0) {
         // greedy sampling, with probs
@@ -324,6 +322,9 @@ static llama_token llama_sampling_sample_impl(
     }
 
     if (ctx_sampling->grammar != NULL && !is_resampling) {
+        // Get a pointer to the logits
+        float * logits = llama_get_logits_ith(ctx_main, idx);
+
         // Create an array with a single token data element for the sampled id
         llama_token_data single_token_data = {id, logits[id], 0.0f};
         llama_token_data_array single_token_data_array = { &single_token_data, 1, false };

From 6f0dbf6ab087bcd286fb78560099ca0458316735 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Mon, 8 Jul 2024 09:34:35 +0300
Subject: [PATCH 132/326] infill : assert prefix/suffix tokens + remove old
 space logic (#8351)

---
 common/log.h               |  2 +-
 examples/infill/infill.cpp | 25 ++++++++-----------------
 2 files changed, 9 insertions(+), 18 deletions(-)

diff --git a/common/log.h b/common/log.h
index 09fa63c2677a7..1bc5328ce3e11 100644
--- a/common/log.h
+++ b/common/log.h
@@ -630,7 +630,7 @@ inline std::string LOG_TOKENS_TOSTR_PRETTY(const C & ctx, const T & tokens)
     buf << "[ ";
 
     bool first = true;
-    for (const auto &token : tokens)
+    for (const auto & token : tokens)
     {
         if (!first) {
             buf << ", ";
diff --git a/examples/infill/infill.cpp b/examples/infill/infill.cpp
index 0e682154d5f6b..dc93d2301391c 100644
--- a/examples/infill/infill.cpp
+++ b/examples/infill/infill.cpp
@@ -204,21 +204,17 @@ int main(int argc, char ** argv) {
     GGML_ASSERT(llama_add_eos_token(model) != 1);
     LOG("add_bos: %d\n", add_bos);
 
-    bool suff_rm_leading_spc = params.escape;
-    if (suff_rm_leading_spc && params.input_suffix.find_first_of(' ') == 0 && params.input_suffix.size() > 1) {
-        params.input_suffix.erase(0, 1);
-        suff_rm_leading_spc = false;
-    }
     std::vector embd_inp;
     std::vector embd_end;
     std::vector inp_pfx = ::llama_tokenize(ctx, params.input_prefix, false);
     std::vector inp_sfx = ::llama_tokenize(ctx, params.input_suffix, false);
-    const int space_token = 29871;
-    if (suff_rm_leading_spc && inp_sfx[0] == space_token) {
-        inp_sfx.erase(inp_sfx.begin());
-    }
+
+    GGML_ASSERT(llama_token_prefix(model) >= 0);
+    GGML_ASSERT(llama_token_suffix(model) >= 0);
+
     inp_pfx.insert(inp_pfx.begin(), llama_token_prefix(model));
     inp_sfx.insert(inp_sfx.begin(), llama_token_suffix(model));
+
     embd_inp = params.spm_infill ? inp_sfx : inp_pfx;
     embd_end = params.spm_infill ? inp_pfx : inp_sfx;
     if (add_bos) {
@@ -516,19 +512,14 @@ int main(int argc, char ** argv) {
                     string_process_escapes(params.input_prefix);
                     string_process_escapes(params.input_suffix);
                 }
-                suff_rm_leading_spc = params.escape;
-                if (suff_rm_leading_spc && params.input_suffix.find_first_of(' ') == 0 && params.input_suffix.size() > 1) {
-                    params.input_suffix.erase(0, 1);
-                    suff_rm_leading_spc = false;
-                }
+
                 // tokenize new prefix and suffix
                 std::vector inp_pfx = ::llama_tokenize(ctx, params.input_prefix, false);
                 std::vector inp_sfx = ::llama_tokenize(ctx, params.input_suffix, false);
-                if (suff_rm_leading_spc && inp_sfx[0] == space_token) {
-                    inp_sfx.erase(inp_sfx.begin());
-                }
+
                 inp_pfx.insert(inp_pfx.begin(), llama_token_prefix(model));
                 inp_sfx.insert(inp_sfx.begin(), llama_token_suffix(model));
+
                 embd_inp = params.spm_infill ? inp_sfx : inp_pfx;
                 embd_end = params.spm_infill ? inp_pfx : inp_sfx;
                 if (add_bos) {

From 470939d483d1c89b7292f78bac1fd27c42c171ce Mon Sep 17 00:00:00 2001
From: Kevin Wang 
Date: Mon, 8 Jul 2024 03:26:53 -0400
Subject: [PATCH 133/326] common : preallocate sampling token data vector
 (#8363)

`emplace_back` repeatedly-called is slower than preallocating the vector to the vocab size and directly inserting the data. Some rudimentary profiling with `chrono` improves the performance of this block of code from ~500us/op to ~40us/op.

Overall, this slightly improves the sampling performance which has a more substantial impact for the `examples/lookahead` implementation -- I am able to see a ~10% performance boost in lookahead inference.
---
 common/sampling.cpp | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/common/sampling.cpp b/common/sampling.cpp
index e9db2715f2649..6a483c8154574 100644
--- a/common/sampling.cpp
+++ b/common/sampling.cpp
@@ -378,7 +378,7 @@ static llama_token_data_array llama_sampling_prepare_impl(
     if (ctx_sampling->grammar != NULL && !apply_grammar) {
         GGML_ASSERT(original_logits != NULL);
         // Only make a copy of the original logits if we are not applying grammar checks, not sure if I actually have to do this.
-        *original_logits = {logits, logits + llama_n_vocab(llama_get_model(ctx_main))};
+        *original_logits = {logits, logits + n_vocab};
     }
 
     // apply params.logit_bias map
@@ -391,10 +391,10 @@ static llama_token_data_array llama_sampling_prepare_impl(
         llama_sample_apply_guidance(ctx_main, logits, logits_guidance, params.cfg_scale);
     }
 
-    cur.clear();
+    cur.resize(n_vocab);
 
     for (llama_token token_id = 0; token_id < n_vocab; token_id++) {
-        cur.emplace_back(llama_token_data{token_id, logits[token_id], 0.0f});
+        cur[token_id] = llama_token_data{token_id, logits[token_id], 0.0f};
     }
 
     llama_token_data_array cur_p = { cur.data(), cur.size(), false };

From fde13b3bb9f569f07fd8af74696ee48a43d05131 Mon Sep 17 00:00:00 2001
From: John Balis 
Date: Tue, 2 Jul 2024 11:09:52 -0500
Subject: [PATCH 134/326] feat: cuda implementation for
 `ggml_conv_transpose_1d` (ggml/854)

* conv transpose 1d passing test for 1d input and kernel

* working for different input and output channel counts, added test for variable stride

* initial draft appears to work with stride other than 1

* working with all old and new conv1d  tests

* added a test for large tensors

* removed use cuda hardcoding

* restored test-conv-transpose.c

* removed unused arugments, and fixed bug where test failure would cause subsequent tests to fail

* fixed accumulator bug

* added test to test-backend-ops

* fixed mistake

* addressed review

* fixed includes

* removed blank lines

* style and warning fixes

* return failure when test fails

* fix supports_op

---------

Co-authored-by: slaren 
---
 ggml/src/ggml-cuda.cu                    | 13 ++++
 ggml/src/ggml-cuda/conv-transpose-1d.cu  | 87 ++++++++++++++++++++++++
 ggml/src/ggml-cuda/conv-transpose-1d.cuh |  5 ++
 tests/test-backend-ops.cpp               | 42 +++++++++++-
 4 files changed, 146 insertions(+), 1 deletion(-)
 create mode 100644 ggml/src/ggml-cuda/conv-transpose-1d.cu
 create mode 100644 ggml/src/ggml-cuda/conv-transpose-1d.cuh

diff --git a/ggml/src/ggml-cuda.cu b/ggml/src/ggml-cuda.cu
index 1c9ccc8a15e54..ed784ea1c2024 100644
--- a/ggml/src/ggml-cuda.cu
+++ b/ggml/src/ggml-cuda.cu
@@ -29,6 +29,7 @@
 #include "ggml-cuda/tsembd.cuh"
 #include "ggml-cuda/unary.cuh"
 #include "ggml-cuda/upscale.cuh"
+#include "ggml-cuda/conv-transpose-1d.cuh"
 
 #include 
 #include 
@@ -2261,6 +2262,9 @@ static bool ggml_cuda_compute_forward(ggml_backend_cuda_context & ctx, struct gg
         case GGML_OP_IM2COL:
             ggml_cuda_op_im2col(ctx, dst);
             break;
+        case GGML_OP_CONV_TRANSPOSE_1D:
+            ggml_cuda_op_conv_transpose_1d(ctx,dst);
+            break;
         case GGML_OP_POOL_2D:
             ggml_cuda_op_pool2d(ctx, dst);
             break;
@@ -2804,6 +2808,15 @@ GGML_CALL static bool ggml_backend_cuda_supports_op(ggml_backend_t backend, cons
                 ggml_type src0_type = op->src[0]->type;
                 return src0_type != GGML_TYPE_I32 && src0_type != GGML_TYPE_I16;
             } break;
+        case GGML_OP_CONV_TRANSPOSE_1D:
+            {
+                ggml_type src0_type = op->src[0]->type;
+                ggml_type src1_type = op->src[1]->type;
+                if (src0_type == GGML_TYPE_F32 && src1_type == GGML_TYPE_F32) {
+                    return true;
+                }
+                return false;
+            } break;
         case GGML_OP_NONE:
         case GGML_OP_RESHAPE:
         case GGML_OP_VIEW:
diff --git a/ggml/src/ggml-cuda/conv-transpose-1d.cu b/ggml/src/ggml-cuda/conv-transpose-1d.cu
new file mode 100644
index 0000000000000..b1e94d6f770aa
--- /dev/null
+++ b/ggml/src/ggml-cuda/conv-transpose-1d.cu
@@ -0,0 +1,87 @@
+#include "conv-transpose-1d.cuh"
+
+static  __global__ void conv_transpose_1d_kernel(
+        const int s0, const int p0, const int d0, const int output_size,
+        const int src0_ne0, const int src0_ne1, const int src0_ne2, const int src0_ne3,
+        const int src1_ne0, const int src1_ne1, const int src1_ne2, const int src1_ne3,
+        const int dst_ne0, const int dst_ne1, const int dst_ne2, const int dst_ne3,
+        const float * src0, const float * src1,  float * dst) {
+    int global_index = threadIdx.x + blockIdx.x * blockDim.x;
+    if (global_index >= output_size) {
+        return;
+    }
+
+    int out_index = global_index / dst_ne0;
+
+    float accumulator = 0;
+
+    for (int c = 0; c < src0_ne2; c++) {
+        int idx = global_index % dst_ne0;
+
+        int kernel_offset = (src0_ne0 * src0_ne1 * c) + (out_index * src0_ne0);
+        int input_offset = src1_ne0 * c;
+
+        for (int i = 0; i < src1_ne0; i++) {
+            if (!(idx >= i*s0 && idx < i*s0 + src0_ne0)) {
+                continue;
+            }
+            int weight_idx = idx - i*s0;
+
+            float kernel_weight = src0[kernel_offset + weight_idx];
+            float input_value =  src1[input_offset+i];
+
+            accumulator += kernel_weight * input_value;
+        }
+    }
+    dst[global_index] = accumulator;
+}
+
+static void conv_transpose_1d_f32_f32_cuda(
+        const int s0, const int p0, const int d0, const int output_size,
+        const int src0_ne0, const int src0_ne1, const int src0_ne2, const int src0_ne3,
+        const int src1_ne0, const int src1_ne1, const int src1_ne2, const int src1_ne3,
+        const int dst_ne0, const int dst_ne1, const int dst_ne2, const int dst_ne3,
+        const float * src0, const float * src1,  float * dst,
+        cudaStream_t stream) {
+
+    const int num_blocks = (output_size + CUDA_CONV_TRANPOSE_1D_BLOCK_SIZE - 1) / CUDA_CONV_TRANPOSE_1D_BLOCK_SIZE;
+    conv_transpose_1d_kernel<<>>(
+        s0,p0,d0,output_size,
+        src0_ne0, src0_ne1,  src0_ne2, src0_ne3,
+        src1_ne0, src1_ne1,  src1_ne2, src1_ne3,
+        dst_ne0,  dst_ne1,   dst_ne2,  dst_ne3,
+        src0,src1, dst);
+}
+
+void ggml_cuda_op_conv_transpose_1d(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
+    const ggml_tensor * src0 = dst->src[0];
+    const float * src0_d = (const float *)src0->data;
+
+    const ggml_tensor * src1 = dst->src[1];
+    const float * src1_d = (const float *)src1->data;
+
+    float * dst_d = (float *)dst->data;
+    cudaStream_t stream = ctx.stream();
+
+    GGML_ASSERT(src0->type == GGML_TYPE_F32);
+    GGML_ASSERT( dst->type == GGML_TYPE_F32);
+
+    GGML_ASSERT(ggml_is_contiguous(src0));
+    GGML_ASSERT(ggml_is_contiguous(src1));
+
+    const int32_t * opts = (const int32_t *)dst->op_params;
+
+    const int s0 = opts[0];
+    const int p0 = 0;//opts[3];
+    const int d0 = 1;//opts[4];
+
+    const int64_t kernel_size = ggml_nelements(src0);
+    const int64_t input_size = ggml_nelements(src1);
+    const int64_t output_size = ggml_nelements(dst);
+
+    conv_transpose_1d_f32_f32_cuda(s0, p0, d0, output_size,
+        src0->ne[0], src0->ne[1], src0->ne[2], src0->ne[3],
+        src1->ne[0], src1->ne[1], src1->ne[2], src1->ne[3],
+        dst->ne[0], dst->ne[1], dst->ne[2], dst->ne[3],
+        src0_d, src1_d, dst_d, stream);
+}
diff --git a/ggml/src/ggml-cuda/conv-transpose-1d.cuh b/ggml/src/ggml-cuda/conv-transpose-1d.cuh
new file mode 100644
index 0000000000000..6c2cf666b68da
--- /dev/null
+++ b/ggml/src/ggml-cuda/conv-transpose-1d.cuh
@@ -0,0 +1,5 @@
+#include "common.cuh"
+
+#define CUDA_CONV_TRANPOSE_1D_BLOCK_SIZE 256
+
+void ggml_cuda_op_conv_transpose_1d(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp
index 2bb71ac03817f..83d4a0eb153cf 100644
--- a/tests/test-backend-ops.cpp
+++ b/tests/test-backend-ops.cpp
@@ -1266,6 +1266,36 @@ struct test_pool2d : public test_case {
     }
 };
 
+// GGML_OP_CONV_TRANSPOSE_1D
+struct test_conv_transpose_1d : public test_case {
+    
+    const std::array ne_input;
+    const std::array ne_kernel;
+
+    // stride
+    const int s0;
+    // padding
+    const int p0;
+    // dilation
+    const int d0;
+
+    std::string vars() override {
+        return VARS_TO_STR5(ne_input, ne_kernel, s0, p0, d0);
+    }
+
+    test_conv_transpose_1d(std::array ne_input = {197, 32, 1, 1}, // [input_width, input_height, input_channels, 1]
+                           std::array ne_kernel = {16, 32, 32, 1}, // [kernel_width, kernel_height, input_channels, 1]
+                           int s0 = 1, int p0 = 0, int d0 = 1)
+        : ne_input(ne_input), ne_kernel(ne_kernel), s0(s0), p0(p0), d0(d0) {}
+
+    ggml_tensor * build_graph(ggml_context * ctx) override {
+        ggml_tensor * input = ggml_new_tensor(ctx, GGML_TYPE_F32, 4, ne_input.data());
+        ggml_tensor * kernel = ggml_new_tensor(ctx, GGML_TYPE_F32, 4, ne_kernel.data());
+        ggml_tensor * out = ggml_conv_transpose_1d(ctx, kernel, input, s0, p0, d0);
+        return out;
+    }
+};
+
 // GGML_OP_IM2COL
 struct test_im2col : public test_case {
     const ggml_type type_input;
@@ -1279,7 +1309,7 @@ struct test_im2col : public test_case {
     // padding
     const int p0;
     const int p1;
-    // dilatation
+    // dilation
     const int d0;
     const int d1;
     // mode
@@ -2098,6 +2128,16 @@ static bool test_backend(ggml_backend_t backend, test_mode mode, const char * op
     test_cases.emplace_back(new test_im2col(GGML_TYPE_F32, GGML_TYPE_F16, GGML_TYPE_F32));
     test_cases.emplace_back(new test_im2col(GGML_TYPE_F32, GGML_TYPE_F16, GGML_TYPE_F16));
 
+    test_cases.emplace_back(new test_conv_transpose_1d());
+    test_cases.emplace_back(new test_conv_transpose_1d({3,2,1,1}, {2,3,2,1}, 3, 0, 1));
+    test_cases.emplace_back(new test_conv_transpose_1d({3,2,1,1}, {2,3,2,1}, 2, 0, 1));
+    test_cases.emplace_back(new test_conv_transpose_1d({3,2,1,1}, {2,3,2,1}, 1, 0, 1));
+    test_cases.emplace_back(new test_conv_transpose_1d({3,2,1,1}, {3,2,2,1}, 2, 0, 1));
+    test_cases.emplace_back(new test_conv_transpose_1d({3,2,1,1}, {3,2,2,1}, 1, 0, 1));
+    test_cases.emplace_back(new test_conv_transpose_1d({3,2,1,1}, {3,1,2,1}, 1, 0, 1));
+    test_cases.emplace_back(new test_conv_transpose_1d({2,1,1,1}, {3,1,1,1}, 1, 0, 1));
+
+
     test_cases.emplace_back(new test_repeat(GGML_TYPE_F32, {10, 10, 10, 10}, {1, 1, 1, 1}));
     test_cases.emplace_back(new test_repeat(GGML_TYPE_F32, {10, 10, 10, 10}, {2, 1, 1, 1}));
     test_cases.emplace_back(new test_repeat(GGML_TYPE_F32, {10, 10, 10, 10}, {1, 2, 1, 1}));

From 6847d54c4f72f8bf6767b6feae7a95394654335e Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Mon, 8 Jul 2024 10:39:36 +0300
Subject: [PATCH 135/326] tests : fix whitespace (#0)

---
 tests/test-backend-ops.cpp | 10 +++-------
 1 file changed, 3 insertions(+), 7 deletions(-)

diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp
index 83d4a0eb153cf..a1bfc8fddd418 100644
--- a/tests/test-backend-ops.cpp
+++ b/tests/test-backend-ops.cpp
@@ -1268,16 +1268,12 @@ struct test_pool2d : public test_case {
 
 // GGML_OP_CONV_TRANSPOSE_1D
 struct test_conv_transpose_1d : public test_case {
-    
     const std::array ne_input;
     const std::array ne_kernel;
 
-    // stride
-    const int s0;
-    // padding
-    const int p0;
-    // dilation
-    const int d0;
+    const int s0; // stride
+    const int p0; // padding
+    const int d0; // dilation
 
     std::string vars() override {
         return VARS_TO_STR5(ne_input, ne_kernel, s0, p0, d0);

From 2ee44c9a1865a928ccbbc16a2d7841d7513f31c1 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Mon, 8 Jul 2024 10:39:50 +0300
Subject: [PATCH 136/326] sync : ggml

ggml-ci
---
 scripts/sync-ggml.last | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/scripts/sync-ggml.last b/scripts/sync-ggml.last
index 2da33e913bc8f..80159b70b9414 100644
--- a/scripts/sync-ggml.last
+++ b/scripts/sync-ggml.last
@@ -1 +1 @@
-5378ea0d3c2f25bcd330ecb226ad2db454be86d0
+e3b3846976c94163f2b3dd128cc959782653edbb

From 3f2d538b817112ad8429341c7e8657dcd660f4d3 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Mon, 8 Jul 2024 13:51:31 +0300
Subject: [PATCH 137/326] scripts : fix sync for sycl

---
 scripts/sync-ggml-am.sh | 3 +++
 scripts/sync-ggml.sh    | 1 +
 2 files changed, 4 insertions(+)

diff --git a/scripts/sync-ggml-am.sh b/scripts/sync-ggml-am.sh
index b05a33747f831..ba3bedf21342a 100755
--- a/scripts/sync-ggml-am.sh
+++ b/scripts/sync-ggml-am.sh
@@ -63,6 +63,7 @@ while read c; do
         src/ggml*.metal \
         src/ggml*.cu \
         src/ggml-cuda/* \
+        src/ggml-sycl/* \
         include/ggml*.h \
         tests/test-opt.cpp \
         tests/test-grad0.cpp \
@@ -113,6 +114,7 @@ if [ -f $SRC_LLAMA/ggml-src.patch ]; then
     # src/ggml-quants.c       -> ggml/src/ggml-quants.c
     # src/ggml-quants.h       -> ggml/src/ggml-quants.h
     # src/ggml-rpc.cpp        -> ggml/src/ggml-rpc.cpp
+    # src/ggml-sycl/*         -> ggml/src/ggml-sycl/
     # src/ggml-sycl.cpp       -> ggml/src/ggml-sycl.cpp
     # src/ggml-vulkan.cpp     -> ggml/src/ggml-vulkan.cpp
     #
@@ -153,6 +155,7 @@ if [ -f $SRC_LLAMA/ggml-src.patch ]; then
         -e 's/([[:space:]]|[ab]\/)src\/ggml-quants\.c/\1ggml\/src\/ggml-quants.c/g' \
         -e 's/([[:space:]]|[ab]\/)src\/ggml-quants\.h/\1ggml\/src\/ggml-quants.h/g' \
         -e 's/([[:space:]]|[ab]\/)src\/ggml-rpc\.cpp/\1ggml\/src\/ggml-rpc.cpp/g' \
+        -e 's/([[:space:]]|[ab]\/)src\/ggml-sycl\//\1ggml\/src\/ggml-sycl\//g' \
         -e 's/([[:space:]]|[ab]\/)src\/ggml-sycl\.cpp/\1ggml\/src\/ggml-sycl.cpp/g' \
         -e 's/([[:space:]]|[ab]\/)src\/ggml-vulkan\.cpp/\1ggml\/src\/ggml-vulkan.cpp/g' \
         -e 's/([[:space:]]|[ab]\/)include\/ggml\.h/\1ggml\/include\/ggml.h/g' \
diff --git a/scripts/sync-ggml.sh b/scripts/sync-ggml.sh
index 2f32c1ce84cc7..402446ef95b77 100755
--- a/scripts/sync-ggml.sh
+++ b/scripts/sync-ggml.sh
@@ -18,6 +18,7 @@ cp -rpv ../ggml/src/ggml-metal.metal    ./ggml/src/ggml-metal.metal
 cp -rpv ../ggml/src/ggml-quants.c       ./ggml/src/ggml-quants.c
 cp -rpv ../ggml/src/ggml-quants.h       ./ggml/src/ggml-quants.h
 cp -rpv ../ggml/src/ggml-rpc.cpp        ./ggml/src/ggml-rpc.cpp
+cp -rpv ../ggml/src/ggml-sycl/*         ./ggml/src/ggml-sycl/
 cp -rpv ../ggml/src/ggml-sycl.cpp       ./ggml/src/ggml-sycl.cpp
 cp -rpv ../ggml/src/ggml-vulkan.cpp     ./ggml/src/ggml-vulkan.cpp
 

From 2ec846d558f6385ea647f7b8e665eb249c1ebce7 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Alberto=20Cabrera=20P=C3=A9rez?= 
Date: Mon, 8 Jul 2024 14:22:41 +0100
Subject: [PATCH 138/326] sycl : fix powf call in device code (#8368)

---
 ggml/src/ggml-sycl/rope.cpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/ggml/src/ggml-sycl/rope.cpp b/ggml/src/ggml-sycl/rope.cpp
index eabf1693e2d2f..6f507941a022a 100644
--- a/ggml/src/ggml-sycl/rope.cpp
+++ b/ggml/src/ggml-sycl/rope.cpp
@@ -55,7 +55,7 @@ static void rope_norm(
     const int i = row*ne0 + i0;
     const int i2 = row/p_delta_rows;
 
-    const float theta_base = pos[i2]*powf(theta_scale, i0/2.0f);
+    const float theta_base = pos[i2] * sycl::pow(theta_scale, i0 / 2.0f);
 
     const float freq_factor = has_ff ? freq_factors[i0/2] : 1.0f;
 
@@ -98,7 +98,7 @@ static void rope_neox(
     const int i  = row*ne0 + i0/2;
     const int i2 = row/p_delta_rows;
 
-    const float theta_base = pos[i2]*powf(theta_scale, i0/2.0f);
+    const float theta_base = pos[i2] * sycl::pow(theta_scale, i0 / 2.0f);
 
     const float freq_factor = has_ff ? freq_factors[i0/2] : 1.0f;
 

From c4dd11d1d3903e1922c06242e189f6310fc4d8c3 Mon Sep 17 00:00:00 2001
From: b4b4o 
Date: Mon, 8 Jul 2024 22:19:24 +0800
Subject: [PATCH 139/326] readme : fix web link error [no ci] (#8347)

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 5498d5fc6755a..aa70708116571 100644
--- a/README.md
+++ b/README.md
@@ -98,7 +98,7 @@ Typically finetunes of the base models below are supported as well.
 - [x] [GPT-NeoX](https://github.com/EleutherAI/gpt-neox) + [Pythia](https://github.com/EleutherAI/pythia)
 - [x] [ChatGLM3-6b](https://huggingface.co/THUDM/chatglm3-6b) + [ChatGLM4-9b](https://huggingface.co/THUDM/glm-4-9b)
 
-(instructions for supporting more models: [HOWTO-add-model.md](./docs/HOWTO-add-model.md))
+(instructions for supporting more models: [HOWTO-add-model.md](./docs/development/HOWTO-add-model.md))
 
 **Multimodal models:**
 

From a130eccef42b75a84da270411cefeed45c153e30 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Alberto=20Cabrera=20P=C3=A9rez?=
 
Date: Mon, 8 Jul 2024 21:35:17 +0100
Subject: [PATCH 140/326] labeler : updated sycl to match docs and code
 refactor (#8373)

---
 .github/labeler.yml | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/.github/labeler.yml b/.github/labeler.yml
index 9c0397d16e1a0..89436740d1ffb 100644
--- a/.github/labeler.yml
+++ b/.github/labeler.yml
@@ -16,7 +16,9 @@ SYCL:
         - any-glob-to-any-file:
             - ggml/include/ggml-sycl.h
             - ggml/src/ggml-sycl.cpp
-            - README-sycl.md
+            - ggml/src/ggml-sycl/**
+            - docs/backend/SYCL.md
+            - examples/sycl/**
 Nvidia GPU:
     - changed-files:
         - any-glob-to-any-file:

From 7fdb6f73e35605c8dbc39e9f19cd9ed84dbc87f2 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Tue, 9 Jul 2024 01:36:38 +0300
Subject: [PATCH 141/326] flake.lock: Update (#8342)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Flake lock file updates:

• Updated input 'flake-parts':
    'github:hercules-ci/flake-parts/2a55567fcf15b1b1c7ed712a2c6fadaec7412ea8?narHash=sha256-iKzJcpdXih14qYVcZ9QC9XuZYnPc6T8YImb6dX166kw%3D' (2024-06-01)
  → 'github:hercules-ci/flake-parts/9227223f6d922fee3c7b190b2cc238a99527bbb7?narHash=sha256-pQMhCCHyQGRzdfAkdJ4cIWiw%2BJNuWsTX7f0ZYSyz0VY%3D' (2024-07-03)
• Updated input 'flake-parts/nixpkgs-lib':
    'https://github.com/NixOS/nixpkgs/archive/eb9ceca17df2ea50a250b6b27f7bf6ab0186f198.tar.gz?narHash=sha256-lIbdfCsf8LMFloheeE6N31%2BBMIeixqyQWbSr2vk79EQ%3D' (2024-06-01)
  → 'https://github.com/NixOS/nixpkgs/archive/5daf0514482af3f97abaefc78a6606365c9108e2.tar.gz?narHash=sha256-Fm2rDDs86sHy0/1jxTOKB1118Q0O3Uc7EC0iXvXKpbI%3D' (2024-07-01)
• Updated input 'nixpkgs':
    'github:NixOS/nixpkgs/b2852eb9365c6de48ffb0dc2c9562591f652242a?narHash=sha256-C8e9S7RzshSdHB7L%2Bv9I51af1gDM5unhJ2xO1ywxNH8%3D' (2024-06-27)
  → 'github:NixOS/nixpkgs/9f4128e00b0ae8ec65918efeba59db998750ead6?narHash=sha256-rwz8NJZV%2B387rnWpTYcXaRNvzUSnnF9aHONoJIYmiUQ%3D' (2024-07-03)

Co-authored-by: github-actions[bot] 
---
 flake.lock | 20 ++++++++++----------
 1 file changed, 10 insertions(+), 10 deletions(-)

diff --git a/flake.lock b/flake.lock
index 973ff4e5675c7..5001fbf912c5c 100644
--- a/flake.lock
+++ b/flake.lock
@@ -5,11 +5,11 @@
         "nixpkgs-lib": "nixpkgs-lib"
       },
       "locked": {
-        "lastModified": 1717285511,
-        "narHash": "sha256-iKzJcpdXih14qYVcZ9QC9XuZYnPc6T8YImb6dX166kw=",
+        "lastModified": 1719994518,
+        "narHash": "sha256-pQMhCCHyQGRzdfAkdJ4cIWiw+JNuWsTX7f0ZYSyz0VY=",
         "owner": "hercules-ci",
         "repo": "flake-parts",
-        "rev": "2a55567fcf15b1b1c7ed712a2c6fadaec7412ea8",
+        "rev": "9227223f6d922fee3c7b190b2cc238a99527bbb7",
         "type": "github"
       },
       "original": {
@@ -20,11 +20,11 @@
     },
     "nixpkgs": {
       "locked": {
-        "lastModified": 1719506693,
-        "narHash": "sha256-C8e9S7RzshSdHB7L+v9I51af1gDM5unhJ2xO1ywxNH8=",
+        "lastModified": 1720031269,
+        "narHash": "sha256-rwz8NJZV+387rnWpTYcXaRNvzUSnnF9aHONoJIYmiUQ=",
         "owner": "NixOS",
         "repo": "nixpkgs",
-        "rev": "b2852eb9365c6de48ffb0dc2c9562591f652242a",
+        "rev": "9f4128e00b0ae8ec65918efeba59db998750ead6",
         "type": "github"
       },
       "original": {
@@ -36,14 +36,14 @@
     },
     "nixpkgs-lib": {
       "locked": {
-        "lastModified": 1717284937,
-        "narHash": "sha256-lIbdfCsf8LMFloheeE6N31+BMIeixqyQWbSr2vk79EQ=",
+        "lastModified": 1719876945,
+        "narHash": "sha256-Fm2rDDs86sHy0/1jxTOKB1118Q0O3Uc7EC0iXvXKpbI=",
         "type": "tarball",
-        "url": "https://github.com/NixOS/nixpkgs/archive/eb9ceca17df2ea50a250b6b27f7bf6ab0186f198.tar.gz"
+        "url": "https://github.com/NixOS/nixpkgs/archive/5daf0514482af3f97abaefc78a6606365c9108e2.tar.gz"
       },
       "original": {
         "type": "tarball",
-        "url": "https://github.com/NixOS/nixpkgs/archive/eb9ceca17df2ea50a250b6b27f7bf6ab0186f198.tar.gz"
+        "url": "https://github.com/NixOS/nixpkgs/archive/5daf0514482af3f97abaefc78a6606365c9108e2.tar.gz"
       }
     },
     "root": {

From 7d0e23d72ef4540d0d4409cb63ae682c17d53926 Mon Sep 17 00:00:00 2001
From: compilade 
Date: Tue, 9 Jul 2024 01:04:49 -0400
Subject: [PATCH 142/326] gguf-py : do not use internal numpy types (#7472)

---
 gguf-py/gguf/lazy.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/gguf-py/gguf/lazy.py b/gguf-py/gguf/lazy.py
index c50124cd912d4..6e266f34f76ac 100644
--- a/gguf-py/gguf/lazy.py
+++ b/gguf-py/gguf/lazy.py
@@ -6,7 +6,6 @@
 from collections import deque
 
 import numpy as np
-from numpy._typing import _Shape
 from numpy.typing import DTypeLike
 
 
@@ -219,7 +218,7 @@ class LazyNumpyTensor(LazyBase):
     _tensor_type = np.ndarray
 
     @classmethod
-    def meta_with_dtype_and_shape(cls, dtype: DTypeLike, shape: _Shape) -> np.ndarray[Any, Any]:
+    def meta_with_dtype_and_shape(cls, dtype: DTypeLike, shape: tuple[int, ...]) -> np.ndarray[Any, Any]:
         # The initial idea was to use np.nan as the fill value,
         # but non-float types like np.int16 can't use that.
         # So zero it is.

From 9beb2dda038e2107a39a95def94a4cf971e048ea Mon Sep 17 00:00:00 2001
From: daghanerdonmez <44506702+daghanerdonmez@users.noreply.github.com>
Date: Tue, 9 Jul 2024 09:16:00 +0300
Subject: [PATCH 143/326] readme : fix typo [no ci] (#8389)

Bakus-Naur --> Backus-Naur
---
 grammars/README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/grammars/README.md b/grammars/README.md
index 886023f770218..01b02abb4de9c 100644
--- a/grammars/README.md
+++ b/grammars/README.md
@@ -4,7 +4,7 @@ GBNF (GGML BNF) is a format for defining [formal grammars](https://en.wikipedia.
 
 ## Background
 
-[Bakus-Naur Form (BNF)](https://en.wikipedia.org/wiki/Backus%E2%80%93Naur_form) is a notation for describing the syntax of formal languages like programming languages, file formats, and protocols. GBNF is an extension of BNF that primarily adds a few modern regex-like features.
+[Backus-Naur Form (BNF)](https://en.wikipedia.org/wiki/Backus%E2%80%93Naur_form) is a notation for describing the syntax of formal languages like programming languages, file formats, and protocols. GBNF is an extension of BNF that primarily adds a few modern regex-like features.
 
 ## Basics
 

From 9925ca4087a34ab973b07bf06c0b770cb586830b Mon Sep 17 00:00:00 2001
From: Borislav Stanimirov 
Date: Tue, 9 Jul 2024 11:38:00 +0300
Subject: [PATCH 144/326] cmake : allow external ggml (#8370)

---
 CMakeLists.txt | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/CMakeLists.txt b/CMakeLists.txt
index 4f6cd68724aa6..cb97d87913955 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -115,7 +115,10 @@ llama_option_depr(WARNING     LLAMA_SYCL_F16            GGML_SYCL_F16)
 # build the library
 #
 
-add_subdirectory(ggml)
+if (NOT TARGET ggml)
+    add_subdirectory(ggml)
+    # ... otherwise assume ggml is added by a parent CMakeLists.txt
+endif()
 add_subdirectory(src)
 
 #

From 5b0b8d8cfb5ddf2118f686ba6c30fab3f71b384b Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Alberto=20Cabrera=20P=C3=A9rez?=
 
Date: Tue, 9 Jul 2024 15:03:15 +0100
Subject: [PATCH 145/326] sycl : Reenabled mmvq path for the SYCL Nvidia
 Backend (#8372)

* SYCL : Reenabled mmvq path for the SYCL Nvidia Backend

* Reduced verbosity of comment
---
 ggml/src/ggml-sycl.cpp | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/ggml/src/ggml-sycl.cpp b/ggml/src/ggml-sycl.cpp
index 21006cd7bebf7..9c419ba896706 100644
--- a/ggml/src/ggml-sycl.cpp
+++ b/ggml/src/ggml-sycl.cpp
@@ -3658,6 +3658,10 @@ static void ggml_sycl_mul_mat(ggml_backend_sycl_context & ctx, const ggml_tensor
     use_mul_mat_q = use_mul_mat_q && (src1->ne[1] <= MMQ_MAX_BATCH_SIZE);
 #endif // SYCL_USE_XMX
 
+    // mmvq path is faster in the CUDA backend.
+    if (ctx.stream()->get_backend() == sycl::backend::ext_oneapi_cuda)
+        use_dequantize_mul_mat_vec = use_dequantize_mul_mat_vec && !use_mul_mat_vec_q;
+
     if (!split && src0->type == GGML_TYPE_F16 && ggml_is_permuted(src0) && ggml_is_permuted(src1) && src1->ne[1] == 1) {
         // KQ single-batch
         ggml_sycl_mul_mat_vec_p021(ctx, src0, src1, dst);

From a03e8dd99d3954e7547137936c5a2a3b348bdb7f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= 
Date: Tue, 9 Jul 2024 17:11:07 +0200
Subject: [PATCH 146/326] make/cmake: LLAMA_NO_CCACHE -> GGML_NO_CCACHE (#8392)

---
 CMakeLists.txt |  4 ----
 Makefile       | 12 +++++++++---
 2 files changed, 9 insertions(+), 7 deletions(-)

diff --git a/CMakeLists.txt b/CMakeLists.txt
index cb97d87913955..befc4433cd0f8 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -50,9 +50,6 @@ endif()
 # option list
 #
 
-# general
-option(LLAMA_CCACHE "llama: use ccache if available" ON)
-
 # debug
 option(LLAMA_ALL_WARNINGS           "llama: enable all compiler warnings"                   ON)
 option(LLAMA_ALL_WARNINGS_3RD_PARTY "llama: enable all compiler warnings in 3rd party libs" OFF)
@@ -77,7 +74,6 @@ option(LLAMA_CURL "llama: use libcurl to download model from an URL" OFF)
 include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info.cmake)
 
 # override ggml options
-set(GGML_CCACHE             ${LLAMA_CCACHE})
 set(GGML_SANITIZE_THREAD    ${LLAMA_SANITIZE_THREAD})
 set(GGML_SANITIZE_ADDRESS   ${LLAMA_SANITIZE_ADDRESS})
 set(GGML_SANITIZE_UNDEFINED ${LLAMA_SANITIZE_UNDEFINED})
diff --git a/Makefile b/Makefile
index bb6e2f968cf0f..be7fb94013beb 100644
--- a/Makefile
+++ b/Makefile
@@ -245,17 +245,22 @@ MK_CFLAGS    = -std=c11   -fPIC
 MK_CXXFLAGS  = -std=c++11 -fPIC
 MK_NVCCFLAGS = -std=c++11
 
-ifndef LLAMA_NO_CCACHE
+ifdef LLAMA_NO_CCACHE
+GGML_NO_CCACHE := 1
+DEPRECATE_WARNING := 1
+endif
+
+ifndef GGML_NO_CCACHE
 CCACHE := $(shell which ccache)
 ifdef CCACHE
 export CCACHE_SLOPPINESS = time_macros
-$(info I ccache found, compilation results will be cached. Disable with LLAMA_NO_CCACHE.)
+$(info I ccache found, compilation results will be cached. Disable with GGML_NO_CCACHE.)
 CC    := $(CCACHE) $(CC)
 CXX   := $(CCACHE) $(CXX)
 else
 $(info I ccache not found. Consider installing it for faster compilation.)
 endif # CCACHE
-endif # LLAMA_NO_CCACHE
+endif # GGML_NO_CCACHE
 
 # clock_gettime came in POSIX.1b (1993)
 # CLOCK_MONOTONIC came in POSIX.1-2001 / SUSv3 as optional
@@ -926,6 +931,7 @@ $(info   - LLAMA_NO_LLAMAFILE)
 $(info   - LLAMA_NO_ACCELERATE)
 $(info   - LLAMA_NO_OPENMP)
 $(info   - LLAMA_NO_METAL)
+$(info   - LLAMA_NO_CCACHE)
 $(info )
 endif
 

From e500d6135ac42c4a23baf6a9a1a934dc023e5c7d Mon Sep 17 00:00:00 2001
From: Clint Herron 
Date: Tue, 9 Jul 2024 11:54:43 -0400
Subject: [PATCH 147/326] Deprecation warning to assist with migration to new
 binary names (#8283)

* Adding a simple program to provide a deprecation warning that can exist to help people notice the binary name change from #7809 and migrate to the new filenames.

* Build legacy replacement binaries only if they already exist. Check for their existence every time so that they are not ignored.
---
 Makefile                                      | 78 ++++++++++++++++++-
 examples/deprecation-warning/README.md        | 51 ++++++++++++
 .../deprecation-warning.cpp                   | 35 +++++++++
 3 files changed, 160 insertions(+), 4 deletions(-)
 create mode 100644 examples/deprecation-warning/README.md
 create mode 100644 examples/deprecation-warning/deprecation-warning.cpp

diff --git a/Makefile b/Makefile
index be7fb94013beb..1041200905371 100644
--- a/Makefile
+++ b/Makefile
@@ -64,10 +64,14 @@ TEST_TARGETS = \
 	tests/test-tokenizer-1-spm
 
 # Legacy build targets that were renamed in #7809, but should still be removed when the project is cleaned
-LEGACY_TARGETS = main quantize quantize-stats perplexity imatrix embedding vdot q8dot train-text-from-scratch convert-llama2c-to-ggml \
+LEGACY_TARGETS_CLEAN = main quantize quantize-stats perplexity imatrix embedding vdot q8dot train-text-from-scratch convert-llama2c-to-ggml \
 	simple batched batched-bench save-load-state server gguf gguf-split eval-callback llama-bench libllava.a llava-cli baby-llama \
 	retrieval speculative infill tokenize benchmark-matmult parallel finetune export-lora lookahead lookup passkey gritlm
 
+# Legacy build targets that were renamed in #7809, but we want to build binaries that for them that output a deprecation warning if people try to use them.
+#  We don't want to clutter things too much, so we only build replacements for the most commonly used binaries.
+LEGACY_TARGETS_BUILD = main quantize perplexity embedding server finetune
+
 # Deprecation aliases
 ifdef LLAMA_CUBLAS
 $(error LLAMA_CUBLAS is removed. Use GGML_CUDA instead.)
@@ -193,7 +197,7 @@ ifdef GGML_RPC
 	BUILD_TARGETS += rpc-server
 endif
 
-default: $(BUILD_TARGETS)
+default: $(BUILD_TARGETS) $(LEGACY_TARGETS_BUILD)
 
 test: $(TEST_TARGETS)
 	@failures=0; \
@@ -228,7 +232,7 @@ test: $(TEST_TARGETS)
 	fi
 	@echo 'All tests passed.'
 
-all: $(BUILD_TARGETS) $(TEST_TARGETS)
+all: $(BUILD_TARGETS) $(TEST_TARGETS) $(LEGACY_TARGETS_BUILD)
 
 ifdef RISCV_CROSS_COMPILE
 CC	:= riscv64-unknown-linux-gnu-gcc
@@ -1098,7 +1102,7 @@ clean:
 	rm -vrf ggml/src/ggml-cuda/template-instances/*.o
 	rm -rvf $(BUILD_TARGETS)
 	rm -rvf $(TEST_TARGETS)
-	rm -rvf $(LEGACY_TARGETS)
+	rm -rvf $(LEGACY_TARGETS_CLEAN)
 	find examples pocs -type f -name "*.o" -delete
 
 #
@@ -1494,3 +1498,69 @@ llama-q8dot: pocs/vdot/q8dot.cpp ggml/src/ggml.o \
 	$(OBJ_GGML)
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
 	$(CXX) $(CXXFLAGS) $(filter-out $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+
+#
+# Deprecated binaries that we want to keep around long enough for people to migrate to the new filenames, then these can be removed.
+#
+# Mark legacy binary targets as .PHONY so that they are always checked.
+.PHONY: main quantize perplexity embedding server finetune
+
+main: examples/deprecation-warning/deprecation-warning.cpp
+ifneq (,$(wildcard main))
+	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
+	$(CXX) $(CXXFLAGS) $(filter-out $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+	@echo "#########"
+	@echo "WARNING: The 'main' binary is deprecated. Please use 'llama-cli' instead."
+	@echo "  Remove the 'main' binary to remove this warning."
+	@echo "#########"
+endif
+
+quantize: examples/deprecation-warning/deprecation-warning.cpp
+ifneq (,$(wildcard quantize))
+	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
+	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+	@echo "#########"
+	@echo "WARNING: The 'quantize' binary is deprecated. Please use 'llama-quantize' instead."
+	@echo "  Remove the 'quantize' binary to remove this warning."
+	@echo "#########"
+endif
+
+perplexity: examples/deprecation-warning/deprecation-warning.cpp
+ifneq (,$(wildcard perplexity))
+	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
+	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+	@echo "#########"
+	@echo "WARNING: The 'perplexity' binary is deprecated. Please use 'llama-perplexity' instead."
+	@echo "  Remove the 'perplexity' binary to remove this warning."
+	@echo "#########"
+endif
+
+embedding: examples/deprecation-warning/deprecation-warning.cpp
+ifneq (,$(wildcard embedding))
+	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
+	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+	@echo "#########"
+	@echo "WARNING: The 'embedding' binary is deprecated. Please use 'llama-embedding' instead."
+	@echo "  Remove the 'embedding' binary to remove this warning."
+	@echo "#########"
+endif
+
+server: examples/deprecation-warning/deprecation-warning.cpp
+ifneq (,$(wildcard server))
+	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
+	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+	@echo "#########"
+	@echo "WARNING: The 'server' binary is deprecated. Please use 'llama-server' instead."
+	@echo "  Remove the 'server' binary to remove this warning."
+	@echo "#########"
+endif
+
+finetune: examples/deprecation-warning/deprecation-warning.cpp
+ifneq (,$(wildcard finetune))
+	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
+	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+	@echo "#########"
+	@echo "WARNING: The 'finetune' binary is deprecated. Please use 'llama-finetune' instead."
+	@echo "  Remove the 'finetune' binary to remove this warning."
+	@echo "#########"
+endif
diff --git a/examples/deprecation-warning/README.md b/examples/deprecation-warning/README.md
new file mode 100644
index 0000000000000..1e20feb4aab87
--- /dev/null
+++ b/examples/deprecation-warning/README.md
@@ -0,0 +1,51 @@
+# Migration notice for binary filenames
+
+> [!IMPORTANT]
+[2024 Jun 12] Binaries have been renamed w/ a `llama-` prefix. `main` is now `llama-cli`, `server` is `llama-server`, etc (https://github.com/ggerganov/llama.cpp/pull/7809)
+
+This migration was important, but it is a breaking change that may not always be immediately obvious to users.
+
+Please update all scripts and workflows to use the new binary names.
+
+| Old Filename | New Filename |
+| ---- | ---- |
+| main | llama-cli |
+| server | llama-server |
+| llama-bench | llama-bench |
+| embedding | llama-embedding |
+| finetune | llama-finetune |
+| quantize | llama-quantize |
+| tokenize | llama-tokenize |
+| export-lora | llama-export-lora |
+| libllava.a | libllava.a |
+| baby-llama | llama-baby-llama |
+| batched | llama-batched |
+| batched-bench | llama-batched-bench |
+| benchmark-matmult | llama-benchmark-matmult |
+| convert-llama2c-to-ggml | llama-convert-llama2c-to-ggml |
+| eval-callback | llama-eval-callback |
+| gbnf-validator | llama-gbnf-validator |
+| gguf | llama-gguf |
+| gguf-split | llama-gguf-split |
+| gritlm | llama-gritlm |
+| imatrix | llama-imatrix |
+| infill | llama-infill |
+| llava-cli | llama-llava-cli |
+| lookahead | llama-lookahead |
+| lookup | llama-lookup |
+| lookup-create | llama-lookup-create |
+| lookup-merge | llama-lookup-merge |
+| lookup-stats | llama-lookup-stats |
+| parallel | llama-parallel |
+| passkey | llama-passkey |
+| perplexity | llama-perplexity |
+| q8dot | llama-q8dot |
+| quantize-stats | llama-quantize-stats |
+| retrieval | llama-retrieval |
+| save-load-state | llama-save-load-state |
+| simple | llama-simple |
+| speculative | llama-speculative |
+| train-text-from-scratch | llama-train-text-from-scratch |
+| vdot | llama-vdot |
+| tests/test-c.o | tests/test-c.o |
+
diff --git a/examples/deprecation-warning/deprecation-warning.cpp b/examples/deprecation-warning/deprecation-warning.cpp
new file mode 100644
index 0000000000000..11b35d2c22500
--- /dev/null
+++ b/examples/deprecation-warning/deprecation-warning.cpp
@@ -0,0 +1,35 @@
+// Warns users that this filename was deprecated, and provides a link for more information.
+
+#include 
+#include 
+#include 
+
+// Main
+int main(int argc, char** argv) {
+    std::string filename = "main";
+    if (argc >= 1) {
+        filename = argv[0];
+    }
+
+    // Get only the program name from the full path
+    auto pos = filename.find_last_of('/');
+    if (pos != std::string::npos) {
+        filename = filename.substr(pos+1);
+    }
+
+    // Append "llama-" to the beginning of filename to get the replacemnt filename
+    auto replacement_filename = "llama-" + filename;
+
+    // The exception is if the filename is "main", then our replacement filename is "llama-cli"
+    if (filename == "main") {
+        replacement_filename = "llama-cli";
+    }
+
+    fprintf(stdout, "\n");
+    fprintf(stdout, "WARNING: The binary '%s' is deprecated.\n", filename.c_str());
+    fprintf(stdout, " Please use '%s' instead.\n", replacement_filename.c_str());
+    fprintf(stdout, " See https://github.com/ggerganov/llama.cpp/tree/master/examples/deprecation-warning/README.md for more information.\n");
+    fprintf(stdout, "\n");
+
+    return EXIT_FAILURE;
+}

From fd560fe680c72fd0a0af2bc8881add20ad919071 Mon Sep 17 00:00:00 2001
From: Andy Salerno 
Date: Tue, 9 Jul 2024 11:58:44 -0700
Subject: [PATCH 148/326] Update README.md to fix broken link to docs (#8399)

Update the "Performance troubleshooting" doc link to be correct - the file was moved into a dir called 'development'
---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index aa70708116571..058919068b872 100644
--- a/README.md
+++ b/README.md
@@ -453,7 +453,7 @@ To learn more how to measure perplexity using llama.cpp, [read this documentatio
 - [How to build](./docs/build.md)
 - [Running on Docker](./docs/docker.md)
 - [Build on Android](./docs/android.md)
-- [Performance troubleshooting](./docs/token_generation_performance_tips.md)
+- [Performance troubleshooting](./docs/development/token_generation_performance_tips.md)
 - [GGML tips & tricks](https://github.com/ggerganov/llama.cpp/wiki/GGML-Tips-&-Tricks)
 
 **Seminal papers and background on the models**

From a59f8fdc85e1119d470d8766e29617962549d993 Mon Sep 17 00:00:00 2001
From: Clint Herron 
Date: Tue, 9 Jul 2024 18:26:40 -0400
Subject: [PATCH 149/326] Server: Enable setting default sampling parameters
 via command-line (#8402)

* Load server sampling parameters from the server context by default.

* Wordsmithing comment
---
 examples/server/server.cpp | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/examples/server/server.cpp b/examples/server/server.cpp
index 47bea15913600..8feff67029da1 100644
--- a/examples/server/server.cpp
+++ b/examples/server/server.cpp
@@ -884,7 +884,8 @@ struct server_context {
 
     bool launch_slot_with_task(server_slot & slot, const server_task & task) {
         slot_params default_params;
-        llama_sampling_params default_sparams;
+        // Sampling parameter defaults are loaded from the global server context (but individual requests can still override them)
+        llama_sampling_params default_sparams = params.sparams;
         auto & data = task.data;
 
         if (data.count("__oaicompat") != 0) {

From 8f0fad42b9589f9b11362c74ea5338c51e4c7e61 Mon Sep 17 00:00:00 2001
From: laik 
Date: Wed, 10 Jul 2024 19:19:10 +0800
Subject: [PATCH 150/326] py : fix extra space in convert_hf_to_gguf.py (#8407)

---
 convert_hf_to_gguf.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py
index 6cea73f08b743..ecb807262b84b 100755
--- a/convert_hf_to_gguf.py
+++ b/convert_hf_to_gguf.py
@@ -1356,7 +1356,7 @@ class LlamaModel(Model):
 
     def set_vocab(self):
         try:
-            self. _set_vocab_sentencepiece()
+            self._set_vocab_sentencepiece()
         except FileNotFoundError:
             try:
                 self._set_vocab_llama_hf()

From e4dd31ff892627665d3c53c5d1a03c0d282d9d45 Mon Sep 17 00:00:00 2001
From: RunningLeon 
Date: Wed, 10 Jul 2024 19:26:40 +0800
Subject: [PATCH 151/326] py : fix converter for internlm2 (#8321)

* update internlm2

* remove unused file

* fix lint
---
 convert_hf_to_gguf.py | 68 +++++++++++++++++++++++++++++++++----------
 1 file changed, 52 insertions(+), 16 deletions(-)

diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py
index ecb807262b84b..ebb5ca376133b 100755
--- a/convert_hf_to_gguf.py
+++ b/convert_hf_to_gguf.py
@@ -2144,6 +2144,9 @@ def set_vocab(self):
                 toktype = SentencePieceTokenTypes.UNUSED
             elif tokenizer.IsByte(token_id):
                 toktype = SentencePieceTokenTypes.BYTE
+            # take care of ununsed raw token
+            if piece.startswith('[UNUSED'):
+                toktype = SentencePieceTokenTypes.UNKNOWN
 
             tokens.append(text)
             scores.append(score)
@@ -2159,6 +2162,47 @@ def set_vocab(self):
                     scores.append(-1000.0)
                     toktypes.append(SentencePieceTokenTypes.USER_DEFINED)
 
+        chat_eos_token = '<|im_end|>'
+        chat_eos_token_id = None
+
+        tokenizer_config_file = self.dir_model / 'tokenizer_config.json'
+        if tokenizer_config_file.is_file():
+            with open(tokenizer_config_file, "r", encoding="utf-8") as f:
+                tokenizer_config_json = json.load(f)
+                added_tokens_decoder = tokenizer_config_json.get("added_tokens_decoder", {})
+                for token_id, foken_data in added_tokens_decoder.items():
+                    token_id = int(token_id)
+                    token = foken_data["content"]
+                    if token == chat_eos_token:
+                        chat_eos_token_id = token_id
+                    token = token.encode("utf-8")
+                    if toktypes[token_id] != SentencePieceTokenTypes.UNKNOWN:
+                        assert(tokens[token_id] == token)
+                    tokens[token_id] = token
+                    scores[token_id] = -1000.0
+                    toktypes[token_id] = SentencePieceTokenTypes.USER_DEFINED
+                    if foken_data.get("special"):
+                        toktypes[token_id] = SentencePieceTokenTypes.CONTROL
+
+        tokenizer_file = self.dir_model / 'tokenizer.json'
+        if tokenizer_file.is_file():
+            with open(tokenizer_file, "r", encoding="utf-8") as f:
+                tokenizer_json = json.load(f)
+                added_tokens = tokenizer_json.get("added_tokens", [])
+                for foken_data in added_tokens:
+                    token_id = int(foken_data["id"])
+                    token = foken_data["content"]
+                    if token == chat_eos_token:
+                        chat_eos_token_id = token_id
+                    token = token.encode("utf-8")
+                    if toktypes[token_id] != SentencePieceTokenTypes.UNKNOWN:
+                        assert(tokens[token_id] == token)
+                    tokens[token_id] = token
+                    scores[token_id] = -1000.0
+                    toktypes[token_id] = SentencePieceTokenTypes.USER_DEFINED
+                    if foken_data.get("special"):
+                        toktypes[token_id] = SentencePieceTokenTypes.CONTROL
+
         self.gguf_writer.add_tokenizer_model("llama")
         self.gguf_writer.add_tokenizer_pre("default")
         self.gguf_writer.add_token_list(tokens)
@@ -2168,28 +2212,16 @@ def set_vocab(self):
 
         special_vocab = gguf.SpecialVocab(self.dir_model, n_vocab=len(tokens))
         old_eos = special_vocab.special_token_ids["eos"]
-        if "chat" in os.path.basename(self.dir_model.absolute()):
+        if chat_eos_token_id is not None:
             # For the chat model, we replace the eos with '<|im_end|>'.
             # TODO: this is a hack, should be fixed
             #       https://github.com/ggerganov/llama.cpp/pull/6745#issuecomment-2067687048
-            special_vocab.special_token_ids["eos"] = self._try_get_sft_eos(tokenizer)
-            logger.warning(f"Replace eos:{old_eos} with a special token:{special_vocab.special_token_ids['eos']} \
-in chat mode so that the conversation can end normally.")
+            special_vocab.special_token_ids["eos"] = chat_eos_token_id
+            logger.warning(f"Replace eos:{old_eos} with a special token:{chat_eos_token_id}"
+                           " in chat mode so that the conversation can end normally.")
 
         special_vocab.add_to_gguf(self.gguf_writer)
 
-    def _try_get_sft_eos(self, tokenizer):
-        unused_145_list = tokenizer.Encode('[UNUSED_TOKEN_145]')
-        im_end_list = tokenizer.Encode('<|im_end|>')
-        eos_token = None
-        assert (len(unused_145_list) == 1) ^ (len(im_end_list) == 1)
-        if len(unused_145_list) == 1:
-            eos_token = unused_145_list[0]
-        if len(im_end_list) == 1:
-            eos_token = im_end_list[0]
-        assert eos_token
-        return eos_token
-
     def _hf_permute_qk(self, weights, n_head: int, n_head_kv: int):
         if n_head_kv is not None and n_head != n_head_kv:
             n_head = n_head_kv
@@ -2208,6 +2240,10 @@ def set_gguf_parameters(self):
         self.gguf_writer.add_layer_norm_rms_eps(self.hparams["rms_norm_eps"])
         self.gguf_writer.add_head_count_kv(self.hparams["num_key_value_heads"])
         self.gguf_writer.add_file_type(self.ftype)
+        if self.hparams.get("rope_scaling") is not None and "factor" in self.hparams["rope_scaling"]:
+            if self.hparams["rope_scaling"].get("type") == "linear":
+                self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
+                self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"])
 
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         num_heads = self.hparams["num_attention_heads"]

From a8be1e6f5995bec3b1d8474d48ce3a139553a8e1 Mon Sep 17 00:00:00 2001
From: fairydreaming <166155368+fairydreaming@users.noreply.github.com>
Date: Wed, 10 Jul 2024 13:38:58 +0200
Subject: [PATCH 152/326] llama : add assert about missing llama_encode() call
 (#8400)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Co-authored-by: Stanisław Szymczyk 
---
 src/llama.cpp | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/src/llama.cpp b/src/llama.cpp
index 2b9ace2858457..80cc1da2660e5 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -13200,6 +13200,8 @@ struct llm_build_context {
                     LLM_NORM_RMS, cb, -1);
             cb(cur, "result_norm", -1);
         } else {
+            GGML_ASSERT(n_outputs_enc > 0 && "call llama_encode() first");
+
             struct ggml_tensor * embd_enc       = llm_build_inp_embd_enc();
             struct ggml_tensor * pos_bucket_dec = llm_build_pos_bucket(true);
 

From 7a80710d93ee0f4e0d335d65984ae747e62c0337 Mon Sep 17 00:00:00 2001
From: Borislav Stanimirov 
Date: Wed, 10 Jul 2024 14:40:53 +0300
Subject: [PATCH 153/326] msvc : silence codecvt c++17 deprecation warnings
 (#8395)

---
 common/common.cpp | 4 ++++
 src/unicode.cpp   | 4 ++++
 2 files changed, 8 insertions(+)

diff --git a/common/common.cpp b/common/common.cpp
index fc0f3b350ec6e..1e5fc30dd458a 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -1,3 +1,7 @@
+#if defined(_MSC_VER)
+#define _SILENCE_CXX17_CODECVT_HEADER_DEPRECATION_WARNING
+#endif
+
 #include "common.h"
 // Change JSON_ASSERT from assert() to GGML_ASSERT:
 #define JSON_ASSERT GGML_ASSERT
diff --git a/src/unicode.cpp b/src/unicode.cpp
index 51daa15afa669..e05fb9d1775dd 100644
--- a/src/unicode.cpp
+++ b/src/unicode.cpp
@@ -1,3 +1,7 @@
+#if defined(_MSC_VER)
+#define _SILENCE_CXX17_CODECVT_HEADER_DEPRECATION_WARNING
+#endif
+
 #include "unicode.h"
 #include "unicode-data.h"
 

From cc61948b1f97165b46990f4c2d9699bf9bb64443 Mon Sep 17 00:00:00 2001
From: Borislav Stanimirov 
Date: Wed, 10 Jul 2024 14:45:44 +0300
Subject: [PATCH 154/326] llama : C++20 compatibility for u8 strings (#8408)

---
 src/llama.cpp | 12 +++++++++---
 1 file changed, 9 insertions(+), 3 deletions(-)

diff --git a/src/llama.cpp b/src/llama.cpp
index 80cc1da2660e5..98a242081ca03 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -57,6 +57,12 @@
     #include 
 #endif
 
+#if __cplusplus >= 202000L
+    #define LU8(x) (const char*)(u8##x)
+#else
+    #define LU8(x) u8##x
+#endif
+
 #include 
 #include 
 #include 
@@ -21511,12 +21517,12 @@ static int32_t llama_chat_apply_template_internal(
         if (add_ass) {
             ss << "<|assistant|>";
         }
-    } else if (tmpl == "minicpm" || tmpl_contains(u8"<用户>")) {
+    } else if (tmpl == "minicpm" || tmpl_contains(LU8("<用户>"))) {
         // MiniCPM-3B-OpenHermes-2.5-v2-GGUF
         for (auto message : chat) {
             std::string role(message->role);
             if (role == "user") {
-                ss << u8"<用户>";
+                ss << LU8("<用户>");
                 ss << trim(message->content);
                 ss << "";
             } else {
@@ -21532,7 +21538,7 @@ static int32_t llama_chat_apply_template_internal(
             } else if (role == "user") {
                 ss << "User: " << message->content << "\n\n";
             } else if (role == "assistant") {
-                ss << "Assistant: " << message->content << u8"<｜end▁of▁sentence｜>";
+                ss << "Assistant: " << message->content << LU8("<｜end▁of▁sentence｜>");
             }
         }
         if (add_ass) {

From 83321c6958acf20747d288031174cc1bf8816e33 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?M=2E=20Yusuf=20Sar=C4=B1g=C3=B6z?= 
Date: Wed, 10 Jul 2024 15:12:35 +0300
Subject: [PATCH 155/326] gguf-py rel pipeline (#8410)

* Upd gguf-py/readme

* Bump patch version for release
---
 gguf-py/README.md      | 1 -
 gguf-py/pyproject.toml | 2 +-
 2 files changed, 1 insertion(+), 2 deletions(-)

diff --git a/gguf-py/README.md b/gguf-py/README.md
index bc46d6e1dd708..9dd888f3180d1 100644
--- a/gguf-py/README.md
+++ b/gguf-py/README.md
@@ -79,5 +79,4 @@ python -m twine upload dist/*
 ```
 
 ## TODO
-- [ ] Add tests
 - [ ] Include conversion scripts as command line entry points in this package.
diff --git a/gguf-py/pyproject.toml b/gguf-py/pyproject.toml
index 36e63ee3b7cd6..62129126bdddc 100644
--- a/gguf-py/pyproject.toml
+++ b/gguf-py/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "gguf"
-version = "0.9.0"
+version = "0.9.1"
 description = "Read and write ML models in GGUF for GGML"
 authors = ["GGML "]
 packages = [

From 0f1a39f3439825acf7e3a1663566d410be152170 Mon Sep 17 00:00:00 2001
From: Dibakar Gope 
Date: Wed, 10 Jul 2024 07:14:51 -0500
Subject: [PATCH 156/326] ggml : add AArch64 optimized GEMV and GEMM Q4 kernels
 (#5780)

* Arm AArch64: optimized GEMV and GEMM kernels for q4_0_q8_0, and q8_0_q8_0 quantization

* Arm AArch64: add optimized GEMV and GEMM asm kernels for q4_0_q8_0 quantization and refactor code to address llama.cpp pr#5780 suggestions

* Arm AArch64: add optimized GEMV and GEMM asm kernels for q4_0_q8_0 quantization and refactor code to address llama.cpp pr#5780 suggestions

* Arm AArch64: add optimized GEMV and GEMM asm kernels for q4_0_q8_0 quantization and refactor code to address llama.cpp pr#5780 suggestions

* Arm AArch64: add optimized GEMV and GEMM asm kernels for q4_0_q8_0 quantization and refactor code to address llama.cpp pr#5780 suggestions

* Arm AArch64: add copyright claim only to ggml-aarch64.cpp and ggml-aarch64.h files

* Arm AArch64: minor code refactoring for rebase

* Arm AArch64: minor code refactoring for resolving a build issue with cmake

* Arm AArch64: minor code refactoring to split the Q4_0_AARC64 type into three separate types: Q4_0_4_4, Q4_0_4_8, and Q4_0_8_8

* Arm AArch64: minor code change for resolving a build issue with server-windows

* retrigger checks

* Arm AArch64: minor code changes for rebase

* Arm AArch64: minor changes to skip the pr#7433 vec_dot code for arm cpus with SVE VL not equal to 256 bits

* Arm AArch64: remove stale LLAMA_QKK_64 from CMakeLists.txt and delete build.zig

* Arm AArch64: add reference scalar gemm and gemv, and avoid dynamic memory allocations during quantization for Q4_0_4_4, Q4_0_4_8, and Q4_0_8_8

* Arm AArch64: add multithreaded quantization support for the new types: Q4_0_4_4, Q4_0_4_8, and Q4_0_8_8

* Arm AArch64: minor code refactoring

* Arm AArch64: simplify logic for calling gemm and gemv functions in ggml_compute_forward_mul_mat

* Arm AArch64: minimize changes in ggml_compute_forward_mul_mat

* Arm AArch64: minor code refactoring, and add reference scalar code to quantize routines for new quant types

* Arm AArch64: minor code refactoring

* Arm AArch64: minor code refactoring

* Arm AArch64: minor code refactoring

* rebase on the latest master commit 3fd62a6 and adapt to the new directory structure

* Arm AArch64: remove a redundant comment

* Arm AArch64: add pragma in ggml-aarch64.c to turn -Woverlength-strings warning off

* Arm AArch64: use __aarch64__ check to guard 64-bit neon kernels

* Arm AArch64: update docs/build.md README to include compile time flags for buiilding the Q4_0_4_4 quant type
---
 Makefile                       |   10 +-
 Package.swift                  |    1 +
 docs/build.md                  |    2 +
 examples/quantize/quantize.cpp |    3 +
 ggml/include/ggml.h            |   17 +
 ggml/src/CMakeLists.txt        |    1 +
 ggml/src/ggml-aarch64.c        | 2187 ++++++++++++++++++++++++++++++++
 ggml/src/ggml-aarch64.h        |   39 +
 ggml/src/ggml-common.h         |   24 +
 ggml/src/ggml-impl.h           |    4 +
 ggml/src/ggml-quants.c         |  122 +-
 ggml/src/ggml.c                |  150 ++-
 include/llama.h                |    3 +
 src/llama.cpp                  |   24 +-
 14 files changed, 2534 insertions(+), 53 deletions(-)
 create mode 100644 ggml/src/ggml-aarch64.c
 create mode 100644 ggml/src/ggml-aarch64.h

diff --git a/Makefile b/Makefile
index 1041200905371..b70ebaed54638 100644
--- a/Makefile
+++ b/Makefile
@@ -835,7 +835,8 @@ OBJ_GGML += \
 	ggml/src/ggml.o \
 	ggml/src/ggml-alloc.o \
 	ggml/src/ggml-backend.o \
-	ggml/src/ggml-quants.o
+	ggml/src/ggml-quants.o \
+	ggml/src/ggml-aarch64.o
 
 OBJ_LLAMA = \
 	src/llama.o \
@@ -969,6 +970,13 @@ ggml/src/ggml-quants.o: \
 	ggml/src/ggml-common.h
 	$(CC) $(CFLAGS)    -c $< -o $@
 
+ggml/src/ggml-aarch64.o: \
+	ggml/src/ggml-aarch64.c \
+	ggml/include/ggml.h \
+	ggml/src/ggml-aarch64.h \
+	ggml/src/ggml-common.h
+	$(CC) $(CFLAGS)    -c $< -o $@
+
 ggml/src/ggml-blas.o: \
 	ggml/src/ggml-blas.cpp \
 	ggml/include/ggml-blas.h
diff --git a/Package.swift b/Package.swift
index 77fed86df3105..d40a48385f8c7 100644
--- a/Package.swift
+++ b/Package.swift
@@ -10,6 +10,7 @@ var sources = [
     "ggml/src/ggml-alloc.c",
     "ggml/src/ggml-backend.c",
     "ggml/src/ggml-quants.c",
+    "ggml/src/ggml-aarch64.c",
 ]
 
 var resources: [Resource] = []
diff --git a/docs/build.md b/docs/build.md
index bf41bfdf9c2f8..d70f72f4c7b82 100644
--- a/docs/build.md
+++ b/docs/build.md
@@ -28,6 +28,7 @@ In order to build llama.cpp you have four different options.
         ```
 
   - Notes:
+    - For `Q4_0_4_4` quantization type build, add the `GGML_NO_LLAMAFILE=1` flag. For example, use `make GGML_NO_LLAMAFILE=1`.
     - For faster compilation, add the `-j` argument to run multiple jobs in parallel. For example, `make -j 8` will run 8 jobs in parallel.
     - For faster repeated compilation, install [ccache](https://ccache.dev/).
     - For debug builds, run `make LLAMA_DEBUG=1`
@@ -41,6 +42,7 @@ In order to build llama.cpp you have four different options.
 
   **Notes**:
 
+    - For `Q4_0_4_4` quantization type build, add the `-DGGML_LLAMAFILE=OFF` cmake option. For example, use `cmake -B build -DGGML_LLAMAFILE=OFF`.
     - For faster compilation, add the `-j` argument to run multiple jobs in parallel. For example, `cmake --build build --config Release -j 8` will run 8 jobs in parallel.
     - For faster repeated compilation, install [ccache](https://ccache.dev/).
     - For debug builds, there are two cases:
diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp
index 76e2052d55d79..1578c4afb5dfa 100644
--- a/examples/quantize/quantize.cpp
+++ b/examples/quantize/quantize.cpp
@@ -46,6 +46,9 @@ static const std::vector QUANT_OPTIONS = {
     { "Q5_K_M", LLAMA_FTYPE_MOSTLY_Q5_K_M, " 5.33G, +0.0569 ppl @ Llama-3-8B",  },
     { "Q6_K",   LLAMA_FTYPE_MOSTLY_Q6_K,   " 6.14G, +0.0217 ppl @ Llama-3-8B",  },
     { "Q8_0",   LLAMA_FTYPE_MOSTLY_Q8_0,   " 7.96G, +0.0026 ppl @ Llama-3-8B",  },
+    { "Q4_0_4_4", LLAMA_FTYPE_MOSTLY_Q4_0_4_4, " 4.34G, +0.4685 ppl @ Llama-3-8B", },
+    { "Q4_0_4_8", LLAMA_FTYPE_MOSTLY_Q4_0_4_8, " 4.34G, +0.4685 ppl @ Llama-3-8B", },
+    { "Q4_0_8_8", LLAMA_FTYPE_MOSTLY_Q4_0_8_8, " 4.34G, +0.4685 ppl @ Llama-3-8B", },
     { "F16",    LLAMA_FTYPE_MOSTLY_F16,    "14.00G, +0.0020 ppl @ Mistral-7B",  },
     { "BF16",   LLAMA_FTYPE_MOSTLY_BF16,   "14.00G, -0.0050 ppl @ Mistral-7B",  },
     { "F32",    LLAMA_FTYPE_ALL_F32,       "26.00G              @ 7B",          },
diff --git a/ggml/include/ggml.h b/ggml/include/ggml.h
index d895c9acdb596..1e367753738d9 100644
--- a/ggml/include/ggml.h
+++ b/ggml/include/ggml.h
@@ -383,6 +383,9 @@ extern "C" {
         GGML_TYPE_F64     = 28,
         GGML_TYPE_IQ1_M   = 29,
         GGML_TYPE_BF16    = 30,
+        GGML_TYPE_Q4_0_4_4 = 31,
+        GGML_TYPE_Q4_0_4_8 = 32,
+        GGML_TYPE_Q4_0_8_8 = 33,
         GGML_TYPE_COUNT,
     };
 
@@ -424,6 +427,9 @@ extern "C" {
         GGML_FTYPE_MOSTLY_IQ4_XS  = 22, // except 1d tensors
         GGML_FTYPE_MOSTLY_IQ1_M   = 23, // except 1d tensors
         GGML_FTYPE_MOSTLY_BF16    = 24, // except 1d tensors
+        GGML_FTYPE_MOSTLY_Q4_0_4_4 = 25, // except 1d tensors
+        GGML_FTYPE_MOSTLY_Q4_0_4_8 = 26, // except 1d tensors
+        GGML_FTYPE_MOSTLY_Q4_0_8_8 = 27, // except 1d tensors
     };
 
     // available tensor operations:
@@ -2406,6 +2412,12 @@ extern "C" {
     typedef void (*ggml_from_float_t)(const float * GGML_RESTRICT x, void  * GGML_RESTRICT y, int64_t k);
     typedef void (*ggml_vec_dot_t)   (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT x, size_t bx,
                                       const void * GGML_RESTRICT y, size_t by, int nrc);
+    typedef void (*ggml_from_float_to_mat_t)(const float * GGML_RESTRICT x, void  * GGML_RESTRICT y, int64_t nr,
+                                             int64_t k, int64_t bx);
+    typedef void (*ggml_gemv_t)      (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT x,
+                                      const void * GGML_RESTRICT y, int nr, int nc);
+    typedef void (*ggml_gemm_t)      (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT x,
+                                      const void * GGML_RESTRICT y, int nr, int nc);
 
     typedef struct {
         const char      * type_name;
@@ -2418,6 +2430,11 @@ extern "C" {
         ggml_vec_dot_t    vec_dot;
         enum ggml_type    vec_dot_type;
         int64_t           nrows; // number of rows to process simultaneously;
+        int64_t           ncols; // number of columns to process simultaneously;
+        int64_t           interleave_blcksize; // interleave elements in blocks of interleave_blcksize;
+        ggml_from_float_to_mat_t from_float_to_mat;
+        ggml_gemv_t       gemv;
+        ggml_gemm_t       gemm;
     } ggml_type_traits_t;
 
     GGML_API ggml_type_traits_t ggml_internal_get_type_traits(enum ggml_type type);
diff --git a/ggml/src/CMakeLists.txt b/ggml/src/CMakeLists.txt
index c6694df678fff..aae5b8e9fe35c 100644
--- a/ggml/src/CMakeLists.txt
+++ b/ggml/src/CMakeLists.txt
@@ -1153,6 +1153,7 @@ add_library(ggml
             ${GGML_SOURCES_ROCM}      ${GGML_HEADERS_ROCM}
             ${GGML_SOURCES_BLAS}      ${GGML_HEADERS_BLAS}
             ${GGML_SOURCES_LLAMAFILE} ${GGML_HEADERS_LLAMAFILE}
+            ggml-aarch64.c            ggml-aarch64.h
             )
 
 if (EMSCRIPTEN)
diff --git a/ggml/src/ggml-aarch64.c b/ggml/src/ggml-aarch64.c
new file mode 100644
index 0000000000000..008718634fe0d
--- /dev/null
+++ b/ggml/src/ggml-aarch64.c
@@ -0,0 +1,2187 @@
+// SPDX-FileCopyrightText: Copyright 2024 Arm Ltd.
+#define GGML_COMMON_IMPL_C
+#include "ggml-common.h"
+
+#include "ggml-quants.h"
+#include "ggml-impl.h"
+
+#include 
+#include 
+#include 
+#include 
+#include  // for qsort
+#include   // for GGML_ASSERT
+
+#include "ggml-aarch64.h"
+
+#pragma GCC diagnostic ignored "-Woverlength-strings"
+
+#define UNUSED GGML_UNUSED
+
+// Functions to create the interleaved data layout formats
+
+// interleave 4 block_q4_0s in blocks of interleave_blcksize
+// returns an interleaved block_q4_0x4
+// in the interleaved block_q4_0x4, place deltas for 4 block_q4_0 blocks
+// first, then interleave quants from 4 block_q4_0s in blocks of interleave_blcksize
+//
+// - in                  : an array of block_q4_0 pointers
+// - interleave_blcksize : the block_q4_0 quants bytes are interleaved in blocks of
+//                         interleave_blcksize bytes
+// - xor_mask            : the mask to convert the nibbles in block_q4_0 quants bytes
+//                         from bias offset form to pure sign form (this saves subtract
+//                         operations durin unpacking)
+//
+static block_q4_0x4 make_block_q4_0x4(block_q4_0 * in, unsigned int interleave_blcksize, unsigned int xor_mask) {
+    block_q4_0x4 out;
+
+    for (int i = 0; i < 4; i++) {
+        out.d[i] = in[i].d;
+    }
+
+    for (int i = 0; i < QK4_0 * 2; i++) {
+        int src_offset = (i / (4 * interleave_blcksize)) * interleave_blcksize;
+        int src_id = (i % (4 * interleave_blcksize)) / interleave_blcksize;
+        src_offset += (i % interleave_blcksize);
+
+        out.qs[i] = in[src_id].qs[src_offset] ^ xor_mask;
+    }
+
+    return out;
+}
+
+// interleave 8 block_q4_0s in blocks of interleave_blcksize
+// returns an interleaved block_q4_0x8
+// in the interleaved block_q4_0x8, place deltas for 8 block_q4_0 blocks
+// first, then interleave quants from 8 block_q4_0s in blocks of interleave_blcksize
+static block_q4_0x8 make_block_q4_0x8(block_q4_0 * in, unsigned int interleave_blcksize, unsigned int xor_mask) {
+    block_q4_0x8 out;
+
+    for (int i = 0; i < 8; i++) {
+        out.d[i] = in[i].d;
+    }
+
+    for (int i = 0; i < QK4_0 * 4; i++) {
+        int src_offset = (i / (8 * interleave_blcksize)) * interleave_blcksize;
+        int src_id = (i % (8 * interleave_blcksize)) / interleave_blcksize;
+        src_offset += (i % interleave_blcksize);
+
+        out.qs[i] = in[src_id].qs[src_offset] ^ xor_mask;
+    }
+
+    return out;
+}
+
+void quantize_q8_0_4x4(const float * restrict x, void * restrict vy, int64_t k) {
+    assert(QK8_0 == 32);
+    assert(k % QK8_0 == 0);
+    const int nb = k / QK8_0;
+
+    block_q8_0x4 * restrict y = (block_q8_0x4 *) vy;
+
+#if defined(__ARM_NEON)
+    float32x4_t srcv[4][8];
+    float id[4];
+
+    for (int i = 0; i < nb; i++) {
+        float32x4_t asrcv[8];
+        float32x4_t amaxv[8];
+
+        for (int row_iter = 0; row_iter < 4; row_iter++) {
+            for (int j = 0; j < 8; j++) srcv[row_iter][j] = vld1q_f32(x + row_iter * k + i * 32 + 4 * j);
+            for (int j = 0; j < 8; j++) asrcv[j] = vabsq_f32(srcv[row_iter][j]);
+
+            for (int j = 0; j < 4; j++) amaxv[2 * j] = vmaxq_f32(asrcv[2 * j], asrcv[2 * j + 1]);
+            for (int j = 0; j < 2; j++) amaxv[4 * j] = vmaxq_f32(amaxv[4 * j], amaxv[4 * j + 2]);
+            for (int j = 0; j < 1; j++) amaxv[8 * j] = vmaxq_f32(amaxv[8 * j], amaxv[8 * j + 4]);
+
+            const float amax = vmaxvq_f32(amaxv[0]);
+
+            const float d = amax / ((1 << 7) - 1);
+            id[row_iter] = d ? 1.0f / d : 0.0f;
+
+            y[i].d[row_iter] = GGML_FP32_TO_FP16(d);
+        }
+
+        for (int j = 0; j < 8; j++) {
+            float32x4_t v = vmulq_n_f32(srcv[0][j], id[0]);
+            int32x4_t vi = vcvtnq_s32_f32(v);
+            y[i].qs[16 * j + 0] = vgetq_lane_s32(vi, 0);
+            y[i].qs[16 * j + 1] = vgetq_lane_s32(vi, 1);
+            y[i].qs[16 * j + 2] = vgetq_lane_s32(vi, 2);
+            y[i].qs[16 * j + 3] = vgetq_lane_s32(vi, 3);
+
+            v = vmulq_n_f32(srcv[1][j], id[1]);
+            vi = vcvtnq_s32_f32(v);
+            y[i].qs[16 * j + 4] = vgetq_lane_s32(vi, 0);
+            y[i].qs[16 * j + 5] = vgetq_lane_s32(vi, 1);
+            y[i].qs[16 * j + 6] = vgetq_lane_s32(vi, 2);
+            y[i].qs[16 * j + 7] = vgetq_lane_s32(vi, 3);
+
+            v = vmulq_n_f32(srcv[2][j], id[2]);
+            vi = vcvtnq_s32_f32(v);
+            y[i].qs[16 * j + 8] = vgetq_lane_s32(vi, 0);
+            y[i].qs[16 * j + 9] = vgetq_lane_s32(vi, 1);
+            y[i].qs[16 * j + 10] = vgetq_lane_s32(vi, 2);
+            y[i].qs[16 * j + 11] = vgetq_lane_s32(vi, 3);
+
+            v = vmulq_n_f32(srcv[3][j], id[3]);
+            vi = vcvtnq_s32_f32(v);
+            y[i].qs[16 * j + 12] = vgetq_lane_s32(vi, 0);
+            y[i].qs[16 * j + 13] = vgetq_lane_s32(vi, 1);
+            y[i].qs[16 * j + 14] = vgetq_lane_s32(vi, 2);
+            y[i].qs[16 * j + 15] = vgetq_lane_s32(vi, 3);
+        }
+    }
+#else
+    // scalar
+    const int interleave_blcksize = 4;
+    float srcv[4][QK8_0];
+    float id[4];
+
+    for (int i = 0; i < nb; i++) {
+        for (int row_iter = 0; row_iter < 4; row_iter++) {
+            float amax = 0.0f; // absolute max
+
+            for (int j = 0; j < QK8_0; j++) {
+                srcv[row_iter][j] = x[row_iter * k + i * QK8_0 + j];
+                amax = MAX(amax, fabsf(srcv[row_iter][j]));
+            }
+
+            const float d = amax / ((1 << 7) - 1);
+            id[row_iter] = d ? 1.0f / d : 0.0f;
+
+            y[i].d[row_iter] = GGML_FP32_TO_FP16(d);
+        }
+
+        for (int j = 0; j < QK8_0 * 4; j++) {
+            int src_offset = (j / (4 * interleave_blcksize)) * interleave_blcksize;
+            int src_id = (j % (4 * interleave_blcksize)) / interleave_blcksize;
+            src_offset += (j % interleave_blcksize);
+
+            float x0 = srcv[src_id][src_offset] * id[src_id];
+            y[i].qs[j] = roundf(x0);;
+        }
+    }
+#endif
+}
+
+void quantize_q8_0_4x8(const float * restrict x, void * restrict vy, int64_t k) {
+    assert(QK8_0 == 32);
+    assert(k % QK8_0 == 0);
+    const int nb = k / QK8_0;
+
+    block_q8_0x4 * restrict y = (block_q8_0x4 *) vy;
+
+#if defined(__ARM_NEON)
+    float32x4_t srcv[4][8];
+    float id[4];
+
+    for (int i = 0; i < nb; i++) {
+        float32x4_t asrcv[8];
+        float32x4_t amaxv[8];
+
+        for (int row_iter = 0; row_iter < 4; row_iter++) {
+            for (int j = 0; j < 8; j++) srcv[row_iter][j] = vld1q_f32(x + row_iter * k + i * 32 + 4 * j);
+            for (int j = 0; j < 8; j++) asrcv[j] = vabsq_f32(srcv[row_iter][j]);
+
+            for (int j = 0; j < 4; j++) amaxv[2 * j] = vmaxq_f32(asrcv[2 * j], asrcv[2 * j + 1]);
+            for (int j = 0; j < 2; j++) amaxv[4 * j] = vmaxq_f32(amaxv[4 * j], amaxv[4 * j + 2]);
+            for (int j = 0; j < 1; j++) amaxv[8 * j] = vmaxq_f32(amaxv[8 * j], amaxv[8 * j + 4]);
+
+            const float amax = vmaxvq_f32(amaxv[0]);
+
+            const float d = amax / ((1 << 7) - 1);
+            id[row_iter] = d ? 1.0f / d : 0.0f;
+
+            y[i].d[row_iter] = GGML_FP32_TO_FP16(d);
+        }
+
+        for (int j = 0; j < 4; j++) {
+            float32x4_t v = vmulq_n_f32(srcv[0][2 * j], id[0]);
+            int32x4_t vi = vcvtnq_s32_f32(v);
+            y[i].qs[32 * j + 0] = vgetq_lane_s32(vi, 0);
+            y[i].qs[32 * j + 1] = vgetq_lane_s32(vi, 1);
+            y[i].qs[32 * j + 2] = vgetq_lane_s32(vi, 2);
+            y[i].qs[32 * j + 3] = vgetq_lane_s32(vi, 3);
+            v = vmulq_n_f32(srcv[0][2 * j + 1], id[0]);
+            vi = vcvtnq_s32_f32(v);
+            y[i].qs[32 * j + 4] = vgetq_lane_s32(vi, 0);
+            y[i].qs[32 * j + 5] = vgetq_lane_s32(vi, 1);
+            y[i].qs[32 * j + 6] = vgetq_lane_s32(vi, 2);
+            y[i].qs[32 * j + 7] = vgetq_lane_s32(vi, 3);
+
+            v = vmulq_n_f32(srcv[1][2 * j], id[1]);
+            vi = vcvtnq_s32_f32(v);
+            y[i].qs[32 * j + 8] = vgetq_lane_s32(vi, 0);
+            y[i].qs[32 * j + 9] = vgetq_lane_s32(vi, 1);
+            y[i].qs[32 * j + 10] = vgetq_lane_s32(vi, 2);
+            y[i].qs[32 * j + 11] = vgetq_lane_s32(vi, 3);
+            v = vmulq_n_f32(srcv[1][2 * j + 1], id[1]);
+            vi = vcvtnq_s32_f32(v);
+            y[i].qs[32 * j + 12] = vgetq_lane_s32(vi, 0);
+            y[i].qs[32 * j + 13] = vgetq_lane_s32(vi, 1);
+            y[i].qs[32 * j + 14] = vgetq_lane_s32(vi, 2);
+            y[i].qs[32 * j + 15] = vgetq_lane_s32(vi, 3);
+
+            v = vmulq_n_f32(srcv[2][2 * j], id[2]);
+            vi = vcvtnq_s32_f32(v);
+            y[i].qs[32 * j + 16] = vgetq_lane_s32(vi, 0);
+            y[i].qs[32 * j + 17] = vgetq_lane_s32(vi, 1);
+            y[i].qs[32 * j + 18] = vgetq_lane_s32(vi, 2);
+            y[i].qs[32 * j + 19] = vgetq_lane_s32(vi, 3);
+            v = vmulq_n_f32(srcv[2][2 * j + 1], id[2]);
+            vi = vcvtnq_s32_f32(v);
+            y[i].qs[32 * j + 20] = vgetq_lane_s32(vi, 0);
+            y[i].qs[32 * j + 21] = vgetq_lane_s32(vi, 1);
+            y[i].qs[32 * j + 22] = vgetq_lane_s32(vi, 2);
+            y[i].qs[32 * j + 23] = vgetq_lane_s32(vi, 3);
+
+            v = vmulq_n_f32(srcv[3][2 * j], id[3]);
+            vi = vcvtnq_s32_f32(v);
+            y[i].qs[32 * j + 24] = vgetq_lane_s32(vi, 0);
+            y[i].qs[32 * j + 25] = vgetq_lane_s32(vi, 1);
+            y[i].qs[32 * j + 26] = vgetq_lane_s32(vi, 2);
+            y[i].qs[32 * j + 27] = vgetq_lane_s32(vi, 3);
+            v = vmulq_n_f32(srcv[3][2 * j + 1], id[3]);
+            vi = vcvtnq_s32_f32(v);
+            y[i].qs[32 * j + 28] = vgetq_lane_s32(vi, 0);
+            y[i].qs[32 * j + 29] = vgetq_lane_s32(vi, 1);
+            y[i].qs[32 * j + 30] = vgetq_lane_s32(vi, 2);
+            y[i].qs[32 * j + 31] = vgetq_lane_s32(vi, 3);
+        }
+    }
+#else
+    // scalar
+    const int interleave_blcksize = 8;
+    float srcv[4][QK8_0];
+    float id[4];
+
+    for (int i = 0; i < nb; i++) {
+        for (int row_iter = 0; row_iter < 4; row_iter++) {
+            float amax = 0.0f; // absolute max
+
+            for (int j = 0; j < QK8_0; j++) {
+                srcv[row_iter][j] = x[row_iter * k + i * QK8_0 + j];
+                amax = MAX(amax, fabsf(srcv[row_iter][j]));
+            }
+
+            const float d = amax / ((1 << 7) - 1);
+            id[row_iter] = d ? 1.0f / d : 0.0f;
+
+            y[i].d[row_iter] = GGML_FP32_TO_FP16(d);
+        }
+
+        for (int j = 0; j < QK8_0 * 4; j++) {
+            int src_offset = (j / (4 * interleave_blcksize)) * interleave_blcksize;
+            int src_id = (j % (4 * interleave_blcksize)) / interleave_blcksize;
+            src_offset += (j % interleave_blcksize);
+
+            float x0 = srcv[src_id][src_offset] * id[src_id];
+            y[i].qs[j] = roundf(x0);;
+        }
+    }
+#endif
+}
+
+void quantize_mat_q8_0(const float * restrict x, void * restrict vy, int64_t nrow, int64_t n_per_row, int64_t interleave_blcksize) {
+    assert(nrow == 4);
+    UNUSED(nrow);
+    if (interleave_blcksize == 4) quantize_q8_0_4x4(x, vy, n_per_row);
+    else if (interleave_blcksize == 8) quantize_q8_0_4x8(x, vy, n_per_row);
+    else assert(false);
+}
+
+static size_t quantize_q4_0_nr_bl(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, int nrows_interleaved, int interleave_blcksize) {
+    assert(n_per_row % QK4_0 == 0);
+    const int nb = n_per_row / QK4_0;
+
+    void * out_ptr = NULL;
+    if (nrows_interleaved == 8) {
+        out_ptr = (block_q4_0x8 *) dst;
+    }
+    else if (nrows_interleaved == 4) {
+        out_ptr = (block_q4_0x4 *) dst;
+    }
+    assert(nrows_interleaved <= 8);
+    block_q4_0 dst_tmp[8];
+
+    for (int b = 0; b < (nrow * n_per_row); b += nrows_interleaved * n_per_row) {
+
+        for (int64_t x = 0; x < nb; x++) {
+
+            for (int i  = 0; i < nrows_interleaved; i++ ) {
+                quantize_row_q4_0_reference(src + b + i * n_per_row + x * QK4_0, (block_q4_0 *) dst_tmp + i, QK4_0);
+            }
+
+            if (nrows_interleaved == 8) {
+                *(block_q4_0x8 *) out_ptr = make_block_q4_0x8(dst_tmp, interleave_blcksize, 0x88);
+                out_ptr = (block_q4_0x8 *) out_ptr + 1;
+            }
+            else if (nrows_interleaved == 4) {
+                *(block_q4_0x4 *) out_ptr = make_block_q4_0x4(dst_tmp, interleave_blcksize, 0x88);
+                out_ptr = (block_q4_0x4 *) out_ptr + 1;
+            }
+        }
+    }
+
+    return ((nrow * n_per_row) / QK4_0 * sizeof(block_q4_0));
+}
+
+size_t quantize_q4_0_4x4(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
+    if (!quant_weights) {
+        return quantize_q4_0_nr_bl(src, dst, nrow, n_per_row, 4, 4);
+    }
+    else {
+        assert(false);
+        return 0;
+    }
+}
+
+size_t quantize_q4_0_4x8(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
+    if (!quant_weights) {
+        return quantize_q4_0_nr_bl(src, dst, nrow, n_per_row, 4, 8);
+    }
+    else {
+        assert(false);
+        return 0;
+    }
+}
+
+size_t quantize_q4_0_8x8(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
+    if (!quant_weights) {
+        return quantize_q4_0_nr_bl(src, dst, nrow, n_per_row, 8, 8);
+    }
+    else {
+        assert(false);
+        return 0;
+    }
+}
+
+void ggml_gemv_q4_0_4x4_q8_0(int n, float * restrict s, size_t bs, const void * restrict vx, const void * restrict vy, int nr, int nc) {
+    const int qk = QK8_0;
+    const int nb = n / qk;
+    const int ncols_interleaved = 4;
+    const int blocklen = 4;
+
+    assert (n % qk == 0);
+    assert (nc % ncols_interleaved == 0);
+
+    UNUSED(s);
+    UNUSED(bs);
+    UNUSED(vx);
+    UNUSED(vy);
+    UNUSED(nr);
+    UNUSED(nc);
+    UNUSED(nb);
+    UNUSED(ncols_interleaved);
+    UNUSED(blocklen);
+
+#if defined(__ARM_FEATURE_SVE)
+    if (svcntw() == 8) {
+        GGML_ASSERT(!(ggml_cpu_has_sve() && (svcntw() == 8)) &&
+                    "__ARM_FEATURE_SVE defined, use the Q4_0_8_8 quantization format for optimal performance");
+    }
+#endif
+#if defined(__ARM_NEON) && defined(__ARM_FEATURE_MATMUL_INT8)
+    GGML_ASSERT(!(ggml_cpu_has_neon() && ggml_cpu_has_matmul_int8()) &&
+                "__ARM_NEON and __ARM_FEATURE_MATMUL_INT8 defined, use the Q4_0_4_8 quantization format for optimal performance");
+#elif defined(__ARM_NEON) && defined(__aarch64__)
+    const void * b_ptr = vx;
+    const void * a_ptr = vy;
+    float * res_ptr = s;
+
+    __asm__ __volatile__(
+        "movi v31.16b, #0x4\n"
+        "movi v30.16b, #0xf0\n"
+        "add %x[b_ptr], %x[b_ptr], #0x8\n"
+        "1:"  // Column loop
+        "add x22, %x[a_ptr], #0x2\n"
+        "movi v29.16b, #0x0\n"
+        "mov x21, %x[nb]\n"
+        "2:"  // Block loop
+        "ldr q28, [%x[b_ptr], #0x0]\n"
+        "ldr q27, [x22, #0x0]\n"
+        "movi v26.4s, #0x0\n"
+        "sub x20, x22, #0x2\n"
+        "ldr q25, [x22, #0x10]\n"
+        "ldr q24, [%x[b_ptr], #0x10]\n"
+        "sub x21, x21, #0x1\n"
+        "add x22, x22, #0x22\n"
+        "ldr q23, [%x[b_ptr], #0x20]\n"
+        "ldr q22, [%x[b_ptr], #0x30]\n"
+        "ld1r { v21.8h }, [x20]\n"
+        "ldr q20, [%x[b_ptr], #-0x8]\n"
+        "sshl v16.16b, v28.16b, v31.16b\n"
+        "and v28.16b, v28.16b, v30.16b\n"
+        "sshl v19.16b, v24.16b, v31.16b\n"
+        "and v24.16b, v24.16b, v30.16b\n"
+        "add %x[b_ptr], %x[b_ptr], #0x48\n"
+        "sshl v18.16b, v23.16b, v31.16b\n"
+        "and v23.16b, v23.16b, v30.16b\n"
+        ".inst 0x4f9be21a  // sdot v26.4s, v16.16b, v27.4b[0]\n"
+        "sshl v17.16b, v22.16b, v31.16b\n"
+        "and v22.16b, v22.16b, v30.16b\n"
+        "fcvtl v21.4s, v21.4h\n"
+        "fcvtl v16.4s, v20.4h\n"
+        ".inst 0x4f99e39a  // sdot v26.4s, v28.16b, v25.4b[0]\n"
+        "fmul v16.4s, v16.4s, v21.4s\n"
+        ".inst 0x4fbbe27a  // sdot v26.4s, v19.16b, v27.4b[1]\n"
+        ".inst 0x4fb9e31a  // sdot v26.4s, v24.16b, v25.4b[1]\n"
+        ".inst 0x4f9bea5a  // sdot v26.4s, v18.16b, v27.4b[2]\n"
+        ".inst 0x4f99eafa  // sdot v26.4s, v23.16b, v25.4b[2]\n"
+        ".inst 0x4fbbea3a  // sdot v26.4s, v17.16b, v27.4b[3]\n"
+        ".inst 0x4fb9eada  // sdot v26.4s, v22.16b, v25.4b[3]\n"
+        "scvtf v26.4s, v26.4s, #0x4\n"
+        "fmla v29.4s, v26.4s, v16.4s\n"
+        "cbnz x21, 2b\n"
+        "sub %x[nc], %x[nc], #0x4\n"
+        "str q29, [%x[res_ptr], #0x0]\n"
+        "add %x[res_ptr], %x[res_ptr], #0x10\n"
+        "cbnz %x[nc], 1b\n"
+        : [b_ptr] "+&r" (b_ptr), [res_ptr] "+&r" (res_ptr), [nc] "+&r" (nc)
+        : [a_ptr] "r" (a_ptr), [nb] "r" (nb)
+        : "memory", "v16", "v17", "v18", "v19", "v20", "v21", "v22", "v23", "v24", "v25", "v26", "v27", "v28", "v29", "v30", "v31", "x20", "x21", "x22"
+    );
+#else
+    float sumf[4];
+    int sumi;
+
+    const block_q8_0 * a_ptr = (const block_q8_0 *) vy;
+    for (int x = 0; x < nc / ncols_interleaved; x++) {
+        const block_q4_0x4 * b_ptr = (const block_q4_0x4 *) vx + (x * nb);
+
+        for (int j = 0; j < ncols_interleaved; j++) sumf[j] = 0.0;
+        for (int l = 0; l < nb; l++) {
+            for (int k = 0; k < (qk / (2 * blocklen)); k++) {
+                for (int j = 0; j < ncols_interleaved; j++) {
+                    sumi = 0;
+                    for (int i = 0; i < blocklen; ++i) {
+                        const int v0 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] << 4);
+                        const int v1 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] & 0xF0);
+                        sumi += ((v0 * a_ptr[l].qs[k * blocklen + i]) + (v1 * a_ptr[l].qs[k * blocklen + i + qk / 2])) >> 4;
+                    }
+                    sumf[j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d);
+                }
+            }
+        }
+        for (int j = 0; j < ncols_interleaved; j++) s[x * ncols_interleaved + j] = sumf[j];
+    }
+#endif
+}
+
+void ggml_gemv_q4_0_4x8_q8_0(int n, float * restrict s, size_t bs, const void * restrict vx, const void * restrict vy, int nr, int nc) {
+    const int qk = QK8_0;
+    const int nb = n / qk;
+    const int ncols_interleaved = 4;
+    const int blocklen = 8;
+
+    assert (n % qk == 0);
+    assert (nc % ncols_interleaved == 0);
+
+    UNUSED(s);
+    UNUSED(bs);
+    UNUSED(vx);
+    UNUSED(vy);
+    UNUSED(nr);
+    UNUSED(nc);
+    UNUSED(nb);
+    UNUSED(ncols_interleaved);
+    UNUSED(blocklen);
+
+#if defined(__ARM_FEATURE_SVE)
+    if (svcntw() == 8) {
+        GGML_ASSERT(!(ggml_cpu_has_sve() && (svcntw() == 8)) &&
+                    "__ARM_FEATURE_SVE defined, use the Q4_0_8_8 quantization format for optimal performance");
+    }
+#endif
+#if defined(__ARM_NEON) && defined(__ARM_FEATURE_MATMUL_INT8)
+    const void * b_ptr = vx;
+    const void * a_ptr = vy;
+    float * res_ptr = s;
+
+    __asm__ __volatile__(
+        "movi v2.16b, #0x4\n"
+        "movi v1.16b, #0xf0\n"
+        "add %x[b_ptr], %x[b_ptr], #0x8\n"
+        "1:"  // Column loop
+        "add x23, %x[a_ptr], #0x2\n"
+        "movi v0.16b, #0x0\n"
+        "mov x22, %x[nb]\n"
+        "2:"  // Block loop
+        "ldr q31, [%x[b_ptr], #0x0]\n"
+        "ldr q30, [%x[b_ptr], #0x10]\n"
+        "mov x21, x23\n"
+        "movi v29.4s, #0x0\n"
+        "ldr q28, [%x[b_ptr], #0x20]\n"
+        "ldr q27, [%x[b_ptr], #0x30]\n"
+        "movi v26.4s, #0x0\n"
+        "sub x20, x23, #0x2\n"
+        "ld1r { v25.8h }, [x20]\n"
+        "ldr q24, [%x[b_ptr], #-0x8]\n"
+        "sub x22, x22, #0x1\n"
+        "add x23, x23, #0x22\n"
+        "ld1r { v23.2d }, [x21], #0x8\n"
+        "sshl v22.16b, v31.16b, v2.16b\n"
+        "sshl v16.16b, v30.16b, v2.16b\n"
+        "add %x[b_ptr], %x[b_ptr], #0x48\n"
+        "ld1r { v21.2d }, [x21], #0x8\n"
+        "sshl v20.16b, v28.16b, v2.16b\n"
+        "sshl v19.16b, v27.16b, v2.16b\n"
+        "ld1r { v18.2d }, [x21], #0x8\n"
+        "ld1r { v17.2d }, [x21], #0x8\n"
+        "and v31.16b, v31.16b, v1.16b\n"
+        "and v30.16b, v30.16b, v1.16b\n"
+        ".inst 0x4e9796dd  // sdot v29.4s, v22.16b, v23.16b\n"
+        ".inst 0x4e97961a  // sdot v26.4s, v16.16b, v23.16b\n"
+        "and v28.16b, v28.16b, v1.16b\n"
+        "and v27.16b, v27.16b, v1.16b\n"
+        "fcvtl v25.4s, v25.4h\n"
+        "fcvtl v16.4s, v24.4h\n"
+        ".inst 0x4e95969d  // sdot v29.4s, v20.16b, v21.16b\n"
+        ".inst 0x4e95967a  // sdot v26.4s, v19.16b, v21.16b\n"
+        "fmul v16.4s, v16.4s, v25.4s\n"
+        ".inst 0x4e9297fd  // sdot v29.4s, v31.16b, v18.16b\n"
+        ".inst 0x4e9297da  // sdot v26.4s, v30.16b, v18.16b\n"
+        ".inst 0x4e91979d  // sdot v29.4s, v28.16b, v17.16b\n"
+        ".inst 0x4e91977a  // sdot v26.4s, v27.16b, v17.16b\n"
+        "addp v29.4s, v29.4s, v26.4s\n"
+        "scvtf v29.4s, v29.4s, #0x4\n"
+        "fmla v0.4s, v29.4s, v16.4s\n"
+        "cbnz x22, 2b\n"
+        "sub %x[nc], %x[nc], #0x4\n"
+        "str q0, [%x[res_ptr], #0x0]\n"
+        "add %x[res_ptr], %x[res_ptr], #0x10\n"
+        "cbnz %x[nc], 1b\n"
+        : [b_ptr] "+&r" (b_ptr), [res_ptr] "+&r" (res_ptr), [nc] "+&r" (nc)
+        : [a_ptr] "r" (a_ptr), [nb] "r" (nb)
+        : "memory", "v0", "v1", "v2", "v16", "v17", "v18", "v19", "v20", "v21", "v22", "v23", "v24", "v25", "v26", "v27", "v28", "v29", "v30", "v31", "x20", "x21", "x22", "x23"
+    );
+#elif defined(__ARM_NEON) && defined(__aarch64__)
+    GGML_ASSERT((ggml_cpu_has_sve() || ggml_cpu_has_matmul_int8()) &&
+                "__ARM_FEATURE_SVE and __ARM_FEATURE_MATMUL_INT8 not defined, use the Q4_0_4_4 quantization format for optimal "
+                "performance");
+#else
+    float sumf[4];
+    int sumi;
+
+    const block_q8_0 * a_ptr = (const block_q8_0 *) vy;
+    for (int x = 0; x < nc / ncols_interleaved; x++) {
+        const block_q4_0x4 * b_ptr = (const block_q4_0x4 *) vx + (x * nb);
+
+        for (int j = 0; j < ncols_interleaved; j++) sumf[j] = 0.0;
+        for (int l = 0; l < nb; l++) {
+            for (int k = 0; k < (qk / (2 * blocklen)); k++) {
+                for (int j = 0; j < ncols_interleaved; j++) {
+                    sumi = 0;
+                    for (int i = 0; i < blocklen; ++i) {
+                        const int v0 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] << 4);
+                        const int v1 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] & 0xF0);
+                        sumi += ((v0 * a_ptr[l].qs[k * blocklen + i]) + (v1 * a_ptr[l].qs[k * blocklen + i + qk / 2])) >> 4;
+                    }
+                    sumf[j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d);
+                }
+            }
+        }
+        for (int j = 0; j < ncols_interleaved; j++) s[x * ncols_interleaved + j] = sumf[j];
+    }
+#endif
+}
+
+void ggml_gemv_q4_0_8x8_q8_0(int n, float * restrict s, size_t bs, const void * restrict vx, const void * restrict vy, int nr, int nc) {
+    const int qk = QK8_0;
+    const int nb = n / qk;
+    const int ncols_interleaved = 8;
+    const int blocklen = 8;
+
+    assert (n % qk == 0);
+    assert (nc % ncols_interleaved == 0);
+
+    UNUSED(s);
+    UNUSED(bs);
+    UNUSED(vx);
+    UNUSED(vy);
+    UNUSED(nr);
+    UNUSED(nc);
+    UNUSED(nb);
+    UNUSED(ncols_interleaved);
+    UNUSED(blocklen);
+
+#if defined(__ARM_FEATURE_SVE)
+    if (svcntw() == 8) {
+        const void * b_ptr = vx;
+        const void * a_ptr = vy;
+        float * res_ptr = s;
+
+        __asm__ __volatile__(
+            "ptrue p0.b\n"
+            "add %x[b_ptr], %x[b_ptr], #0x10\n"
+            "1:"  // Column loop
+            "add x22, %x[a_ptr], #0x2\n"
+            "mov z31.b, #0x0\n"
+            "mov x21, %x[nb]\n"
+            "2:"  // Block loop
+            "ld1b { z30.b }, p0/Z, [%x[b_ptr]]\n"
+            "ld1b { z29.b }, p0/Z, [%x[b_ptr], #1, MUL VL]\n"
+            "mov z28.s, #0x0\n"
+            "mov z27.s, #0x0\n"
+            "ld1rd { z26.d }, p0/Z, [x22]\n"
+            "ld1b { z25.b }, p0/Z, [%x[b_ptr], #2, MUL VL]\n"
+            "sub x20, x22, #0x2\n"
+            "sub x21, x21, #0x1\n"
+            "ld1b { z24.b }, p0/Z, [%x[b_ptr], #3, MUL VL]\n"
+            "ld1rd { z23.d }, p0/Z, [x22, #8]\n"
+            "lsl z22.b, z30.b, #0x4\n"
+            "lsl z16.b, z29.b, #0x4\n"
+            "and z30.b, z30.b, #0xf0\n"
+            "and z29.b, z29.b, #0xf0\n"
+            "ld1rd { z21.d }, p0/Z, [x22, #16]\n"
+            "ld1rd { z20.d }, p0/Z, [x22, #24]\n"
+            "lsl z19.b, z25.b, #0x4\n"
+            "and z25.b, z25.b, #0xf0\n"
+            "ld1rh { z17.h }, p0/Z, [x20]\n"
+            "ld1h { z18.s }, p0/Z, [%x[b_ptr], #-1, MUL VL]\n"
+            "sdot z28.s, z22.b, z26.b\n"
+            "sdot z27.s, z16.b, z26.b\n"
+            "lsl z16.b, z24.b, #0x4\n"
+            "add x22, x22, #0x22\n"
+            "and z24.b, z24.b, #0xf0\n"
+            "add %x[b_ptr], %x[b_ptr], #0x90\n"
+            "fcvt z17.s, p0/m, z17.h\n"
+            "fcvt z18.s, p0/m, z18.h\n"
+            "sdot z28.s, z19.b, z23.b\n"
+            "sdot z27.s, z16.b, z23.b\n"
+            "fmul z18.s, z18.s, z17.s\n"
+            "sdot z28.s, z30.b, z21.b\n"
+            "sdot z27.s, z29.b, z21.b\n"
+            "sdot z28.s, z25.b, z20.b\n"
+            "sdot z27.s, z24.b, z20.b\n"
+            "uzp1 z17.s, z28.s, z27.s\n"
+            "uzp2 z16.s, z28.s, z27.s\n"
+            "add z17.s, z17.s, z16.s\n"
+            "asr z17.s, z17.s, #0x4\n"
+            "scvtf z17.s, p0/m, z17.s\n"
+            "fmla z31.s, p0/M, z17.s, z18.s\n"
+            "cbnz x21, 2b\n"
+            "sub %x[nc], %x[nc], #0x8\n"
+            "st1w { z31.s }, p0, [%x[res_ptr]]\n"
+            "add %x[res_ptr], %x[res_ptr], #0x20\n"
+            "cbnz %x[nc], 1b\n"
+            : [b_ptr] "+&r" (b_ptr), [res_ptr] "+&r" (res_ptr), [nc] "+&r" (nc)
+            : [a_ptr] "r" (a_ptr), [nb] "r" (nb)
+            : "memory", "p0", "x20", "x21", "x22", "z16", "z17", "z18", "z19", "z20", "z21", "z22", "z23", "z24", "z25", "z26", "z27", "z28", "z29", "z30", "z31"
+        );
+        return;
+    }
+    else if (ggml_cpu_has_neon() && ggml_cpu_has_matmul_int8()) {
+        GGML_ASSERT((ggml_cpu_has_sve() && (svcntw() == 8)) &&
+                    "__ARM_FEATURE_SVE for vector size of 256-bits not defined, use the Q4_0_4_8 quantization format for optimal "
+                    "performance");
+    }
+    else if (ggml_cpu_has_neon()) {
+        GGML_ASSERT(((ggml_cpu_has_sve() && (svcntw() == 8)) || ggml_cpu_has_matmul_int8()) &&
+                    "__ARM_FEATURE_SVE for vector size of 256-bits and __ARM_FEATURE_MATMUL_INT8 not defined, use the Q4_0_4_4 "
+                    "quantization format for optimal performance");
+    }
+#endif
+#if defined(__ARM_NEON) && defined(__ARM_FEATURE_MATMUL_INT8)
+    GGML_ASSERT(ggml_cpu_has_sve() &&
+                "__ARM_FEATURE_SVE not defined, use the Q4_0_4_8 quantization format for optimal performance");
+#elif defined(__ARM_NEON) && defined(__aarch64__)
+    GGML_ASSERT((ggml_cpu_has_sve() || ggml_cpu_has_matmul_int8()) &&
+                "__ARM_FEATURE_SVE and __ARM_FEATURE_MATMUL_INT8 not defined, use the Q4_0_4_4 quantization format for optimal "
+                "performance");
+#else
+    float sumf[8];
+    int sumi;
+
+    const block_q8_0 * a_ptr = (const block_q8_0 *) vy;
+    for (int x = 0; x < nc / ncols_interleaved; x++) {
+        const block_q4_0x8 * b_ptr = (const block_q4_0x8 *) vx + (x * nb);
+
+        for (int j = 0; j < ncols_interleaved; j++) sumf[j] = 0.0;
+        for (int l = 0; l < nb; l++) {
+            for (int k = 0; k < (qk / (2 * blocklen)); k++) {
+                for (int j = 0; j < ncols_interleaved; j++) {
+                    sumi = 0;
+                    for (int i = 0; i < blocklen; ++i) {
+                        const int v0 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] << 4);
+                        const int v1 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] & 0xF0);
+                        sumi += ((v0 * a_ptr[l].qs[k * blocklen + i]) + (v1 * a_ptr[l].qs[k * blocklen + i + qk / 2])) >> 4;
+                    }
+                    sumf[j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d);
+                }
+            }
+        }
+        for (int j = 0; j < ncols_interleaved; j++) s[x * ncols_interleaved + j] = sumf[j];
+    }
+#endif
+}
+
+void ggml_gemm_q4_0_4x4_q8_0(int n, float * restrict s, size_t bs, const void * restrict vx, const void * restrict vy, int nr, int nc) {
+    const int qk = QK8_0;
+    const int nb = n / qk;
+    const int ncols_interleaved = 4;
+    const int blocklen = 4;
+
+    assert (n % qk == 0);
+    assert (nr % 4 == 0);
+    assert (nc % ncols_interleaved == 0);
+
+    UNUSED(s);
+    UNUSED(bs);
+    UNUSED(vx);
+    UNUSED(vy);
+    UNUSED(nr);
+    UNUSED(nc);
+    UNUSED(nb);
+    UNUSED(ncols_interleaved);
+    UNUSED(blocklen);
+
+#if defined(__ARM_FEATURE_SVE) && defined(__ARM_FEATURE_MATMUL_INT8)
+    if (svcntw() == 8) {
+        GGML_ASSERT(!(ggml_cpu_has_sve() && (svcntw() == 8)) &&
+                    "__ARM_FEATURE_SVE defined, use the Q4_0_8_8 quantization format for optimal performance");
+    }
+#endif
+#if defined(__ARM_NEON) && defined(__ARM_FEATURE_MATMUL_INT8)
+    GGML_ASSERT(!(ggml_cpu_has_neon() && ggml_cpu_has_matmul_int8()) &&
+                "__ARM_NEON and __ARM_FEATURE_MATMUL_INT8 defined, use the Q4_0_4_8 quantization format for optimal performance");
+#elif defined(__ARM_NEON) && defined(__aarch64__)
+    const void * b_ptr = vx;
+    const void * a_ptr = vy;
+    float * res_ptr = s;
+    size_t res_stride = bs * sizeof(float);
+
+    __asm__ __volatile__(
+        "mov x10, %x[nr]\n"
+        "mov x9, #0x88\n"
+        "cmp x10, #0x10\n"
+        "mul x9, %x[nb], x9\n"
+        "blt 4f\n"
+        "1:"  // Row loop
+        "add x28, %x[b_ptr], #0x8\n"
+        "mov x27, %x[nc]\n"
+        "add x26, %x[res_ptr], %x[res_stride], LSL #4\n"
+        "2:"  // Column loop
+        "add x25, %x[a_ptr], #0x8\n"
+        "movi v15.16b, #0x0\n"
+        "movi v19.16b, #0x0\n"
+        "mov x24, %x[nb]\n"
+        "add x23, x25, x9\n"
+        "movi v18.16b, #0x0\n"
+        "movi v14.16b, #0x0\n"
+        "add x22, x23, x9\n"
+        "movi v11.16b, #0x0\n"
+        "movi v13.16b, #0x0\n"
+        "add x21, x22, x9\n"
+        "movi v23.16b, #0x0\n"
+        "movi v16.16b, #0x0\n"
+        "movi v25.16b, #0x0\n"
+        "movi v7.16b, #0x0\n"
+        "movi v0.16b, #0x0\n"
+        "movi v4.16b, #0x0\n"
+        "movi v5.16b, #0x0\n"
+        "movi v21.16b, #0x0\n"
+        "movi v8.16b, #0x0\n"
+        "movi v1.16b, #0x0\n"
+        "3:"  // Block loop
+        "ldr q3, [x28, #0x0]\n"
+        "ldr q31, [x25, #0x0]\n"
+        "movi v28.16b, #0x4\n"
+        "movi v10.4s, #0x0\n"
+        "ldr q22, [x28, #0x10]\n"
+        "ldr q6, [x25, #0x10]\n"
+        "movi v29.4s, #0x0\n"
+        "movi v9.4s, #0x0\n"
+        "ldr q27, [x28, #0x20]\n"
+        "ldr q30, [x28, #0x30]\n"
+        "movi v20.4s, #0x0\n"
+        "movi v24.16b, #0xf0\n"
+        "ldr d2, [x25, #-0x8]\n"
+        "ldr d26, [x23, #-0x8]\n"
+        "sshl v12.16b, v3.16b, v28.16b\n"
+        "sub x20, x28, #0x8\n"
+        "ldr d17, [x20, #0x0]\n"
+        "and v3.16b, v3.16b, v24.16b\n"
+        "subs x24, x24, #0x1\n"
+        "add x28, x28, #0x48\n"
+        ".inst 0x4f9fe18a  // sdot v10.4s, v12.16b, v31.4b[0]\n"
+        ".inst 0x4fbfe19d  // sdot v29.4s, v12.16b, v31.4b[1]\n"
+        ".inst 0x4f9fe989  // sdot v9.4s, v12.16b, v31.4b[2]\n"
+        ".inst 0x4fbfe994  // sdot v20.4s, v12.16b, v31.4b[3]\n"
+        "sshl v31.16b, v22.16b, v28.16b\n"
+        "and v22.16b, v22.16b, v24.16b\n"
+        "fcvtl v17.4s, v17.4h\n"
+        "fcvtl v2.4s, v2.4h\n"
+        "fcvtl v26.4s, v26.4h\n"
+        ".inst 0x4f86e3ea  // sdot v10.4s, v31.16b, v6.4b[0]\n"
+        ".inst 0x4fa6e3fd  // sdot v29.4s, v31.16b, v6.4b[1]\n"
+        ".inst 0x4f86ebe9  // sdot v9.4s, v31.16b, v6.4b[2]\n"
+        ".inst 0x4fa6ebf4  // sdot v20.4s, v31.16b, v6.4b[3]\n"
+        "sshl v6.16b, v27.16b, v28.16b\n"
+        "sshl v28.16b, v30.16b, v28.16b\n"
+        "and v27.16b, v27.16b, v24.16b\n"
+        "and v30.16b, v30.16b, v24.16b\n"
+        "ldr q24, [x25, #0x20]\n"
+        ".inst 0x4f98e0ca  // sdot v10.4s, v6.16b, v24.4b[0]\n"
+        ".inst 0x4fb8e0dd  // sdot v29.4s, v6.16b, v24.4b[1]\n"
+        ".inst 0x4f98e8c9  // sdot v9.4s, v6.16b, v24.4b[2]\n"
+        ".inst 0x4fb8e8d4  // sdot v20.4s, v6.16b, v24.4b[3]\n"
+        "ldr q24, [x25, #0x30]\n"
+        ".inst 0x4f98e38a  // sdot v10.4s, v28.16b, v24.4b[0]\n"
+        ".inst 0x4fb8e39d  // sdot v29.4s, v28.16b, v24.4b[1]\n"
+        ".inst 0x4f98eb89  // sdot v9.4s, v28.16b, v24.4b[2]\n"
+        ".inst 0x4fb8eb94  // sdot v20.4s, v28.16b, v24.4b[3]\n"
+        "ldr q24, [x25, #0x40]\n"
+        ".inst 0x4f98e06a  // sdot v10.4s, v3.16b, v24.4b[0]\n"
+        ".inst 0x4fb8e07d  // sdot v29.4s, v3.16b, v24.4b[1]\n"
+        ".inst 0x4f98e869  // sdot v9.4s, v3.16b, v24.4b[2]\n"
+        ".inst 0x4fb8e874  // sdot v20.4s, v3.16b, v24.4b[3]\n"
+        "ldr q24, [x25, #0x50]\n"
+        ".inst 0x4f98e2ca  // sdot v10.4s, v22.16b, v24.4b[0]\n"
+        ".inst 0x4fb8e2dd  // sdot v29.4s, v22.16b, v24.4b[1]\n"
+        ".inst 0x4f98eac9  // sdot v9.4s, v22.16b, v24.4b[2]\n"
+        ".inst 0x4fb8ead4  // sdot v20.4s, v22.16b, v24.4b[3]\n"
+        "ldr q24, [x25, #0x60]\n"
+        ".inst 0x4f98e36a  // sdot v10.4s, v27.16b, v24.4b[0]\n"
+        ".inst 0x4fb8e37d  // sdot v29.4s, v27.16b, v24.4b[1]\n"
+        ".inst 0x4f98eb69  // sdot v9.4s, v27.16b, v24.4b[2]\n"
+        ".inst 0x4fb8eb74  // sdot v20.4s, v27.16b, v24.4b[3]\n"
+        "ldr q24, [x25, #0x70]\n"
+        "add x25, x25, #0x88\n"
+        ".inst 0x4f98e3ca  // sdot v10.4s, v30.16b, v24.4b[0]\n"
+        ".inst 0x4fb8e3dd  // sdot v29.4s, v30.16b, v24.4b[1]\n"
+        ".inst 0x4f98ebc9  // sdot v9.4s, v30.16b, v24.4b[2]\n"
+        ".inst 0x4fb8ebd4  // sdot v20.4s, v30.16b, v24.4b[3]\n"
+        "fmul v24.4s, v17.4s, v2.s[0]\n"
+        "scvtf v10.4s, v10.4s, #0x4\n"
+        "scvtf v29.4s, v29.4s, #0x4\n"
+        "scvtf v9.4s, v9.4s, #0x4\n"
+        "scvtf v20.4s, v20.4s, #0x4\n"
+        "fmla v15.4s, v10.4s, v24.4s\n"
+        "ldr q24, [x23, #0x0]\n"
+        "fmul v10.4s, v17.4s, v2.s[1]\n"
+        "fmla v19.4s, v29.4s, v10.4s\n"
+        "ldr q10, [x23, #0x10]\n"
+        "fmul v29.4s, v17.4s, v2.s[2]\n"
+        "fmul v2.4s, v17.4s, v2.s[3]\n"
+        "fmla v18.4s, v9.4s, v29.4s\n"
+        "movi v9.4s, #0x0\n"
+        "movi v29.4s, #0x0\n"
+        ".inst 0x4f98e189  // sdot v9.4s, v12.16b, v24.4b[0]\n"
+        ".inst 0x4fb8e19d  // sdot v29.4s, v12.16b, v24.4b[1]\n"
+        "fmla v14.4s, v20.4s, v2.4s\n"
+        "movi v20.4s, #0x0\n"
+        "movi v2.4s, #0x0\n"
+        ".inst 0x4f98e994  // sdot v20.4s, v12.16b, v24.4b[2]\n"
+        ".inst 0x4fb8e982  // sdot v2.4s, v12.16b, v24.4b[3]\n"
+        "ldr q24, [x23, #0x20]\n"
+        ".inst 0x4f8ae3e9  // sdot v9.4s, v31.16b, v10.4b[0]\n"
+        ".inst 0x4faae3fd  // sdot v29.4s, v31.16b, v10.4b[1]\n"
+        ".inst 0x4f8aebf4  // sdot v20.4s, v31.16b, v10.4b[2]\n"
+        ".inst 0x4faaebe2  // sdot v2.4s, v31.16b, v10.4b[3]\n"
+        "ldr q10, [x23, #0x30]\n"
+        ".inst 0x4f98e0c9  // sdot v9.4s, v6.16b, v24.4b[0]\n"
+        ".inst 0x4fb8e0dd  // sdot v29.4s, v6.16b, v24.4b[1]\n"
+        ".inst 0x4f98e8d4  // sdot v20.4s, v6.16b, v24.4b[2]\n"
+        ".inst 0x4fb8e8c2  // sdot v2.4s, v6.16b, v24.4b[3]\n"
+        "ldr q24, [x23, #0x40]\n"
+        ".inst 0x4f8ae389  // sdot v9.4s, v28.16b, v10.4b[0]\n"
+        ".inst 0x4faae39d  // sdot v29.4s, v28.16b, v10.4b[1]\n"
+        ".inst 0x4f8aeb94  // sdot v20.4s, v28.16b, v10.4b[2]\n"
+        ".inst 0x4faaeb82  // sdot v2.4s, v28.16b, v10.4b[3]\n"
+        "ldr q10, [x23, #0x50]\n"
+        ".inst 0x4f98e069  // sdot v9.4s, v3.16b, v24.4b[0]\n"
+        ".inst 0x4fb8e07d  // sdot v29.4s, v3.16b, v24.4b[1]\n"
+        ".inst 0x4f98e874  // sdot v20.4s, v3.16b, v24.4b[2]\n"
+        ".inst 0x4fb8e862  // sdot v2.4s, v3.16b, v24.4b[3]\n"
+        "ldr q24, [x23, #0x60]\n"
+        ".inst 0x4f8ae2c9  // sdot v9.4s, v22.16b, v10.4b[0]\n"
+        ".inst 0x4faae2dd  // sdot v29.4s, v22.16b, v10.4b[1]\n"
+        ".inst 0x4f8aead4  // sdot v20.4s, v22.16b, v10.4b[2]\n"
+        ".inst 0x4faaeac2  // sdot v2.4s, v22.16b, v10.4b[3]\n"
+        "ldr q10, [x23, #0x70]\n"
+        "add x23, x23, #0x88\n"
+        ".inst 0x4f98e369  // sdot v9.4s, v27.16b, v24.4b[0]\n"
+        ".inst 0x4fb8e37d  // sdot v29.4s, v27.16b, v24.4b[1]\n"
+        ".inst 0x4f98eb74  // sdot v20.4s, v27.16b, v24.4b[2]\n"
+        ".inst 0x4fb8eb62  // sdot v2.4s, v27.16b, v24.4b[3]\n"
+        "ldr q24, [x22, #0x0]\n"
+        ".inst 0x4f8ae3c9  // sdot v9.4s, v30.16b, v10.4b[0]\n"
+        ".inst 0x4faae3dd  // sdot v29.4s, v30.16b, v10.4b[1]\n"
+        ".inst 0x4f8aebd4  // sdot v20.4s, v30.16b, v10.4b[2]\n"
+        ".inst 0x4faaebc2  // sdot v2.4s, v30.16b, v10.4b[3]\n"
+        "fmul v10.4s, v17.4s, v26.s[0]\n"
+        "scvtf v9.4s, v9.4s, #0x4\n"
+        "scvtf v29.4s, v29.4s, #0x4\n"
+        "scvtf v20.4s, v20.4s, #0x4\n"
+        "scvtf v2.4s, v2.4s, #0x4\n"
+        "fmla v11.4s, v9.4s, v10.4s\n"
+        "ldr q9, [x22, #0x10]\n"
+        "fmul v10.4s, v17.4s, v26.s[1]\n"
+        "fmla v13.4s, v29.4s, v10.4s\n"
+        "ldr d29, [x22, #-0x8]\n"
+        "fmul v10.4s, v17.4s, v26.s[2]\n"
+        "fmul v26.4s, v17.4s, v26.s[3]\n"
+        "fcvtl v29.4s, v29.4h\n"
+        "fmla v23.4s, v20.4s, v10.4s\n"
+        "movi v20.4s, #0x0\n"
+        "movi v10.4s, #0x0\n"
+        "fmla v16.4s, v2.4s, v26.4s\n"
+        "movi v26.4s, #0x0\n"
+        "movi v2.4s, #0x0\n"
+        ".inst 0x4f98e194  // sdot v20.4s, v12.16b, v24.4b[0]\n"
+        ".inst 0x4fb8e18a  // sdot v10.4s, v12.16b, v24.4b[1]\n"
+        ".inst 0x4f98e99a  // sdot v26.4s, v12.16b, v24.4b[2]\n"
+        ".inst 0x4fb8e982  // sdot v2.4s, v12.16b, v24.4b[3]\n"
+        "ldr q24, [x22, #0x20]\n"
+        ".inst 0x4f89e3f4  // sdot v20.4s, v31.16b, v9.4b[0]\n"
+        ".inst 0x4fa9e3ea  // sdot v10.4s, v31.16b, v9.4b[1]\n"
+        ".inst 0x4f89ebfa  // sdot v26.4s, v31.16b, v9.4b[2]\n"
+        ".inst 0x4fa9ebe2  // sdot v2.4s, v31.16b, v9.4b[3]\n"
+        "ldr q9, [x22, #0x30]\n"
+        ".inst 0x4f98e0d4  // sdot v20.4s, v6.16b, v24.4b[0]\n"
+        ".inst 0x4fb8e0ca  // sdot v10.4s, v6.16b, v24.4b[1]\n"
+        ".inst 0x4f98e8da  // sdot v26.4s, v6.16b, v24.4b[2]\n"
+        ".inst 0x4fb8e8c2  // sdot v2.4s, v6.16b, v24.4b[3]\n"
+        "ldr q24, [x22, #0x40]\n"
+        ".inst 0x4f89e394  // sdot v20.4s, v28.16b, v9.4b[0]\n"
+        ".inst 0x4fa9e38a  // sdot v10.4s, v28.16b, v9.4b[1]\n"
+        ".inst 0x4f89eb9a  // sdot v26.4s, v28.16b, v9.4b[2]\n"
+        ".inst 0x4fa9eb82  // sdot v2.4s, v28.16b, v9.4b[3]\n"
+        "ldr q9, [x22, #0x50]\n"
+        ".inst 0x4f98e074  // sdot v20.4s, v3.16b, v24.4b[0]\n"
+        ".inst 0x4fb8e06a  // sdot v10.4s, v3.16b, v24.4b[1]\n"
+        ".inst 0x4f98e87a  // sdot v26.4s, v3.16b, v24.4b[2]\n"
+        ".inst 0x4fb8e862  // sdot v2.4s, v3.16b, v24.4b[3]\n"
+        "ldr q24, [x22, #0x60]\n"
+        ".inst 0x4f89e2d4  // sdot v20.4s, v22.16b, v9.4b[0]\n"
+        ".inst 0x4fa9e2ca  // sdot v10.4s, v22.16b, v9.4b[1]\n"
+        ".inst 0x4f89eada  // sdot v26.4s, v22.16b, v9.4b[2]\n"
+        ".inst 0x4fa9eac2  // sdot v2.4s, v22.16b, v9.4b[3]\n"
+        "ldr q9, [x22, #0x70]\n"
+        "add x22, x22, #0x88\n"
+        ".inst 0x4f98e374  // sdot v20.4s, v27.16b, v24.4b[0]\n"
+        ".inst 0x4fb8e36a  // sdot v10.4s, v27.16b, v24.4b[1]\n"
+        ".inst 0x4f98eb7a  // sdot v26.4s, v27.16b, v24.4b[2]\n"
+        ".inst 0x4fb8eb62  // sdot v2.4s, v27.16b, v24.4b[3]\n"
+        "ldr q24, [x21, #0x0]\n"
+        ".inst 0x4f89e3d4  // sdot v20.4s, v30.16b, v9.4b[0]\n"
+        ".inst 0x4fa9e3ca  // sdot v10.4s, v30.16b, v9.4b[1]\n"
+        ".inst 0x4f89ebda  // sdot v26.4s, v30.16b, v9.4b[2]\n"
+        ".inst 0x4fa9ebc2  // sdot v2.4s, v30.16b, v9.4b[3]\n"
+        "fmul v9.4s, v17.4s, v29.s[0]\n"
+        "scvtf v20.4s, v20.4s, #0x4\n"
+        "scvtf v10.4s, v10.4s, #0x4\n"
+        "scvtf v26.4s, v26.4s, #0x4\n"
+        "scvtf v2.4s, v2.4s, #0x4\n"
+        "fmla v25.4s, v20.4s, v9.4s\n"
+        "ldr q9, [x21, #0x10]\n"
+        "fmul v20.4s, v17.4s, v29.s[1]\n"
+        "fmla v7.4s, v10.4s, v20.4s\n"
+        "ldr d20, [x21, #-0x8]\n"
+        "fmul v10.4s, v17.4s, v29.s[2]\n"
+        "fmul v29.4s, v17.4s, v29.s[3]\n"
+        "fcvtl v20.4s, v20.4h\n"
+        "fmla v0.4s, v26.4s, v10.4s\n"
+        "movi v26.4s, #0x0\n"
+        "movi v10.4s, #0x0\n"
+        "fmla v4.4s, v2.4s, v29.4s\n"
+        "movi v2.4s, #0x0\n"
+        "movi v29.4s, #0x0\n"
+        ".inst 0x4f98e19a  // sdot v26.4s, v12.16b, v24.4b[0]\n"
+        ".inst 0x4fb8e18a  // sdot v10.4s, v12.16b, v24.4b[1]\n"
+        ".inst 0x4f98e982  // sdot v2.4s, v12.16b, v24.4b[2]\n"
+        ".inst 0x4fb8e99d  // sdot v29.4s, v12.16b, v24.4b[3]\n"
+        "ldr q12, [x21, #0x20]\n"
+        "fmul v24.4s, v17.4s, v20.s[0]\n"
+        ".inst 0x4f89e3fa  // sdot v26.4s, v31.16b, v9.4b[0]\n"
+        ".inst 0x4fa9e3ea  // sdot v10.4s, v31.16b, v9.4b[1]\n"
+        ".inst 0x4f89ebe2  // sdot v2.4s, v31.16b, v9.4b[2]\n"
+        ".inst 0x4fa9ebfd  // sdot v29.4s, v31.16b, v9.4b[3]\n"
+        "ldr q9, [x21, #0x30]\n"
+        "fmul v31.4s, v17.4s, v20.s[1]\n"
+        ".inst 0x4f8ce0da  // sdot v26.4s, v6.16b, v12.4b[0]\n"
+        ".inst 0x4face0ca  // sdot v10.4s, v6.16b, v12.4b[1]\n"
+        ".inst 0x4f8ce8c2  // sdot v2.4s, v6.16b, v12.4b[2]\n"
+        ".inst 0x4face8dd  // sdot v29.4s, v6.16b, v12.4b[3]\n"
+        "ldr q12, [x21, #0x40]\n"
+        "fmul v6.4s, v17.4s, v20.s[2]\n"
+        "fmul v20.4s, v17.4s, v20.s[3]\n"
+        ".inst 0x4f89e39a  // sdot v26.4s, v28.16b, v9.4b[0]\n"
+        ".inst 0x4fa9e38a  // sdot v10.4s, v28.16b, v9.4b[1]\n"
+        ".inst 0x4f89eb82  // sdot v2.4s, v28.16b, v9.4b[2]\n"
+        ".inst 0x4fa9eb9d  // sdot v29.4s, v28.16b, v9.4b[3]\n"
+        "ldr q9, [x21, #0x50]\n"
+        ".inst 0x4f8ce07a  // sdot v26.4s, v3.16b, v12.4b[0]\n"
+        ".inst 0x4face06a  // sdot v10.4s, v3.16b, v12.4b[1]\n"
+        ".inst 0x4f8ce862  // sdot v2.4s, v3.16b, v12.4b[2]\n"
+        ".inst 0x4face87d  // sdot v29.4s, v3.16b, v12.4b[3]\n"
+        "ldr q12, [x21, #0x60]\n"
+        ".inst 0x4f89e2da  // sdot v26.4s, v22.16b, v9.4b[0]\n"
+        ".inst 0x4fa9e2ca  // sdot v10.4s, v22.16b, v9.4b[1]\n"
+        ".inst 0x4f89eac2  // sdot v2.4s, v22.16b, v9.4b[2]\n"
+        ".inst 0x4fa9eadd  // sdot v29.4s, v22.16b, v9.4b[3]\n"
+        "ldr q17, [x21, #0x70]\n"
+        "add x21, x21, #0x88\n"
+        ".inst 0x4f8ce37a  // sdot v26.4s, v27.16b, v12.4b[0]\n"
+        ".inst 0x4face36a  // sdot v10.4s, v27.16b, v12.4b[1]\n"
+        ".inst 0x4f8ceb62  // sdot v2.4s, v27.16b, v12.4b[2]\n"
+        ".inst 0x4faceb7d  // sdot v29.4s, v27.16b, v12.4b[3]\n"
+        ".inst 0x4f91e3da  // sdot v26.4s, v30.16b, v17.4b[0]\n"
+        ".inst 0x4fb1e3ca  // sdot v10.4s, v30.16b, v17.4b[1]\n"
+        ".inst 0x4f91ebc2  // sdot v2.4s, v30.16b, v17.4b[2]\n"
+        ".inst 0x4fb1ebdd  // sdot v29.4s, v30.16b, v17.4b[3]\n"
+        "scvtf v26.4s, v26.4s, #0x4\n"
+        "scvtf v10.4s, v10.4s, #0x4\n"
+        "fmla v5.4s, v26.4s, v24.4s\n"
+        "scvtf v2.4s, v2.4s, #0x4\n"
+        "scvtf v29.4s, v29.4s, #0x4\n"
+        "fmla v21.4s, v10.4s, v31.4s\n"
+        "fmla v8.4s, v2.4s, v6.4s\n"
+        "fmla v1.4s, v29.4s, v20.4s\n"
+        "bgt 3b\n"
+        "mov x20, %x[res_ptr]\n"
+        "subs x27, x27, #0x4\n"
+        "add %x[res_ptr], %x[res_ptr], #0x10\n"
+        "str q15, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q19, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q18, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q14, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q11, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q13, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q23, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q16, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q25, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q7, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q0, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q4, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q5, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q21, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q8, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q1, [x20, #0x0]\n"
+        "bne 2b\n"
+        "mov x20, #0x4\n"
+        "sub x10, x10, #0x10\n"
+        "cmp x10, #0x10\n"
+        "mov %x[res_ptr], x26\n"
+        "madd %x[a_ptr], x20, x9, %x[a_ptr]\n"
+        "bge 1b\n"
+        "4:"  // Row loop skip
+        "cbz x10, 9f\n"
+        "5:"  // Row tail: Row loop
+        "add x24, %x[b_ptr], #0x8\n"
+        "mov x23, %x[nc]\n"
+        "add x22, %x[res_ptr], %x[res_stride], LSL #2\n"
+        "6:"  // Row tail: Column loop
+        "movi v15.16b, #0x0\n"
+        "movi v19.16b, #0x0\n"
+        "add x25, %x[a_ptr], #0x8\n"
+        "mov x21, %x[nb]\n"
+        "movi v18.16b, #0x0\n"
+        "movi v14.16b, #0x0\n"
+        "7:"  // Row tail: Block loop
+        "ldr q7, [x24, #0x0]\n"
+        "ldr q5, [x25, #0x0]\n"
+        "movi v9.16b, #0x4\n"
+        "movi v4.4s, #0x0\n"
+        "ldr q3, [x24, #0x10]\n"
+        "ldr q2, [x25, #0x10]\n"
+        "movi v1.4s, #0x0\n"
+        "movi v0.4s, #0x0\n"
+        "ldr q13, [x24, #0x20]\n"
+        "ldr q31, [x25, #0x20]\n"
+        "movi v30.4s, #0x0\n"
+        "movi v29.16b, #0xf0\n"
+        "ldr q28, [x24, #0x30]\n"
+        "ldr q27, [x25, #0x30]\n"
+        "sshl v20.16b, v7.16b, v9.16b\n"
+        "sub x20, x24, #0x8\n"
+        "ldr q26, [x25, #0x40]\n"
+        "ldr q25, [x25, #0x50]\n"
+        "sshl v17.16b, v3.16b, v9.16b\n"
+        "and v7.16b, v7.16b, v29.16b\n"
+        "ldr q24, [x25, #0x60]\n"
+        "ldr q16, [x25, #0x70]\n"
+        "sshl v22.16b, v13.16b, v9.16b\n"
+        "and v3.16b, v3.16b, v29.16b\n"
+        "ldr d21, [x20, #0x0]\n"
+        "ldr d12, [x25, #-0x8]\n"
+        ".inst 0x4f85e284  // sdot v4.4s, v20.16b, v5.4b[0]\n"
+        ".inst 0x4fa5e281  // sdot v1.4s, v20.16b, v5.4b[1]\n"
+        ".inst 0x4f85ea80  // sdot v0.4s, v20.16b, v5.4b[2]\n"
+        ".inst 0x4fa5ea9e  // sdot v30.4s, v20.16b, v5.4b[3]\n"
+        "sshl v9.16b, v28.16b, v9.16b\n"
+        "subs x21, x21, #0x1\n"
+        "and v13.16b, v13.16b, v29.16b\n"
+        "and v28.16b, v28.16b, v29.16b\n"
+        "add x25, x25, #0x88\n"
+        "add x24, x24, #0x48\n"
+        "fcvtl v21.4s, v21.4h\n"
+        "fcvtl v12.4s, v12.4h\n"
+        ".inst 0x4f82e224  // sdot v4.4s, v17.16b, v2.4b[0]\n"
+        ".inst 0x4fa2e221  // sdot v1.4s, v17.16b, v2.4b[1]\n"
+        ".inst 0x4f82ea20  // sdot v0.4s, v17.16b, v2.4b[2]\n"
+        ".inst 0x4fa2ea3e  // sdot v30.4s, v17.16b, v2.4b[3]\n"
+        "fmul v11.4s, v21.4s, v12.s[0]\n"
+        "fmul v23.4s, v21.4s, v12.s[1]\n"
+        "fmul v17.4s, v21.4s, v12.s[2]\n"
+        ".inst 0x4f9fe2c4  // sdot v4.4s, v22.16b, v31.4b[0]\n"
+        "fmul v6.4s, v21.4s, v12.s[3]\n"
+        ".inst 0x4fbfe2c1  // sdot v1.4s, v22.16b, v31.4b[1]\n"
+        ".inst 0x4f9feac0  // sdot v0.4s, v22.16b, v31.4b[2]\n"
+        ".inst 0x4fbfeade  // sdot v30.4s, v22.16b, v31.4b[3]\n"
+        ".inst 0x4f9be124  // sdot v4.4s, v9.16b, v27.4b[0]\n"
+        ".inst 0x4fbbe121  // sdot v1.4s, v9.16b, v27.4b[1]\n"
+        ".inst 0x4f9be920  // sdot v0.4s, v9.16b, v27.4b[2]\n"
+        ".inst 0x4fbbe93e  // sdot v30.4s, v9.16b, v27.4b[3]\n"
+        ".inst 0x4f9ae0e4  // sdot v4.4s, v7.16b, v26.4b[0]\n"
+        ".inst 0x4fbae0e1  // sdot v1.4s, v7.16b, v26.4b[1]\n"
+        ".inst 0x4f9ae8e0  // sdot v0.4s, v7.16b, v26.4b[2]\n"
+        ".inst 0x4fbae8fe  // sdot v30.4s, v7.16b, v26.4b[3]\n"
+        ".inst 0x4f99e064  // sdot v4.4s, v3.16b, v25.4b[0]\n"
+        ".inst 0x4fb9e061  // sdot v1.4s, v3.16b, v25.4b[1]\n"
+        ".inst 0x4f99e860  // sdot v0.4s, v3.16b, v25.4b[2]\n"
+        ".inst 0x4fb9e87e  // sdot v30.4s, v3.16b, v25.4b[3]\n"
+        ".inst 0x4f98e1a4  // sdot v4.4s, v13.16b, v24.4b[0]\n"
+        ".inst 0x4fb8e1a1  // sdot v1.4s, v13.16b, v24.4b[1]\n"
+        ".inst 0x4f98e9a0  // sdot v0.4s, v13.16b, v24.4b[2]\n"
+        ".inst 0x4fb8e9be  // sdot v30.4s, v13.16b, v24.4b[3]\n"
+        ".inst 0x4f90e384  // sdot v4.4s, v28.16b, v16.4b[0]\n"
+        ".inst 0x4fb0e381  // sdot v1.4s, v28.16b, v16.4b[1]\n"
+        ".inst 0x4f90eb80  // sdot v0.4s, v28.16b, v16.4b[2]\n"
+        ".inst 0x4fb0eb9e  // sdot v30.4s, v28.16b, v16.4b[3]\n"
+        "scvtf v4.4s, v4.4s, #0x4\n"
+        "scvtf v1.4s, v1.4s, #0x4\n"
+        "scvtf v0.4s, v0.4s, #0x4\n"
+        "fmla v15.4s, v4.4s, v11.4s\n"
+        "scvtf v30.4s, v30.4s, #0x4\n"
+        "fmla v19.4s, v1.4s, v23.4s\n"
+        "fmla v18.4s, v0.4s, v17.4s\n"
+        "fmla v14.4s, v30.4s, v6.4s\n"
+        "bgt 7b\n"
+        "mov x20, %x[res_ptr]\n"
+        "cmp x10, #0x1\n"
+        "str q15, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "ble 8f\n"
+        "cmp x10, #0x2\n"
+        "str q19, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "ble 8f\n"
+        "cmp x10, #0x3\n"
+        "str q18, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "ble 8f\n"
+        "str q14, [x20, #0x0]\n"
+        "8:"  // Row tail: Accumulator store skip
+        "subs x23, x23, #0x4\n"
+        "add %x[res_ptr], %x[res_ptr], #0x10\n"
+        "bne 6b\n"
+        "subs x10, x10, #0x4\n"
+        "add %x[a_ptr], %x[a_ptr], x9\n"
+        "mov %x[res_ptr], x22\n"
+        "bgt 5b\n"
+        "9:"  // Row tail: Row loop skip
+        : [a_ptr] "+&r" (a_ptr), [res_ptr] "+&r" (res_ptr)
+        : [b_ptr] "r" (b_ptr), [nr] "r" (nr), [nb] "r" (nb), [res_stride] "r" (res_stride), [nc] "r" (nc)
+        : "cc", "memory", "v0", "v1", "v2", "v3", "v4", "v5", "v6", "v7", "v8", "v9", "v10", "v11", "v12", "v13", "v14", "v15", "v16", "v17", "v18", "v19", "v20", "v21", "v22", "v23", "v24", "v25", "v26", "v27", "v28", "v29", "v30", "v31", "x9", "x10", "x20", "x21", "x22", "x23", "x24", "x25", "x26", "x27", "x28"
+    );
+#else
+    float sumf[4][4];
+    int sumi;
+
+    for (int y = 0; y < nr / 4; y++) {
+        const block_q8_0x4 * a_ptr = (const block_q8_0x4 *) vy + (y * nb);
+        for (int x = 0; x < nc / ncols_interleaved; x++) {
+            const block_q4_0x4 * b_ptr = (const block_q4_0x4 *) vx + (x * nb);
+            for (int m = 0; m < 4; m++) {
+                for (int j = 0; j < ncols_interleaved; j++) sumf[m][j] = 0.0;
+            }
+            for (int l = 0; l < nb; l++) {
+                for (int k = 0; k < (qk / (2 * blocklen)); k++) {
+                    for (int m = 0; m < 4; m++) {
+                        for (int j = 0; j < ncols_interleaved; j++) {
+                            sumi = 0;
+                            for (int i = 0; i < blocklen; ++i) {
+                                const int v0 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] << 4);
+                                const int v1 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] & 0xF0);
+                                sumi += ((v0 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i]) +
+                                         (v1 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i + qk / 2 * 4])) >> 4;
+                            }
+                            sumf[m][j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d[m]);
+                        }
+                    }
+                }
+            }
+            for (int m = 0; m < 4; m++) {
+                for (int j = 0; j < ncols_interleaved; j++)
+                    s[(y * 4 + m) * bs + x * ncols_interleaved + j] = sumf[m][j];
+            }
+        }
+    }
+#endif
+}
+
+void ggml_gemm_q4_0_4x8_q8_0(int n, float * restrict s, size_t bs, const void * restrict vx, const void * restrict vy, int nr, int nc) {
+    const int qk = QK8_0;
+    const int nb = n / qk;
+    const int ncols_interleaved = 4;
+    const int blocklen = 8;
+
+    assert (n % qk == 0);
+    assert (nr % 4 == 0);
+    assert (nc % ncols_interleaved == 0);
+
+    UNUSED(s);
+    UNUSED(bs);
+    UNUSED(vx);
+    UNUSED(vy);
+    UNUSED(nr);
+    UNUSED(nc);
+    UNUSED(nb);
+    UNUSED(ncols_interleaved);
+    UNUSED(blocklen);
+
+#if defined(__ARM_FEATURE_SVE) && defined(__ARM_FEATURE_MATMUL_INT8)
+    if (svcntw() == 8) {
+        GGML_ASSERT(!(ggml_cpu_has_sve() && (svcntw() == 8)) &&
+                    "__ARM_FEATURE_SVE defined, use the Q4_0_8_8 quantization format for optimal performance");
+    }
+#endif
+#if defined(__ARM_NEON) && defined(__ARM_FEATURE_MATMUL_INT8)
+    const void * b_ptr = vx;
+    const void * a_ptr = vy;
+    float * res_ptr = s;
+    size_t res_stride = bs * sizeof(float);
+
+    __asm__ __volatile__(
+        "mov x10, %x[nr]\n"
+        "mov x9, #0x88\n"
+        "cmp x10, #0x10\n"
+        "mul x9, %x[nb], x9\n"
+        "blt 4f\n"
+        "1:"  // Row loop
+        "add x28, %x[b_ptr], #0x8\n"
+        "mov x27, %x[nc]\n"
+        "add x26, %x[res_ptr], %x[res_stride], LSL #4\n"
+        "2:"  // Column loop
+        "add x25, %x[a_ptr], #0x8\n"
+        "movi v2.16b, #0x0\n"
+        "movi v10.16b, #0x0\n"
+        "mov x24, %x[nb]\n"
+        "add x23, x25, x9\n"
+        "movi v12.16b, #0x0\n"
+        "movi v28.16b, #0x0\n"
+        "add x22, x23, x9\n"
+        "movi v11.16b, #0x0\n"
+        "movi v13.16b, #0x0\n"
+        "add x21, x22, x9\n"
+        "movi v22.16b, #0x0\n"
+        "movi v23.16b, #0x0\n"
+        "movi v25.16b, #0x0\n"
+        "movi v5.16b, #0x0\n"
+        "movi v7.16b, #0x0\n"
+        "movi v4.16b, #0x0\n"
+        "movi v6.16b, #0x0\n"
+        "movi v30.16b, #0x0\n"
+        "movi v24.16b, #0x0\n"
+        "movi v14.16b, #0x0\n"
+        "3:"  // Block loop
+        "ldr q21, [x28, #0x0]\n"
+        "ldr q16, [x28, #0x10]\n"
+        "movi v1.16b, #0x4\n"
+        "movi v19.4s, #0x0\n"
+        "ldr q27, [x25, #0x0]\n"
+        "ldr q15, [x25, #0x10]\n"
+        "movi v26.4s, #0x0\n"
+        "movi v18.4s, #0x0\n"
+        "ldr q29, [x28, #0x20]\n"
+        "ldr q3, [x28, #0x30]\n"
+        "movi v17.4s, #0x0\n"
+        "movi v0.16b, #0xf0\n"
+        "ldr d20, [x25, #-0x8]\n"
+        "ldr d9, [x23, #-0x8]\n"
+        "sshl v8.16b, v21.16b, v1.16b\n"
+        "sshl v31.16b, v16.16b, v1.16b\n"
+        "and v21.16b, v21.16b, v0.16b\n"
+        "and v16.16b, v16.16b, v0.16b\n"
+        "sub x20, x28, #0x8\n"
+        "subs x24, x24, #0x1\n"
+        "add x28, x28, #0x48\n"
+        ".inst 0x4e88a773  // smmla v19.4s, v27.16b, v8.16b\n"
+        ".inst 0x4e9fa77a  // smmla v26.4s, v27.16b, v31.16b\n"
+        "ldr q27, [x25, #0x20]\n"
+        ".inst 0x4e88a5f2  // smmla v18.4s, v15.16b, v8.16b\n"
+        ".inst 0x4e9fa5f1  // smmla v17.4s, v15.16b, v31.16b\n"
+        "sshl v15.16b, v29.16b, v1.16b\n"
+        "sshl v1.16b, v3.16b, v1.16b\n"
+        "and v29.16b, v29.16b, v0.16b\n"
+        "and v3.16b, v3.16b, v0.16b\n"
+        "ldr q0, [x25, #0x30]\n"
+        "fcvtl v20.4s, v20.4h\n"
+        ".inst 0x4e8fa773  // smmla v19.4s, v27.16b, v15.16b\n"
+        "fcvtl v9.4s, v9.4h\n"
+        ".inst 0x4e81a77a  // smmla v26.4s, v27.16b, v1.16b\n"
+        "ldr q27, [x25, #0x40]\n"
+        ".inst 0x4e8fa412  // smmla v18.4s, v0.16b, v15.16b\n"
+        ".inst 0x4e81a411  // smmla v17.4s, v0.16b, v1.16b\n"
+        "ldr q0, [x25, #0x50]\n"
+        ".inst 0x4e95a773  // smmla v19.4s, v27.16b, v21.16b\n"
+        ".inst 0x4e90a77a  // smmla v26.4s, v27.16b, v16.16b\n"
+        "ldr q27, [x25, #0x60]\n"
+        ".inst 0x4e95a412  // smmla v18.4s, v0.16b, v21.16b\n"
+        ".inst 0x4e90a411  // smmla v17.4s, v0.16b, v16.16b\n"
+        "ldr q0, [x25, #0x70]\n"
+        "add x25, x25, #0x88\n"
+        ".inst 0x4e9da773  // smmla v19.4s, v27.16b, v29.16b\n"
+        ".inst 0x4e83a77a  // smmla v26.4s, v27.16b, v3.16b\n"
+        "ldr d27, [x20, #0x0]\n"
+        ".inst 0x4e9da412  // smmla v18.4s, v0.16b, v29.16b\n"
+        ".inst 0x4e83a411  // smmla v17.4s, v0.16b, v3.16b\n"
+        "fcvtl v27.4s, v27.4h\n"
+        "uzp1 v0.2d, v19.2d, v26.2d\n"
+        "uzp2 v26.2d, v19.2d, v26.2d\n"
+        "fmul v19.4s, v27.4s, v20.s[0]\n"
+        "scvtf v0.4s, v0.4s, #0x4\n"
+        "scvtf v26.4s, v26.4s, #0x4\n"
+        "fmla v2.4s, v0.4s, v19.4s\n"
+        "ldr q19, [x23, #0x0]\n"
+        "uzp1 v0.2d, v18.2d, v17.2d\n"
+        "uzp2 v18.2d, v18.2d, v17.2d\n"
+        "fmul v17.4s, v27.4s, v20.s[1]\n"
+        "scvtf v0.4s, v0.4s, #0x4\n"
+        "scvtf v18.4s, v18.4s, #0x4\n"
+        "fmla v10.4s, v26.4s, v17.4s\n"
+        "ldr q17, [x23, #0x10]\n"
+        "fmul v26.4s, v27.4s, v20.s[2]\n"
+        "fmul v20.4s, v27.4s, v20.s[3]\n"
+        "fmla v12.4s, v0.4s, v26.4s\n"
+        "ldr d0, [x22, #-0x8]\n"
+        "ldr d26, [x21, #-0x8]\n"
+        "fcvtl v0.4s, v0.4h\n"
+        "fmla v28.4s, v18.4s, v20.4s\n"
+        "movi v20.4s, #0x0\n"
+        "movi v18.4s, #0x0\n"
+        ".inst 0x4e88a674  // smmla v20.4s, v19.16b, v8.16b\n"
+        ".inst 0x4e9fa672  // smmla v18.4s, v19.16b, v31.16b\n"
+        "ldr q19, [x23, #0x20]\n"
+        "fcvtl v26.4s, v26.4h\n"
+        ".inst 0x4e8fa674  // smmla v20.4s, v19.16b, v15.16b\n"
+        ".inst 0x4e81a672  // smmla v18.4s, v19.16b, v1.16b\n"
+        "ldr q19, [x23, #0x40]\n"
+        ".inst 0x4e95a674  // smmla v20.4s, v19.16b, v21.16b\n"
+        ".inst 0x4e90a672  // smmla v18.4s, v19.16b, v16.16b\n"
+        "ldr q19, [x23, #0x60]\n"
+        ".inst 0x4e9da674  // smmla v20.4s, v19.16b, v29.16b\n"
+        ".inst 0x4e83a672  // smmla v18.4s, v19.16b, v3.16b\n"
+        "uzp1 v19.2d, v20.2d, v18.2d\n"
+        "scvtf v19.4s, v19.4s, #0x4\n"
+        "uzp2 v20.2d, v20.2d, v18.2d\n"
+        "fmul v18.4s, v27.4s, v9.s[0]\n"
+        "scvtf v20.4s, v20.4s, #0x4\n"
+        "fmla v11.4s, v19.4s, v18.4s\n"
+        "ldr q18, [x22, #0x0]\n"
+        "fmul v19.4s, v27.4s, v9.s[1]\n"
+        "fmla v13.4s, v20.4s, v19.4s\n"
+        "movi v19.4s, #0x0\n"
+        "movi v20.4s, #0x0\n"
+        ".inst 0x4e88a633  // smmla v19.4s, v17.16b, v8.16b\n"
+        ".inst 0x4e9fa634  // smmla v20.4s, v17.16b, v31.16b\n"
+        "ldr q17, [x23, #0x30]\n"
+        ".inst 0x4e8fa633  // smmla v19.4s, v17.16b, v15.16b\n"
+        ".inst 0x4e81a634  // smmla v20.4s, v17.16b, v1.16b\n"
+        "ldr q17, [x23, #0x50]\n"
+        ".inst 0x4e95a633  // smmla v19.4s, v17.16b, v21.16b\n"
+        ".inst 0x4e90a634  // smmla v20.4s, v17.16b, v16.16b\n"
+        "ldr q17, [x23, #0x70]\n"
+        "add x23, x23, #0x88\n"
+        ".inst 0x4e9da633  // smmla v19.4s, v17.16b, v29.16b\n"
+        ".inst 0x4e83a634  // smmla v20.4s, v17.16b, v3.16b\n"
+        "uzp1 v17.2d, v19.2d, v20.2d\n"
+        "scvtf v17.4s, v17.4s, #0x4\n"
+        "uzp2 v20.2d, v19.2d, v20.2d\n"
+        "fmul v19.4s, v27.4s, v9.s[2]\n"
+        "fmul v9.4s, v27.4s, v9.s[3]\n"
+        "scvtf v20.4s, v20.4s, #0x4\n"
+        "fmla v22.4s, v17.4s, v19.4s\n"
+        "ldr q17, [x22, #0x10]\n"
+        "movi v19.4s, #0x0\n"
+        ".inst 0x4e88a653  // smmla v19.4s, v18.16b, v8.16b\n"
+        "fmla v23.4s, v20.4s, v9.4s\n"
+        "movi v20.4s, #0x0\n"
+        "movi v9.4s, #0x0\n"
+        ".inst 0x4e9fa654  // smmla v20.4s, v18.16b, v31.16b\n"
+        "ldr q18, [x22, #0x20]\n"
+        ".inst 0x4e88a629  // smmla v9.4s, v17.16b, v8.16b\n"
+        ".inst 0x4e8fa653  // smmla v19.4s, v18.16b, v15.16b\n"
+        ".inst 0x4e81a654  // smmla v20.4s, v18.16b, v1.16b\n"
+        "ldr q18, [x22, #0x40]\n"
+        ".inst 0x4e95a653  // smmla v19.4s, v18.16b, v21.16b\n"
+        ".inst 0x4e90a654  // smmla v20.4s, v18.16b, v16.16b\n"
+        "ldr q18, [x22, #0x60]\n"
+        ".inst 0x4e9da653  // smmla v19.4s, v18.16b, v29.16b\n"
+        ".inst 0x4e83a654  // smmla v20.4s, v18.16b, v3.16b\n"
+        "movi v18.4s, #0x0\n"
+        ".inst 0x4e9fa632  // smmla v18.4s, v17.16b, v31.16b\n"
+        "ldr q17, [x22, #0x30]\n"
+        ".inst 0x4e8fa629  // smmla v9.4s, v17.16b, v15.16b\n"
+        ".inst 0x4e81a632  // smmla v18.4s, v17.16b, v1.16b\n"
+        "ldr q17, [x22, #0x50]\n"
+        ".inst 0x4e95a629  // smmla v9.4s, v17.16b, v21.16b\n"
+        ".inst 0x4e90a632  // smmla v18.4s, v17.16b, v16.16b\n"
+        "ldr q17, [x22, #0x70]\n"
+        "add x22, x22, #0x88\n"
+        ".inst 0x4e9da629  // smmla v9.4s, v17.16b, v29.16b\n"
+        ".inst 0x4e83a632  // smmla v18.4s, v17.16b, v3.16b\n"
+        "uzp1 v17.2d, v19.2d, v20.2d\n"
+        "uzp2 v20.2d, v19.2d, v20.2d\n"
+        "fmul v19.4s, v27.4s, v0.s[0]\n"
+        "scvtf v17.4s, v17.4s, #0x4\n"
+        "scvtf v20.4s, v20.4s, #0x4\n"
+        "fmla v25.4s, v17.4s, v19.4s\n"
+        "ldr q19, [x21, #0x0]\n"
+        "fmul v17.4s, v27.4s, v0.s[1]\n"
+        "fmla v5.4s, v20.4s, v17.4s\n"
+        "ldr q17, [x21, #0x10]\n"
+        "uzp1 v20.2d, v9.2d, v18.2d\n"
+        "uzp2 v9.2d, v9.2d, v18.2d\n"
+        "fmul v18.4s, v27.4s, v0.s[2]\n"
+        "fmul v0.4s, v27.4s, v0.s[3]\n"
+        "scvtf v20.4s, v20.4s, #0x4\n"
+        "scvtf v9.4s, v9.4s, #0x4\n"
+        "fmla v7.4s, v20.4s, v18.4s\n"
+        "movi v20.4s, #0x0\n"
+        "movi v18.4s, #0x0\n"
+        ".inst 0x4e88a674  // smmla v20.4s, v19.16b, v8.16b\n"
+        ".inst 0x4e9fa672  // smmla v18.4s, v19.16b, v31.16b\n"
+        "ldr q19, [x21, #0x20]\n"
+        "fmla v4.4s, v9.4s, v0.4s\n"
+        "movi v9.4s, #0x0\n"
+        "movi v0.4s, #0x0\n"
+        ".inst 0x4e88a629  // smmla v9.4s, v17.16b, v8.16b\n"
+        "fmul v8.4s, v27.4s, v26.s[0]\n"
+        ".inst 0x4e9fa620  // smmla v0.4s, v17.16b, v31.16b\n"
+        "ldr q17, [x21, #0x30]\n"
+        ".inst 0x4e8fa674  // smmla v20.4s, v19.16b, v15.16b\n"
+        "fmul v31.4s, v27.4s, v26.s[1]\n"
+        ".inst 0x4e81a672  // smmla v18.4s, v19.16b, v1.16b\n"
+        "ldr q19, [x21, #0x40]\n"
+        ".inst 0x4e8fa629  // smmla v9.4s, v17.16b, v15.16b\n"
+        "fmul v15.4s, v27.4s, v26.s[2]\n"
+        "fmul v27.4s, v27.4s, v26.s[3]\n"
+        ".inst 0x4e81a620  // smmla v0.4s, v17.16b, v1.16b\n"
+        "ldr q1, [x21, #0x50]\n"
+        ".inst 0x4e95a674  // smmla v20.4s, v19.16b, v21.16b\n"
+        ".inst 0x4e90a672  // smmla v18.4s, v19.16b, v16.16b\n"
+        "ldr q26, [x21, #0x60]\n"
+        ".inst 0x4e95a429  // smmla v9.4s, v1.16b, v21.16b\n"
+        ".inst 0x4e90a420  // smmla v0.4s, v1.16b, v16.16b\n"
+        "ldr q21, [x21, #0x70]\n"
+        "add x21, x21, #0x88\n"
+        ".inst 0x4e9da754  // smmla v20.4s, v26.16b, v29.16b\n"
+        ".inst 0x4e83a752  // smmla v18.4s, v26.16b, v3.16b\n"
+        ".inst 0x4e9da6a9  // smmla v9.4s, v21.16b, v29.16b\n"
+        ".inst 0x4e83a6a0  // smmla v0.4s, v21.16b, v3.16b\n"
+        "uzp1 v29.2d, v20.2d, v18.2d\n"
+        "uzp2 v21.2d, v20.2d, v18.2d\n"
+        "scvtf v29.4s, v29.4s, #0x4\n"
+        "uzp1 v18.2d, v9.2d, v0.2d\n"
+        "uzp2 v16.2d, v9.2d, v0.2d\n"
+        "scvtf v21.4s, v21.4s, #0x4\n"
+        "fmla v6.4s, v29.4s, v8.4s\n"
+        "scvtf v18.4s, v18.4s, #0x4\n"
+        "scvtf v16.4s, v16.4s, #0x4\n"
+        "fmla v30.4s, v21.4s, v31.4s\n"
+        "fmla v24.4s, v18.4s, v15.4s\n"
+        "fmla v14.4s, v16.4s, v27.4s\n"
+        "bgt 3b\n"
+        "mov x20, %x[res_ptr]\n"
+        "subs x27, x27, #0x4\n"
+        "add %x[res_ptr], %x[res_ptr], #0x10\n"
+        "str q2, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q10, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q12, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q28, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q11, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q13, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q22, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q23, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q25, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q5, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q7, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q4, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q6, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q30, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q24, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "str q14, [x20, #0x0]\n"
+        "bne 2b\n"
+        "mov x20, #0x4\n"
+        "sub x10, x10, #0x10\n"
+        "cmp x10, #0x10\n"
+        "mov %x[res_ptr], x26\n"
+        "madd %x[a_ptr], x20, x9, %x[a_ptr]\n"
+        "bge 1b\n"
+        "4:"  // Row loop skip
+        "cbz x10, 9f\n"
+        "5:"  // Row tail: Row loop
+        "add x24, %x[b_ptr], #0x8\n"
+        "mov x23, %x[nc]\n"
+        "add x22, %x[res_ptr], %x[res_stride], LSL #2\n"
+        "6:"  // Row tail: Column loop
+        "movi v2.16b, #0x0\n"
+        "movi v10.16b, #0x0\n"
+        "add x25, %x[a_ptr], #0x8\n"
+        "mov x21, %x[nb]\n"
+        "movi v12.16b, #0x0\n"
+        "movi v28.16b, #0x0\n"
+        "7:"  // Row tail: Block loop
+        "ldr q6, [x24, #0x0]\n"
+        "ldr q5, [x24, #0x10]\n"
+        "movi v17.16b, #0x4\n"
+        "movi v8.4s, #0x0\n"
+        "ldr q4, [x25, #0x0]\n"
+        "ldr q13, [x25, #0x10]\n"
+        "movi v27.4s, #0x0\n"
+        "movi v0.4s, #0x0\n"
+        "ldr q31, [x24, #0x20]\n"
+        "ldr q14, [x24, #0x30]\n"
+        "movi v29.4s, #0x0\n"
+        "movi v22.16b, #0xf0\n"
+        "ldr q11, [x25, #0x20]\n"
+        "ldr q23, [x25, #0x30]\n"
+        "sshl v21.16b, v6.16b, v17.16b\n"
+        "sshl v16.16b, v5.16b, v17.16b\n"
+        "ldr q20, [x25, #0x40]\n"
+        "ldr q26, [x25, #0x50]\n"
+        "and v6.16b, v6.16b, v22.16b\n"
+        "and v5.16b, v5.16b, v22.16b\n"
+        "ldr q25, [x25, #0x60]\n"
+        "ldr q3, [x25, #0x70]\n"
+        "sshl v19.16b, v31.16b, v17.16b\n"
+        "sshl v18.16b, v14.16b, v17.16b\n"
+        "ldr d17, [x25, #-0x8]\n"
+        ".inst 0x4e95a488  // smmla v8.4s, v4.16b, v21.16b\n"
+        ".inst 0x4e90a49b  // smmla v27.4s, v4.16b, v16.16b\n"
+        "and v31.16b, v31.16b, v22.16b\n"
+        ".inst 0x4e95a5a0  // smmla v0.4s, v13.16b, v21.16b\n"
+        ".inst 0x4e90a5bd  // smmla v29.4s, v13.16b, v16.16b\n"
+        "and v14.16b, v14.16b, v22.16b\n"
+        "sub x20, x24, #0x8\n"
+        "ldr d16, [x20, #0x0]\n"
+        "subs x21, x21, #0x1\n"
+        "add x25, x25, #0x88\n"
+        "fcvtl v17.4s, v17.4h\n"
+        "add x24, x24, #0x48\n"
+        ".inst 0x4e93a568  // smmla v8.4s, v11.16b, v19.16b\n"
+        ".inst 0x4e92a57b  // smmla v27.4s, v11.16b, v18.16b\n"
+        ".inst 0x4e93a6e0  // smmla v0.4s, v23.16b, v19.16b\n"
+        ".inst 0x4e92a6fd  // smmla v29.4s, v23.16b, v18.16b\n"
+        "fcvtl v16.4s, v16.4h\n"
+        ".inst 0x4e86a688  // smmla v8.4s, v20.16b, v6.16b\n"
+        ".inst 0x4e85a69b  // smmla v27.4s, v20.16b, v5.16b\n"
+        "fmul v23.4s, v16.4s, v17.s[0]\n"
+        "fmul v21.4s, v16.4s, v17.s[1]\n"
+        "fmul v1.4s, v16.4s, v17.s[2]\n"
+        "fmul v20.4s, v16.4s, v17.s[3]\n"
+        ".inst 0x4e86a740  // smmla v0.4s, v26.16b, v6.16b\n"
+        ".inst 0x4e85a75d  // smmla v29.4s, v26.16b, v5.16b\n"
+        ".inst 0x4e9fa728  // smmla v8.4s, v25.16b, v31.16b\n"
+        ".inst 0x4e8ea73b  // smmla v27.4s, v25.16b, v14.16b\n"
+        ".inst 0x4e9fa460  // smmla v0.4s, v3.16b, v31.16b\n"
+        ".inst 0x4e8ea47d  // smmla v29.4s, v3.16b, v14.16b\n"
+        "uzp1 v19.2d, v8.2d, v27.2d\n"
+        "uzp2 v18.2d, v8.2d, v27.2d\n"
+        "scvtf v19.4s, v19.4s, #0x4\n"
+        "uzp1 v17.2d, v0.2d, v29.2d\n"
+        "uzp2 v16.2d, v0.2d, v29.2d\n"
+        "scvtf v18.4s, v18.4s, #0x4\n"
+        "fmla v2.4s, v19.4s, v23.4s\n"
+        "scvtf v17.4s, v17.4s, #0x4\n"
+        "scvtf v16.4s, v16.4s, #0x4\n"
+        "fmla v10.4s, v18.4s, v21.4s\n"
+        "fmla v12.4s, v17.4s, v1.4s\n"
+        "fmla v28.4s, v16.4s, v20.4s\n"
+        "bgt 7b\n"
+        "mov x20, %x[res_ptr]\n"
+        "cmp x10, #0x1\n"
+        "str q2, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "ble 8f\n"
+        "cmp x10, #0x2\n"
+        "str q10, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "ble 8f\n"
+        "cmp x10, #0x3\n"
+        "str q12, [x20, #0x0]\n"
+        "add x20, x20, %x[res_stride]\n"
+        "ble 8f\n"
+        "str q28, [x20, #0x0]\n"
+        "8:"  // Row tail: Accumulator store skip
+        "subs x23, x23, #0x4\n"
+        "add %x[res_ptr], %x[res_ptr], #0x10\n"
+        "bne 6b\n"
+        "subs x10, x10, #0x4\n"
+        "add %x[a_ptr], %x[a_ptr], x9\n"
+        "mov %x[res_ptr], x22\n"
+        "bgt 5b\n"
+        "9:"  // Row tail: Row loop skip
+        : [a_ptr] "+&r" (a_ptr), [res_ptr] "+&r" (res_ptr)
+        : [b_ptr] "r" (b_ptr), [nr] "r" (nr), [nb] "r" (nb), [res_stride] "r" (res_stride), [nc] "r" (nc)
+        : "cc", "memory", "v0", "v1", "v2", "v3", "v4", "v5", "v6", "v7", "v8", "v9", "v10", "v11", "v12", "v13", "v14", "v15", "v16", "v17", "v18", "v19", "v20", "v21", "v22", "v23", "v24", "v25", "v26", "v27", "v28", "v29", "v30", "v31", "x9", "x10", "x20", "x21", "x22", "x23", "x24", "x25", "x26", "x27", "x28"
+    );
+#elif defined(__ARM_NEON) && defined(__aarch64__)
+    GGML_ASSERT((ggml_cpu_has_sve() || ggml_cpu_has_matmul_int8()) &&
+                "__ARM_FEATURE_SVE and __ARM_FEATURE_MATMUL_INT8 not defined, use the Q4_0_4_4 quantization format for optimal "
+                "performance");
+#else
+    float sumf[4][4];
+    int sumi;
+
+    for (int y = 0; y < nr / 4; y++) {
+        const block_q8_0x4 * a_ptr = (const block_q8_0x4 *) vy + (y * nb);
+        for (int x = 0; x < nc / ncols_interleaved; x++) {
+            const block_q4_0x4 * b_ptr = (const block_q4_0x4 *) vx + (x * nb);
+            for (int m = 0; m < 4; m++) {
+                for (int j = 0; j < ncols_interleaved; j++) sumf[m][j] = 0.0;
+            }
+            for (int l = 0; l < nb; l++) {
+                for (int k = 0; k < (qk / (2 * blocklen)); k++) {
+                    for (int m = 0; m < 4; m++) {
+                        for (int j = 0; j < ncols_interleaved; j++) {
+                            sumi = 0;
+                            for (int i = 0; i < blocklen; ++i) {
+                                const int v0 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] << 4);
+                                const int v1 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] & 0xF0);
+                                sumi += ((v0 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i]) +
+                                         (v1 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i + qk / 2 * 4])) >> 4;
+                            }
+                            sumf[m][j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d[m]);
+                        }
+                    }
+                }
+            }
+            for (int m = 0; m < 4; m++) {
+                for (int j = 0; j < ncols_interleaved; j++)
+                    s[(y * 4 + m) * bs + x * ncols_interleaved + j] = sumf[m][j];
+            }
+        }
+    }
+#endif
+}
+
+void ggml_gemm_q4_0_8x8_q8_0(int n, float * restrict s, size_t bs, const void * restrict vx, const void * restrict vy, int nr, int nc) {
+    const int qk = QK8_0;
+    const int nb = n / qk;
+    const int ncols_interleaved = 8;
+    const int blocklen = 8;
+
+    assert (n % qk == 0);
+    assert (nr % 4 == 0);
+    assert (nc % ncols_interleaved == 0);
+
+    UNUSED(s);
+    UNUSED(bs);
+    UNUSED(vx);
+    UNUSED(vy);
+    UNUSED(nr);
+    UNUSED(nc);
+    UNUSED(nb);
+    UNUSED(ncols_interleaved);
+    UNUSED(blocklen);
+
+#if defined(__ARM_FEATURE_SVE) && defined(__ARM_FEATURE_MATMUL_INT8)
+    if (svcntw() == 8) {
+        const void * b_ptr = vx;
+        const void * a_ptr = vy;
+        float * res_ptr = s;
+        size_t res_stride = bs * sizeof(float);
+
+        __asm__ __volatile__(
+            "mov x20, #0x4\n"
+            "mov x13, %x[nr]\n"
+            "mov z28.s, #-0x4\n"
+            "mov x12, #0x88\n"
+            "ptrue p1.b\n"
+            "whilelt p0.s, XZR, x20\n"
+            "cmp x13, #0x10\n"
+            "mul x12, %x[nb], x12\n"
+            "blt 4f\n"
+            "1:"  // Row loop
+            "add x11, %x[b_ptr], #0x10\n"
+            "mov x10, %x[nc]\n"
+            "add x9, %x[res_ptr], %x[res_stride], LSL #4\n"
+            "2:"  // Column loop
+            "add x28, %x[a_ptr], #0x8\n"
+            "mov z24.b, #0x0\n"
+            "mov z15.b, #0x0\n"
+            "mov x27, %x[nb]\n"
+            "add x26, x28, x12\n"
+            "mov z12.b, #0x0\n"
+            "mov z0.b, #0x0\n"
+            "add x25, x26, x12\n"
+            "mov z13.b, #0x0\n"
+            "mov z1.b, #0x0\n"
+            "add x24, x25, x12\n"
+            "mov z20.b, #0x0\n"
+            "mov z25.b, #0x0\n"
+            "mov z11.b, #0x0\n"
+            "mov z16.b, #0x0\n"
+            "mov z19.b, #0x0\n"
+            "mov z26.b, #0x0\n"
+            "mov z8.b, #0x0\n"
+            "mov z29.b, #0x0\n"
+            "mov z27.b, #0x0\n"
+            "mov z10.b, #0x0\n"
+            "3:"  // Block loop
+            "ld1b { z30.b }, p1/Z, [x11]\n"
+            "ld1b { z21.b }, p1/Z, [x11, #1, MUL VL]\n"
+            "mov z18.s, #0x0\n"
+            "mov z7.s, #0x0\n"
+            "ld1rqb { z3.b }, p1/Z, [x28]\n"
+            "ld1rqb { z5.b }, p1/Z, [x28, #16]\n"
+            "mov z9.s, #0x0\n"
+            "mov z22.s, #0x0\n"
+            "ld1b { z4.b }, p1/Z, [x11, #2, MUL VL]\n"
+            "ld1b { z17.b }, p1/Z, [x11, #3, MUL VL]\n"
+            "sub x20, x11, #0x10\n"
+            "sub x23, x28, #0x8\n"
+            "lsl z31.b, z30.b, #0x4\n"
+            "lsl z6.b, z21.b, #0x4\n"
+            "ld1h { z23.s }, p1/Z, [x20]\n"
+            "sub x22, x26, #0x8\n"
+            "and z30.b, z30.b, #0xf0\n"
+            "and z21.b, z21.b, #0xf0\n"
+            "sub x21, x25, #0x8\n"
+            "sub x20, x24, #0x8\n"
+            "lsl z14.b, z4.b, #0x4\n"
+            "lsl z2.b, z17.b, #0x4\n"
+            "subs x27, x27, #0x1\n"
+            "add x11, x11, #0x90\n"
+            ".inst 0x451f9872  // smmla z18.s, z3.b, z31.b\n"
+            ".inst 0x45069867  // smmla z7.s, z3.b, z6.b\n"
+            "ld1rqb { z3.b }, p1/Z, [x28, #32]\n"
+            "and z4.b, z4.b, #0xf0\n"
+            ".inst 0x451f98a9  // smmla z9.s, z5.b, z31.b\n"
+            ".inst 0x450698b6  // smmla z22.s, z5.b, z6.b\n"
+            "ld1rqb { z5.b }, p1/Z, [x28, #48]\n"
+            "and z17.b, z17.b, #0xf0\n"
+            "fcvt z23.s, p1/m, z23.h\n"
+            ".inst 0x450e9872  // smmla z18.s, z3.b, z14.b\n"
+            ".inst 0x45029867  // smmla z7.s, z3.b, z2.b\n"
+            "ld1rqb { z3.b }, p1/Z, [x28, #64]\n"
+            ".inst 0x450e98a9  // smmla z9.s, z5.b, z14.b\n"
+            ".inst 0x450298b6  // smmla z22.s, z5.b, z2.b\n"
+            "ld1rqb { z5.b }, p1/Z, [x28, #80]\n"
+            "fscale z23.s, p1/m, z23.s, z28.s\n"
+            ".inst 0x451e9872  // smmla z18.s, z3.b, z30.b\n"
+            ".inst 0x45159867  // smmla z7.s, z3.b, z21.b\n"
+            "ld1rqb { z3.b }, p1/Z, [x28, #96]\n"
+            ".inst 0x451e98a9  // smmla z9.s, z5.b, z30.b\n"
+            ".inst 0x451598b6  // smmla z22.s, z5.b, z21.b\n"
+            "ld1rqb { z5.b }, p1/Z, [x28, #112]\n"
+            "add x28, x28, #0x88\n"
+            ".inst 0x45049872  // smmla z18.s, z3.b, z4.b\n"
+            ".inst 0x45119867  // smmla z7.s, z3.b, z17.b\n"
+            "ld1h { z3.s }, p0/Z, [x23]\n"
+            ".inst 0x450498a9  // smmla z9.s, z5.b, z4.b\n"
+            ".inst 0x451198b6  // smmla z22.s, z5.b, z17.b\n"
+            "fcvt z3.s, p1/m, z3.h\n"
+            "uzp1 z5.d, z18.d, z7.d\n"
+            "uzp2 z18.d, z18.d, z7.d\n"
+            "mov z3.q, z3.q[0]\n"
+            "uzp1 z7.d, z9.d, z22.d\n"
+            "uzp2 z22.d, z9.d, z22.d\n"
+            "fmul z9.s, z23.s, z3.s[0]\n"
+            "scvtf z5.s, p1/m, z5.s\n"
+            "scvtf z18.s, p1/m, z18.s\n"
+            "scvtf z7.s, p1/m, z7.s\n"
+            "scvtf z22.s, p1/m, z22.s\n"
+            "fmla z24.s, p1/M, z5.s, z9.s\n"
+            "ld1rqb { z5.b }, p1/Z, [x26]\n"
+            "fmul z9.s, z23.s, z3.s[1]\n"
+            "fmla z15.s, p1/M, z18.s, z9.s\n"
+            "ld1rqb { z18.b }, p1/Z, [x26, #16]\n"
+            "fmul z9.s, z23.s, z3.s[2]\n"
+            "fmul z3.s, z23.s, z3.s[3]\n"
+            "fmla z12.s, p1/M, z7.s, z9.s\n"
+            "mov z9.s, #0x0\n"
+            "ld1h { z7.s }, p0/Z, [x22]\n"
+            ".inst 0x451f98a9  // smmla z9.s, z5.b, z31.b\n"
+            "fmla z0.s, p1/M, z22.s, z3.s\n"
+            "mov z22.s, #0x0\n"
+            "ld1h { z3.s }, p0/Z, [x21]\n"
+            ".inst 0x450698b6  // smmla z22.s, z5.b, z6.b\n"
+            "ld1rqb { z5.b }, p1/Z, [x26, #32]\n"
+            "fcvt z7.s, p1/m, z7.h\n"
+            "fcvt z3.s, p1/m, z3.h\n"
+            ".inst 0x450e98a9  // smmla z9.s, z5.b, z14.b\n"
+            ".inst 0x450298b6  // smmla z22.s, z5.b, z2.b\n"
+            "ld1rqb { z5.b }, p1/Z, [x26, #64]\n"
+            "mov z7.q, z7.q[0]\n"
+            "mov z3.q, z3.q[0]\n"
+            ".inst 0x451e98a9  // smmla z9.s, z5.b, z30.b\n"
+            ".inst 0x451598b6  // smmla z22.s, z5.b, z21.b\n"
+            "ld1rqb { z5.b }, p1/Z, [x26, #96]\n"
+            ".inst 0x450498a9  // smmla z9.s, z5.b, z4.b\n"
+            ".inst 0x451198b6  // smmla z22.s, z5.b, z17.b\n"
+            "uzp1 z5.d, z9.d, z22.d\n"
+            "scvtf z5.s, p1/m, z5.s\n"
+            "uzp2 z22.d, z9.d, z22.d\n"
+            "fmul z9.s, z23.s, z7.s[0]\n"
+            "scvtf z22.s, p1/m, z22.s\n"
+            "fmla z13.s, p1/M, z5.s, z9.s\n"
+            "ld1rqb { z9.b }, p1/Z, [x25]\n"
+            "fmul z5.s, z23.s, z7.s[1]\n"
+            "fmla z1.s, p1/M, z22.s, z5.s\n"
+            "mov z5.s, #0x0\n"
+            "mov z22.s, #0x0\n"
+            ".inst 0x451f9a45  // smmla z5.s, z18.b, z31.b\n"
+            ".inst 0x45069a56  // smmla z22.s, z18.b, z6.b\n"
+            "ld1rqb { z18.b }, p1/Z, [x26, #48]\n"
+            ".inst 0x450e9a45  // smmla z5.s, z18.b, z14.b\n"
+            ".inst 0x45029a56  // smmla z22.s, z18.b, z2.b\n"
+            "ld1rqb { z18.b }, p1/Z, [x26, #80]\n"
+            ".inst 0x451e9a45  // smmla z5.s, z18.b, z30.b\n"
+            ".inst 0x45159a56  // smmla z22.s, z18.b, z21.b\n"
+            "ld1rqb { z18.b }, p1/Z, [x26, #112]\n"
+            "add x26, x26, #0x88\n"
+            ".inst 0x45049a45  // smmla z5.s, z18.b, z4.b\n"
+            ".inst 0x45119a56  // smmla z22.s, z18.b, z17.b\n"
+            "uzp1 z18.d, z5.d, z22.d\n"
+            "scvtf z18.s, p1/m, z18.s\n"
+            "uzp2 z22.d, z5.d, z22.d\n"
+            "fmul z5.s, z23.s, z7.s[2]\n"
+            "fmul z7.s, z23.s, z7.s[3]\n"
+            "scvtf z22.s, p1/m, z22.s\n"
+            "fmla z20.s, p1/M, z18.s, z5.s\n"
+            "ld1rqb { z18.b }, p1/Z, [x25, #16]\n"
+            "ld1h { z5.s }, p0/Z, [x20]\n"
+            "fcvt z5.s, p1/m, z5.h\n"
+            "fmla z25.s, p1/M, z22.s, z7.s\n"
+            "mov z22.s, #0x0\n"
+            "mov z7.s, #0x0\n"
+            ".inst 0x451f9936  // smmla z22.s, z9.b, z31.b\n"
+            ".inst 0x45069927  // smmla z7.s, z9.b, z6.b\n"
+            "ld1rqb { z9.b }, p1/Z, [x25, #32]\n"
+            "mov z5.q, z5.q[0]\n"
+            ".inst 0x450e9936  // smmla z22.s, z9.b, z14.b\n"
+            ".inst 0x45029927  // smmla z7.s, z9.b, z2.b\n"
+            "ld1rqb { z9.b }, p1/Z, [x25, #64]\n"
+            ".inst 0x451e9936  // smmla z22.s, z9.b, z30.b\n"
+            ".inst 0x45159927  // smmla z7.s, z9.b, z21.b\n"
+            "ld1rqb { z9.b }, p1/Z, [x25, #96]\n"
+            ".inst 0x45049936  // smmla z22.s, z9.b, z4.b\n"
+            ".inst 0x45119927  // smmla z7.s, z9.b, z17.b\n"
+            "uzp1 z9.d, z22.d, z7.d\n"
+            "scvtf z9.s, p1/m, z9.s\n"
+            "uzp2 z22.d, z22.d, z7.d\n"
+            "fmul z7.s, z23.s, z3.s[0]\n"
+            "scvtf z22.s, p1/m, z22.s\n"
+            "fmla z11.s, p1/M, z9.s, z7.s\n"
+            "ld1rqb { z9.b }, p1/Z, [x24]\n"
+            "fmul z7.s, z23.s, z3.s[1]\n"
+            "fmla z16.s, p1/M, z22.s, z7.s\n"
+            "mov z22.s, #0x0\n"
+            "mov z7.s, #0x0\n"
+            ".inst 0x451f9a56  // smmla z22.s, z18.b, z31.b\n"
+            ".inst 0x45069a47  // smmla z7.s, z18.b, z6.b\n"
+            "ld1rqb { z18.b }, p1/Z, [x25, #48]\n"
+            ".inst 0x450e9a56  // smmla z22.s, z18.b, z14.b\n"
+            ".inst 0x45029a47  // smmla z7.s, z18.b, z2.b\n"
+            "ld1rqb { z18.b }, p1/Z, [x25, #80]\n"
+            ".inst 0x451e9a56  // smmla z22.s, z18.b, z30.b\n"
+            ".inst 0x45159a47  // smmla z7.s, z18.b, z21.b\n"
+            "ld1rqb { z18.b }, p1/Z, [x25, #112]\n"
+            "add x25, x25, #0x88\n"
+            ".inst 0x45049a56  // smmla z22.s, z18.b, z4.b\n"
+            ".inst 0x45119a47  // smmla z7.s, z18.b, z17.b\n"
+            "uzp1 z18.d, z22.d, z7.d\n"
+            "scvtf z18.s, p1/m, z18.s\n"
+            "uzp2 z7.d, z22.d, z7.d\n"
+            "fmul z22.s, z23.s, z3.s[2]\n"
+            "fmul z3.s, z23.s, z3.s[3]\n"
+            "scvtf z7.s, p1/m, z7.s\n"
+            "fmla z19.s, p1/M, z18.s, z22.s\n"
+            "ld1rqb { z18.b }, p1/Z, [x24, #16]\n"
+            "fmul z22.s, z23.s, z5.s[0]\n"
+            "fmla z26.s, p1/M, z7.s, z3.s\n"
+            "mov z3.s, #0x0\n"
+            "mov z7.s, #0x0\n"
+            ".inst 0x451f9923  // smmla z3.s, z9.b, z31.b\n"
+            ".inst 0x45069927  // smmla z7.s, z9.b, z6.b\n"
+            "ld1rqb { z9.b }, p1/Z, [x24, #32]\n"
+            ".inst 0x450e9923  // smmla z3.s, z9.b, z14.b\n"
+            ".inst 0x45029927  // smmla z7.s, z9.b, z2.b\n"
+            "mov z9.s, #0x0\n"
+            ".inst 0x451f9a49  // smmla z9.s, z18.b, z31.b\n"
+            "mov z31.s, #0x0\n"
+            ".inst 0x45069a5f  // smmla z31.s, z18.b, z6.b\n"
+            "ld1rqb { z6.b }, p1/Z, [x24, #48]\n"
+            "ld1rqb { z18.b }, p1/Z, [x24, #64]\n"
+            ".inst 0x450e98c9  // smmla z9.s, z6.b, z14.b\n"
+            "fmul z14.s, z23.s, z5.s[1]\n"
+            ".inst 0x450298df  // smmla z31.s, z6.b, z2.b\n"
+            "ld1rqb { z6.b }, p1/Z, [x24, #80]\n"
+            "fmul z2.s, z23.s, z5.s[2]\n"
+            "fmul z23.s, z23.s, z5.s[3]\n"
+            ".inst 0x451e9a43  // smmla z3.s, z18.b, z30.b\n"
+            ".inst 0x45159a47  // smmla z7.s, z18.b, z21.b\n"
+            "ld1rqb { z5.b }, p1/Z, [x24, #96]\n"
+            ".inst 0x451e98c9  // smmla z9.s, z6.b, z30.b\n"
+            ".inst 0x451598df  // smmla z31.s, z6.b, z21.b\n"
+            "ld1rqb { z18.b }, p1/Z, [x24, #112]\n"
+            "add x24, x24, #0x88\n"
+            ".inst 0x450498a3  // smmla z3.s, z5.b, z4.b\n"
+            ".inst 0x451198a7  // smmla z7.s, z5.b, z17.b\n"
+            ".inst 0x45049a49  // smmla z9.s, z18.b, z4.b\n"
+            ".inst 0x45119a5f  // smmla z31.s, z18.b, z17.b\n"
+            "uzp1 z18.d, z3.d, z7.d\n"
+            "uzp2 z5.d, z3.d, z7.d\n"
+            "scvtf z18.s, p1/m, z18.s\n"
+            "uzp1 z6.d, z9.d, z31.d\n"
+            "uzp2 z9.d, z9.d, z31.d\n"
+            "scvtf z5.s, p1/m, z5.s\n"
+            "fmla z8.s, p1/M, z18.s, z22.s\n"
+            "scvtf z6.s, p1/m, z6.s\n"
+            "scvtf z9.s, p1/m, z9.s\n"
+            "fmla z29.s, p1/M, z5.s, z14.s\n"
+            "fmla z27.s, p1/M, z6.s, z2.s\n"
+            "fmla z10.s, p1/M, z9.s, z23.s\n"
+            "bgt 3b\n"
+            "mov x20, %x[res_ptr]\n"
+            "subs x10, x10, #0x8\n"
+            "add %x[res_ptr], %x[res_ptr], #0x20\n"
+            "st1w { z24.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "st1w { z15.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "st1w { z12.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "st1w { z0.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "st1w { z13.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "st1w { z1.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "st1w { z20.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "st1w { z25.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "st1w { z11.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "st1w { z16.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "st1w { z19.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "st1w { z26.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "st1w { z8.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "st1w { z29.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "st1w { z27.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "st1w { z10.s }, p1, [x20]\n"
+            "bne 2b\n"
+            "mov x20, #0x4\n"
+            "sub x13, x13, #0x10\n"
+            "cmp x13, #0x10\n"
+            "mov %x[res_ptr], x9\n"
+            "madd %x[a_ptr], x20, x12, %x[a_ptr]\n"
+            "bge 1b\n"
+            "4:"  // Row loop skip
+            "cbz x13, 9f\n"
+            "5:"  // Row tail: Row loop
+            "add x25, %x[b_ptr], #0x10\n"
+            "mov x24, %x[nc]\n"
+            "add x23, %x[res_ptr], %x[res_stride], LSL #2\n"
+            "6:"  // Row tail: Column loop
+            "mov z24.b, #0x0\n"
+            "mov z15.b, #0x0\n"
+            "add x28, %x[a_ptr], #0x8\n"
+            "mov x22, %x[nb]\n"
+            "mov z12.b, #0x0\n"
+            "mov z0.b, #0x0\n"
+            "7:"  // Row tail: Block loop
+            "ld1b { z3.b }, p1/Z, [x25]\n"
+            "ld1b { z6.b }, p1/Z, [x25, #1, MUL VL]\n"
+            "mov z2.s, #0x0\n"
+            "mov z25.s, #0x0\n"
+            "ld1rqb { z26.b }, p1/Z, [x28]\n"
+            "ld1rqb { z21.b }, p1/Z, [x28, #16]\n"
+            "mov z27.s, #0x0\n"
+            "mov z19.s, #0x0\n"
+            "ld1b { z29.b }, p1/Z, [x25, #2, MUL VL]\n"
+            "ld1b { z16.b }, p1/Z, [x25, #3, MUL VL]\n"
+            "sub x21, x25, #0x10\n"
+            "sub x20, x28, #0x8\n"
+            "lsl z20.b, z3.b, #0x4\n"
+            "lsl z4.b, z6.b, #0x4\n"
+            "ld1rqb { z10.b }, p1/Z, [x28, #32]\n"
+            "ld1rqb { z23.b }, p1/Z, [x28, #48]\n"
+            "and z3.b, z3.b, #0xf0\n"
+            "and z6.b, z6.b, #0xf0\n"
+            "ld1rqb { z11.b }, p1/Z, [x28, #64]\n"
+            "ld1rqb { z7.b }, p1/Z, [x28, #80]\n"
+            "lsl z8.b, z29.b, #0x4\n"
+            "lsl z14.b, z16.b, #0x4\n"
+            "ld1rqb { z18.b }, p1/Z, [x28, #96]\n"
+            "ld1rqb { z30.b }, p1/Z, [x28, #112]\n"
+            ".inst 0x45149b42  // smmla z2.s, z26.b, z20.b\n"
+            ".inst 0x45049b59  // smmla z25.s, z26.b, z4.b\n"
+            "and z29.b, z29.b, #0xf0\n"
+            "ld1h { z17.s }, p1/Z, [x21]\n"
+            ".inst 0x45149abb  // smmla z27.s, z21.b, z20.b\n"
+            ".inst 0x45049ab3  // smmla z19.s, z21.b, z4.b\n"
+            "and z16.b, z16.b, #0xf0\n"
+            "ld1h { z4.s }, p0/Z, [x20]\n"
+            "subs x22, x22, #0x1\n"
+            "add x28, x28, #0x88\n"
+            "fcvt z17.s, p1/m, z17.h\n"
+            "add x25, x25, #0x90\n"
+            ".inst 0x45089942  // smmla z2.s, z10.b, z8.b\n"
+            ".inst 0x450e9959  // smmla z25.s, z10.b, z14.b\n"
+            "fcvt z4.s, p1/m, z4.h\n"
+            ".inst 0x45089afb  // smmla z27.s, z23.b, z8.b\n"
+            ".inst 0x450e9af3  // smmla z19.s, z23.b, z14.b\n"
+            "fscale z17.s, p1/m, z17.s, z28.s\n"
+            "mov z4.q, z4.q[0]\n"
+            ".inst 0x45039962  // smmla z2.s, z11.b, z3.b\n"
+            ".inst 0x45069979  // smmla z25.s, z11.b, z6.b\n"
+            "fmul z23.s, z17.s, z4.s[0]\n"
+            "fmul z9.s, z17.s, z4.s[1]\n"
+            "fmul z21.s, z17.s, z4.s[2]\n"
+            "fmul z4.s, z17.s, z4.s[3]\n"
+            ".inst 0x450398fb  // smmla z27.s, z7.b, z3.b\n"
+            ".inst 0x450698f3  // smmla z19.s, z7.b, z6.b\n"
+            ".inst 0x451d9a42  // smmla z2.s, z18.b, z29.b\n"
+            ".inst 0x45109a59  // smmla z25.s, z18.b, z16.b\n"
+            ".inst 0x451d9bdb  // smmla z27.s, z30.b, z29.b\n"
+            ".inst 0x45109bd3  // smmla z19.s, z30.b, z16.b\n"
+            "uzp1 z31.d, z2.d, z25.d\n"
+            "uzp2 z13.d, z2.d, z25.d\n"
+            "scvtf z31.s, p1/m, z31.s\n"
+            "uzp1 z17.d, z27.d, z19.d\n"
+            "uzp2 z18.d, z27.d, z19.d\n"
+            "scvtf z13.s, p1/m, z13.s\n"
+            "fmla z24.s, p1/M, z31.s, z23.s\n"
+            "scvtf z17.s, p1/m, z17.s\n"
+            "scvtf z18.s, p1/m, z18.s\n"
+            "fmla z15.s, p1/M, z13.s, z9.s\n"
+            "fmla z12.s, p1/M, z17.s, z21.s\n"
+            "fmla z0.s, p1/M, z18.s, z4.s\n"
+            "bgt 7b\n"
+            "mov x20, %x[res_ptr]\n"
+            "cmp x13, #0x1\n"
+            "st1w { z24.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "ble 8f\n"
+            "cmp x13, #0x2\n"
+            "st1w { z15.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "ble 8f\n"
+            "cmp x13, #0x3\n"
+            "st1w { z12.s }, p1, [x20]\n"
+            "add x20, x20, %x[res_stride]\n"
+            "ble 8f\n"
+            "st1w { z0.s }, p1, [x20]\n"
+            "8:"  // Row tail: Accumulator store skip
+            "subs x24, x24, #0x8\n"
+            "add %x[res_ptr], %x[res_ptr], #0x20\n"
+            "bne 6b\n"
+            "subs x13, x13, #0x4\n"
+            "add %x[a_ptr], %x[a_ptr], x12\n"
+            "mov %x[res_ptr], x23\n"
+            "bgt 5b\n"
+            "9:"  // Row tail: Row loop skip
+            : [a_ptr] "+&r" (a_ptr), [res_ptr] "+&r" (res_ptr)
+            : [b_ptr] "r" (b_ptr), [nr] "r" (nr), [nb] "r" (nb), [res_stride] "r" (res_stride), [nc] "r" (nc)
+            : "cc", "memory", "p0", "p1", "x9", "x10", "x11", "x12", "x13", "x20", "x21", "x22", "x23", "x24", "x25", "x26", "x27", "x28", "z0", "z1", "z2", "z3", "z4", "z5", "z6", "z7", "z8", "z9", "z10", "z11", "z12", "z13", "z14", "z15", "z16", "z17", "z18", "z19", "z20", "z21", "z22", "z23", "z24", "z25", "z26", "z27", "z28", "z29", "z30", "z31"
+        );
+        return;
+    }
+    else if (ggml_cpu_has_neon() && ggml_cpu_has_matmul_int8()) {
+        GGML_ASSERT((ggml_cpu_has_sve() && (svcntw() == 8)) &&
+                    "__ARM_FEATURE_SVE for vector size of 256-bits not defined, use the Q4_0_4_8 quantization format for optimal "
+                    "performance");
+    }
+    else if (ggml_cpu_has_neon()) {
+        GGML_ASSERT(((ggml_cpu_has_sve() && (svcntw() == 8)) || ggml_cpu_has_matmul_int8()) &&
+                    "__ARM_FEATURE_SVE for vector size of 256-bits and __ARM_FEATURE_MATMUL_INT8 not defined, use the Q4_0_4_4 "
+                    "quantization format for optimal performance");
+    }
+#endif
+#if defined(__ARM_NEON) && defined(__ARM_FEATURE_MATMUL_INT8)
+    GGML_ASSERT(ggml_cpu_has_sve() &&
+                "__ARM_FEATURE_SVE not defined, use the Q4_0_4_8 quantization format for optimal performance");
+#elif defined(__ARM_NEON) && defined(__aarch64__)
+    GGML_ASSERT((ggml_cpu_has_sve() || ggml_cpu_has_matmul_int8()) &&
+                "__ARM_FEATURE_SVE and __ARM_FEATURE_MATMUL_INT8 not defined, use the Q4_0_4_4 quantization format for optimal "
+                "performance");
+#else
+    float sumf[4][8];
+    int sumi;
+
+    for (int y = 0; y < nr / 4; y++) {
+        const block_q8_0x4 * a_ptr = (const block_q8_0x4 *) vy + (y * nb);
+        for (int x = 0; x < nc / ncols_interleaved; x++) {
+            const block_q4_0x8 * b_ptr = (const block_q4_0x8 *) vx + (x * nb);
+            for (int m = 0; m < 4; m++) {
+                for (int j = 0; j < ncols_interleaved; j++) sumf[m][j] = 0.0;
+            }
+            for (int l = 0; l < nb; l++) {
+                for (int k = 0; k < (qk / (2 * blocklen)); k++) {
+                    for (int m = 0; m < 4; m++) {
+                        for (int j = 0; j < ncols_interleaved; j++) {
+                            sumi = 0;
+                            for (int i = 0; i < blocklen; ++i) {
+                                const int v0 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] << 4);
+                                const int v1 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] & 0xF0);
+                                sumi += ((v0 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i]) +
+                                         (v1 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i + qk / 2 * 4])) >> 4;
+                            }
+                            sumf[m][j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d[m]);
+                        }
+                    }
+                }
+            }
+            for (int m = 0; m < 4; m++) {
+                for (int j = 0; j < ncols_interleaved; j++)
+                    s[(y * 4 + m) * bs + x * ncols_interleaved + j] = sumf[m][j];
+            }
+        }
+    }
+#endif
+}
diff --git a/ggml/src/ggml-aarch64.h b/ggml/src/ggml-aarch64.h
new file mode 100644
index 0000000000000..65ead1efed572
--- /dev/null
+++ b/ggml/src/ggml-aarch64.h
@@ -0,0 +1,39 @@
+// SPDX-FileCopyrightText: Copyright 2024 Arm Ltd.
+#pragma once
+
+#define GGML_COMMON_DECL_C
+#include "ggml-common.h"
+
+#include "ggml.h"
+
+// GGML internal header
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+// Quantization
+void quantize_q8_0_4x4(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+void quantize_q8_0_4x8(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+
+void quantize_mat_q8_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t nrows, int64_t n_per_row, int64_t interleave_blcksize);
+
+// Quantization utilizing an importance matrix (a.k.a. "Activation aWare Quantization")
+size_t quantize_q4_0_4x4(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_q4_0_4x8(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_q4_0_8x8(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+
+// GEMV
+void ggml_gemv_q4_0_4x4_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemv_q4_0_4x8_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemv_q4_0_8x8_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+
+// GEMM
+void ggml_gemm_q4_0_4x4_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemm_q4_0_4x8_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemm_q4_0_8x8_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+
+#ifdef __cplusplus
+}
+#endif
+
diff --git a/ggml/src/ggml-common.h b/ggml/src/ggml-common.h
index c74060cc4b991..fafd5fa7ae000 100644
--- a/ggml/src/ggml-common.h
+++ b/ggml/src/ggml-common.h
@@ -199,6 +199,30 @@ typedef struct {
 } block_q8_1;
 static_assert(sizeof(block_q8_1) == 2*sizeof(ggml_half) + QK8_1, "wrong q8_1 block size/padding");
 
+typedef struct {
+    ggml_half d[4];        // deltas for 4 q4_0 blocks
+    uint8_t qs[QK4_0 * 2]; // nibbles / quants for 4 q4_0 blocks
+} block_q4_0x4;
+static_assert(sizeof(block_q4_0x4) == 4 * sizeof(ggml_half) + QK4_0 * 2, "wrong q4_0x4 block size/padding");
+
+typedef struct {
+    ggml_half d[8];        // deltas for 8 q4_0 blocks
+    uint8_t qs[QK4_0 * 4]; // nibbles / quants for 8 q4_0 blocks
+} block_q4_0x8;
+static_assert(sizeof(block_q4_0x8) == 8 * sizeof(ggml_half) + QK4_0 * 4, "wrong q4_0x8 block size/padding");
+
+typedef struct {
+    ggml_half d[4];        // deltas for 4 q8_0 blocks
+    int8_t qs[QK8_0 * 4];  // quants for 4 q8_0 blocks
+} block_q8_0x4;
+static_assert(sizeof(block_q8_0x4) == 4 * sizeof(ggml_half) + QK8_0 * 4, "wrong q8_0x4 block size/padding");
+
+typedef struct {
+    ggml_half d[8];        // deltas for 8 q8_0 blocks
+    int8_t qs[QK8_0 * 8];  // quants for 8 q8_0 blocks
+} block_q8_0x8;
+static_assert(sizeof(block_q8_0x8) == 8 * sizeof(ggml_half) + QK8_0 * 8, "wrong q8_0x8 block size/padding");
+
 //
 // Super-block quantization structures
 //
diff --git a/ggml/src/ggml-impl.h b/ggml/src/ggml-impl.h
index 1d23361906c34..a2c8dbec0824f 100644
--- a/ggml/src/ggml-impl.h
+++ b/ggml/src/ggml-impl.h
@@ -609,6 +609,10 @@ static inline ggml_fp16_t ggml_compute_fp32_to_fp16(float f) {
 
 #endif // defined(__ARM_NEON) && (!defined(__MSC_VER)
 
+#ifdef __ARM_FEATURE_SVE
+#include 
+#endif // __ARM_FEATURE_SVE
+
 // precomputed f32 table for f16 (256 KB)
 // defined in ggml.c, initialized in ggml_init()
 extern float ggml_table_f32_f16[1 << 16];
diff --git a/ggml/src/ggml-quants.c b/ggml/src/ggml-quants.c
index 0eb52e485089f..cbe377cf5caee 100644
--- a/ggml/src/ggml-quants.c
+++ b/ggml/src/ggml-quants.c
@@ -3814,43 +3814,47 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * restrict s, size_t bs, const void * r
     }
 #endif
 #if defined(__ARM_FEATURE_SVE)
-    const svbool_t ptrueh = svptrue_pat_b8(SV_VL16);
-    const svbool_t ptruel = svnot_b_z(svptrue_b8(), ptrueh);
+    if (svcntb() == QK8_0) {
+        const svbool_t ptrueh = svptrue_pat_b8(SV_VL16);
+        const svbool_t ptruel = svnot_b_z(svptrue_b8(), ptrueh);
 
-    svfloat32_t sumv0 = svdup_n_f32(0.0f);
-    svfloat32_t sumv1 = svdup_n_f32(0.0f);
+        svfloat32_t sumv0 = svdup_n_f32(0.0f);
+        svfloat32_t sumv1 = svdup_n_f32(0.0f);
 
-    assert(nb % 2 == 0); // TODO: handle odd nb
+        assert(nb % 2 == 0); // TODO: handle odd nb
 
-    for (int i = 0; i < nb; i += 2) {
-        const block_q4_0 * restrict x0 = &x[i + 0];
-        const block_q4_0 * restrict x1 = &x[i + 1];
-        const block_q8_0 * restrict y0 = &y[i + 0];
-        const block_q8_0 * restrict y1 = &y[i + 1];
+        for (int i = 0; i < nb; i += 2) {
+            const block_q4_0 * restrict x0 = &x[i + 0];
+            const block_q4_0 * restrict x1 = &x[i + 1];
+            const block_q8_0 * restrict y0 = &y[i + 0];
+            const block_q8_0 * restrict y1 = &y[i + 1];
 
-        // load x
-        const svuint8_t qx0r = svld1rq_u8(svptrue_b8(), x0->qs);
-        const svuint8_t qx1r = svld1rq_u8(svptrue_b8(), x1->qs);
+            // load x
+            const svuint8_t qx0r = svld1rq_u8(svptrue_b8(), x0->qs);
+            const svuint8_t qx1r = svld1rq_u8(svptrue_b8(), x1->qs);
 
-        // 4-bit -> 8-bit
-        const svint8_t qx0 = svreinterpret_s8_u8(svlsr_n_u8_m(ptruel, svand_n_u8_m(ptrueh, qx0r, 0x0F), 0x04));
-        const svint8_t qx1 = svreinterpret_s8_u8(svlsr_n_u8_m(ptruel, svand_n_u8_m(ptrueh, qx1r, 0x0F), 0x04));
+            // 4-bit -> 8-bit
+            const svint8_t qx0 = svreinterpret_s8_u8(svlsr_n_u8_m(ptruel, svand_n_u8_m(ptrueh, qx0r, 0x0F), 0x04));
+            const svint8_t qx1 = svreinterpret_s8_u8(svlsr_n_u8_m(ptruel, svand_n_u8_m(ptrueh, qx1r, 0x0F), 0x04));
 
-        // sub 8
-        const svint8_t qx0s = svsub_n_s8_x(svptrue_b8(), qx0, 8);
-        const svint8_t qx1s = svsub_n_s8_x(svptrue_b8(), qx1, 8);
+            // sub 8
+            const svint8_t qx0s = svsub_n_s8_x(svptrue_b8(), qx0, 8);
+            const svint8_t qx1s = svsub_n_s8_x(svptrue_b8(), qx1, 8);
 
-        // load y
-        const svint8_t qy0 = svld1_s8(svptrue_b8(), y0->qs);
-        const svint8_t qy1 = svld1_s8(svptrue_b8(), y1->qs);
+            // load y
+            const svint8_t qy0 = svld1_s8(svptrue_b8(), y0->qs);
+            const svint8_t qy1 = svld1_s8(svptrue_b8(), y1->qs);
 
-        // dot product
-        sumv0 = svmla_n_f32_x(svptrue_b32(), sumv0, svcvt_f32_s32_x(svptrue_b32(), svdot_s32(svdup_n_s32(0), qx0s, qy0)), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
-        sumv1 = svmla_n_f32_x(svptrue_b32(), sumv1, svcvt_f32_s32_x(svptrue_b32(), svdot_s32(svdup_n_s32(0), qx1s, qy1)), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
-    }
+            // dot product
+            sumv0 = svmla_n_f32_x(svptrue_b32(), sumv0, svcvt_f32_s32_x(svptrue_b32(), svdot_s32(svdup_n_s32(0), qx0s, qy0)), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
+            sumv1 = svmla_n_f32_x(svptrue_b32(), sumv1, svcvt_f32_s32_x(svptrue_b32(), svdot_s32(svdup_n_s32(0), qx1s, qy1)), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
+        }
 
-    *s = svaddv_f32(svptrue_b32(), svadd_f32_x(svptrue_b32(), sumv0, sumv1));
-#elif defined(__ARM_NEON)
+        *s = svaddv_f32(svptrue_b32(), svadd_f32_x(svptrue_b32(), sumv0, sumv1));
+        return;
+    }
+#endif
+#if defined(__ARM_NEON)
     float32x4_t sumv0 = vdupq_n_f32(0.0f);
     float32x4_t sumv1 = vdupq_n_f32(0.0f);
 
@@ -5422,31 +5426,35 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * restrict s, size_t bs, const void * r
     }
 #endif
 #if defined(__ARM_FEATURE_SVE)
-    svfloat32_t sumv0 = svdup_n_f32(0.0f);
-    svfloat32_t sumv1 = svdup_n_f32(0.0f);
+    if (svcntb() == QK8_0) {
+        svfloat32_t sumv0 = svdup_n_f32(0.0f);
+        svfloat32_t sumv1 = svdup_n_f32(0.0f);
 
-    assert(nb % 2 == 0); // TODO: handle odd nb
+        assert(nb % 2 == 0); // TODO: handle odd nb
 
-    for (int i = 0; i < nb; i += 2) {
-        const block_q8_0 * restrict x0 = &x[i + 0];
-        const block_q8_0 * restrict x1 = &x[i + 1];
-        const block_q8_0 * restrict y0 = &y[i + 0];
-        const block_q8_0 * restrict y1 = &y[i + 1];
+        for (int i = 0; i < nb; i += 2) {
+            const block_q8_0 * restrict x0 = &x[i + 0];
+            const block_q8_0 * restrict x1 = &x[i + 1];
+            const block_q8_0 * restrict y0 = &y[i + 0];
+            const block_q8_0 * restrict y1 = &y[i + 1];
 
-        // load x
-        const svint8_t qx0 = svld1_s8(svptrue_b8(), x0->qs);
-        const svint8_t qx1 = svld1_s8(svptrue_b8(), x1->qs);
+            // load x
+            const svint8_t qx0 = svld1_s8(svptrue_b8(), x0->qs);
+            const svint8_t qx1 = svld1_s8(svptrue_b8(), x1->qs);
 
-        // load y
-        const svint8_t qy0 = svld1_s8(svptrue_b8(), y0->qs);
-        const svint8_t qy1 = svld1_s8(svptrue_b8(), y1->qs);
+            // load y
+            const svint8_t qy0 = svld1_s8(svptrue_b8(), y0->qs);
+            const svint8_t qy1 = svld1_s8(svptrue_b8(), y1->qs);
 
-        sumv0 = svmla_n_f32_x(svptrue_b32(), sumv0, svcvt_f32_s32_x(svptrue_b32(), svdot_s32(svdup_n_s32(0), qx0, qy0)), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
-        sumv1 = svmla_n_f32_x(svptrue_b32(), sumv1, svcvt_f32_s32_x(svptrue_b32(), svdot_s32(svdup_n_s32(0), qx1, qy1)), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
-    }
+            sumv0 = svmla_n_f32_x(svptrue_b32(), sumv0, svcvt_f32_s32_x(svptrue_b32(), svdot_s32(svdup_n_s32(0), qx0, qy0)), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
+            sumv1 = svmla_n_f32_x(svptrue_b32(), sumv1, svcvt_f32_s32_x(svptrue_b32(), svdot_s32(svdup_n_s32(0), qx1, qy1)), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
+        }
 
-    *s = svaddv_f32(svptrue_b32(), svadd_f32_x(svptrue_b32(), sumv0, sumv1));
-#elif defined(__ARM_NEON)
+        *s = svaddv_f32(svptrue_b32(), svadd_f32_x(svptrue_b32(), sumv0, sumv1));
+        return;
+    }
+#endif
+#if defined(__ARM_NEON)
     float32x4_t sumv0 = vdupq_n_f32(0.0f);
     float32x4_t sumv1 = vdupq_n_f32(0.0f);
 
@@ -14760,6 +14768,16 @@ static bool validate_fp16(ggml_fp16_t f, size_t i) {
         } \
     }
 
+#define VALIDATE_ROW_DATA_DVEC_F16_IMPL(type, data, nb, nr) \
+    const type * q = (const type *) (data); \
+    for (size_t i = 0; i < (nb); ++i) { \
+        for (size_t j = 0; j < (nr); ++j) { \
+            if (!validate_fp16(q[i].d[j], i)) { \
+                return false; \
+            } \
+        } \
+    }
+
 bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbytes) {
     if (type < 0 || type >= GGML_TYPE_COUNT) {
         fprintf(stderr, "%s: invalid type %d\n", __func__, type);
@@ -14977,6 +14995,16 @@ bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbyte
             {
                 VALIDATE_ROW_DATA_D_F16_IMPL(block_iq4_nl, data, nb);
             } break;
+        case GGML_TYPE_Q4_0_4_4:
+        case GGML_TYPE_Q4_0_4_8:
+            {
+                VALIDATE_ROW_DATA_DVEC_F16_IMPL(block_q4_0x4, data, nbytes / sizeof(block_q4_0x4), 4);
+            } break;
+        case GGML_TYPE_Q4_0_8_8:
+            {
+                VALIDATE_ROW_DATA_DVEC_F16_IMPL(block_q4_0x8, data, nbytes / sizeof(block_q4_0x8), 8);
+            } break;
+
         case GGML_TYPE_I8:
         case GGML_TYPE_I16:
         case GGML_TYPE_I32:
diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c
index bc91ac3a726ab..c0aced3d2d069 100644
--- a/ggml/src/ggml.c
+++ b/ggml/src/ggml.c
@@ -4,6 +4,7 @@
 #include "ggml-impl.h"
 #include "ggml-quants.h"
 #include "ggml.h"
+#include "ggml-aarch64.h"
 
 
 #if defined(_MSC_VER) || defined(__MINGW32__)
@@ -37,7 +38,7 @@
 #include 
 #endif
 
-#ifdef __ARM_FEATURE_MATMUL_INT8
+#if defined(__ARM_FEATURE_SVE) || defined(__ARM_FEATURE_MATMUL_INT8)
 #undef GGML_USE_LLAMAFILE
 #endif
 
@@ -692,6 +693,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
 #else
         .nrows                    = 1,
 #endif
+        .from_float_to_mat        = quantize_mat_q8_0,
     },
     [GGML_TYPE_Q8_1] = {
         .type_name                = "q8_1",
@@ -889,6 +891,54 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .vec_dot                  = (ggml_vec_dot_t) ggml_vec_dot_bf16,
         .vec_dot_type             = GGML_TYPE_BF16,
         .nrows                    = 1,
+    },
+    [GGML_TYPE_Q4_0_4_4] = {
+        .type_name                = "q4_0_4x4",
+        .blck_size                = QK4_0,
+        .type_size                = sizeof(block_q4_0),
+        .is_quantized             = true,
+        .to_float                 = NULL,
+        .from_float               = NULL,
+        .from_float_reference     = NULL,
+        .vec_dot                  = NULL,
+        .vec_dot_type             = GGML_TYPE_Q8_0,
+        .nrows                    = 1,
+        .ncols                    = 4,
+        .interleave_blcksize      = 4,
+        .gemv                     = ggml_gemv_q4_0_4x4_q8_0,
+        .gemm                     = ggml_gemm_q4_0_4x4_q8_0,
+    },
+    [GGML_TYPE_Q4_0_4_8] = {
+        .type_name                = "q4_0_4x8",
+        .blck_size                = QK4_0,
+        .type_size                = sizeof(block_q4_0),
+        .is_quantized             = true,
+        .to_float                 = NULL,
+        .from_float               = NULL,
+        .from_float_reference     = NULL,
+        .vec_dot                  = NULL,
+        .vec_dot_type             = GGML_TYPE_Q8_0,
+        .nrows                    = 1,
+        .ncols                    = 4,
+        .interleave_blcksize      = 8,
+        .gemv                     = ggml_gemv_q4_0_4x8_q8_0,
+        .gemm                     = ggml_gemm_q4_0_4x8_q8_0,
+    },
+    [GGML_TYPE_Q4_0_8_8] = {
+        .type_name                = "q4_0_8x8",
+        .blck_size                = QK4_0,
+        .type_size                = sizeof(block_q4_0),
+        .is_quantized             = true,
+        .to_float                 = NULL,
+        .from_float               = NULL,
+        .from_float_reference     = NULL,
+        .vec_dot                  = NULL,
+        .vec_dot_type             = GGML_TYPE_Q8_0,
+        .nrows                    = 1,
+        .ncols                    = 8,
+        .interleave_blcksize      = 8,
+        .gemv                     = ggml_gemv_q4_0_8x8_q8_0,
+        .gemm                     = ggml_gemm_q4_0_8x8_q8_0,
     }
 };
 
@@ -3188,6 +3238,9 @@ enum ggml_type ggml_ftype_to_ggml_type(enum ggml_ftype ftype) {
         case GGML_FTYPE_MOSTLY_IQ4_XS:        wtype = GGML_TYPE_IQ4_XS;   break;
         case GGML_FTYPE_MOSTLY_IQ3_S:         wtype = GGML_TYPE_IQ3_S;    break;
         case GGML_FTYPE_MOSTLY_IQ2_S:         wtype = GGML_TYPE_IQ2_S;    break;
+        case GGML_FTYPE_MOSTLY_Q4_0_4_4:      wtype = GGML_TYPE_Q4_0_4_4; break;
+        case GGML_FTYPE_MOSTLY_Q4_0_4_8:      wtype = GGML_TYPE_Q4_0_4_8; break;
+        case GGML_FTYPE_MOSTLY_Q4_0_8_8:      wtype = GGML_TYPE_Q4_0_8_8; break;
         case GGML_FTYPE_UNKNOWN:              wtype = GGML_TYPE_COUNT; break;
         case GGML_FTYPE_MOSTLY_Q4_1_SOME_F16: wtype = GGML_TYPE_COUNT; break;
     }
@@ -9432,6 +9485,9 @@ static void ggml_compute_forward_add(
         case GGML_TYPE_IQ4_XS:
         case GGML_TYPE_IQ3_S:
         case GGML_TYPE_IQ2_S:
+        case GGML_TYPE_Q4_0_4_4:
+        case GGML_TYPE_Q4_0_4_8:
+        case GGML_TYPE_Q4_0_8_8:
             {
                 ggml_compute_forward_add_q_f32(params, dst);
             } break;
@@ -9807,6 +9863,9 @@ static void ggml_compute_forward_add1(
         case GGML_TYPE_IQ4_XS:
         case GGML_TYPE_IQ3_S:
         case GGML_TYPE_IQ2_S:
+        case GGML_TYPE_Q4_0_4_4:
+        case GGML_TYPE_Q4_0_4_8:
+        case GGML_TYPE_Q4_0_8_8:
             {
                 ggml_compute_forward_add1_q_f32(params, dst);
             } break;
@@ -9932,6 +9991,9 @@ static void ggml_compute_forward_acc(
         case GGML_TYPE_IQ4_XS:
         case GGML_TYPE_IQ3_S:
         case GGML_TYPE_IQ2_S:
+        case GGML_TYPE_Q4_0_4_4:
+        case GGML_TYPE_Q4_0_4_8:
+        case GGML_TYPE_Q4_0_8_8:
         default:
             {
                 GGML_ASSERT(false);
@@ -12134,6 +12196,12 @@ static void ggml_compute_forward_mul_mat(
     enum ggml_type    const vec_dot_type          = type_traits[type].vec_dot_type;
     ggml_from_float_t const from_float_to_vec_dot = type_traits[vec_dot_type].from_float;
     int64_t           const vec_dot_num_rows      = type_traits[type].nrows;
+    int64_t           const matmul_num_cols       = type_traits[type].ncols;
+    int64_t           const interleave_blcksize   = type_traits[type].interleave_blcksize;
+    ggml_from_float_to_mat_t const from_float_to_mat
+                                                  = type_traits[vec_dot_type].from_float_to_mat;
+    ggml_gemv_t       const gemv                  = type_traits[type].gemv;
+    ggml_gemm_t       const gemm                  = type_traits[type].gemm;
 
     GGML_ASSERT(ne0 == ne01);
     GGML_ASSERT(ne1 == ne11);
@@ -12192,7 +12260,16 @@ UseGgmlGemm1:;
 
         for (int64_t i13 = 0; i13 < ne13; ++i13) {
             for (int64_t i12 = 0; i12 < ne12; ++i12) {
-                for (int64_t i11 = ith; i11 < ne11; i11 += nth) {
+                int64_t i11_processed = 0;
+                if ((ggml_n_dims(src1) == 2) && from_float_to_mat && gemm) {
+                    for (int64_t i11 = ith * 4; i11 < ne11 - ne11 % 4; i11 += nth * 4) {
+                        from_float_to_mat((float *)((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11),
+                                          (void *)               (wdata + i13*nbw3 + i12*nbw2 + i11*nbw1),
+                                          4, ne10, interleave_blcksize);
+                    }
+                    i11_processed = ne11 - ne11 % 4;
+                }
+                for (int64_t i11 = i11_processed + ith; i11 < ne11; i11 += nth) {
                     from_float_to_vec_dot((float *)((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11),
                                           (void *)               (wdata + i13*nbw3 + i12*nbw2 + i11*nbw1),
                                            ne10);
@@ -12273,6 +12350,28 @@ UseGgmlGemm2:;
     const int64_t dr0 = (nr0 + nchunk0 - 1) / nchunk0;
     const int64_t dr1 = (nr1 + nchunk1 - 1) / nchunk1;
 
+    if ((ggml_n_dims(src0) == 2) && gemv) {
+        const void * src1_wdata      = (src1->type == vec_dot_type) ? src1->data : params->wdata;
+        const size_t src1_col_stride = ggml_is_contiguous(src1) || src1->type != vec_dot_type ? ggml_row_size(vec_dot_type, ne10) : nb11;
+        int64_t src0_start = (ith * ne01) / nth;
+        int64_t src0_end   = ((ith + 1) * ne01) / nth;
+        src0_start = (src0_start % matmul_num_cols) ? src0_start + matmul_num_cols - (src0_start % matmul_num_cols): src0_start;
+        src0_end   = (src0_end % matmul_num_cols) ? src0_end + matmul_num_cols - (src0_end % matmul_num_cols): src0_end;
+        if (src0_start >= src0_end) return;
+
+        // If there are more than three rows in src1, use gemm; otherwise, use gemv.
+        if (gemm && (ne11 > 3)) {
+            gemm(ne00, (float *)((char *) dst->data) + src0_start, ne01, (const char *) src0->data + src0_start * nb01,
+                 (const char *) src1_wdata, ne11 - ne11 % 4, src0_end - src0_start);
+        }
+        for (int iter = gemm ? ne11 - ne11 % 4 : 0; iter < ne11; iter++) {
+            gemv(ne00, (float *)((char *) dst->data + (iter * nb1)) + src0_start, ne01,
+                 (const char *) src0->data + src0_start * nb01, (const char *) src1_wdata + (src1_col_stride * iter), 1,
+                 src0_end - src0_start);
+        }
+        return;
+    }
+
     // The first chunk comes from our thread_id, the rest will get auto-assigned.
     int current_chunk = ith;
 
@@ -12318,6 +12417,8 @@ static void ggml_compute_forward_mul_mat_id(
     ggml_vec_dot_t    const vec_dot               = type_traits[type].vec_dot;
     enum ggml_type    const vec_dot_type          = type_traits[type].vec_dot_type;
     ggml_from_float_t const from_float_to_vec_dot = type_traits[vec_dot_type].from_float;
+    int64_t           const matmul_num_cols       = type_traits[type].ncols;
+    ggml_gemv_t       const gemv                  = type_traits[type].gemv;
 
     // we don't support permuted src0 or src1
     GGML_ASSERT(nb00 == ggml_type_size(type));
@@ -12403,6 +12504,34 @@ static void ggml_compute_forward_mul_mat_id(
         const int64_t nr0 = ne01; // src0 rows
         const int64_t nr1 = cne1; // src1 rows
 
+        if (((ggml_n_dims(src0) - 1) == 2) && gemv) {
+            int64_t src0_cur_start = (ith * ne01) / nth;
+            int64_t src0_cur_end   = ((ith + 1) * ne01) / nth;
+            src0_cur_start = (src0_cur_start % matmul_num_cols) ? src0_cur_start + matmul_num_cols - (src0_cur_start % matmul_num_cols): src0_cur_start;
+            src0_cur_end   = (src0_cur_end % matmul_num_cols) ? src0_cur_end + matmul_num_cols - (src0_cur_end % matmul_num_cols): src0_cur_end;
+            if (src0_cur_start >= src0_cur_end) return;
+
+            for (int ir1 = 0; ir1 < nr1; ir1++) {
+                struct mmid_row_mapping row_mapping = MMID_MATRIX_ROW(cur_a, ir1);
+                const int id       = row_mapping.i1; // selected expert index
+
+                const int64_t  i11 = id % ne11;
+                const int64_t  i12 = row_mapping.i2; // row index in src1
+
+                const int64_t  i1 = id;  // selected expert index
+                const int64_t  i2 = i12; // row
+
+                const char * src1_col = (const char *) wdata +
+                    (src1_cont || src1->type != vec_dot_type
+                    ? (i11        + i12 * ne11) * row_size
+                    : (i11 * nb11 + i12 * nb12));
+
+                gemv(ne00, (float *)((char *) dst->data + (i1 * nb1 + i2 * nb2)) + src0_cur_start, ne01,
+                     (const char *) src0_cur + src0_cur_start * nb01, src1_col, 1, src0_cur_end - src0_cur_start);
+            }
+            continue;
+        }
+
         // distribute the thread work across the inner or outer loop based on which one is larger
 
         const int64_t nth0 = nr0 > nr1 ? nth : 1; // parallelize by src0 rows
@@ -12704,6 +12833,9 @@ static void ggml_compute_forward_out_prod(
         case GGML_TYPE_IQ4_XS:
         case GGML_TYPE_IQ3_S:
         case GGML_TYPE_IQ2_S:
+        case GGML_TYPE_Q4_0_4_4:
+        case GGML_TYPE_Q4_0_4_8:
+        case GGML_TYPE_Q4_0_8_8:
             {
                 ggml_compute_forward_out_prod_q_f32(params, dst);
             } break;
@@ -12889,6 +13021,9 @@ static void ggml_compute_forward_set(
         case GGML_TYPE_IQ4_XS:
         case GGML_TYPE_IQ3_S:
         case GGML_TYPE_IQ2_S:
+        case GGML_TYPE_Q4_0_4_4:
+        case GGML_TYPE_Q4_0_4_8:
+        case GGML_TYPE_Q4_0_8_8:
         default:
             {
                 GGML_ASSERT(false);
@@ -13148,6 +13283,9 @@ static void ggml_compute_forward_get_rows(
         case GGML_TYPE_IQ4_XS:
         case GGML_TYPE_IQ3_S:
         case GGML_TYPE_IQ2_S:
+        case GGML_TYPE_Q4_0_4_4:
+        case GGML_TYPE_Q4_0_4_8:
+        case GGML_TYPE_Q4_0_8_8:
             {
                 ggml_compute_forward_get_rows_q(params, dst);
             } break;
@@ -13734,6 +13872,9 @@ static void ggml_compute_forward_clamp(
         case GGML_TYPE_IQ3_S:
         case GGML_TYPE_IQ2_S:
         case GGML_TYPE_Q8_K:
+        case GGML_TYPE_Q4_0_4_4:
+        case GGML_TYPE_Q4_0_4_8:
+        case GGML_TYPE_Q4_0_8_8:
         case GGML_TYPE_I8:
         case GGML_TYPE_I16:
         case GGML_TYPE_I32:
@@ -20457,6 +20598,9 @@ size_t ggml_quantize_chunk(
         case GGML_TYPE_IQ1_M:   result = quantize_iq1_m  (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
         case GGML_TYPE_IQ4_NL:  result = quantize_iq4_nl (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
         case GGML_TYPE_IQ4_XS:  result = quantize_iq4_xs (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_Q4_0_4_4: result = quantize_q4_0_4x4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_Q4_0_4_8: result = quantize_q4_0_4x8(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_Q4_0_8_8: result = quantize_q4_0_8x8(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
         case GGML_TYPE_F16:
             {
                 size_t elemsize = sizeof(ggml_fp16_t);
@@ -21759,8 +21903,6 @@ int ggml_cpu_has_neon(void) {
 
 int ggml_cpu_has_sve(void) {
 #if defined(__ARM_FEATURE_SVE)
-    // TODO: Currently, SVE 256 bit is only supported.
-    GGML_ASSERT(svcntb() == QK8_0);
     return 1;
 #else
     return 0;
diff --git a/include/llama.h b/include/llama.h
index bb4b05ba63671..3970c3aebcd62 100644
--- a/include/llama.h
+++ b/include/llama.h
@@ -162,6 +162,9 @@ extern "C" {
         LLAMA_FTYPE_MOSTLY_IQ4_XS        = 30, // except 1d tensors
         LLAMA_FTYPE_MOSTLY_IQ1_M         = 31, // except 1d tensors
         LLAMA_FTYPE_MOSTLY_BF16          = 32, // except 1d tensors
+        LLAMA_FTYPE_MOSTLY_Q4_0_4_4      = 33, // except 1d tensors
+        LLAMA_FTYPE_MOSTLY_Q4_0_4_8      = 34, // except 1d tensors
+        LLAMA_FTYPE_MOSTLY_Q4_0_8_8      = 35, // except 1d tensors
 
         LLAMA_FTYPE_GUESSED = 1024, // not specified in the model file
     };
diff --git a/src/llama.cpp b/src/llama.cpp
index 98a242081ca03..b19d786e23643 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -3788,6 +3788,9 @@ struct llama_model_loader {
                 case GGML_TYPE_IQ4_NL:  ftype = LLAMA_FTYPE_MOSTLY_IQ4_NL;  break;
                 case GGML_TYPE_IQ4_XS:  ftype = LLAMA_FTYPE_MOSTLY_IQ4_XS;  break;
                 case GGML_TYPE_IQ3_S:   ftype = LLAMA_FTYPE_MOSTLY_IQ3_S;   break;
+                case GGML_TYPE_Q4_0_4_4: ftype = LLAMA_FTYPE_MOSTLY_Q4_0_4_4; break;
+                case GGML_TYPE_Q4_0_4_8: ftype = LLAMA_FTYPE_MOSTLY_Q4_0_4_8; break;
+                case GGML_TYPE_Q4_0_8_8: ftype = LLAMA_FTYPE_MOSTLY_Q4_0_8_8; break;
                 default:
                     {
                         LLAMA_LOG_WARN("%s: unknown type %s\n", __func__, ggml_type_name(type_max));
@@ -4481,6 +4484,9 @@ static std::string llama_model_ftype_name(llama_ftype ftype) {
         case LLAMA_FTYPE_MOSTLY_IQ4_XS: return "IQ4_XS - 4.25 bpw";
         case LLAMA_FTYPE_MOSTLY_IQ3_S:  return "IQ3_S - 3.4375 bpw";
         case LLAMA_FTYPE_MOSTLY_IQ3_M:  return "IQ3_S mix - 3.66 bpw";
+        case LLAMA_FTYPE_MOSTLY_Q4_0_4_4: return "Q4_0_4_4";
+        case LLAMA_FTYPE_MOSTLY_Q4_0_4_8: return "Q4_0_4_8";
+        case LLAMA_FTYPE_MOSTLY_Q4_0_8_8: return "Q4_0_8_8";
 
         default: return "unknown, may not work";
     }
@@ -17768,6 +17774,10 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
             else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XXS) {
                 new_type = GGML_TYPE_IQ3_S;
             }
+            else if (new_type == GGML_TYPE_Q4_0_4_4 || new_type == GGML_TYPE_Q4_0_4_8 ||
+                     new_type == GGML_TYPE_Q4_0_8_8) {
+                new_type = GGML_TYPE_Q4_0;
+            }
         }
     } else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_XXS || ftype == LLAMA_FTYPE_MOSTLY_IQ2_XS || ftype == LLAMA_FTYPE_MOSTLY_IQ1_S ||
                ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M    || ftype == LLAMA_FTYPE_MOSTLY_IQ1_M) {
@@ -18080,6 +18090,9 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
         case LLAMA_FTYPE_MOSTLY_IQ4_XS:  default_type = GGML_TYPE_IQ4_XS;  break;
         case LLAMA_FTYPE_MOSTLY_IQ3_S:   default_type = GGML_TYPE_IQ3_S;   break;
         case LLAMA_FTYPE_MOSTLY_IQ3_M:   default_type = GGML_TYPE_IQ3_S;   break;
+        case LLAMA_FTYPE_MOSTLY_Q4_0_4_4: default_type = GGML_TYPE_Q4_0_4_4; break;
+        case LLAMA_FTYPE_MOSTLY_Q4_0_4_8: default_type = GGML_TYPE_Q4_0_4_8; break;
+        case LLAMA_FTYPE_MOSTLY_Q4_0_8_8: default_type = GGML_TYPE_Q4_0_8_8; break;
 
         default: throw std::runtime_error(format("invalid output file type %d\n", ftype));
     }
@@ -18390,6 +18403,14 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
                 f32_data = (float *) f32_conv_buf.data();
             }
 
+            int chunk_size_multiplier = 1;
+            if (new_type == GGML_TYPE_Q4_0_4_4 || new_type == GGML_TYPE_Q4_0_4_8 || new_type == GGML_TYPE_Q4_0_8_8) {
+                if ((new_type == GGML_TYPE_Q4_0_8_8) && (tensor->ne[1] % 8 != 0)) new_type = GGML_TYPE_Q4_0;
+                else if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_Q4_0;
+                if (new_type == GGML_TYPE_Q4_0_8_8) chunk_size_multiplier = 8;
+                else if (new_type == GGML_TYPE_Q4_0_4_4 || new_type == GGML_TYPE_Q4_0_4_8) chunk_size_multiplier = 4;
+            }
+
             LLAMA_LOG_INFO("converting to %s .. ", ggml_type_name(new_type));
             fflush(stdout);
 
@@ -18402,7 +18423,8 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
             const int64_t nrows = tensor->ne[1];
 
             static const int64_t min_chunk_size = 32 * 512;
-            const int64_t chunk_size = n_per_row >= min_chunk_size ? n_per_row : n_per_row * ((min_chunk_size + n_per_row - 1)/n_per_row);
+            const int64_t chunk_size = (n_per_row >= min_chunk_size ? n_per_row : n_per_row * ((min_chunk_size + n_per_row - 1)/n_per_row)) *
+                                       chunk_size_multiplier;
 
             const int64_t nelements_matrix = tensor->ne[0] * tensor->ne[1];
             const int64_t nchunk = (nelements_matrix + chunk_size - 1)/chunk_size;

From 6b2a849d1f43d46b82d2f9c08c3275137b528784 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Wed, 10 Jul 2024 15:23:29 +0300
Subject: [PATCH 157/326] ggml : move sgemm sources to llamafile subfolder
 (#8394)

ggml-ci
---
 Makefile                           | 8 ++++----
 ggml/CMakeLists.txt                | 2 +-
 ggml/src/CMakeLists.txt            | 6 +++---
 ggml/src/ggml.c                    | 3 +--
 ggml/src/{ => llamafile}/sgemm.cpp | 0
 ggml/src/{ => llamafile}/sgemm.h   | 0
 6 files changed, 9 insertions(+), 10 deletions(-)
 rename ggml/src/{ => llamafile}/sgemm.cpp (100%)
 rename ggml/src/{ => llamafile}/sgemm.h (100%)

diff --git a/Makefile b/Makefile
index b70ebaed54638..68197fef80019 100644
--- a/Makefile
+++ b/Makefile
@@ -554,7 +554,7 @@ endif # GGML_BLIS
 
 ifndef GGML_NO_LLAMAFILE
 	MK_CPPFLAGS += -DGGML_USE_LLAMAFILE
-	OBJ_GGML    += ggml/src/sgemm.o
+	OBJ_GGML    += ggml/src/llamafile/sgemm.o
 endif
 
 ifdef GGML_RPC
@@ -983,9 +983,9 @@ ggml/src/ggml-blas.o: \
 	$(CXX) $(CXXFLAGS) -c $< -o $@
 
 ifndef GGML_NO_LLAMAFILE
-ggml/src/sgemm.o: \
-	ggml/src/sgemm.cpp \
-	ggml/src/sgemm.h \
+ggml/src/llamafile/sgemm.o: \
+	ggml/src/llamafile/sgemm.cpp \
+	ggml/src/llamafile/sgemm.h \
 	ggml/include/ggml.h
 	$(CXX) $(CXXFLAGS) -c $< -o $@
 endif # GGML_NO_LLAMAFILE
diff --git a/ggml/CMakeLists.txt b/ggml/CMakeLists.txt
index 0d0d52d575971..649ac3dcc4f63 100644
--- a/ggml/CMakeLists.txt
+++ b/ggml/CMakeLists.txt
@@ -104,7 +104,7 @@ option(GGML_ACCELERATE                      "ggml: enable Accelerate framework"
 option(GGML_BLAS                            "ggml: use BLAS"                                  ${GGML_BLAS_DEFAULT})
 set(GGML_BLAS_VENDOR ${GGML_BLAS_VENDOR_DEFAULT} CACHE STRING
                                             "ggml: BLAS library vendor")
-option(GGML_LLAMAFILE                       "ggml: use ggml SGEMM"                            OFF)
+option(GGML_LLAMAFILE                       "ggml: use LLAMAFILE"                             OFF)
 
 option(GGML_CUDA                            "ggml: use CUDA"                                  OFF)
 option(GGML_CUDA_FORCE_DMMV                 "ggml: use dmmv instead of mmvq CUDA kernels"     OFF)
diff --git a/ggml/src/CMakeLists.txt b/ggml/src/CMakeLists.txt
index aae5b8e9fe35c..c5ee7e4255ee5 100644
--- a/ggml/src/CMakeLists.txt
+++ b/ggml/src/CMakeLists.txt
@@ -238,12 +238,12 @@ if (GGML_BLAS)
 endif()
 
 if (GGML_LLAMAFILE)
-    message(STATUS "Using ggml SGEMM")
+    message(STATUS "Using llamafile")
 
     add_compile_definitions(GGML_USE_LLAMAFILE)
 
-    set(GGML_HEADERS_LLAMAFILE sgemm.h)
-    set(GGML_SOURCES_LLAMAFILE sgemm.cpp)
+    set(GGML_HEADERS_LLAMAFILE llamafile/sgemm.h)
+    set(GGML_SOURCES_LLAMAFILE llamafile/sgemm.cpp)
 endif()
 
 if (GGML_CUDA)
diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c
index c0aced3d2d069..1bb731e16d51d 100644
--- a/ggml/src/ggml.c
+++ b/ggml/src/ggml.c
@@ -6,7 +6,6 @@
 #include "ggml.h"
 #include "ggml-aarch64.h"
 
-
 #if defined(_MSC_VER) || defined(__MINGW32__)
 #include  // using malloc.h with MSC/MINGW
 #elif !defined(__FreeBSD__) && !defined(__NetBSD__) && !defined(__OpenBSD__)
@@ -43,7 +42,7 @@
 #endif
 
 #ifdef GGML_USE_LLAMAFILE
-#include "sgemm.h"
+#include 
 #endif
 
 #if defined(_MSC_VER)
diff --git a/ggml/src/sgemm.cpp b/ggml/src/llamafile/sgemm.cpp
similarity index 100%
rename from ggml/src/sgemm.cpp
rename to ggml/src/llamafile/sgemm.cpp
diff --git a/ggml/src/sgemm.h b/ggml/src/llamafile/sgemm.h
similarity index 100%
rename from ggml/src/sgemm.h
rename to ggml/src/llamafile/sgemm.h

From f4444d992c16b6b9442f4770c7c3a10b19a08343 Mon Sep 17 00:00:00 2001
From: AidanBeltonS 
Date: Wed, 10 Jul 2024 16:10:49 +0100
Subject: [PATCH 158/326] [SYCL] Use multi_ptr to clean up deprecated warnings
 (#8256)

---
 ggml/src/ggml-sycl/common.hpp  |   6 ++
 ggml/src/ggml-sycl/convert.cpp |   2 +-
 ggml/src/ggml-sycl/mmq.cpp     | 184 ++++++++++++++++-----------------
 ggml/src/ggml-sycl/norm.cpp    |   6 +-
 ggml/src/ggml-sycl/softmax.cpp |   2 +-
 5 files changed, 103 insertions(+), 97 deletions(-)

diff --git a/ggml/src/ggml-sycl/common.hpp b/ggml/src/ggml-sycl/common.hpp
index 9a1c161b69db5..68d41411b5ece 100644
--- a/ggml/src/ggml-sycl/common.hpp
+++ b/ggml/src/ggml-sycl/common.hpp
@@ -346,4 +346,10 @@ inline sycl::vec vec_aligned_load(const Tp* aligned_ptr) {
     return *reinterpret_cast*>(aligned_ptr);
 }
 
+// Helper for accessing pointers with no warnings
+template 
+static __dpct_inline__ Tp* get_pointer(sycl::local_accessor acc) {
+    return acc.template get_multi_ptr().get();
+}
+
 #endif // GGML_SYCL_COMMON_HPP
diff --git a/ggml/src/ggml-sycl/convert.cpp b/ggml/src/ggml-sycl/convert.cpp
index a15271b516fa8..39c28753cf85c 100644
--- a/ggml/src/ggml-sycl/convert.cpp
+++ b/ggml/src/ggml-sycl/convert.cpp
@@ -158,7 +158,7 @@ static void dequantize_row_q4_K_sycl(const void *vx, dst_t *y, const int k,
                                                    sycl::range<3>(1, 1, 32),
                                                sycl::range<3>(1, 1, 32)),
                              [=](sycl::nd_item<3> item_ct1) {
-                                 dequantize_block_q4_K(vx, y, scale_local_acc.get_pointer(), item_ct1);
+                                 dequantize_block_q4_K(vx, y, get_pointer(scale_local_acc), item_ct1);
                              });
         });
     }
diff --git a/ggml/src/ggml-sycl/mmq.cpp b/ggml/src/ggml-sycl/mmq.cpp
index b514f00404e1f..3107ba91948c6 100644
--- a/ggml/src/ggml-sycl/mmq.cpp
+++ b/ggml/src/ggml-sycl/mmq.cpp
@@ -1835,10 +1835,10 @@ static void ggml_mul_mat_q4_0_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q4_0(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_qs_q4_0_acc_ct1.get_pointer(),
-                            tile_x_d_q4_0_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_qs_q4_0_acc_ct1),
+                            get_pointer(tile_x_d_q4_0_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -1870,10 +1870,10 @@ static void ggml_mul_mat_q4_0_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q4_0(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_qs_q4_0_acc_ct1.get_pointer(),
-                            tile_x_d_q4_0_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_qs_q4_0_acc_ct1),
+                            get_pointer(tile_x_d_q4_0_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -1950,10 +1950,10 @@ static void ggml_mul_mat_q4_1_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q4_1(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_qs_q4_1_acc_ct1.get_pointer(),
-                            tile_x_dm_q4_1_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_qs_q4_1_acc_ct1),
+                            get_pointer(tile_x_dm_q4_1_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -1985,10 +1985,10 @@ static void ggml_mul_mat_q4_1_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q4_1(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_qs_q4_1_acc_ct1.get_pointer(),
-                            tile_x_dm_q4_1_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_qs_q4_1_acc_ct1),
+                            get_pointer(tile_x_dm_q4_1_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -2065,10 +2065,10 @@ static void ggml_mul_mat_q5_0_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q5_0(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_ql_q5_0_acc_ct1.get_pointer(),
-                            tile_x_d_q5_0_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q5_0_acc_ct1),
+                            get_pointer(tile_x_d_q5_0_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -2100,10 +2100,10 @@ static void ggml_mul_mat_q5_0_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q5_0(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_ql_q5_0_acc_ct1.get_pointer(),
-                            tile_x_d_q5_0_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q5_0_acc_ct1),
+                            get_pointer(tile_x_d_q5_0_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -2180,10 +2180,10 @@ static void ggml_mul_mat_q5_1_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q5_1(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_ql_q5_1_acc_ct1.get_pointer(),
-                            tile_x_dm_q5_1_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q5_1_acc_ct1),
+                            get_pointer(tile_x_dm_q5_1_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -2215,10 +2215,10 @@ static void ggml_mul_mat_q5_1_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q5_1(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_ql_q5_1_acc_ct1.get_pointer(),
-                            tile_x_dm_q5_1_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q5_1_acc_ct1),
+                            get_pointer(tile_x_dm_q5_1_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -2295,10 +2295,10 @@ static void ggml_mul_mat_q8_0_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q8_0(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_qs_q8_0_acc_ct1.get_pointer(),
-                            tile_x_d_q8_0_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_qs_q8_0_acc_ct1),
+                            get_pointer(tile_x_d_q8_0_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -2330,10 +2330,10 @@ static void ggml_mul_mat_q8_0_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q8_0(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_qs_q8_0_acc_ct1.get_pointer(),
-                            tile_x_d_q8_0_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_qs_q8_0_acc_ct1),
+                            get_pointer(tile_x_d_q8_0_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -2412,11 +2412,11 @@ static void ggml_mul_mat_q2_K_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q2_K(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_ql_q2_K_acc_ct1.get_pointer(),
-                            tile_x_dm_q2_K_acc_ct1.get_pointer(),
-                            tile_x_sc_q2_K_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q2_K_acc_ct1),
+                            get_pointer(tile_x_dm_q2_K_acc_ct1),
+                            get_pointer(tile_x_sc_q2_K_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -2450,11 +2450,11 @@ static void ggml_mul_mat_q2_K_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q2_K(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_ql_q2_K_acc_ct1.get_pointer(),
-                            tile_x_dm_q2_K_acc_ct1.get_pointer(),
-                            tile_x_sc_q2_K_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q2_K_acc_ct1),
+                            get_pointer(tile_x_dm_q2_K_acc_ct1),
+                            get_pointer(tile_x_sc_q2_K_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -2537,12 +2537,12 @@ static void ggml_mul_mat_q3_K_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q3_K(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_ql_q3_K_acc_ct1.get_pointer(),
-                            tile_x_dm_q3_K_acc_ct1.get_pointer(),
-                            tile_x_qh_q3_K_acc_ct1.get_pointer(),
-                            tile_x_sc_q3_K_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q3_K_acc_ct1),
+                            get_pointer(tile_x_dm_q3_K_acc_ct1),
+                            get_pointer(tile_x_qh_q3_K_acc_ct1),
+                            get_pointer(tile_x_sc_q3_K_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -2578,12 +2578,12 @@ static void ggml_mul_mat_q3_K_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q3_K(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_ql_q3_K_acc_ct1.get_pointer(),
-                            tile_x_dm_q3_K_acc_ct1.get_pointer(),
-                            tile_x_qh_q3_K_acc_ct1.get_pointer(),
-                            tile_x_sc_q3_K_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q3_K_acc_ct1),
+                            get_pointer(tile_x_dm_q3_K_acc_ct1),
+                            get_pointer(tile_x_qh_q3_K_acc_ct1),
+                            get_pointer(tile_x_sc_q3_K_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -2663,11 +2663,11 @@ static void ggml_mul_mat_q4_K_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q4_K(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_ql_q4_K_acc_ct1.get_pointer(),
-                            tile_x_dm_q4_K_acc_ct1.get_pointer(),
-                            tile_x_sc_q4_K_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q4_K_acc_ct1),
+                            get_pointer(tile_x_dm_q4_K_acc_ct1),
+                            get_pointer(tile_x_sc_q4_K_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -2701,11 +2701,11 @@ static void ggml_mul_mat_q4_K_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q4_K(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_ql_q4_K_acc_ct1.get_pointer(),
-                            tile_x_dm_q4_K_acc_ct1.get_pointer(),
-                            tile_x_sc_q4_K_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q4_K_acc_ct1),
+                            get_pointer(tile_x_dm_q4_K_acc_ct1),
+                            get_pointer(tile_x_sc_q4_K_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -2784,11 +2784,11 @@ static void ggml_mul_mat_q5_K_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q5_K(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_ql_q5_K_acc_ct1.get_pointer(),
-                            tile_x_dm_q5_K_acc_ct1.get_pointer(),
-                            tile_x_sc_q5_K_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q5_K_acc_ct1),
+                            get_pointer(tile_x_dm_q5_K_acc_ct1),
+                            get_pointer(tile_x_sc_q5_K_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -2822,11 +2822,11 @@ static void ggml_mul_mat_q5_K_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q5_K(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_ql_q5_K_acc_ct1.get_pointer(),
-                            tile_x_dm_q5_K_acc_ct1.get_pointer(),
-                            tile_x_sc_q5_K_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_q5_K_acc_ct1),
+                            get_pointer(tile_x_dm_q5_K_acc_ct1),
+                            get_pointer(tile_x_sc_q5_K_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -2905,11 +2905,11 @@ static void ggml_mul_mat_q6_K_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q6_K(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_ql_acc_ct1.get_pointer(),
-                            tile_x_dm_acc_ct1.get_pointer(),
-                            tile_x_sc_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_acc_ct1),
+                            get_pointer(tile_x_dm_acc_ct1),
+                            get_pointer(tile_x_sc_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
@@ -2943,11 +2943,11 @@ static void ggml_mul_mat_q6_K_q8_1_sycl(const void *vx, const void *vy,
                         mul_mat_q6_K(
                             vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y,
                             nrows_dst, item_ct1,
-                            tile_x_ql_acc_ct1.get_pointer(),
-                            tile_x_dm_acc_ct1.get_pointer(),
-                            tile_x_sc_acc_ct1.get_pointer(),
-                            tile_y_qs_acc_ct1.get_pointer(),
-                            tile_y_ds_acc_ct1.get_pointer());
+                            get_pointer(tile_x_ql_acc_ct1),
+                            get_pointer(tile_x_dm_acc_ct1),
+                            get_pointer(tile_x_sc_acc_ct1),
+                            get_pointer(tile_y_qs_acc_ct1),
+                            get_pointer(tile_y_ds_acc_ct1));
                     });
             });
         }
diff --git a/ggml/src/ggml-sycl/norm.cpp b/ggml/src/ggml-sycl/norm.cpp
index e0c5dfeca96ca..cccf87d069a31 100644
--- a/ggml/src/ggml-sycl/norm.cpp
+++ b/ggml/src/ggml-sycl/norm.cpp
@@ -218,7 +218,7 @@ static void norm_f32_sycl(const float* x, float* dst, const int ncols,
                 [=](sycl::nd_item<3> item_ct1)
                 [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                     norm_f32(x, dst, ncols, eps, item_ct1,
-                        s_sum_acc_ct1.get_pointer(), work_group_size);
+                        get_pointer(s_sum_acc_ct1), work_group_size);
                 });
             });
     }
@@ -265,7 +265,7 @@ static void group_norm_f32_sycl(const float* x, float* dst,
                 [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                     group_norm_f32(x, dst, group_size, ne_elements,
                         eps_ct4, item_ct1,
-                        s_sum_acc_ct1.get_pointer(), work_group_size);
+                        get_pointer(s_sum_acc_ct1), work_group_size);
                 });
             });
     }
@@ -306,7 +306,7 @@ static void rms_norm_f32_sycl(const float* x, float* dst, const int ncols,
                 [=](sycl::nd_item<3> item_ct1)
                 [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                     rms_norm_f32(x, dst, ncols, eps, item_ct1,
-                        s_sum_acc_ct1.get_pointer(), work_group_size);
+                        get_pointer(s_sum_acc_ct1), work_group_size);
                 });
             });
     }
diff --git a/ggml/src/ggml-sycl/softmax.cpp b/ggml/src/ggml-sycl/softmax.cpp
index e624b6ba31b0d..c5d9a837eb794 100644
--- a/ggml/src/ggml-sycl/softmax.cpp
+++ b/ggml/src/ggml-sycl/softmax.cpp
@@ -136,7 +136,7 @@ static void soft_max_f32_submitter(const float * x, const float * mask, float *
                 soft_max_f32(x, mask, dst, ncols_par,
                                                                              nrows_y, scale, max_bias, m0,
                                                                              m1, n_head_log2, item_ct1,
-                                                                             local_buf_acc.get_pointer());
+                                                                             get_pointer(local_buf_acc));
             });
     });
 }

From dd07a123b79f9bd9e8a4ba0447427b3083e9347a Mon Sep 17 00:00:00 2001
From: Clint Herron 
Date: Wed, 10 Jul 2024 12:35:18 -0400
Subject: [PATCH 159/326] Name Migration: Build the deprecation-warning 'main'
 binary every time (#8404)

* Modify the deprecation-warning 'main' binary to build every time, instead of only when a legacy binary is present. This is to help users of tutorials and other instruction sets from knowing what to do when the 'main' binary is missing and they are trying to follow instructions.

* Adjusting 'server' name-deprecation binary to build all the time, similar to the 'main' legacy name binary.
---
 Makefile | 24 ++++++++----------------
 1 file changed, 8 insertions(+), 16 deletions(-)

diff --git a/Makefile b/Makefile
index 68197fef80019..668b38b99c312 100644
--- a/Makefile
+++ b/Makefile
@@ -1513,15 +1513,17 @@ llama-q8dot: pocs/vdot/q8dot.cpp ggml/src/ggml.o \
 # Mark legacy binary targets as .PHONY so that they are always checked.
 .PHONY: main quantize perplexity embedding server finetune
 
+# NOTE: We currently will always build the deprecation-warning `main` and `server` binaries to help users migrate.
+#  Eventually we will want to remove these target from building all the time.
 main: examples/deprecation-warning/deprecation-warning.cpp
-ifneq (,$(wildcard main))
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
 	$(CXX) $(CXXFLAGS) $(filter-out $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
-	@echo "#########"
-	@echo "WARNING: The 'main' binary is deprecated. Please use 'llama-cli' instead."
-	@echo "  Remove the 'main' binary to remove this warning."
-	@echo "#########"
-endif
+	@echo "NOTICE: The 'main' binary is deprecated. Please use 'llama-cli' instead."
+
+server: examples/deprecation-warning/deprecation-warning.cpp
+	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
+	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+	@echo "NOTICE: The 'server' binary is deprecated. Please use 'llama-server' instead."
 
 quantize: examples/deprecation-warning/deprecation-warning.cpp
 ifneq (,$(wildcard quantize))
@@ -1553,16 +1555,6 @@ ifneq (,$(wildcard embedding))
 	@echo "#########"
 endif
 
-server: examples/deprecation-warning/deprecation-warning.cpp
-ifneq (,$(wildcard server))
-	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
-	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
-	@echo "#########"
-	@echo "WARNING: The 'server' binary is deprecated. Please use 'llama-server' instead."
-	@echo "  Remove the 'server' binary to remove this warning."
-	@echo "#########"
-endif
-
 finetune: examples/deprecation-warning/deprecation-warning.cpp
 ifneq (,$(wildcard finetune))
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)

From 278d0e18469aacf505be18ce790a63c7cc31be26 Mon Sep 17 00:00:00 2001
From: Clint Herron 
Date: Wed, 10 Jul 2024 20:08:17 -0400
Subject: [PATCH 160/326] Initialize default slot sampling parameters from the
 global context. (#8418)

---
 examples/server/server.cpp | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/examples/server/server.cpp b/examples/server/server.cpp
index 8feff67029da1..efd426289a54c 100644
--- a/examples/server/server.cpp
+++ b/examples/server/server.cpp
@@ -737,6 +737,8 @@ struct server_context {
             slot.ga_n = ga_n;
             slot.ga_w = ga_w;
 
+            slot.sparams = params.sparams;
+
             slot.reset();
 
             slots.push_back(slot);

From 7a221b672e49dfae459b1af27210ba3f2b5419b6 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Thu, 11 Jul 2024 10:21:30 +0300
Subject: [PATCH 161/326] llama : use F32 precision in Qwen2 attention and no
 FA (#8412)

---
 src/llama.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/llama.cpp b/src/llama.cpp
index b19d786e23643..ed77ed918e554 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -8134,7 +8134,7 @@ static struct ggml_tensor * llm_build_kqv(
         struct ggml_tensor * kq = ggml_mul_mat(ctx, k, q);
         cb(kq, "kq", il);
 
-        if (model.arch == LLM_ARCH_PHI2 || model.arch == LLM_ARCH_PHI3 || model.arch == LLM_ARCH_GPTNEOX) {
+        if (model.arch == LLM_ARCH_PHI2 || model.arch == LLM_ARCH_PHI3 || model.arch == LLM_ARCH_GPTNEOX || model.arch == LLM_ARCH_QWEN2) {
             // for this arch, we need to perform the KQ multiplication with F32 precision, otherwise we get NaNs
             // ref: https://github.com/ggerganov/llama.cpp/pull/4490#issuecomment-1859055847
             ggml_mul_mat_set_prec(kq, GGML_PREC_F32);

From 9a55ffe6fbf7f19c865f8f277ca7cd585cc0b094 Mon Sep 17 00:00:00 2001
From: compilade 
Date: Thu, 11 Jul 2024 03:41:48 -0400
Subject: [PATCH 162/326] tokenize : add --no-parse-special option (#8423)

This should allow more easily explaining
how parse_special affects tokenization.
---
 examples/tokenize/tokenize.cpp | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/examples/tokenize/tokenize.cpp b/examples/tokenize/tokenize.cpp
index 0180c87d863bf..2afb6024ce1bf 100644
--- a/examples/tokenize/tokenize.cpp
+++ b/examples/tokenize/tokenize.cpp
@@ -29,6 +29,7 @@ static void print_usage_information(const char * argv0, FILE * stream) {
     fprintf(stream, "    -p PROMPT, --prompt PROMPT           read prompt from the argument.\n");
     fprintf(stream, "    --stdin                              read prompt from standard input.\n");
     fprintf(stream, "    --no-bos                             do not ever add a BOS token to the prompt, even if normally the model uses a BOS token.\n");
+    fprintf(stream, "    --no-parse-special                   do not parse control tokens.\n");
     fprintf(stream, "    --log-disable                        disable logs. Makes stderr quiet when loading the model.\n");
     fprintf(stream, "    --show-count                         print the total number of tokens.\n");
 }
@@ -195,6 +196,7 @@ int main(int raw_argc, char ** raw_argv) {
     // variables where to put any arguments we see.
     bool printing_ids = false;
     bool no_bos = false;
+    bool no_parse_special = false;
     bool disable_logging = false;
     bool show_token_count = false;
     const char * model_path = NULL;
@@ -229,6 +231,9 @@ int main(int raw_argc, char ** raw_argv) {
         else if (arg == "--no-bos") {
             no_bos = true;
         }
+        else if (arg == "--no-parse-special") {
+            no_parse_special = true;
+        }
         else if (arg == "-p" || arg == "--prompt") {
             if (prompt_set) {
                 fprintf(stderr, "Error: -p or --prompt specified multiple times.\n");
@@ -359,9 +364,10 @@ int main(int raw_argc, char ** raw_argv) {
 
     const bool model_wants_add_bos = llama_should_add_bos_token(model);
     const bool add_bos = model_wants_add_bos && !no_bos;
+    const bool parse_special = !no_parse_special;
 
     std::vector tokens;
-    tokens = ::llama_tokenize(model, prompt, add_bos, true);
+    tokens = ::llama_tokenize(model, prompt, add_bos, parse_special);
 
     if (printing_ids) {
         printf("[");

From a977c115448e40856fb9cbe3ceb6d8ce802553b0 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Thu, 11 Jul 2024 11:20:40 +0300
Subject: [PATCH 163/326] gitignore : deprecated binaries

---
 .gitignore | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/.gitignore b/.gitignore
index 4866f612277f7..7c7dee0c607aa 100644
--- a/.gitignore
+++ b/.gitignore
@@ -61,6 +61,11 @@ llama-batched-swift
 out/
 tmp/
 
+# Deprecated
+
+/main
+/server
+
 # CI
 
 !.github/workflows/*.yml

From 808aba39161e5d7ca2ff24110b5aa14d2e536988 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= 
Date: Thu, 11 Jul 2024 16:47:47 +0200
Subject: [PATCH 164/326] CUDA: optimize and refactor MMQ (#8416)

* CUDA: optimize and refactor MMQ

* explicit q8_1 memory layouts, add documentation
---
 ggml/src/ggml-cuda/mma.cuh      |    4 +
 ggml/src/ggml-cuda/mmq.cuh      | 1319 +++++++++++++++++--------------
 ggml/src/ggml-cuda/quantize.cu  |  107 ++-
 ggml/src/ggml-cuda/quantize.cuh |    6 +-
 ggml/src/ggml-cuda/vecdotq.cuh  |   72 +-
 5 files changed, 844 insertions(+), 664 deletions(-)

diff --git a/ggml/src/ggml-cuda/mma.cuh b/ggml/src/ggml-cuda/mma.cuh
index 5d87dd8e64c0a..a452a3cc3d152 100644
--- a/ggml/src/ggml-cuda/mma.cuh
+++ b/ggml/src/ggml-cuda/mma.cuh
@@ -70,6 +70,10 @@ struct mma_int_A_I16K8 {
         }
 #endif // defined(INT8_MMA_AVAILABLE)
     }
+
+    __device__ __forceinline__ void load_low(const int * __restrict__ xs0, const int & stride) {
+        ((mma_int_A_I16K4 *) x)[0].load(xs0, stride);
+    }
 };
 
 struct mma_int_B_J8K4 {
diff --git a/ggml/src/ggml-cuda/mmq.cuh b/ggml/src/ggml-cuda/mmq.cuh
index 118e34d2847fc..51c44d857a490 100644
--- a/ggml/src/ggml-cuda/mmq.cuh
+++ b/ggml/src/ggml-cuda/mmq.cuh
@@ -8,18 +8,70 @@
 #include 
 
 #define MMQ_DP4A_MAX_BATCH_SIZE 64 // Max. batch size to use for dp4a MMQ kernels when FP16 tensor cores are available.
+#define MMQ_ITER_K 256
+#define MMQ_NWARPS 8
 
 typedef void (*load_tiles_mmq_t)(const char * __restrict__ x, int * x_tile, const int & kbx0, const int & i_max, const int & stride);
-typedef void (*vec_dot_mmq_t)(const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0);
+typedef void (*vec_dot_mmq_t)(const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00);
 typedef void (*mmq_write_back_t)(const float * __restrict__ sum, float * __restrict__ dst, const int & stride, const int & i_max, const int & j_max);
 
+enum mmq_q8_1_ds_layout {
+    MMQ_Q8_1_DS_LAYOUT_D4,
+    MMQ_Q8_1_DS_LAYOUT_DS4,
+    MMQ_Q8_1_DS_LAYOUT_D2S6,
+};
+
 struct block_q8_1_mmq {
-    half2  ds[4];
-    int8_t qs[4*QK8_1];
+    // The y float data is converted to a data layout that can simply be copied to shared memory as a contiguous block.
+    // The y float data is first grouped as blocks of 128 values.
+    // These blocks are then treated as individual data values and transposed.
+    //
+    // To avoid shared memory bank conflicts each block is padded with 16 bytes.
+    // This padding is also used to store block scales/partial sums.
+    // The scales multiplied with the quantized data are equal to the unquantized values.
+    // The partial sums are obtained by summing up a subgroup of the contained values (prior to quantization)
+    //     and are only needed for performance reasons.
+    //
+    // The exact data stored depends on the x data type.
+    union {
+        float d4[4];    // 1 32 bit scale per 32 values, stored as d0,d1,d2,d3
+        half2 ds4[4];   // 1 16 bit scale + 1 16 bit partial sum per 32 values, stored as d0,s0,d1,s1,d2,s2,d3,s3
+        half  d2s6[8];  // 1 16 bit scale per 64 values + 1 16 bit partial sum per 16 values for the first 96 values,
+                        //     stored as d0,d1,s1,s2,s3,s4,s5
+    };
+    int8_t qs[4*QK8_1]; // 128 values quantized to 8 bit each
 };
 static_assert(sizeof(block_q8_1_mmq) == 4*QK8_1 + 4*sizeof(half2), "Unexpected block_q8_1_mmq size");
 static_assert(sizeof(block_q8_1_mmq) == 4*sizeof(block_q8_1),      "Unexpected block_q8_1_mmq size");
 
+static mmq_q8_1_ds_layout mmq_get_q8_1_ds_layout(const ggml_type type_x) {
+    switch (type_x) {
+        case GGML_TYPE_Q4_0:
+        case GGML_TYPE_Q4_1:
+            return MMQ_Q8_1_DS_LAYOUT_DS4;
+        case GGML_TYPE_Q5_0:
+            return MMQ_Q8_1_DS_LAYOUT_D4;
+        case GGML_TYPE_Q5_1:
+            return MMQ_Q8_1_DS_LAYOUT_DS4;
+        case GGML_TYPE_Q8_0:
+            return MMQ_Q8_1_DS_LAYOUT_D4;
+        case GGML_TYPE_Q2_K:
+            return MMQ_Q8_1_DS_LAYOUT_D2S6;
+        case GGML_TYPE_Q3_K:
+            return MMQ_Q8_1_DS_LAYOUT_D4;
+        case GGML_TYPE_Q4_K:
+        case GGML_TYPE_Q5_K:
+            return MMQ_Q8_1_DS_LAYOUT_DS4;
+        case GGML_TYPE_Q6_K:
+        case GGML_TYPE_IQ4_XS:
+        case GGML_TYPE_IQ4_NL:
+            return MMQ_Q8_1_DS_LAYOUT_D4;
+        default:
+            GGML_ASSERT(false);
+            break;
+    }
+}
+
 struct tile_x_sizes {
     int qs;
     int dm;
@@ -79,49 +131,46 @@ static constexpr __device__ int get_mmq_y_device() {
 #endif // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
 }
 
-#define MMQ_DP4A_TXS_Q4_0 tile_x_sizes{mmq_y*WARP_SIZE   + mmq_y, mmq_y*WARP_SIZE/QI4_0 + mmq_y/QI4_0, 0}
-#define MMQ_DP4A_TXS_Q4_1 tile_x_sizes{mmq_y*WARP_SIZE   + mmq_y, mmq_y*WARP_SIZE/QI4_1 + mmq_y/QI4_1, 0}
-#define MMQ_DP4A_TXS_Q5_0 tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE/QI5_0 + mmq_y/QI5_0, 0}
-#define MMQ_DP4A_TXS_Q5_1 tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE/QI5_1 + mmq_y/QI5_1, 0}
-#define MMQ_DP4A_TXS_Q8_0 tile_x_sizes{mmq_y*WARP_SIZE   + mmq_y, mmq_y*WARP_SIZE/QI8_0 + mmq_y/QI8_0, 0}
-#define MMQ_DP4A_TXS_Q2_K tile_x_sizes{mmq_y*WARP_SIZE   + mmq_y, mmq_y*WARP_SIZE       + mmq_y,       0}
-#define MMQ_DP4A_TXS_Q3_K tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE/QI3_K + mmq_y/QI3_K, mmq_y*WARP_SIZE/4 + mmq_y/4}
-#define MMQ_DP4A_TXS_Q4_K tile_x_sizes{mmq_y*WARP_SIZE   + mmq_y, mmq_y*WARP_SIZE/QI4_K + mmq_y/QI4_K, mmq_y*WARP_SIZE/8 + mmq_y/8}
-#define MMQ_DP4A_TXS_Q5_K tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE/QI5_K + mmq_y/QI5_K, mmq_y*WARP_SIZE/8 + mmq_y/8}
-#define MMQ_DP4A_TXS_Q6_K tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE/QI6_K + mmq_y/QI6_K, mmq_y*WARP_SIZE/8 + mmq_y/8}
+#define MMQ_DP4A_TXS_Q4_0 tile_x_sizes{mmq_y*WARP_SIZE   + mmq_y, mmq_y*WARP_SIZE/QI4_0   + mmq_y/QI4_0,     0}
+#define MMQ_DP4A_TXS_Q4_1 tile_x_sizes{mmq_y*WARP_SIZE   + mmq_y, mmq_y*WARP_SIZE/QI4_1   + mmq_y/QI4_1,     0}
+#define MMQ_DP4A_TXS_Q8_0 tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE*2/QI8_0 + mmq_y/(QI8_0/2), 0}
+#define MMQ_DP4A_TXS_Q8_1 tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE*2/QI8_1 + mmq_y/(QI8_1/2), 0}
+#define MMQ_DP4A_TXS_Q2_K tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE         + mmq_y,           0}
+#define MMQ_DP4A_TXS_Q3_K tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y,                                     mmq_y*WARP_SIZE/8 + mmq_y/8}
+#define MMQ_DP4A_TXS_Q4_K tile_x_sizes{mmq_y*WARP_SIZE   + mmq_y, mmq_y*WARP_SIZE/QI4_K   + mmq_y/QI4_K,     mmq_y*WARP_SIZE/8 + mmq_y/8}
+#define MMQ_DP4A_TXS_Q5_K tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE/QI5_K   + mmq_y/QI5_K,     mmq_y*WARP_SIZE/8 + mmq_y/8}
+#define MMQ_DP4A_TXS_Q6_K tile_x_sizes{mmq_y*WARP_SIZE*2 + mmq_y, mmq_y*WARP_SIZE/QI6_K   + mmq_y/QI6_K,     mmq_y*WARP_SIZE/8 + mmq_y/8}
 
 static constexpr __host__ __device__ tile_x_sizes mmq_get_dp4a_tile_x_sizes(ggml_type type, int mmq_y) {
     return type == GGML_TYPE_Q4_0 ? MMQ_DP4A_TXS_Q4_0 :
         type == GGML_TYPE_Q4_1    ? MMQ_DP4A_TXS_Q4_1 :
-        type == GGML_TYPE_Q5_0    ? MMQ_DP4A_TXS_Q5_0 :
-        type == GGML_TYPE_Q5_1    ? MMQ_DP4A_TXS_Q5_1 :
+        type == GGML_TYPE_Q5_0    ? MMQ_DP4A_TXS_Q8_0 :
+        type == GGML_TYPE_Q5_1    ? MMQ_DP4A_TXS_Q8_1 :
         type == GGML_TYPE_Q8_0    ? MMQ_DP4A_TXS_Q8_0 :
         type == GGML_TYPE_Q2_K    ? MMQ_DP4A_TXS_Q2_K :
         type == GGML_TYPE_Q3_K    ? MMQ_DP4A_TXS_Q3_K :
         type == GGML_TYPE_Q4_K    ? MMQ_DP4A_TXS_Q4_K :
         type == GGML_TYPE_Q5_K    ? MMQ_DP4A_TXS_Q5_K :
         type == GGML_TYPE_Q6_K    ? MMQ_DP4A_TXS_Q6_K :
-        type == GGML_TYPE_IQ4_XS  ? MMQ_DP4A_TXS_Q5_0 :
-        type == GGML_TYPE_IQ4_NL  ? MMQ_DP4A_TXS_Q5_0 :
+        type == GGML_TYPE_IQ4_XS  ? MMQ_DP4A_TXS_Q8_0 :
+        type == GGML_TYPE_IQ4_NL  ? MMQ_DP4A_TXS_Q8_0 :
         tile_x_sizes{0, 0, 0};
 }
 
-#define MMQ_MMA_TILE_X_K_Q4_0 (1*WARP_SIZE + WARP_SIZE/QI4_0               + 4)
-#define MMQ_MMA_TILE_X_K_Q4_1 (1*WARP_SIZE + WARP_SIZE/QI4_1               + 4)
-#define MMQ_MMA_TILE_X_K_Q5_0 (2*WARP_SIZE + WARP_SIZE/QI5_0               + 4)
-#define MMQ_MMA_TILE_X_K_Q5_1 (2*WARP_SIZE + WARP_SIZE/QI5_1               + 4)
-#define MMQ_MMA_TILE_X_K_Q8_0 (1*WARP_SIZE + WARP_SIZE/QI8_0               + 0)
-#define MMQ_MMA_TILE_X_K_Q2_K (1*WARP_SIZE + WARP_SIZE                     + 4)
-#define MMQ_MMA_TILE_X_K_Q3_K (2*WARP_SIZE + WARP_SIZE/QI3_K + WARP_SIZE/4 + 2)
-#define MMQ_MMA_TILE_X_K_Q4_K (1*WARP_SIZE + WARP_SIZE/QI4_K + WARP_SIZE/8 + 7)
-#define MMQ_MMA_TILE_X_K_Q5_K (2*WARP_SIZE + WARP_SIZE/QI5_K + WARP_SIZE/8 + 7)
-#define MMQ_MMA_TILE_X_K_Q6_K (2*WARP_SIZE + WARP_SIZE/QI6_K + WARP_SIZE/8 + 7)
+#define MMQ_MMA_TILE_X_K_Q4_0 (1*WARP_SIZE + WARP_SIZE/QI4_0                   + 4)
+#define MMQ_MMA_TILE_X_K_Q4_1 (1*WARP_SIZE + WARP_SIZE/QI4_1                   + 4)
+#define MMQ_MMA_TILE_X_K_Q8_0 (2*WARP_SIZE + 2*WARP_SIZE/QI8_0                 + 4)
+#define MMQ_MMA_TILE_X_K_Q8_1 (2*WARP_SIZE + 2*WARP_SIZE/QI8_0                 + 4)
+#define MMQ_MMA_TILE_X_K_Q2_K (2*WARP_SIZE + WARP_SIZE                         + 4)
+#define MMQ_MMA_TILE_X_K_Q3_K (2*WARP_SIZE + WARP_SIZE/(2*QI3_K) + WARP_SIZE/8 + 7)
+#define MMQ_MMA_TILE_X_K_Q4_K (1*WARP_SIZE + WARP_SIZE/QI4_K     + WARP_SIZE/8 + 7)
+#define MMQ_MMA_TILE_X_K_Q5_K (2*WARP_SIZE + WARP_SIZE/QI5_K     + WARP_SIZE/8 + 7)
+#define MMQ_MMA_TILE_X_K_Q6_K (2*WARP_SIZE + WARP_SIZE/QI6_K     + WARP_SIZE/8 + 7)
 
 static_assert(MMQ_MMA_TILE_X_K_Q4_0 % 8 == 4, "Wrong padding.");
 static_assert(MMQ_MMA_TILE_X_K_Q4_1 % 8 == 4, "Wrong padding.");
-static_assert(MMQ_MMA_TILE_X_K_Q5_0 % 8 == 4, "Wrong padding.");
-static_assert(MMQ_MMA_TILE_X_K_Q5_1 % 8 == 4, "Wrong padding.");
 static_assert(MMQ_MMA_TILE_X_K_Q8_0 % 8 == 4, "Wrong padding.");
+static_assert(MMQ_MMA_TILE_X_K_Q8_1 % 8 == 4, "Wrong padding.");
 static_assert(MMQ_MMA_TILE_X_K_Q2_K % 8 == 4, "Wrong padding.");
 static_assert(MMQ_MMA_TILE_X_K_Q3_K % 8 == 4, "Wrong padding.");
 static_assert(MMQ_MMA_TILE_X_K_Q4_K % 8 == 4, "Wrong padding.");
@@ -131,21 +180,20 @@ static_assert(MMQ_MMA_TILE_X_K_Q6_K % 8 == 4, "Wrong padding.");
 static constexpr __host__ __device__ int mmq_get_mma_tile_x_k(ggml_type type) {
     return type == GGML_TYPE_Q4_0 ? MMQ_MMA_TILE_X_K_Q4_0 :
         type == GGML_TYPE_Q4_1    ? MMQ_MMA_TILE_X_K_Q4_1 :
-        type == GGML_TYPE_Q5_0    ? MMQ_MMA_TILE_X_K_Q5_0 :
-        type == GGML_TYPE_Q5_1    ? MMQ_MMA_TILE_X_K_Q5_1 :
+        type == GGML_TYPE_Q5_0    ? MMQ_MMA_TILE_X_K_Q8_0 :
+        type == GGML_TYPE_Q5_1    ? MMQ_MMA_TILE_X_K_Q8_1 :
         type == GGML_TYPE_Q8_0    ? MMQ_MMA_TILE_X_K_Q8_0 :
         type == GGML_TYPE_Q2_K    ? MMQ_MMA_TILE_X_K_Q2_K :
         type == GGML_TYPE_Q3_K    ? MMQ_MMA_TILE_X_K_Q3_K :
         type == GGML_TYPE_Q4_K    ? MMQ_MMA_TILE_X_K_Q4_K :
         type == GGML_TYPE_Q5_K    ? MMQ_MMA_TILE_X_K_Q5_K :
         type == GGML_TYPE_Q6_K    ? MMQ_MMA_TILE_X_K_Q6_K :
-        type == GGML_TYPE_IQ4_XS  ? MMQ_MMA_TILE_X_K_Q5_0 :
-        type == GGML_TYPE_IQ4_NL  ? MMQ_MMA_TILE_X_K_Q5_0 :
+        type == GGML_TYPE_IQ4_XS  ? MMQ_MMA_TILE_X_K_Q8_0 :
+        type == GGML_TYPE_IQ4_NL  ? MMQ_MMA_TILE_X_K_Q8_0 :
         0;
 }
 
 #define MMQ_TILE_Y_K (WARP_SIZE + WARP_SIZE/QI8_1)
-#define MMQ_NWARPS 8
 
 static int mmq_get_granularity_host(const int mmq_x, const int cc) {
     return int8_mma_available(cc) && mmq_x >= 48 ? 16 : 8;
@@ -218,7 +266,7 @@ template  static __device__ __forceinlin
 
 template 
 static __device__ __forceinline__ void vec_dot_q4_0_q8_1_dp4a(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 
     constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q4_0, mmq_y);
     const int   * x_qs = (const int   *) x;
@@ -226,34 +274,39 @@ static __device__ __forceinline__ void vec_dot_q4_0_q8_1_dp4a(
     const int   * y_qs = (const int   *) y + 4;
     const half2 * y_ds = (const half2 *) y;
 
+// #pragma unroll
+    for (int k01 = 0; k01 < WARP_SIZE; k01 += QR4_0*VDR_Q4_0_Q8_1_MMQ) {
+        const int k0 = k00 + k01;
+
 #pragma unroll
-    for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
-        const int j = j0 + threadIdx.y;
+        for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
+            const int j = j0 + threadIdx.y;
 
 #pragma unroll
-        for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
-            const int i = i0 + threadIdx.x;
+            for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
+                const int i = i0 + threadIdx.x;
 
-            const int kyqs = k0 % (QI8_1/2) + QI8_1 * (k0 / (QI8_1/2));
+                const int kyqs = QI8_1 * ((k01/2) / (QI8_1/2)) + (k01/2) % (QI8_1/2);
 
-            int u[2*VDR_Q4_0_Q8_1_MMQ];
+                int u[2*VDR_Q4_0_Q8_1_MMQ];
 
 #pragma unroll
-            for (int l = 0; l < VDR_Q4_0_Q8_1_MMQ; ++l) {
-                u[2*l+0] = y_qs[j*MMQ_TILE_Y_K + (kyqs + l)         % WARP_SIZE];
-                u[2*l+1] = y_qs[j*MMQ_TILE_Y_K + (kyqs + l + QI4_0) % WARP_SIZE];
-            }
+                for (int l = 0; l < VDR_Q4_0_Q8_1_MMQ; ++l) {
+                    u[2*l+0] = y_qs[j*MMQ_TILE_Y_K + kyqs +  l];
+                    u[2*l+1] = y_qs[j*MMQ_TILE_Y_K + kyqs + (l + QI4_0)];
+                }
 
-            sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q4_0_q8_1_impl
-                (&x_qs[i*(WARP_SIZE + 1) + k0], u, x_df[i*(WARP_SIZE/QI4_0) + i/QI4_0 + k0/QI4_0],
-                y_ds[j*MMQ_TILE_Y_K + (2*k0/QI8_1) % (WARP_SIZE/QI8_1)]);
+                sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q4_0_q8_1_impl
+                    (&x_qs[i*(WARP_SIZE + 1) + k0/QR4_0], u,
+                     x_df[i*(WARP_SIZE/QI4_0) + i/QI4_0 + k0/(QR4_0*QI4_0)], y_ds[j*MMQ_TILE_Y_K + k01/QI8_1]);
+            }
         }
     }
 }
 
 template 
 static __device__ __forceinline__ void vec_dot_q4_0_q8_1_mma(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 #ifdef INT8_MMA_AVAILABLE
 
     typedef mma_int_A_I16K8 mma_A;
@@ -271,52 +324,60 @@ static __device__ __forceinline__ void vec_dot_q4_0_q8_1_mma(
     const int   * y_qs = (const int   *) y + 4;
     const half2 * y_ds = (const half2 *) y;
 
-    mma_A A[ntx];
-    float dA[ntx][mma_C::ne/2];
+    mma_A A[ntx][4];
+    float dA[ntx][mma_C::ne/2][4];
 
     const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I);
 
 #pragma unroll
     for (int n = 0; n < ntx; ++n) {
 #pragma unroll
-        for (int l = 0; l < mma_A::ne; ++l) {
-            const int i     = i0 + n*mma_A::I + mma_A::get_i(l);
-            const int k     = k0              + mma_A::get_k(l) % QI4_0;
-            const int shift =                4*(mma_A::get_k(l) / QI4_0);
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += QR4_0*QI4_0) {
+            const int k0 = k00 + k01;
 
-            A[n].x[l] = __vsubss4((x_qs[i*MMQ_MMA_TILE_X_K_Q4_0 + k] >> shift) & 0x0F0F0F0F, 0x08080808);
-        }
+#pragma unroll
+            for (int l = 0; l < mma_A::ne; ++l) {
+                const int i     = i0 + n*mma_A::I + mma_A::get_i(l);
+                const int k     = k0/QR4_0        + mma_A::get_k(l) % QI4_0;
+                const int shift =                4*(mma_A::get_k(l) / QI4_0);
+
+                A[n][k01/(QR4_0*QI4_0)].x[l] = __vsubss4((x_qs[i*MMQ_MMA_TILE_X_K_Q4_0 + k] >> shift) & 0x0F0F0F0F, 0x08080808);
+            }
 
 #pragma unroll
-        for (int l = 0; l < mma_C::ne/2; ++l) {
-            const int i = i0 + n*mma_C::I + mma_C::get_i(2*l);
+            for (int l = 0; l < mma_C::ne/2; ++l) {
+                const int i = i0 + n*mma_C::I + mma_C::get_i(2*l);
 
-            dA[n][l] = x_df[i*MMQ_MMA_TILE_X_K_Q4_0 + k0/QI4_0];
+                dA[n][l][k01/(QR4_0*QI4_0)] = x_df[i*MMQ_MMA_TILE_X_K_Q4_0 + k0/(QR4_0*QI4_0)];
+            }
         }
     }
 
 #pragma unroll
     for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) {
-        mma_B  B;
-        float dB[mma_C::ne/2];
+#pragma unroll
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += QR4_0*QI4_0) {
+            mma_B  B;
+            float dB[mma_C::ne/2];
 
-        B.load(y_qs + j0*MMQ_TILE_Y_K + (2*k0) % WARP_SIZE, MMQ_TILE_Y_K);
+            B.load(y_qs + j0*MMQ_TILE_Y_K + k01, MMQ_TILE_Y_K);
 
 #pragma unroll
-        for (int l = 0; l < mma_C::ne/2; ++l) {
-            const int j = j0 + mma_C::get_j(l);
+            for (int l = 0; l < mma_C::ne/2; ++l) {
+                const int j = j0 + mma_C::get_j(l);
 
-            dB[l] = __low2float(y_ds[j*MMQ_TILE_Y_K + (2*k0/QI8_1) % (WARP_SIZE/QI8_1)]);
-        }
+                dB[l] = __low2float(y_ds[j*MMQ_TILE_Y_K + k01/QI8_1]);
+            }
 
 #pragma unroll
-    for (int n = 0; n < ntx; ++n) {
-            mma_C C;
-            C.mma_K8(A[n], B);
+            for (int n = 0; n < ntx; ++n) {
+                mma_C C;
+                C.mma_K8(A[n][k01/(QR4_0*QI4_0)], B);
 
 #pragma unroll
-            for (int l = 0; l < mma_C::ne; ++l) {
-                sum[(j0/mma_C::J + n)*mma_C::ne + l] += dA[n][l/2]*dB[l%2]*C.x[l];
+                for (int l = 0; l < mma_C::ne; ++l) {
+                    sum[(j0/mma_C::J + n)*mma_C::ne + l] += dA[n][l/2][k01/(QR4_0*QI4_0)]*dB[l%2]*C.x[l];
+                }
             }
         }
     }
@@ -381,7 +442,7 @@ template  static __device__ __forceinlin
 
 template 
 static __device__ __forceinline__ void vec_dot_q4_1_q8_1_dp4a(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 
     constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q4_1, mmq_y);
     const int   * x_qs = (const int   *) x;
@@ -389,34 +450,39 @@ static __device__ __forceinline__ void vec_dot_q4_1_q8_1_dp4a(
     const int   * y_qs = (const int   *) y + 4;
     const half2 * y_ds = (const half2 *) y;
 
+// #pragma unroll
+    for (int k01 = 0; k01 < WARP_SIZE; k01 += QR4_1*VDR_Q4_1_Q8_1_MMQ) {
+        const int k0 = k00 + k01;
+
 #pragma unroll
-    for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
-        const int j = j0 + threadIdx.y;
+        for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
+            const int j = j0 + threadIdx.y;
 
 #pragma unroll
-        for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
-            const int i = i0 + threadIdx.x;
+            for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
+                const int i = i0 + threadIdx.x;
 
-            const int kyqs = k0 % (QI8_1/2) + QI8_1 * (k0 / (QI8_1/2));
+                const int kyqs = QI8_1 * ((k01/2) / (QI8_1/2)) + (k01/2) % (QI8_1/2);
 
-            int u[2*VDR_Q4_1_Q8_1_MMQ];
+                int u[2*VDR_Q4_1_Q8_1_MMQ];
 
 #pragma unroll
-            for (int l = 0; l < VDR_Q4_1_Q8_1_MMQ; ++l) {
-                u[2*l+0] = y_qs[j*MMQ_TILE_Y_K + (kyqs + l)         % WARP_SIZE];
-                u[2*l+1] = y_qs[j*MMQ_TILE_Y_K + (kyqs + l + QI4_1) % WARP_SIZE];
-            }
+                for (int l = 0; l < VDR_Q4_1_Q8_1_MMQ; ++l) {
+                    u[2*l+0] = y_qs[j*MMQ_TILE_Y_K + kyqs +  l];
+                    u[2*l+1] = y_qs[j*MMQ_TILE_Y_K + kyqs + (l + QI4_1)];
+                }
 
-            sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q4_1_q8_1_impl
-                (&x_qs[i*(WARP_SIZE + 1) + k0], u, x_dm[i*(WARP_SIZE/QI4_1) + i/QI4_1 + k0/QI4_1],
-                y_ds[j*MMQ_TILE_Y_K + (2*k0/QI8_1) % (WARP_SIZE/QI8_1)]);
+                sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q4_1_q8_1_impl
+                    (&x_qs[i*(WARP_SIZE + 1) + k0/QR4_1], u,
+                     x_dm[i*(WARP_SIZE/QI4_1) + i/QI4_1 + k0/(QR4_1*QI4_1)], y_ds[j*MMQ_TILE_Y_K + k01/QI8_1]);
+            }
         }
     }
 }
 
 template 
 static __device__ __forceinline__ void vec_dot_q4_1_q8_1_mma(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 #ifdef INT8_MMA_AVAILABLE
 
     typedef mma_int_A_I16K8 mma_A;
@@ -435,50 +501,58 @@ static __device__ __forceinline__ void vec_dot_q4_1_q8_1_mma(
     const int   * y_qs = (const int   *) y + 4;
     const half2 * y_ds = (const half2 *) y;
 
-    mma_A A[ntx];
-    half2 dmA[ntx][mma_C::ne/2];
+    mma_A A[ntx][4];
+    half2 dmA[ntx][mma_C::ne/2][4];
 
     const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I);
 
 #pragma unroll
     for (int n = 0; n < ntx; ++n) {
-        ((mma_A_K4 *) &A[n])[0].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q4_1 + k0, MMQ_MMA_TILE_X_K_Q4_1);
-        A[n].x[2]  = (A[n].x[0] >> 4) & 0x0F0F0F0F;
-        A[n].x[3]  = (A[n].x[1] >> 4) & 0x0F0F0F0F;
-        A[n].x[0] &= 0x0F0F0F0F;
-        A[n].x[1] &= 0x0F0F0F0F;
+#pragma unroll
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += QR4_1*QI4_1) {
+            const int k0 = k00 + k01;
+
+            A[n][k01/(QR4_1*QI4_1)].load_low(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q4_1 + k0/QR4_1, MMQ_MMA_TILE_X_K_Q4_1);
+            A[n][k01/(QR4_1*QI4_1)].x[2]  = (A[n][k01/(QR4_1*QI4_1)].x[0] >> 4) & 0x0F0F0F0F;
+            A[n][k01/(QR4_1*QI4_1)].x[3]  = (A[n][k01/(QR4_1*QI4_1)].x[1] >> 4) & 0x0F0F0F0F;
+            A[n][k01/(QR4_1*QI4_1)].x[0] &= 0x0F0F0F0F;
+            A[n][k01/(QR4_1*QI4_1)].x[1] &= 0x0F0F0F0F;
 
 #pragma unroll
-        for (int l = 0; l < mma_C::ne/2; ++l) {
-            const int i = i0 + n*mma_C::I + mma_C::get_i(2*l);
+            for (int l = 0; l < mma_C::ne/2; ++l) {
+                const int i = i0 + n*mma_C::I + mma_C::get_i(2*l);
 
-            dmA[n][l] = x_dm[i*MMQ_MMA_TILE_X_K_Q4_1 + k0/QI4_1];
+                dmA[n][l][k01/(QR4_1*QI4_1)] = x_dm[i*MMQ_MMA_TILE_X_K_Q4_1 + k0/(QR4_1*QI4_1)];
+            }
         }
     }
 
 #pragma unroll
     for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) {
-        mma_B B;
-        half2 dsB[mma_C::ne/2];
+#pragma unroll
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += QR4_1*QI4_1) {
+            mma_B B;
+            half2 dsB[mma_C::ne/2];
 
-        B.load(y_qs + j0*MMQ_TILE_Y_K + (2*k0) % WARP_SIZE, MMQ_TILE_Y_K);
+            B.load(y_qs + j0*MMQ_TILE_Y_K + k01, MMQ_TILE_Y_K);
 
 #pragma unroll
-        for (int l = 0; l < mma_C::ne/2; ++l) {
-            const int j = j0 + mma_C::get_j(l);
+            for (int l = 0; l < mma_C::ne/2; ++l) {
+                const int j = j0 + mma_C::get_j(l);
 
-            dsB[l] = y_ds[j*MMQ_TILE_Y_K + (2*k0/QI8_1) % (WARP_SIZE/QI8_1)];
-        }
+                dsB[l] = y_ds[j*MMQ_TILE_Y_K + k01/QI8_1];
+            }
 
 #pragma unroll
-        for (int n = 0; n < ntx; ++n) {
-            mma_C C;
-            C.mma_K8(A[n], B);
+            for (int n = 0; n < ntx; ++n) {
+                mma_C C;
+                C.mma_K8(A[n][k01/(QR4_1*QI4_1)], B);
 
 #pragma unroll
-            for (int l = 0; l < mma_C::ne; ++l) {
-                const half2 dmA_dsB = dmA[n][l/2]*dsB[l%2];
-                sum[(j0/mma_C::J + n)*mma_C::ne + l] += __low2float(dmA_dsB)*C.x[l] + __high2float(dmA_dsB);
+                for (int l = 0; l < mma_C::ne; ++l) {
+                    const half2 dmA_dsB = dmA[n][l/2][k01/(QR4_1*QI4_1)]*dsB[l%2];
+                    sum[(j0/mma_C::J + n)*mma_C::ne + l] += __low2float(dmA_dsB)*C.x[l] + __high2float(dmA_dsB);
+                }
             }
         }
     }
@@ -531,8 +605,8 @@ template  static __device__ __forceinlin
         qs1     = __vsubss4(qs1, 0x10101010); // subtract 16
 
 #ifdef INT8_MMA_AVAILABLE
-        x_qs[i*MMQ_MMA_TILE_X_K_Q5_0 + kbx*(2*QI5_0) + kqsx + 0]     = qs0;
-        x_qs[i*MMQ_MMA_TILE_X_K_Q5_0 + kbx*(2*QI5_0) + kqsx + QI5_0] = qs1;
+        x_qs[i*MMQ_MMA_TILE_X_K_Q8_0 + kbx*(2*QI5_0) + kqsx + 0]     = qs0;
+        x_qs[i*MMQ_MMA_TILE_X_K_Q8_0 + kbx*(2*QI5_0) + kqsx + QI5_0] = qs1;
 #else
         x_qs[i*(2*WARP_SIZE + 1)     + kbx*(2*QI5_0) + kqsx + 0]     = qs0;
         x_qs[i*(2*WARP_SIZE + 1)     + kbx*(2*QI5_0) + kqsx + QI5_0] = qs1;
@@ -553,106 +627,13 @@ template  static __device__ __forceinlin
         const block_q5_0 * bxi = (const block_q5_0 *) x + kbx0 + i*stride + kbxd;
 
 #ifdef INT8_MMA_AVAILABLE
-        x_df[i*MMQ_MMA_TILE_X_K_Q5_0       + kbxd] = bxi->d;
+        x_df[i*MMQ_MMA_TILE_X_K_Q8_0       + kbxd] = bxi->d;
 #else
         x_df[i*(WARP_SIZE/QI5_0) + i/QI5_0 + kbxd] = bxi->d;
 #endif // INT8_MMA_AVAILABLE
     }
 }
 
-template 
-static __device__ __forceinline__ void vec_dot_q5_0_q8_1_dp4a(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
-
-    constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q5_0, mmq_y);
-    const int   * x_qs = (const int   *) x;
-    const float * x_df = (const float *) x_qs + txs.qs;
-    const int   * y_qs = (const int   *) y + 4;
-    const float * y_df = (const float *) y;
-
-#pragma unroll
-    for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
-        const int j = j0 + threadIdx.y;
-
-#pragma unroll
-        for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
-            const int i = i0 + threadIdx.x;
-
-            sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q8_0_q8_1_impl
-                (&x_qs[i*(2*WARP_SIZE + 1) + 2*k0], &y_qs[j*MMQ_TILE_Y_K + (2*k0) % WARP_SIZE],
-                 x_df[i*(WARP_SIZE/QI5_0) + i/QI5_0 + k0/QI5_0], y_df[j*MMQ_TILE_Y_K + (2*k0/QI8_1) % (WARP_SIZE/QI8_1)]);
-        }
-    }
-}
-
-template 
-static __device__ __forceinline__ void vec_dot_q5_0_q8_1_mma(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
-#ifdef INT8_MMA_AVAILABLE
-
-    typedef mma_int_A_I16K8 mma_A;
-    typedef mma_int_B_J8K8  mma_B;
-    typedef mma_int_C_I16J8 mma_C;
-
-    constexpr int granularity = mmq_get_granularity_device(mmq_x);
-    constexpr int rows_per_warp = 2 * granularity;
-    constexpr int ntx = rows_per_warp/mma_C::I; // Number of x minitiles per warp.
-
-    y += (threadIdx.y % ntx) * (mma_B::J*MMQ_TILE_Y_K);
-
-    const int   * x_qs = (const int   *) x;
-    const float * x_df = (const float *) x_qs + WARP_SIZE*2;
-    const int   * y_qs = (const int   *) y + 4;
-    const float * y_df = (const float *) y;
-
-    mma_A A[ntx];
-    float dA[ntx][mma_C::ne/2];
-
-    const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I);
-
-#pragma unroll
-    for (int n = 0; n < ntx; ++n) {
-        A[n].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q5_0 + QR5_1*k0, MMQ_MMA_TILE_X_K_Q5_0);
-
-#pragma unroll
-        for (int l = 0; l < mma_C::ne/2; ++l) {
-            const int i = i0 + mma_C::get_i(2*l) + n*mma_C::I;
-
-            dA[n][l] = x_df[i*MMQ_MMA_TILE_X_K_Q5_0 + k0/QI5_0];
-        }
-    }
-
-#pragma unroll
-    for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) {
-        mma_B B;
-        float dB[mma_C::ne/2];
-
-        B.load(y_qs + j0*MMQ_TILE_Y_K + (2*k0) % WARP_SIZE, MMQ_TILE_Y_K);
-
-#pragma unroll
-        for (int l = 0; l < mma_C::ne/2; ++l) {
-            const int j = j0 + mma_C::get_j(l);
-
-            dB[l] = y_df[j*MMQ_TILE_Y_K + (2*k0/QI8_1) % (WARP_SIZE/QI8_1)];
-        }
-
-#pragma unroll
-        for (int n = 0; n < ntx; ++n) {
-            mma_C C;
-            C.mma_K8(A[n], B);
-
-#pragma unroll
-            for (int l = 0; l < mma_C::ne; ++l) {
-                sum[(j0/mma_C::J + n)*mma_C::ne + l] += dA[n][l/2]*dB[l%2]*C.x[l];
-            }
-        }
-    }
-#else
-    GGML_UNUSED(x); GGML_UNUSED(y); GGML_UNUSED(sum);
-    NO_DEVICE_CODE;
-#endif // INT8_MMA_AVAILABLE
-}
-
 template  static __device__ __forceinline__ void load_tiles_q5_1(
     const char * __restrict__ x, int * __restrict__ x_tile, const int & kbx0, const int & i_max, const int & stride) {
 
@@ -694,8 +675,8 @@ template  static __device__ __forceinlin
         qs1    |= (qh <<  9) & 0x10000000; // 19 -> 28
 
 #ifdef INT8_MMA_AVAILABLE
-        x_qs[i*MMQ_MMA_TILE_X_K_Q5_1 + kbx*(2*QI5_1) + kqsx + 0]     = qs0;
-        x_qs[i*MMQ_MMA_TILE_X_K_Q5_1 + kbx*(2*QI5_1) + kqsx + QI5_1] = qs1;
+        x_qs[i*MMQ_MMA_TILE_X_K_Q8_1 + kbx*(2*QI5_1) + kqsx + 0]     = qs0;
+        x_qs[i*MMQ_MMA_TILE_X_K_Q8_1 + kbx*(2*QI5_1) + kqsx + QI5_1] = qs1;
 #else
         x_qs[i*(2*WARP_SIZE + 1)     + kbx*(2*QI5_1) + kqsx + 0]     = qs0;
         x_qs[i*(2*WARP_SIZE + 1)     + kbx*(2*QI5_1) + kqsx + QI5_1] = qs1;
@@ -716,41 +697,101 @@ template  static __device__ __forceinlin
         const block_q5_1 * bxi = (const block_q5_1 *) x + kbx0 + i*stride + kbxd;
 
 #ifdef INT8_MMA_AVAILABLE
-        x_dm[i*MMQ_MMA_TILE_X_K_Q5_1       + kbxd] = bxi->dm;
+        x_dm[i*MMQ_MMA_TILE_X_K_Q8_1       + kbxd] = bxi->dm;
 #else
         x_dm[i*(WARP_SIZE/QI5_1) + i/QI5_1 + kbxd] = bxi->dm;
 #endif // INT8_MMA_AVAILABLE
     }
 }
 
+template  static __device__ __forceinline__ void load_tiles_q8_0(
+    const char * __restrict__ x, int * __restrict__ x_tile, const int & kbx0, const int & i_max, const int & stride) {
+
+#ifdef INT8_MMA_AVAILABLE
+    int   * x_qs = (int   *)  x_tile;
+    float * x_df = (float *) (x_tile + 2*WARP_SIZE);
+#else
+    constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q8_0, mmq_y);
+    int   * x_qs = (int   *)  x_tile;
+    float * x_df = (float *) (x_qs + txs.qs);
+#endif // INT8_MMA_AVAILABLE
+
+    const int kbx  = threadIdx.x / QI8_0;
+    const int kqsx = threadIdx.x % QI8_0;
+
+#pragma unroll
+    for (int i0 = 0; i0 < mmq_y; i0 += nwarps) {
+        int i = i0 + threadIdx.y;
+
+        if (need_check) {
+            i = min(i, i_max);
+        }
+
+        const block_q8_0 * bxi = (const block_q8_0 *) x + kbx0 + i*stride + kbx;
+
+#ifdef INT8_MMA_AVAILABLE
+        x_qs[i*MMQ_MMA_TILE_X_K_Q8_0 + 0         + threadIdx.x] = get_int_b2(bxi[0].qs,               kqsx);
+        x_qs[i*MMQ_MMA_TILE_X_K_Q8_0 + WARP_SIZE + threadIdx.x] = get_int_b2(bxi[WARP_SIZE/QI8_0].qs, kqsx);
+#else
+        x_qs[i*(2*WARP_SIZE + 1)     + 0         + threadIdx.x] = get_int_b2(bxi[0].qs,               kqsx);
+        x_qs[i*(2*WARP_SIZE + 1)     + WARP_SIZE + threadIdx.x] = get_int_b2(bxi[WARP_SIZE/QI8_0].qs, kqsx);
+#endif // INT8_MMA_AVAILABLE
+    }
+
+    const int blocks_per_tile_x_row = 2*WARP_SIZE / QI8_0;
+    const int kbxd = threadIdx.x % blocks_per_tile_x_row;
+
+#pragma unroll
+    for (int i0 = 0; i0 < mmq_y; i0 += nwarps * QI8_0/2) {
+        int i = i0 + threadIdx.y * (QI8_0/2) + threadIdx.x / blocks_per_tile_x_row;
+
+        if (need_check) {
+            i = min(i, i_max);
+        }
+
+        const block_q8_0 * bxi = (const block_q8_0 *) x + kbx0 + i*stride + kbxd;
+
+#ifdef INT8_MMA_AVAILABLE
+        x_df[i*MMQ_MMA_TILE_X_K_Q8_0             + kbxd] = bxi->d;
+#else
+        x_df[i*(2*WARP_SIZE/QI8_0) + i/(QI8_0/2) + kbxd] = bxi->d;
+#endif // INT8_MMA_AVAILABLE
+    }
+}
+
 template 
-static __device__ __forceinline__ void vec_dot_q5_1_q8_1_dp4a(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+static __device__ __forceinline__ void vec_dot_q8_0_q8_1_dp4a(
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 
-    constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q5_1, mmq_y);
+    constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q8_0, mmq_y);
     const int   * x_qs = (const int   *) x;
-    const half2 * x_dm = (const half2 *) x_qs + txs.qs;
+    const float * x_df = (const float *) x_qs + txs.qs;
     const int   * y_qs = (const int   *) y + 4;
-    const half2 * y_ds = (const half2 *) y;
+    const float * y_df = (const float *) y;
+
+// #pragma unroll
+    for (int k01 = 0; k01 < WARP_SIZE; k01 += VDR_Q8_0_Q8_1_MMQ) {
+        const int k0 = k00 + k01;
 
 #pragma unroll
-    for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
-        const int j = j0 + threadIdx.y;
+        for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
+            const int j = j0 + threadIdx.y;
 
 #pragma unroll
-        for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
-            const int i = i0 + threadIdx.x;
+            for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
+                const int i = i0 + threadIdx.x;
 
-            sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q8_1_q8_1_impl
-                (&x_qs[i*(2*WARP_SIZE + 1) + 2*k0], &y_qs[j*MMQ_TILE_Y_K + (2*k0) % WARP_SIZE],
-                 x_dm[i*(WARP_SIZE/QI5_1) + i/QI5_1 + k0/QI5_1], y_ds[j*MMQ_TILE_Y_K + (2*k0/QI8_1) % (WARP_SIZE/QI8_1)]);
+                sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q8_0_q8_1_impl
+                    (&x_qs[i*(2*WARP_SIZE + 1) + k0], &y_qs[j*MMQ_TILE_Y_K + k0 % WARP_SIZE],
+                     x_df[i*(2*WARP_SIZE/QI8_0) + i/(QI8_0/2) + k0/QI8_0], y_df[j*MMQ_TILE_Y_K + (k0/QI8_1) % (WARP_SIZE/QI8_1)]);
+            }
         }
     }
 }
 
 template 
-static __device__ __forceinline__ void vec_dot_q5_1_q8_1_mma(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+static __device__ __forceinline__ void vec_dot_q8_0_q8_1_mma(
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 #ifdef INT8_MMA_AVAILABLE
 
     typedef mma_int_A_I16K8 mma_A;
@@ -764,140 +805,106 @@ static __device__ __forceinline__ void vec_dot_q5_1_q8_1_mma(
     y += (threadIdx.y % ntx) * (mma_B::J*MMQ_TILE_Y_K);
 
     const int   * x_qs = (const int   *) x;
-    const half2 * x_dm = (const half2 *) x_qs + 2*WARP_SIZE;
+    const float * x_df = (const float *) x_qs + 2*WARP_SIZE;
     const int   * y_qs = (const int   *) y + 4;
-    const half2 * y_ds = (const half2 *) y;
+    const float * y_df = (const float *) y;
 
-    mma_A A[ntx];
-    half2 dmA[ntx][mma_C::ne/2];
+    mma_A A[ntx][WARP_SIZE/QI8_0];
+    float dA[ntx][mma_C::ne/2][WARP_SIZE/QI8_0];
 
-    const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I);
+    const int i0 = (threadIdx.y/ntx)*rows_per_warp;
 
 #pragma unroll
     for (int n = 0; n < ntx; ++n) {
-        A[n].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q5_1 + QR5_1*k0, MMQ_MMA_TILE_X_K_Q5_1);
-
 #pragma unroll
-        for (int l = 0; l < mma_C::ne/2; ++l) {
-            const int i = i0 + mma_C::get_i(2*l) + n*mma_C::I;
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += QI8_0) {
+            const int k0 = k00 + k01;
 
-            dmA[n][l] = x_dm[i*MMQ_MMA_TILE_X_K_Q5_1 + k0/QI5_1];
+            A[n][k01/QI8_0].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q8_0 + k0, MMQ_MMA_TILE_X_K_Q8_0);
         }
-    }
-
-#pragma unroll
-    for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) {
-        mma_B B;
-        half2 dsB[mma_C::ne/2];
-
-        B.load(y_qs + j0*MMQ_TILE_Y_K + (2*k0) % WARP_SIZE, MMQ_TILE_Y_K);
 
 #pragma unroll
         for (int l = 0; l < mma_C::ne/2; ++l) {
-            const int j = j0 + mma_C::get_j(l);
-
-            dsB[l] = y_ds[j*MMQ_TILE_Y_K + (2*k0/QI8_1) % (WARP_SIZE/QI8_1)];
-        }
+            const int i = i0 + n*mma_A::I + mma_C::get_i(2*l);
 
 #pragma unroll
-        for (int n = 0; n < ntx; ++n) {
-            mma_C C;
-            C.mma_K8(A[n], B);
+            for (int k01 = 0; k01 < WARP_SIZE; k01 += QI8_0) {
+                const int k0 = k00 + k01;
 
-#pragma unroll
-            for (int l = 0; l < mma_C::ne; ++l) {
-                const half2 dmA_dsB = dmA[n][l/2]*dsB[l%2];
-                sum[(j0/mma_C::J + n)*mma_C::ne + l] += __low2float(dmA_dsB)*C.x[l] + __high2float(dmA_dsB);
+                dA[n][l][k01/QI8_0] = x_df[i*MMQ_MMA_TILE_X_K_Q8_0 + k0/QI8_0];
             }
         }
     }
-#else
-    GGML_UNUSED(x); GGML_UNUSED(y); GGML_UNUSED(sum);
-    NO_DEVICE_CODE;
-#endif // INT8_MMA_AVAILABLE
-}
 
-template  static __device__ __forceinline__ void load_tiles_q8_0(
-    const char * __restrict__ x, int * __restrict__ x_tile, const int & kbx0, const int & i_max, const int & stride) {
+#pragma unroll
+    for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) {
+#pragma unroll
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += QI8_0) {
+            const int k0 = k00 + k01;
 
-#ifdef INT8_MMA_AVAILABLE
-    int   * x_qs = (int   *)  x_tile;
-    float * x_df = (float *) (x_tile + WARP_SIZE);
-#else
-    constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q8_0, mmq_y);
-    int   * x_qs = (int   *)  x_tile;
-    float * x_df = (float *) (x_qs + txs.qs);
-#endif // INT8_MMA_AVAILABLE
+            mma_B B;
+            float dB[mma_C::ne/2];
 
-    const int kbx  = threadIdx.x / QI8_0;
-    const int kqsx = threadIdx.x % QI8_0;
+            B.load(y_qs + j0*MMQ_TILE_Y_K + k0 % WARP_SIZE, MMQ_TILE_Y_K);
 
 #pragma unroll
-    for (int i0 = 0; i0 < mmq_y; i0 += nwarps) {
-        int i = i0 + threadIdx.y;
-
-        if (need_check) {
-            i = min(i, i_max);
-        }
-
-        const block_q8_0 * bxi = (const block_q8_0 *) x + kbx0 + i*stride + kbx;
+            for (int l = 0; l < mma_C::ne/2; ++l) {
+                const int j = j0 + mma_C::get_j(l);
 
-#ifdef INT8_MMA_AVAILABLE
-        x_qs[i*MMQ_MMA_TILE_X_K_Q8_0 + threadIdx.x] = get_int_b2(bxi->qs, kqsx);
-#else
-        x_qs[i*(WARP_SIZE + 1)       + threadIdx.x] = get_int_b2(bxi->qs, kqsx);
-#endif // INT8_MMA_AVAILABLE
-    }
+                dB[l] = y_df[j*MMQ_TILE_Y_K + (k0/QI8_1) % (WARP_SIZE/QI8_1)];
+            }
 
-    const int blocks_per_tile_x_row = WARP_SIZE / QI8_0;
-    const int kbxd = threadIdx.x % blocks_per_tile_x_row;
+#pragma unroll
+            for (int n = 0; n < ntx; ++n) {
+                mma_C C;
+                C.mma_K8(A[n][k01/QI8_0], B);
 
 #pragma unroll
-    for (int i0 = 0; i0 < mmq_y; i0 += nwarps * QI8_0) {
-        int i = i0 + threadIdx.y * QI8_0 + threadIdx.x / blocks_per_tile_x_row;
-
-        if (need_check) {
-            i = min(i, i_max);
+                for (int l = 0; l < mma_C::ne; ++l) {
+                    sum[(j0/mma_C::J + n)*mma_C::ne + l] += C.x[l]*dA[n][l/2][k01/QI8_0]*dB[l%2];
+                }
+            }
         }
-
-        const block_q8_0 * bxi = (const block_q8_0 *) x + kbx0 + i*stride + kbxd;
-
-#ifdef INT8_MMA_AVAILABLE
-        x_df[i*MMQ_MMA_TILE_X_K_Q8_0         + kbxd] = bxi->d;
+    }
 #else
-        x_df[i*(WARP_SIZE/QI8_0) + i / QI8_0 + kbxd] = bxi->d;
+    GGML_UNUSED(x); GGML_UNUSED(y); GGML_UNUSED(sum);
+    NO_DEVICE_CODE;
 #endif // INT8_MMA_AVAILABLE
-    }
 }
 
 template 
-static __device__ __forceinline__ void vec_dot_q8_0_q8_1_dp4a(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+static __device__ __forceinline__ void vec_dot_q8_1_q8_1_dp4a(
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 
-    constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q8_0, mmq_y);
+    constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q5_1, mmq_y);
     const int   * x_qs = (const int   *) x;
-    const float * x_df = (const float *) x_qs + txs.qs;
+    const half2 * x_dm = (const half2 *) x_qs + txs.qs;
     const int   * y_qs = (const int   *) y + 4;
-    const float * y_df = (const float *) y;
+    const half2 * y_ds = (const half2 *) y;
+
+// #pragma unroll
+    for (int k01 = 0; k01 < WARP_SIZE; k01 += VDR_Q8_0_Q8_1_MMQ) {
+        const int k0 = k00 + k01;
 
 #pragma unroll
-    for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
-        const int j = j0 + threadIdx.y;
+        for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
+            const int j = j0 + threadIdx.y;
 
 #pragma unroll
-        for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
-            const int i = i0 + threadIdx.x;
+            for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
+                const int i = i0 + threadIdx.x;
 
-            sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q8_0_q8_1_impl
-                (&x_qs[i*(WARP_SIZE + 1) + k0], &y_qs[j*MMQ_TILE_Y_K + k0], x_df[i*(WARP_SIZE/QI8_0) + i/QI8_0 + k0/QI8_0],
-                y_df[j*MMQ_TILE_Y_K + k0/QI8_1]);
+                sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q8_1_q8_1_impl
+                    (&x_qs[i*(2*WARP_SIZE + 1) + k0], &y_qs[j*MMQ_TILE_Y_K + k01],
+                    x_dm[i*(WARP_SIZE/QI5_1) + i/QI5_1 + k0/QI8_1], y_ds[j*MMQ_TILE_Y_K + k01/QI8_1]);
+            }
         }
     }
 }
 
 template 
-static __device__ __forceinline__ void vec_dot_q8_0_q8_1_mma(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+static __device__ __forceinline__ void vec_dot_q8_1_q8_1_mma(
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 #ifdef INT8_MMA_AVAILABLE
 
     typedef mma_int_A_I16K8 mma_A;
@@ -911,49 +918,65 @@ static __device__ __forceinline__ void vec_dot_q8_0_q8_1_mma(
     y += (threadIdx.y % ntx) * (mma_B::J*MMQ_TILE_Y_K);
 
     const int   * x_qs = (const int   *) x;
-    const float * x_df = (const float *) x_qs + WARP_SIZE;
+    const half2 * x_dm = (const half2 *) x_qs + 2*WARP_SIZE;
     const int   * y_qs = (const int   *) y + 4;
-    const float * y_df = (const float *) y;
+    const half2 * y_dm = (const half2 *) y;
 
-    mma_A A[ntx];
-    float dA[ntx][mma_C::ne/2];
+    mma_A   A[ntx][WARP_SIZE/QI8_1];
+    half2 dmA[ntx][mma_C::ne/2][WARP_SIZE/QI8_1];
 
     const int i0 = (threadIdx.y/ntx)*rows_per_warp;
 
 #pragma unroll
     for (int n = 0; n < ntx; ++n) {
-        A[n].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q8_0 + k0, MMQ_MMA_TILE_X_K_Q8_0);
+#pragma unroll
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += QI8_1) {
+            const int k0 = k00 + k01;
+
+            A[n][k01/QI8_1].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q8_1 + k0, MMQ_MMA_TILE_X_K_Q8_1);
+        }
 
 #pragma unroll
         for (int l = 0; l < mma_C::ne/2; ++l) {
             const int i = i0 + n*mma_A::I + mma_C::get_i(2*l);
 
-            dA[n][l] = x_df[i*MMQ_MMA_TILE_X_K_Q8_0 + k0/QI8_0];
+#pragma unroll
+            for (int k01 = 0; k01 < WARP_SIZE; k01 += QI8_1) {
+                const int k0 = k00 + k01;
+
+                dmA[n][l][k01/QI8_1] = x_dm[i*MMQ_MMA_TILE_X_K_Q8_1 + k0/QI8_1];
+            }
         }
     }
 
 #pragma unroll
     for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) {
-        mma_B B;
-        float dB[mma_C::ne/2];
+#pragma unroll
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += QI8_1) {
+            const int k0 = k00 + k01;
+
+            mma_B   B;
+            half2 dsB[mma_C::ne/2];
 
-        B.load(y_qs + j0*MMQ_TILE_Y_K + k0, MMQ_TILE_Y_K);
+            B.load(y_qs + j0*MMQ_TILE_Y_K + k0 % WARP_SIZE, MMQ_TILE_Y_K);
 
 #pragma unroll
-        for (int l = 0; l < mma_C::ne/2; ++l) {
-            const int j = j0 + mma_C::get_j(l);
+            for (int l = 0; l < mma_C::ne/2; ++l) {
+                const int j = j0 + mma_C::get_j(l);
 
-            dB[l] = y_df[j*MMQ_TILE_Y_K + k0/QI8_1];
-        }
+                dsB[l] = y_dm[j*MMQ_TILE_Y_K + (k0/QI8_1) % (WARP_SIZE/QI8_1)];
+            }
 
 #pragma unroll
-        for (int n = 0; n < ntx; ++n) {
-            mma_C C;
-            C.mma_K8(A[n], B);
+            for (int n = 0; n < ntx; ++n) {
+                mma_C C;
+                C.mma_K8(A[n][k01/QI8_1], B);
 
 #pragma unroll
-            for (int l = 0; l < mma_C::ne; ++l) {
-                sum[(j0/mma_C::J + n)*mma_C::ne + l] += C.x[l]*dA[n][l/2]*dB[l%2];
+                for (int l = 0; l < mma_C::ne; ++l) {
+                const half2 dmA_dsB = dmA[n][l/2][k01/QI8_1]*dsB[l%2];
+                sum[(j0/mma_C::J + n)*mma_C::ne + l] += __low2float(dmA_dsB)*C.x[l] + __high2float(dmA_dsB);
+                }
             }
         }
     }
@@ -968,44 +991,37 @@ template  static __device__ __forceinlin
 
 #ifdef INT8_MMA_AVAILABLE
     int   * x_qs = (int   *)  x_tile;
-    half2 * x_dm = (half2 *) (x_qs + WARP_SIZE);
+    half2 * x_dm = (half2 *) (x_qs + 2*WARP_SIZE);
 #else
     constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q2_K, mmq_y);
     int   * x_qs = (int   *)  x_tile;
     half2 * x_dm = (half2 *) (x_qs + txs.qs);
 #endif // INT8_MMA_AVAILABLE
 
-    const int kbx  = threadIdx.x / QI2_K;
     const int kqsx = threadIdx.x % QI2_K;
 
 #pragma unroll
-    for (int i0 = 0; i0 < mmq_y; i0 += nwarps) {
-        int i = i0 + threadIdx.y;
+    for (int i0 = 0; i0 < mmq_y; i0 += nwarps * WARP_SIZE/QI2_K) {
+        int i = i0 + threadIdx.y*(WARP_SIZE/QI2_K) + threadIdx.x/QI2_K;
 
         if (need_check) {
             i = min(i, i_max);
         }
 
-        const block_q2_K * bxi = (const block_q2_K *) x + kbx0 + i*stride + kbx;
+        const block_q2_K * bxi = (const block_q2_K *) x + kbx0 + i*stride;
 
         const int x_ql_0 = get_int_b2(bxi->qs, kqsx);
 
 #pragma unroll
         for (int l = 0; l < QR2_K; ++l) {
-            const int k = kbx*QI2_K + (kqsx/8)*8 + l*2 + (kqsx % 8)/4;
+            const int k = (kqsx/8)*32 + l*8 + kqsx % 8;
 
-            int x_qs_k = ((x_ql_0 >> (2*l)) & 0x03030303) << (2*(kqsx % 4));
-            x_qs_k |= __shfl_xor_sync(0xFFFFFFFF, x_qs_k, 1, WARP_SIZE);
-            x_qs_k |= __shfl_xor_sync(0xFFFFFFFF, x_qs_k, 2, WARP_SIZE);
-
-            if (kqsx % QR2_K != 0) {
-                continue;
-            }
+            const int x_qs_k = (x_ql_0 >> (2*l)) & 0x03030303;
 
 #ifdef INT8_MMA_AVAILABLE
             x_qs[i*MMQ_MMA_TILE_X_K_Q2_K + k] = x_qs_k;
 #else
-            x_qs[i*(WARP_SIZE + 1)       + k] = x_qs_k;
+            x_qs[i*(2*WARP_SIZE + 1)     + k] = x_qs_k;
 #endif // INT8_MMA_AVAILABLE
         }
 
@@ -1018,44 +1034,68 @@ template  static __device__ __forceinlin
 #endif // FAST_FP16_AVAILABLE
 
 #ifdef INT8_MMA_AVAILABLE
-        x_dm[i*MMQ_MMA_TILE_X_K_Q2_K + threadIdx.x] = x_dm_ik;
+        x_dm[i*MMQ_MMA_TILE_X_K_Q2_K + kqsx] = x_dm_ik;
 #else
-        x_dm[i*(WARP_SIZE + 1)       + threadIdx.x] = x_dm_ik;
+        x_dm[i*(WARP_SIZE + 1)       + kqsx] = x_dm_ik;
 #endif // INT8_MMA_AVAILABLE
     }
 }
 
 template 
 static __device__ __forceinline__ void vec_dot_q2_K_q8_1_dp4a(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 
     constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q2_K, mmq_y);
     const int   * x_qs = (const int   *) x;
     const half2 * x_dm = (const half2 *) x_qs + txs.qs;
     const int   * y_qs = (const int   *) y + 4;
-    const float * y_df = (const float *) y;
+    const half2 * y_ds = (const half2 *) y;
 
+    float2 y_df[mmq_x/nwarps];
 #pragma unroll
     for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
         const int j = j0 + threadIdx.y;
 
+        y_df[j0/nwarps] = __half22float2(y_ds[j*MMQ_TILE_Y_K]);
+    }
+
 #pragma unroll
-        for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
-            const int i = i0 + threadIdx.x;
+    for (int k01 = 0; k01 < WARP_SIZE; k01 += QR2_K*VDR_Q2_K_Q8_1_MMQ) {
+        const int k0 = k00 + k01;
+
+#pragma unroll
+        for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
+            const int j = j0 + threadIdx.y;
+
+#pragma unroll
+            for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
+                const int i = i0 + threadIdx.x;
 
-            sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q2_K_q8_1_impl_mmq(
-                &x_qs[i*(WARP_SIZE + 1) + k0], &y_qs[j*MMQ_TILE_Y_K + (QR2_K*k0) % WARP_SIZE],
-                &x_dm[i*(WARP_SIZE + 1) + k0], y_df[j*MMQ_TILE_Y_K + ((QR2_K*k0) % WARP_SIZE)/QI8_1]);
+                if (k01 < WARP_SIZE/2) {
+                    constexpr int ns = 2;
+                    sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q2_K_q8_1_impl_mmq(
+                        &x_qs[i*(2*WARP_SIZE + 1) + k0], &y_qs[j*MMQ_TILE_Y_K + k01],
+                        &x_dm[i*(WARP_SIZE + 1) + k0/4], k01 < WARP_SIZE/2 ? y_df[j0/nwarps].x : y_df[j0/nwarps].y,
+                        &y_ds[j*MMQ_TILE_Y_K + (1 + k01/QI8_1)]);
+                } else {
+                    constexpr int ns = 1;
+                    sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q2_K_q8_1_impl_mmq(
+                        &x_qs[i*(2*WARP_SIZE + 1) + k0], &y_qs[j*MMQ_TILE_Y_K + k01],
+                        &x_dm[i*(WARP_SIZE + 1) + k0/4], k01 < WARP_SIZE/2 ? y_df[j0/nwarps].x : y_df[j0/nwarps].y,
+                        &y_ds[j*MMQ_TILE_Y_K + (1 + k01/QI8_1)]);
+                }
+            }
         }
     }
 }
 
 template 
 static __device__ __forceinline__ void vec_dot_q2_K_q8_1_mma(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 #ifdef INT8_MMA_AVAILABLE
 
     typedef mma_int_A_I16K4 mma_A;
+    typedef mma_int_A_I16K8 mma_A_K8;
     typedef mma_int_B_J8K4  mma_B;
     typedef mma_int_C_I16J8 mma_C;
 
@@ -1066,74 +1106,107 @@ static __device__ __forceinline__ void vec_dot_q2_K_q8_1_mma(
     y += (threadIdx.y % ntx) * (mma_B::J*MMQ_TILE_Y_K);
 
     const int   * x_qs = (const int   *) x;
-    const half2 * x_dm = (const half2 *) x_qs + WARP_SIZE;
+    const half2 * x_dm = (const half2 *) x_qs + WARP_SIZE*2;
     const int   * y_qs = (const int   *) y + 4;
-    const float * y_df = (const float *) y;
+    const half2 * y_ds = (const half2 *) y;
 
     const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I);
 
-    mma_A   A[ntx][2];
-    float  dA[ntx][mma_C::ne/2][2];
-    float  mA[ntx][mma_C::ne/2][2];
+    mma_A   A[ntx][8];
+    float  dA[ntx][mma_C::ne/2][8];
+    float  mA[ntx][mma_C::ne/2][8];
 
 #pragma unroll
     for (int n = 0; n < ntx; ++n) {
 #pragma unroll
-        for (int l = 0; l < mma_A::ne; ++l) {
-            const int i = i0 + n*mma_A::I + mma_A::get_i(l);
-            const int shift = 2*mma_A::get_k(l);
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += QI8_1) {
+            const int k0 = k00 + k01;
 
-            A[n][0].x[l] = (x_qs[i*MMQ_MMA_TILE_X_K_Q2_K + k0 + 0] >> shift) & 0x03030303;
-            A[n][1].x[l] = (x_qs[i*MMQ_MMA_TILE_X_K_Q2_K + k0 + 1] >> shift) & 0x03030303;
+            ((mma_A_K8 *) A[n])[k01/QI8_1].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q2_K + k0, MMQ_MMA_TILE_X_K_Q2_K);
         }
+    }
 
+#pragma unroll
+    for (int n = 0; n < ntx; ++n) {
 #pragma unroll
         for (int l = 0; l < mma_C::ne/2; ++l) {
             const int i = i0 + n*mma_C::I + mma_C::get_i(2*l);
 
 #pragma unroll
-            for (int kdm = 0; kdm < 2; ++kdm) {
-                const float2 dm = __half22float2(x_dm[i*MMQ_MMA_TILE_X_K_Q2_K + k0 + kdm]);
+            for (int k01 = 0; k01 < WARP_SIZE; k01 += QI8_1/2) {
+                const int k0 = k00 + k01;
 
-                dA[n][l][kdm] = dm.x;
-                mA[n][l][kdm] = dm.y;
+                const float2 dm = __half22float2(x_dm[i*MMQ_MMA_TILE_X_K_Q2_K + k0/(QI8_1/2)]);
+
+                dA[n][l][k01/(QI8_1/2)] = dm.x;
+                mA[n][l][k01/(QI8_1/2)] = dm.y;
             }
         }
     }
 
 #pragma unroll
     for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) {
-        mma_B B[2];
-        float dB[mma_C::ne/2];
-
-        B[0].load(y_qs + j0*MMQ_TILE_Y_K + (QR2_K*k0 + 0)        % WARP_SIZE, MMQ_TILE_Y_K);
-        B[1].load(y_qs + j0*MMQ_TILE_Y_K + (QR2_K*k0 + mma_B::K) % WARP_SIZE, MMQ_TILE_Y_K);
+        float2 dB[mma_C::ne/2];
 
 #pragma unroll
         for (int l = 0; l < mma_C::ne/2; ++l) {
             const int j = j0 + mma_C::get_j(l);
 
-            dB[l] = y_df[j*MMQ_TILE_Y_K + ((4*k0)/QI8_1) % (WARP_SIZE/QI8_1)];
+            dB[l] = __half22float2(y_ds[j*MMQ_TILE_Y_K]);
         }
 
-        mma_C Cm[2];
-        mma_A A1;
-        A1.x[0] = 0x01010101;
-        A1.x[1] = 0x01010101;
-        Cm[0].mma_K4(A1, B[0]);
-        Cm[1].mma_K4(A1, B[1]);
+#pragma unroll
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += QI8_1) {
+            mma_B B[2];
+
+            B[0].load(y_qs + j0*MMQ_TILE_Y_K + (k01 + 0),        MMQ_TILE_Y_K);
+            B[1].load(y_qs + j0*MMQ_TILE_Y_K + (k01 + mma_B::K), MMQ_TILE_Y_K);
+
+            mma_C Cm[2];
+            if (k01 >= WARP_SIZE * 3/4) {
+                mma_A A1;
+                A1.x[0] = 0x01010101;
+                A1.x[1] = 0x01010101;
+                Cm[0].mma_K4(A1, B[0]);
+                Cm[1].mma_K4(A1, B[1]);
+            }
 
 #pragma unroll
-    for (int n = 0; n < ntx; ++n) {
-            mma_C Cd[2];
+            for (int n = 0; n < ntx; ++n) {
+                mma_C Cd[2];
 
-            Cd[0].mma_K4(A[n][0], B[0]);
-            Cd[1].mma_K4(A[n][1], B[1]);
+                Cd[0].mma_K4(A[n][k01/4 + 0], B[0]);
+                Cd[1].mma_K4(A[n][k01/4 + 1], B[1]);
 
 #pragma unroll
-            for (int l = 0; l < mma_C::ne; ++l) {
-                sum[(j0/mma_C::J + n)*mma_C::ne + l] += (
-                    Cd[0].x[l]*dA[n][l/2][0] + Cd[1].x[l]*dA[n][l/2][1] - Cm[0].x[l]*mA[n][l/2][0] - Cm[1].x[l]*mA[n][l/2][1])*dB[l%2];
+                for (int l = 0; l < mma_C::ne; ++l) {
+                    float tmp = Cd[0].x[l]*dA[n][l/2][k01/4 + 0] + Cd[1].x[l]*dA[n][l/2][k01/4 + 1];
+                    if (k01 >= WARP_SIZE * 3/4) {
+                        tmp -= Cm[0].x[l]*mA[n][l/2][k01/4 + 0] + Cm[1].x[l]*mA[n][l/2][k01/4 + 1];
+                    }
+                    sum[(j0/mma_C::J + n)*mma_C::ne + l] += tmp*(k01 < WARP_SIZE/2 ? dB[l%2].x : dB[l%2].y);
+                }
+            }
+        }
+
+#pragma unroll
+        for (int k01 = 0; k01 < WARP_SIZE * 3/4; k01 += QI8_1) {
+            float2 sB[mma_C::ne/2];
+
+#pragma unroll
+            for (int l = 0; l < mma_C::ne/2; ++l) {
+                const int j = j0 + mma_C::get_j(l);
+
+                sB[l] = __half22float2(y_ds[j*MMQ_TILE_Y_K + (1 + k01/QI8_1)]);
+            }
+
+#pragma unroll
+            for (int n = 0; n < ntx; ++n) {
+#pragma unroll
+                for (int l = 0; l < mma_C::ne; ++l) {
+                    sum[(j0/mma_C::J + n)*mma_C::ne + l] -= mA[n][l/2][k01/4 + 0]*sB[l%2].x;
+                    sum[(j0/mma_C::J + n)*mma_C::ne + l] -= mA[n][l/2][k01/4 + 1]*sB[l%2].y;
+                }
             }
         }
     }
@@ -1149,7 +1222,7 @@ template  static __device__ __forceinlin
 #ifdef INT8_MMA_AVAILABLE
     int   * x_qs = (int   *)  x_tile;
     float * x_df = (float *) (x_qs + WARP_SIZE*2);
-    int   * x_sc = (int   *) (x_df + WARP_SIZE/QI3_K);
+    int   * x_sc = (int   *) (x_df + 1);
 #else
     constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q3_K, mmq_y);
     int   * x_qs = (int   *)  x_tile;
@@ -1157,75 +1230,66 @@ template  static __device__ __forceinlin
     int   * x_sc = (int   *) (x_df + txs.dm);
 #endif // INT8_MMA_AVAILABLE
 
-    const int kbx  = threadIdx.x / QI3_K;
     const int kqsx = threadIdx.x % QI3_K;
 
 #pragma unroll
-    for (int i0 = 0; i0 < mmq_y; i0 += nwarps) {
-        int i = i0 + threadIdx.y;
+    for (int i0 = 0; i0 < mmq_y; i0 += nwarps * WARP_SIZE/QI3_K) {
+        int i = i0 + threadIdx.y * (WARP_SIZE/QI3_K) + threadIdx.x / QI3_K;
 
         if (need_check) {
             i = min(i, i_max);
         }
 
-        const block_q3_K * bxi = (const block_q3_K *) x + kbx0 + i*stride + kbx;
+        const block_q3_K * bxi = (const block_q3_K *) x + kbx0 + i*stride;
 
         const int x_ql_0 = get_int_b2(bxi->qs,    kqsx);
         const int x_qh_0 = get_int_b2(bxi->hmask, kqsx % (QI3_K/2)) >> (4 * (kqsx / (QI3_K/2)));
 
 #pragma unroll
         for (int l = 0; l < QR3_K; ++l) {
-            const int k = kbx*(QR3_K*QI3_K) + (kqsx/8)*32 + l*8 + kqsx % 8;
+            const int k = (kqsx/8)*32 + l*8 + kqsx % 8;
 
             const int x_ql_k =  (x_ql_0 >> (2*l))       & 0x03030303;
             const int x_qh_k = ((x_qh_0 >>    l)  << 2) & 0x04040404;
 
-            int x_qs_k = (x_ql_k | x_qh_k) << (4*(k%2));
-            x_qs_k |= __shfl_xor_sync(0xFFFFFFFF, x_qs_k, 1, WARP_SIZE);
-
-            if (kqsx % 2 != 0) {
-                continue;
-            }
+            const int x_qs_k = __vsubss4(x_ql_k | x_qh_k, 0x04040404);
 
 #ifdef INT8_MMA_AVAILABLE
-            x_qs[i*MMQ_MMA_TILE_X_K_Q3_K + k/2] = x_qs_k;
+            x_qs[i*MMQ_MMA_TILE_X_K_Q3_K + k] = x_qs_k;
 #else
-            x_qs[i*(2*WARP_SIZE + 1)     + k/2] = x_qs_k;
+            x_qs[i*(2*WARP_SIZE + 1)     + k] = x_qs_k;
 #endif // INT8_MMA_AVAILABLE
         }
     }
 
-    const int blocks_per_tile_x_row = WARP_SIZE / QI3_K;
-    const int kbxd = threadIdx.x % blocks_per_tile_x_row;
-
 #pragma unroll
-    for (int i0 = 0; i0 < mmq_y; i0 += nwarps * QI3_K) {
-        int i = (i0 + threadIdx.y * QI3_K + threadIdx.x / blocks_per_tile_x_row) % mmq_y;
+    for (int i0 = 0; i0 < mmq_y; i0 += nwarps*WARP_SIZE) {
+        int i = (i0 + threadIdx.y*WARP_SIZE + threadIdx.x) % mmq_y;
 
         if (need_check) {
             i = min(i, i_max);
         }
 
-        const block_q3_K * bxi = (const block_q3_K *) x + kbx0 + i*stride + kbxd;
+        const block_q3_K * bxi = (const block_q3_K *) x + kbx0 + i*stride;
 
 #ifdef INT8_MMA_AVAILABLE
-        x_df[i*MMQ_MMA_TILE_X_K_Q3_K       + kbxd] = bxi->d;
+        x_df[i*MMQ_MMA_TILE_X_K_Q3_K] = bxi->d;
 #else
-        x_df[i*(WARP_SIZE/QI3_K) + i/QI3_K + kbxd] = bxi->d;
+        x_df[i]                       = bxi->d;
 #endif // INT8_MMA_AVAILABLE
     }
 
 #pragma unroll
-    for (int i0 = 0; i0 < mmq_y; i0 += nwarps * 4) {
-        int i = i0 + threadIdx.y * 4 + threadIdx.x / (WARP_SIZE/4);
+    for (int i0 = 0; i0 < mmq_y; i0 += nwarps*8) {
+        int i = i0 + threadIdx.y*8 + threadIdx.x/(WARP_SIZE/8);
 
         if (need_check) {
             i = min(i, i_max);
         }
 
-        const block_q3_K * bxi = (const block_q3_K *) x + kbx0 + i*stride + (threadIdx.x % (WARP_SIZE/4)) / (QI3_K/4);
+        const block_q3_K * bxi = (const block_q3_K *) x + kbx0 + i*stride;
 
-        const int ksc = threadIdx.x % (QI3_K/4);
+        const int ksc = threadIdx.x % (WARP_SIZE/8);
 
         const int ksc_low = ksc % (QI3_K/8);
         const int shift_low = 4 * (ksc / (QI3_K/8));
@@ -1238,16 +1302,16 @@ template  static __device__ __forceinlin
         const int sc = __vsubss4(sc_low | sc_high, 0x20202020);
 
 #ifdef INT8_MMA_AVAILABLE
-        x_sc[i*MMQ_MMA_TILE_X_K_Q3_K + threadIdx.x % (WARP_SIZE/4)] = sc;
+        x_sc[i*MMQ_MMA_TILE_X_K_Q3_K + threadIdx.x % (WARP_SIZE/8)] = sc;
 #else
-        x_sc[i*(WARP_SIZE/4) + i/4   + threadIdx.x % (WARP_SIZE/4)] = sc;
+        x_sc[i*(WARP_SIZE/8) + i/8   + threadIdx.x % (WARP_SIZE/8)] = sc;
 #endif // INT8_MMA_AVAILABLE
     }
 }
 
 template 
 static __device__ __forceinline__ void vec_dot_q3_K_q8_1_dp4a(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 
     constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q3_K, mmq_y);
     const int   * x_qs = (const int   *) x;
@@ -1256,32 +1320,35 @@ static __device__ __forceinline__ void vec_dot_q3_K_q8_1_dp4a(
     const int   * y_qs = (const int   *) y + 4;
     const float * y_df = (const float *) y;
 
-#pragma unroll
-    for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
-        const int j = j0 + threadIdx.y;
+// #pragma unroll
+    for (int k01 = 0; k01 < WARP_SIZE; k01 += QR3_K*VDR_Q3_K_Q8_1_MMQ) {
+        const int k0 = k00 + k01;
 
 #pragma unroll
-        for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
-            const int i = i0 + threadIdx.x;
+        for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
+            const int j = j0 + threadIdx.y;
 
-            const int kbx  = k0 / QI3_K;
-            const int ky  = (k0 % QI3_K) * QR3_K;
+#pragma unroll
+            for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
+                const int i = i0 + threadIdx.x;
 
-            const int8_t * scales = ((const int8_t *) (x_sc + i * (WARP_SIZE/4) + i/4 + kbx*4)) + ky/4;
+                const int8_t * scales = ((const int8_t *) (x_sc + i*(WARP_SIZE/8) + i/8)) + k0/4;
 
-            sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q3_K_q8_1_impl_mmq(
-                &x_qs[i*(2*WARP_SIZE + 1) + 2*k0], &y_qs[j*MMQ_TILE_Y_K + (k0*QR3_K) % WARP_SIZE], scales,
-                x_df[i*(WARP_SIZE/QI3_K) + i/QI3_K + kbx], y_df[j*MMQ_TILE_Y_K + ((k0*QR3_K) % WARP_SIZE)/QI8_1]);
+                sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q3_K_q8_1_impl_mmq(
+                    &x_qs[i*(2*WARP_SIZE + 1) + k0], &y_qs[j*MMQ_TILE_Y_K + k01], scales,
+                    x_df[i], y_df[j*MMQ_TILE_Y_K + k01/QI8_1]);
+            }
         }
     }
 }
 
 template 
 static __device__ __forceinline__ void vec_dot_q3_K_q8_1_mma(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 #ifdef INT8_MMA_AVAILABLE
 
     typedef mma_int_A_I16K4 mma_A;
+    typedef mma_int_A_I16K8 mma_A_K8;
     typedef mma_int_B_J8K4  mma_B;
     typedef mma_int_C_I16J8 mma_C;
 
@@ -1293,73 +1360,74 @@ static __device__ __forceinline__ void vec_dot_q3_K_q8_1_mma(
 
     const int   * x_qs = (const int   *) x;
     const float * x_df = (const float *) x_qs + WARP_SIZE*2;
-    const int   * x_sc = (const int   *) x_df + WARP_SIZE/QI3_K;
+    const int   * x_sc = (const int   *) x_df + 1;
     const int   * y_qs = (const int   *) y + 4;
     const float * y_df = (const float *) y;
 
     const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I);
 
-    mma_A   A[ntx][2];
-    int   scA[ntx][mma_C::ne/2][2];
+    mma_A   A[ntx][8];
+    int   scA[ntx][mma_C::ne/2][8];
     float  dA[ntx][mma_C::ne/2];
 
 #pragma unroll
     for (int n = 0; n < ntx; ++n) {
 #pragma unroll
-        for (int l = 0; l < mma_A::ne; ++l) {
-            const int i = i0 + n*mma_A::I + mma_A::get_i(l);
-            const int k = QR3_K*k0 + mma_A::get_k(l);
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += 8) {
+            const int k0 = k00 + k01;
 
-            A[n][0].x[l] = (x_qs[i*MMQ_MMA_TILE_X_K_Q3_K + k/2 + 0]          >> (4*(k%2))) & 0x0F0F0F0F;
-            A[n][1].x[l] = (x_qs[i*MMQ_MMA_TILE_X_K_Q3_K + k/2 + mma_A::K/2] >> (4*(k%2))) & 0x0F0F0F0F;
-            A[n][0].x[l] = __vsubss4(A[n][0].x[l], 0x04040404);
-            A[n][1].x[l] = __vsubss4(A[n][1].x[l], 0x04040404);
+            ((mma_A_K8 *) A[n])[k01/8].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q3_K + k0, MMQ_MMA_TILE_X_K_Q3_K);
         }
 
 #pragma unroll
         for (int l = 0; l < mma_C::ne/2; ++l) {
             const int i = i0 + n*mma_C::I + mma_C::get_i(2*l);
 
-            const int kbx  = k0 / QI3_K;
-            const int ky  = (k0 % QI3_K) * QR3_K;
-            const int8_t * sc = ((const int8_t *) (x_sc + i*MMQ_MMA_TILE_X_K_Q3_K + kbx*4)) + ky/4;
+#pragma unroll
+            for (int k01 = 0; k01 < WARP_SIZE; k01 += 16) {
+                const int k0 = k00 + k01;
 
-            scA[n][l][0] = sc[0];
-            scA[n][l][1] = sc[1];
-        }
+                const int sc_packed = x_sc[i*MMQ_MMA_TILE_X_K_Q3_K + k0/16];
+                const int8_t * sc = (const int8_t *) &sc_packed;
 
 #pragma unroll
-        for (int l = 0; l < mma_C::ne/2; ++l) {
-            const int i = i0 + n*mma_C::I + mma_C::get_i(2*l);
+                for (int ksc = 0; ksc < sizeof(int); ++ksc) {
+                    scA[n][l][k01/4 + ksc] = sc[ksc];
+                }
+            }
 
-            dA[n][l] = x_df[i*MMQ_MMA_TILE_X_K_Q3_K + k0/QI3_K];
+            dA[n][l] = x_df[i*MMQ_MMA_TILE_X_K_Q3_K];
         }
     }
 
 #pragma unroll
     for (int j0 = 0; j0 < mmq_x; j0 += ntx*mma_C::J) {
-        mma_B B[2];
-        float dB[mma_C::ne/2];
+#pragma unroll
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += QR3_K*VDR_Q3_K_Q8_1_MMQ) {
+            mma_B B[2];
+            float dB[mma_C::ne/2];
 
-        B[0].load(y_qs + j0*MMQ_TILE_Y_K + (QR3_K*k0 + 0)        % WARP_SIZE, MMQ_TILE_Y_K);
-        B[1].load(y_qs + j0*MMQ_TILE_Y_K + (QR3_K*k0 + mma_B::K) % WARP_SIZE, MMQ_TILE_Y_K);
+            B[0].load(y_qs + j0*MMQ_TILE_Y_K + (k01 + 0),        MMQ_TILE_Y_K);
+            B[1].load(y_qs + j0*MMQ_TILE_Y_K + (k01 + mma_B::K), MMQ_TILE_Y_K);
 
 #pragma unroll
-        for (int l = 0; l < mma_C::ne/2; ++l) {
-            const int j = j0 + mma_C::get_j(l);
+            for (int l = 0; l < mma_C::ne/2; ++l) {
+                const int j = j0 + mma_C::get_j(l);
 
-            dB[l] = y_df[j*MMQ_TILE_Y_K + ((4*k0)/QI8_1) % (WARP_SIZE/QI8_1)];
-        }
+                dB[l] = y_df[j*MMQ_TILE_Y_K + k01/QI8_1];
+            }
 
 #pragma unroll
-        for (int n = 0; n < ntx; ++n) {
-            mma_C C[2];
-            C[0].mma_K4(A[n][0], B[0]);
-            C[1].mma_K4(A[n][1], B[1]);
+            for (int n = 0; n < ntx; ++n) {
+                mma_C C[2];
+                C[0].mma_K4(A[n][k01/4 + 0], B[0]);
+                C[1].mma_K4(A[n][k01/4 + 1], B[1]);
 
 #pragma unroll
-            for (int l = 0; l < mma_C::ne; ++l) {
-                sum[(j0/mma_C::J + n)*mma_C::ne + l] += (C[0].x[l]*scA[n][l/2][0] + C[1].x[l]*scA[n][l/2][1])*dA[n][l/2]*dB[l%2];
+                for (int l = 0; l < mma_C::ne; ++l) {
+                    sum[(j0/mma_C::J + n)*mma_C::ne + l] += dA[n][l/2]*dB[l%2]*
+                        (C[0].x[l]*scA[n][l/2][k01/4 + 0] + C[1].x[l]*scA[n][l/2][k01/4 + 1]);
+                }
             }
         }
     }
@@ -1451,7 +1519,7 @@ template  static __device__ __forceinlin
 
 template 
 static __device__ __forceinline__ void vec_dot_q4_K_q8_1_dp4a(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 
     constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q4_K, mmq_y);
     const int   * x_qs = (const int   *) x;
@@ -1460,26 +1528,31 @@ static __device__ __forceinline__ void vec_dot_q4_K_q8_1_dp4a(
     const int   * y_qs = (const int   *) y + 4;
     const half2 * y_ds = (const half2 *) y;
 
+// #pragma unroll
+    for (int k01 = 0; k01 < WARP_SIZE; k01 += QR4_K*VDR_Q4_K_Q8_1_MMQ) {
+        const int k0 = k00 + k01;
+
 #pragma unroll
-    for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
-        const int j = j0 + threadIdx.y;
+        for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
+            const int j = j0 + threadIdx.y;
 
 #pragma unroll
-        for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
-            const int i = i0 + threadIdx.x;
+            for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
+                const int i = i0 + threadIdx.x;
 
-            const uint8_t * sc = ((const uint8_t *) &x_sc[i * (WARP_SIZE/8) + i/8 + k0/16]) + 2*((k0 % 16) / 8);
+                const uint8_t * sc = (const uint8_t *) &x_sc[i * (WARP_SIZE/8) + i/8 + k0/32] + 2*(k01/16);
 
-            sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q4_K_q8_1_impl_mmq(
-                &x_qs[i*(WARP_SIZE + 1) + k0], &y_qs[j*MMQ_TILE_Y_K + (QR4_K*k0) % WARP_SIZE], sc, sc+8,
-                x_dm[i*(WARP_SIZE/QI4_K) + i/QI4_K], &y_ds[j*MMQ_TILE_Y_K + ((QR4_K*k0) % WARP_SIZE)/QI8_1]);
+                sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q4_K_q8_1_impl_mmq(
+                    &x_qs[i*(WARP_SIZE + 1) + k0/2], &y_qs[j*MMQ_TILE_Y_K + k01], sc, sc+8,
+                    x_dm[i*(WARP_SIZE/QI4_K) + i/QI4_K], &y_ds[j*MMQ_TILE_Y_K + k01/QI8_1]);
+            }
         }
     }
 }
 
 template 
 static __device__ __forceinline__ void vec_dot_q4_K_q8_1_mma(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 #ifdef INT8_MMA_AVAILABLE
 
     typedef mma_int_A_I16K8 mma_A;
@@ -1500,35 +1573,40 @@ static __device__ __forceinline__ void vec_dot_q4_K_q8_1_mma(
 
     const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I);
 
-    mma_A   A[ntx][2];
-    int   scA[ntx][mma_C::ne/2][2];
-    int    mA[ntx][mma_C::ne/2][2];
+    mma_A   A[ntx][4];
+    int   scA[ntx][mma_C::ne/2][4];
+    int    mA[ntx][mma_C::ne/2][4];
     half2 dmA[ntx][mma_C::ne/2];
 
 #pragma unroll
     for (int n = 0; n < ntx; ++n) {
 #pragma unroll
-        for (int kvdr = 0; kvdr < VDR_Q4_K_Q8_1_MMQ; kvdr += 8) {
-            A[n][kvdr/4 + 0].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q4_K + k0, MMQ_MMA_TILE_X_K_Q4_K);
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += 16) {
+            const int k0 = k00 + k01;
+
+            A[n][k01/8 + 0].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q4_K + k0/QR4_K, MMQ_MMA_TILE_X_K_Q4_K);
 
 #pragma unroll
             for (int l = 0; l < mma_A::ne; ++l) {
-                A[n][kvdr/4 + 1].x[l]  = (A[n][kvdr/4 + 0].x[l] >> 4) & 0x0F0F0F0F;
-                A[n][kvdr/4 + 0].x[l] &= 0x0F0F0F0F;
+                A[n][k01/8 + 1].x[l]  = (A[n][k01/8 + 0].x[l] >> 4) & 0x0F0F0F0F;
+                A[n][k01/8 + 0].x[l] &= 0x0F0F0F0F;
             }
         }
 
 #pragma unroll
-        for (int kvdr = 0; kvdr < VDR_Q4_K_Q8_1_MMQ; kvdr += 4) {
-#pragma unroll
-            for (int l = 0; l < mma_C::ne/2; ++l) {
-                const int i = i0 + n*mma_A::I + mma_C::get_i(2*l);
+        for (int l = 0; l < mma_C::ne/2; ++l) {
+            const int i = i0 + n*mma_C::I + mma_C::get_i(2*l);
+
+            const int sc_packed = x_sc[i*MMQ_MMA_TILE_X_K_Q4_K + (k00/32 + 0)];
+            const int  m_packed = x_sc[i*MMQ_MMA_TILE_X_K_Q4_K + (k00/32 + 2)];
 
-                const uint8_t * sc = ((const uint8_t *) &x_sc[i*MMQ_MMA_TILE_X_K_Q4_K + k0/16]) + 2 * ((k0 % 16) / 8);
-                const uint8_t *  m = sc + 8;
+            const uint8_t * sc = (const uint8_t *) &sc_packed;
+            const uint8_t *  m = (const uint8_t *)  &m_packed;
 
-                scA[n][l][kvdr/4] = sc[kvdr/4];
-                mA[n][l][kvdr/4]  =  m[kvdr/4];
+#pragma unroll
+            for (int ksc = 0; ksc < sizeof(int); ++ksc) {
+                scA[n][l][ksc] = sc[ksc];
+                mA[n][l][ksc]  =  m[ksc];
             }
         }
 
@@ -1536,7 +1614,7 @@ static __device__ __forceinline__ void vec_dot_q4_K_q8_1_mma(
         for (int l = 0; l < mma_C::ne/2; ++l) {
             const int i = i0 + n*mma_A::I + mma_C::get_i(2*l);
 
-            dmA[n][l] = x_dm[i*MMQ_MMA_TILE_X_K_Q4_K + k0/QI4_K];
+            dmA[n][l] = x_dm[i*MMQ_MMA_TILE_X_K_Q4_K];
         }
     }
 
@@ -1546,28 +1624,28 @@ static __device__ __forceinline__ void vec_dot_q4_K_q8_1_mma(
         float tmpm[ntx][mma_C::ne] = {{0.0f}};
 
 #pragma unroll
-        for (int kvdr = 0; kvdr < VDR_Q4_K_Q8_1_MMQ; kvdr += 4) {
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += 8) {
             mma_B   B;
             half2 dsB[mma_C::ne/2];
 
-            B.load(y_qs + j0*MMQ_TILE_Y_K + (2*k0 + 2*kvdr) % WARP_SIZE, MMQ_TILE_Y_K);
+            B.load(y_qs + j0*MMQ_TILE_Y_K + k01, MMQ_TILE_Y_K);
 
 #pragma unroll
             for (int l = 0; l < mma_C::ne/2; ++l) {
                 const int j = j0 + mma_C::get_j(l);
 
-                dsB[l] = y_ds[j*MMQ_TILE_Y_K + ((2*k0 + 2*kvdr)/QI8_1) % (WARP_SIZE/QI8_1)];
+                dsB[l] = y_ds[j*MMQ_TILE_Y_K + k01/QI8_1];
             }
 
 #pragma unroll
             for (int n = 0; n < ntx; ++n) {
                 mma_C C;
-                C.mma_K8(A[n][kvdr/4], B);
+                C.mma_K8(A[n][k01/8], B);
 
 #pragma unroll
                 for (int l = 0; l < mma_C::ne; ++l) {
-                    tmpd[n][l] += (C.x[l]*scA[n][l/2][kvdr/4]) *  __low2float(dsB[l%2]);
-                    tmpm[n][l] += mA[n][l/2][kvdr/4]           * __high2float(dsB[l%2]);
+                    tmpd[n][l] += (C.x[l]*scA[n][l/2][k01/8]) *  __low2float(dsB[l%2]);
+                    tmpm[n][l] += mA[n][l/2][k01/8]           * __high2float(dsB[l%2]);
                 }
             }
         }
@@ -1682,7 +1760,7 @@ template  static __device__ __forceinlin
 
 template 
 static __device__ __forceinline__ void vec_dot_q5_K_q8_1_dp4a(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 
     constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q5_K, mmq_y);
     const int   * x_qs = (const int   *) x;
@@ -1691,26 +1769,31 @@ static __device__ __forceinline__ void vec_dot_q5_K_q8_1_dp4a(
     const int   * y_qs = (const int   *) y + 4;
     const half2 * y_ds = (const half2 *) y;
 
+// #pragma unroll
+    for (int k01 = 0; k01 < WARP_SIZE; k01 += QR5_K*VDR_Q5_K_Q8_1_MMQ) {
+        const int k0 = k00 + k01;
+
 #pragma unroll
-    for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
-        const int j = j0 + threadIdx.y;
+        for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
+            const int j = j0 + threadIdx.y;
 
 #pragma unroll
-        for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
-            const int i = i0 + threadIdx.x;
+            for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
+                const int i = i0 + threadIdx.x;
 
-            const uint8_t * sc = ((const uint8_t *) &x_sc[i * (WARP_SIZE/8) + i/8 + k0/16]) + 2 * ((k0 % 16) / 8);
+                const uint8_t * sc = ((const uint8_t *) &x_sc[i * (WARP_SIZE/8) + i/8 + k00/32]) + 2*(k01/16);
 
-            sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q5_K_q8_1_impl_mmq(
-                &x_qs[i*(QR5_K*WARP_SIZE + 1) + QR5_K*k0], &y_qs[j*MMQ_TILE_Y_K + (QR5_K*k0) % WARP_SIZE], sc, sc+8,
-                x_dm[i*(WARP_SIZE/QI5_K) + i/QI5_K], &y_ds[j*MMQ_TILE_Y_K + ((QR5_K*k0) % WARP_SIZE)/QI8_1]);
+                sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q5_K_q8_1_impl_mmq(
+                    &x_qs[i*(QR5_K*WARP_SIZE + 1) + k0], &y_qs[j*MMQ_TILE_Y_K + k01], sc, sc+8,
+                    x_dm[i*(WARP_SIZE/QI5_K) + i/QI5_K], &y_ds[j*MMQ_TILE_Y_K + k01/QI8_1]);
+            }
         }
     }
 }
 
 template 
 static __device__ __forceinline__ void vec_dot_q5_K_q8_1_mma(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 #ifdef INT8_MMA_AVAILABLE
 
     typedef mma_int_A_I16K8 mma_A;
@@ -1731,26 +1814,34 @@ static __device__ __forceinline__ void vec_dot_q5_K_q8_1_mma(
 
     const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I);
 
-    mma_A   A[ntx][2];
-    int   scA[ntx][mma_C::ne/2][2];
-    int    mA[ntx][mma_C::ne/2][2];
+    mma_A   A[ntx][4];
+    int   scA[ntx][mma_C::ne/2][4];
+    int    mA[ntx][mma_C::ne/2][4];
     half2 dmA[ntx][mma_C::ne/2];
 
 #pragma unroll
     for (int n = 0; n < ntx; ++n) {
 #pragma unroll
-        for (int kvdr = 0; kvdr < VDR_Q5_K_Q8_1_MMQ; kvdr += 4) {
-            A[n][kvdr/4].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q5_K + (QR5_K*k0 + QR5_K*kvdr), MMQ_MMA_TILE_X_K_Q5_K);
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += 8) {
+            const int k0 = k00 + k01;
+
+            A[n][k01/8].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q5_K + k0, MMQ_MMA_TILE_X_K_Q5_K);
+        }
 
 #pragma unroll
-            for (int l = 0; l < mma_C::ne/2; ++l) {
-                const int i = i0 + n*mma_C::I + mma_C::get_i(2*l);
+        for (int l = 0; l < mma_C::ne/2; ++l) {
+            const int i = i0 + n*mma_C::I + mma_C::get_i(2*l);
+
+            const int sc_packed = x_sc[i*MMQ_MMA_TILE_X_K_Q5_K + (k00/32 + 0)];
+            const int  m_packed = x_sc[i*MMQ_MMA_TILE_X_K_Q5_K + (k00/32 + 2)];
 
-                const uint8_t * sc = ((const uint8_t *) &x_sc[i*MMQ_MMA_TILE_X_K_Q5_K + k0/16]) + 2 * ((k0 % 16) / 8);
-                const uint8_t *  m = sc + 8;
+            const uint8_t * sc = (const uint8_t *) &sc_packed;
+            const uint8_t *  m = (const uint8_t *)  &m_packed;
 
-                scA[n][l][kvdr/4] = sc[kvdr/4];
-                mA[n][l][kvdr/4]  =  m[kvdr/4];
+#pragma unroll
+            for (int ksc = 0; ksc < sizeof(int); ++ksc) {
+                scA[n][l][ksc] = sc[ksc];
+                mA[n][l][ksc]  =  m[ksc];
             }
         }
 
@@ -1758,7 +1849,7 @@ static __device__ __forceinline__ void vec_dot_q5_K_q8_1_mma(
         for (int l = 0; l < mma_C::ne/2; ++l) {
             const int i = i0 + n*mma_C::I + mma_C::get_i(2*l);
 
-            dmA[n][l] = x_dm[i*MMQ_MMA_TILE_X_K_Q5_K + k0/QI5_K];
+            dmA[n][l] = x_dm[i*MMQ_MMA_TILE_X_K_Q5_K];
         }
     }
 
@@ -1768,28 +1859,30 @@ static __device__ __forceinline__ void vec_dot_q5_K_q8_1_mma(
         float tmpm[ntx][mma_C::ne] = {{0.0f}};
 
 #pragma unroll
-        for (int kvdr = 0; kvdr < VDR_Q5_K_Q8_1_MMQ; kvdr += 4) {
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += 8) {
+            const int k0 = k00 + k01;
+
             mma_B   B;
             half2 dsB[mma_C::ne/2];
 
-            B.load(y_qs + j0*MMQ_TILE_Y_K + (2*k0 + 2*kvdr) % WARP_SIZE, MMQ_TILE_Y_K);
+            B.load(y_qs + j0*MMQ_TILE_Y_K + k0 % WARP_SIZE, MMQ_TILE_Y_K);
 
 #pragma unroll
             for (int l = 0; l < mma_C::ne/2; ++l) {
                 const int j = j0 + mma_C::get_j(l);
 
-                dsB[l] = y_ds[j*MMQ_TILE_Y_K + ((2*k0 + 2*kvdr)/QI8_1) % (WARP_SIZE/QI8_1)];
+                dsB[l] = y_ds[j*MMQ_TILE_Y_K + (k0/QI8_1) % (WARP_SIZE/QI8_1)];
             }
 
 #pragma unroll
         for (int n = 0; n < ntx; ++n) {
                 mma_C C;
-                C.mma_K8(A[n][kvdr/4], B);
+                C.mma_K8(A[n][k01/8], B);
 
 #pragma unroll
                 for (int l = 0; l < mma_C::ne; ++l) {
-                    tmpd[n][l] += (C.x[l]*scA[n][l/2][kvdr/4]) *  __low2float(dsB[l%2]);
-                    tmpm[n][l] += mA[n][l/2][kvdr/4]           * __high2float(dsB[l%2]);
+                    tmpd[n][l] += (C.x[l]*scA[n][l/2][k01/8]) *  __low2float(dsB[l%2]);
+                    tmpm[n][l] += mA[n][l/2][k01/8]           * __high2float(dsB[l%2]);
                 }
             }
         }
@@ -1896,7 +1989,7 @@ template  static __device__ __forceinlin
 
 template 
 static __device__ __forceinline__ void vec_dot_q6_K_q8_1_dp4a(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 
     constexpr tile_x_sizes txs = mmq_get_dp4a_tile_x_sizes(GGML_TYPE_Q6_K, mmq_y);
     const int   * x_qs = (const int   *) x;
@@ -1905,26 +1998,31 @@ static __device__ __forceinline__ void vec_dot_q6_K_q8_1_dp4a(
     const int   * y_qs = (const int   *) y + 4;
     const float * y_df = (const float *) y;
 
+// #pragma unroll
+    for (int k01 = 0; k01 < WARP_SIZE; k01 += QR6_K*VDR_Q6_K_Q8_1_MMQ) {
+        const int k0 = k00 + k01;
+
 #pragma unroll
-    for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
-        const int j = j0 + threadIdx.y;
+        for (int j0 = 0; j0 < mmq_x; j0 += nwarps) {
+            const int j = j0 + threadIdx.y;
 
 #pragma unroll
-        for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
-            const int i = i0 + threadIdx.x;
+            for (int i0 = 0; i0 < mmq_y; i0 += WARP_SIZE) {
+                const int i = i0 + threadIdx.x;
 
-            const int8_t * sc = ((const int8_t *) &x_sc[i * (WARP_SIZE/8) + i/8 + k0/8]);
+                const int8_t * sc = ((const int8_t *) &x_sc[i * (WARP_SIZE/8) + i/8 + k0/16]);
 
-            sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q6_K_q8_1_impl_mmq(
-                &x_qs[i*(QR6_K*WARP_SIZE + 1) + QR6_K*k0], &y_qs[j*MMQ_TILE_Y_K + (QR6_K*k0) % WARP_SIZE], sc,
-                x_df[i*(WARP_SIZE/QI6_K) + i/QI6_K], &y_df[j*MMQ_TILE_Y_K + ((QR6_K*k0) % WARP_SIZE)/QI8_1]);
+                sum[j0/nwarps*mmq_y/WARP_SIZE + i0/WARP_SIZE] += vec_dot_q6_K_q8_1_impl_mmq(
+                    &x_qs[i*(QR6_K*WARP_SIZE + 1) + k0], &y_qs[j*MMQ_TILE_Y_K + k01], sc,
+                    x_df[i*(WARP_SIZE/QI6_K) + i/QI6_K], &y_df[j*MMQ_TILE_Y_K + k01/QI8_1]);
+            }
         }
     }
 }
 
 template 
 static __device__ __forceinline__ void vec_dot_q6_K_q8_1_mma(
-    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k0) {
+    const int * __restrict__ x, const int * __restrict__ y, float * __restrict__ sum, const int & k00) {
 #ifdef INT8_MMA_AVAILABLE
 
     typedef mma_int_A_I16K4 mma_A;
@@ -1945,25 +2043,35 @@ static __device__ __forceinline__ void vec_dot_q6_K_q8_1_mma(
 
     const int i0 = (threadIdx.y / ntx) * (ntx*mma_A::I);
 
-    mma_A   A[ntx][4];
-    int   scA[ntx][mma_C::ne/2][4];
+    mma_A   A[ntx][8];
+    int   scA[ntx][mma_C::ne/2][8];
     float  dA[ntx][mma_C::ne/2];
 
 #pragma unroll
     for (int n = 0; n < ntx; ++n) {
 #pragma unroll
-        for (int kvdr = 0; kvdr < VDR_Q6_K_Q8_1_MMQ; kvdr += 4) {
-            A[n][kvdr/2 + 0].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q6_K + (QR6_K*k0 + QR6_K*kvdr + 0),        MMQ_MMA_TILE_X_K_Q6_K);
-            A[n][kvdr/2 + 1].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q6_K + (QR6_K*k0 + QR6_K*kvdr + mma_A::K), MMQ_MMA_TILE_X_K_Q6_K);
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += 8) {
+            const int k0 = k00 + k01;
+
+            A[n][k01/4 + 0].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q6_K + (k0 + 0),        MMQ_MMA_TILE_X_K_Q6_K);
+            A[n][k01/4 + 1].load(x_qs + (i0 + n*mma_A::I)*MMQ_MMA_TILE_X_K_Q6_K + (k0 + mma_A::K), MMQ_MMA_TILE_X_K_Q6_K);
+        }
+
+#pragma unroll
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += 16) {
+            const int k0 = k00 + k01;
 
 #pragma unroll
             for (int l = 0; l < mma_C::ne/2; ++l) {
                 const int i = i0 + n*mma_C::I + mma_C::get_i(2*l);
 
-                const int8_t * sc = ((const int8_t *) &x_sc[i*MMQ_MMA_TILE_X_K_Q6_K + k0/8]);
+                const int      sc_packed = x_sc[i*MMQ_MMA_TILE_X_K_Q6_K + k0/16];
+                const int8_t * sc        = (const int8_t *) &sc_packed;
 
-                scA[n][l][kvdr/2 + 0] = sc[kvdr/2 + 0];
-                scA[n][l][kvdr/2 + 1] = sc[kvdr/2 + 1];
+#pragma unroll
+                for (int ksc = 0; ksc < sizeof(int); ++ksc) {
+                    scA[n][l][k01/4 + ksc] = sc[ksc];
+                }
             }
         }
 
@@ -1971,7 +2079,7 @@ static __device__ __forceinline__ void vec_dot_q6_K_q8_1_mma(
         for (int l = 0; l < mma_C::ne/2; ++l) {
             const int i = i0 + n*mma_C::I + mma_C::get_i(2*l);
 
-            dA[n][l] = x_df[i*MMQ_MMA_TILE_X_K_Q6_K + k0/QI6_K];
+            dA[n][l] = x_df[i*MMQ_MMA_TILE_X_K_Q6_K];
         }
     }
 
@@ -1980,30 +2088,29 @@ static __device__ __forceinline__ void vec_dot_q6_K_q8_1_mma(
         float tmp[ntx][mma_C::ne] = {{0.0f}};
 
 #pragma unroll
-        for (int kvdr = 0; kvdr < VDR_Q6_K_Q8_1_MMQ; kvdr += 4) {
+        for (int k01 = 0; k01 < WARP_SIZE; k01 += 8) {
             mma_B B[2];
             float dB[mma_C::ne/2];
 
-            const int k0B = (2*k0 + 2*kvdr) % WARP_SIZE;
-            B[0].load(y_qs + j0*MMQ_TILE_Y_K + 0        + k0B, MMQ_TILE_Y_K);
-            B[1].load(y_qs + j0*MMQ_TILE_Y_K + mma_B::K + k0B, MMQ_TILE_Y_K);
+            B[0].load(y_qs + j0*MMQ_TILE_Y_K + 0        + k01, MMQ_TILE_Y_K);
+            B[1].load(y_qs + j0*MMQ_TILE_Y_K + mma_B::K + k01, MMQ_TILE_Y_K);
 
 #pragma unroll
             for (int l = 0; l < mma_C::ne/2; ++l) {
                 const int j = j0 + mma_C::get_j(l);
 
-                dB[l] = y_df[j*MMQ_TILE_Y_K + ((2*k0 + 2*kvdr)/QI8_1) % (WARP_SIZE/QI8_1)];
+                dB[l] = y_df[j*MMQ_TILE_Y_K + k01/QI8_1];
             }
 
 #pragma unroll
             for (int n = 0; n < ntx; ++n) {
                 mma_C C[2];
-                C[0].mma_K4(A[n][kvdr/2 + 0], B[0]);
-                C[1].mma_K4(A[n][kvdr/2 + 1], B[1]);
+                C[0].mma_K4(A[n][k01/4 + 0], B[0]);
+                C[1].mma_K4(A[n][k01/4 + 1], B[1]);
 
 #pragma unroll
                 for (int l = 0; l < mma_C::ne; ++l) {
-                    tmp[n][l] += (C[0].x[l]*scA[n][l/2][kvdr/2 + 0] + C[1].x[l]*scA[n][l/2][kvdr/2 + 1])*dB[l%2];
+                    tmp[n][l] += (C[0].x[l]*scA[n][l/2][k01/4 + 0] + C[1].x[l]*scA[n][l/2][k01/4 + 1])*dB[l%2];
                 }
             }
         }
@@ -2051,8 +2158,8 @@ template  static __device__ __forceinlin
         const int2 v = get_int_from_table_16(aux_q4);
         const int k0 = 8 * (threadIdx.x / 4) + threadIdx.x % 4;
 #ifdef INT8_MMA_AVAILABLE
-        x_qs[i*MMQ_MMA_TILE_X_K_Q5_0 + k0 + 0] = v.x;
-        x_qs[i*MMQ_MMA_TILE_X_K_Q5_0 + k0 + 4] = v.y;
+        x_qs[i*MMQ_MMA_TILE_X_K_Q8_0 + k0 + 0] = v.x;
+        x_qs[i*MMQ_MMA_TILE_X_K_Q8_0 + k0 + 4] = v.y;
 #else
         x_qs[i*(2*WARP_SIZE + 1)     + k0 + 0] = v.x;
         x_qs[i*(2*WARP_SIZE + 1)     + k0 + 4] = v.y;
@@ -2073,7 +2180,7 @@ template  static __device__ __forceinlin
         const block_iq4_nl * bxi = (const block_iq4_nl *) x + kbx0 + i*stride + kbxd;
 
 #ifdef INT8_MMA_AVAILABLE
-        x_df[i*MMQ_MMA_TILE_X_K_Q5_0 + kbxd] = __half2float(bxi->d);
+        x_df[i*MMQ_MMA_TILE_X_K_Q8_0 + kbxd] = __half2float(bxi->d);
 #else
         x_df[i*(WARP_SIZE/4) + i/4   + kbxd] = __half2float(bxi->d);
 #endif // INT8_MMA_AVAILABLE
@@ -2109,8 +2216,8 @@ template  static __device__ __forceinlin
         const int2 v = get_int_from_table_16(aux_q4);
         const int k0 = 8 * (threadIdx.x / 4) + threadIdx.x % 4;
 #ifdef INT8_MMA_AVAILABLE
-        x_qs[i*MMQ_MMA_TILE_X_K_Q5_0 + k0 + 0] = v.x;
-        x_qs[i*MMQ_MMA_TILE_X_K_Q5_0 + k0 + 4] = v.y;
+        x_qs[i*MMQ_MMA_TILE_X_K_Q8_0 + k0 + 0] = v.x;
+        x_qs[i*MMQ_MMA_TILE_X_K_Q8_0 + k0 + 4] = v.y;
 #else
         x_qs[i*(2*WARP_SIZE + 1)     + k0 + 0] = v.x;
         x_qs[i*(2*WARP_SIZE + 1)     + k0 + 4] = v.y;
@@ -2133,7 +2240,7 @@ template  static __device__ __forceinlin
             | (((bxi->scales_h >> (2*(threadIdx.x % 8))) & 0x03) << 4);
 
 #ifdef INT8_MMA_AVAILABLE
-        x_df[i*MMQ_MMA_TILE_X_K_Q5_0 + threadIdx.x % 8] = d * (ls - 32);
+        x_df[i*MMQ_MMA_TILE_X_K_Q8_0 + threadIdx.x % 8] = d * (ls - 32);
 #else
         x_df[i*(WARP_SIZE/4) + i/4   + threadIdx.x % 8] = d * (ls - 32);
 #endif // INT8_MMA_AVAILABLE
@@ -2229,16 +2336,16 @@ template 
 struct mmq_type_traits {
     static constexpr int              vdr          = VDR_Q5_0_Q8_1_MMQ;
     static constexpr load_tiles_mmq_t load_tiles   = load_tiles_q5_0;
-    static constexpr vec_dot_mmq_t    vec_dot_mma  = vec_dot_q5_0_q8_1_mma;
-    static constexpr vec_dot_mmq_t    vec_dot_dp4a = vec_dot_q5_0_q8_1_dp4a;
+    static constexpr vec_dot_mmq_t    vec_dot_mma  = vec_dot_q8_0_q8_1_mma;
+    static constexpr vec_dot_mmq_t    vec_dot_dp4a = vec_dot_q8_0_q8_1_dp4a;
 };
 
 template 
 struct mmq_type_traits {
     static constexpr int              vdr          = VDR_Q5_1_Q8_1_MMQ;
     static constexpr load_tiles_mmq_t load_tiles   = load_tiles_q5_1;
-    static constexpr vec_dot_mmq_t    vec_dot_mma  = vec_dot_q5_1_q8_1_mma;
-    static constexpr vec_dot_mmq_t    vec_dot_dp4a = vec_dot_q5_1_q8_1_dp4a;
+    static constexpr vec_dot_mmq_t    vec_dot_mma  = vec_dot_q8_1_q8_1_mma;
+    static constexpr vec_dot_mmq_t    vec_dot_dp4a = vec_dot_q8_1_q8_1_dp4a;
 };
 
 template 
@@ -2293,45 +2400,18 @@ template 
 struct mmq_type_traits {
     static constexpr int              vdr          = VDR_IQ4_NL_Q8_1_MMQ;
     static constexpr load_tiles_mmq_t load_tiles   = load_tiles_iq4_nl;
-    static constexpr vec_dot_mmq_t    vec_dot_mma  = vec_dot_q5_0_q8_1_mma;
-    static constexpr vec_dot_mmq_t    vec_dot_dp4a = vec_dot_q5_0_q8_1_dp4a;
+    static constexpr vec_dot_mmq_t    vec_dot_mma  = vec_dot_q8_0_q8_1_mma;
+    static constexpr vec_dot_mmq_t    vec_dot_dp4a = vec_dot_q8_0_q8_1_dp4a;
 };
 
 template 
 struct mmq_type_traits {
     static constexpr int              vdr          = VDR_IQ4_XS_Q8_1_MMQ;
     static constexpr load_tiles_mmq_t load_tiles   = load_tiles_iq4_xs;
-    static constexpr vec_dot_mmq_t    vec_dot_mma  = vec_dot_q5_0_q8_1_mma;
-    static constexpr vec_dot_mmq_t    vec_dot_dp4a = vec_dot_q5_0_q8_1_dp4a;
+    static constexpr vec_dot_mmq_t    vec_dot_mma  = vec_dot_q8_0_q8_1_mma;
+    static constexpr vec_dot_mmq_t    vec_dot_dp4a = vec_dot_q8_0_q8_1_dp4a;
 };
 
-static bool mmq_need_sum(const ggml_type type_x) {
-    switch (type_x) {
-        case GGML_TYPE_Q4_0:
-        case GGML_TYPE_Q4_1:
-            return true;
-        case GGML_TYPE_Q5_0:
-            return false;
-        case GGML_TYPE_Q5_1:
-            return true;
-        case GGML_TYPE_Q8_0:
-        case GGML_TYPE_Q2_K:
-        case GGML_TYPE_Q3_K:
-            return false;
-        case GGML_TYPE_Q4_K:
-        case GGML_TYPE_Q5_K:
-            return true;
-        case GGML_TYPE_Q6_K:
-        case GGML_TYPE_IQ4_XS:
-        case GGML_TYPE_IQ4_NL:
-            return false;
-        default:
-            GGML_ASSERT(false);
-            break;
-    }
-    return false;
-}
-
 template 
 static __device__ void mul_mat_q_process_tile(
     const char * __restrict__ x, const char * __restrict__ yc, float * __restrict__ dst, float * __restrict__ tmp_fixup,
@@ -2339,10 +2419,7 @@ static __device__ void mul_mat_q_process_tile(
     const int & it, const int & jt, const int & kb0_start, const int & kb0_stop) {
 
     constexpr int              qk         = ggml_cuda_type_traits::qk;
-    constexpr int              qr         = ggml_cuda_type_traits::qr;
-    constexpr int              qi         = ggml_cuda_type_traits::qi;
     constexpr int              mmq_y      = get_mmq_y_device();
-    constexpr int              vdr        = mmq_type_traits::vdr;
     constexpr load_tiles_mmq_t load_tiles = mmq_type_traits::load_tiles;
 
     extern __shared__ char data_mul_mat_q[];
@@ -2357,7 +2434,7 @@ static __device__ void mul_mat_q_process_tile(
     constexpr mmq_write_back_t write_back = mmq_write_back_dp4a;
 #endif // INT8_MMA_AVAILABLE
 
-    constexpr int blocks_per_warp = WARP_SIZE / qi;
+    constexpr int blocks_per_iter = MMQ_ITER_K / qk;
 
     float sum[mmq_x*mmq_y / (nwarps*WARP_SIZE)] = {0.0f};
 
@@ -2366,29 +2443,40 @@ static __device__ void mul_mat_q_process_tile(
 
     const int * y = (const int *) yc + jt*(mmq_x*sizeof(block_q8_1_mmq)/sizeof(int));
 
-    for (int kb0 = kb0_start; kb0 < kb0_stop; kb0 += blocks_per_warp) {
-
+    for (int kb0 = kb0_start; kb0 < kb0_stop; kb0 += blocks_per_iter) {
         load_tiles(x, tile_x, stride01*it*mmq_y + kb0, tile_x_max_i, stride01);
 
-#pragma unroll
-        for (int kr = 0; kr < qr; ++kr) {
-            const int * by0 = y + stride11*(kb0*(qk*sizeof(block_q8_1_mmq) / (4*QK8_1*sizeof(int))) + kr*sizeof(block_q8_1_mmq)/sizeof(int));
+        {
+            const int * by0 = y + stride11*(kb0*(qk*sizeof(block_q8_1_mmq) / (4*QK8_1*sizeof(int))) + 0*sizeof(block_q8_1_mmq)/sizeof(int));
 #pragma unroll
             for (int l0 = 0; l0 < mmq_x*MMQ_TILE_Y_K; l0 += nwarps*WARP_SIZE) {
                 int l = l0 + threadIdx.y*WARP_SIZE + threadIdx.x;
 
                 tile_y[l] = by0[l];
             }
+        }
 
-            __syncthreads();
+        __syncthreads();
 
-// #pragma unroll // unrolling this loop causes too much register pressure
-            for (int k0 = kr*WARP_SIZE/qr; k0 < (kr+1)*WARP_SIZE/qr; k0 += vdr) {
-                vec_dot(tile_x, tile_y, sum, k0);
-            }
+        vec_dot(tile_x, tile_y, sum, 0);
+
+        __syncthreads();
+
+        {
+            const int * by0 = y + stride11*(kb0*(qk*sizeof(block_q8_1_mmq) / (4*QK8_1*sizeof(int))) + 1*sizeof(block_q8_1_mmq)/sizeof(int));
+#pragma unroll
+            for (int l0 = 0; l0 < mmq_x*MMQ_TILE_Y_K; l0 += nwarps*WARP_SIZE) {
+                int l = l0 + threadIdx.y*WARP_SIZE + threadIdx.x;
 
-            __syncthreads();
+                tile_y[l] = by0[l];
+            }
         }
+
+        __syncthreads();
+
+        vec_dot(tile_x, tile_y, sum, WARP_SIZE);
+
+        __syncthreads();
     }
 
     if (fixup) {
@@ -2424,7 +2512,6 @@ static __global__ void mul_mat_q(
     }
 
     constexpr int qk    = ggml_cuda_type_traits::qk;
-    constexpr int qi    = ggml_cuda_type_traits::qi;
     constexpr int mmq_y = get_mmq_y_device();
 
     // On AMD or old CUDA the performance with stream-k was worse, use conventional tiling instead:
@@ -2439,7 +2526,7 @@ static __global__ void mul_mat_q(
 #endif // (defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) || __CUDA_ARCH__ < CC_VOLTA
 
     const     int64_t blocks_per_ne00 = ne00 / qk;
-    constexpr int     blocks_per_warp = WARP_SIZE / qi;
+    constexpr int     blocks_per_iter = MMQ_ITER_K / qk;
 
     const int ntx = (ne11 + mmq_x - 1) / mmq_x; // Number of tiles x
     const int nty = (ne01 + mmq_y - 1) / mmq_y; // Number of tiles y
@@ -2448,8 +2535,8 @@ static __global__ void mul_mat_q(
     int64_t kbc      = (int64_t) blockIdx.x     *blocks_per_ne00*ntx*nty / gridDim.x;
     int64_t kbc_stop = (int64_t)(blockIdx.x + 1)*blocks_per_ne00*ntx*nty / gridDim.x;
 
-    kbc      -= (kbc      % blocks_per_ne00) % blocks_per_warp;
-    kbc_stop -= (kbc_stop % blocks_per_ne00) % blocks_per_warp;
+    kbc      -= (kbc      % blocks_per_ne00) % blocks_per_iter;
+    kbc_stop -= (kbc_stop % blocks_per_ne00) % blocks_per_iter;
 
     // kb0 == k index when doing the matrix multiplication for an output tile.
     int kb0_start = kbc % blocks_per_ne00;
@@ -2490,8 +2577,7 @@ static __global__ void mul_mat_q_stream_k_fixup(
 
     constexpr int     mmq_y           = get_mmq_y_device();
     constexpr int     qk              = ggml_cuda_type_traits::qk;
-    constexpr int     qi              = ggml_cuda_type_traits::qi;
-    constexpr int     blocks_per_warp = WARP_SIZE / qi;
+    constexpr int     blocks_per_iter = MMQ_ITER_K / qk;
     const     int64_t blocks_per_ne00 = ne00 / qk;
 
     float sum[mmq_x*mmq_y / (nwarps*WARP_SIZE)] = {0.0f};
@@ -2501,15 +2587,18 @@ static __global__ void mul_mat_q_stream_k_fixup(
 
     bool any_fixup = false;
 
-    const int bidx_start = (blockIdx.y*nty + blockIdx.x)     * block_num_mmq / (gridDim.y*gridDim.x);
-    const int bidx_stop  = (blockIdx.y*nty + blockIdx.x + 1) * block_num_mmq / (gridDim.y*gridDim.x) + 1;
+    const int bidx_start = ((blockIdx.y*nty + blockIdx.x)     * block_num_mmq)                           / (gridDim.y*gridDim.x);
+    const int bidx_stop  = ((blockIdx.y*nty + blockIdx.x + 1) * block_num_mmq + gridDim.y*gridDim.x - 1) / (gridDim.y*gridDim.x);
+
+    int64_t kbc_0;
+    int64_t kbc_stop_0 = (int64_t) bidx_start*blocks_per_ne00*ntx*nty / block_num_mmq;
 
     for (int bidx = bidx_start; bidx < bidx_stop; ++bidx) {
-        int64_t kbc      = (int64_t) bidx     *blocks_per_ne00*ntx*nty / block_num_mmq;
-        int64_t kbc_stop = (int64_t)(bidx + 1)*blocks_per_ne00*ntx*nty / block_num_mmq;
+        kbc_0 = kbc_stop_0;
+        kbc_stop_0 = (int64_t) (bidx + 1)*blocks_per_ne00*ntx*nty / block_num_mmq;
 
-        kbc      -= (kbc      % blocks_per_ne00) % blocks_per_warp;
-        kbc_stop -= (kbc_stop % blocks_per_ne00) % blocks_per_warp;
+        const int64_t kbc      = kbc_0      - (kbc_0      % blocks_per_ne00) % blocks_per_iter;
+        const int64_t kbc_stop = kbc_stop_0 - (kbc_stop_0 % blocks_per_ne00) % blocks_per_iter;
 
         // Skip fixup tile if the MMQ CUDA block never wrote anything to it:
         if (kbc == kbc_stop || kbc_stop % blocks_per_ne00 == 0) {
diff --git a/ggml/src/ggml-cuda/quantize.cu b/ggml/src/ggml-cuda/quantize.cu
index b4678682238d3..aa7f1eff0e6a2 100644
--- a/ggml/src/ggml-cuda/quantize.cu
+++ b/ggml/src/ggml-cuda/quantize.cu
@@ -37,47 +37,92 @@ static __global__ void quantize_q8_1(const float * __restrict__ x, void * __rest
     reinterpret_cast(y[ib].ds.y) = sum;
 }
 
-template 
+template 
 static __global__ void quantize_mmq_q8_1(
     const float * __restrict__ x, void * __restrict__ vy, const int64_t kx0, const int64_t kx1, const int64_t kx0_padded) {
 
-    const int64_t ix0 = (int64_t)blockDim.x*blockIdx.x + threadIdx.x;
+    constexpr int vals_per_scale = ds_layout == MMQ_Q8_1_DS_LAYOUT_D2S6 ? 64 : 32;
+    constexpr int vals_per_sum   = ds_layout == MMQ_Q8_1_DS_LAYOUT_D2S6 ? 16 : 32;
+
+    const int64_t ix0 = ((int64_t)blockDim.x*blockIdx.x + threadIdx.x)*4;
 
     if (ix0 >= kx0_padded) {
         return;
     }
 
+    const float4 * x4 = (const float4 *) x;
+
     const int64_t ix1 = kx1*blockIdx.z + blockIdx.y;
 
     block_q8_1_mmq * y = (block_q8_1_mmq *) vy;
 
-    const int64_t ib0 = blockIdx.z*(gridDim.y*gridDim.x*blockDim.x/(4*QK8_1)); // first block of channel
-    const int64_t ib  = ib0 + (ix0 / (4*QK8_1))*kx1 + blockIdx.y;              // block index in channel
-    const int64_t iqs = ix0 % (4*QK8_1);                                       // quant index in block
-
-    const float xi = ix0 < kx0 ? x[ix1*kx0 + ix0] : 0.0f;
-    float amax = fabsf(xi);
-
-    amax = warp_reduce_max(amax);
+    const int64_t ib0 = blockIdx.z*((int64_t)gridDim.y*gridDim.x*blockDim.x/QK8_1); // first block of channel
+    const int64_t ib  = ib0 + (ix0 / (4*QK8_1))*kx1 + blockIdx.y;                   // block index in channel
+    const int64_t iqs = ix0 % (4*QK8_1);                                            // quant index in block
+
+    // Load 4 floats per thread and calculate max. abs. value between them:
+    const float4 xi = ix0 < kx0 ? x4[(ix1*kx0 + ix0)/4] : make_float4(0.0f, 0.0f, 0.0f, 0.0f);
+    float amax = fabsf(xi.x);
+    amax = fmaxf(amax, fabsf(xi.y));
+    amax = fmaxf(amax, fabsf(xi.z));
+    amax = fmaxf(amax, fabsf(xi.w));
+
+    // Exchange max. abs. value between vals_per_scale/4 threads.
+#pragma unroll
+    for (int mask = vals_per_scale/8; mask > 0; mask >>= 1) {
+        amax = fmaxf(amax, __shfl_xor_sync(0xFFFFFFFF, amax, mask, WARP_SIZE));
+    }
 
     float sum;
-    if (need_sum) {
-        sum = warp_reduce_sum(xi);
+    if (ds_layout != MMQ_Q8_1_DS_LAYOUT_D4) {
+        sum = xi.x + xi.y + xi.z + xi.w;
+
+        // Exchange calculate sum across vals_per_sum/4 threads.
+#pragma unroll
+        for (int mask = vals_per_sum/8; mask > 0; mask >>= 1) {
+            sum += __shfl_xor_sync(0xFFFFFFFF, sum, mask, WARP_SIZE);
+        }
     }
 
-    const float d = amax / 127;
-    const int8_t q = amax == 0.0f ? 0 : roundf(xi / d);
+    const float d_inv = 127.0f / amax;
+    char4 q;
+    q.x = roundf(xi.x*d_inv);
+    q.y = roundf(xi.y*d_inv);
+    q.z = roundf(xi.z*d_inv);
+    q.w = roundf(xi.w*d_inv);
 
-    y[ib].qs[iqs] = q;
+    // Write back 4 int8 values as a single 32 bit value for better memroy bandwidth:
+    char4 * yqs4 = (char4 *) y[ib].qs;
+    yqs4[iqs/4] = q;
+
+    if (ds_layout == MMQ_Q8_1_DS_LAYOUT_D2S6) {
+        if (iqs % 16 != 0 || iqs >= 96) {
+            return;
+        }
+
+        y[ib].d2s6[2 + iqs/16] = sum;
+
+        if (iqs % 64 != 0) {
+            return;
+        }
+
+        const float d = 1.0f / d_inv;
+
+        y[ib].d2s6[iqs/64] = d;
 
-    if (iqs % QK8_1 != 0) {
         return;
     }
 
-    if (need_sum) {
-        y[ib].ds[iqs/QK8_1] = make_half2(d, sum);
+    if (iqs % 32 != 0) {
+        return;
+    }
+
+    const float d = 1.0f / d_inv;
+
+    if (ds_layout == MMQ_Q8_1_DS_LAYOUT_DS4) {
+        y[ib].ds4[iqs/32] = make_half2(d, sum);
     } else {
-        ((float *) y[ib].ds)[iqs/QK8_1] = d;
+        y[ib].d4[iqs/32]  = d;
     }
 }
 
@@ -101,12 +146,24 @@ void quantize_mmq_q8_1_cuda(
 
     GGML_ASSERT(kx0_padded % (4*QK8_1) == 0);
 
-    const int64_t block_num_x = (kx0_padded + CUDA_QUANTIZE_BLOCK_SIZE - 1) / CUDA_QUANTIZE_BLOCK_SIZE;
+    const int64_t block_num_x = (kx0_padded + 4*CUDA_QUANTIZE_BLOCK_SIZE_MMQ - 1) / (4*CUDA_QUANTIZE_BLOCK_SIZE_MMQ);
     const dim3 num_blocks(block_num_x, kx1, channels);
-    const dim3 block_size(CUDA_QUANTIZE_BLOCK_SIZE, 1, 1);
-    if (mmq_need_sum(type_x)) {
-        quantize_mmq_q8_1<<>>(x, vy, kx0, kx1, kx0_padded);
-    } else {
-        quantize_mmq_q8_1<<>>(x, vy, kx0, kx1, kx0_padded);
+    const dim3 block_size(CUDA_QUANTIZE_BLOCK_SIZE_MMQ, 1, 1);
+    switch (mmq_get_q8_1_ds_layout(type_x)) {
+        case MMQ_Q8_1_DS_LAYOUT_D4:
+            quantize_mmq_q8_1
+                <<>>(x, vy, kx0, kx1, kx0_padded);
+            break;
+        case MMQ_Q8_1_DS_LAYOUT_DS4:
+            quantize_mmq_q8_1
+                <<>>(x, vy, kx0, kx1, kx0_padded);
+            break;
+        case MMQ_Q8_1_DS_LAYOUT_D2S6:
+            quantize_mmq_q8_1
+                <<>>(x, vy, kx0, kx1, kx0_padded);
+            break;
+        default:
+            GGML_ASSERT(false);
+            break;
     }
 }
diff --git a/ggml/src/ggml-cuda/quantize.cuh b/ggml/src/ggml-cuda/quantize.cuh
index 486c9360a46fd..03bf322b95873 100644
--- a/ggml/src/ggml-cuda/quantize.cuh
+++ b/ggml/src/ggml-cuda/quantize.cuh
@@ -5,7 +5,11 @@
 
 #include 
 
-#define CUDA_QUANTIZE_BLOCK_SIZE 256
+#define CUDA_QUANTIZE_BLOCK_SIZE     256
+#define CUDA_QUANTIZE_BLOCK_SIZE_MMQ 128
+
+static_assert(MATRIX_ROW_PADDING %    CUDA_QUANTIZE_BLOCK_SIZE      == 0, "Risk of out-of-bounds access.");
+static_assert(MATRIX_ROW_PADDING % (4*CUDA_QUANTIZE_BLOCK_SIZE_MMQ) == 0, "Risk of out-of-bounds access.");
 
 typedef void (*quantize_cuda_t)(
     const float * x, void * vy, const int64_t kx0, const int64_t kx1, const int64_t channels, const int64_t kx0_padded,
diff --git a/ggml/src/ggml-cuda/vecdotq.cuh b/ggml/src/ggml-cuda/vecdotq.cuh
index 1d510484ac474..6a17d0f3eb0d2 100644
--- a/ggml/src/ggml-cuda/vecdotq.cuh
+++ b/ggml/src/ggml-cuda/vecdotq.cuh
@@ -189,7 +189,7 @@ template  static __device__ __forceinline__ float vec_dot_q8_1_q8_1_imp
 }
 
 #define VDR_Q2_K_Q8_1_MMVQ 1
-#define VDR_Q2_K_Q8_1_MMQ  2
+#define VDR_Q2_K_Q8_1_MMQ  4
 
 // contiguous v/x values
 static __device__ __forceinline__ float vec_dot_q2_K_q8_1_impl_mmvq(
@@ -219,32 +219,56 @@ static __device__ __forceinline__ float vec_dot_q2_K_q8_1_impl_mmvq(
     return dm2f.x*sumf_d - dm2f.y*sumf_m;
 }
 
-// contiguous u/y values
+// contiguous v/x + u/y values
+template 
 static __device__ __forceinline__ float vec_dot_q2_K_q8_1_impl_mmq(
-    const int * __restrict__ v, const int * __restrict__ u, const half2 * dm2, const float & d8) {
+    const int * __restrict__ v, const int * __restrict__ u, const half2 * dm2, const float & d8, const half2 * s8) {
 
-    float sumf_d = 0.0f;
-    float sumf_m = 0.0f;
+    float sumf    = 0.0f;
+    float sumf_d8 = 0.0f;
 
 #pragma unroll
-    for (int i0 = 0; i0 < QI8_1; i0 += QI8_1/2) {
-        const float2 dm2f = __half22float2(dm2[i0/(QI8_1/2)]);
-        int sumi_d = 0;
-        int sumi_m = 0;
+    for (int i0 = 0; i0 < QR2_K*VDR_Q2_K_Q8_1_MMQ; i0 += QI8_1) {
+        const float2 dm2f0 = __half22float2(dm2[i0/(QI8_1/2) + 0]);
+        int sumi_d0 = 0;
+
+        const float2 dm2f1 = __half22float2(dm2[i0/(QI8_1/2) + 1]);
+        int sumi_d1 = 0;
 
-        const int vi0 = v[i0/(QI8_1/2)];
 #pragma unroll
         for (int i = i0; i < i0 + QI8_1/2; ++i) {
-            const int vi = (vi0 >> (2*(i % (QI8_1/2)))) & 0x03030303;
-            sumi_d = ggml_cuda_dp4a(vi,         u[i], sumi_d); // SIMD dot product
-            sumi_m = ggml_cuda_dp4a(0x01010101, u[i], sumi_m);
+            sumi_d0 = ggml_cuda_dp4a(v[i], u[i], sumi_d0);
+        }
+        sumf_d8 += dm2f0.x * sumi_d0;
+
+#pragma unroll
+        for (int i = i0 + QI8_1/2; i < i0 + QI8_1; ++i) {
+            sumi_d1 = ggml_cuda_dp4a(v[i], u[i], sumi_d1);
         }
+        sumf_d8 += dm2f1.x * sumi_d1;
 
-        sumf_d += dm2f.x * sumi_d;
-        sumf_m += dm2f.y * sumi_m;
+        if (i0/QI8_1 < ns8) {
+            const float2 s8f = __half22float2(s8[i0/QI8_1]);
+            sumf -= dm2f0.y*s8f.x;
+            sumf -= dm2f1.y*s8f.y;
+        } else {
+            int sumi_m0 = 0;
+#pragma unroll
+            for (int i = i0; i < i0 + QI8_1/2; ++i) {
+                sumi_m0 = ggml_cuda_dp4a(0x01010101, u[i], sumi_m0);
+            }
+            sumf_d8 -= dm2f0.y * sumi_m0;
+
+            int sumi_m1 = 0;
+#pragma unroll
+            for (int i = i0 + QI8_1/2; i < i0 + QI8_1; ++i) {
+                sumi_m1 = ggml_cuda_dp4a(0x01010101, u[i], sumi_m1);
+            }
+            sumf_d8 -= dm2f1.y * sumi_m1;
+        }
     }
 
-    return d8*(sumf_d - sumf_m);
+    return sumf + d8*sumf_d8;
 }
 
 #define VDR_Q3_K_Q8_1_MMVQ 1
@@ -283,7 +307,7 @@ static __device__ __forceinline__ float vec_dot_q3_K_q8_1_impl_mmvq(
     return d3 * sumf;
 }
 
-// contiguous u/y values
+// contiguous v/x + u/y values
 static __device__ __forceinline__ float vec_dot_q3_K_q8_1_impl_mmq(
     const int * __restrict__ v, const int * __restrict__ u, const int8_t * __restrict__ scales,
     const float & d3, const float & d8) {
@@ -296,8 +320,7 @@ static __device__ __forceinline__ float vec_dot_q3_K_q8_1_impl_mmq(
 
 #pragma unroll
         for (int i = i0; i < i0 + QI8_1/2; ++i) {
-            const int vi = __vsubss4((v[i/2] >> (4*(i%2))) & 0x0F0F0F0F, 0x04040404);
-            sumi_sc = ggml_cuda_dp4a(vi, u[i], sumi_sc); // SIMD dot product
+            sumi_sc = ggml_cuda_dp4a(v[i], u[i], sumi_sc); // SIMD dot product
         }
 
         sumi += sumi_sc * scales[i0 / (QI8_1/2)];
@@ -334,7 +357,7 @@ static __device__ __forceinline__ float vec_dot_q4_K_q8_1_impl_vmmq(
     return dm4f.x*sumf_d - dm4f.y*sumf_m;
 }
 
-// contiguous u/y values
+// contiguous v/x + u/y values
 static __device__ __forceinline__ float vec_dot_q4_K_q8_1_impl_mmq(
     const int * __restrict__ v, const int * __restrict__ u, const uint8_t * __restrict__ sc,
     const uint8_t * __restrict__ m, const half2 & dm4, const half2 * __restrict__ ds8) {
@@ -397,7 +420,7 @@ static __device__ __forceinline__ float vec_dot_q5_K_q8_1_impl_vmmq(
     return dm5f.x*sumf_d - dm5f.y*sumf_m;
 }
 
-// contiguous u/y values
+// contiguous v/x + u/y values
 static __device__ __forceinline__ float vec_dot_q5_K_q8_1_impl_mmq(
     const int * __restrict__ v, const int * __restrict__ u, const uint8_t * __restrict__ sc,
     const uint8_t * __restrict__ m, const half2 & dm4, const half2 * __restrict__ ds8) {
@@ -451,13 +474,16 @@ static __device__ __forceinline__ float vec_dot_q6_K_q8_1_impl_mmvq(
     return d*sumf;
 }
 
-// contiguous u/y values
+// contiguous v/x + u/y values
 static __device__ __forceinline__ float vec_dot_q6_K_q8_1_impl_mmq(
     const int * __restrict__ v, const int * __restrict__ u, const int8_t * __restrict__ sc,
     const float & d6, const float * __restrict__ d8) {
 
     float sumf_d = 0.0f;
 
+    const int      sc_packed = get_int_b4(sc, 0);
+    const int8_t * sc_reg    = (const int8_t *) &sc_packed;
+
 #pragma unroll
     for (int i0 = 0; i0 < VDR_Q6_K_Q8_1_MMQ; i0 += 4) {
         int2 sumi_d = {0, 0}; // 2 q6_K scales per q8_1 scale
@@ -471,7 +497,7 @@ static __device__ __forceinline__ float vec_dot_q6_K_q8_1_impl_mmq(
             sumi_d.y = ggml_cuda_dp4a(v[2*i+5], u[2*i+5], sumi_d.y); // SIMD dot product
         }
 
-        sumf_d += d8[i0/4] * (sc[i0/2+0]*sumi_d.x + sc[i0/2+1]*sumi_d.y);
+        sumf_d += d8[i0/4] * (sc_reg[i0/2+0]*sumi_d.x + sc_reg[i0/2+1]*sumi_d.y);
     }
 
     return d6 * sumf_d;

From b078c619aa4e97fe726d61b0b5499a2e19a418a4 Mon Sep 17 00:00:00 2001
From: Daniel Bevenius 
Date: Thu, 11 Jul 2024 17:53:42 +0200
Subject: [PATCH 165/326] cuda : suppress 'noreturn' warn in no_device_code
 (#8414)

* cuda : suppress 'noreturn' warn in no_device_code

This commit adds a while(true) loop to the no_device_code function in
common.cuh. This is done to suppress the warning:

```console
/ggml/src/ggml-cuda/template-instances/../common.cuh:346:1: warning:
function declared 'noreturn' should not return [-Winvalid-noreturn]
  346 | }
      | ^
```

The motivation for this is to reduce the number of warnings when
compilng with GGML_HIPBLAS=ON.

Signed-off-by: Daniel Bevenius 

* squash! cuda : suppress 'noreturn' warn in no_device_code

Update __trap macro instead of using a while loop to suppress the
warning.

Signed-off-by: Daniel Bevenius 

---------

Signed-off-by: Daniel Bevenius 
---
 ggml/src/ggml-cuda/common.cuh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ggml/src/ggml-cuda/common.cuh b/ggml/src/ggml-cuda/common.cuh
index 4ff06b8719d37..26d9412a23eb6 100644
--- a/ggml/src/ggml-cuda/common.cuh
+++ b/ggml/src/ggml-cuda/common.cuh
@@ -104,7 +104,7 @@
 #define cudaStreamWaitEvent(stream, event, flags) hipStreamWaitEvent(stream, event, flags)
 #define cudaStream_t hipStream_t
 #define cudaSuccess hipSuccess
-#define __trap abort
+#define __trap() do { abort(); __builtin_unreachable(); } while(0)
 #define CUBLAS_STATUS_SUCCESS HIPBLAS_STATUS_SUCCESS
 #define CUBLAS_STATUS_NOT_INITIALIZED HIPBLAS_STATUS_NOT_INITIALIZED
 #define CUBLAS_STATUS_ALLOC_FAILED HIPBLAS_STATUS_ALLOC_FAILED

From 368645698ab648e390dcd7c00a2bf60efa654f57 Mon Sep 17 00:00:00 2001
From: Nicholai Tukanov 
Date: Thu, 11 Jul 2024 11:49:15 -0500
Subject: [PATCH 166/326] ggml : add NVPL BLAS support (#8329) (#8425)

* ggml : add NVPL BLAS support

* ggml : replace `_ENABLE_CBLAS` with `GGML_BLAS_USE_`

---------

Co-authored-by: ntukanov 
---
 Makefile               |  8 +++++++-
 ggml/src/ggml-blas.cpp | 13 +++++++++----
 2 files changed, 16 insertions(+), 5 deletions(-)

diff --git a/Makefile b/Makefile
index 668b38b99c312..4869d2ecf3be2 100644
--- a/Makefile
+++ b/Makefile
@@ -547,11 +547,17 @@ ifdef GGML_OPENBLAS64
 endif # GGML_OPENBLAS64
 
 ifdef GGML_BLIS
-	MK_CPPFLAGS += -DGGML_USE_BLAS -I/usr/local/include/blis -I/usr/include/blis
+	MK_CPPFLAGS += -DGGML_USE_BLAS -DGGML_BLAS_USE_BLIS -I/usr/local/include/blis -I/usr/include/blis
 	MK_LDFLAGS  += -lblis -L/usr/local/lib
 	OBJ_GGML    += ggml/src/ggml-blas.o
 endif # GGML_BLIS
 
+ifdef GGML_NVPL
+	MK_CPPFLAGS += -DGGML_USE_BLAS -DGGML_BLAS_USE_NVPL -DNVPL_ILP64 -I/usr/local/include/nvpl_blas -I/usr/include/nvpl_blas
+	MK_LDFLAGS  += -L/usr/local/lib -lnvpl_blas_core -lnvpl_blas_ilp64_gomp
+	OBJ_GGML    += ggml/src/ggml-blas.o
+endif # GGML_NVPL
+
 ifndef GGML_NO_LLAMAFILE
 	MK_CPPFLAGS += -DGGML_USE_LLAMAFILE
 	OBJ_GGML    += ggml/src/llamafile/sgemm.o
diff --git a/ggml/src/ggml-blas.cpp b/ggml/src/ggml-blas.cpp
index d709a357bbf29..a37aa407282b9 100644
--- a/ggml/src/ggml-blas.cpp
+++ b/ggml/src/ggml-blas.cpp
@@ -8,11 +8,12 @@
 #   include 
 #elif defined(GGML_BLAS_USE_MKL)
 #   include 
+#elif defined(GGML_BLAS_USE_BLIS)
+#   include 
+#elif defined(GGML_BLAS_USE_NVPL)
+#   include 
 #else
 #   include 
-#   ifdef BLIS_ENABLE_CBLAS
-#       include 
-#   endif
 #endif
 
 struct ggml_backend_blas_context {
@@ -140,10 +141,14 @@ static void ggml_backend_blas_mul_mat(ggml_backend_blas_context * ctx, struct gg
     openblas_set_num_threads(ctx->n_threads);
 #endif
 
-#if defined(BLIS_ENABLE_CBLAS)
+#if defined(GGML_BLAS_USE_BLIS)
     bli_thread_set_num_threads(ctx->n_threads);
 #endif
 
+#if defined(GGML_BLAS_USE_NVPL)
+    nvpl_blas_set_num_threads(ctx->n_threads);
+#endif
+
     for (int64_t i13 = 0; i13 < ne13; i13++) {
         for (int64_t i12 = 0; i12 < ne12; i12++) {
             const int64_t i03 = i13/r3;

From b549a1bbefb2f1fbb8b558bac1f2ae7967e60964 Mon Sep 17 00:00:00 2001
From: Chen Xi 
Date: Fri, 12 Jul 2024 00:52:04 +0000
Subject: [PATCH 167/326] [SYCL] fix the mul_mat_id ut issues (#8427)

* fix part of mul_mat_id

* skip the bfloat 16 sycl ut

Signed-off-by: Chen Xi 

---------

Signed-off-by: Chen Xi 
Co-authored-by: Meng, Hengyu 
Co-authored-by: Chen Xi 
---
 ggml/src/ggml-backend.c |  2 +-
 ggml/src/ggml-sycl.cpp  | 49 +++++++++++------------------------------
 src/llama.cpp           |  7 ------
 3 files changed, 14 insertions(+), 44 deletions(-)

diff --git a/ggml/src/ggml-backend.c b/ggml/src/ggml-backend.c
index 13c71c310c446..dbbaa3941febe 100644
--- a/ggml/src/ggml-backend.c
+++ b/ggml/src/ggml-backend.c
@@ -394,7 +394,7 @@ void ggml_backend_event_wait(ggml_backend_t backend, ggml_backend_event_t event)
 
 // backend registry
 
-#define GGML_REG_MAX_BACKENDS 16
+#define GGML_REG_MAX_BACKENDS 64
 
 struct ggml_backend_reg {
     char name[128];
diff --git a/ggml/src/ggml-sycl.cpp b/ggml/src/ggml-sycl.cpp
index 9c419ba896706..5a890237f2453 100644
--- a/ggml/src/ggml-sycl.cpp
+++ b/ggml/src/ggml-sycl.cpp
@@ -3768,37 +3768,13 @@ static void ggml_sycl_mul_mat_id(ggml_backend_sycl_context & ctx, const ggml_ten
         stream->memcpy(ids_host.data(), ids_dev, ggml_nbytes(ids))));
     SYCL_CHECK(CHECK_TRY_ERROR(stream->wait()));
 
-    const ggml_tensor_extra_gpu *src0_extra =
-        (const ggml_tensor_extra_gpu *)src0->extra;
-    const ggml_tensor_extra_gpu *src1_extra =
-        (const ggml_tensor_extra_gpu *)src1->extra;
-    const ggml_tensor_extra_gpu *dst_extra =
-        (const ggml_tensor_extra_gpu *)dst->extra;
-
-    ggml_tensor_extra_gpu src0_row_extra;
-    ggml_tensor_extra_gpu src1_row_extra;
-    ggml_tensor_extra_gpu dst_row_extra;
-
     ggml_tensor src0_row = *src0;
     ggml_tensor src1_row = *src1;
     ggml_tensor dst_row = *dst;
 
-    src1_row.backend = GGML_BACKEND_TYPE_GPU;
-    dst_row.backend  = GGML_BACKEND_TYPE_GPU;
-
-    src0_row.extra = &src0_row_extra;
-    src1_row.extra = &src1_row_extra;
-    dst_row.extra = &dst_row_extra;
-
-    char *src0_original = src1->backend == GGML_BACKEND_TYPE_CPU
-                              ? (char *)src0->data
-                              : (char *)src0_extra->data_device[ctx.device];
-    char *src1_original = src1->backend == GGML_BACKEND_TYPE_CPU
-                              ? (char *)src1->data
-                              : (char *)src1_extra->data_device[ctx.device];
-    char *dst_original = dst->backend == GGML_BACKEND_TYPE_CPU
-                             ? (char *)dst->data
-                             : (char *)dst_extra->data_device[ctx.device];
+    char *src0_original = (char *)src0->data;
+    char *src1_original = (char *)src1->data;
+    char *dst_original = (char *)dst->data;
 
     src0_row.ne[2] = 1;
     src0_row.ne[3] = 1;
@@ -3827,12 +3803,9 @@ static void ggml_sycl_mul_mat_id(ggml_backend_sycl_context & ctx, const ggml_ten
                 const int64_t i1 = id;
                 const int64_t i2 = i12;
 
-            src0_row_extra.data_device[ctx.device] =
-                src0_original + i02*nb02;
-            src1_row_extra.data_device[ctx.device] =
-                src1_original + + i11*nb11 + i12*nb12;
-            dst_row_extra.data_device[ctx.device] =
-                dst_original + i1*nb1   + i2*nb2;
+            src0_row.data = src0_original + i02*nb02;
+            src1_row.data = src1_original + + i11*nb11 + i12*nb12;
+            dst_row.data = dst_original + i1*nb1   + i2*nb2;
 
             ggml_sycl_mul_mat(ctx, &src0_row, &src1_row, &dst_row);
             }
@@ -3841,8 +3814,8 @@ static void ggml_sycl_mul_mat_id(ggml_backend_sycl_context & ctx, const ggml_ten
         ggml_sycl_pool_alloc src1_contiguous(ctx.pool(), sizeof(float)*ggml_nelements(src1));
         ggml_sycl_pool_alloc  dst_contiguous(ctx.pool(), sizeof(float)*ggml_nelements(dst));
 
-        src1_row_extra.data_device[ctx.device] = src1_contiguous.get();
-        dst_row_extra.data_device[ctx.device]  =  dst_contiguous.get();
+        src1_row.data = src1_contiguous.get();
+        dst_row.data  =  dst_contiguous.get();
 
         for (int64_t i02 = 0; i02 < n_as; i02++) {
             int64_t num_src1_rows = 0;
@@ -3898,7 +3871,7 @@ static void ggml_sycl_mul_mat_id(ggml_backend_sycl_context & ctx, const ggml_ten
                 });
             }
 
-            src0_row_extra.data_device[ctx.device] = src0_original + i02*nb02;
+            src0_row.data = src0_original + i02*nb02;
 
             GGML_ASSERT(nb11 == sizeof(float)*ne10);
             GGML_ASSERT(nb1 == sizeof(float)*ne0);
@@ -5221,6 +5194,10 @@ GGML_CALL static bool ggml_backend_sycl_supports_op(ggml_backend_t backend, cons
                         return false;
                     }
                 }
+                ggml_type src0_type = op->src[0]->type;
+                if (src0_type == GGML_TYPE_BF16) {
+                    return false;
+                }
                 return true;
             } break;
         case GGML_OP_GET_ROWS:
diff --git a/src/llama.cpp b/src/llama.cpp
index ed77ed918e554..f91ac777969d9 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -5883,13 +5883,6 @@ static bool llm_load_tensors(
 
     auto & hparams = model.hparams;
 
-#ifdef GGML_USE_SYCL
-    // disable MoE with SYCL until mul_mat_id is updated
-    if (hparams.n_expert > 0) {
-        n_gpu_layers = 0;
-    }
-#endif
-
     model.split_mode   = split_mode;
     model.main_gpu     = main_gpu;
     model.n_gpu_layers = n_gpu_layers;

From 370b1f7e7a7514d9a63daf15f7b0f00319b7f908 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Fri, 12 Jul 2024 10:46:02 +0300
Subject: [PATCH 168/326] ggml : minor naming changes (#8433)

* ggml : minor naming changes

ggml-ci

* ggml : use PRId64 [no ci]

* ggml : revert FA K/Q names
---
 examples/quantize-stats/quantize-stats.cpp |   2 +-
 ggml/include/ggml.h                        |  50 +++++-----
 ggml/src/ggml-aarch64.c                    |  68 +++++++------
 ggml/src/ggml-aarch64.h                    |  14 +--
 ggml/src/ggml-quants.c                     |  94 ++++++++---------
 ggml/src/ggml-quants.h                     |  38 +++----
 ggml/src/ggml.c                            | 111 ++++++++++-----------
 tests/test-double-float.cpp                |   4 +-
 tests/test-quantize-fns.cpp                |   2 +-
 tests/test-quantize-perf.cpp               |   2 +-
 10 files changed, 194 insertions(+), 191 deletions(-)

diff --git a/examples/quantize-stats/quantize-stats.cpp b/examples/quantize-stats/quantize-stats.cpp
index 746df8446b85e..68cf8d3595e87 100644
--- a/examples/quantize-stats/quantize-stats.cpp
+++ b/examples/quantize-stats/quantize-stats.cpp
@@ -154,7 +154,7 @@ static void test_roundtrip_on_chunk(
     }
 
     if (use_reference) {
-        qfns.from_float_reference(input_scratch, quantized_scratch, chunk_size);
+        qfns.from_float_ref(input_scratch, quantized_scratch, chunk_size);
     } else {
         qfns.from_float(input_scratch, quantized_scratch, chunk_size);
     }
diff --git a/ggml/include/ggml.h b/ggml/include/ggml.h
index 1e367753738d9..f2145ff356cbd 100644
--- a/ggml/include/ggml.h
+++ b/ggml/include/ggml.h
@@ -714,9 +714,9 @@ extern "C" {
     GGML_API GGML_CALL size_t  ggml_nbytes      (const struct ggml_tensor * tensor);
     GGML_API           size_t  ggml_nbytes_pad  (const struct ggml_tensor * tensor); // same as ggml_nbytes() but padded to GGML_MEM_ALIGN
 
-    GGML_API GGML_CALL int    ggml_blck_size(enum ggml_type type);
-    GGML_API GGML_CALL size_t ggml_type_size(enum ggml_type type);             // size in bytes for all elements in a block
-    GGML_API GGML_CALL size_t ggml_row_size (enum ggml_type type, int64_t ne); // size in bytes for all elements in a row
+    GGML_API GGML_CALL int64_t ggml_blck_size(enum ggml_type type);
+    GGML_API GGML_CALL size_t  ggml_type_size(enum ggml_type type);             // size in bytes for all elements in a block
+    GGML_API GGML_CALL size_t  ggml_row_size (enum ggml_type type, int64_t ne); // size in bytes for all elements in a row
 
     GGML_DEPRECATED(
     GGML_API double ggml_type_sizef(enum ggml_type type), // ggml_type_size()/ggml_blck_size() as float
@@ -2410,31 +2410,31 @@ extern "C" {
 #endif
     typedef void (*ggml_to_float_t)  (const void  * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
     typedef void (*ggml_from_float_t)(const float * GGML_RESTRICT x, void  * GGML_RESTRICT y, int64_t k);
-    typedef void (*ggml_vec_dot_t)   (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT x, size_t bx,
-                                      const void * GGML_RESTRICT y, size_t by, int nrc);
-    typedef void (*ggml_from_float_to_mat_t)(const float * GGML_RESTRICT x, void  * GGML_RESTRICT y, int64_t nr,
-                                             int64_t k, int64_t bx);
-    typedef void (*ggml_gemv_t)      (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT x,
-                                      const void * GGML_RESTRICT y, int nr, int nc);
-    typedef void (*ggml_gemm_t)      (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT x,
-                                      const void * GGML_RESTRICT y, int nr, int nc);
+    typedef void (*ggml_from_float_to_mat_t)
+                                     (const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t nr, int64_t k, int64_t bs);
+    typedef void (*ggml_vec_dot_t)  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT x, size_t bx,
+                                       const void * GGML_RESTRICT y, size_t by, int nrc);
+    typedef void (*ggml_gemv_t)     (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT x,
+                                       const void * GGML_RESTRICT y, int nr, int nc);
+    typedef void (*ggml_gemm_t)     (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT x,
+                                       const void * GGML_RESTRICT y, int nr, int nc);
 
     typedef struct {
-        const char      * type_name;
-        int               blck_size;
-        size_t            type_size;
-        bool              is_quantized;
-        ggml_to_float_t   to_float;
-        ggml_from_float_t from_float;
-        ggml_from_float_t from_float_reference;
-        ggml_vec_dot_t    vec_dot;
-        enum ggml_type    vec_dot_type;
-        int64_t           nrows; // number of rows to process simultaneously;
-        int64_t           ncols; // number of columns to process simultaneously;
-        int64_t           interleave_blcksize; // interleave elements in blocks of interleave_blcksize;
+        const char             * type_name;
+        int64_t                  blck_size;
+        int64_t                  blck_size_interleave; // interleave elements in blocks
+        size_t                   type_size;
+        bool                     is_quantized;
+        ggml_to_float_t          to_float;
+        ggml_from_float_t        from_float;
+        ggml_from_float_t        from_float_ref;
         ggml_from_float_to_mat_t from_float_to_mat;
-        ggml_gemv_t       gemv;
-        ggml_gemm_t       gemm;
+        ggml_vec_dot_t           vec_dot;
+        enum ggml_type           vec_dot_type;
+        int64_t                  nrows; // number of rows to process simultaneously
+        int64_t                  ncols; // number of columns to process simultaneously
+        ggml_gemv_t              gemv;
+        ggml_gemm_t              gemm;
     } ggml_type_traits_t;
 
     GGML_API ggml_type_traits_t ggml_internal_get_type_traits(enum ggml_type type);
diff --git a/ggml/src/ggml-aarch64.c b/ggml/src/ggml-aarch64.c
index 008718634fe0d..40838cf4ffdcf 100644
--- a/ggml/src/ggml-aarch64.c
+++ b/ggml/src/ggml-aarch64.c
@@ -20,19 +20,19 @@
 
 // Functions to create the interleaved data layout formats
 
-// interleave 4 block_q4_0s in blocks of interleave_blcksize
+// interleave 4 block_q4_0s in blocks of blck_size_interleave
 // returns an interleaved block_q4_0x4
 // in the interleaved block_q4_0x4, place deltas for 4 block_q4_0 blocks
-// first, then interleave quants from 4 block_q4_0s in blocks of interleave_blcksize
+// first, then interleave quants from 4 block_q4_0s in blocks of blck_size_interleave
 //
 // - in                  : an array of block_q4_0 pointers
-// - interleave_blcksize : the block_q4_0 quants bytes are interleaved in blocks of
-//                         interleave_blcksize bytes
+// - blck_size_interleave : the block_q4_0 quants bytes are interleaved in blocks of
+//                         blck_size_interleave bytes
 // - xor_mask            : the mask to convert the nibbles in block_q4_0 quants bytes
 //                         from bias offset form to pure sign form (this saves subtract
 //                         operations durin unpacking)
 //
-static block_q4_0x4 make_block_q4_0x4(block_q4_0 * in, unsigned int interleave_blcksize, unsigned int xor_mask) {
+static block_q4_0x4 make_block_q4_0x4(block_q4_0 * in, unsigned int blck_size_interleave, unsigned int xor_mask) {
     block_q4_0x4 out;
 
     for (int i = 0; i < 4; i++) {
@@ -40,9 +40,9 @@ static block_q4_0x4 make_block_q4_0x4(block_q4_0 * in, unsigned int interleave_b
     }
 
     for (int i = 0; i < QK4_0 * 2; i++) {
-        int src_offset = (i / (4 * interleave_blcksize)) * interleave_blcksize;
-        int src_id = (i % (4 * interleave_blcksize)) / interleave_blcksize;
-        src_offset += (i % interleave_blcksize);
+        int src_offset = (i / (4 * blck_size_interleave)) * blck_size_interleave;
+        int src_id = (i % (4 * blck_size_interleave)) / blck_size_interleave;
+        src_offset += (i % blck_size_interleave);
 
         out.qs[i] = in[src_id].qs[src_offset] ^ xor_mask;
     }
@@ -50,11 +50,11 @@ static block_q4_0x4 make_block_q4_0x4(block_q4_0 * in, unsigned int interleave_b
     return out;
 }
 
-// interleave 8 block_q4_0s in blocks of interleave_blcksize
+// interleave 8 block_q4_0s in blocks of blck_size_interleave
 // returns an interleaved block_q4_0x8
 // in the interleaved block_q4_0x8, place deltas for 8 block_q4_0 blocks
-// first, then interleave quants from 8 block_q4_0s in blocks of interleave_blcksize
-static block_q4_0x8 make_block_q4_0x8(block_q4_0 * in, unsigned int interleave_blcksize, unsigned int xor_mask) {
+// first, then interleave quants from 8 block_q4_0s in blocks of blck_size_interleave
+static block_q4_0x8 make_block_q4_0x8(block_q4_0 * in, unsigned int blck_size_interleave, unsigned int xor_mask) {
     block_q4_0x8 out;
 
     for (int i = 0; i < 8; i++) {
@@ -62,9 +62,9 @@ static block_q4_0x8 make_block_q4_0x8(block_q4_0 * in, unsigned int interleave_b
     }
 
     for (int i = 0; i < QK4_0 * 4; i++) {
-        int src_offset = (i / (8 * interleave_blcksize)) * interleave_blcksize;
-        int src_id = (i % (8 * interleave_blcksize)) / interleave_blcksize;
-        src_offset += (i % interleave_blcksize);
+        int src_offset = (i / (8 * blck_size_interleave)) * blck_size_interleave;
+        int src_id = (i % (8 * blck_size_interleave)) / blck_size_interleave;
+        src_offset += (i % blck_size_interleave);
 
         out.qs[i] = in[src_id].qs[src_offset] ^ xor_mask;
     }
@@ -135,7 +135,7 @@ void quantize_q8_0_4x4(const float * restrict x, void * restrict vy, int64_t k)
     }
 #else
     // scalar
-    const int interleave_blcksize = 4;
+    const int blck_size_interleave = 4;
     float srcv[4][QK8_0];
     float id[4];
 
@@ -155,12 +155,12 @@ void quantize_q8_0_4x4(const float * restrict x, void * restrict vy, int64_t k)
         }
 
         for (int j = 0; j < QK8_0 * 4; j++) {
-            int src_offset = (j / (4 * interleave_blcksize)) * interleave_blcksize;
-            int src_id = (j % (4 * interleave_blcksize)) / interleave_blcksize;
-            src_offset += (j % interleave_blcksize);
+            int src_offset = (j / (4 * blck_size_interleave)) * blck_size_interleave;
+            int src_id = (j % (4 * blck_size_interleave)) / blck_size_interleave;
+            src_offset += (j % blck_size_interleave);
 
             float x0 = srcv[src_id][src_offset] * id[src_id];
-            y[i].qs[j] = roundf(x0);;
+            y[i].qs[j] = roundf(x0);
         }
     }
 #endif
@@ -253,7 +253,7 @@ void quantize_q8_0_4x8(const float * restrict x, void * restrict vy, int64_t k)
     }
 #else
     // scalar
-    const int interleave_blcksize = 8;
+    const int blck_size_interleave = 8;
     float srcv[4][QK8_0];
     float id[4];
 
@@ -273,26 +273,30 @@ void quantize_q8_0_4x8(const float * restrict x, void * restrict vy, int64_t k)
         }
 
         for (int j = 0; j < QK8_0 * 4; j++) {
-            int src_offset = (j / (4 * interleave_blcksize)) * interleave_blcksize;
-            int src_id = (j % (4 * interleave_blcksize)) / interleave_blcksize;
-            src_offset += (j % interleave_blcksize);
+            int src_offset = (j / (4 * blck_size_interleave)) * blck_size_interleave;
+            int src_id = (j % (4 * blck_size_interleave)) / blck_size_interleave;
+            src_offset += (j % blck_size_interleave);
 
             float x0 = srcv[src_id][src_offset] * id[src_id];
-            y[i].qs[j] = roundf(x0);;
+            y[i].qs[j] = roundf(x0);
         }
     }
 #endif
 }
 
-void quantize_mat_q8_0(const float * restrict x, void * restrict vy, int64_t nrow, int64_t n_per_row, int64_t interleave_blcksize) {
+void quantize_mat_q8_0(const float * restrict x, void * restrict vy, int64_t nrow, int64_t n_per_row, int64_t blck_size_interleave) {
     assert(nrow == 4);
     UNUSED(nrow);
-    if (interleave_blcksize == 4) quantize_q8_0_4x4(x, vy, n_per_row);
-    else if (interleave_blcksize == 8) quantize_q8_0_4x8(x, vy, n_per_row);
-    else assert(false);
+    if (blck_size_interleave == 4) {
+        quantize_q8_0_4x4(x, vy, n_per_row);
+    } else if (blck_size_interleave == 8) {
+        quantize_q8_0_4x8(x, vy, n_per_row);
+    } else {
+        assert(false);
+    }
 }
 
-static size_t quantize_q4_0_nr_bl(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, int nrows_interleaved, int interleave_blcksize) {
+static size_t quantize_q4_0_nr_bl(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, int nrows_interleaved, int blck_size_interleave) {
     assert(n_per_row % QK4_0 == 0);
     const int nb = n_per_row / QK4_0;
 
@@ -311,15 +315,15 @@ static size_t quantize_q4_0_nr_bl(const float * restrict src, void * restrict ds
         for (int64_t x = 0; x < nb; x++) {
 
             for (int i  = 0; i < nrows_interleaved; i++ ) {
-                quantize_row_q4_0_reference(src + b + i * n_per_row + x * QK4_0, (block_q4_0 *) dst_tmp + i, QK4_0);
+                quantize_row_q4_0_ref(src + b + i * n_per_row + x * QK4_0, (block_q4_0 *) dst_tmp + i, QK4_0);
             }
 
             if (nrows_interleaved == 8) {
-                *(block_q4_0x8 *) out_ptr = make_block_q4_0x8(dst_tmp, interleave_blcksize, 0x88);
+                *(block_q4_0x8 *) out_ptr = make_block_q4_0x8(dst_tmp, blck_size_interleave, 0x88);
                 out_ptr = (block_q4_0x8 *) out_ptr + 1;
             }
             else if (nrows_interleaved == 4) {
-                *(block_q4_0x4 *) out_ptr = make_block_q4_0x4(dst_tmp, interleave_blcksize, 0x88);
+                *(block_q4_0x4 *) out_ptr = make_block_q4_0x4(dst_tmp, blck_size_interleave, 0x88);
                 out_ptr = (block_q4_0x4 *) out_ptr + 1;
             }
         }
diff --git a/ggml/src/ggml-aarch64.h b/ggml/src/ggml-aarch64.h
index 65ead1efed572..517babaf1691b 100644
--- a/ggml/src/ggml-aarch64.h
+++ b/ggml/src/ggml-aarch64.h
@@ -16,7 +16,7 @@ extern "C" {
 void quantize_q8_0_4x4(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
 void quantize_q8_0_4x8(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
 
-void quantize_mat_q8_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t nrows, int64_t n_per_row, int64_t interleave_blcksize);
+void quantize_mat_q8_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t nrows, int64_t n_per_row, int64_t blck_size_interleave);
 
 // Quantization utilizing an importance matrix (a.k.a. "Activation aWare Quantization")
 size_t quantize_q4_0_4x4(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
@@ -24,14 +24,14 @@ size_t quantize_q4_0_4x8(const float * GGML_RESTRICT src, void * GGML_RESTRICT d
 size_t quantize_q4_0_8x8(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
 
 // GEMV
-void ggml_gemv_q4_0_4x4_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
-void ggml_gemv_q4_0_4x8_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
-void ggml_gemv_q4_0_8x8_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemv_q4_0_4x4_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemv_q4_0_4x8_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemv_q4_0_8x8_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
 
 // GEMM
-void ggml_gemm_q4_0_4x4_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
-void ggml_gemm_q4_0_4x8_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
-void ggml_gemm_q4_0_8x8_q8_0  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemm_q4_0_4x4_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemm_q4_0_4x8_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemm_q4_0_8x8_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
 
 #ifdef __cplusplus
 }
diff --git a/ggml/src/ggml-quants.c b/ggml/src/ggml-quants.c
index cbe377cf5caee..1839a722ed00c 100644
--- a/ggml/src/ggml-quants.c
+++ b/ggml/src/ggml-quants.c
@@ -658,7 +658,7 @@ static inline __m128i packNibbles( __m256i bytes ) {
 #endif  //__loongarch_asx
 
 // reference implementation for deterministic creation of model files
-void quantize_row_q4_0_reference(const float * restrict x, block_q4_0 * restrict y, int64_t k) {
+void quantize_row_q4_0_ref(const float * restrict x, block_q4_0 * restrict y, int64_t k) {
     static const int qk = QK4_0;
 
     assert(k % qk == 0);
@@ -696,11 +696,11 @@ void quantize_row_q4_0_reference(const float * restrict x, block_q4_0 * restrict
 }
 
 void quantize_row_q4_0(const float * restrict x, void * restrict y, int64_t k) {
-    quantize_row_q4_0_reference(x, y, k);
+    quantize_row_q4_0_ref(x, y, k);
 }
 
 
-void quantize_row_q4_1_reference(const float * restrict x, block_q4_1 * restrict y, int64_t k) {
+void quantize_row_q4_1_ref(const float * restrict x, block_q4_1 * restrict y, int64_t k) {
     const int qk = QK4_1;
 
     assert(k % qk == 0);
@@ -738,10 +738,10 @@ void quantize_row_q4_1_reference(const float * restrict x, block_q4_1 * restrict
 }
 
 void quantize_row_q4_1(const float * restrict x, void * restrict y, int64_t k) {
-    quantize_row_q4_1_reference(x, y, k);
+    quantize_row_q4_1_ref(x, y, k);
 }
 
-void quantize_row_q5_0_reference(const float * restrict x, block_q5_0 * restrict y, int64_t k) {
+void quantize_row_q5_0_ref(const float * restrict x, block_q5_0 * restrict y, int64_t k) {
     static const int qk = QK5_0;
 
     assert(k % qk == 0);
@@ -786,10 +786,10 @@ void quantize_row_q5_0_reference(const float * restrict x, block_q5_0 * restrict
 }
 
 void quantize_row_q5_0(const float * restrict x, void * restrict y, int64_t k) {
-    quantize_row_q5_0_reference(x, y, k);
+    quantize_row_q5_0_ref(x, y, k);
 }
 
-void quantize_row_q5_1_reference(const float * restrict x, block_q5_1 * restrict y, int64_t k) {
+void quantize_row_q5_1_ref(const float * restrict x, block_q5_1 * restrict y, int64_t k) {
     const int qk = QK5_1;
 
     assert(k % qk == 0);
@@ -834,11 +834,11 @@ void quantize_row_q5_1_reference(const float * restrict x, block_q5_1 * restrict
 }
 
 void quantize_row_q5_1(const float * restrict x, void * restrict y, int64_t k) {
-    quantize_row_q5_1_reference(x, y, k);
+    quantize_row_q5_1_ref(x, y, k);
 }
 
 // reference implementation for deterministic creation of model files
-void quantize_row_q8_0_reference(const float * restrict x, block_q8_0 * restrict y, int64_t k) {
+void quantize_row_q8_0_ref(const float * restrict x, block_q8_0 * restrict y, int64_t k) {
     assert(k % QK8_0 == 0);
     const int nb = k / QK8_0;
 
@@ -1144,12 +1144,12 @@ void quantize_row_q8_0(const float * restrict x, void * restrict vy, int64_t k)
 #else
     GGML_UNUSED(nb);
     // scalar
-    quantize_row_q8_0_reference(x, y, k);
+    quantize_row_q8_0_ref(x, y, k);
 #endif
 }
 
 // reference implementation for deterministic creation of model files
-void quantize_row_q8_1_reference(const float * restrict x, block_q8_1 * restrict y, int64_t k) {
+void quantize_row_q8_1_ref(const float * restrict x, block_q8_1 * restrict y, int64_t k) {
     assert(QK8_1 == 32);
     assert(k % QK8_1 == 0);
     const int nb = k / QK8_1;
@@ -1508,7 +1508,7 @@ void quantize_row_q8_1(const float * restrict x, void * restrict vy, int64_t k)
 #else
     GGML_UNUSED(nb);
     // scalar
-    quantize_row_q8_1_reference(x, y, k);
+    quantize_row_q8_1_ref(x, y, k);
 #endif
 }
 
@@ -1899,7 +1899,7 @@ static inline void get_scale_min_k4(int j, const uint8_t * restrict q, uint8_t *
 
 //========================- 2-bit (de)-quantization
 
-void quantize_row_q2_K_reference(const float * restrict x, block_q2_K * restrict y, int64_t k) {
+void quantize_row_q2_K_ref(const float * restrict x, block_q2_K * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     const int nb = k / QK_K;
 
@@ -2002,7 +2002,7 @@ void dequantize_row_q2_K(const block_q2_K * restrict x, float * restrict y, int6
 }
 
 void quantize_row_q2_K(const float * restrict x, void * restrict vy, int64_t k) {
-    quantize_row_q2_K_reference(x, vy, k);
+    quantize_row_q2_K_ref(x, vy, k);
 }
 
 static float make_qkx3_quants(int n, int nmax, const float * restrict x, const float * restrict weights,
@@ -2226,7 +2226,7 @@ static void quantize_row_q2_K_impl(const float * restrict x, block_q2_K * restri
 size_t quantize_q2_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     size_t row_size = ggml_row_size(GGML_TYPE_Q2_K, n_per_row);
     if (!quant_weights) {
-        quantize_row_q2_K_reference(src, dst, (int64_t)nrow*n_per_row);
+        quantize_row_q2_K_ref(src, dst, (int64_t)nrow*n_per_row);
     }
     else {
         char * qrow = (char *)dst;
@@ -2241,7 +2241,7 @@ size_t quantize_q2_K(const float * restrict src, void * restrict dst, int64_t nr
 
 //========================= 3-bit (de)-quantization
 
-void quantize_row_q3_K_reference(const float * restrict x, block_q3_K * restrict y, int64_t k) {
+void quantize_row_q3_K_ref(const float * restrict x, block_q3_K * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     const int nb = k / QK_K;
 
@@ -2368,7 +2368,7 @@ void dequantize_row_q3_K(const block_q3_K * restrict x, float * restrict y, int6
 }
 
 void quantize_row_q3_K(const float * restrict x, void * restrict vy, int64_t k) {
-    quantize_row_q3_K_reference(x, vy, k);
+    quantize_row_q3_K_ref(x, vy, k);
 }
 
 static void quantize_row_q3_K_impl(const float * restrict x, block_q3_K * restrict y, int64_t n_per_row, const float * restrict quant_weights) {
@@ -2458,7 +2458,7 @@ static void quantize_row_q3_K_impl(const float * restrict x, block_q3_K * restri
 size_t quantize_q3_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     size_t row_size = ggml_row_size(GGML_TYPE_Q3_K, n_per_row);
     if (!quant_weights) {
-        quantize_row_q3_K_reference(src, dst, (int64_t)nrow*n_per_row);
+        quantize_row_q3_K_ref(src, dst, (int64_t)nrow*n_per_row);
     }
     else {
         char * qrow = (char *)dst;
@@ -2473,7 +2473,7 @@ size_t quantize_q3_K(const float * restrict src, void * restrict dst, int64_t nr
 
 // ====================== 4-bit (de)-quantization
 
-void quantize_row_q4_K_reference(const float * restrict x, block_q4_K * restrict y, int64_t k) {
+void quantize_row_q4_K_ref(const float * restrict x, block_q4_K * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     const int nb = k / QK_K;
 
@@ -2572,7 +2572,7 @@ void dequantize_row_q4_K(const block_q4_K * restrict x, float * restrict y, int6
 void quantize_row_q4_K(const float * restrict x, void * restrict vy, int64_t k) {
     assert(k % QK_K == 0);
     block_q4_K * restrict y = vy;
-    quantize_row_q4_K_reference(x, y, k);
+    quantize_row_q4_K_ref(x, y, k);
 }
 
 static void quantize_row_q4_K_impl(const float * restrict x, block_q4_K * restrict y, int64_t n_per_row, const float * quant_weights) {
@@ -2651,7 +2651,7 @@ static void quantize_row_q4_K_impl(const float * restrict x, block_q4_K * restri
 size_t quantize_q4_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     size_t row_size = ggml_row_size(GGML_TYPE_Q4_K, n_per_row);
     if (!quant_weights) {
-        quantize_row_q4_K_reference(src, dst, (int64_t)nrow*n_per_row);
+        quantize_row_q4_K_ref(src, dst, (int64_t)nrow*n_per_row);
     }
     else {
         char * qrow = (char *)dst;
@@ -2666,7 +2666,7 @@ size_t quantize_q4_K(const float * restrict src, void * restrict dst, int64_t nr
 
 // ====================== 5-bit (de)-quantization
 
-void quantize_row_q5_K_reference(const float * restrict x, block_q5_K * restrict y, int64_t k) {
+void quantize_row_q5_K_ref(const float * restrict x, block_q5_K * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     const int64_t nb = k / QK_K;
 
@@ -2783,7 +2783,7 @@ void dequantize_row_q5_K(const block_q5_K * restrict x, float * restrict y, int6
 void quantize_row_q5_K(const float * restrict x, void * restrict vy, int64_t k) {
     assert(k % QK_K == 0);
     block_q5_K * restrict y = vy;
-    quantize_row_q5_K_reference(x, y, k);
+    quantize_row_q5_K_ref(x, y, k);
 }
 
 static void quantize_row_q5_K_impl(const float * restrict x, block_q5_K * restrict y, int64_t n_per_row, const float * quant_weights) {
@@ -2882,7 +2882,7 @@ static void quantize_row_q5_K_impl(const float * restrict x, block_q5_K * restri
 size_t quantize_q5_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     size_t row_size = ggml_row_size(GGML_TYPE_Q5_K, n_per_row);
     if (!quant_weights) {
-        quantize_row_q5_K_reference(src, dst, (int64_t)nrow*n_per_row);
+        quantize_row_q5_K_ref(src, dst, (int64_t)nrow*n_per_row);
     }
     else {
         char * qrow = (char *)dst;
@@ -2897,7 +2897,7 @@ size_t quantize_q5_K(const float * restrict src, void * restrict dst, int64_t nr
 
 // ====================== 6-bit (de)-quantization
 
-void quantize_row_q6_K_reference(const float * restrict x, block_q6_K * restrict y, int64_t k) {
+void quantize_row_q6_K_ref(const float * restrict x, block_q6_K * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     const int64_t nb = k / QK_K;
 
@@ -3001,7 +3001,7 @@ void dequantize_row_q6_K(const block_q6_K * restrict x, float * restrict y, int6
 void quantize_row_q6_K(const float * restrict x, void * restrict vy, int64_t k) {
     assert(k % QK_K == 0);
     block_q6_K * restrict y = vy;
-    quantize_row_q6_K_reference(x, y, k);
+    quantize_row_q6_K_ref(x, y, k);
 }
 
 static void quantize_row_q6_K_impl(const float * restrict x, block_q6_K * restrict y, int64_t n_per_row, const float * quant_weights) {
@@ -3091,7 +3091,7 @@ static void quantize_row_q6_K_impl(const float * restrict x, block_q6_K * restri
 size_t quantize_q6_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     size_t row_size = ggml_row_size(GGML_TYPE_Q6_K, n_per_row);
     if (!quant_weights) {
-        quantize_row_q6_K_reference(src, dst, (int64_t)nrow*n_per_row);
+        quantize_row_q6_K_ref(src, dst, (int64_t)nrow*n_per_row);
     }
     else {
         char * qrow = (char *)dst;
@@ -3108,7 +3108,7 @@ static void quantize_row_q4_0_impl(const float * restrict x, block_q4_0 * restri
     static_assert(QK4_0 == 32, "QK4_0 must be 32");
 
     if (!quant_weights) {
-        quantize_row_q4_0_reference(x, y, n_per_row);
+        quantize_row_q4_0_ref(x, y, n_per_row);
         return;
     }
 
@@ -3134,7 +3134,7 @@ static void quantize_row_q4_0_impl(const float * restrict x, block_q4_0 * restri
 
 size_t quantize_q4_0(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     if (!quant_weights) {
-        quantize_row_q4_0_reference(src, dst, (int64_t)nrow*n_per_row);
+        quantize_row_q4_0_ref(src, dst, (int64_t)nrow*n_per_row);
         return nrow * ggml_row_size(GGML_TYPE_Q4_0, n_per_row);
     }
     size_t row_size = ggml_row_size(GGML_TYPE_Q4_0, n_per_row);
@@ -3151,7 +3151,7 @@ static void quantize_row_q4_1_impl(const float * restrict x, block_q4_1 * restri
     static_assert(QK4_1 == 32, "QK4_1 must be 32");
 
     if (!quant_weights) {
-        quantize_row_q4_1_reference(x, y, n_per_row);
+        quantize_row_q4_1_ref(x, y, n_per_row);
         return;
     }
 
@@ -3179,7 +3179,7 @@ static void quantize_row_q4_1_impl(const float * restrict x, block_q4_1 * restri
 
 size_t quantize_q4_1(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     if (!quant_weights) {
-        quantize_row_q4_1_reference(src, dst, (int64_t)nrow*n_per_row);
+        quantize_row_q4_1_ref(src, dst, (int64_t)nrow*n_per_row);
         return nrow * ggml_row_size(GGML_TYPE_Q4_1, n_per_row);
     }
     size_t row_size = ggml_row_size(GGML_TYPE_Q4_1, n_per_row);
@@ -3196,7 +3196,7 @@ static void quantize_row_q5_0_impl(const float * restrict x, block_q5_0 * restri
     static_assert(QK5_0 == 32, "QK5_0 must be 32");
 
     if (!quant_weights) {
-        quantize_row_q5_0_reference(x, y, n_per_row);
+        quantize_row_q5_0_ref(x, y, n_per_row);
         return;
     }
 
@@ -3233,7 +3233,7 @@ static void quantize_row_q5_0_impl(const float * restrict x, block_q5_0 * restri
 
 size_t quantize_q5_0(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     if (!quant_weights) {
-        quantize_row_q5_0_reference(src, dst, (int64_t)nrow*n_per_row);
+        quantize_row_q5_0_ref(src, dst, (int64_t)nrow*n_per_row);
         return nrow * ggml_row_size(GGML_TYPE_Q5_0, n_per_row);
     }
     size_t row_size = ggml_row_size(GGML_TYPE_Q5_0, n_per_row);
@@ -3250,7 +3250,7 @@ static void quantize_row_q5_1_impl(const float * restrict x, block_q5_1 * restri
     static_assert(QK5_1 == 32, "QK5_1 must be 32");
 
     if (!quant_weights) {
-        quantize_row_q5_1_reference(x, y, n_per_row);
+        quantize_row_q5_1_ref(x, y, n_per_row);
         return;
     }
 
@@ -3286,7 +3286,7 @@ static void quantize_row_q5_1_impl(const float * restrict x, block_q5_1 * restri
 
 size_t quantize_q5_1(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     if (!quant_weights) {
-        quantize_row_q5_1_reference(src, dst, (int64_t)nrow*n_per_row);
+        quantize_row_q5_1_ref(src, dst, (int64_t)nrow*n_per_row);
         return nrow * ggml_row_size(GGML_TYPE_Q5_1, n_per_row);
     }
     size_t row_size = ggml_row_size(GGML_TYPE_Q5_1, n_per_row);
@@ -3302,7 +3302,7 @@ size_t quantize_q5_1(const float * restrict src, void * restrict dst, int64_t nr
 size_t quantize_q8_0(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     (void)quant_weights; // not used
     const size_t row_size = ggml_row_size(GGML_TYPE_Q8_0, n_per_row);
-    quantize_row_q8_0_reference(src, dst, (int64_t)nrow*n_per_row);
+    quantize_row_q8_0_ref(src, dst, (int64_t)nrow*n_per_row);
     return nrow * row_size;
 }
 
@@ -3590,7 +3590,7 @@ void dequantize_row_iq4_xs(const block_iq4_xs * restrict x, float * restrict y,
 
 //===================================== Q8_K ==============================================
 
-void quantize_row_q8_K_reference(const float * restrict x, block_q8_K * restrict y, int64_t k) {
+void quantize_row_q8_K_ref(const float * restrict x, block_q8_K * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     const int64_t nb = k / QK_K;
 
@@ -3641,7 +3641,7 @@ void dequantize_row_q8_K(const block_q8_K * restrict x, float * restrict y, int6
 }
 
 void quantize_row_q8_K(const float * restrict x, void * restrict y, int64_t k) {
-    quantize_row_q8_K_reference(x, y, k);
+    quantize_row_q8_K_ref(x, y, k);
 }
 
 //===================================== Dot ptoducts =================================
@@ -13530,10 +13530,10 @@ size_t quantize_iq3_xxs(const float * restrict src, void * restrict dst, int64_t
 void quantize_row_iq3_xxs(const float * restrict x, void * restrict vy, int64_t k) {
     assert(k % QK_K == 0);
     block_iq3_xxs * restrict y = vy;
-    quantize_row_iq3_xxs_reference(x, y, k);
+    quantize_row_iq3_xxs_ref(x, y, k);
 }
 
-void quantize_row_iq3_xxs_reference(const float * restrict x, block_iq3_xxs * restrict y, int64_t k) {
+void quantize_row_iq3_xxs_ref(const float * restrict x, block_iq3_xxs * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     quantize_row_iq3_xxs_impl(256, x, y, k, NULL);
 }
@@ -13746,10 +13746,10 @@ size_t quantize_iq3_s(const float * restrict src, void * restrict dst, int64_t n
 void quantize_row_iq3_s(const float * restrict x, void * restrict vy, int64_t k) {
     assert(k % QK_K == 0);
     block_iq3_s * restrict y = vy;
-    quantize_row_iq3_s_reference(x, y, k);
+    quantize_row_iq3_s_ref(x, y, k);
 }
 
-void quantize_row_iq3_s_reference(const float * restrict x, block_iq3_s * restrict y, int64_t k) {
+void quantize_row_iq3_s_ref(const float * restrict x, block_iq3_s * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     quantize_iq3_s(x, y, 1, k, NULL);
 }
@@ -14487,7 +14487,7 @@ void quantize_row_iq4_nl(const float * restrict x, void * restrict vy, int64_t k
     }
 }
 
-void quantize_row_iq4_nl_reference(const float * restrict x, block_iq4_nl * restrict y, int64_t k) {
+void quantize_row_iq4_nl_ref(const float * restrict x, block_iq4_nl * restrict y, int64_t k) {
     assert(k % QK4_NL == 0);
     quantize_row_iq4_nl(x, y, k);
 }
@@ -14515,10 +14515,10 @@ size_t quantize_iq4_xs(const float * restrict src, void * restrict dst, int64_t
 void quantize_row_iq4_xs(const float * restrict x, void * restrict vy, int64_t k) {
     assert(k % QK_K == 0);
     block_iq4_xs * restrict y = vy;
-    quantize_row_iq4_xs_reference(x, y, k);
+    quantize_row_iq4_xs_ref(x, y, k);
 }
 
-void quantize_row_iq4_xs_reference(const float * restrict x, block_iq4_xs * restrict y, int64_t k) {
+void quantize_row_iq4_xs_ref(const float * restrict x, block_iq4_xs * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     quantize_iq4_xs(x, y, 1, k, NULL);
 }
@@ -14705,7 +14705,7 @@ size_t quantize_iq2_s(const float * restrict src, void * restrict dst, int64_t n
     return nrow * nblock * sizeof(block_iq2_s);
 }
 
-void quantize_row_iq2_s_reference(const float * restrict x, block_iq2_s * restrict y, int64_t k) {
+void quantize_row_iq2_s_ref(const float * restrict x, block_iq2_s * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     quantize_iq2_s(x, y, 1, k, NULL);
 }
@@ -14713,7 +14713,7 @@ void quantize_row_iq2_s_reference(const float * restrict x, block_iq2_s * restri
 void quantize_row_iq2_s(const float * restrict x, void * restrict vy, int64_t k) {
     assert(k % QK_K == 0);
     block_iq2_s * restrict y = vy;
-    quantize_row_iq2_s_reference(x, y, k);
+    quantize_row_iq2_s_ref(x, y, k);
 }
 
 static bool validate_float(float f, size_t i) {
diff --git a/ggml/src/ggml-quants.h b/ggml/src/ggml-quants.h
index 30983b8728fa2..88b1f3269646d 100644
--- a/ggml/src/ggml-quants.h
+++ b/ggml/src/ggml-quants.h
@@ -12,25 +12,25 @@ extern "C" {
 #endif
 
 // Quantization
-void quantize_row_q4_0_reference(const float * GGML_RESTRICT x, block_q4_0 * GGML_RESTRICT y, int64_t k);
-void quantize_row_q4_1_reference(const float * GGML_RESTRICT x, block_q4_1 * GGML_RESTRICT y, int64_t k);
-void quantize_row_q5_0_reference(const float * GGML_RESTRICT x, block_q5_0 * GGML_RESTRICT y, int64_t k);
-void quantize_row_q5_1_reference(const float * GGML_RESTRICT x, block_q5_1 * GGML_RESTRICT y, int64_t k);
-void quantize_row_q8_0_reference(const float * GGML_RESTRICT x, block_q8_0 * GGML_RESTRICT y, int64_t k);
-void quantize_row_q8_1_reference(const float * GGML_RESTRICT x, block_q8_1 * GGML_RESTRICT y, int64_t k);
-
-void quantize_row_q2_K_reference(const float * GGML_RESTRICT x, block_q2_K * GGML_RESTRICT y, int64_t k);
-void quantize_row_q3_K_reference(const float * GGML_RESTRICT x, block_q3_K * GGML_RESTRICT y, int64_t k);
-void quantize_row_q4_K_reference(const float * GGML_RESTRICT x, block_q4_K * GGML_RESTRICT y, int64_t k);
-void quantize_row_q5_K_reference(const float * GGML_RESTRICT x, block_q5_K * GGML_RESTRICT y, int64_t k);
-void quantize_row_q6_K_reference(const float * GGML_RESTRICT x, block_q6_K * GGML_RESTRICT y, int64_t k);
-void quantize_row_q8_K_reference(const float * GGML_RESTRICT x, block_q8_K * GGML_RESTRICT y, int64_t k);
-
-void quantize_row_iq3_xxs_reference(const float * GGML_RESTRICT x, block_iq3_xxs * GGML_RESTRICT y, int64_t k);
-void quantize_row_iq4_nl_reference (const float * GGML_RESTRICT x, block_iq4_nl  * GGML_RESTRICT y, int64_t k);
-void quantize_row_iq4_xs_reference (const float * GGML_RESTRICT x, block_iq4_xs  * GGML_RESTRICT y, int64_t k);
-void quantize_row_iq3_s_reference  (const float * GGML_RESTRICT x, block_iq3_s   * GGML_RESTRICT y, int64_t k);
-void quantize_row_iq2_s_reference  (const float * GGML_RESTRICT x, block_iq2_s   * GGML_RESTRICT y, int64_t k);
+void quantize_row_q4_0_ref(const float * GGML_RESTRICT x, block_q4_0 * GGML_RESTRICT y, int64_t k);
+void quantize_row_q4_1_ref(const float * GGML_RESTRICT x, block_q4_1 * GGML_RESTRICT y, int64_t k);
+void quantize_row_q5_0_ref(const float * GGML_RESTRICT x, block_q5_0 * GGML_RESTRICT y, int64_t k);
+void quantize_row_q5_1_ref(const float * GGML_RESTRICT x, block_q5_1 * GGML_RESTRICT y, int64_t k);
+void quantize_row_q8_0_ref(const float * GGML_RESTRICT x, block_q8_0 * GGML_RESTRICT y, int64_t k);
+void quantize_row_q8_1_ref(const float * GGML_RESTRICT x, block_q8_1 * GGML_RESTRICT y, int64_t k);
+
+void quantize_row_q2_K_ref(const float * GGML_RESTRICT x, block_q2_K * GGML_RESTRICT y, int64_t k);
+void quantize_row_q3_K_ref(const float * GGML_RESTRICT x, block_q3_K * GGML_RESTRICT y, int64_t k);
+void quantize_row_q4_K_ref(const float * GGML_RESTRICT x, block_q4_K * GGML_RESTRICT y, int64_t k);
+void quantize_row_q5_K_ref(const float * GGML_RESTRICT x, block_q5_K * GGML_RESTRICT y, int64_t k);
+void quantize_row_q6_K_ref(const float * GGML_RESTRICT x, block_q6_K * GGML_RESTRICT y, int64_t k);
+void quantize_row_q8_K_ref(const float * GGML_RESTRICT x, block_q8_K * GGML_RESTRICT y, int64_t k);
+
+void quantize_row_iq3_xxs_ref(const float * GGML_RESTRICT x, block_iq3_xxs * GGML_RESTRICT y, int64_t k);
+void quantize_row_iq4_nl_ref (const float * GGML_RESTRICT x, block_iq4_nl  * GGML_RESTRICT y, int64_t k);
+void quantize_row_iq4_xs_ref (const float * GGML_RESTRICT x, block_iq4_xs  * GGML_RESTRICT y, int64_t k);
+void quantize_row_iq3_s_ref  (const float * GGML_RESTRICT x, block_iq3_s   * GGML_RESTRICT y, int64_t k);
+void quantize_row_iq2_s_ref  (const float * GGML_RESTRICT x, block_iq2_s   * GGML_RESTRICT y, int64_t k);
 
 void quantize_row_q4_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
 void quantize_row_q4_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c
index 1bb731e16d51d..9a54147871847 100644
--- a/ggml/src/ggml.c
+++ b/ggml/src/ggml.c
@@ -592,7 +592,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = false,
         .to_float                 = (ggml_to_float_t) ggml_fp16_to_fp32_row,
         .from_float               = (ggml_from_float_t) ggml_fp32_to_fp16_row,
-        .from_float_reference     = (ggml_from_float_t) ggml_fp32_to_fp16_row,
+        .from_float_ref           = (ggml_from_float_t) ggml_fp32_to_fp16_row,
         .vec_dot                  = (ggml_vec_dot_t) ggml_vec_dot_f16,
         .vec_dot_type             = GGML_TYPE_F16,
         .nrows                    = 1,
@@ -604,7 +604,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_q4_0,
         .from_float               = quantize_row_q4_0,
-        .from_float_reference     = (ggml_from_float_t) quantize_row_q4_0_reference,
+        .from_float_ref           = (ggml_from_float_t) quantize_row_q4_0_ref,
         .vec_dot                  = ggml_vec_dot_q4_0_q8_0,
         .vec_dot_type             = GGML_TYPE_Q8_0,
 #if defined (__ARM_FEATURE_MATMUL_INT8)
@@ -620,7 +620,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_q4_1,
         .from_float               = quantize_row_q4_1,
-        .from_float_reference     = (ggml_from_float_t) quantize_row_q4_1_reference,
+        .from_float_ref           = (ggml_from_float_t) quantize_row_q4_1_ref,
         .vec_dot                  = ggml_vec_dot_q4_1_q8_1,
         .vec_dot_type             = GGML_TYPE_Q8_1,
 #if defined (__ARM_FEATURE_MATMUL_INT8)
@@ -636,7 +636,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = false,
         .to_float                 = NULL,
         .from_float               = NULL,
-        .from_float_reference     = NULL,
+        .from_float_ref           = NULL,
         .vec_dot                  = NULL,
         .vec_dot_type             = GGML_TYPE_COUNT,
         .nrows                    = 1,
@@ -648,7 +648,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = false,
         .to_float                 = NULL,
         .from_float               = NULL,
-        .from_float_reference     = NULL,
+        .from_float_ref           = NULL,
         .vec_dot                  = NULL,
         .vec_dot_type             = GGML_TYPE_COUNT,
         .nrows                    = 1,
@@ -660,7 +660,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_q5_0,
         .from_float               = quantize_row_q5_0,
-        .from_float_reference     = (ggml_from_float_t) quantize_row_q5_0_reference,
+        .from_float_ref           = (ggml_from_float_t) quantize_row_q5_0_ref,
         .vec_dot                  = ggml_vec_dot_q5_0_q8_0,
         .vec_dot_type             = GGML_TYPE_Q8_0,
         .nrows                    = 1,
@@ -672,7 +672,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_q5_1,
         .from_float               = quantize_row_q5_1,
-        .from_float_reference     = (ggml_from_float_t) quantize_row_q5_1_reference,
+        .from_float_ref           = (ggml_from_float_t) quantize_row_q5_1_ref,
         .vec_dot                  = ggml_vec_dot_q5_1_q8_1,
         .vec_dot_type             = GGML_TYPE_Q8_1,
         .nrows                    = 1,
@@ -684,7 +684,8 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_q8_0,
         .from_float               = quantize_row_q8_0,
-        .from_float_reference     = (ggml_from_float_t) quantize_row_q8_0_reference,
+        .from_float_ref           = (ggml_from_float_t) quantize_row_q8_0_ref,
+        .from_float_to_mat        = quantize_mat_q8_0,
         .vec_dot                  = ggml_vec_dot_q8_0_q8_0,
         .vec_dot_type             = GGML_TYPE_Q8_0,
 #if defined (__ARM_FEATURE_MATMUL_INT8)
@@ -692,7 +693,6 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
 #else
         .nrows                    = 1,
 #endif
-        .from_float_to_mat        = quantize_mat_q8_0,
     },
     [GGML_TYPE_Q8_1] = {
         .type_name                = "q8_1",
@@ -700,7 +700,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .type_size                = sizeof(block_q8_1),
         .is_quantized             = true,
         .from_float               = quantize_row_q8_1,
-        .from_float_reference     = (ggml_from_float_t) quantize_row_q8_1_reference,
+        .from_float_ref           = (ggml_from_float_t) quantize_row_q8_1_ref,
         .vec_dot_type             = GGML_TYPE_Q8_1,
         .nrows                    = 1,
     },
@@ -711,7 +711,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_q2_K,
         .from_float               = quantize_row_q2_K,
-        .from_float_reference     = (ggml_from_float_t) quantize_row_q2_K_reference,
+        .from_float_ref           = (ggml_from_float_t) quantize_row_q2_K_ref,
         .vec_dot                  = ggml_vec_dot_q2_K_q8_K,
         .vec_dot_type             = GGML_TYPE_Q8_K,
         .nrows                    = 1,
@@ -723,7 +723,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_q3_K,
         .from_float               = quantize_row_q3_K,
-        .from_float_reference     = (ggml_from_float_t) quantize_row_q3_K_reference,
+        .from_float_ref           = (ggml_from_float_t) quantize_row_q3_K_ref,
         .vec_dot                  = ggml_vec_dot_q3_K_q8_K,
         .vec_dot_type             = GGML_TYPE_Q8_K,
         .nrows                    = 1,
@@ -735,7 +735,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_q4_K,
         .from_float               = quantize_row_q4_K,
-        .from_float_reference     = (ggml_from_float_t) quantize_row_q4_K_reference,
+        .from_float_ref           = (ggml_from_float_t) quantize_row_q4_K_ref,
         .vec_dot                  = ggml_vec_dot_q4_K_q8_K,
         .vec_dot_type             = GGML_TYPE_Q8_K,
         .nrows                    = 1,
@@ -747,7 +747,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_q5_K,
         .from_float               = quantize_row_q5_K,
-        .from_float_reference     = (ggml_from_float_t) quantize_row_q5_K_reference,
+        .from_float_ref           = (ggml_from_float_t) quantize_row_q5_K_ref,
         .vec_dot                  = ggml_vec_dot_q5_K_q8_K,
         .vec_dot_type             = GGML_TYPE_Q8_K,
         .nrows                    = 1,
@@ -759,7 +759,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_q6_K,
         .from_float               = quantize_row_q6_K,
-        .from_float_reference     = (ggml_from_float_t) quantize_row_q6_K_reference,
+        .from_float_ref           = (ggml_from_float_t) quantize_row_q6_K_ref,
         .vec_dot                  = ggml_vec_dot_q6_K_q8_K,
         .vec_dot_type             = GGML_TYPE_Q8_K,
         .nrows                    = 1,
@@ -771,7 +771,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_iq2_xxs,
         .from_float               = NULL,
-        .from_float_reference     = NULL,
+        .from_float_ref           = NULL,
         .vec_dot                  = ggml_vec_dot_iq2_xxs_q8_K,
         .vec_dot_type             = GGML_TYPE_Q8_K,
         .nrows                    = 1,
@@ -783,7 +783,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_iq2_xs,
         .from_float               = NULL,
-        .from_float_reference     = NULL,
+        .from_float_ref           = NULL,
         .vec_dot                  = ggml_vec_dot_iq2_xs_q8_K,
         .vec_dot_type             = GGML_TYPE_Q8_K,
         .nrows                    = 1,
@@ -795,7 +795,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_iq3_xxs,
         .from_float               = quantize_row_iq3_xxs,
-        .from_float_reference     = (ggml_from_float_t)quantize_row_iq3_xxs_reference,
+        .from_float_ref           = (ggml_from_float_t)quantize_row_iq3_xxs_ref,
         .vec_dot                  = ggml_vec_dot_iq3_xxs_q8_K,
         .vec_dot_type             = GGML_TYPE_Q8_K,
         .nrows                    = 1,
@@ -807,7 +807,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_iq3_s,
         .from_float               = quantize_row_iq3_s,
-        .from_float_reference     = (ggml_from_float_t)quantize_row_iq3_s_reference,
+        .from_float_ref           = (ggml_from_float_t)quantize_row_iq3_s_ref,
         .vec_dot                  = ggml_vec_dot_iq3_s_q8_K,
         .vec_dot_type             = GGML_TYPE_Q8_K,
         .nrows                    = 1,
@@ -819,7 +819,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_iq2_s,
         .from_float               = quantize_row_iq2_s,
-        .from_float_reference     = (ggml_from_float_t)quantize_row_iq2_s_reference,
+        .from_float_ref           = (ggml_from_float_t)quantize_row_iq2_s_ref,
         .vec_dot                  = ggml_vec_dot_iq2_s_q8_K,
         .vec_dot_type             = GGML_TYPE_Q8_K,
         .nrows                    = 1,
@@ -831,7 +831,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_iq1_s,
         .from_float               = NULL,
-        .from_float_reference     = NULL,
+        .from_float_ref           = NULL,
         .vec_dot                  = ggml_vec_dot_iq1_s_q8_K,
         .vec_dot_type             = GGML_TYPE_Q8_K,
         .nrows                    = 1,
@@ -843,7 +843,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_iq1_m,
         .from_float               = NULL,
-        .from_float_reference     = NULL,
+        .from_float_ref           = NULL,
         .vec_dot                  = ggml_vec_dot_iq1_m_q8_K,
         .vec_dot_type             = GGML_TYPE_Q8_K,
         .nrows                    = 1,
@@ -855,7 +855,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_iq4_nl,
         .from_float               = quantize_row_iq4_nl,
-        .from_float_reference     = (ggml_from_float_t)quantize_row_iq4_nl_reference,
+        .from_float_ref           = (ggml_from_float_t)quantize_row_iq4_nl_ref,
         .vec_dot                  = ggml_vec_dot_iq4_nl_q8_0,
         .vec_dot_type             = GGML_TYPE_Q8_0,
         .nrows                    = 1,
@@ -867,7 +867,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_iq4_xs,
         .from_float               = quantize_row_iq4_xs,
-        .from_float_reference     = (ggml_from_float_t)quantize_row_iq4_xs_reference,
+        .from_float_ref           = (ggml_from_float_t)quantize_row_iq4_xs_ref,
         .vec_dot                  = ggml_vec_dot_iq4_xs_q8_K,
         .vec_dot_type             = GGML_TYPE_Q8_K,
         .nrows                    = 1,
@@ -886,7 +886,7 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .is_quantized             = false,
         .to_float                 = (ggml_to_float_t) ggml_bf16_to_fp32_row,
         .from_float               = (ggml_from_float_t) ggml_fp32_to_bf16_row,
-        .from_float_reference     = (ggml_from_float_t) ggml_fp32_to_bf16_row,
+        .from_float_ref           = (ggml_from_float_t) ggml_fp32_to_bf16_row,
         .vec_dot                  = (ggml_vec_dot_t) ggml_vec_dot_bf16,
         .vec_dot_type             = GGML_TYPE_BF16,
         .nrows                    = 1,
@@ -894,48 +894,48 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
     [GGML_TYPE_Q4_0_4_4] = {
         .type_name                = "q4_0_4x4",
         .blck_size                = QK4_0,
+        .blck_size_interleave     = 4,
         .type_size                = sizeof(block_q4_0),
         .is_quantized             = true,
         .to_float                 = NULL,
         .from_float               = NULL,
-        .from_float_reference     = NULL,
+        .from_float_ref           = NULL,
         .vec_dot                  = NULL,
         .vec_dot_type             = GGML_TYPE_Q8_0,
         .nrows                    = 1,
         .ncols                    = 4,
-        .interleave_blcksize      = 4,
         .gemv                     = ggml_gemv_q4_0_4x4_q8_0,
         .gemm                     = ggml_gemm_q4_0_4x4_q8_0,
     },
     [GGML_TYPE_Q4_0_4_8] = {
         .type_name                = "q4_0_4x8",
         .blck_size                = QK4_0,
+        .blck_size_interleave     = 8,
         .type_size                = sizeof(block_q4_0),
         .is_quantized             = true,
         .to_float                 = NULL,
         .from_float               = NULL,
-        .from_float_reference     = NULL,
+        .from_float_ref           = NULL,
         .vec_dot                  = NULL,
         .vec_dot_type             = GGML_TYPE_Q8_0,
         .nrows                    = 1,
         .ncols                    = 4,
-        .interleave_blcksize      = 8,
         .gemv                     = ggml_gemv_q4_0_4x8_q8_0,
         .gemm                     = ggml_gemm_q4_0_4x8_q8_0,
     },
     [GGML_TYPE_Q4_0_8_8] = {
         .type_name                = "q4_0_8x8",
         .blck_size                = QK4_0,
+        .blck_size_interleave     = 8,
         .type_size                = sizeof(block_q4_0),
         .is_quantized             = true,
         .to_float                 = NULL,
         .from_float               = NULL,
-        .from_float_reference     = NULL,
+        .from_float_ref           = NULL,
         .vec_dot                  = NULL,
         .vec_dot_type             = GGML_TYPE_Q8_0,
         .nrows                    = 1,
         .ncols                    = 8,
-        .interleave_blcksize      = 8,
         .gemv                     = ggml_gemv_q4_0_8x8_q8_0,
         .gemm                     = ggml_gemm_q4_0_8x8_q8_0,
     }
@@ -3115,7 +3115,7 @@ size_t ggml_nbytes_pad(const struct ggml_tensor * tensor) {
     return GGML_PAD(ggml_nbytes(tensor), GGML_MEM_ALIGN);
 }
 
-GGML_CALL int ggml_blck_size(enum ggml_type type) {
+GGML_CALL int64_t ggml_blck_size(enum ggml_type type) {
     return type_traits[type].blck_size;
 }
 
@@ -12192,15 +12192,14 @@ static void ggml_compute_forward_mul_mat(
 
     const enum ggml_type type = src0->type;
 
-    enum ggml_type    const vec_dot_type          = type_traits[type].vec_dot_type;
-    ggml_from_float_t const from_float_to_vec_dot = type_traits[vec_dot_type].from_float;
-    int64_t           const vec_dot_num_rows      = type_traits[type].nrows;
-    int64_t           const matmul_num_cols       = type_traits[type].ncols;
-    int64_t           const interleave_blcksize   = type_traits[type].interleave_blcksize;
-    ggml_from_float_to_mat_t const from_float_to_mat
-                                                  = type_traits[vec_dot_type].from_float_to_mat;
-    ggml_gemv_t       const gemv                  = type_traits[type].gemv;
-    ggml_gemm_t       const gemm                  = type_traits[type].gemm;
+    enum ggml_type           const vec_dot_type         = type_traits[type].vec_dot_type;
+    ggml_from_float_t        const from_float           = type_traits[vec_dot_type].from_float;
+    ggml_from_float_to_mat_t const from_float_to_mat    = type_traits[vec_dot_type].from_float_to_mat;
+    int64_t                  const vec_dot_num_rows     = type_traits[type].nrows;
+    int64_t                  const matmul_num_cols      = type_traits[type].ncols;
+    int64_t                  const blck_size_interleave = type_traits[type].blck_size_interleave;
+    ggml_gemv_t              const gemv                 = type_traits[type].gemv;
+    ggml_gemm_t              const gemm                 = type_traits[type].gemm;
 
     GGML_ASSERT(ne0 == ne01);
     GGML_ASSERT(ne1 == ne11);
@@ -12264,14 +12263,14 @@ UseGgmlGemm1:;
                     for (int64_t i11 = ith * 4; i11 < ne11 - ne11 % 4; i11 += nth * 4) {
                         from_float_to_mat((float *)((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11),
                                           (void *)               (wdata + i13*nbw3 + i12*nbw2 + i11*nbw1),
-                                          4, ne10, interleave_blcksize);
+                                          4, ne10, blck_size_interleave);
                     }
                     i11_processed = ne11 - ne11 % 4;
                 }
                 for (int64_t i11 = i11_processed + ith; i11 < ne11; i11 += nth) {
-                    from_float_to_vec_dot((float *)((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11),
-                                          (void *)               (wdata + i13*nbw3 + i12*nbw2 + i11*nbw1),
-                                           ne10);
+                    from_float((float *)((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11),
+                           (void *)               (wdata + i13*nbw3 + i12*nbw2 + i11*nbw1),
+                           ne10);
                 }
             }
         }
@@ -12355,7 +12354,7 @@ UseGgmlGemm2:;
         int64_t src0_start = (ith * ne01) / nth;
         int64_t src0_end   = ((ith + 1) * ne01) / nth;
         src0_start = (src0_start % matmul_num_cols) ? src0_start + matmul_num_cols - (src0_start % matmul_num_cols): src0_start;
-        src0_end   = (src0_end % matmul_num_cols) ? src0_end + matmul_num_cols - (src0_end % matmul_num_cols): src0_end;
+        src0_end   = (src0_end   % matmul_num_cols) ? src0_end   + matmul_num_cols - (src0_end   % matmul_num_cols): src0_end;
         if (src0_start >= src0_end) return;
 
         // If there are more than three rows in src1, use gemm; otherwise, use gemv.
@@ -12413,11 +12412,11 @@ static void ggml_compute_forward_mul_mat_id(
 
     const bool src1_cont = ggml_is_contiguous(src1);
 
-    ggml_vec_dot_t    const vec_dot               = type_traits[type].vec_dot;
-    enum ggml_type    const vec_dot_type          = type_traits[type].vec_dot_type;
-    ggml_from_float_t const from_float_to_vec_dot = type_traits[vec_dot_type].from_float;
-    int64_t           const matmul_num_cols       = type_traits[type].ncols;
-    ggml_gemv_t       const gemv                  = type_traits[type].gemv;
+    ggml_vec_dot_t    const vec_dot         = type_traits[type].vec_dot;
+    enum ggml_type    const vec_dot_type    = type_traits[type].vec_dot_type;
+    ggml_from_float_t const from_float      = type_traits[vec_dot_type].from_float;
+    int64_t           const matmul_num_cols = type_traits[type].ncols;
+    ggml_gemv_t       const gemv            = type_traits[type].gemv;
 
     // we don't support permuted src0 or src1
     GGML_ASSERT(nb00 == ggml_type_size(type));
@@ -12458,9 +12457,9 @@ static void ggml_compute_forward_mul_mat_id(
         for (int64_t i13 = 0; i13 < ne13; ++i13) {
             for (int64_t i12 = 0; i12 < ne12; ++i12) {
                 for (int64_t i11 = ith; i11 < ne11; i11 += nth) {
-                    from_float_to_vec_dot((float *)((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11),
-                                          (void *)               (wdata + i13*nbw3 + i12*nbw2 + i11*nbw1),
-                                           ne10);
+                    from_float((float *)((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11),
+                               (void *)               (wdata + i13*nbw3 + i12*nbw2 + i11*nbw1),
+                               ne10);
                 }
             }
         }
@@ -21063,8 +21062,8 @@ struct gguf_context * gguf_init_from_file(const char * fname, struct gguf_init_p
                 (int64_t) info->ne[3];
 
             if (ne % ggml_blck_size(info->type) != 0) {
-                fprintf(stderr, "%s: tensor '%s' of type %d (%s) number of elements (%" PRId64 ") is not a multiple of block size (%d)\n",
-                        __func__, info->name.data, (int)info->type, ggml_type_name(info->type), ne, ggml_blck_size(info->type));
+                fprintf(stderr, "%s: tensor '%s' of type %d (%s) number of elements (%" PRId64 ") is not a multiple of block size (%" PRId64 ")\n",
+                        __func__, info->name.data, (int) info->type, ggml_type_name(info->type), ne, ggml_blck_size(info->type));
                 fclose(file);
                 gguf_free(ctx);
                 return NULL;
diff --git a/tests/test-double-float.cpp b/tests/test-double-float.cpp
index 753dae911b0cb..6aac4737a7df0 100644
--- a/tests/test-double-float.cpp
+++ b/tests/test-double-float.cpp
@@ -14,7 +14,7 @@
 #pragma GCC diagnostic push
 #pragma GCC diagnostic ignored "-Wdouble-promotion"
 
-// ggml.c::quantize_row_q4_0_reference
+// ggml.c::quantize_row_q4_0_ref
 inline static uint8_t round_orig(float v0) { return ((int8_t) (round(v0))) + 8; }
 
 // ggml.c::ggml_silu_f32
@@ -24,7 +24,7 @@ inline static float silu_orig(float x) {
 
 #pragma GCC diagnostic pop
 
-// ggml.c::quantize_row_q4_0_reference
+// ggml.c::quantize_row_q4_0_ref
 inline static uint8_t round_float(float v0) { return (int8_t)roundf(v0) + 8; }
 
 // ggml.c::ggml_silu_f32
diff --git a/tests/test-quantize-fns.cpp b/tests/test-quantize-fns.cpp
index e690ac6c85a71..c97458d1df2b8 100644
--- a/tests/test-quantize-fns.cpp
+++ b/tests/test-quantize-fns.cpp
@@ -60,7 +60,7 @@ static float reference_quantization_error(ggml_type_traits_t & qfns, size_t test
     qfns.from_float(test_data, tmp_q.data(), test_size);
     qfns.to_float(tmp_q.data(), tmp_out.data(), test_size);
 
-    qfns.from_float_reference(test_data, tmp_q.data(), test_size);
+    qfns.from_float_ref(test_data, tmp_q.data(), test_size);
     qfns.to_float(tmp_q.data(), tmp_out_ref.data(), test_size);
 
     return array_rmse(tmp_out.data(), tmp_out_ref.data(), test_size);
diff --git a/tests/test-quantize-perf.cpp b/tests/test-quantize-perf.cpp
index 48d9fae3dc06e..24e066053219a 100644
--- a/tests/test-quantize-perf.cpp
+++ b/tests/test-quantize-perf.cpp
@@ -285,7 +285,7 @@ int main(int argc, char * argv[]) {
                 for (size_t size : params.test_sizes) {
                     printf("    %zu values (%.2f MB)\n", size, 4*size/(float)(1024*1024));
                     auto quantize_fn = [&](void) -> float {
-                        qfns.from_float_reference(test_data1, test_q1, size);
+                        qfns.from_float_ref(test_data1, test_q1, size);
                         return test_q1[0];
                     };
                     size_t quantized_size = ggml_row_size(type, size);

From 71c1121d11f1437be9421fd0cbaa011b9ef49098 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Fri, 12 Jul 2024 10:46:14 +0300
Subject: [PATCH 169/326] examples : sprintf -> snprintf (#8434)

* examples : sprintf -> snprintf

ggml-ci

* examples : use sizeof() instead of hardcoded constants
---
 examples/eval-callback/eval-callback.cpp |  2 +-
 examples/gguf-hash/gguf-hash.cpp         | 14 +++++++-------
 2 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/examples/eval-callback/eval-callback.cpp b/examples/eval-callback/eval-callback.cpp
index 64cd338c26351..c8a3016a4d80a 100644
--- a/examples/eval-callback/eval-callback.cpp
+++ b/examples/eval-callback/eval-callback.cpp
@@ -99,7 +99,7 @@ static bool ggml_debug(struct ggml_tensor * t, bool ask, void * user_data) {
 
     char src1_str[128] = {0};
     if (src1) {
-        sprintf(src1_str, "%s{%s}", src1->name, ggml_ne_string(src1).c_str());
+        snprintf(src1_str, sizeof(src1_str), "%s{%s}", src1->name, ggml_ne_string(src1).c_str());
     }
 
     printf("%s: %24s = (%s) %10s(%s{%s}, %s}) = {%s}\n", __func__,
diff --git a/examples/gguf-hash/gguf-hash.cpp b/examples/gguf-hash/gguf-hash.cpp
index c34728c3df4be..e96c75117f533 100644
--- a/examples/gguf-hash/gguf-hash.cpp
+++ b/examples/gguf-hash/gguf-hash.cpp
@@ -347,7 +347,7 @@ static hash_exit_code_t gguf_hash(const hash_params & hash_params) {
                 char hex_result[17];
                 for (int  offset = 0; offset < 8; offset++) {
                     unsigned int shift_bits_by = (8 * (8 - offset - 1));
-                    sprintf( ( hex_result + (2*offset)), "%02x", (unsigned char) (hash >> shift_bits_by)&0xff);
+                    snprintf( ( hex_result + (2*offset)), sizeof(hex_result) - (2*offset), "%02x", (unsigned char) (hash >> shift_bits_by)&0xff);
                 }
 
                 if (hash_params.manifest_is_usable) {
@@ -384,7 +384,7 @@ static hash_exit_code_t gguf_hash(const hash_params & hash_params) {
 
                 char hex_result[41] = {0};
                 for (int  offset = 0; offset < 20; offset++) {
-                    sprintf( ( hex_result + (2*offset)), "%02x", result[offset]&0xff);
+                    snprintf( ( hex_result + (2*offset)), sizeof(hex_result) - (2*offset), "%02x", result[offset]&0xff);
                 }
 
                 if (hash_params.manifest_is_usable) {
@@ -421,7 +421,7 @@ static hash_exit_code_t gguf_hash(const hash_params & hash_params) {
 
                 char hex_result[SHA256_DIGEST_SIZE * 2 + 1] = {0};
                 for (int  offset = 0; offset < SHA256_DIGEST_SIZE; offset++) {
-                    sprintf( ( hex_result + (2*offset)), "%02x", result[offset]&0xff);
+                    snprintf( ( hex_result + (2*offset)), sizeof(hex_result) - (2*offset), "%02x", result[offset]&0xff);
                 }
 
                 if (hash_params.manifest_is_usable) {
@@ -460,7 +460,7 @@ static hash_exit_code_t gguf_hash(const hash_params & hash_params) {
         char hex_result[17];
         for (int  offset = 0; offset < 8; offset++) {
             unsigned int shift_bits_by = (8 * (8 - offset - 1));
-            sprintf( ( hex_result + (2*offset)), "%02x", (unsigned char) (hash >> shift_bits_by)&0xff);
+            snprintf( ( hex_result + (2*offset)), sizeof(hex_result) - (2*offset), "%02x", (unsigned char) (hash >> shift_bits_by)&0xff);
         }
 
         if (hash_params.manifest_is_usable) {
@@ -490,7 +490,7 @@ static hash_exit_code_t gguf_hash(const hash_params & hash_params) {
 
         char hex_result[41];
         for (int  offset = 0; offset < 20; offset++) {
-            sprintf( ( hex_result + (2*offset)), "%02x", result[offset]&0xff);
+            snprintf( ( hex_result + (2*offset)), sizeof(hex_result) - (2*offset), "%02x", result[offset]&0xff);
         }
 
         if (hash_params.manifest_is_usable) {
@@ -520,7 +520,7 @@ static hash_exit_code_t gguf_hash(const hash_params & hash_params) {
 
         char hex_result[SHA256_DIGEST_SIZE * 2 + 1] = {0};
         for (int  offset = 0; offset < SHA256_DIGEST_SIZE; offset++) {
-            sprintf( ( hex_result + (2*offset)), "%02x", result[offset]&0xff);
+            snprintf( ( hex_result + (2*offset)), sizeof(hex_result) - (2*offset), "%02x", result[offset]&0xff);
         }
 
         if (hash_params.manifest_is_usable) {
@@ -552,7 +552,7 @@ static hash_exit_code_t gguf_hash(const hash_params & hash_params) {
         generate_uuidv5(result, uuid);
 
         char string_buffer[37] = {0};
-        sprintf(string_buffer, "%02x%02x%02x%02x-%02x%02x-%02x%02x-%02x%02x-%02x%02x%02x%02x%02x%02x",
+        snprintf(string_buffer, sizeof(string_buffer), "%02x%02x%02x%02x-%02x%02x-%02x%02x-%02x%02x-%02x%02x%02x%02x%02x%02x",
             uuid[0], uuid[1], uuid[2], uuid[3],
             uuid[4], uuid[5], uuid[6], uuid[7],
             uuid[8], uuid[9], uuid[10], uuid[11],

From 5aefbce27a66473d4b1263ba3f7bdd3d14245975 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Ji=C5=99=C3=AD=20Podiv=C3=ADn?=
 <66251151+jpodivin@users.noreply.github.com>
Date: Fri, 12 Jul 2024 10:06:33 +0200
Subject: [PATCH 170/326] convert : remove fsep token from GPTRefactForCausalLM
 (#8237)

The  token used by Refact doesn't serve
the same purpose as the  from CodeGemma.

Signed-off-by: Jiri Podivin 
---
 convert_hf_to_gguf.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py
index ebb5ca376133b..cf930be17a6e0 100755
--- a/convert_hf_to_gguf.py
+++ b/convert_hf_to_gguf.py
@@ -1203,11 +1203,10 @@ def set_vocab(self):
 
         # TODO: how to determine special FIM tokens automatically?
         special_vocab = gguf.SpecialVocab(self.dir_model, load_merges=False,
-                                          special_token_types = ['prefix', 'suffix', 'middle', 'fsep', 'eot'])
+                                          special_token_types = ['prefix', 'suffix', 'middle', 'eot'])
         special_vocab._set_special_token("prefix", 1)
         special_vocab._set_special_token("suffix", 3)
         special_vocab._set_special_token("middle", 2)
-        special_vocab._set_special_token("fsep",   4) # is this correct?
         special_vocab.add_to_gguf(self.gguf_writer)
 
     def set_gguf_parameters(self):

From 8a4441ea1a2564578134404f31158c318e9c0bf3 Mon Sep 17 00:00:00 2001
From: Armen Kaleshian 
Date: Fri, 12 Jul 2024 04:08:19 -0400
Subject: [PATCH 171/326] docker : fix filename for convert-hf-to-gguf.py in
 tools.sh (#8441)

Commit b0a4699 changed the name of this script from convert-hf-to-gguf.py to
convert_hf_to_gguf.py breaking how convert is called from within a Docker
container.
---
 .devops/tools.sh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.devops/tools.sh b/.devops/tools.sh
index 335382f69ee1f..cf0e8f32d738c 100755
--- a/.devops/tools.sh
+++ b/.devops/tools.sh
@@ -8,7 +8,7 @@ arg1="$1"
 shift
 
 if [[ "$arg1" == '--convert' || "$arg1" == '-c' ]]; then
-    python3 ./convert-hf-to-gguf.py "$@"
+    python3 ./convert_hf_to_gguf.py "$@"
 elif [[ "$arg1" == '--quantize' || "$arg1" == '-q' ]]; then
     ./llama-quantize "$@"
 elif [[ "$arg1" == '--run' || "$arg1" == '-r' ]]; then

From c3ebcfa148e867a68e78fd5c4f0c23e8f84c788b Mon Sep 17 00:00:00 2001
From: Douglas Hanley 
Date: Fri, 12 Jul 2024 03:14:12 -0500
Subject: [PATCH 172/326] server : ensure batches are either all embed or all
 completion (#8420)

* make sure batches are all embed or all non-embed

* non-embedding batch for sampled tokens; fix unused params warning
---
 examples/server/server.cpp | 38 ++++++++++++++++++++++++++++++++------
 1 file changed, 32 insertions(+), 6 deletions(-)

diff --git a/examples/server/server.cpp b/examples/server/server.cpp
index efd426289a54c..badeb9121324f 100644
--- a/examples/server/server.cpp
+++ b/examples/server/server.cpp
@@ -2005,6 +2005,11 @@ struct server_context {
         int32_t n_batch  = llama_n_batch(ctx);
         int32_t n_ubatch = llama_n_ubatch(ctx);
 
+        // track if this is an embedding or non-embedding batch
+        // if we've added sampled tokens above, we are in non-embedding mode
+        // -1: none, 0: non-embedding, 1: embedding
+        int32_t batch_type = batch.n_tokens > 0 ? 0 : -1;
+
         // next, batch any pending prompts without exceeding n_batch
         if (params.cont_batching || batch.n_tokens == 0) {
             for (auto & slot : slots) {
@@ -2175,6 +2180,14 @@ struct server_context {
                         }
                     }
 
+                    // check that we are in the right batch_type, if not defer the slot
+                    bool slot_type = slot.embedding ? 1 : 0;
+                    if (batch_type == -1) {
+                        batch_type = slot_type;
+                    } else if (batch_type != slot_type) {
+                        continue;
+                    }
+
                     // keep only the common part
                     int p0 = (int) system_tokens.size() + slot.n_past;
                     if (!llama_kv_cache_seq_rm(ctx, slot.id + 1, p0, -1)) {
@@ -2276,6 +2289,9 @@ struct server_context {
             {"n_tokens", batch.n_tokens},
         });
 
+        // make sure we're in the right embedding mode
+        llama_set_embeddings(ctx, batch_type == 1);
+
         // process the created batch of tokens
         for (int32_t i = 0; i < batch.n_tokens; i += n_batch) {
             const int32_t n_tokens = std::min(n_batch, batch.n_tokens - i);
@@ -2990,6 +3006,11 @@ int main(int argc, char ** argv) {
     };
 
     const auto handle_completions = [&ctx_server, &res_error](const httplib::Request & req, httplib::Response & res) {
+        if (ctx_server.params.embedding) {
+            res_error(res, format_error_response("This server does not support completions. Start it without `--embeddings`", ERROR_TYPE_NOT_SUPPORTED));
+            return;
+        }
+
         res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
 
         json data = json::parse(req.body);
@@ -3085,6 +3106,11 @@ int main(int argc, char ** argv) {
     };
 
     const auto handle_chat_completions = [&ctx_server, ¶ms, &res_error](const httplib::Request & req, httplib::Response & res) {
+        if (ctx_server.params.embedding) {
+            res_error(res, format_error_response("This server does not support chat completions. Start it without `--embeddings`", ERROR_TYPE_NOT_SUPPORTED));
+            return;
+        }
+
         res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
         json data = oaicompat_completion_params_parse(ctx_server.model, json::parse(req.body), params.chat_template);
 
@@ -3157,6 +3183,11 @@ int main(int argc, char ** argv) {
     };
 
     const auto handle_infill = [&ctx_server, &res_error](const httplib::Request & req, httplib::Response & res) {
+        if (ctx_server.params.embedding) {
+            res_error(res, format_error_response("This server does not support infill. Start it without `--embeddings`", ERROR_TYPE_NOT_SUPPORTED));
+            return;
+        }
+
         res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
 
         json data = json::parse(req.body);
@@ -3243,13 +3274,8 @@ int main(int argc, char ** argv) {
         return res.set_content(data.dump(), "application/json; charset=utf-8");
     };
 
-    const auto handle_embeddings = [¶ms, &ctx_server, &res_error](const httplib::Request & req, httplib::Response & res) {
+    const auto handle_embeddings = [&ctx_server, &res_error](const httplib::Request & req, httplib::Response & res) {
         res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
-        if (!params.embedding) {
-            res.status = 501;
-            res.set_content("This server does not support embeddings. Start it with `--embeddings`", "text/plain; charset=utf-8");
-            return;
-        }
 
         const json body = json::parse(req.body);
         bool is_openai = false;

From f53226245f421bd01b47cce43a47e791de82c636 Mon Sep 17 00:00:00 2001
From: Daniel Bevenius 
Date: Fri, 12 Jul 2024 11:05:21 +0200
Subject: [PATCH 173/326] llama : suppress unary minus operator warning (#8448)

This commit updates the _try_copy lambda and moves the unary minus
operator to after the cast to int32_t.

The motivation for this that currently the following warning is
generated on windows:

```console
llama.cpp\src\llama.cpp(21147,30): warning C4146: unary minus operator
applied to unsigned type, result still unsigned
```
---
 src/llama.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/llama.cpp b/src/llama.cpp
index f91ac777969d9..59b76a6d80cdf 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -21144,7 +21144,7 @@ int32_t llama_token_to_piece(const struct llama_model * model, llama_token token
             size--;
         }
         if (length < (int32_t)size) {
-            return (int32_t) -size;
+            return -(int32_t) size;
         }
         memcpy(buf, token, size);
         return (int32_t) size;

From 6af51c0d96e6268769fc05c98d5b1a5e832c0017 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Fri, 12 Jul 2024 14:48:04 +0300
Subject: [PATCH 174/326] main : print error on empty input (#8456)

---
 examples/main/main.cpp | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/examples/main/main.cpp b/examples/main/main.cpp
index 4ef55c1e6b3cf..a0d817b1a89d1 100644
--- a/examples/main/main.cpp
+++ b/examples/main/main.cpp
@@ -289,8 +289,13 @@ int main(int argc, char ** argv) {
 
     // Should not run without any tokens
     if (embd_inp.empty()) {
-        embd_inp.push_back(llama_token_bos(model));
-        LOG("embd_inp was considered empty and bos was added: %s\n", LOG_TOKENS_TOSTR_PRETTY(ctx, embd_inp).c_str());
+        if (add_bos) {
+            embd_inp.push_back(llama_token_bos(model));
+            LOG("embd_inp was considered empty and bos was added: %s\n", LOG_TOKENS_TOSTR_PRETTY(ctx, embd_inp).c_str());
+        } else {
+            LOG_TEE("error: input is empty\n");
+            return -1;
+        }
     }
 
     // Tokenize negative prompt

From 4e24cffd8cccd653634e24ee461c252bd77b1426 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Fri, 12 Jul 2024 14:48:15 +0300
Subject: [PATCH 175/326] server : handle content array in chat API (#8449)

* server : handle content array in chat API

* Update examples/server/utils.hpp

Co-authored-by: Xuan Son Nguyen 

---------

Co-authored-by: Xuan Son Nguyen 
---
 examples/server/utils.hpp | 22 ++++++++++++++++++++--
 1 file changed, 20 insertions(+), 2 deletions(-)

diff --git a/examples/server/utils.hpp b/examples/server/utils.hpp
index 7ef2a519a10c7..db6b3b74d1dd2 100644
--- a/examples/server/utils.hpp
+++ b/examples/server/utils.hpp
@@ -122,8 +122,26 @@ inline std::string format_chat(const struct llama_model * model, const std::stri
 
     for (size_t i = 0; i < messages.size(); ++i) {
         const auto & curr_msg = messages[i];
-        std::string role    = json_value(curr_msg, "role",    std::string(""));
-        std::string content = json_value(curr_msg, "content", std::string(""));
+
+        std::string role = json_value(curr_msg, "role", std::string(""));
+
+        std::string content;
+        if (curr_msg.contains("content")) {
+            if (curr_msg["content"].is_string()) {
+                content = curr_msg["content"].get();
+            } else if (curr_msg["content"].is_array()) {
+                for (const auto & part : curr_msg["content"]) {
+                    if (part.contains("text")) {
+                        content += "\n" + part["text"].get();
+                    }
+                }
+            } else {
+                throw std::runtime_error("Invalid 'content' type (ref: https://github.com/ggerganov/llama.cpp/issues/8367)");
+            }
+        } else {
+            throw std::runtime_error("Missing 'content' (ref: https://github.com/ggerganov/llama.cpp/issues/8367)");
+        }
+
         chat.push_back({role, content});
     }
 

From c917b67f06c42d8ca8391b9bc73f5fe62c83bf70 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Sat, 13 Jul 2024 18:32:33 +0300
Subject: [PATCH 176/326] metal : template-ify some of the kernels (#8447)

ggml-ci
---
 ggml/src/ggml-metal.m     |  28 +-
 ggml/src/ggml-metal.metal | 729 ++++++++++----------------------------
 2 files changed, 193 insertions(+), 564 deletions(-)

diff --git a/ggml/src/ggml-metal.m b/ggml/src/ggml-metal.m
index 79902c9a80616..b5939efa6c279 100644
--- a/ggml/src/ggml-metal.m
+++ b/ggml/src/ggml-metal.m
@@ -193,16 +193,16 @@
   //GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_F16_H256,     // https://github.com/ggerganov/llama.cpp/issues/7261
     GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_VEC_F16_H128,
   //GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_VEC_F16_H256, // https://github.com/ggerganov/llama.cpp/issues/7261
-    GGML_METAL_KERNEL_TYPE_CPY_F32_F16,
     GGML_METAL_KERNEL_TYPE_CPY_F32_F32,
+    GGML_METAL_KERNEL_TYPE_CPY_F32_F16,
+    GGML_METAL_KERNEL_TYPE_CPY_F16_F16,
+    GGML_METAL_KERNEL_TYPE_CPY_F16_F32,
     GGML_METAL_KERNEL_TYPE_CPY_F32_Q8_0,
     GGML_METAL_KERNEL_TYPE_CPY_F32_Q4_0,
     GGML_METAL_KERNEL_TYPE_CPY_F32_Q4_1,
     GGML_METAL_KERNEL_TYPE_CPY_F32_Q5_0,
     GGML_METAL_KERNEL_TYPE_CPY_F32_Q5_1,
     GGML_METAL_KERNEL_TYPE_CPY_F32_IQ4_NL,
-    GGML_METAL_KERNEL_TYPE_CPY_F16_F16,
-    GGML_METAL_KERNEL_TYPE_CPY_F16_F32,
     GGML_METAL_KERNEL_TYPE_CONCAT,
     GGML_METAL_KERNEL_TYPE_SQR,
     GGML_METAL_KERNEL_TYPE_SUM_ROWS,
@@ -651,14 +651,14 @@ static void ggml_metal_log(enum ggml_log_level level, const char * format, ...){
       //GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_VEC_F16_H256,   flash_attn_ext_vec_f16_h256,    ctx->support_simdgroup_reduction);
         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_F16,                   cpy_f32_f16,                    true);
         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_F32,                   cpy_f32_f32,                    true);
+        GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F16_F16,                   cpy_f16_f16,                    true);
+        GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F16_F32,                   cpy_f16_f32,                    true);
         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_Q8_0,                  cpy_f32_q8_0,                   true);
         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_Q4_0,                  cpy_f32_q4_0,                   true);
         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_Q4_1,                  cpy_f32_q4_1,                   true);
         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_Q5_0,                  cpy_f32_q5_0,                   true);
         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_Q5_1,                  cpy_f32_q5_1,                   true);
         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_IQ4_NL,                cpy_f32_iq4_nl,                 true);
-        GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F16_F16,                   cpy_f16_f16,                    true);
-        GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F16_F32,                   cpy_f16_f32,                    true);
         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CONCAT,                        concat,                         true);
         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SQR,                           sqr,                            true);
         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SUM_ROWS,                      sum_rows,                       true);
@@ -810,8 +810,8 @@ static bool ggml_metal_supports_op(const struct ggml_metal_context * ctx, const
                 switch (op->src[0]->type) {
                     case GGML_TYPE_F32:
                         switch (op->type) {
-                           case GGML_TYPE_F16:
                            case GGML_TYPE_F32:
+                           case GGML_TYPE_F16:
                            case GGML_TYPE_Q8_0:
                            case GGML_TYPE_Q4_0:
                            case GGML_TYPE_Q4_1:
@@ -824,8 +824,8 @@ static bool ggml_metal_supports_op(const struct ggml_metal_context * ctx, const
                         }
                     case GGML_TYPE_F16:
                         switch (op->type) {
-                           case GGML_TYPE_F16:
                            case GGML_TYPE_F32:
+                           case GGML_TYPE_F16:
                                 return true;
                            default:
                                 return false;
@@ -837,7 +837,7 @@ static bool ggml_metal_supports_op(const struct ggml_metal_context * ctx, const
         case GGML_OP_DIAG_MASK_INF:
         case GGML_OP_GET_ROWS:
             {
-                return op->src[0]->type != GGML_TYPE_BF16 && op->ne[3] == 1;
+                return op->ne[3] == 1;
             }
         default:
             return false;
@@ -1580,8 +1580,8 @@ static enum ggml_status ggml_metal_graph_compute(
                             // some Metal matrix data types require aligned pointers
                             // ref: https://developer.apple.com/metal/Metal-Shading-Language-Specification.pdf (Table 2.5)
                             switch (src0->type) {
-                                case GGML_TYPE_F32: GGML_ASSERT(nb01 % 16 == 0); break;
-                                case GGML_TYPE_F16: GGML_ASSERT(nb01 % 8  == 0); break;
+                                case GGML_TYPE_F32:  GGML_ASSERT(nb01 % 16 == 0); break;
+                                case GGML_TYPE_F16:  GGML_ASSERT(nb01 % 8  == 0); break;
                                 default: break;
                             }
 
@@ -2775,8 +2775,8 @@ static enum ggml_status ggml_metal_graph_compute(
                                     GGML_ASSERT(ne0 % ggml_blck_size(dst->type) == 0);
 
                                     switch (dstt) {
-                                        case GGML_TYPE_F16:    pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_F16].pipeline;  break;
-                                        case GGML_TYPE_F32:    pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_F32].pipeline;  break;
+                                        case GGML_TYPE_F32:    pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_F32].pipeline; break;
+                                        case GGML_TYPE_F16:    pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_F16].pipeline; break;
                                         case GGML_TYPE_Q8_0:   pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_Q8_0].pipeline; break;
                                         case GGML_TYPE_Q4_0:   pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_Q4_0].pipeline; break;
                                         case GGML_TYPE_Q4_1:   pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_Q4_1].pipeline; break;
@@ -2789,8 +2789,8 @@ static enum ggml_status ggml_metal_graph_compute(
                             case GGML_TYPE_F16:
                                 {
                                     switch (dstt) {
-                                        case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F16_F16].pipeline; break;
-                                        case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F16_F32].pipeline; break;
+                                        case GGML_TYPE_F32:  pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F16_F32].pipeline; break;
+                                        case GGML_TYPE_F16:  pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F16_F16].pipeline; break;
                                         default: GGML_ASSERT(false && "not implemented");
                                     };
                                 } break;
diff --git a/ggml/src/ggml-metal.metal b/ggml/src/ggml-metal.metal
index c3503479b35ba..2a3b0c0a69a74 100644
--- a/ggml/src/ggml-metal.metal
+++ b/ggml/src/ggml-metal.metal
@@ -1219,9 +1219,10 @@ kernel void kernel_mul_mv_q8_0_f32(
     kernel_mul_mv_q8_0_f32_impl(src0,src1,dst,ne00,ne01,ne02,ne10,ne12,ne0,ne1,r2,r3,nullptr,tgpig,tiisg,sgitg);
 }
 
-#define N_F32_F32 4
+#define N_MV_T_T 4
 
-void kernel_mul_mv_f32_f32_impl(
+template
+void kernel_mul_mv_impl(
         device const  char * src0,
         device const  char * src1,
         device       float * dst,
@@ -1239,13 +1240,12 @@ void kernel_mul_mv_f32_f32_impl(
                   uint64_t   nb12,
                    int64_t   ne0,
                    int64_t   ne1,
-                     uint    r2,
-                     uint    r3,
-                     uint3   tgpig,
-                     uint    tiisg) {
-
+                   uint      r2,
+                   uint      r3,
+                   uint3     tgpig,
+                   uint      tiisg) {
     const int64_t r0 = tgpig.x;
-    const int64_t rb = tgpig.y*N_F32_F32;
+    const int64_t rb = tgpig.y*N_MV_T_T;
     const int64_t im = tgpig.z;
 
     const uint i12 = im%ne12;
@@ -1253,20 +1253,20 @@ void kernel_mul_mv_f32_f32_impl(
 
     const uint offset0 = r0*nb01 + (i12/r2)*nb02 + (i13/r3)*nb02*ne02;
 
-    device const float * x = (device const float *) (src0 + offset0);
+    device const T0 * x = (device const T0 *) (src0 + offset0);
 
     if (ne00 < 128) {
-        for (int row = 0; row < N_F32_F32; ++row) {
+        for (int row = 0; row < N_MV_T_T; ++row) {
             int r1 = rb + row;
             if (r1 >= ne11) {
                 break;
             }
 
-            device const float * y = (device const float *) (src1 + r1*nb11 + im*nb12);
+            device const T1 * y = (device const T1 *) (src1 + r1*nb11 + im*nb12);
 
             float sumf = 0;
             for (int i = tiisg; i < ne00; i += 32) {
-                sumf += (float) x[i] * (float) y[i];
+                sumf += (T0) x[i] * (T1) y[i];
             }
 
             float all_sum = simd_sum(sumf);
@@ -1275,32 +1275,32 @@ void kernel_mul_mv_f32_f32_impl(
             }
         }
     } else {
-        device const float4 * x4 = (device const float4 *)x;
-        for (int row = 0; row < N_F32_F32; ++row) {
+        device const T04 * x4 = (device const T04 *) x;
+        for (int row = 0; row < N_MV_T_T; ++row) {
             int r1 = rb + row;
             if (r1 >= ne11) {
                 break;
             }
 
-            device const float  * y  = (device const float  *) (src1 + r1*nb11 + im*nb12);
-            device const float4 * y4 = (device const float4 *) y;
+            device const T1  * y  = (device const T1  *) (src1 + r1*nb11 + im*nb12);
+            device const T14 * y4 = (device const T14 *) y;
 
             float sumf = 0;
             for (int i = tiisg; i < ne00/4; i += 32) {
-                for (int k = 0; k < 4; ++k) sumf += (float) x4[i][k] * y4[i][k];
+                for (int k = 0; k < 4; ++k) sumf += (float) (x4[i][k] * y4[i][k]);
             }
 
             float all_sum = simd_sum(sumf);
             if (tiisg == 0) {
-                for (int i = 4*(ne00/4); i < ne00; ++i) all_sum += (float) x[i] * y[i];
+                for (int i = 4*(ne00/4); i < ne00; ++i) all_sum += (float) (x[i] * y[i]);
                 dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum;
             }
         }
     }
 }
 
-[[host_name("kernel_mul_mv_f32_f32")]]
-kernel void kernel_mul_mv_f32_f32(
+template
+kernel void kernel_mul_mv(
         device const  char * src0,
         device const  char * src1,
         device       float * dst,
@@ -1322,90 +1322,38 @@ kernel void kernel_mul_mv_f32_f32(
         constant   uint    & r3,
         uint3 tgpig[[threadgroup_position_in_grid]],
         uint  tiisg[[thread_index_in_simdgroup]]) {
-    kernel_mul_mv_f32_f32_impl(src0, src1, dst, ne00, ne01, ne02, nb00, nb01, nb02, ne10, ne11, ne12, nb10, nb11, nb12, ne0, ne1, r2, r3, tgpig, tiisg);
+    kernel_mul_mv_impl(
+        src0,
+        src1,
+        dst,
+        ne00,
+        ne01,
+        ne02,
+        nb00,
+        nb01,
+        nb02,
+        ne10,
+        ne11,
+        ne12,
+        nb10,
+        nb11,
+        nb12,
+        ne0,
+        ne1,
+        r2,
+        r3,
+        tgpig,
+        tiisg);
 }
 
-#define N_F16_F16 4
+typedef decltype(kernel_mul_mv) mul_mv_t;
 
-kernel void kernel_mul_mv_f16_f16(
-        device const  char * src0,
-        device const  char * src1,
-        device       float * dst,
-        constant   int64_t & ne00,
-        constant   int64_t & ne01,
-        constant   int64_t & ne02,
-        constant  uint64_t & nb00,
-        constant  uint64_t & nb01,
-        constant  uint64_t & nb02,
-        constant   int64_t & ne10,
-        constant   int64_t & ne11,
-        constant   int64_t & ne12,
-        constant  uint64_t & nb10,
-        constant  uint64_t & nb11,
-        constant  uint64_t & nb12,
-        constant   int64_t & ne0,
-        constant   int64_t & ne1,
-        constant   uint    & r2,
-        constant   uint    & r3,
-        uint3 tgpig[[threadgroup_position_in_grid]],
-        uint  tiisg[[thread_index_in_simdgroup]]) {
+template [[host_name("kernel_mul_mv_f32_f32")]]   kernel mul_mv_t kernel_mul_mv;
+template [[host_name("kernel_mul_mv_f16_f32")]]   kernel mul_mv_t kernel_mul_mv;
+template [[host_name("kernel_mul_mv_f16_f16")]]   kernel mul_mv_t kernel_mul_mv;
 
-    const int64_t r0 = tgpig.x;
-    const int64_t rb = tgpig.y*N_F16_F16;
-    const int64_t im = tgpig.z;
-
-    const uint i12 = im%ne12;
-    const uint i13 = im/ne12;
-
-    const uint offset0 = r0*nb01 + (i12/r2)*nb02 + (i13/r3)*nb02*ne02;
-
-    device const half * x = (device const half *) (src0 + offset0);
-
-    if (ne00 < 128) {
-        for (int row = 0; row < N_F16_F16; ++row) {
-            int r1 = rb + row;
-            if (r1 >= ne11) {
-                break;
-            }
-
-            device const half * y = (device const half *) (src1 + r1*nb11 + im*nb12);
-
-            float sumf = 0;
-            for (int i = tiisg; i < ne00; i += 32) {
-                sumf += (half) x[i] * (half) y[i];
-            }
-
-            float all_sum = simd_sum(sumf);
-            if (tiisg == 0) {
-                dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum;
-            }
-        }
-    } else {
-        device const half4 * x4 = (device const half4 *)x;
-        for (int row = 0; row < N_F16_F16; ++row) {
-            int r1 = rb + row;
-            if (r1 >= ne11) {
-                break;
-            }
-
-            device const half  * y  = (device const half  *) (src1 + r1*nb11 + im*nb12);
-            device const half4 * y4 = (device const half4 *) y;
-
-            float sumf = 0;
-            for (int i = tiisg; i < ne00/4; i += 32) {
-                for (int k = 0; k < 4; ++k) sumf += (half) x4[i][k] * y4[i][k];
-            }
-
-            float all_sum = simd_sum(sumf);
-            if (tiisg == 0) {
-                for (int i = 4*(ne00/4); i < ne00; ++i) all_sum += (half) x[i] * y[i];
-                dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum;
-            }
-        }
-    }
-}
-
-void kernel_mul_mv_f16_f32_1row_impl(
+template
+kernel void kernel_mul_mv_1row(
         device const  char * src0,
         device const  char * src1,
         device       float * dst,
@@ -1437,7 +1385,7 @@ void kernel_mul_mv_f16_f32_1row_impl(
 
     const uint offset0 = r0*nb01 + (i12/r2)*nb02 + (i13/r3)*nb02*ne02;
 
-    device const half  * x = (device const half  *) (src0 + offset0);
+    device const T     * x = (device const T     *) (src0 + offset0);
     device const float * y = (device const float *) (src1 + r1*nb11 + im*nb12);
 
     float sumf = 0;
@@ -1450,153 +1398,29 @@ void kernel_mul_mv_f16_f32_1row_impl(
             dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum;
         }
     } else {
-        device const half4  * x4 = (device const half4  *) x;
+        device const T4     * x4 = (device const T4     *) x;
         device const float4 * y4 = (device const float4 *) y;
+
         for (int i = tiisg; i < ne00/4; i += 32) {
-            for (int k = 0; k < 4; ++k) sumf += (float)x4[i][k] * y4[i][k];
+            for (int k = 0; k < 4; ++k) sumf += (float) (x4[i][k] * y4[i][k]);
         }
+
         float all_sum = simd_sum(sumf);
+
         if (tiisg == 0) {
-            for (int i = 4*(ne00/4); i < ne00; ++i) all_sum += (float) x[i] * y[i];
+            for (int i = 4*(ne00/4); i < ne00; ++i) all_sum += (float) (x[i] * y[i]);
             dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum;
         }
     }
 }
 
-[[host_name("kernel_mul_mv_f16_f32_1row")]]
-kernel void kernel_mul_mv_f16_f32_1row(
-        device const  char * src0,
-        device const  char * src1,
-        device       float * dst,
-        constant   int64_t & ne00,
-        constant   int64_t & ne01,
-        constant   int64_t & ne02,
-        constant  uint64_t & nb00,
-        constant  uint64_t & nb01,
-        constant  uint64_t & nb02,
-        constant   int64_t & ne10,
-        constant   int64_t & ne11,
-        constant   int64_t & ne12,
-        constant  uint64_t & nb10,
-        constant  uint64_t & nb11,
-        constant  uint64_t & nb12,
-        constant   int64_t & ne0,
-        constant   int64_t & ne1,
-        constant   uint    & r2,
-        constant   uint    & r3,
-        uint3 tgpig[[threadgroup_position_in_grid]],
-        uint  tiisg[[thread_index_in_simdgroup]]) {
-    kernel_mul_mv_f16_f32_1row_impl(src0, src1, dst, ne00, ne01, ne02, nb00, nb01, nb02, ne10, ne11, ne12, nb10, nb11, nb12, ne0, ne1, r2, r3, tgpig, tiisg);
-}
-
-#define N_F16_F32 4
-
-void kernel_mul_mv_f16_f32_impl(
-        device const  char * src0,
-        device const  char * src1,
-        device       float * dst,
-                   int64_t   ne00,
-                   int64_t   ne01,
-                   int64_t   ne02,
-                  uint64_t   nb00,
-                  uint64_t   nb01,
-                  uint64_t   nb02,
-                   int64_t   ne10,
-                   int64_t   ne11,
-                   int64_t   ne12,
-                  uint64_t   nb10,
-                  uint64_t   nb11,
-                  uint64_t   nb12,
-                   int64_t   ne0,
-                   int64_t   ne1,
-                   uint      r2,
-                   uint      r3,
-                   uint3     tgpig,
-                   uint      tiisg) {
-
-    const int64_t r0 = tgpig.x;
-    const int64_t rb = tgpig.y*N_F16_F32;
-    const int64_t im = tgpig.z;
-
-    const uint i12 = im%ne12;
-    const uint i13 = im/ne12;
-
-    const uint offset0 = r0*nb01 + (i12/r2)*nb02 + (i13/r3)*nb02*ne02;
-
-    device const half * x = (device const half *) (src0 + offset0);
-
-    if (ne00 < 128) {
-        for (int row = 0; row < N_F16_F32; ++row) {
-            int r1 = rb + row;
-            if (r1 >= ne11) {
-                break;
-            }
-
-            device const float * y = (device const float *) (src1 + r1*nb11 + im*nb12);
-
-            float sumf = 0;
-            for (int i = tiisg; i < ne00; i += 32) {
-                sumf += (float) x[i] * (float) y[i];
-            }
-
-            float all_sum = simd_sum(sumf);
-            if (tiisg == 0) {
-                dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum;
-            }
-        }
-    } else {
-        device const half4 * x4 = (device const half4 *)x;
-        for (int row = 0; row < N_F16_F32; ++row) {
-            int r1 = rb + row;
-            if (r1 >= ne11) {
-                break;
-            }
-
-            device const float  * y  = (device const float  *) (src1 + r1*nb11 + im*nb12);
-            device const float4 * y4 = (device const float4 *) y;
-
-            float sumf = 0;
-            for (int i = tiisg; i < ne00/4; i += 32) {
-                for (int k = 0; k < 4; ++k) sumf += (float) x4[i][k] * y4[i][k];
-            }
+typedef decltype(kernel_mul_mv_1row) mul_mv_1row_t;
 
-            float all_sum = simd_sum(sumf);
-            if (tiisg == 0) {
-                for (int i = 4*(ne00/4); i < ne00; ++i) all_sum += (float) x[i] * y[i];
-                dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum;
-            }
-        }
-    }
-}
-
-[[host_name("kernel_mul_mv_f16_f32")]]
-kernel void kernel_mul_mv_f16_f32(
-        device const  char * src0,
-        device const  char * src1,
-        device       float * dst,
-        constant   int64_t & ne00,
-        constant   int64_t & ne01,
-        constant   int64_t & ne02,
-        constant  uint64_t & nb00,
-        constant  uint64_t & nb01,
-        constant  uint64_t & nb02,
-        constant   int64_t & ne10,
-        constant   int64_t & ne11,
-        constant   int64_t & ne12,
-        constant  uint64_t & nb10,
-        constant  uint64_t & nb11,
-        constant  uint64_t & nb12,
-        constant   int64_t & ne0,
-        constant   int64_t & ne1,
-        constant   uint    & r2,
-        constant   uint    & r3,
-        uint3 tgpig[[threadgroup_position_in_grid]],
-        uint tiisg[[thread_index_in_simdgroup]]) {
-    kernel_mul_mv_f16_f32_impl(src0, src1, dst, ne00, ne01, ne02, nb00, nb01, nb02, ne10, ne11, ne12, nb10, nb11, nb12, ne0, ne1, r2, r3, tgpig, tiisg);
-}
+template [[host_name("kernel_mul_mv_f16_f32_1row")]]  kernel mul_mv_1row_t kernel_mul_mv_1row;
 
 // Assumes row size (ne00) is a multiple of 4
-kernel void kernel_mul_mv_f16_f32_l4(
+template
+kernel void kernel_mul_mv_l4(
         device const  char * src0,
         device const  char * src1,
         device       float * dst,
@@ -1628,14 +1452,14 @@ kernel void kernel_mul_mv_f16_f32_l4(
 
     const uint offset0 = r0*nb01 + (i12/r2)*nb02 + (i13/r3)*nb02*ne02;
 
-    device const half4 * x4 = (device const half4 *) (src0 + offset0);
+    device const T4 * x4 = (device const T4 *) (src0 + offset0);
 
     for (int r1 = 0; r1 < nrows; ++r1) {
         device const float4 * y4 = (device const float4 *) (src1 + r1*nb11 + im*nb12);
 
         float sumf = 0;
         for (int i = tiisg; i < ne00/4; i += 32) {
-            for (int k = 0; k < 4; ++k) sumf += (float) x4[i][k] * y4[i][k];
+            for (int k = 0; k < 4; ++k) sumf += (float) (x4[i][k] * y4[i][k]);
         }
 
         float all_sum = simd_sum(sumf);
@@ -1645,6 +1469,10 @@ kernel void kernel_mul_mv_f16_f32_l4(
     }
 }
 
+typedef decltype(kernel_mul_mv_l4) mul_mv_l4_t;
+
+template [[host_name("kernel_mul_mv_f16_f32_l4")]]  kernel mul_mv_l4_t kernel_mul_mv_l4;
+
 static float rope_yarn_ramp(const float low, const float high, const int i0) {
     const float y = (i0 / 2 - low) / max(0.001f, high - low);
     return 1.0f - min(1.0f, max(0.0f, y));
@@ -2765,91 +2593,10 @@ kernel void kernel_flash_attn_ext_vec_f16(
 template [[host_name("kernel_flash_attn_ext_vec_f16_h128")]] kernel flash_attn_ext_f16_t kernel_flash_attn_ext_vec_f16<128>;
 //template [[host_name("kernel_flash_attn_ext_vec_f16_h256")]] kernel flash_attn_ext_f16_t kernel_flash_attn_ext_vec_f16<256>;
 
-kernel void kernel_cpy_f16_f16(
-        device  const half * src0,
-        device        half * dst,
-        constant   int64_t & ne00,
-        constant   int64_t & ne01,
-        constant   int64_t & ne02,
-        constant   int64_t & ne03,
-        constant  uint64_t & nb00,
-        constant  uint64_t & nb01,
-        constant  uint64_t & nb02,
-        constant  uint64_t & nb03,
-        constant   int64_t & ne0,
-        constant   int64_t & ne1,
-        constant   int64_t & ne2,
-        constant   int64_t & ne3,
-        constant  uint64_t & nb0,
-        constant  uint64_t & nb1,
-        constant  uint64_t & nb2,
-        constant  uint64_t & nb3,
-        uint3 tgpig[[threadgroup_position_in_grid]],
-        uint3 tpitg[[thread_position_in_threadgroup]],
-        uint3   ntg[[threads_per_threadgroup]]) {
-    const int64_t i03 = tgpig[2];
-    const int64_t i02 = tgpig[1];
-    const int64_t i01 = tgpig[0];
-
-    const int64_t n = i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00;
-
-    const int64_t i3 = n / (ne2*ne1*ne0);
-    const int64_t i2 = (n - i3*ne2*ne1*ne0) / (ne1*ne0);
-    const int64_t i1 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0) / ne0;
-    const int64_t i0 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0 - i1*ne0);
-
-    device half * dst_data = (device half *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
-
-    for (int64_t i00 = tpitg.x; i00 < ne00; i00 += ntg.x) {
-        device const half * src = (device half *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00);
-        dst_data[i00] = src[0];
-    }
-}
-
-kernel void kernel_cpy_f16_f32(
-        device  const half * src0,
-        device       float * dst,
-        constant   int64_t & ne00,
-        constant   int64_t & ne01,
-        constant   int64_t & ne02,
-        constant   int64_t & ne03,
-        constant  uint64_t & nb00,
-        constant  uint64_t & nb01,
-        constant  uint64_t & nb02,
-        constant  uint64_t & nb03,
-        constant   int64_t & ne0,
-        constant   int64_t & ne1,
-        constant   int64_t & ne2,
-        constant   int64_t & ne3,
-        constant  uint64_t & nb0,
-        constant  uint64_t & nb1,
-        constant  uint64_t & nb2,
-        constant  uint64_t & nb3,
-        uint3 tgpig[[threadgroup_position_in_grid]],
-        uint3 tpitg[[thread_position_in_threadgroup]],
-        uint3   ntg[[threads_per_threadgroup]]) {
-    const int64_t i03 = tgpig[2];
-    const int64_t i02 = tgpig[1];
-    const int64_t i01 = tgpig[0];
-
-    const int64_t n = i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00;
-
-    const int64_t i3 = n / (ne2*ne1*ne0);
-    const int64_t i2 = (n - i3*ne2*ne1*ne0) / (ne1*ne0);
-    const int64_t i1 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0) / ne0;
-    const int64_t i0 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0 - i1*ne0);
-
-    device float * dst_data = (device float *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
-
-    for (int64_t i00 = tpitg.x; i00 < ne00; i00 += ntg.x) {
-        device const half * src = (device half *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00);
-        dst_data[i00] = src[0];
-    }
-}
-
-kernel void kernel_cpy_f32_f16(
-        device const float * src0,
-        device        half * dst,
+template
+kernel void kernel_cpy(
+        device  const void * src0,
+        device        void * dst,
         constant   int64_t & ne00,
         constant   int64_t & ne01,
         constant   int64_t & ne02,
@@ -2880,56 +2627,20 @@ kernel void kernel_cpy_f32_f16(
     const int64_t i1 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0) / ne0;
     const int64_t i0 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0 - i1*ne0);
 
-    device half * dst_data = (device half *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
+    device T1 * dst_data = (device T1 *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
 
     for (int64_t i00 = tpitg.x; i00 < ne00; i00 += ntg.x) {
-        device const float * src = (device float *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00);
-
-        dst_data[i00] = src[0];
+        device const T0 * src = (device T0 *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00);
+        dst_data[i00] = (T1) src[0];
     }
 }
 
-kernel void kernel_cpy_f32_f32(
-        device const float * src0,
-        device       float * dst,
-        constant   int64_t & ne00,
-        constant   int64_t & ne01,
-        constant   int64_t & ne02,
-        constant   int64_t & ne03,
-        constant  uint64_t & nb00,
-        constant  uint64_t & nb01,
-        constant  uint64_t & nb02,
-        constant  uint64_t & nb03,
-        constant   int64_t & ne0,
-        constant   int64_t & ne1,
-        constant   int64_t & ne2,
-        constant   int64_t & ne3,
-        constant  uint64_t & nb0,
-        constant  uint64_t & nb1,
-        constant  uint64_t & nb2,
-        constant  uint64_t & nb3,
-        uint3 tgpig[[threadgroup_position_in_grid]],
-        uint3 tpitg[[thread_position_in_threadgroup]],
-        uint3   ntg[[threads_per_threadgroup]]) {
-    const int64_t i03 = tgpig[2];
-    const int64_t i02 = tgpig[1];
-    const int64_t i01 = tgpig[0];
-
-    const int64_t n = i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00;
+typedef decltype(kernel_cpy) kernel_cpy_t;
 
-    const int64_t i3 = n / (ne2*ne1*ne0);
-    const int64_t i2 = (n - i3*ne2*ne1*ne0) / (ne1*ne0);
-    const int64_t i1 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0) / ne0;
-    const int64_t i0 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0 - i1*ne0);
-
-    device float * dst_data = (device float *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
-
-    for (int64_t i00 = tpitg.x; i00 < ne00; i00 += ntg.x) {
-        device const float * src = (device float *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00);
-
-        dst_data[i00] = src[0];
-    }
-}
+template [[host_name("kernel_cpy_f32_f32")]]  kernel kernel_cpy_t kernel_cpy;
+template [[host_name("kernel_cpy_f32_f16")]]  kernel kernel_cpy_t kernel_cpy;
+template [[host_name("kernel_cpy_f16_f16")]]  kernel kernel_cpy_t kernel_cpy;
+template [[host_name("kernel_cpy_f16_f32")]]  kernel kernel_cpy_t kernel_cpy;
 
 kernel void kernel_cpy_f32_q8_0(
         device const float * src0,
@@ -5730,9 +5441,9 @@ void dequantize_iq4_xs(device const block_iq4_xs * xb, short il, thread type4x4
 }
 
 template
-kernel void kernel_get_rows(
+kernel void kernel_get_rows_q(
         device const  void * src0,
-        device const  char * src1,
+        device const  void * src1,
         device       float * dst,
         constant   int64_t & ne00,
         constant  uint64_t & nb01,
@@ -5745,55 +5456,24 @@ kernel void kernel_get_rows(
         uint3                tgpig[[threadgroup_position_in_grid]],
         uint                 tiitg[[thread_index_in_threadgroup]],
         uint3                tptg [[threads_per_threadgroup]]) {
-    //const int64_t i = tgpig;
-    //const int64_t r = ((device int32_t *) src1)[i];
-
     const int64_t i10 = tgpig.x;
     const int64_t i11 = tgpig.y;
 
-    const int64_t r = ((device int32_t *) ((device char *) src1 + i11*nb11 + i10*nb10))[0];
+    const int64_t r = ((const device int32_t *) ((const device char *) src1 + i11*nb11 + i10*nb10))[0];
 
     const int64_t i02 = i11;
 
     for (int64_t ind = tiitg; ind < ne00/16; ind += tptg.x) {
         float4x4 temp;
-        dequantize_func(
-            ((device const block_q *) ((device char *) src0 + r*nb01 + i02*nb02)) + ind/nl, ind%nl, temp);
+        dequantize_func(((device const block_q *) ((const device char *) src0 + r*nb01 + i02*nb02)) + ind/nl, ind%nl, temp);
         *(((device float4x4 *) ((device char *) dst + i11*nb2 + i10*nb1)) + ind) = temp;
     }
 }
 
-kernel void kernel_get_rows_f32(
-        device const  void * src0,
-        device const  char * src1,
-        device       float * dst,
-        constant   int64_t & ne00,
-        constant  uint64_t & nb01,
-        constant  uint64_t & nb02,
-        constant   int64_t & ne10,
-        constant  uint64_t & nb10,
-        constant  uint64_t & nb11,
-        constant  uint64_t & nb1,
-        constant  uint64_t & nb2,
-        uint3                tgpig[[threadgroup_position_in_grid]],
-        uint                 tiitg[[thread_index_in_threadgroup]],
-        uint3                tptg [[threads_per_threadgroup]]) {
-    const int64_t i10 = tgpig.x;
-    const int64_t i11 = tgpig.y;
-
-    const int64_t r = ((device int32_t *) ((device char *) src1 + i11*nb11 + i10*nb10))[0];
-
-    const int64_t i02 = i11;
-
-    for (int ind = tiitg; ind < ne00; ind += tptg.x) {
-        ((device float *) ((device char *) dst + i11*nb2 + i10*nb1))[ind] =
-            ((device float *) ((device char *) src0 + r*nb01 + i02*nb02))[ind];
-    }
-}
-
-kernel void kernel_get_rows_f16(
+template
+kernel void kernel_get_rows_f(
         device const  void * src0,
-        device const  char * src1,
+        device const  void * src1,
         device       float * dst,
         constant   int64_t & ne00,
         constant  uint64_t & nb01,
@@ -5809,19 +5489,19 @@ kernel void kernel_get_rows_f16(
     const int64_t i10 = tgpig.x;
     const int64_t i11 = tgpig.y;
 
-    const int64_t r = ((device int32_t *) ((device char *) src1 + i11*nb11 + i10*nb10))[0];
+    const int64_t r = ((const device int32_t *) ((const device char *) src1 + i11*nb11 + i10*nb10))[0];
 
     const int64_t i02 = i11;
 
     for (int ind = tiitg; ind < ne00; ind += tptg.x) {
-        ((device float *) ((device char *) dst + i11*nb2 + i10*nb1))[ind] =
-            ((device half *) ((device char *) src0 + r*nb01 + i02*nb02))[ind];
+        ((      device float *) ((      device char *)  dst + i11*nb2  + i10*nb1))[ind] =
+        ((const device T     *) ((const device char *) src0 + i02*nb02 +  r*nb01))[ind];
     }
 }
 
 kernel void kernel_get_rows_i32(
         device const  void * src0,
-        device const  char * src1,
+        device const  void * src1,
         device     int32_t * dst,
         constant   int64_t & ne00,
         constant  uint64_t & nb01,
@@ -5837,13 +5517,13 @@ kernel void kernel_get_rows_i32(
     const int64_t i10 = tgpig.x;
     const int64_t i11 = tgpig.y;
 
-    const int64_t r = ((device int32_t *) ((device char *) src1 + i11*nb11 + i10*nb10))[0];
+    const int64_t r = ((const device int32_t *) ((const device char *) src1 + i11*nb11 + i10*nb10))[0];
 
     const int64_t i02 = i11;
 
     for (int ind = tiitg; ind < ne00; ind += tptg.x) {
-        ((device int32_t *) ((device char *) dst + i11*nb2 + i10*nb1))[ind] =
-            ((device int32_t *) ((device char *) src0 + r*nb01 + i02*nb02))[ind];
+        ((      device int32_t *) ((      device char *) dst  + i11*nb2 + i10*nb1))[ind] =
+        ((const device int32_t *) ((const device char *) src0 + i02*nb02 + r*nb01))[ind];
     }
 }
 
@@ -5860,28 +5540,28 @@ kernel void kernel_get_rows_i32(
 #define SG_MAT_ROW 8
 
 // each block_q contains 16*nl weights
-template
-void kernel_mul_mm_impl(device const  uchar * src0,
-                        device const  uchar * src1,
-                        device        float * dst,
-                        constant    int64_t & ne00,
-                        constant    int64_t & ne02,
-                        constant   uint64_t & nb01,
-                        constant   uint64_t & nb02,
-                        constant    int64_t & ne12,
-                        constant   uint64_t & nb10,
-                        constant   uint64_t & nb11,
-                        constant   uint64_t & nb12,
-                        constant    int64_t & ne0,
-                        constant    int64_t & ne1,
-                        constant       uint & r2,
-                        constant       uint & r3,
-                        threadgroup   uchar * shared_memory [[threadgroup(0)]],
-                        uint3                 tgpig[[threadgroup_position_in_grid]],
-                        uint                  tiitg[[thread_index_in_threadgroup]],
-                        uint                  sgitg[[simdgroup_index_in_threadgroup]]) {
+template
+kernel void kernel_mul_mm(device const  uchar * src0,
+                          device const  uchar * src1,
+                          device        float * dst,
+                          constant    int64_t & ne00,
+                          constant    int64_t & ne02,
+                          constant   uint64_t & nb01,
+                          constant   uint64_t & nb02,
+                          constant    int64_t & ne12,
+                          constant   uint64_t & nb10,
+                          constant   uint64_t & nb11,
+                          constant   uint64_t & nb12,
+                          constant    int64_t & ne0,
+                          constant    int64_t & ne1,
+                          constant       uint & r2,
+                          constant       uint & r3,
+                          threadgroup   uchar * shared_memory [[threadgroup(0)]],
+                          uint3                 tgpig[[threadgroup_position_in_grid]],
+                          uint                  tiitg[[thread_index_in_threadgroup]],
+                          uint                  sgitg[[simdgroup_index_in_threadgroup]]) {
 
-    threadgroup half  * sa = (threadgroup half  *)(shared_memory);
+    threadgroup T     * sa = (threadgroup T     *)(shared_memory);
     threadgroup float * sb = (threadgroup float *)(shared_memory + 4096);
 
     const uint r0 = tgpig.y;
@@ -5896,7 +5576,7 @@ void kernel_mul_mm_impl(device const  uchar * src0,
     short thread_row = ((short)tiitg/THREAD_PER_ROW) < n_rows ? ((short)tiitg/THREAD_PER_ROW) : n_rows - 1;
     short thread_col = ((short)tiitg/THREAD_PER_COL) < n_cols ? ((short)tiitg/THREAD_PER_COL) : n_cols - 1;
 
-    simdgroup_half8x8  ma[4];
+    simdgroup_T8x8     ma[4];
     simdgroup_float8x8 mb[2];
     simdgroup_float8x8 c_res[8];
     for (int i = 0; i < 8; i++){
@@ -5919,7 +5599,7 @@ void kernel_mul_mm_impl(device const  uchar * src0,
 
     for (int loop_k = 0; loop_k < ne00; loop_k += BLOCK_SIZE_K) {
         // load data and store to threadgroup memory
-        half4x4 temp_a;
+        T4x4 temp_a;
         dequantize_func(x, il, temp_a);
         threadgroup_barrier(mem_flags::mem_threadgroup);
 
@@ -5939,7 +5619,7 @@ void kernel_mul_mm_impl(device const  uchar * src0,
         threadgroup_barrier(mem_flags::mem_threadgroup);
 
         // load matrices from threadgroup memory and conduct outer products
-        threadgroup half  * lsma = (sa + THREAD_MAT_M * SG_MAT_SIZE * (sgitg % 2));
+        threadgroup T     * lsma = (sa + THREAD_MAT_M * SG_MAT_SIZE * (sgitg % 2));
         threadgroup float * lsmb = (sb + THREAD_MAT_N * SG_MAT_SIZE * (sgitg / 2));
 
         #pragma unroll(4)
@@ -6115,48 +5795,6 @@ void kernel_mul_mm_id_impl(
     }
 }
 
-template
-kernel void kernel_mul_mm(device const  uchar * src0,
-                          device const  uchar * src1,
-                          device        float * dst,
-                          constant    int64_t & ne00,
-                          constant    int64_t & ne02,
-                          constant   uint64_t & nb01,
-                          constant   uint64_t & nb02,
-                          constant    int64_t & ne12,
-                          constant   uint64_t & nb10,
-                          constant   uint64_t & nb11,
-                          constant   uint64_t & nb12,
-                          constant    int64_t & ne0,
-                          constant    int64_t & ne1,
-                          constant       uint & r2,
-                          constant       uint & r3,
-                          threadgroup   uchar * shared_memory [[threadgroup(0)]],
-                          uint3                 tgpig[[threadgroup_position_in_grid]],
-                          uint                  tiitg[[thread_index_in_threadgroup]],
-                          uint                  sgitg[[simdgroup_index_in_threadgroup]]) {
-    kernel_mul_mm_impl(
-        src0,
-        src1,
-        dst,
-        ne00,
-        ne02,
-        nb01,
-        nb02,
-        ne12,
-        nb10,
-        nb11,
-        nb12,
-        ne0,
-        ne1,
-        r2,
-        r3,
-        shared_memory,
-        tgpig,
-        tiitg,
-        sgitg);
-}
-
 template
 kernel void kernel_mul_mm_id(
         device const   uchar * src0s,
@@ -6237,69 +5875,60 @@ kernel void kernel_mul_mm_id(
 // get rows
 //
 
-typedef void (get_rows_t)(
-        device const void * src0,
-        device const char * src1,
-        device      float * dst,
-        constant  int64_t & ne00,
-        constant uint64_t & nb01,
-        constant uint64_t & nb02,
-        constant  int64_t & ne10,
-        constant uint64_t & nb10,
-        constant uint64_t & nb11,
-        constant uint64_t & nb1,
-        constant uint64_t & nb2,
-        uint3, uint, uint3);
-
-//template [[host_name("kernel_get_rows_f32")]]  kernel get_rows_t kernel_get_rows;
-//template [[host_name("kernel_get_rows_f16")]]  kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_q4_0")]] kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_q4_1")]] kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_q5_0")]] kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_q5_1")]] kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_q8_0")]] kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_q2_K")]] kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_q3_K")]] kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_q4_K")]] kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_q5_K")]] kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_q6_K")]] kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_iq2_xxs")]] kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_iq2_xs")]]  kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_iq3_xxs")]] kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_iq3_s")]]   kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_iq2_s")]]   kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_iq1_s")]]   kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_iq1_m")]]   kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_iq4_nl")]]  kernel get_rows_t kernel_get_rows;
-template [[host_name("kernel_get_rows_iq4_xs")]]  kernel get_rows_t kernel_get_rows;
+typedef decltype(kernel_get_rows_f) get_rows_f_t;
+
+template [[host_name("kernel_get_rows_f32")]]  kernel get_rows_f_t kernel_get_rows_f;
+template [[host_name("kernel_get_rows_f16")]]  kernel get_rows_f_t kernel_get_rows_f;
+
+typedef decltype(kernel_get_rows_q) get_rows_q_t;
+
+template [[host_name("kernel_get_rows_q4_0")]]    kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_q4_1")]]    kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_q5_0")]]    kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_q5_1")]]    kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_q8_0")]]    kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_q2_K")]]    kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_q3_K")]]    kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_q4_K")]]    kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_q5_K")]]    kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_q6_K")]]    kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_iq2_xxs")]] kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_iq2_xs")]]  kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_iq3_xxs")]] kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_iq3_s")]]   kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_iq2_s")]]   kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_iq1_s")]]   kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_iq1_m")]]   kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_iq4_nl")]]  kernel get_rows_q_t kernel_get_rows_q;
+template [[host_name("kernel_get_rows_iq4_xs")]]  kernel get_rows_q_t kernel_get_rows_q;
 
 //
 // matrix-matrix multiplication
 //
 
-typedef decltype(kernel_mul_mm) mat_mm_t;
-
-template [[host_name("kernel_mul_mm_f32_f32")]]     kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_f16_f32")]]     kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_q4_0_f32")]]    kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_q4_1_f32")]]    kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_q5_0_f32")]]    kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_q5_1_f32")]]    kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_q8_0_f32")]]    kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_q2_K_f32")]]    kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_q3_K_f32")]]    kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_q4_K_f32")]]    kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_q5_K_f32")]]    kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_q6_K_f32")]]    kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_iq2_xxs_f32")]] kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_iq2_xs_f32")]]  kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_iq3_xxs_f32")]] kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_iq3_s_f32")]]   kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_iq2_s_f32")]]   kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_iq1_s_f32")]]   kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_iq1_m_f32")]]   kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_iq4_nl_f32")]]  kernel mat_mm_t kernel_mul_mm;
-template [[host_name("kernel_mul_mm_iq4_xs_f32")]]  kernel mat_mm_t kernel_mul_mm;
+typedef decltype(kernel_mul_mm) mat_mm_t;
+
+template [[host_name("kernel_mul_mm_f32_f32")]]     kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_f16_f32")]]     kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_q4_0_f32")]]    kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_q4_1_f32")]]    kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_q5_0_f32")]]    kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_q5_1_f32")]]    kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_q8_0_f32")]]    kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_q2_K_f32")]]    kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_q3_K_f32")]]    kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_q4_K_f32")]]    kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_q5_K_f32")]]    kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_q6_K_f32")]]    kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_iq2_xxs_f32")]] kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_iq2_xs_f32")]]  kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_iq3_xxs_f32")]] kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_iq3_s_f32")]]   kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_iq2_s_f32")]]   kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_iq1_s_f32")]]   kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_iq1_m_f32")]]   kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_iq4_nl_f32")]]  kernel mat_mm_t kernel_mul_mm;
+template [[host_name("kernel_mul_mm_iq4_xs_f32")]]  kernel mat_mm_t kernel_mul_mm;
 
 //
 // indirect matrix-matrix multiplication
@@ -6436,7 +6065,7 @@ void mmv_fn(
     impl_fn(src0,(const device float *)src1,dst,ne00,ne01,ne02,ne10,ne12,ne0,ne1,r2,r3,shared_values,tgpig,tiisg,sgitg);
 }
 
-typedef decltype(mmv_fn) mul_mv_impl_fn_t;
+typedef decltype(mmv_fn>) mul_mv_impl_fn_t;
 
 template
 kernel void kernel_mul_mv_id(
@@ -6514,20 +6143,20 @@ kernel void kernel_mul_mv_id(
         sgitg);
 }
 
-typedef decltype(kernel_mul_mv_id>) kernel_mul_mv_id_t;
-
-template [[host_name("kernel_mul_mv_id_f32_f32")]]  kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
-template [[host_name("kernel_mul_mv_id_f16_f32")]]  kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
-template [[host_name("kernel_mul_mv_id_q8_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
-template [[host_name("kernel_mul_mv_id_q4_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>;
-template [[host_name("kernel_mul_mv_id_q4_1_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>;
-template [[host_name("kernel_mul_mv_id_q5_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>;
-template [[host_name("kernel_mul_mv_id_q5_1_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>;
-template [[host_name("kernel_mul_mv_id_q2_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
-template [[host_name("kernel_mul_mv_id_q3_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
-template [[host_name("kernel_mul_mv_id_q4_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
-template [[host_name("kernel_mul_mv_id_q5_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
-template [[host_name("kernel_mul_mv_id_q6_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
+typedef decltype(kernel_mul_mv_id>>) kernel_mul_mv_id_t;
+
+template [[host_name("kernel_mul_mv_id_f32_f32")]]     kernel kernel_mul_mv_id_t kernel_mul_mv_id>>;
+template [[host_name("kernel_mul_mv_id_f16_f32")]]     kernel kernel_mul_mv_id_t kernel_mul_mv_id>>;
+template [[host_name("kernel_mul_mv_id_q8_0_f32")]]    kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
+template [[host_name("kernel_mul_mv_id_q4_0_f32")]]    kernel kernel_mul_mv_id_t kernel_mul_mv_id>>;
+template [[host_name("kernel_mul_mv_id_q4_1_f32")]]    kernel kernel_mul_mv_id_t kernel_mul_mv_id>>;
+template [[host_name("kernel_mul_mv_id_q5_0_f32")]]    kernel kernel_mul_mv_id_t kernel_mul_mv_id>>;
+template [[host_name("kernel_mul_mv_id_q5_1_f32")]]    kernel kernel_mul_mv_id_t kernel_mul_mv_id>>;
+template [[host_name("kernel_mul_mv_id_q2_K_f32")]]    kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
+template [[host_name("kernel_mul_mv_id_q3_K_f32")]]    kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
+template [[host_name("kernel_mul_mv_id_q4_K_f32")]]    kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
+template [[host_name("kernel_mul_mv_id_q5_K_f32")]]    kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
+template [[host_name("kernel_mul_mv_id_q6_K_f32")]]    kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
 template [[host_name("kernel_mul_mv_id_iq1_s_f32")]]   kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
 template [[host_name("kernel_mul_mv_id_iq1_m_f32")]]   kernel kernel_mul_mv_id_t kernel_mul_mv_id>;
 template [[host_name("kernel_mul_mv_id_iq2_xxs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>;

From 17eb6aa8a992cda37ee65cf848d9289bd6cad860 Mon Sep 17 00:00:00 2001
From: bandoti <141645996+bandoti@users.noreply.github.com>
Date: Sat, 13 Jul 2024 13:12:39 -0300
Subject: [PATCH 177/326] vulkan : cmake integration (#8119)

* Add Vulkan to CMake pkg

* Add Sycl to CMake pkg

* Add OpenMP to CMake pkg

* Split generated shader file into separate translation unit

* Add CMake target for Vulkan shaders

* Update README.md

* Add make target for Vulkan shaders

* Use pkg-config to locate vulkan library

* Add vulkan SDK dep to ubuntu-22-cmake-vulkan workflow

* Clean up tabs

* Move sudo to apt-key invocation

* Forward GGML_EXTRA_LIBS to CMake config pkg

* Update vulkan obj file paths

* Add shaderc to nix pkg

* Add python3 to Vulkan nix build

* Link against ggml in cmake pkg

* Remove Python dependency from Vulkan build

* code review changes

* Remove trailing newline

* Add cflags from pkg-config to fix w64devkit build

* Update README.md

* Remove trailing whitespace

* Update README.md

* Remove trailing whitespace

* Fix doc heading

* Make glslc required Vulkan component

* remove clblast from nix pkg
---
 .devops/nix/package.nix                       |      2 +
 .github/workflows/build.yml                   |      6 +-
 CMakeLists.txt                                |     11 +-
 Makefile                                      |     35 +-
 cmake/llama-config.cmake.in                   |     29 +-
 docs/build.md                                 |     39 +
 ggml/.gitignore                               |      2 +
 ggml/ggml_vk_generate_shaders.py              |    220 -
 ggml/src/CMakeLists.txt                       |     37 +-
 ggml/src/ggml-vulkan-shaders.hpp              | 144956 ---------------
 ggml/src/vulkan-shaders/CMakeLists.txt        |      5 +
 .../src/vulkan-shaders/vulkan-shaders-gen.cpp |    524 +
 12 files changed, 674 insertions(+), 145192 deletions(-)
 create mode 100644 ggml/.gitignore
 delete mode 100644 ggml/ggml_vk_generate_shaders.py
 delete mode 100644 ggml/src/ggml-vulkan-shaders.hpp
 create mode 100644 ggml/src/vulkan-shaders/CMakeLists.txt
 create mode 100644 ggml/src/vulkan-shaders/vulkan-shaders-gen.cpp

diff --git a/.devops/nix/package.nix b/.devops/nix/package.nix
index 00be596ce3fb7..911c42ecb16cf 100644
--- a/.devops/nix/package.nix
+++ b/.devops/nix/package.nix
@@ -18,6 +18,7 @@
   vulkan-headers,
   vulkan-loader,
   curl,
+  shaderc,
   useBlas ? builtins.all (x: !x) [
     useCuda
     useMetalKit
@@ -146,6 +147,7 @@ let
   vulkanBuildInputs = [
     vulkan-headers
     vulkan-loader
+    shaderc
   ];
 in
 
diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 1e344db6b09e9..1f275603a3742 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -355,8 +355,10 @@ jobs:
       - name: Dependencies
         id: depends
         run: |
-          sudo apt-get update
-          sudo apt-get install build-essential libvulkan-dev
+          wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | sudo apt-key add -
+          sudo wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list
+          sudo apt-get update -y
+          sudo apt-get install -y build-essential vulkan-sdk
 
       - name: Build
         id: cmake_build
diff --git a/CMakeLists.txt b/CMakeLists.txt
index befc4433cd0f8..67dcf86d4fab7 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -132,7 +132,16 @@ set(LLAMA_INCLUDE_INSTALL_DIR ${CMAKE_INSTALL_INCLUDEDIR} CACHE PATH "Location o
 set(LLAMA_LIB_INSTALL_DIR     ${CMAKE_INSTALL_LIBDIR}     CACHE PATH "Location of library files")
 set(LLAMA_BIN_INSTALL_DIR     ${CMAKE_INSTALL_BINDIR}     CACHE PATH "Location of binary  files")
 
-get_directory_property(LLAMA_TRANSIENT_DEFINES COMPILE_DEFINITIONS)
+
+# At the moment some compile definitions are placed within the ggml/src
+# directory but not exported on the `ggml` target. This could be improved by
+# determining _precisely_ which defines are necessary for the llama-config
+# package.
+#
+get_directory_property(GGML_DIR_DEFINES DIRECTORY ggml/src COMPILE_DEFINITIONS)
+get_target_property(GGML_TARGET_DEFINES ggml COMPILE_DEFINITIONS)
+set(GGML_TRANSIENT_DEFINES ${GGML_TARGET_DEFINES} ${GGML_DIR_DEFINES})
+get_target_property(GGML_LINK_LIBRARIES ggml LINK_LIBRARIES)
 
 set_target_properties(llama PROPERTIES PUBLIC_HEADER ${CMAKE_CURRENT_SOURCE_DIR}/include/llama.h)
 install(TARGETS llama LIBRARY PUBLIC_HEADER)
diff --git a/Makefile b/Makefile
index 4869d2ecf3be2..bec332ec57b55 100644
--- a/Makefile
+++ b/Makefile
@@ -197,6 +197,10 @@ ifdef GGML_RPC
 	BUILD_TARGETS += rpc-server
 endif
 
+ifdef GGML_VULKAN
+	BUILD_TARGETS += vulkan-shaders-gen
+endif
+
 default: $(BUILD_TARGETS) $(LEGACY_TARGETS_BUILD)
 
 test: $(TEST_TARGETS)
@@ -710,8 +714,8 @@ endif # GGML_CUDA
 
 ifdef GGML_VULKAN
 	MK_CPPFLAGS += -DGGML_USE_VULKAN
-	MK_LDFLAGS  += -lvulkan
-	OBJ_GGML    += ggml/src/ggml-vulkan.o
+	MK_LDFLAGS  += $(shell pkg-config --libs vulkan)
+	OBJ_GGML    += ggml/src/ggml-vulkan.o ggml/src/ggml-vulkan-shaders.o
 
 ifdef GGML_VULKAN_CHECK_RESULTS
 	MK_CPPFLAGS  += -DGGML_VULKAN_CHECK_RESULTS
@@ -733,10 +737,28 @@ ifdef GGML_VULKAN_RUN_TESTS
 	MK_CPPFLAGS  += -DGGML_VULKAN_RUN_TESTS
 endif
 
-ggml/src/ggml-vulkan.o: \
-	ggml/src/ggml-vulkan.cpp \
-	ggml/include/ggml-vulkan.h
-	$(CXX) $(CXXFLAGS) -c $< -o $@
+GLSLC_CMD  = glslc
+_ggml_vk_genshaders_cmd = $(shell pwd)/vulkan-shaders-gen
+_ggml_vk_header = ggml/src/ggml-vulkan-shaders.hpp
+_ggml_vk_source = ggml/src/ggml-vulkan-shaders.cpp
+_ggml_vk_input_dir = ggml/src/vulkan-shaders
+_ggml_vk_shader_deps = $(echo $(_ggml_vk_input_dir)/*.comp)
+
+ggml/src/ggml-vulkan.o: ggml/src/ggml-vulkan.cpp ggml/include/ggml-vulkan.h $(_ggml_vk_header) $(_ggml_vk_source)
+	$(CXX) $(CXXFLAGS) $(shell pkg-config --cflags vulkan) -c $< -o $@
+
+$(_ggml_vk_header): $(_ggml_vk_source)
+
+$(_ggml_vk_source): $(_ggml_vk_shader_deps) vulkan-shaders-gen
+	$(_ggml_vk_genshaders_cmd) \
+		--glslc      $(GLSLC_CMD) \
+		--input-dir  $(_ggml_vk_input_dir) \
+		--target-hpp $(_ggml_vk_header) \
+		--target-cpp $(_ggml_vk_source)
+
+vulkan-shaders-gen: ggml/src/vulkan-shaders/vulkan-shaders-gen.cpp
+	$(CXX) $(CXXFLAGS) -o $@ $(LDFLAGS) ggml/src/vulkan-shaders/vulkan-shaders-gen.cpp
+
 endif # GGML_VULKAN
 
 ifdef GGML_HIPBLAS
@@ -1116,6 +1138,7 @@ clean:
 	rm -vrf ggml/src/ggml-cuda/template-instances/*.o
 	rm -rvf $(BUILD_TARGETS)
 	rm -rvf $(TEST_TARGETS)
+	rm -f vulkan-shaders-gen ggml/src/ggml-vulkan-shaders.hpp ggml/src/ggml-vulkan-shaders.cpp
 	rm -rvf $(LEGACY_TARGETS_CLEAN)
 	find examples pocs -type f -name "*.o" -delete
 
diff --git a/cmake/llama-config.cmake.in b/cmake/llama-config.cmake.in
index 2e7da2f8ebd69..f072b76a39d2e 100644
--- a/cmake/llama-config.cmake.in
+++ b/cmake/llama-config.cmake.in
@@ -8,6 +8,13 @@ set(GGML_CUDA       @GGML_CUDA@)
 set(GGML_METAL      @GGML_METAL@)
 set(GGML_HIPBLAS    @GGML_HIPBLAS@)
 set(GGML_ACCELERATE @GGML_ACCELERATE@)
+set(GGML_VULKAN @GGML_VULKAN@)
+set(GGML_VULKAN_CHECK_RESULTS @GGML_VULKAN_CHECK_RESULTS@)
+set(GGML_VULKAN_DEBUG @GGML_VULKAN_DEBUG@)
+set(GGML_VULKAN_MEMORY_DEBUG @GGML_VULKAN_MEMORY_DEBUG@)
+set(GGML_VULKAN_VALIDATE @GGML_VULKAN_VALIDATE@)
+set(GGML_SYCL @GGML_SYCL@)
+set(GGML_OPENMP @GGML_OPENMP@)
 
 @PACKAGE_INIT@
 
@@ -37,18 +44,36 @@ if (GGML_METAL)
     find_library(METALKIT_FRAMEWORK MetalKit REQUIRED)
 endif()
 
+if (GGML_VULKAN)
+    find_package(Vulkan REQUIRED)
+endif()
+
 if (GGML_HIPBLAS)
     find_package(hip REQUIRED)
     find_package(hipblas REQUIRED)
     find_package(rocblas REQUIRED)
 endif()
 
+if (GGML_SYCL)
+    find_package(IntelSYCL REQUIRED)
+    find_package(MKL REQUIRED)
+endif()
+
+if (GGML_OPENMP)
+    find_package(OpenMP REQUIRED)
+endif()
+
+
+find_library(ggml_LIBRARY ggml
+    REQUIRED
+    HINTS ${LLAMA_LIB_DIR})
+
 find_library(llama_LIBRARY llama
     REQUIRED
     HINTS ${LLAMA_LIB_DIR})
 
-set(_llama_link_deps "Threads::Threads" "@LLAMA_EXTRA_LIBS@")
-set(_llama_transient_defines "@LLAMA_TRANSIENT_DEFINES@")
+set(_llama_link_deps "${ggml_LIBRARY}" "@GGML_LINK_LIBRARIES@")
+set(_llama_transient_defines "@GGML_TRANSIENT_DEFINES@")
 
 add_library(llama UNKNOWN IMPORTED)
 
diff --git a/docs/build.md b/docs/build.md
index d70f72f4c7b82..916fcf22d7924 100644
--- a/docs/build.md
+++ b/docs/build.md
@@ -242,6 +242,45 @@ The following compilation options are also available to tweak performance (yes,
 
 ### Vulkan
 
+**Windows**
+
+#### w64devkit
+
+Download and extract [w64devkit](https://github.com/skeeto/w64devkit/releases).
+
+Download and install the [Vulkan SDK](https://vulkan.lunarg.com/sdk/home#windows). When selecting components, only the Vulkan SDK Core is required.
+
+Launch `w64devkit.exe` and run the following commands to copy Vulkan dependencies:
+```sh
+SDK_VERSION=1.3.283.0
+cp /VulkanSDK/$SDK_VERSION/Bin/glslc.exe $W64DEVKIT_HOME/bin/
+cp /VulkanSDK/$SDK_VERSION/Lib/vulkan-1.lib $W64DEVKIT_HOME/x86_64-w64-mingw32/lib/
+cp -r /VulkanSDK/$SDK_VERSION/Include/* $W64DEVKIT_HOME/x86_64-w64-mingw32/include/
+cat > $W64DEVKIT_HOME/x86_64-w64-mingw32/lib/pkgconfig/vulkan.pc <\n\n")
-        for name, path in sorted(shader_fnames):
-
-            with open(path, "rb") as spv:
-                counter = 0
-                newline_counter = 0
-                f.write(f"unsigned char {name}_data[] = {{\n")
-                for val in spv.read():
-                    f.write(f"0x{val:02x},")
-                    newline_counter += 1
-                    counter += 1
-                    if newline_counter >= 12:
-                        newline_counter = 0
-                        f.write("\n")
-            f.write("\n};\n")
-            f.write(f"const uint64_t {name}_len = {counter};\n\n")
-            os.remove(path)
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="GGML Vulkan Shader Generator")
-
-    parser.add_argument("--glslc", help="Path to glslc")
-    parser.add_argument("--verbose", action="store_true", help="increase output verbosity")
-
-    args = parser.parse_args()
-
-    logging.basicConfig(level=logging.DEBUG if args.verbose else logging.INFO)
-
-    if args.glslc:
-        GLSLC = args.glslc
-
-    asyncio.run(main())
diff --git a/ggml/src/CMakeLists.txt b/ggml/src/CMakeLists.txt
index c5ee7e4255ee5..41e50ad2c9e33 100644
--- a/ggml/src/CMakeLists.txt
+++ b/ggml/src/CMakeLists.txt
@@ -527,14 +527,11 @@ if (GGML_RPC)
 endif()
 
 if (GGML_VULKAN)
-    find_package(Vulkan)
+    find_package(Vulkan COMPONENTS glslc REQUIRED)
 
     if (Vulkan_FOUND)
         message(STATUS "Vulkan found")
 
-        set(GGML_HEADERS_VULKAN ../include/ggml-vulkan.h)
-        set(GGML_SOURCES_VULKAN ggml-vulkan.cpp)
-
         list(APPEND GGML_CDEF_PUBLIC GGML_USE_VULKAN)
 
         # Workaround to the "can't dereference invalidated vector iterator" bug in clang-cl debug build
@@ -563,7 +560,37 @@ if (GGML_VULKAN)
             add_compile_definitions(GGML_VULKAN_RUN_TESTS)
         endif()
 
-        set(GGML_EXTRA_LIBS ${GGML_EXTRA_LIBS} Vulkan::Vulkan)
+        add_subdirectory(vulkan-shaders)
+
+        set (_ggml_vk_genshaders_cmd vulkan-shaders-gen)
+        set (_ggml_vk_header     ${CMAKE_CURRENT_BINARY_DIR}/ggml-vulkan-shaders.hpp)
+        set (_ggml_vk_source     ${CMAKE_CURRENT_BINARY_DIR}/ggml-vulkan-shaders.cpp)
+        set (_ggml_vk_input_dir  ${CMAKE_CURRENT_SOURCE_DIR}/vulkan-shaders)
+        set (_ggml_vk_output_dir ${CMAKE_CURRENT_BINARY_DIR}/vulkan-shaders.spv)
+
+        file(GLOB _ggml_vk_shader_deps "${_ggml_vk_input_dir}/*.comp")
+
+        add_custom_command(
+            OUTPUT ${_ggml_vk_header}
+                   ${_ggml_vk_source}
+
+            COMMAND ${_ggml_vk_genshaders_cmd}
+                --glslc      ${Vulkan_GLSLC_EXECUTABLE}
+                --input-dir  ${_ggml_vk_input_dir}
+                --output-dir ${_ggml_vk_output_dir}
+                --target-hpp ${_ggml_vk_header}
+                --target-cpp ${_ggml_vk_source}
+                --no-clean
+
+            DEPENDS ${_ggml_vk_shader_deps}
+            COMMENT "Generate vulkan shaders"
+        )
+
+        set(GGML_HEADERS_VULKAN ${CMAKE_CURRENT_SOURCE_DIR}/../include/ggml-vulkan.h ${_ggml_vk_header})
+        set(GGML_SOURCES_VULKAN ggml-vulkan.cpp ${_ggml_vk_source})
+
+        set(GGML_EXTRA_LIBS     ${GGML_EXTRA_LIBS} Vulkan::Vulkan)
+        set(GGML_EXTRA_INCLUDES ${GGML_EXTRA_INCLUDES} ${CMAKE_CURRENT_BINARY_DIR})
     else()
         message(WARNING "Vulkan not found")
     endif()
diff --git a/ggml/src/ggml-vulkan-shaders.hpp b/ggml/src/ggml-vulkan-shaders.hpp
deleted file mode 100644
index f0c4c6baf592b..0000000000000
--- a/ggml/src/ggml-vulkan-shaders.hpp
+++ /dev/null
@@ -1,144956 +0,0 @@
-#include 
-
-unsigned char add_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x67,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x17,0x00,0x00,0x00,0x2f,0x01,0x00,0x00,0x3f,0x01,0x00,0x00,
-0x4b,0x01,0x00,0x00,0x56,0x01,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0x06,0x00,0x00,0x00,0x64,0x02,0x00,0x00,0x63,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x65,0x02,0x00,0x00,
-0x62,0x02,0x00,0x00,0x64,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x66,0x02,0x00,0x00,0x5e,0x02,0x00,0x00,
-0x65,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0x50,0x01,0x00,0x00,
-0x5b,0x01,0x00,0x00,0x56,0x01,0x00,0x00,0x34,0x01,0x00,0x00,
-0x66,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x14,0x00,0x00,0x00,
-0x5c,0x01,0x00,0x00,0x5b,0x01,0x00,0x00,0x81,0x00,0x05,0x00,
-0x14,0x00,0x00,0x00,0x5d,0x01,0x00,0x00,0x52,0x01,0x00,0x00,
-0x5c,0x01,0x00,0x00,0x41,0x00,0x06,0x00,0x50,0x01,0x00,0x00,
-0x5e,0x01,0x00,0x00,0x3f,0x01,0x00,0x00,0x34,0x01,0x00,0x00,
-0x47,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x5e,0x01,0x00,0x00,
-0x5d,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x62,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x62,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t add_f32_len = 4276;
-
-unsigned char argsort_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x41,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0b,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2a,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0x8c,0x00,0x00,0x00,0x12,0x01,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x00,0x04,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x23,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x2a,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x30,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x30,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x30,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x30,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x89,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x8a,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x8a,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x8a,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x8c,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x8c,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0f,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x10,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x10,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x12,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x12,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1c,0x01,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
-0x0d,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x00,0x04,0x00,0x00,0x1c,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
-0x0d,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x12,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0x21,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x22,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x22,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x25,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x22,0x00,0x00,0x00,
-0x2a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x1e,0x00,0x05,0x00,0x30,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x31,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x31,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,
-0x33,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x34,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x14,0x00,0x02,0x00,0x37,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x0d,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x45,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x46,0x00,0x00,0x00,0x08,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x0d,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x16,0x00,0x03,0x00,0x88,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0x89,0x00,0x00,0x00,0x88,0x00,0x00,0x00,
-0x1e,0x00,0x03,0x00,0x8a,0x00,0x00,0x00,0x89,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x8b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x8a,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x8b,0x00,0x00,0x00,
-0x8c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x93,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x88,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0x0f,0x01,0x00,0x00,0x0d,0x00,0x00,0x00,
-0x1e,0x00,0x03,0x00,0x10,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,
-0x20,0x00,0x04,0x00,0x11,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x10,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0x11,0x01,0x00,0x00,
-0x12,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x1a,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
-0x2c,0x00,0x06,0x00,0x21,0x00,0x00,0x00,0x1c,0x01,0x00,0x00,
-0x10,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,
-0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x05,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x1d,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfb,0x00,0x03,0x00,0x24,0x00,0x00,0x00,
-0x1e,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x1e,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x25,0x00,0x00,0x00,0x26,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x27,0x00,0x00,0x00,0x26,0x00,0x00,0x00,
-0x7c,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x25,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x2a,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x2f,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x34,0x00,0x00,0x00,0x35,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x33,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x36,0x00,0x00,0x00,0x35,0x00,0x00,0x00,0xae,0x00,0x05,0x00,
-0x37,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x2f,0x00,0x00,0x00,
-0x36,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x3a,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x38,0x00,0x00,0x00,
-0x39,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x39,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x1d,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x3a,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x34,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x44,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x44,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x45,0x00,0x00,0x00,0x45,0x00,0x00,0x00,
-0x46,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x48,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x48,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x3c,0x01,0x00,0x00,0x45,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x07,0x01,0x00,0x00,0x4b,0x00,0x00,0x00,
-0xb2,0x00,0x05,0x00,0x37,0x00,0x00,0x00,0x50,0x00,0x00,0x00,
-0x3c,0x01,0x00,0x00,0x36,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x4a,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x50,0x00,0x00,0x00,0x49,0x00,0x00,0x00,
-0x4a,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x49,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x53,0x00,0x00,0x00,
-0x3c,0x01,0x00,0x00,0x45,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x54,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x54,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x3d,0x01,0x00,0x00,
-0x53,0x00,0x00,0x00,0x49,0x00,0x00,0x00,0x05,0x01,0x00,0x00,
-0x57,0x00,0x00,0x00,0xac,0x00,0x05,0x00,0x37,0x00,0x00,0x00,
-0x5a,0x00,0x00,0x00,0x3d,0x01,0x00,0x00,0x24,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x56,0x00,0x00,0x00,0x57,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x5a,0x00,0x00,0x00,
-0x55,0x00,0x00,0x00,0x56,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x55,0x00,0x00,0x00,0xc6,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x5f,0x00,0x00,0x00,0x2f,0x00,0x00,0x00,0x3d,0x01,0x00,0x00,
-0xac,0x00,0x05,0x00,0x37,0x00,0x00,0x00,0x63,0x00,0x00,0x00,
-0x5f,0x00,0x00,0x00,0x2f,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
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-0xf8,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xcf,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xcf,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x37,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,
-0xcd,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0x3f,0x01,0x00,0x00,
-0xd5,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xc6,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc6,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x37,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,
-0xbc,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xfd,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xfb,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,
-0xfd,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xfc,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x32,0x01,0x00,0x00,
-0x13,0x00,0x00,0x00,0x2f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x0d,0x00,0x00,0x00,0x33,0x01,0x00,0x00,0x32,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,0x37,0x01,0x00,0x00,
-0xbe,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x32,0x01,0x00,0x00,
-0x37,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0xbe,0x00,0x00,0x00,
-0x33,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0xfd,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xfd,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x6c,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x6c,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x65,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x65,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,0x45,0x00,0x00,0x00,
-0x45,0x00,0x00,0x00,0x46,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x57,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x57,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x05,0x01,0x00,0x00,
-0x3d,0x01,0x00,0x00,0x45,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x54,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x56,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x4b,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x4b,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x07,0x01,0x00,0x00,0x3c,0x01,0x00,0x00,0x45,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x48,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x4a,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,0x37,0x00,0x00,0x00,
-0x0c,0x01,0x00,0x00,0x2f,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x0e,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x0c,0x01,0x00,0x00,0x0d,0x01,0x00,0x00,
-0x0e,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x0d,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x16,0x01,0x00,0x00,
-0x41,0x00,0x00,0x00,0x2f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x0d,0x00,0x00,0x00,0x19,0x01,0x00,0x00,0x44,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x1a,0x01,0x00,0x00,0x1b,0x01,0x00,0x00,
-0x12,0x01,0x00,0x00,0x3e,0x00,0x00,0x00,0x16,0x01,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x1b,0x01,0x00,0x00,0x19,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x0e,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x0e,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x1d,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x1d,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t argsort_f32_len = 4096;
-
-unsigned char clamp_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xb6,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x09,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0xd9,0x00,0x00,0x00,
-0xe4,0x00,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x38,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x40,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x44,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x12,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x48,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xc7,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xd6,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xd7,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xd7,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xd7,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xd9,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xd9,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xe1,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xe2,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xe2,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xe2,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xe4,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xe4,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0a,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,
-0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x11,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x1e,0x00,0x16,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x13,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x17,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x55,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x5a,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x66,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x6f,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x72,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x76,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0xad,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0xb2,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0xbe,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0xc5,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0xc6,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0xc5,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0xc6,0x00,0x00,0x00,
-0xc7,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0xc9,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0xcc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x14,0x00,0x02,0x00,
-0xcf,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0xd6,0x00,0x00,0x00,
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-0xad,0x01,0x00,0x00,0xb1,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xec,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,
-0xb2,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0xef,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0xee,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x11,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0xb8,0x00,0x05,0x00,0xcf,0x00,0x00,0x00,
-0xf2,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xf5,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xf2,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,
-0xf8,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xf4,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xf5,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf8,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0xef,0x00,0x00,0x00,
-0xfb,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x11,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,
-0xfb,0x00,0x00,0x00,0xba,0x00,0x05,0x00,0xcf,0x00,0x00,0x00,
-0xfd,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,
-0xa9,0x00,0x06,0x00,0x11,0x00,0x00,0x00,0xb5,0x01,0x00,0x00,
-0xfd,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xf5,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf5,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x11,0x00,0x00,0x00,
-0xb4,0x01,0x00,0x00,0xf1,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,
-0xb5,0x01,0x00,0x00,0xf8,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0xde,0x00,0x00,0x00,0x07,0x01,0x00,0x00,0xe4,0x00,0x00,0x00,
-0xcc,0x00,0x00,0x00,0xec,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x07,0x01,0x00,0x00,0xb4,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x0b,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x0b,0x01,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t clamp_f32_len = 3512;
-
-unsigned char cpy_f16_f16_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x98,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x09,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0xc7,0x00,0x00,0x00,0xd8,0x00,0x00,0x00,0xe4,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x34,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x48,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x4c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x12,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xc7,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xd5,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0xd6,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xd6,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0xd6,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xd8,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xd8,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xe1,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0xe2,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xe2,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0xe2,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xe4,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xe4,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xef,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,
-0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x16,0x00,0x03,0x00,0x11,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x1e,0x00,0x16,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x13,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x13,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x17,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x1e,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x55,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x5a,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x60,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x66,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x72,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x76,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xad,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0xb2,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,
-0x0d,0x00,0x00,0x00,0x17,0x00,0x04,0x00,0xc5,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0xc6,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0xc6,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xc8,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0xc9,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x14,0x00,0x02,0x00,0xcf,0x00,0x00,0x00,
-0x16,0x00,0x03,0x00,0xd4,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0xd5,0x00,0x00,0x00,0xd4,0x00,0x00,0x00,
-0x1e,0x00,0x03,0x00,0xd6,0x00,0x00,0x00,0xd5,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0xd7,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0xd6,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0xd7,0x00,0x00,0x00,
-0xd8,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0xd9,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0xe1,0x00,0x00,0x00,0xd4,0x00,0x00,0x00,
-0x1e,0x00,0x03,0x00,0xe2,0x00,0x00,0x00,0xe1,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0xe3,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0xe2,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0xe3,0x00,0x00,0x00,
-0xe4,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0xe9,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0xd4,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xee,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2c,0x00,0x06,0x00,
-0xc5,0x00,0x00,0x00,0xef,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0xee,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0x36,0x00,0x05,0x00,
-0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xf0,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
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-0x17,0x00,0x00,0x00,0x8a,0x01,0x00,0x00,0x14,0x00,0x00,0x00,
-0x5a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x8b,0x01,0x00,0x00,0x8a,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8c,0x01,0x00,0x00,0x6b,0x01,0x00,0x00,
-0x8b,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8d,0x01,0x00,0x00,0x88,0x01,0x00,0x00,0x8c,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x8f,0x01,0x00,0x00,
-0x14,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x90,0x01,0x00,0x00,0x8f,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x91,0x01,0x00,0x00,
-0x7a,0x01,0x00,0x00,0x90,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x92,0x01,0x00,0x00,0x8d,0x01,0x00,0x00,
-0x91,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x94,0x01,0x00,0x00,0x14,0x00,0x00,0x00,0x66,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x95,0x01,0x00,0x00,
-0x94,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x96,0x01,0x00,0x00,0x84,0x01,0x00,0x00,0x95,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x97,0x01,0x00,0x00,
-0x92,0x01,0x00,0x00,0x96,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0xe9,0x00,0x00,0x00,0xea,0x00,0x00,0x00,0xe4,0x00,0x00,0x00,
-0xcc,0x00,0x00,0x00,0x97,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xd4,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,0xea,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0xe9,0x00,0x00,0x00,0xec,0x00,0x00,0x00,
-0xd8,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xec,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xf0,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf0,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t cpy_f16_f16_len = 3252;
-
-unsigned char cpy_f32_f16_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x9a,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x09,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0xc7,0x00,0x00,0x00,0xd8,0x00,0x00,0x00,0xe4,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
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-0x06,0x00,0x00,0x00,0x98,0x01,0x00,0x00,0x86,0x01,0x00,0x00,
-0x97,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x99,0x01,0x00,0x00,0x94,0x01,0x00,0x00,0x98,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0xe9,0x00,0x00,0x00,0xea,0x00,0x00,0x00,
-0xe4,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,0x99,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x11,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
-0xea,0x00,0x00,0x00,0x73,0x00,0x04,0x00,0xd4,0x00,0x00,0x00,
-0xec,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0xed,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0xd8,0x00,0x00,0x00,
-0xcc,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xee,0x00,0x00,0x00,0xec,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xf2,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xf2,0x00,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t cpy_f32_f16_len = 3284;
-
-unsigned char cpy_f32_f32_data[] = {
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-0x53,0x01,0x00,0x00,0x50,0x01,0x00,0x00,0x52,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x54,0x01,0x00,0x00,
-0x14,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x55,0x01,0x00,0x00,0x54,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x56,0x01,0x00,0x00,
-0x53,0x01,0x00,0x00,0x55,0x01,0x00,0x00,0x86,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x57,0x01,0x00,0x00,0xcb,0x00,0x00,0x00,
-0x56,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x5b,0x01,0x00,0x00,0x57,0x01,0x00,0x00,0x50,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x5e,0x01,0x00,0x00,
-0x5b,0x01,0x00,0x00,0x52,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x61,0x01,0x00,0x00,0x5e,0x01,0x00,0x00,
-0x55,0x01,0x00,0x00,0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x64,0x01,0x00,0x00,0xcb,0x00,0x00,0x00,0x61,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x69,0x01,0x00,0x00,
-0x52,0x01,0x00,0x00,0x55,0x01,0x00,0x00,0x86,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x6a,0x01,0x00,0x00,0x64,0x01,0x00,0x00,
-0x69,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x6e,0x01,0x00,0x00,0x6a,0x01,0x00,0x00,0x52,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x71,0x01,0x00,0x00,
-0x6e,0x01,0x00,0x00,0x55,0x01,0x00,0x00,0x82,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x76,0x01,0x00,0x00,0x64,0x01,0x00,0x00,
-0x71,0x01,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x79,0x01,0x00,0x00,0x76,0x01,0x00,0x00,0x55,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x82,0x01,0x00,0x00,
-0x79,0x01,0x00,0x00,0x55,0x01,0x00,0x00,0x82,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x83,0x01,0x00,0x00,0x76,0x01,0x00,0x00,
-0x82,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x85,0x01,0x00,0x00,0x14,0x00,0x00,0x00,0x55,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x86,0x01,0x00,0x00,
-0x85,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x87,0x01,0x00,0x00,0x57,0x01,0x00,0x00,0x86,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x89,0x01,0x00,0x00,
-0x14,0x00,0x00,0x00,0x5a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x8a,0x01,0x00,0x00,0x89,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8b,0x01,0x00,0x00,
-0x6a,0x01,0x00,0x00,0x8a,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8c,0x01,0x00,0x00,0x87,0x01,0x00,0x00,
-0x8b,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x8e,0x01,0x00,0x00,0x14,0x00,0x00,0x00,0x60,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x8f,0x01,0x00,0x00,
-0x8e,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x90,0x01,0x00,0x00,0x79,0x01,0x00,0x00,0x8f,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x91,0x01,0x00,0x00,
-0x8c,0x01,0x00,0x00,0x90,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x93,0x01,0x00,0x00,0x14,0x00,0x00,0x00,
-0x66,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x94,0x01,0x00,0x00,0x93,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x95,0x01,0x00,0x00,0x83,0x01,0x00,0x00,
-0x94,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x96,0x01,0x00,0x00,0x91,0x01,0x00,0x00,0x95,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0xe8,0x00,0x00,0x00,0xe9,0x00,0x00,0x00,
-0xe3,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,0x96,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x11,0x00,0x00,0x00,0xea,0x00,0x00,0x00,
-0xe9,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0xe8,0x00,0x00,0x00,
-0xeb,0x00,0x00,0x00,0xd7,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,
-0xdf,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0xeb,0x00,0x00,0x00,
-0xea,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xef,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xef,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t cpy_f32_f32_len = 3232;
-
-unsigned char dequant_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x1f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x09,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x15,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x35,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x00,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x13,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x13,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x13,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x13,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x13,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x13,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x29,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x2a,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x2a,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x2c,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x2c,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x32,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x33,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x33,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x33,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x35,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x35,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x44,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,
-0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x17,0x00,0x04,0x00,0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x0a,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x1e,0x00,0x07,0x00,0x13,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x14,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x14,0x00,0x00,0x00,0x15,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x16,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x17,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x18,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x14,0x00,0x02,0x00,0x1b,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0x28,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x29,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x2a,0x00,0x00,0x00,0x29,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x2b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x2a,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x2b,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
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-0x32,0x00,0x00,0x00,0x31,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x33,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x34,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x33,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x34,0x00,0x00,0x00,0x35,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x39,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x31,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x3d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x42,0x00,0x00,0x00,
-0x00,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x43,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2c,0x00,0x06,0x00,
-0x09,0x00,0x00,0x00,0x44,0x00,0x00,0x00,0x42,0x00,0x00,0x00,
-0x43,0x00,0x00,0x00,0x43,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x11,0x01,0x00,0x00,0x02,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x12,0x01,0x00,0x00,
-0x03,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x13,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x14,0x01,0x00,0x00,0x05,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x15,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x16,0x01,0x00,0x00,0x07,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x17,0x01,0x00,0x00,0x08,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x18,0x01,0x00,0x00,
-0x09,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x19,0x01,0x00,0x00,0x0a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x1a,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x1b,0x01,0x00,0x00,
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-0x73,0x00,0x04,0x00,0x28,0x00,0x00,0x00,0xff,0x00,0x00,0x00,
-0xfe,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x3d,0x00,0x00,0x00,
-0x00,0x01,0x00,0x00,0x2c,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,
-0xfb,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x00,0x01,0x00,0x00,
-0xff,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x08,0x01,0x00,0x00,0x11,0x00,0x00,0x00,0x1e,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0x39,0x00,0x00,0x00,0x0a,0x01,0x00,0x00,
-0x35,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,0x08,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x31,0x00,0x00,0x00,0x0b,0x01,0x00,0x00,
-0x0a,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x28,0x00,0x00,0x00,
-0x0c,0x01,0x00,0x00,0x0b,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x3d,0x00,0x00,0x00,0x0d,0x01,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x2d,0x00,0x00,0x00,0x08,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x0d,0x01,0x00,0x00,0x0c,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x45,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x45,0x00,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t dequant_f32_len = 3200;
-
-unsigned char dequant_q2_k_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x10,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x5e,0x00,0x00,0x00,0x79,0x00,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x16,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x1e,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x30,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x55,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x57,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x5a,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x5a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x5a,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x50,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x5b,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x5c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x5c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x5c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x5e,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x5e,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x76,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x77,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x77,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x77,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x79,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x79,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x00,0x01,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x00,0x01,0x00,0x00,0x14,0x00,0x02,0x00,0x11,0x00,0x00,0x00,
-0x17,0x00,0x04,0x00,0x14,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x17,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x1e,0x00,0x07,0x00,0x1e,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x1f,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x1f,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x21,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x21,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x23,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x21,0x00,0x00,0x00,
-0x26,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x35,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x3d,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x47,0x00,0x00,0x00,
-0x80,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x52,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,
-0x55,0x00,0x00,0x00,0x52,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x56,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0x57,0x00,0x00,0x00,
-0x52,0x00,0x00,0x00,0x56,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0x58,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0x59,0x00,0x00,0x00,0x58,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x1e,0x00,0x05,0x00,0x5a,0x00,0x00,0x00,0x55,0x00,0x00,0x00,
-0x57,0x00,0x00,0x00,0x59,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x5b,0x00,0x00,0x00,0x5a,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x5c,0x00,0x00,0x00,0x5b,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x5d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x5d,0x00,0x00,0x00,0x5e,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x64,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x52,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0x67,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x21,0x00,0x00,0x00,0x6b,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x6c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x58,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x72,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x76,0x00,0x00,0x00,0x58,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x77,0x00,0x00,0x00,0x76,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x78,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x77,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x78,0x00,0x00,0x00,0x79,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x21,0x00,0x00,0x00,
-0x84,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x21,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x21,0x00,0x00,0x00,0x95,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xa1,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xc1,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xdd,0x00,0x00,0x00,
-0x60,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xe2,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x21,0x00,0x00,0x00,0xea,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x2c,0x00,0x06,0x00,0x14,0x00,0x00,0x00,0x00,0x01,0x00,0x00,
-0x56,0x00,0x00,0x00,0x72,0x00,0x00,0x00,0x72,0x00,0x00,0x00,
-0x2a,0x00,0x03,0x00,0x11,0x00,0x00,0x00,0x03,0x01,0x00,0x00,
-0x29,0x00,0x03,0x00,0x11,0x00,0x00,0x00,0x06,0x01,0x00,0x00,
-0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x05,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x01,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfb,0x00,0x03,0x00,0x09,0x00,0x00,0x00,
-0x02,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x02,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x0a,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x0a,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x09,0x01,0x00,0x00,0x09,0x00,0x00,0x00,0x02,0x01,0x00,0x00,
-0xff,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x09,0x01,0x00,0x00,
-0x10,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x0c,0x00,0x00,0x00,
-0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x0b,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
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-0xe3,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x52,0x00,0x00,0x00,
-0xe5,0x00,0x00,0x00,0xe4,0x00,0x00,0x00,0x71,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xe6,0x00,0x00,0x00,0xe5,0x00,0x00,0x00,
-0x7c,0x00,0x04,0x00,0x21,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,
-0xe6,0x00,0x00,0x00,0xc7,0x00,0x05,0x00,0x21,0x00,0x00,0x00,
-0xe8,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,0x84,0x00,0x00,0x00,
-0xc2,0x00,0x05,0x00,0x52,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
-0x66,0x00,0x00,0x00,0xea,0x00,0x00,0x00,0x71,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xec,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
-0x7c,0x00,0x04,0x00,0x21,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0xec,0x00,0x00,0x00,0xc7,0x00,0x05,0x00,0x21,0x00,0x00,0x00,
-0xee,0x00,0x00,0x00,0xed,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x21,0x00,0x00,0x00,0xef,0x00,0x00,0x00,
-0xe8,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0x6f,0x00,0x04,0x00,
-0x67,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,0xef,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x52,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,
-0xe4,0x00,0x00,0x00,0xc2,0x00,0x05,0x00,0x52,0x00,0x00,0x00,
-0xf8,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,0x95,0x00,0x00,0x00,
-0x70,0x00,0x04,0x00,0x67,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,
-0xf8,0x00,0x00,0x00,0x85,0x00,0x05,0x00,0x67,0x00,0x00,0x00,
-0xfa,0x00,0x00,0x00,0x75,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,
-0x7f,0x00,0x04,0x00,0x67,0x00,0x00,0x00,0x0f,0x01,0x00,0x00,
-0xfa,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,0x67,0x00,0x00,0x00,
-0xfb,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x6f,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,0x0f,0x01,0x00,0x00,
-0x73,0x00,0x04,0x00,0x58,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,
-0xfb,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x6c,0x00,0x00,0x00,
-0xfd,0x00,0x00,0x00,0x79,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0xde,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0xfd,0x00,0x00,0x00,
-0xfc,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x0d,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x0d,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xff,0x00,0x00,0x00,0x09,0x01,0x00,0x00,
-0x26,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x0a,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x0c,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x11,0x00,0x00,0x00,0x0a,0x01,0x00,0x00,0x03,0x01,0x00,0x00,
-0x0a,0x00,0x00,0x00,0x06,0x01,0x00,0x00,0x2c,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x07,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x0a,0x01,0x00,0x00,0x01,0x01,0x00,0x00,
-0x07,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x07,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x01,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x01,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t dequant_q2_k_len = 4032;
-
-unsigned char dequant_q3_k_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x3f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x77,0x00,0x00,0x00,0x06,0x01,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x16,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x1e,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x30,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x6d,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x6f,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x71,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x73,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x73,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x73,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x73,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x6c,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x74,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x75,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x75,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x75,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x77,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x77,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x03,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x04,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x04,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x04,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x06,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x06,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x2c,0x01,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x00,0x01,0x00,0x00,0x14,0x00,0x02,0x00,0x11,0x00,0x00,0x00,
-0x17,0x00,0x04,0x00,0x14,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x17,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x1e,0x00,0x07,0x00,0x1e,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x1f,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x1f,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x21,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x21,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x23,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x21,0x00,0x00,0x00,
-0x26,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x33,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x37,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x4d,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x55,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x59,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
-0x1c,0x00,0x04,0x00,0x6f,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0x6e,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x70,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,
-0x71,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x70,0x00,0x00,0x00,
-0x16,0x00,0x03,0x00,0x72,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x1e,0x00,0x06,0x00,0x73,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x6f,0x00,0x00,0x00,0x71,0x00,0x00,0x00,0x72,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0x74,0x00,0x00,0x00,0x73,0x00,0x00,0x00,
-0x1e,0x00,0x03,0x00,0x75,0x00,0x00,0x00,0x74,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x76,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x75,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x76,0x00,0x00,0x00,
-0x77,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x21,0x00,0x00,0x00,0x79,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x7c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x21,0x00,0x00,0x00,
-0x81,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x21,0x00,0x00,0x00,0x8b,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x21,0x00,0x00,0x00,0x8d,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x21,0x00,0x00,0x00,
-0xd0,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0xdb,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0xdf,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x72,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x21,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
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-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x01,0x01,0x00,0x00,
-0x44,0x00,0x00,0x00,0x33,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x02,0x01,0x00,0x00,0x39,0x01,0x00,0x00,
-0x01,0x01,0x00,0x00,0xf6,0x00,0x04,0x00,0xfc,0x00,0x00,0x00,
-0xfb,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x02,0x01,0x00,0x00,0xfb,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,
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-0x21,0x01,0x00,0x00,0x6f,0x00,0x04,0x00,0xdb,0x00,0x00,0x00,
-0x23,0x01,0x00,0x00,0x22,0x01,0x00,0x00,0x85,0x00,0x05,0x00,
-0xdb,0x00,0x00,0x00,0x24,0x01,0x00,0x00,0xea,0x00,0x00,0x00,
-0x23,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x72,0x00,0x00,0x00,
-0x25,0x01,0x00,0x00,0x24,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0xdf,0x00,0x00,0x00,0x26,0x01,0x00,0x00,0x06,0x01,0x00,0x00,
-0x22,0x00,0x00,0x00,0x09,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x26,0x01,0x00,0x00,0x25,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x28,0x01,0x00,0x00,0x39,0x01,0x00,0x00,
-0x26,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xfa,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xfc,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x0d,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x0d,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x2a,0x01,0x00,0x00,
-0x35,0x01,0x00,0x00,0x26,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x0a,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x0c,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x11,0x00,0x00,0x00,0x3e,0x01,0x00,0x00,
-0x2f,0x01,0x00,0x00,0x0a,0x00,0x00,0x00,0x32,0x01,0x00,0x00,
-0x2c,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x33,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x3e,0x01,0x00,0x00,
-0x2d,0x01,0x00,0x00,0x33,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x33,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x2d,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x2d,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t dequant_q3_k_len = 4804;
-
-unsigned char dequant_q4_0_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x83,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x66,0x00,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x00,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x29,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
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-
-};
-const uint64_t dequant_q4_0_len = 5184;
-
-unsigned char dequant_q4_1_data[] = {
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-0x7c,0x00,0x04,0x00,0x2c,0x00,0x00,0x00,0x45,0x01,0x00,0x00,
-0x44,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,0x2c,0x00,0x00,0x00,
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-0x68,0x01,0x00,0x00,0x41,0x00,0x06,0x00,0x50,0x00,0x00,0x00,
-0x6a,0x01,0x00,0x00,0x68,0x00,0x00,0x00,0x4e,0x00,0x00,0x00,
-0x5e,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x6a,0x01,0x00,0x00,
-0x69,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x6c,0x01,0x00,0x00,0x41,0x00,0x00,0x00,0x84,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x46,0x00,0x00,0x00,0x6f,0x01,0x00,0x00,
-0x61,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,0x46,0x00,0x00,0x00,
-0x70,0x01,0x00,0x00,0x6f,0x01,0x00,0x00,0x2d,0x00,0x00,0x00,
-0x70,0x00,0x04,0x00,0x42,0x00,0x00,0x00,0x71,0x01,0x00,0x00,
-0x70,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,0x42,0x00,0x00,0x00,
-0x73,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x53,0x00,0x00,0x00,0x71,0x01,0x00,0x00,0x59,0x00,0x00,0x00,
-0x73,0x00,0x04,0x00,0x45,0x00,0x00,0x00,0x74,0x01,0x00,0x00,
-0x73,0x01,0x00,0x00,0x41,0x00,0x06,0x00,0x50,0x00,0x00,0x00,
-0x75,0x01,0x00,0x00,0x68,0x00,0x00,0x00,0x4e,0x00,0x00,0x00,
-0x6c,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x75,0x01,0x00,0x00,
-0x74,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x97,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x97,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t dequant_q4_1_len = 5248;
-
-unsigned char dequant_q4_k_data[] = {
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-0xae,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
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-0x70,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,0x9d,0x01,0x00,0x00,
-0x9c,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,0x3e,0x00,0x00,0x00,
-0x9f,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0xf7,0x00,0x00,0x00,0x9d,0x01,0x00,0x00,0xa5,0x01,0x00,0x00,
-0x73,0x00,0x04,0x00,0x41,0x00,0x00,0x00,0xa0,0x01,0x00,0x00,
-0x9f,0x01,0x00,0x00,0x41,0x00,0x06,0x00,0x4e,0x00,0x00,0x00,
-0xa1,0x01,0x00,0x00,0x08,0x01,0x00,0x00,0x22,0x00,0x00,0x00,
-0x98,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0xa1,0x01,0x00,0x00,
-0xa0,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x0d,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x0d,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x32,0x01,0x00,0x00,0x3c,0x01,0x00,0x00,
-0x26,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x0a,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x0c,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x11,0x00,0x00,0x00,0x45,0x01,0x00,0x00,0x36,0x01,0x00,0x00,
-0x0a,0x00,0x00,0x00,0x39,0x01,0x00,0x00,0x2c,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x3a,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x45,0x01,0x00,0x00,0x34,0x01,0x00,0x00,
-0x3a,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x3a,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x34,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x34,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t dequant_q4_k_len = 5916;
-
-unsigned char dequant_q5_0_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xb7,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
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-0x4d,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x4e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4e,0x00,0x00,0x00,
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-0x47,0x00,0x03,0x00,0x4e,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x50,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
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-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x7c,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x7d,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
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-0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x17,0x00,0x04,0x00,0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x0a,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,
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-0x97,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x45,0x00,0x00,0x00,
-0x99,0x01,0x00,0x00,0x98,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x53,0x00,0x00,0x00,0x9a,0x01,0x00,0x00,0x7f,0x00,0x00,0x00,
-0x51,0x00,0x00,0x00,0x8f,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x9a,0x01,0x00,0x00,0x99,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9c,0x01,0x00,0x00,0x41,0x00,0x00,0x00,
-0xb6,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9d,0x01,0x00,0x00,0x8e,0x01,0x00,0x00,0x2d,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9e,0x01,0x00,0x00,
-0x40,0x00,0x00,0x00,0xaf,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9f,0x01,0x00,0x00,0x64,0x00,0x00,0x00,
-0x9e,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa0,0x01,0x00,0x00,0x9f,0x01,0x00,0x00,0x4a,0x00,0x00,0x00,
-0xc5,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa1,0x01,0x00,0x00,
-0x9d,0x01,0x00,0x00,0xa0,0x01,0x00,0x00,0x70,0x00,0x04,0x00,
-0x42,0x00,0x00,0x00,0xa2,0x01,0x00,0x00,0xa1,0x01,0x00,0x00,
-0x83,0x00,0x05,0x00,0x42,0x00,0x00,0x00,0xa3,0x01,0x00,0x00,
-0xa2,0x01,0x00,0x00,0x8f,0x00,0x00,0x00,0x85,0x00,0x05,0x00,
-0x42,0x00,0x00,0x00,0xa4,0x01,0x00,0x00,0x56,0x00,0x00,0x00,
-0xa3,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x45,0x00,0x00,0x00,
-0xa5,0x01,0x00,0x00,0xa4,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x53,0x00,0x00,0x00,0xa6,0x01,0x00,0x00,0x7f,0x00,0x00,0x00,
-0x51,0x00,0x00,0x00,0x9c,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xa6,0x01,0x00,0x00,0xa5,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xac,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xac,0x00,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t dequant_q5_0_len = 6644;
-
-unsigned char dequant_q5_1_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xb4,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x2b,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x7a,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x00,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x12,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x29,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x29,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x29,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x48,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x49,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x49,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x49,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x49,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4a,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x4b,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4b,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x4b,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x4d,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4d,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x77,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x78,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x78,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x78,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x7a,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x7a,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xa7,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,
-0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,0x09,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x15,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x1e,0x00,0x07,0x00,0x29,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x2a,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x29,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x2a,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x2c,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x2c,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x2e,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x14,0x00,0x02,0x00,0x32,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0x00,0x04,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0x42,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0x45,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
-0x46,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x47,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0x48,0x00,0x00,0x00,
-0x46,0x00,0x00,0x00,0x47,0x00,0x00,0x00,0x1e,0x00,0x06,0x00,
-0x49,0x00,0x00,0x00,0x45,0x00,0x00,0x00,0x45,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x48,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x4a,0x00,0x00,0x00,0x49,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x4b,0x00,0x00,0x00,0x4a,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x4c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x4c,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x2c,0x00,0x00,0x00,
-0x4e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x50,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x45,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x2c,0x00,0x00,0x00,0x56,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x2c,0x00,0x00,0x00,
-0x5c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x5d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x2c,0x00,0x00,0x00,0x71,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x73,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x46,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x77,0x00,0x00,0x00,0x45,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x78,0x00,0x00,0x00,0x77,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x79,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x78,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x79,0x00,0x00,0x00,0x7a,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x81,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x98,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,
-0x00,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xa6,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2c,0x00,0x06,0x00,
-0x09,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,
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-0xa8,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
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-0x0e,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xab,0x01,0x00,0x00,0x03,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xac,0x01,0x00,0x00,0x13,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xad,0x01,0x00,0x00,
-0x14,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xae,0x01,0x00,0x00,0x05,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xaf,0x01,0x00,0x00,0x15,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xb0,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xb1,0x01,0x00,0x00,0x16,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
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-0x41,0x00,0x00,0x00,0xb0,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x6a,0x01,0x00,0x00,0x67,0x01,0x00,0x00,
-0x81,0x00,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x6b,0x01,0x00,0x00,0x5f,0x00,0x00,0x00,0x64,0x01,0x00,0x00,
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-0x72,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x75,0x01,0x00,0x00,0x41,0x00,0x00,0x00,0xb1,0x01,0x00,0x00,
-0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x76,0x01,0x00,0x00,
-0x67,0x01,0x00,0x00,0x2d,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x77,0x01,0x00,0x00,0x40,0x00,0x00,0x00,
-0xa9,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x78,0x01,0x00,0x00,0x5f,0x00,0x00,0x00,0x77,0x01,0x00,0x00,
-0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x79,0x01,0x00,0x00,
-0x78,0x01,0x00,0x00,0x47,0x00,0x00,0x00,0xc5,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x7a,0x01,0x00,0x00,0x76,0x01,0x00,0x00,
-0x79,0x01,0x00,0x00,0x70,0x00,0x04,0x00,0x42,0x00,0x00,0x00,
-0x7b,0x01,0x00,0x00,0x7a,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,
-0x42,0x00,0x00,0x00,0x7d,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0x53,0x00,0x00,0x00,0x7b,0x01,0x00,0x00,
-0x59,0x00,0x00,0x00,0x73,0x00,0x04,0x00,0x45,0x00,0x00,0x00,
-0x7e,0x01,0x00,0x00,0x7d,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x50,0x00,0x00,0x00,0x7f,0x01,0x00,0x00,0x7a,0x00,0x00,0x00,
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-0x27,0x00,0x00,0x00,0x71,0x00,0x00,0x00,0x87,0x01,0x00,0x00,
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-0x88,0x01,0x00,0x00,0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x8a,0x01,0x00,0x00,0x89,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8b,0x01,0x00,0x00,0x41,0x00,0x00,0x00,
-0xb2,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8d,0x01,0x00,0x00,0x8a,0x01,0x00,0x00,0x81,0x00,0x00,0x00,
-0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8e,0x01,0x00,0x00,
-0x5f,0x00,0x00,0x00,0x87,0x01,0x00,0x00,0xc4,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8f,0x01,0x00,0x00,0x8e,0x01,0x00,0x00,
-0x2d,0x00,0x00,0x00,0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
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-0xc5,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x91,0x01,0x00,0x00,
-0x8d,0x01,0x00,0x00,0x90,0x01,0x00,0x00,0x70,0x00,0x04,0x00,
-0x42,0x00,0x00,0x00,0x92,0x01,0x00,0x00,0x91,0x01,0x00,0x00,
-0x0c,0x00,0x08,0x00,0x42,0x00,0x00,0x00,0x94,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x53,0x00,0x00,0x00,
-0x92,0x01,0x00,0x00,0x59,0x00,0x00,0x00,0x73,0x00,0x04,0x00,
-0x45,0x00,0x00,0x00,0x95,0x01,0x00,0x00,0x94,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0x50,0x00,0x00,0x00,0x96,0x01,0x00,0x00,
-0x7a,0x00,0x00,0x00,0x4e,0x00,0x00,0x00,0x8b,0x01,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x96,0x01,0x00,0x00,0x95,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x98,0x01,0x00,0x00,
-0x41,0x00,0x00,0x00,0xb3,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x99,0x01,0x00,0x00,0x8a,0x01,0x00,0x00,
-0x2d,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9a,0x01,0x00,0x00,0x40,0x00,0x00,0x00,0xac,0x01,0x00,0x00,
-0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9b,0x01,0x00,0x00,
-0x5f,0x00,0x00,0x00,0x9a,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9c,0x01,0x00,0x00,0x9b,0x01,0x00,0x00,
-0x47,0x00,0x00,0x00,0xc5,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9d,0x01,0x00,0x00,0x99,0x01,0x00,0x00,0x9c,0x01,0x00,0x00,
-0x70,0x00,0x04,0x00,0x42,0x00,0x00,0x00,0x9e,0x01,0x00,0x00,
-0x9d,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,0x42,0x00,0x00,0x00,
-0xa0,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x53,0x00,0x00,0x00,0x9e,0x01,0x00,0x00,0x59,0x00,0x00,0x00,
-0x73,0x00,0x04,0x00,0x45,0x00,0x00,0x00,0xa1,0x01,0x00,0x00,
-0xa0,0x01,0x00,0x00,0x41,0x00,0x06,0x00,0x50,0x00,0x00,0x00,
-0xa2,0x01,0x00,0x00,0x7a,0x00,0x00,0x00,0x4e,0x00,0x00,0x00,
-0x98,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0xa2,0x01,0x00,0x00,
-0xa1,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0xa8,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa8,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t dequant_q5_1_len = 6412;
-
-unsigned char dequant_q5_k_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x9e,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x4e,0x00,0x00,0x00,0x11,0x01,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x16,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x1e,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x30,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x45,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x47,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x49,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4a,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4a,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4a,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4a,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x30,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x4b,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0xb0,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x4c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x4c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4e,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4e,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0e,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x0f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x0f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x0f,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x11,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x11,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x87,0x01,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x00,0x01,0x00,0x00,0x14,0x00,0x02,0x00,0x11,0x00,0x00,0x00,
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-0x22,0x00,0x00,0x00,0x69,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x84,0x01,0x00,0x00,0x83,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x0d,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x0d,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x86,0x01,0x00,0x00,
-0x90,0x01,0x00,0x00,0x26,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x0a,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x0c,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x11,0x00,0x00,0x00,0x97,0x01,0x00,0x00,
-0x8a,0x01,0x00,0x00,0x0a,0x00,0x00,0x00,0x8d,0x01,0x00,0x00,
-0x2c,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x8e,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x97,0x01,0x00,0x00,
-0x88,0x01,0x00,0x00,0x8e,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8e,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x88,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x88,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t dequant_q5_k_len = 5980;
-
-unsigned char dequant_q6_k_data[] = {
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-0x73,0x00,0x04,0x00,0x5a,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,
-0xfc,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x6d,0x00,0x00,0x00,
-0xfe,0x00,0x00,0x00,0x74,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0xde,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0xfe,0x00,0x00,0x00,
-0xfd,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x0d,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x0d,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x0b,0x01,0x00,0x00,
-0x26,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x0a,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x0c,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x11,0x00,0x00,0x00,0x0c,0x01,0x00,0x00,0x05,0x01,0x00,0x00,
-0x0a,0x00,0x00,0x00,0x08,0x01,0x00,0x00,0x2c,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x09,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x0c,0x01,0x00,0x00,0x03,0x01,0x00,0x00,
-0x09,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x09,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x03,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x03,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t dequant_q6_k_len = 4272;
-
-unsigned char dequant_q8_0_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x4c,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,
-0x4c,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x00,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x29,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x29,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x47,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x48,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x48,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x49,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x4a,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4a,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x4a,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4c,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4c,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x5e,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x5f,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x5f,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x5f,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x61,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
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-0x0b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x0a,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x15,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x1e,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x1e,0x00,0x07,0x00,
-0x29,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
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-0x15,0x00,0x04,0x00,0x46,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
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-0x4a,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x4b,0x00,0x00,0x00,
-0x4c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
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-0x06,0x00,0x00,0x00,0xe9,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0x45,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xeb,0x00,0x00,0x00,0x40,0x00,0x00,0x00,0x45,0x01,0x00,0x00,
-0x41,0x00,0x08,0x00,0x6b,0x00,0x00,0x00,0xec,0x00,0x00,0x00,
-0x4c,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x67,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x46,0x00,0x00,0x00,0xed,0x00,0x00,0x00,0xec,0x00,0x00,0x00,
-0x6f,0x00,0x04,0x00,0x42,0x00,0x00,0x00,0xee,0x00,0x00,0x00,
-0xed,0x00,0x00,0x00,0x85,0x00,0x05,0x00,0x42,0x00,0x00,0x00,
-0xef,0x00,0x00,0x00,0x52,0x00,0x00,0x00,0xee,0x00,0x00,0x00,
-0x73,0x00,0x04,0x00,0x45,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,
-0xef,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x4f,0x00,0x00,0x00,
-0xf1,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0xe9,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0xf1,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf9,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0x46,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x46,0x01,0x00,0x00,0x41,0x00,0x08,0x00,
-0x6b,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x27,0x00,0x00,0x00,0x67,0x00,0x00,0x00,
-0xfa,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x46,0x00,0x00,0x00,
-0xfc,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0x6f,0x00,0x04,0x00,
-0x42,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x42,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,
-0x52,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,0x73,0x00,0x04,0x00,
-0x45,0x00,0x00,0x00,0xff,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x4f,0x00,0x00,0x00,0x00,0x01,0x00,0x00,
-0x61,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x00,0x01,0x00,0x00,0xff,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x02,0x01,0x00,0x00,
-0x41,0x00,0x00,0x00,0x47,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x04,0x01,0x00,0x00,0x40,0x00,0x00,0x00,
-0x47,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x6b,0x00,0x00,0x00,
-0x05,0x01,0x00,0x00,0x4c,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0x67,0x00,0x00,0x00,0x04,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x46,0x00,0x00,0x00,0x06,0x01,0x00,0x00,
-0x05,0x01,0x00,0x00,0x6f,0x00,0x04,0x00,0x42,0x00,0x00,0x00,
-0x07,0x01,0x00,0x00,0x06,0x01,0x00,0x00,0x85,0x00,0x05,0x00,
-0x42,0x00,0x00,0x00,0x08,0x01,0x00,0x00,0x52,0x00,0x00,0x00,
-0x07,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x45,0x00,0x00,0x00,
-0x09,0x01,0x00,0x00,0x08,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x4f,0x00,0x00,0x00,0x0a,0x01,0x00,0x00,0x61,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x02,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x0a,0x01,0x00,0x00,0x09,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x12,0x01,0x00,0x00,0x41,0x00,0x00,0x00,
-0x48,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x13,0x01,0x00,0x00,0x40,0x00,0x00,0x00,0x48,0x01,0x00,0x00,
-0x41,0x00,0x08,0x00,0x6b,0x00,0x00,0x00,0x14,0x01,0x00,0x00,
-0x4c,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x67,0x00,0x00,0x00,0x13,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x46,0x00,0x00,0x00,0x15,0x01,0x00,0x00,0x14,0x01,0x00,0x00,
-0x6f,0x00,0x04,0x00,0x42,0x00,0x00,0x00,0x16,0x01,0x00,0x00,
-0x15,0x01,0x00,0x00,0x85,0x00,0x05,0x00,0x42,0x00,0x00,0x00,
-0x17,0x01,0x00,0x00,0x52,0x00,0x00,0x00,0x16,0x01,0x00,0x00,
-0x73,0x00,0x04,0x00,0x45,0x00,0x00,0x00,0x18,0x01,0x00,0x00,
-0x17,0x01,0x00,0x00,0x41,0x00,0x06,0x00,0x4f,0x00,0x00,0x00,
-0x19,0x01,0x00,0x00,0x61,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0x12,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x19,0x01,0x00,0x00,
-0x18,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x1b,0x01,0x00,0x00,0x41,0x00,0x00,0x00,0x49,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1d,0x01,0x00,0x00,
-0x40,0x00,0x00,0x00,0x49,0x01,0x00,0x00,0x41,0x00,0x08,0x00,
-0x6b,0x00,0x00,0x00,0x1e,0x01,0x00,0x00,0x4c,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x27,0x00,0x00,0x00,0x67,0x00,0x00,0x00,
-0x1d,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x46,0x00,0x00,0x00,
-0x1f,0x01,0x00,0x00,0x1e,0x01,0x00,0x00,0x6f,0x00,0x04,0x00,
-0x42,0x00,0x00,0x00,0x20,0x01,0x00,0x00,0x1f,0x01,0x00,0x00,
-0x85,0x00,0x05,0x00,0x42,0x00,0x00,0x00,0x21,0x01,0x00,0x00,
-0x52,0x00,0x00,0x00,0x20,0x01,0x00,0x00,0x73,0x00,0x04,0x00,
-0x45,0x00,0x00,0x00,0x22,0x01,0x00,0x00,0x21,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0x4f,0x00,0x00,0x00,0x23,0x01,0x00,0x00,
-0x61,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x1b,0x01,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x23,0x01,0x00,0x00,0x22,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x2b,0x01,0x00,0x00,
-0x41,0x00,0x00,0x00,0x4a,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x2c,0x01,0x00,0x00,0x40,0x00,0x00,0x00,
-0x4a,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x6b,0x00,0x00,0x00,
-0x2d,0x01,0x00,0x00,0x4c,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0x67,0x00,0x00,0x00,0x2c,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x46,0x00,0x00,0x00,0x2e,0x01,0x00,0x00,
-0x2d,0x01,0x00,0x00,0x6f,0x00,0x04,0x00,0x42,0x00,0x00,0x00,
-0x2f,0x01,0x00,0x00,0x2e,0x01,0x00,0x00,0x85,0x00,0x05,0x00,
-0x42,0x00,0x00,0x00,0x30,0x01,0x00,0x00,0x52,0x00,0x00,0x00,
-0x2f,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x45,0x00,0x00,0x00,
-0x31,0x01,0x00,0x00,0x30,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x4f,0x00,0x00,0x00,0x32,0x01,0x00,0x00,0x61,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x2b,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x32,0x01,0x00,0x00,0x31,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x34,0x01,0x00,0x00,0x41,0x00,0x00,0x00,
-0x4b,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x36,0x01,0x00,0x00,0x40,0x00,0x00,0x00,0x4b,0x01,0x00,0x00,
-0x41,0x00,0x08,0x00,0x6b,0x00,0x00,0x00,0x37,0x01,0x00,0x00,
-0x4c,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x67,0x00,0x00,0x00,0x36,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x46,0x00,0x00,0x00,0x38,0x01,0x00,0x00,0x37,0x01,0x00,0x00,
-0x6f,0x00,0x04,0x00,0x42,0x00,0x00,0x00,0x39,0x01,0x00,0x00,
-0x38,0x01,0x00,0x00,0x85,0x00,0x05,0x00,0x42,0x00,0x00,0x00,
-0x3a,0x01,0x00,0x00,0x52,0x00,0x00,0x00,0x39,0x01,0x00,0x00,
-0x73,0x00,0x04,0x00,0x45,0x00,0x00,0x00,0x3b,0x01,0x00,0x00,
-0x3a,0x01,0x00,0x00,0x41,0x00,0x06,0x00,0x4f,0x00,0x00,0x00,
-0x3c,0x01,0x00,0x00,0x61,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0x34,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x3c,0x01,0x00,0x00,
-0x3b,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x88,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x88,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t dequant_q8_0_len = 4780;
-
-unsigned char diag_mask_inf_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x53,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x09,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x45,0x00,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x15,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x37,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x38,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x38,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x38,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x3a,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x3a,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x42,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x43,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x43,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x43,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x45,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x45,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,
-0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x17,0x00,0x04,0x00,0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x0a,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x1e,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x16,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x15,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x16,0x00,0x00,0x00,0x17,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x18,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x18,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x14,0x00,0x02,0x00,0x1d,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x18,0x00,0x00,0x00,0x2a,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x18,0x00,0x00,0x00,
-0x2e,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0x36,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x37,0x00,0x00,0x00,0x36,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x38,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x39,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x39,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x36,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x42,0x00,0x00,0x00,0x36,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x43,0x00,0x00,0x00,0x42,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x44,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x43,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x44,0x00,0x00,0x00,0x45,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x4a,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x2c,0x00,0x06,0x00,
-0x09,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,0x4a,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x36,0x00,0x00,0x00,0x52,0x00,0x00,0x00,0x00,0x00,0x80,0xff,
-0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x05,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x4c,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfb,0x00,0x03,0x00,0x11,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x4d,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x17,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0xae,0x00,0x05,0x00,0x1d,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x1e,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x1f,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x4c,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x20,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x26,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x26,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,
-0x2b,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x2a,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x2b,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,
-0x2f,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x2f,0x00,0x00,0x00,0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x31,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x31,0x00,0x00,0x00,0xac,0x00,0x05,0x00,
-0x1d,0x00,0x00,0x00,0x33,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x35,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x33,0x00,0x00,0x00,
-0x34,0x00,0x00,0x00,0x40,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x34,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x3e,0x00,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x3f,0x00,0x00,0x00,
-0x52,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x35,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x40,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x3e,0x00,0x00,0x00,0x47,0x00,0x00,0x00,0x45,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x36,0x00,0x00,0x00,0x48,0x00,0x00,0x00,0x47,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x3e,0x00,0x00,0x00,0x49,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x49,0x00,0x00,0x00,0x48,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x35,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x35,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x4c,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x4c,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t diag_mask_inf_f32_len = 1504;
-
-unsigned char div_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x67,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x17,0x00,0x00,0x00,0x2f,0x01,0x00,0x00,0x3f,0x01,0x00,0x00,
-0x4b,0x01,0x00,0x00,0x56,0x01,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x3c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x44,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x48,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x50,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x15,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x54,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x58,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x17,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x60,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x64,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x68,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x6c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x15,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x2f,0x01,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x3c,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x3d,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x3d,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x3d,0x01,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x3f,0x01,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x3f,0x01,0x00,0x00,
-0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x48,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x49,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x49,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x49,0x01,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4b,0x01,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x4b,0x01,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x53,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x54,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
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-0x17,0x00,0x00,0x00,0x26,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xb6,0x01,0x00,0x00,0xb5,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb7,0x01,0x00,0x00,
-0xa5,0x01,0x00,0x00,0xb6,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb8,0x01,0x00,0x00,0xb3,0x01,0x00,0x00,
-0xb7,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x47,0x01,0x00,0x00,0x42,0x01,0x00,0x00,0xb8,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0xc2,0x01,0x00,0x00,
-0x17,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xc3,0x01,0x00,0x00,0xc2,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0xc4,0x01,0x00,0x00,
-0x17,0x00,0x00,0x00,0x1d,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xc5,0x01,0x00,0x00,0xc4,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc6,0x01,0x00,0x00,
-0xc3,0x01,0x00,0x00,0xc5,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1a,0x00,0x00,0x00,0xc7,0x01,0x00,0x00,0x17,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xc8,0x01,0x00,0x00,0xc7,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc9,0x01,0x00,0x00,0xc6,0x01,0x00,0x00,
-0xc8,0x01,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xca,0x01,0x00,0x00,0x33,0x01,0x00,0x00,0xc9,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xce,0x01,0x00,0x00,
-0xca,0x01,0x00,0x00,0xc3,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd1,0x01,0x00,0x00,0xce,0x01,0x00,0x00,
-0xc5,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd4,0x01,0x00,0x00,0xd1,0x01,0x00,0x00,0xc8,0x01,0x00,0x00,
-0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd7,0x01,0x00,0x00,
-0x33,0x01,0x00,0x00,0xd4,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xdc,0x01,0x00,0x00,0xc5,0x01,0x00,0x00,
-0xc8,0x01,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdd,0x01,0x00,0x00,0xd7,0x01,0x00,0x00,0xdc,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe1,0x01,0x00,0x00,
-0xdd,0x01,0x00,0x00,0xc5,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe4,0x01,0x00,0x00,0xe1,0x01,0x00,0x00,
-0xc8,0x01,0x00,0x00,0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe9,0x01,0x00,0x00,0xd7,0x01,0x00,0x00,0xe4,0x01,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xec,0x01,0x00,0x00,
-0xe9,0x01,0x00,0x00,0xc8,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf5,0x01,0x00,0x00,0xec,0x01,0x00,0x00,
-0xc8,0x01,0x00,0x00,0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf6,0x01,0x00,0x00,0xe9,0x01,0x00,0x00,0xf5,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0xf8,0x01,0x00,0x00,
-0x17,0x00,0x00,0x00,0x58,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xf9,0x01,0x00,0x00,0xf8,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xfa,0x01,0x00,0x00,
-0xca,0x01,0x00,0x00,0xf9,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1a,0x00,0x00,0x00,0xfc,0x01,0x00,0x00,0x17,0x00,0x00,0x00,
-0x5d,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xfd,0x01,0x00,0x00,0xfc,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xfe,0x01,0x00,0x00,0xdd,0x01,0x00,0x00,
-0xfd,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xff,0x01,0x00,0x00,0xfa,0x01,0x00,0x00,0xfe,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0x01,0x02,0x00,0x00,
-0x17,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x02,0x02,0x00,0x00,0x01,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x03,0x02,0x00,0x00,
-0xec,0x01,0x00,0x00,0x02,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x04,0x02,0x00,0x00,0xff,0x01,0x00,0x00,
-0x03,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,
-0x06,0x02,0x00,0x00,0x17,0x00,0x00,0x00,0x69,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x07,0x02,0x00,0x00,
-0x06,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x08,0x02,0x00,0x00,0xf6,0x01,0x00,0x00,0x07,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x09,0x02,0x00,0x00,
-0x04,0x02,0x00,0x00,0x08,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0x50,0x01,0x00,0x00,0x51,0x01,0x00,0x00,0x4b,0x01,0x00,0x00,
-0x34,0x01,0x00,0x00,0x09,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x14,0x00,0x00,0x00,0x52,0x01,0x00,0x00,0x51,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0x49,0x02,0x00,0x00,
-0x17,0x00,0x00,0x00,0xad,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x4a,0x02,0x00,0x00,0x49,0x02,0x00,0x00,
-0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x4b,0x02,0x00,0x00,
-0xca,0x01,0x00,0x00,0x4a,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1a,0x00,0x00,0x00,0x4c,0x02,0x00,0x00,0x17,0x00,0x00,0x00,
-0xb1,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x4d,0x02,0x00,0x00,0x4c,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x4e,0x02,0x00,0x00,0x4b,0x02,0x00,0x00,
-0x4d,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,
-0x50,0x02,0x00,0x00,0x17,0x00,0x00,0x00,0xb6,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x51,0x02,0x00,0x00,
-0x50,0x02,0x00,0x00,0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x52,0x02,0x00,0x00,0xdd,0x01,0x00,0x00,0x51,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0x53,0x02,0x00,0x00,
-0x17,0x00,0x00,0x00,0xba,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x54,0x02,0x00,0x00,0x53,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x55,0x02,0x00,0x00,
-0x52,0x02,0x00,0x00,0x54,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x56,0x02,0x00,0x00,0x4e,0x02,0x00,0x00,
-0x55,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,
-0x58,0x02,0x00,0x00,0x17,0x00,0x00,0x00,0xc0,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x59,0x02,0x00,0x00,
-0x58,0x02,0x00,0x00,0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x5a,0x02,0x00,0x00,0xec,0x01,0x00,0x00,0x59,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0x5b,0x02,0x00,0x00,
-0x17,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x5c,0x02,0x00,0x00,0x5b,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x5d,0x02,0x00,0x00,
-0x5a,0x02,0x00,0x00,0x5c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x5e,0x02,0x00,0x00,0x56,0x02,0x00,0x00,
-0x5d,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,
-0x60,0x02,0x00,0x00,0x17,0x00,0x00,0x00,0xca,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x61,0x02,0x00,0x00,
-0x60,0x02,0x00,0x00,0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x62,0x02,0x00,0x00,0xf6,0x01,0x00,0x00,0x61,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0x63,0x02,0x00,0x00,
-0x17,0x00,0x00,0x00,0xce,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x64,0x02,0x00,0x00,0x63,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x65,0x02,0x00,0x00,
-0x62,0x02,0x00,0x00,0x64,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x66,0x02,0x00,0x00,0x5e,0x02,0x00,0x00,
-0x65,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0x50,0x01,0x00,0x00,
-0x5b,0x01,0x00,0x00,0x56,0x01,0x00,0x00,0x34,0x01,0x00,0x00,
-0x66,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x14,0x00,0x00,0x00,
-0x5c,0x01,0x00,0x00,0x5b,0x01,0x00,0x00,0x88,0x00,0x05,0x00,
-0x14,0x00,0x00,0x00,0x5d,0x01,0x00,0x00,0x52,0x01,0x00,0x00,
-0x5c,0x01,0x00,0x00,0x41,0x00,0x06,0x00,0x50,0x01,0x00,0x00,
-0x5e,0x01,0x00,0x00,0x3f,0x01,0x00,0x00,0x34,0x01,0x00,0x00,
-0x47,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x5e,0x01,0x00,0x00,
-0x5d,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x62,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x62,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t div_f32_len = 4276;
-
-unsigned char gelu_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x4b,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x09,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x38,0x00,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x12,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x21,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x22,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x24,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x24,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x35,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x36,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x36,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x36,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x38,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x38,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x48,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x11,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x1e,0x00,0x06,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x13,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x13,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x17,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x14,0x00,0x02,0x00,0x1a,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x21,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x22,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x26,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x11,0x00,0x00,0x00,0x2a,0x00,0x00,0x00,0x2a,0x42,0x4c,0x3f,
-0x2b,0x00,0x04,0x00,0x11,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,
-0x00,0x00,0x80,0x3f,0x2b,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
-0x2e,0x00,0x00,0x00,0x13,0x27,0x37,0x3d,0x1d,0x00,0x03,0x00,
-0x35,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x36,0x00,0x00,0x00,0x35,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x37,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x36,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x37,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x00,0x00,0x00,0x3f,0x2b,0x00,0x04,0x00,
-0x11,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,0x00,0x00,0x00,0x40,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x46,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x47,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2c,0x00,0x06,0x00,
-0x09,0x00,0x00,0x00,0x48,0x00,0x00,0x00,0x46,0x00,0x00,0x00,
-0x47,0x00,0x00,0x00,0x47,0x00,0x00,0x00,0x36,0x00,0x05,0x00,
-0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x49,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfb,0x00,0x03,0x00,0x0c,0x00,0x00,0x00,0x4a,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x4a,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x0d,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0xae,0x00,0x05,0x00,
-0x1a,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x1d,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x1d,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x1c,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x49,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x1d,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x26,0x00,0x00,0x00,0x27,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x11,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x2a,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x85,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,0x11,0x00,0x00,0x00,
-0x33,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x30,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x33,0x00,0x00,0x00,0x85,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x85,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
-0x0c,0x00,0x06,0x00,0x11,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,0x88,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x42,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,
-0x41,0x00,0x00,0x00,0x83,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x43,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,0x42,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0x3c,0x00,0x00,0x00,0x43,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x26,0x00,0x00,0x00,0x45,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x45,0x00,0x00,0x00,0x44,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x49,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x49,0x00,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t gelu_f32_len = 1484;
-
-unsigned char get_rows_f16_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x87,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0a,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x35,0x00,0x00,0x00,0x74,0x00,0x00,0x00,
-0x7b,0x00,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x3c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x44,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x48,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x50,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x15,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x54,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x58,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x17,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x60,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x64,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x68,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x6c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x19,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x32,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x33,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x33,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
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-0x1e,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x60,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x62,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x62,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,
-0x66,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x65,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x67,0x00,0x00,0x00,
-0x66,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x68,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x67,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x69,0x00,0x00,0x00,
-0x63,0x00,0x00,0x00,0x68,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x6b,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x6f,0x00,0x00,0x00,0x69,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x77,0x00,0x00,0x00,
-0x6f,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,0x5d,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x7f,0x00,0x00,0x00,
-0x80,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,0x36,0x00,0x00,0x00,
-0x7e,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x70,0x00,0x00,0x00,
-0x81,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x7f,0x00,0x00,0x00,0x82,0x00,0x00,0x00,0x74,0x00,0x00,0x00,
-0x36,0x00,0x00,0x00,0x77,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x82,0x00,0x00,0x00,0x81,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x85,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x85,0x00,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t get_rows_f16_len = 2996;
-
-unsigned char get_rows_f16_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x89,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0a,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x35,0x00,0x00,0x00,0x73,0x00,0x00,0x00,
-0x7b,0x00,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x3c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x44,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x48,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x50,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x15,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x54,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x58,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x17,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x60,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x64,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x68,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x6c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x19,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x32,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x33,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x33,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x33,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x35,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x35,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x70,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x71,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x71,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x71,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x73,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x73,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x78,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x79,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x79,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x79,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x7b,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x7b,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x86,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x15,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x16,0x00,0x03,0x00,0x18,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x1e,0x00,0x1e,0x00,0x19,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
-0x1c,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x1c,0x00,0x00,0x00,0x1d,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x1e,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x1c,0x00,0x00,0x00,0x29,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x14,0x00,0x02,0x00,0x2c,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x32,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x33,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x34,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x33,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x34,0x00,0x00,0x00,0x35,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x1c,0x00,0x00,0x00,
-0x36,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x1c,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x1c,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x1c,0x00,0x00,0x00,
-0x43,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x48,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x1c,0x00,0x00,0x00,0x4e,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x1c,0x00,0x00,0x00,
-0x53,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x1c,0x00,0x00,0x00,0x59,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x1c,0x00,0x00,0x00,0x60,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x1c,0x00,0x00,0x00,
-0x65,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x1c,0x00,0x00,0x00,0x6b,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0x70,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x1e,0x00,0x03,0x00,0x71,0x00,0x00,0x00,0x70,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x72,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x71,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x72,0x00,0x00,0x00,
-0x73,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0x77,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x78,0x00,0x00,0x00,0x77,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x79,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x7a,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x79,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x7a,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x7f,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x77,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x83,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x85,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x2c,0x00,0x06,0x00,0x09,0x00,0x00,0x00,
-0x86,0x00,0x00,0x00,0x85,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x87,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfb,0x00,0x03,0x00,
-0x0c,0x00,0x00,0x00,0x88,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x88,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,
-0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x12,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x15,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x17,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,
-0x1f,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x1d,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x1f,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x17,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x2a,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x29,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x2b,0x00,0x00,0x00,0x2a,0x00,0x00,0x00,0xae,0x00,0x05,0x00,
-0x2c,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x2b,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x2f,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x2d,0x00,0x00,0x00,
-0x2e,0x00,0x00,0x00,0x2f,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x2e,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x87,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x2f,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x38,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x3b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0x3b,0x00,0x00,0x00,0x40,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x44,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x43,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x45,0x00,0x00,0x00,0x44,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x46,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x45,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x47,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0x46,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x48,0x00,0x00,0x00,0x49,0x00,0x00,0x00,
-0x35,0x00,0x00,0x00,0x36,0x00,0x00,0x00,0x47,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x1c,0x00,0x00,0x00,0x4a,0x00,0x00,0x00,
-0x49,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x4b,0x00,0x00,0x00,0x4a,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x4e,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x50,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x51,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,
-0x50,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,
-0x54,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x53,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x55,0x00,0x00,0x00,
-0x54,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x56,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x55,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x57,0x00,0x00,0x00,
-0x51,0x00,0x00,0x00,0x56,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x5a,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x59,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x5b,0x00,0x00,0x00,0x5a,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x5b,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x5d,0x00,0x00,0x00,0x57,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,0x61,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x61,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x63,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x66,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x65,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x67,0x00,0x00,0x00,0x66,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x68,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x67,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x69,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x68,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x6b,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,0x69,0x00,0x00,0x00,
-0x6e,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x76,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,
-0x5d,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x7f,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0x36,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x77,0x00,0x00,0x00,0x81,0x00,0x00,0x00,0x80,0x00,0x00,0x00,
-0x73,0x00,0x04,0x00,0x18,0x00,0x00,0x00,0x82,0x00,0x00,0x00,
-0x81,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x83,0x00,0x00,0x00,
-0x84,0x00,0x00,0x00,0x73,0x00,0x00,0x00,0x36,0x00,0x00,0x00,
-0x76,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x84,0x00,0x00,0x00,
-0x82,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x87,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x87,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t get_rows_f16_f32_len = 3028;
-
-unsigned char get_rows_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x89,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0a,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x35,0x00,0x00,0x00,0x74,0x00,0x00,0x00,
-0x7b,0x00,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
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-0x1e,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x38,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x3b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0x3b,0x00,0x00,0x00,0x40,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x44,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x43,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x45,0x00,0x00,0x00,0x44,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x46,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x45,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x47,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0x46,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x48,0x00,0x00,0x00,0x49,0x00,0x00,0x00,
-0x35,0x00,0x00,0x00,0x36,0x00,0x00,0x00,0x47,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x1c,0x00,0x00,0x00,0x4a,0x00,0x00,0x00,
-0x49,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x4b,0x00,0x00,0x00,0x4a,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x4e,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x50,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x51,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,
-0x50,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,
-0x54,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x53,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x55,0x00,0x00,0x00,
-0x54,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x56,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x55,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x57,0x00,0x00,0x00,
-0x51,0x00,0x00,0x00,0x56,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x5a,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x59,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x5b,0x00,0x00,0x00,0x5a,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x5b,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x5d,0x00,0x00,0x00,0x57,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,0x61,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x61,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x63,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x66,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x65,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x67,0x00,0x00,0x00,0x66,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x68,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x67,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x69,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x68,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x6b,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,0x69,0x00,0x00,0x00,
-0x6e,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x77,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,
-0x5d,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x7f,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0x36,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x18,0x00,0x00,0x00,0x81,0x00,0x00,0x00,0x80,0x00,0x00,0x00,
-0x73,0x00,0x04,0x00,0x70,0x00,0x00,0x00,0x82,0x00,0x00,0x00,
-0x81,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x83,0x00,0x00,0x00,
-0x84,0x00,0x00,0x00,0x74,0x00,0x00,0x00,0x36,0x00,0x00,0x00,
-0x77,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x84,0x00,0x00,0x00,
-0x82,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x87,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x87,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t get_rows_f32_len = 3028;
-
-unsigned char get_rows_f32_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x86,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x35,0x00,0x00,0x00,
-0x73,0x00,0x00,0x00,0x7a,0x00,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x34,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x48,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x4c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x50,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x15,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x58,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x17,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x64,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x68,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x19,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x32,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x33,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x33,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x33,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x35,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x35,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x70,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x71,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x71,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x71,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x73,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x73,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x77,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x78,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x78,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x78,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x7a,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x7a,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
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-0x36,0x00,0x00,0x00,0x7d,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x18,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x7f,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x7e,0x00,0x00,0x00,0x81,0x00,0x00,0x00,
-0x73,0x00,0x00,0x00,0x36,0x00,0x00,0x00,0x76,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x81,0x00,0x00,0x00,0x80,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x84,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x84,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t get_rows_f32_f32_len = 2976;
-
-unsigned char get_rows_q4_0_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xf8,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0x51,0x00,0x00,0x00,0x69,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x17,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x18,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x18,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x41,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x34,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x48,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x4c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x50,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x15,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x58,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
-0x17,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x64,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x68,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x4f,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x66,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x67,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x67,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x67,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x69,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x69,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xba,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0xbb,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xbb,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0xbb,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xbd,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xbd,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xd2,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,
-0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x16,0x00,0x03,0x00,0x08,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x17,0x00,0x04,0x00,0x09,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x12,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x13,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x1c,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x1e,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x12,0x00,0x00,0x00,0x15,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x17,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x18,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x19,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x19,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x1b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x20,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x12,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x2a,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x2f,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,
-0x33,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0x00,0x00,0x00,0x41,
-0x17,0x00,0x04,0x00,0x3f,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x40,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x40,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x42,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x43,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x46,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x49,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x1e,0x00,0x1e,0x00,0x4f,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x50,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x50,0x00,0x00,0x00,0x51,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,0x52,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x53,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x14,0x00,0x02,0x00,
-0x60,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0x66,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0x67,0x00,0x00,0x00,
-0x66,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x68,0x00,0x00,0x00,
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-0x20,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xd0,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xd3,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xd3,0x00,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t get_rows_q4_0_len = 3704;
-
-unsigned char get_rows_q4_0_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xf7,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0x51,0x00,0x00,0x00,0x69,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x17,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x18,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x18,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x41,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x34,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x48,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x4c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x50,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x15,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x58,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
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-0x4f,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x64,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,
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-0x48,0x00,0x05,0x00,0x4f,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x4f,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
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-0x48,0x00,0x04,0x00,0x67,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x67,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x67,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x69,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x69,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xba,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0xbb,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xbb,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0xbb,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
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-0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
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-0x1c,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x1e,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x12,0x00,0x00,0x00,0x15,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x17,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x18,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x19,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x19,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
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-0xf8,0x00,0x02,0x00,0xd2,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t get_rows_q4_0_f32_len = 3688;
-
-unsigned char get_rows_q4_1_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x05,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x49,0x00,0x00,0x00,
-0x59,0x00,0x00,0x00,0x71,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x16,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x17,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
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-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x49,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
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-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,
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-0x3c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x44,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x57,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x48,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,
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-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
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-0x48,0x00,0x05,0x00,0xc3,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
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-0xd7,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x20,0x00,0x00,0x00,0xd8,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0xd4,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xd8,0x00,0x00,0x00,0xd7,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xdb,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xdb,0x00,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t get_rows_q4_1_len = 3788;
-
-unsigned char get_rows_q4_1_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x04,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x49,0x00,0x00,0x00,
-0x59,0x00,0x00,0x00,0x71,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x16,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x17,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
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-0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x18,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x1a,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x49,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
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-0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x57,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,
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-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x57,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
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-0x57,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x57,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x3c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x44,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x57,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x48,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,
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-0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x50,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
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-0x48,0x00,0x05,0x00,0x6f,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
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-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
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-0x48,0x00,0x05,0x00,0xc3,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
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-0x3e,0x00,0x03,0x00,0xce,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd4,0x00,0x00,0x00,
-0xca,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x51,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,0x03,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0xcd,0x00,0x00,0x00,
-0xd7,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0xd4,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0xd7,0x00,0x00,0x00,
-0xd6,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xda,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xda,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t get_rows_q4_1_f32_len = 3772;
-
-unsigned char get_rows_q5_0_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x4d,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x1d,0x00,0x00,0x00,0x72,0x00,0x00,0x00,
-0x7f,0x00,0x00,0x00,0x97,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x18,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x1a,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x1b,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x1d,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1d,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x72,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x34,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x48,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x4c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x50,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x15,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x58,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x17,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x64,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x68,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x7d,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x94,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x95,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x95,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x95,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x97,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x97,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xe8,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0xe9,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xe9,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0xe9,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xeb,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xeb,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x00,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,
-0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
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-0x02,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x12,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x13,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x1c,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x1c,0x00,0x04,0x00,0x18,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x17,0x00,0x00,0x00,0x1e,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
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-0x30,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
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-0x24,0x01,0x00,0x00,0x23,0x01,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x25,0x01,0x00,0x00,
-0x24,0x01,0x00,0x00,0x17,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,
-0x1e,0x00,0x00,0x00,0x26,0x01,0x00,0x00,0x25,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x29,0x01,0x00,0x00,
-0xda,0x00,0x00,0x00,0x45,0x00,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x2a,0x01,0x00,0x00,0x20,0x01,0x00,0x00,
-0x29,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x2b,0x01,0x00,0x00,0x2a,0x01,0x00,0x00,0x17,0x00,0x00,0x00,
-0x7c,0x00,0x04,0x00,0x1e,0x00,0x00,0x00,0x2c,0x01,0x00,0x00,
-0x2b,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x51,0x00,0x00,0x00,
-0x32,0x01,0x00,0x00,0x1d,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,
-0xd6,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0xda,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,0x33,0x01,0x00,0x00,
-0x32,0x01,0x00,0x00,0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x34,0x01,0x00,0x00,0x33,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x36,0x01,0x00,0x00,0x34,0x01,0x00,0x00,
-0x56,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x39,0x01,0x00,0x00,0x26,0x01,0x00,0x00,0xc5,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x3a,0x01,0x00,0x00,0x36,0x01,0x00,0x00,
-0x39,0x01,0x00,0x00,0x70,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x3b,0x01,0x00,0x00,0x3a,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x3d,0x01,0x00,0x00,0x34,0x01,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x40,0x01,0x00,0x00,0x2c,0x01,0x00,0x00,0xc5,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x41,0x01,0x00,0x00,0x3d,0x01,0x00,0x00,
-0x40,0x01,0x00,0x00,0x70,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x42,0x01,0x00,0x00,0x41,0x01,0x00,0x00,0x50,0x00,0x05,0x00,
-0x09,0x00,0x00,0x00,0x43,0x01,0x00,0x00,0x3b,0x01,0x00,0x00,
-0x42,0x01,0x00,0x00,0x83,0x00,0x05,0x00,0x09,0x00,0x00,0x00,
-0x45,0x01,0x00,0x00,0x43,0x01,0x00,0x00,0x4c,0x01,0x00,0x00,
-0x8e,0x00,0x05,0x00,0x09,0x00,0x00,0x00,0x47,0x01,0x00,0x00,
-0x45,0x01,0x00,0x00,0x12,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xdf,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0xda,0x00,0x00,0x00,
-0x51,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,
-0x47,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x73,0x00,0x04,0x00,
-0x12,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x23,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,
-0xeb,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xf4,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x51,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0x47,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x73,0x00,0x04,0x00,0x12,0x00,0x00,0x00,
-0xfd,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x23,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
-0x1f,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xfe,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x01,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x01,0x01,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t get_rows_q5_0_len = 4232;
-
-unsigned char get_rows_q5_0_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x4c,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x1d,0x00,0x00,0x00,0x72,0x00,0x00,0x00,
-0x7f,0x00,0x00,0x00,0x97,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x18,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x1a,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x1b,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x1d,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1d,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x72,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x34,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x48,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x4c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x50,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x15,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x58,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x17,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x64,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x68,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x7d,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x94,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x95,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x95,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x95,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x97,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x97,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xe8,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0xe9,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xe9,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0xe9,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xeb,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xeb,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xff,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,
-0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x16,0x00,0x03,0x00,0x08,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x17,0x00,0x04,0x00,0x09,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x12,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x13,0x00,0x00,0x00,
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-0xc2,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc4,0x00,0x00,0x00,0x79,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x81,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,
-0x7f,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc9,0x00,0x00,0x00,
-0x84,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xca,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,
-0xc9,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x81,0x00,0x00,0x00,
-0xcd,0x00,0x00,0x00,0x7f,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xce,0x00,0x00,0x00,
-0xcd,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xcf,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,0xce,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xca,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x86,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd5,0x00,0x00,0x00,0x76,0x00,0x00,0x00,
-0xd4,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd6,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0xd5,0x00,0x00,0x00,
-0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd9,0x00,0x00,0x00,
-0x76,0x00,0x00,0x00,0xd4,0x00,0x00,0x00,0x86,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xda,0x00,0x00,0x00,0xd9,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdf,0x00,0x00,0x00,0x76,0x00,0x00,0x00,0xd9,0x00,0x00,0x00,
-0x41,0x00,0x07,0x00,0x23,0x00,0x00,0x00,0x0f,0x01,0x00,0x00,
-0x1d,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,
-0x1f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x12,0x00,0x00,0x00,
-0x10,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,0x73,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x11,0x01,0x00,0x00,0x10,0x01,0x00,0x00,
-0x41,0x00,0x08,0x00,0x2c,0x00,0x00,0x00,0x15,0x01,0x00,0x00,
-0x1d,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,
-0x2b,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x13,0x00,0x00,0x00,0x16,0x01,0x00,0x00,0x15,0x01,0x00,0x00,
-0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x17,0x01,0x00,0x00,
-0x16,0x01,0x00,0x00,0xc4,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x18,0x01,0x00,0x00,0x17,0x01,0x00,0x00,0x30,0x00,0x00,0x00,
-0x41,0x00,0x08,0x00,0x2c,0x00,0x00,0x00,0x1c,0x01,0x00,0x00,
-0x1d,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,
-0x2b,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x13,0x00,0x00,0x00,0x1d,0x01,0x00,0x00,0x1c,0x01,0x00,0x00,
-0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x1e,0x01,0x00,0x00,
-0x1d,0x01,0x00,0x00,0xc5,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x1f,0x01,0x00,0x00,0x18,0x01,0x00,0x00,0x1e,0x01,0x00,0x00,
-0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x22,0x01,0x00,0x00,
-0x1f,0x01,0x00,0x00,0xda,0x00,0x00,0x00,0xc4,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x23,0x01,0x00,0x00,0x22,0x01,0x00,0x00,
-0x3f,0x00,0x00,0x00,0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x24,0x01,0x00,0x00,0x23,0x01,0x00,0x00,0x17,0x00,0x00,0x00,
-0x7c,0x00,0x04,0x00,0x1e,0x00,0x00,0x00,0x25,0x01,0x00,0x00,
-0x24,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x28,0x01,0x00,0x00,0xda,0x00,0x00,0x00,0x45,0x00,0x00,0x00,
-0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x29,0x01,0x00,0x00,
-0x1f,0x01,0x00,0x00,0x28,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x2a,0x01,0x00,0x00,0x29,0x01,0x00,0x00,
-0x17,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,0x1e,0x00,0x00,0x00,
-0x2b,0x01,0x00,0x00,0x2a,0x01,0x00,0x00,0x41,0x00,0x08,0x00,
-0x51,0x00,0x00,0x00,0x31,0x01,0x00,0x00,0x1d,0x00,0x00,0x00,
-0x1f,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
-0xda,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x32,0x01,0x00,0x00,0x31,0x01,0x00,0x00,0x71,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x33,0x01,0x00,0x00,0x32,0x01,0x00,0x00,
-0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x35,0x01,0x00,0x00,
-0x33,0x01,0x00,0x00,0x56,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x38,0x01,0x00,0x00,0x25,0x01,0x00,0x00,
-0xc5,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x39,0x01,0x00,0x00,
-0x35,0x01,0x00,0x00,0x38,0x01,0x00,0x00,0x70,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x3a,0x01,0x00,0x00,0x39,0x01,0x00,0x00,
-0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x3c,0x01,0x00,0x00,
-0x33,0x01,0x00,0x00,0x3f,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x3f,0x01,0x00,0x00,0x2b,0x01,0x00,0x00,
-0xc5,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x40,0x01,0x00,0x00,
-0x3c,0x01,0x00,0x00,0x3f,0x01,0x00,0x00,0x70,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x41,0x01,0x00,0x00,0x40,0x01,0x00,0x00,
-0x50,0x00,0x05,0x00,0x09,0x00,0x00,0x00,0x42,0x01,0x00,0x00,
-0x3a,0x01,0x00,0x00,0x41,0x01,0x00,0x00,0x83,0x00,0x05,0x00,
-0x09,0x00,0x00,0x00,0x44,0x01,0x00,0x00,0x42,0x01,0x00,0x00,
-0x4b,0x01,0x00,0x00,0x8e,0x00,0x05,0x00,0x09,0x00,0x00,0x00,
-0x46,0x01,0x00,0x00,0x44,0x01,0x00,0x00,0x11,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xee,0x00,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xdf,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,0xee,0x00,0x00,0x00,
-0xda,0x00,0x00,0x00,0x51,0x00,0x05,0x00,0x08,0x00,0x00,0x00,
-0xf2,0x00,0x00,0x00,0x46,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0xf3,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,
-0xeb,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xf4,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x51,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0x46,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0xf3,0x00,0x00,0x00,
-0xfd,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,
-0xfa,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0xfd,0x00,0x00,0x00,
-0xfc,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x00,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x00,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t get_rows_q5_0_f32_len = 4216;
-
-unsigned char get_rows_q5_1_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x43,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x7b,0x00,0x00,0x00,0x93,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x16,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x17,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x18,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x18,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x18,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x1a,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x79,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x79,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x79,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x79,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x79,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x79,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x79,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x79,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x79,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x79,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x79,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x79,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x79,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x79,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x79,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x38,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x79,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x79,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x40,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x79,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x44,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x79,0x00,0x00,0x00,
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-0x9b,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9d,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9e,0x00,0x00,0x00,
-0x98,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0xa1,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0xa0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xa2,0x00,0x00,0x00,0xa1,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa3,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
-0xa2,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa4,0x00,0x00,0x00,0x9e,0x00,0x00,0x00,0xa3,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0xa5,0x00,0x00,0x00,0xa6,0x00,0x00,0x00,
-0x93,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0xa4,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,
-0xa6,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xa8,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0xac,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0xab,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xad,0x00,0x00,0x00,0xac,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xae,0x00,0x00,0x00,0xa8,0x00,0x00,0x00,
-0xad,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,
-0xb1,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,0xb0,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xb2,0x00,0x00,0x00,
-0xb1,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb3,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0xb2,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,
-0xae,0x00,0x00,0x00,0xb3,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0xb7,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0xb6,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xb8,0x00,0x00,0x00,0xb7,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
-0xb8,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xba,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,
-0x7b,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc0,0x00,0x00,0x00,
-0x75,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x7d,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0xc2,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xc4,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0x80,0x00,0x00,0x00,
-0xc4,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc6,0x00,0x00,0x00,0xc0,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x7d,0x00,0x00,0x00,0xc9,0x00,0x00,0x00,
-0x7b,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xca,0x00,0x00,0x00,0xc9,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,
-0x86,0x00,0x00,0x00,0xca,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,
-0xcb,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd1,0x00,0x00,0x00,0x72,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd2,0x00,0x00,0x00,
-0xba,0x00,0x00,0x00,0xd1,0x00,0x00,0x00,0x89,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd5,0x00,0x00,0x00,0x72,0x00,0x00,0x00,
-0xd0,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd6,0x00,0x00,0x00,0xd5,0x00,0x00,0x00,0x71,0x00,0x00,0x00,
-0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdb,0x00,0x00,0x00,
-0x72,0x00,0x00,0x00,0xd5,0x00,0x00,0x00,0x41,0x00,0x07,0x00,
-0x20,0x00,0x00,0x00,0x0d,0x01,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0xd2,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x12,0x00,0x00,0x00,0x0e,0x01,0x00,0x00,
-0x0d,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x0f,0x01,0x00,0x00,0x0e,0x01,0x00,0x00,0x41,0x00,0x07,0x00,
-0x20,0x00,0x00,0x00,0x13,0x01,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0xd2,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x12,0x00,0x00,0x00,0x14,0x01,0x00,0x00,
-0x13,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x15,0x01,0x00,0x00,0x14,0x01,0x00,0x00,0x41,0x00,0x07,0x00,
-0x31,0x00,0x00,0x00,0x19,0x01,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0xd2,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x1a,0x01,0x00,0x00,
-0x19,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x1d,0x01,0x00,0x00,0x1a,0x01,0x00,0x00,0xd6,0x00,0x00,0x00,
-0xc4,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1e,0x01,0x00,0x00,
-0x1d,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0xc7,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x1f,0x01,0x00,0x00,0x1e,0x01,0x00,0x00,
-0x14,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,
-0x20,0x01,0x00,0x00,0x1f,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x23,0x01,0x00,0x00,0xd6,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x24,0x01,0x00,0x00,0x1a,0x01,0x00,0x00,0x23,0x01,0x00,0x00,
-0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x25,0x01,0x00,0x00,
-0x24,0x01,0x00,0x00,0x14,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,
-0x1b,0x00,0x00,0x00,0x26,0x01,0x00,0x00,0x25,0x01,0x00,0x00,
-0x41,0x00,0x08,0x00,0x4c,0x00,0x00,0x00,0x2c,0x01,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0xd2,0x00,0x00,0x00,
-0x4a,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x13,0x00,0x00,0x00,0x2d,0x01,0x00,0x00,0x2c,0x01,0x00,0x00,
-0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x2e,0x01,0x00,0x00,
-0x2d,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x30,0x01,0x00,0x00,0x2e,0x01,0x00,0x00,0x51,0x00,0x00,0x00,
-0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x33,0x01,0x00,0x00,
-0x20,0x01,0x00,0x00,0xc5,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x34,0x01,0x00,0x00,0x30,0x01,0x00,0x00,0x33,0x01,0x00,0x00,
-0x70,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x35,0x01,0x00,0x00,
-0x34,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x37,0x01,0x00,0x00,0x2e,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x3a,0x01,0x00,0x00,
-0x26,0x01,0x00,0x00,0xc5,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x3b,0x01,0x00,0x00,0x37,0x01,0x00,0x00,0x3a,0x01,0x00,0x00,
-0x70,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x3c,0x01,0x00,0x00,
-0x3b,0x01,0x00,0x00,0x50,0x00,0x05,0x00,0x09,0x00,0x00,0x00,
-0x3d,0x01,0x00,0x00,0x35,0x01,0x00,0x00,0x3c,0x01,0x00,0x00,
-0x8e,0x00,0x05,0x00,0x09,0x00,0x00,0x00,0x3f,0x01,0x00,0x00,
-0x3d,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,0x50,0x00,0x05,0x00,
-0x09,0x00,0x00,0x00,0x41,0x01,0x00,0x00,0x15,0x01,0x00,0x00,
-0x15,0x01,0x00,0x00,0x81,0x00,0x05,0x00,0x09,0x00,0x00,0x00,
-0x42,0x01,0x00,0x00,0x3f,0x01,0x00,0x00,0x41,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xea,0x00,0x00,0x00,
-0xcc,0x00,0x00,0x00,0xdb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xec,0x00,0x00,0x00,0xea,0x00,0x00,0x00,
-0xd6,0x00,0x00,0x00,0x51,0x00,0x05,0x00,0x08,0x00,0x00,0x00,
-0xee,0x00,0x00,0x00,0x42,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x73,0x00,0x04,0x00,0x12,0x00,0x00,0x00,0xef,0x00,0x00,0x00,
-0xee,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x20,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0xec,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0xf0,0x00,0x00,0x00,
-0xef,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf6,0x00,0x00,0x00,0xec,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x51,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,
-0x42,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x73,0x00,0x04,0x00,
-0x12,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x20,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,
-0xe7,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0xf6,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xfa,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xfd,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xfd,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t get_rows_q5_1_len = 4128;
-
-unsigned char get_rows_q5_1_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x42,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x7b,0x00,0x00,0x00,0x93,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x16,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x17,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x18,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x18,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x18,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
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-0xf9,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xfc,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xfc,0x00,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t get_rows_q5_1_f32_len = 4112;
-
-unsigned char get_rows_q8_0_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xf3,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
-0x4f,0x00,0x00,0x00,0x67,0x00,0x00,0x00,0xba,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x17,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x18,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x18,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x40,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4d,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4d,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4d,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4d,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x34,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4d,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x48,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4d,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x4c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x50,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,0x15,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4d,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x58,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,
-0x17,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4d,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x64,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x68,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4d,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x4d,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x64,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x65,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x65,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x65,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x67,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x67,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xb7,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0xb8,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xb8,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0xb8,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xba,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xba,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xcf,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,
-0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x16,0x00,0x03,0x00,0x08,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x17,0x00,0x04,0x00,0x09,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x12,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x13,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x1c,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x1e,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x12,0x00,0x00,0x00,0x15,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x17,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x18,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x19,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x19,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x1b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
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-0x29,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x17,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x3f,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x3f,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x41,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x42,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x45,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x1e,0x00,0x1e,0x00,0x4d,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
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-0x4e,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,0x50,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x51,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x14,0x00,0x02,0x00,
-0x5e,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0x64,0x00,0x00,0x00,
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-0x6e,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x1b,0x00,0x00,0x00,0x74,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
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-0x1b,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,
-0x7f,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x1b,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,
-0x91,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x1b,0x00,0x00,0x00,0x96,0x00,0x00,0x00,0x17,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0xb7,0x00,0x00,0x00,
-0x12,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0xb8,0x00,0x00,0x00,
-0xb7,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xb9,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0xb9,0x00,0x00,0x00,0xba,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xce,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x2c,0x00,0x06,0x00,0x3e,0x00,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xce,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xd0,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfb,0x00,0x03,0x00,
-0x41,0x00,0x00,0x00,0xd1,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd1,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x42,0x00,0x00,0x00,
-0x43,0x00,0x00,0x00,0x40,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0x43,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x46,0x00,0x00,0x00,0x44,0x00,0x00,0x00,0x45,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x42,0x00,0x00,0x00,0x48,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x49,0x00,0x00,0x00,0x48,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x42,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x45,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x51,0x00,0x00,0x00,0x52,0x00,0x00,0x00,
-0x4f,0x00,0x00,0x00,0x50,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x53,0x00,0x00,0x00,0x52,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x54,0x00,0x00,0x00,
-0x4c,0x00,0x00,0x00,0x53,0x00,0x00,0x00,0x89,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x5a,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,
-0x53,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x51,0x00,0x00,0x00,
-0x5c,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x5d,0x00,0x00,0x00,
-0x5c,0x00,0x00,0x00,0xae,0x00,0x05,0x00,0x5e,0x00,0x00,0x00,
-0x5f,0x00,0x00,0x00,0x46,0x00,0x00,0x00,0x5d,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x61,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x5f,0x00,0x00,0x00,0x60,0x00,0x00,0x00,
-0x61,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x60,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xd0,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x61,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x51,0x00,0x00,0x00,
-0x6a,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x69,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x6b,0x00,0x00,0x00,
-0x6a,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x6c,0x00,0x00,0x00,0x49,0x00,0x00,0x00,0x6b,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x51,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,
-0x4f,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x70,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x71,0x00,0x00,0x00,
-0x54,0x00,0x00,0x00,0x70,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x72,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,
-0x71,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x51,0x00,0x00,0x00,
-0x75,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x74,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x76,0x00,0x00,0x00,
-0x75,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x77,0x00,0x00,0x00,0x5a,0x00,0x00,0x00,0x76,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x78,0x00,0x00,0x00,
-0x72,0x00,0x00,0x00,0x77,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x79,0x00,0x00,0x00,0x7a,0x00,0x00,0x00,0x67,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x1b,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,0x7a,0x00,0x00,0x00,
-0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x7c,0x00,0x00,0x00,
-0x7b,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x51,0x00,0x00,0x00,
-0x80,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x7f,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x81,0x00,0x00,0x00,
-0x80,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x82,0x00,0x00,0x00,0x7c,0x00,0x00,0x00,0x81,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x51,0x00,0x00,0x00,0x85,0x00,0x00,0x00,
-0x4f,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0x85,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x87,0x00,0x00,0x00,
-0x54,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x88,0x00,0x00,0x00,0x82,0x00,0x00,0x00,
-0x87,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x51,0x00,0x00,0x00,
-0x8b,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x8c,0x00,0x00,0x00,
-0x8b,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8d,0x00,0x00,0x00,0x5a,0x00,0x00,0x00,0x8c,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8e,0x00,0x00,0x00,
-0x88,0x00,0x00,0x00,0x8d,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x51,0x00,0x00,0x00,0x92,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
-0x91,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x93,0x00,0x00,0x00,0x92,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x94,0x00,0x00,0x00,0x49,0x00,0x00,0x00,
-0x93,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x51,0x00,0x00,0x00,
-0x97,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x96,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x98,0x00,0x00,0x00,
-0x97,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x99,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x98,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9a,0x00,0x00,0x00,
-0x94,0x00,0x00,0x00,0x99,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x51,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
-0x9c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x9e,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9f,0x00,0x00,0x00,0x5a,0x00,0x00,0x00,
-0x9e,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa0,0x00,0x00,0x00,0x9a,0x00,0x00,0x00,0x9f,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa4,0x00,0x00,0x00,
-0x46,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,0x8e,0x00,0x00,0x00,
-0xa4,0x00,0x00,0x00,0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa8,0x00,0x00,0x00,0x46,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa9,0x00,0x00,0x00,
-0xa8,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x82,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xae,0x00,0x00,0x00,0x46,0x00,0x00,0x00,
-0xa8,0x00,0x00,0x00,0x41,0x00,0x07,0x00,0x20,0x00,0x00,0x00,
-0xdc,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0xa5,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x12,0x00,0x00,0x00,0xdd,0x00,0x00,0x00,0xdc,0x00,0x00,0x00,
-0x73,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xde,0x00,0x00,0x00,
-0xdd,0x00,0x00,0x00,0x41,0x00,0x08,0x00,0x29,0x00,0x00,0x00,
-0xe3,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0xa5,0x00,0x00,0x00,0x27,0x00,0x00,0x00,0xa9,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0xe4,0x00,0x00,0x00,
-0xe3,0x00,0x00,0x00,0x72,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,
-0xe5,0x00,0x00,0x00,0xe4,0x00,0x00,0x00,0x6f,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xe6,0x00,0x00,0x00,0xe5,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
-0xa9,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x41,0x00,0x08,0x00,
-0x29,0x00,0x00,0x00,0xec,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0xeb,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x13,0x00,0x00,0x00,
-0xed,0x00,0x00,0x00,0xec,0x00,0x00,0x00,0x72,0x00,0x04,0x00,
-0x1b,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0x6f,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xef,0x00,0x00,0x00,
-0xee,0x00,0x00,0x00,0x50,0x00,0x05,0x00,0x09,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0xe6,0x00,0x00,0x00,0xef,0x00,0x00,0x00,
-0x8e,0x00,0x05,0x00,0x09,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0xde,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,
-0xae,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xbf,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0xa9,0x00,0x00,0x00,
-0x51,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xc1,0x00,0x00,0x00,
-0xf2,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x73,0x00,0x04,0x00,
-0x12,0x00,0x00,0x00,0xc2,0x00,0x00,0x00,0xc1,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x20,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,
-0xba,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xc3,0x00,0x00,0x00,0xc2,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc9,0x00,0x00,0x00,
-0xbf,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x51,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x73,0x00,0x04,0x00,0x12,0x00,0x00,0x00,
-0xcc,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x20,0x00,0x00,0x00,0xcd,0x00,0x00,0x00,0xba,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0xc9,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xcd,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xd0,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xd0,0x00,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t get_rows_q8_0_len = 3644;
-
-unsigned char get_rows_q8_0_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
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-0x08,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0xb8,0x00,0x00,0x00,
-0xb7,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xb9,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0xb9,0x00,0x00,0x00,0xba,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0xc2,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xcd,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x2c,0x00,0x06,0x00,
-0x3e,0x00,0x00,0x00,0xce,0x00,0x00,0x00,0xcd,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x36,0x00,0x05,0x00,
-0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xcf,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfb,0x00,0x03,0x00,0x41,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd0,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x42,0x00,0x00,0x00,0x43,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
-0x41,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x44,0x00,0x00,0x00,0x43,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x46,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0x45,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x42,0x00,0x00,0x00,
-0x48,0x00,0x00,0x00,0x40,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x49,0x00,0x00,0x00,
-0x48,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x42,0x00,0x00,0x00,
-0x4b,0x00,0x00,0x00,0x40,0x00,0x00,0x00,0x45,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,
-0x4b,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x51,0x00,0x00,0x00,
-0x52,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x50,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x53,0x00,0x00,0x00,
-0x52,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x54,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,0x53,0x00,0x00,0x00,
-0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x5a,0x00,0x00,0x00,
-0x4c,0x00,0x00,0x00,0x53,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x51,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x5d,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,0xae,0x00,0x05,0x00,
-0x5e,0x00,0x00,0x00,0x5f,0x00,0x00,0x00,0x46,0x00,0x00,0x00,
-0x5d,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x61,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x5f,0x00,0x00,0x00,
-0x60,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x60,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xcf,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x61,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x51,0x00,0x00,0x00,0x6a,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
-0x69,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x6b,0x00,0x00,0x00,0x6a,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x49,0x00,0x00,0x00,
-0x6b,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x51,0x00,0x00,0x00,
-0x6f,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x70,0x00,0x00,0x00,
-0x6f,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x71,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x70,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x72,0x00,0x00,0x00,
-0x6c,0x00,0x00,0x00,0x71,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x51,0x00,0x00,0x00,0x75,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
-0x74,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x76,0x00,0x00,0x00,0x75,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x77,0x00,0x00,0x00,0x5a,0x00,0x00,0x00,
-0x76,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x78,0x00,0x00,0x00,0x72,0x00,0x00,0x00,0x77,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x79,0x00,0x00,0x00,0x7a,0x00,0x00,0x00,
-0x67,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x78,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0x7a,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x7c,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x51,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
-0x7f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x81,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x82,0x00,0x00,0x00,0x7c,0x00,0x00,0x00,
-0x81,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x51,0x00,0x00,0x00,
-0x85,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x84,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
-0x85,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x87,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x88,0x00,0x00,0x00,
-0x82,0x00,0x00,0x00,0x87,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x51,0x00,0x00,0x00,0x8b,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
-0x8a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x8c,0x00,0x00,0x00,0x8b,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8d,0x00,0x00,0x00,0x5a,0x00,0x00,0x00,
-0x8c,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8e,0x00,0x00,0x00,0x88,0x00,0x00,0x00,0x8d,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x51,0x00,0x00,0x00,0x92,0x00,0x00,0x00,
-0x4f,0x00,0x00,0x00,0x91,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x93,0x00,0x00,0x00,0x92,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x94,0x00,0x00,0x00,
-0x49,0x00,0x00,0x00,0x93,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x51,0x00,0x00,0x00,0x97,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
-0x96,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x98,0x00,0x00,0x00,0x97,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x99,0x00,0x00,0x00,0x54,0x00,0x00,0x00,
-0x98,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9a,0x00,0x00,0x00,0x94,0x00,0x00,0x00,0x99,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x51,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,
-0x4f,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x9e,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9f,0x00,0x00,0x00,
-0x5a,0x00,0x00,0x00,0x9e,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,0x9a,0x00,0x00,0x00,
-0x9f,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa4,0x00,0x00,0x00,0x46,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,
-0x8e,0x00,0x00,0x00,0xa4,0x00,0x00,0x00,0x89,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa8,0x00,0x00,0x00,0x46,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa9,0x00,0x00,0x00,0xa8,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xae,0x00,0x00,0x00,
-0x46,0x00,0x00,0x00,0xa8,0x00,0x00,0x00,0x41,0x00,0x07,0x00,
-0x20,0x00,0x00,0x00,0xdb,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x12,0x00,0x00,0x00,0xdc,0x00,0x00,0x00,
-0xdb,0x00,0x00,0x00,0x73,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xdd,0x00,0x00,0x00,0xdc,0x00,0x00,0x00,0x41,0x00,0x08,0x00,
-0x29,0x00,0x00,0x00,0xe2,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0xa9,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x13,0x00,0x00,0x00,
-0xe3,0x00,0x00,0x00,0xe2,0x00,0x00,0x00,0x72,0x00,0x04,0x00,
-0x1b,0x00,0x00,0x00,0xe4,0x00,0x00,0x00,0xe3,0x00,0x00,0x00,
-0x6f,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xe5,0x00,0x00,0x00,
-0xe4,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xea,0x00,0x00,0x00,0xa9,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x41,0x00,0x08,0x00,0x29,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0xea,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x13,0x00,0x00,0x00,0xec,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
-0x72,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0xec,0x00,0x00,0x00,0x6f,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xee,0x00,0x00,0x00,0xed,0x00,0x00,0x00,0x50,0x00,0x05,0x00,
-0x09,0x00,0x00,0x00,0xef,0x00,0x00,0x00,0xe5,0x00,0x00,0x00,
-0xee,0x00,0x00,0x00,0x8e,0x00,0x05,0x00,0x09,0x00,0x00,0x00,
-0xf1,0x00,0x00,0x00,0xef,0x00,0x00,0x00,0xdd,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,
-0xa0,0x00,0x00,0x00,0xae,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,
-0xa9,0x00,0x00,0x00,0x51,0x00,0x05,0x00,0x08,0x00,0x00,0x00,
-0xc1,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0xc2,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,
-0xba,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xc3,0x00,0x00,0x00,0xc1,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc9,0x00,0x00,0x00,
-0xbf,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x51,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0xc2,0x00,0x00,0x00,
-0xcc,0x00,0x00,0x00,0xba,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0xc9,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0xcc,0x00,0x00,0x00,
-0xcb,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xcf,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xcf,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t get_rows_q8_0_f32_len = 3628;
-
-unsigned char matmul_f16_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xd8,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
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-0x06,0x00,0x00,0x00,0x6f,0x02,0x00,0x00,0x54,0x02,0x00,0x00,
-0xad,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0x72,0x02,0x00,0x00,0x6f,0x02,0x00,0x00,0x37,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x74,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x72,0x02,0x00,0x00,0x73,0x02,0x00,0x00,
-0x74,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x73,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x77,0x02,0x00,0x00,
-0x5c,0x02,0x00,0x00,0xab,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x78,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0xcf,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x79,0x02,0x00,0x00,0x78,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0x7a,0x02,0x00,0x00,0x77,0x02,0x00,0x00,
-0x79,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x74,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x74,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0xc1,0x00,0x00,0x00,0x7b,0x02,0x00,0x00,0x72,0x02,0x00,0x00,
-0x67,0x02,0x00,0x00,0x7a,0x02,0x00,0x00,0x73,0x02,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x7d,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x7b,0x02,0x00,0x00,0x7c,0x02,0x00,0x00,
-0x7d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7c,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x85,0x02,0x00,0x00,
-0x5c,0x02,0x00,0x00,0xab,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x87,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0x86,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x88,0x02,0x00,0x00,0x87,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x89,0x02,0x00,0x00,0x85,0x02,0x00,0x00,
-0x88,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8a,0x02,0x00,0x00,0x3c,0x02,0x00,0x00,0x89,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8c,0x02,0x00,0x00,
-0x8a,0x02,0x00,0x00,0x54,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8e,0x02,0x00,0x00,0x8c,0x02,0x00,0x00,
-0xad,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x90,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,0xbb,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x92,0x02,0x00,0x00,
-0x90,0x02,0x00,0x00,0xab,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x94,0x02,0x00,0x00,0x92,0x02,0x00,0x00,
-0x93,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x96,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x97,0x02,0x00,0x00,
-0x94,0x02,0x00,0x00,0x96,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x99,0x02,0x00,0x00,0x97,0x02,0x00,0x00,
-0xad,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xcc,0x00,0x00,0x00,
-0x9a,0x02,0x00,0x00,0xc9,0x00,0x00,0x00,0x99,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,0x9b,0x02,0x00,0x00,
-0x9a,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0x9c,0x02,0x00,0x00,
-0x9d,0x02,0x00,0x00,0x81,0x02,0x00,0x00,0x35,0x00,0x00,0x00,
-0x8e,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0x9d,0x02,0x00,0x00,
-0x9b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x7d,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7d,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x69,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x69,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,
-0xad,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x66,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x68,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x61,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x61,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa1,0x02,0x00,0x00,0xab,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x60,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x49,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x49,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa3,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x46,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x48,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x41,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x41,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa5,0x02,0x00,0x00,
-0xa8,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x3e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x40,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_f16_len = 10316;
-
-unsigned char matmul_f16_aligned_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x08,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,
-0x05,0x01,0x00,0x00,0x63,0x01,0x00,0x00,0x69,0x01,0x00,0x00,
-0x68,0x02,0x00,0x00,0xb1,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x12,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x38,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x3e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4d,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x50,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x54,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x63,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xa7,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xb9,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xbc,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x02,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x03,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x03,0x01,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x05,0x01,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x05,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x3b,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x3c,0x01,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x66,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x67,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x67,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x67,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x67,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x67,0x01,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x69,0x01,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x69,0x01,0x00,0x00,
-0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x68,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xae,0x02,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xaf,0x02,0x00,0x00,
-0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xaf,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xaf,0x02,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xb1,0x02,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xb1,0x02,0x00,0x00,0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
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-0xa4,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xa2,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,0xa4,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa3,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,0x8c,0x02,0x00,0x00,
-0xdb,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0xa8,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xa9,0x02,0x00,0x00,
-0xa8,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xaa,0x02,0x00,0x00,0xa7,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa4,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa4,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0xc2,0x00,0x00,0x00,
-0xab,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,0x97,0x02,0x00,0x00,
-0xaa,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xad,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xab,0x02,0x00,0x00,0xac,0x02,0x00,0x00,0xad,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xac,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb5,0x02,0x00,0x00,0x8c,0x02,0x00,0x00,
-0xdb,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0xb7,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xb6,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xb8,0x02,0x00,0x00,
-0xb7,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb9,0x02,0x00,0x00,0xb5,0x02,0x00,0x00,0xb8,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xba,0x02,0x00,0x00,
-0x6c,0x02,0x00,0x00,0xb9,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbc,0x02,0x00,0x00,0xba,0x02,0x00,0x00,
-0x84,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xbe,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,0xdd,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc0,0x02,0x00,0x00,
-0xd8,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc2,0x02,0x00,0x00,0xc0,0x02,0x00,0x00,
-0xdb,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc4,0x02,0x00,0x00,0xc2,0x02,0x00,0x00,0xc3,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc6,0x02,0x00,0x00,
-0xd9,0x02,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc7,0x02,0x00,0x00,0xc4,0x02,0x00,0x00,
-0xc6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc9,0x02,0x00,0x00,0xc7,0x02,0x00,0x00,0xdd,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,0xca,0x02,0x00,0x00,
-0xca,0x00,0x00,0x00,0xc9,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xc4,0x00,0x00,0x00,0xcb,0x02,0x00,0x00,0xca,0x02,0x00,0x00,
-0x41,0x00,0x06,0x00,0xcc,0x02,0x00,0x00,0xcd,0x02,0x00,0x00,
-0xb1,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0xbe,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xcd,0x02,0x00,0x00,0xcb,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xad,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xad,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x99,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x99,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xcf,0x02,0x00,0x00,0xdd,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x96,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x98,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x91,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x91,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd1,0x02,0x00,0x00,
-0xdb,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x8e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x90,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x79,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x79,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd3,0x02,0x00,0x00,0xd9,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x76,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x78,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x71,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x71,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd5,0x02,0x00,0x00,0xd8,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x6e,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x70,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_f16_aligned_len = 11200;
-
-unsigned char matmul_f16_aligned_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xd8,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0xfd,0x00,0x00,0x00,0x04,0x01,0x00,0x00,0x4a,0x01,0x00,0x00,
-0x50,0x01,0x00,0x00,0x38,0x02,0x00,0x00,0x81,0x02,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x38,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x4d,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x50,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x54,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xa7,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xb9,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xbc,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x01,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x02,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x02,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x02,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x04,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x04,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x22,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x23,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4d,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x4e,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4e,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x4e,0x01,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x50,0x01,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x50,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x38,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x7e,0x02,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x7f,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7f,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x7f,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x81,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x81,0x02,0x00,0x00,0x21,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,
-0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,0x09,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x1e,0x00,0x10,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
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-0x0c,0x00,0x00,0x00,0x70,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xd7,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xd7,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x21,0x02,0x00,0x00,
-0xa7,0x02,0x00,0x00,0x6d,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xd4,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xd6,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x26,0x02,0x00,0x00,
-0x56,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x27,0x02,0x00,0x00,0x97,0x00,0x00,0x00,
-0x26,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x2c,0x02,0x00,0x00,0x5a,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x2d,0x02,0x00,0x00,
-0xa8,0x00,0x00,0x00,0x2c,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x31,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0x30,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x32,0x02,0x00,0x00,0x31,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x33,0x02,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x32,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x37,0x02,0x00,0x00,0x48,0x00,0x00,0x00,0x32,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,0x39,0x02,0x00,0x00,
-0x38,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x3a,0x02,0x00,0x00,0x39,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x3b,0x02,0x00,0x00,
-0x37,0x02,0x00,0x00,0x3a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x3c,0x02,0x00,0x00,0x33,0x02,0x00,0x00,
-0x3b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x3e,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x3e,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xa8,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xd6,0x00,0x00,0x00,0xa5,0x02,0x00,0x00,0x41,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0x44,0x02,0x00,0x00,
-0xa8,0x02,0x00,0x00,0xbf,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x40,0x02,0x00,0x00,0x41,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x44,0x02,0x00,0x00,0x3f,0x02,0x00,0x00,
-0x40,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x3f,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x46,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x46,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xa9,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x3f,0x02,0x00,0x00,
-0xa3,0x02,0x00,0x00,0x49,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0x4c,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,
-0x61,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x48,0x02,0x00,0x00,
-0x49,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x4c,0x02,0x00,0x00,0x47,0x02,0x00,0x00,0x48,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x47,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x50,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,
-0x62,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x51,0x02,0x00,0x00,0x27,0x02,0x00,0x00,0x50,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x53,0x02,0x00,0x00,
-0x65,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x54,0x02,0x00,0x00,0x51,0x02,0x00,0x00,
-0x53,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x58,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,0xc7,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x59,0x02,0x00,0x00,
-0x2d,0x02,0x00,0x00,0x58,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x5b,0x02,0x00,0x00,0x69,0x00,0x00,0x00,
-0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x5c,0x02,0x00,0x00,0x59,0x02,0x00,0x00,0x5b,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5e,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xab,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x47,0x02,0x00,0x00,
-0xa1,0x02,0x00,0x00,0x61,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0x64,0x02,0x00,0x00,0xab,0x02,0x00,0x00,
-0xbc,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x60,0x02,0x00,0x00,
-0x61,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x64,0x02,0x00,0x00,0x5f,0x02,0x00,0x00,0x60,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x66,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x66,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xad,0x02,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x5f,0x02,0x00,0x00,0x9f,0x02,0x00,0x00,
-0x69,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0x6c,0x02,0x00,0x00,0xad,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x68,0x02,0x00,0x00,0x69,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x6c,0x02,0x00,0x00,
-0x67,0x02,0x00,0x00,0x68,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x67,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x6f,0x02,0x00,0x00,0x54,0x02,0x00,0x00,0xad,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0x72,0x02,0x00,0x00,
-0x6f,0x02,0x00,0x00,0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x74,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x72,0x02,0x00,0x00,0x73,0x02,0x00,0x00,0x74,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x73,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x77,0x02,0x00,0x00,0x5c,0x02,0x00,0x00,
-0xab,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x78,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x79,0x02,0x00,0x00,
-0x78,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0x7a,0x02,0x00,0x00,0x77,0x02,0x00,0x00,0x79,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x74,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x74,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0xc2,0x00,0x00,0x00,
-0x7b,0x02,0x00,0x00,0x72,0x02,0x00,0x00,0x67,0x02,0x00,0x00,
-0x7a,0x02,0x00,0x00,0x73,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x7d,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x7b,0x02,0x00,0x00,0x7c,0x02,0x00,0x00,0x7d,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x85,0x02,0x00,0x00,0x5c,0x02,0x00,0x00,
-0xab,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x87,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0x86,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x88,0x02,0x00,0x00,
-0x87,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x89,0x02,0x00,0x00,0x85,0x02,0x00,0x00,0x88,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8a,0x02,0x00,0x00,
-0x3c,0x02,0x00,0x00,0x89,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8c,0x02,0x00,0x00,0x8a,0x02,0x00,0x00,
-0x54,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8e,0x02,0x00,0x00,0x8c,0x02,0x00,0x00,0xad,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x90,0x02,0x00,0x00,
-0xa8,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x92,0x02,0x00,0x00,0x90,0x02,0x00,0x00,
-0xab,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x94,0x02,0x00,0x00,0x92,0x02,0x00,0x00,0x93,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x96,0x02,0x00,0x00,
-0xa9,0x02,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x97,0x02,0x00,0x00,0x94,0x02,0x00,0x00,
-0x96,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x99,0x02,0x00,0x00,0x97,0x02,0x00,0x00,0xad,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,0x9a,0x02,0x00,0x00,
-0xca,0x00,0x00,0x00,0x99,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xc4,0x00,0x00,0x00,0x9b,0x02,0x00,0x00,0x9a,0x02,0x00,0x00,
-0x41,0x00,0x06,0x00,0x9c,0x02,0x00,0x00,0x9d,0x02,0x00,0x00,
-0x81,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0x8e,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x9d,0x02,0x00,0x00,0x9b,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x7d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7d,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x69,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x69,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,0xad,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x66,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x68,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x61,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x61,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa1,0x02,0x00,0x00,
-0xab,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x5e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x60,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x49,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x49,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa3,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x46,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x48,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x41,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x41,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa5,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x3e,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x40,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_f16_aligned_fp32_len = 10288;
-
-unsigned char matmul_f16_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xd9,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,
-0x06,0x01,0x00,0x00,0x46,0x01,0x00,0x00,0x51,0x01,0x00,0x00,
-0x3a,0x02,0x00,0x00,0x83,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
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-0x75,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x79,0x02,0x00,0x00,0x5e,0x02,0x00,0x00,0xac,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x7a,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
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-0x79,0x02,0x00,0x00,0x7b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
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-0xf9,0x00,0x02,0x00,0x6b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x6b,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa0,0x02,0x00,0x00,0xae,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x68,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x6a,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x63,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x63,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,0xac,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x60,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x62,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x4b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x4b,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa4,0x02,0x00,0x00,
-0xaa,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x48,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x4a,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x43,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x43,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa6,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x40,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x42,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_f16_f32_len = 10332;
-
-unsigned char matmul_f16_f32_aligned_data[] = {
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-0xd9,0x02,0x00,0x00,0xa4,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,0xe7,0x02,0x00,0x00,
-0x63,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xa3,0x02,0x00,0x00,
-0xa4,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xa7,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xaa,0x02,0x00,0x00,0x8f,0x02,0x00,0x00,
-0xe7,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xad,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0x37,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xaf,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xad,0x02,0x00,0x00,0xae,0x02,0x00,0x00,
-0xaf,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xae,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb2,0x02,0x00,0x00,
-0x97,0x02,0x00,0x00,0xe5,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0xb3,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0xd0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xb4,0x02,0x00,0x00,0xb3,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0xb5,0x02,0x00,0x00,0xb2,0x02,0x00,0x00,
-0xb4,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xaf,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xaf,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0xc2,0x00,0x00,0x00,0xb6,0x02,0x00,0x00,0xad,0x02,0x00,0x00,
-0xa2,0x02,0x00,0x00,0xb5,0x02,0x00,0x00,0xae,0x02,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xb8,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xb6,0x02,0x00,0x00,0xb7,0x02,0x00,0x00,
-0xb8,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb7,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc0,0x02,0x00,0x00,
-0x97,0x02,0x00,0x00,0xe5,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0xc2,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0xc1,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xc3,0x02,0x00,0x00,0xc2,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc4,0x02,0x00,0x00,0xc0,0x02,0x00,0x00,
-0xc3,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc5,0x02,0x00,0x00,0x77,0x02,0x00,0x00,0xc4,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc7,0x02,0x00,0x00,
-0xc5,0x02,0x00,0x00,0x8f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc9,0x02,0x00,0x00,0xc7,0x02,0x00,0x00,
-0xe7,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xcb,0x02,0x00,0x00,0xe2,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xcd,0x02,0x00,0x00,
-0xcb,0x02,0x00,0x00,0xe5,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xcf,0x02,0x00,0x00,0xcd,0x02,0x00,0x00,
-0xce,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd1,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd2,0x02,0x00,0x00,
-0xcf,0x02,0x00,0x00,0xd1,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd4,0x02,0x00,0x00,0xd2,0x02,0x00,0x00,
-0xe7,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,
-0xd5,0x02,0x00,0x00,0xca,0x00,0x00,0x00,0xd4,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xd6,0x02,0x00,0x00,
-0xd5,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0x6d,0x01,0x00,0x00,
-0xd7,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,0x35,0x00,0x00,0x00,
-0xc9,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0xd7,0x02,0x00,0x00,
-0xd6,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xb8,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb8,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa4,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa4,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd9,0x02,0x00,0x00,
-0xe7,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa3,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x9c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdb,0x02,0x00,0x00,0xe5,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x99,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x84,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x84,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xdd,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x81,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x83,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7c,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdf,0x02,0x00,0x00,
-0xe2,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x79,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_f16_f32_aligned_len = 11360;
-
-unsigned char matmul_f16_f32_aligned_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xd5,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0xfd,0x00,0x00,0x00,0x04,0x01,0x00,0x00,0x4a,0x01,0x00,0x00,
-0x51,0x01,0x00,0x00,0x36,0x02,0x00,0x00,0x7f,0x02,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x38,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x4d,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x50,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x54,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xa7,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xb9,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xbc,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x01,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x02,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x02,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x02,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x04,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x04,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x22,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x23,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4e,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x4f,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x4f,0x01,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x51,0x01,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x51,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x36,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x7c,0x02,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x7d,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x7d,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x7f,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x7f,0x02,0x00,0x00,0x21,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,
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-0xd9,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0xdb,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x79,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x79,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x1d,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x76,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x78,0x01,0x00,0x00,0xe0,0x00,0x04,0x00,0x0c,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x6e,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xd7,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xd7,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1f,0x02,0x00,0x00,
-0xa4,0x02,0x00,0x00,0x6d,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xd4,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xd6,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x24,0x02,0x00,0x00,
-0x56,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x25,0x02,0x00,0x00,0x97,0x00,0x00,0x00,
-0x24,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x2a,0x02,0x00,0x00,0x5a,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x2b,0x02,0x00,0x00,
-0xa8,0x00,0x00,0x00,0x2a,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x2f,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0x2e,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x30,0x02,0x00,0x00,0x2f,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x31,0x02,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x30,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x35,0x02,0x00,0x00,0x48,0x00,0x00,0x00,0x30,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,0x37,0x02,0x00,0x00,
-0x36,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x38,0x02,0x00,0x00,0x37,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x39,0x02,0x00,0x00,
-0x35,0x02,0x00,0x00,0x38,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x3a,0x02,0x00,0x00,0x31,0x02,0x00,0x00,
-0x39,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x3c,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x3c,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xa5,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xd6,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,0x3f,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0x42,0x02,0x00,0x00,
-0xa5,0x02,0x00,0x00,0xbf,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x3e,0x02,0x00,0x00,0x3f,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x42,0x02,0x00,0x00,0x3d,0x02,0x00,0x00,
-0x3e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x3d,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x44,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x44,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xa6,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x3d,0x02,0x00,0x00,
-0xa0,0x02,0x00,0x00,0x47,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0x4a,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,
-0x61,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x46,0x02,0x00,0x00,
-0x47,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x4a,0x02,0x00,0x00,0x45,0x02,0x00,0x00,0x46,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x45,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x4e,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,
-0x62,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x4f,0x02,0x00,0x00,0x25,0x02,0x00,0x00,0x4e,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x51,0x02,0x00,0x00,
-0x65,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x52,0x02,0x00,0x00,0x4f,0x02,0x00,0x00,
-0x51,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x56,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0xc5,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x57,0x02,0x00,0x00,
-0x2b,0x02,0x00,0x00,0x56,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x59,0x02,0x00,0x00,0x69,0x00,0x00,0x00,
-0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x5a,0x02,0x00,0x00,0x57,0x02,0x00,0x00,0x59,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5c,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xa8,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x45,0x02,0x00,0x00,
-0x9e,0x02,0x00,0x00,0x5f,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0x62,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
-0xbc,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x5e,0x02,0x00,0x00,
-0x5f,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x62,0x02,0x00,0x00,0x5d,0x02,0x00,0x00,0x5e,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x5d,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x64,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x64,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xaa,0x02,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x5d,0x02,0x00,0x00,0x9c,0x02,0x00,0x00,
-0x67,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0x6a,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x66,0x02,0x00,0x00,0x67,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x6a,0x02,0x00,0x00,
-0x65,0x02,0x00,0x00,0x66,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x65,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x6d,0x02,0x00,0x00,0x52,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0x70,0x02,0x00,0x00,
-0x6d,0x02,0x00,0x00,0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x72,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x70,0x02,0x00,0x00,0x71,0x02,0x00,0x00,0x72,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x71,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x75,0x02,0x00,0x00,0x5a,0x02,0x00,0x00,
-0xa8,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x76,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x77,0x02,0x00,0x00,
-0x76,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0x78,0x02,0x00,0x00,0x75,0x02,0x00,0x00,0x77,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x72,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x72,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0xc2,0x00,0x00,0x00,
-0x79,0x02,0x00,0x00,0x70,0x02,0x00,0x00,0x65,0x02,0x00,0x00,
-0x78,0x02,0x00,0x00,0x71,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x7b,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x79,0x02,0x00,0x00,0x7a,0x02,0x00,0x00,0x7b,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x83,0x02,0x00,0x00,0x5a,0x02,0x00,0x00,
-0xa8,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x85,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0x84,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x86,0x02,0x00,0x00,
-0x85,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x87,0x02,0x00,0x00,0x83,0x02,0x00,0x00,0x86,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x88,0x02,0x00,0x00,
-0x3a,0x02,0x00,0x00,0x87,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8a,0x02,0x00,0x00,0x88,0x02,0x00,0x00,
-0x52,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8c,0x02,0x00,0x00,0x8a,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8e,0x02,0x00,0x00,
-0xa5,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x90,0x02,0x00,0x00,0x8e,0x02,0x00,0x00,
-0xa8,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x92,0x02,0x00,0x00,0x90,0x02,0x00,0x00,0x91,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x94,0x02,0x00,0x00,
-0xa6,0x02,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x95,0x02,0x00,0x00,0x92,0x02,0x00,0x00,
-0x94,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x97,0x02,0x00,0x00,0x95,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,0x98,0x02,0x00,0x00,
-0xca,0x00,0x00,0x00,0x97,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xc4,0x00,0x00,0x00,0x99,0x02,0x00,0x00,0x98,0x02,0x00,0x00,
-0x41,0x00,0x06,0x00,0x53,0x01,0x00,0x00,0x9a,0x02,0x00,0x00,
-0x7f,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0x8c,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x9a,0x02,0x00,0x00,0x99,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x67,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x67,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9c,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x64,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x66,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x5f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,
-0xa8,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x5c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5e,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x47,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x47,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa0,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x44,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x46,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x3f,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x3f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x3c,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x3e,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_f16_f32_aligned_fp32_len = 10240;
-
-unsigned char matmul_f16_f32_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xd5,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
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-0x71,0x02,0x00,0x00,0x72,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x71,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x75,0x02,0x00,0x00,0x5a,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x76,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x77,0x02,0x00,0x00,0x76,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x78,0x02,0x00,0x00,
-0x75,0x02,0x00,0x00,0x77,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x72,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x72,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0xc1,0x00,0x00,0x00,0x79,0x02,0x00,0x00,
-0x70,0x02,0x00,0x00,0x65,0x02,0x00,0x00,0x78,0x02,0x00,0x00,
-0x71,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,0x7b,0x02,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x79,0x02,0x00,0x00,
-0x7a,0x02,0x00,0x00,0x7b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x83,0x02,0x00,0x00,0x5a,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x85,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0x84,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x86,0x02,0x00,0x00,0x85,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x87,0x02,0x00,0x00,
-0x83,0x02,0x00,0x00,0x86,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x88,0x02,0x00,0x00,0x3a,0x02,0x00,0x00,
-0x87,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8a,0x02,0x00,0x00,0x88,0x02,0x00,0x00,0x52,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8c,0x02,0x00,0x00,
-0x8a,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8e,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,
-0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x90,0x02,0x00,0x00,0x8e,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x92,0x02,0x00,0x00,
-0x90,0x02,0x00,0x00,0x91,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x94,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,
-0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x95,0x02,0x00,0x00,0x92,0x02,0x00,0x00,0x94,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x97,0x02,0x00,0x00,
-0x95,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0xcc,0x00,0x00,0x00,0x98,0x02,0x00,0x00,0xc9,0x00,0x00,0x00,
-0x97,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,
-0x99,0x02,0x00,0x00,0x98,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0x5c,0x01,0x00,0x00,0x9a,0x02,0x00,0x00,0x7f,0x02,0x00,0x00,
-0x35,0x00,0x00,0x00,0x8c,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x9a,0x02,0x00,0x00,0x99,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x67,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x67,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9c,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x64,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x66,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x5c,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x5e,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x47,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x47,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa0,0x02,0x00,0x00,
-0xa6,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x44,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x46,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x3f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x3f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa2,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x3c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x3e,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_f16_f32_fp32_len = 10260;
-
-unsigned char matmul_f16_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xd6,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0xfa,0x00,0x00,0x00,0x06,0x01,0x00,0x00,0x46,0x01,0x00,0x00,
-0x51,0x01,0x00,0x00,0x36,0x02,0x00,0x00,0x7f,0x02,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x38,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
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-0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x04,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x04,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x04,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
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-0x48,0x00,0x05,0x00,0x7d,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x7d,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x7f,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
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-0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
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-0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,0x09,0x00,0x00,0x00,
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-0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
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-0xd6,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xd6,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1f,0x02,0x00,0x00,
-0xa5,0x02,0x00,0x00,0x6d,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xd3,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xd5,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x24,0x02,0x00,0x00,
-0x56,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x25,0x02,0x00,0x00,0x96,0x00,0x00,0x00,
-0x24,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x2a,0x02,0x00,0x00,0x5a,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x2b,0x02,0x00,0x00,
-0xa7,0x00,0x00,0x00,0x2a,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x2f,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0x2e,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x30,0x02,0x00,0x00,0x2f,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x31,0x02,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x30,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x35,0x02,0x00,0x00,0x48,0x00,0x00,0x00,0x30,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,0x37,0x02,0x00,0x00,
-0x36,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x38,0x02,0x00,0x00,0x37,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x39,0x02,0x00,0x00,
-0x35,0x02,0x00,0x00,0x38,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x3a,0x02,0x00,0x00,0x31,0x02,0x00,0x00,
-0x39,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x3c,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x3c,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xa6,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xd5,0x00,0x00,0x00,0xa3,0x02,0x00,0x00,0x3f,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x42,0x02,0x00,0x00,
-0xa6,0x02,0x00,0x00,0xbe,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x3e,0x02,0x00,0x00,0x3f,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x42,0x02,0x00,0x00,0x3d,0x02,0x00,0x00,
-0x3e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x3d,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x44,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x44,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xa7,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x3d,0x02,0x00,0x00,
-0xa1,0x02,0x00,0x00,0x47,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0x4a,0x02,0x00,0x00,0xa7,0x02,0x00,0x00,
-0x61,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x46,0x02,0x00,0x00,
-0x47,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x4a,0x02,0x00,0x00,0x45,0x02,0x00,0x00,0x46,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x45,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x4e,0x02,0x00,0x00,0xa7,0x02,0x00,0x00,
-0x62,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x4f,0x02,0x00,0x00,0x25,0x02,0x00,0x00,0x4e,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x51,0x02,0x00,0x00,
-0x65,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x52,0x02,0x00,0x00,0x4f,0x02,0x00,0x00,
-0x51,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x56,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,0xc5,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x57,0x02,0x00,0x00,
-0x2b,0x02,0x00,0x00,0x56,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x59,0x02,0x00,0x00,0x69,0x00,0x00,0x00,
-0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x5a,0x02,0x00,0x00,0x57,0x02,0x00,0x00,0x59,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5c,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xa9,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x45,0x02,0x00,0x00,
-0x9f,0x02,0x00,0x00,0x5f,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0x62,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,
-0xbb,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x5e,0x02,0x00,0x00,
-0x5f,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x62,0x02,0x00,0x00,0x5d,0x02,0x00,0x00,0x5e,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x5d,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x64,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x64,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xab,0x02,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x5d,0x02,0x00,0x00,0x9d,0x02,0x00,0x00,
-0x67,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0x6a,0x02,0x00,0x00,0xab,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x66,0x02,0x00,0x00,0x67,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x6a,0x02,0x00,0x00,
-0x65,0x02,0x00,0x00,0x66,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x65,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x6d,0x02,0x00,0x00,0x52,0x02,0x00,0x00,0xab,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x70,0x02,0x00,0x00,
-0x6d,0x02,0x00,0x00,0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x72,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x70,0x02,0x00,0x00,0x71,0x02,0x00,0x00,0x72,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x71,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x75,0x02,0x00,0x00,0x5a,0x02,0x00,0x00,
-0xa9,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x76,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x77,0x02,0x00,0x00,
-0x76,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0x78,0x02,0x00,0x00,0x75,0x02,0x00,0x00,0x77,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x72,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x72,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0xc1,0x00,0x00,0x00,
-0x79,0x02,0x00,0x00,0x70,0x02,0x00,0x00,0x65,0x02,0x00,0x00,
-0x78,0x02,0x00,0x00,0x71,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x7b,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x79,0x02,0x00,0x00,0x7a,0x02,0x00,0x00,0x7b,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x83,0x02,0x00,0x00,0x5a,0x02,0x00,0x00,
-0xa9,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x85,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0x84,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x86,0x02,0x00,0x00,
-0x85,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x87,0x02,0x00,0x00,0x83,0x02,0x00,0x00,0x86,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x88,0x02,0x00,0x00,
-0x3a,0x02,0x00,0x00,0x87,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8a,0x02,0x00,0x00,0x88,0x02,0x00,0x00,
-0x52,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8c,0x02,0x00,0x00,0x8a,0x02,0x00,0x00,0xab,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8e,0x02,0x00,0x00,
-0xa6,0x02,0x00,0x00,0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x90,0x02,0x00,0x00,0x8e,0x02,0x00,0x00,
-0xa9,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x92,0x02,0x00,0x00,0x90,0x02,0x00,0x00,0x91,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x94,0x02,0x00,0x00,
-0xa7,0x02,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x95,0x02,0x00,0x00,0x92,0x02,0x00,0x00,
-0x94,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x97,0x02,0x00,0x00,0x95,0x02,0x00,0x00,0xab,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0xcc,0x00,0x00,0x00,0x98,0x02,0x00,0x00,
-0xc9,0x00,0x00,0x00,0x97,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xc3,0x00,0x00,0x00,0x99,0x02,0x00,0x00,0x98,0x02,0x00,0x00,
-0x41,0x00,0x06,0x00,0x9a,0x02,0x00,0x00,0x9b,0x02,0x00,0x00,
-0x7f,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0x8c,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x9b,0x02,0x00,0x00,0x99,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x67,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x67,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9d,0x02,0x00,0x00,0xab,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x64,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x66,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x5f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,
-0xa9,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x5c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5e,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x47,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x47,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa1,0x02,0x00,0x00,0xa7,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x44,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x46,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x3f,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x3f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa3,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x3c,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x3e,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_f16_fp32_len = 10276;
-
-unsigned char matmul_f32_f16_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xd9,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,
-0x06,0x01,0x00,0x00,0x47,0x01,0x00,0x00,0x52,0x01,0x00,0x00,
-0x3a,0x02,0x00,0x00,0x83,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
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-0x79,0x02,0x00,0x00,0x5e,0x02,0x00,0x00,0xac,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x7a,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x7b,0x02,0x00,0x00,0x7a,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x7c,0x02,0x00,0x00,
-0x79,0x02,0x00,0x00,0x7b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x76,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x76,0x02,0x00,0x00,
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-0x8b,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
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-0x9e,0x02,0x00,0x00,0x9d,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7f,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x6b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x6b,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa0,0x02,0x00,0x00,0xae,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x68,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x6a,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x63,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x63,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,0xac,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x60,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x62,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x4b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x4b,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa4,0x02,0x00,0x00,
-0xaa,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x48,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x4a,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x43,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x43,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa6,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x40,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x42,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_f32_f16_len = 10332;
-
-unsigned char matmul_f32_f16_aligned_data[] = {
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-0xc2,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,0xe7,0x02,0x00,0x00,
-0x63,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xa3,0x02,0x00,0x00,
-0xa4,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xa7,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xaa,0x02,0x00,0x00,0x8f,0x02,0x00,0x00,
-0xe7,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xad,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0x37,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xaf,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xad,0x02,0x00,0x00,0xae,0x02,0x00,0x00,
-0xaf,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xae,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb2,0x02,0x00,0x00,
-0x97,0x02,0x00,0x00,0xe5,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0xb3,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0xd0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xb4,0x02,0x00,0x00,0xb3,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0xb5,0x02,0x00,0x00,0xb2,0x02,0x00,0x00,
-0xb4,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xaf,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xaf,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0xc2,0x00,0x00,0x00,0xb6,0x02,0x00,0x00,0xad,0x02,0x00,0x00,
-0xa2,0x02,0x00,0x00,0xb5,0x02,0x00,0x00,0xae,0x02,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xb8,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xb6,0x02,0x00,0x00,0xb7,0x02,0x00,0x00,
-0xb8,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb7,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc0,0x02,0x00,0x00,
-0x97,0x02,0x00,0x00,0xe5,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0xc2,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0xc1,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xc3,0x02,0x00,0x00,0xc2,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc4,0x02,0x00,0x00,0xc0,0x02,0x00,0x00,
-0xc3,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc5,0x02,0x00,0x00,0x77,0x02,0x00,0x00,0xc4,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc7,0x02,0x00,0x00,
-0xc5,0x02,0x00,0x00,0x8f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc9,0x02,0x00,0x00,0xc7,0x02,0x00,0x00,
-0xe7,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xcb,0x02,0x00,0x00,0xe2,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xcd,0x02,0x00,0x00,
-0xcb,0x02,0x00,0x00,0xe5,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xcf,0x02,0x00,0x00,0xcd,0x02,0x00,0x00,
-0xce,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd1,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd2,0x02,0x00,0x00,
-0xcf,0x02,0x00,0x00,0xd1,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd4,0x02,0x00,0x00,0xd2,0x02,0x00,0x00,
-0xe7,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,
-0xd5,0x02,0x00,0x00,0xca,0x00,0x00,0x00,0xd4,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xd6,0x02,0x00,0x00,
-0xd5,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0x07,0x01,0x00,0x00,
-0xd7,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,0x35,0x00,0x00,0x00,
-0xc9,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0xd7,0x02,0x00,0x00,
-0xd6,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xb8,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb8,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa4,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa4,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd9,0x02,0x00,0x00,
-0xe7,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa3,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x9c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdb,0x02,0x00,0x00,0xe5,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x99,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x84,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x84,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xdd,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x81,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x83,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7c,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdf,0x02,0x00,0x00,
-0xe2,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x79,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_f32_f16_aligned_len = 11360;
-
-unsigned char matmul_f32_f16_aligned_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xd5,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0xfd,0x00,0x00,0x00,0x03,0x01,0x00,0x00,0x45,0x01,0x00,0x00,
-0x4d,0x01,0x00,0x00,0x36,0x02,0x00,0x00,0x7f,0x02,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x38,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x4d,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x50,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x54,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xa7,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xb9,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xbc,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x00,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x01,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x01,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x01,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x03,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x03,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1d,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x1e,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4a,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x4b,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4b,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x4b,0x01,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x4d,0x01,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4d,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x36,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x7c,0x02,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x7d,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7d,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x7d,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x7f,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x7f,0x02,0x00,0x00,0x21,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,
-0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
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-0xf9,0x00,0x02,0x00,0x79,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x79,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x1d,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x76,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
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-0xd4,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xd6,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x24,0x02,0x00,0x00,
-0x56,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x25,0x02,0x00,0x00,0x97,0x00,0x00,0x00,
-0x24,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x2a,0x02,0x00,0x00,0x5a,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x2b,0x02,0x00,0x00,
-0xa8,0x00,0x00,0x00,0x2a,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x2f,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0x2e,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x30,0x02,0x00,0x00,0x2f,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x31,0x02,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x30,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x35,0x02,0x00,0x00,0x48,0x00,0x00,0x00,0x30,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,0x37,0x02,0x00,0x00,
-0x36,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x38,0x02,0x00,0x00,0x37,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x39,0x02,0x00,0x00,
-0x35,0x02,0x00,0x00,0x38,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x3a,0x02,0x00,0x00,0x31,0x02,0x00,0x00,
-0x39,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x3c,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x3c,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xa5,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xd6,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,0x3f,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0x42,0x02,0x00,0x00,
-0xa5,0x02,0x00,0x00,0xbf,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x3e,0x02,0x00,0x00,0x3f,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x42,0x02,0x00,0x00,0x3d,0x02,0x00,0x00,
-0x3e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x3d,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x44,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x44,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xa6,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x3d,0x02,0x00,0x00,
-0xa0,0x02,0x00,0x00,0x47,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0x4a,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,
-0x61,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x46,0x02,0x00,0x00,
-0x47,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x4a,0x02,0x00,0x00,0x45,0x02,0x00,0x00,0x46,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x45,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x4e,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,
-0x62,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x4f,0x02,0x00,0x00,0x25,0x02,0x00,0x00,0x4e,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x51,0x02,0x00,0x00,
-0x65,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x52,0x02,0x00,0x00,0x4f,0x02,0x00,0x00,
-0x51,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x56,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0xc5,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x57,0x02,0x00,0x00,
-0x2b,0x02,0x00,0x00,0x56,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x59,0x02,0x00,0x00,0x69,0x00,0x00,0x00,
-0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x5a,0x02,0x00,0x00,0x57,0x02,0x00,0x00,0x59,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5c,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xa8,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x45,0x02,0x00,0x00,
-0x9e,0x02,0x00,0x00,0x5f,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0x62,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
-0xbc,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x5e,0x02,0x00,0x00,
-0x5f,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x62,0x02,0x00,0x00,0x5d,0x02,0x00,0x00,0x5e,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x5d,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x64,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x64,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xaa,0x02,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x5d,0x02,0x00,0x00,0x9c,0x02,0x00,0x00,
-0x67,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0x6a,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x66,0x02,0x00,0x00,0x67,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x6a,0x02,0x00,0x00,
-0x65,0x02,0x00,0x00,0x66,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x65,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x6d,0x02,0x00,0x00,0x52,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0x70,0x02,0x00,0x00,
-0x6d,0x02,0x00,0x00,0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x72,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x70,0x02,0x00,0x00,0x71,0x02,0x00,0x00,0x72,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x71,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x75,0x02,0x00,0x00,0x5a,0x02,0x00,0x00,
-0xa8,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x76,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x77,0x02,0x00,0x00,
-0x76,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0x78,0x02,0x00,0x00,0x75,0x02,0x00,0x00,0x77,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x72,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x72,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0xc2,0x00,0x00,0x00,
-0x79,0x02,0x00,0x00,0x70,0x02,0x00,0x00,0x65,0x02,0x00,0x00,
-0x78,0x02,0x00,0x00,0x71,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x7b,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x79,0x02,0x00,0x00,0x7a,0x02,0x00,0x00,0x7b,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x83,0x02,0x00,0x00,0x5a,0x02,0x00,0x00,
-0xa8,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x85,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0x84,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x86,0x02,0x00,0x00,
-0x85,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x87,0x02,0x00,0x00,0x83,0x02,0x00,0x00,0x86,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x88,0x02,0x00,0x00,
-0x3a,0x02,0x00,0x00,0x87,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8a,0x02,0x00,0x00,0x88,0x02,0x00,0x00,
-0x52,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8c,0x02,0x00,0x00,0x8a,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8e,0x02,0x00,0x00,
-0xa5,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x90,0x02,0x00,0x00,0x8e,0x02,0x00,0x00,
-0xa8,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x92,0x02,0x00,0x00,0x90,0x02,0x00,0x00,0x91,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x94,0x02,0x00,0x00,
-0xa6,0x02,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x95,0x02,0x00,0x00,0x92,0x02,0x00,0x00,
-0x94,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x97,0x02,0x00,0x00,0x95,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,0x98,0x02,0x00,0x00,
-0xca,0x00,0x00,0x00,0x97,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xc4,0x00,0x00,0x00,0x99,0x02,0x00,0x00,0x98,0x02,0x00,0x00,
-0x41,0x00,0x06,0x00,0x05,0x01,0x00,0x00,0x9a,0x02,0x00,0x00,
-0x7f,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0x8c,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x9a,0x02,0x00,0x00,0x99,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x67,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x67,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9c,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x64,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x66,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x5f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,
-0xa8,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x5c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5e,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x47,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x47,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa0,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x44,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x46,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x3f,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x3f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x3c,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x3e,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_f32_f16_aligned_fp32_len = 10240;
-
-unsigned char matmul_f32_f16_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xd5,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0xfa,0x00,0x00,0x00,0x05,0x01,0x00,0x00,0x44,0x01,0x00,0x00,
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-0x71,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x75,0x02,0x00,0x00,0x5a,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x76,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x77,0x02,0x00,0x00,0x76,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x78,0x02,0x00,0x00,
-0x75,0x02,0x00,0x00,0x77,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x72,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x72,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0xc1,0x00,0x00,0x00,0x79,0x02,0x00,0x00,
-0x70,0x02,0x00,0x00,0x65,0x02,0x00,0x00,0x78,0x02,0x00,0x00,
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-0x7a,0x02,0x00,0x00,0x7b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
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-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x87,0x02,0x00,0x00,
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-0x06,0x00,0x00,0x00,0x88,0x02,0x00,0x00,0x3a,0x02,0x00,0x00,
-0x87,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8a,0x02,0x00,0x00,0x88,0x02,0x00,0x00,0x52,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8c,0x02,0x00,0x00,
-0x8a,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8e,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,
-0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x90,0x02,0x00,0x00,0x8e,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x92,0x02,0x00,0x00,
-0x90,0x02,0x00,0x00,0x91,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x94,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,
-0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x95,0x02,0x00,0x00,0x92,0x02,0x00,0x00,0x94,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x97,0x02,0x00,0x00,
-0x95,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0xcc,0x00,0x00,0x00,0x98,0x02,0x00,0x00,0xc9,0x00,0x00,0x00,
-0x97,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,
-0x99,0x02,0x00,0x00,0x98,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0x10,0x01,0x00,0x00,0x9a,0x02,0x00,0x00,0x7f,0x02,0x00,0x00,
-0x35,0x00,0x00,0x00,0x8c,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x9a,0x02,0x00,0x00,0x99,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x67,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x67,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9c,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x64,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x66,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x5c,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x5e,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x47,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x47,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa0,0x02,0x00,0x00,
-0xa6,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x44,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x46,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x3f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x3f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa2,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x3c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x3e,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_f32_f16_fp32_len = 10260;
-
-unsigned char matmul_f32_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xd9,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
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-0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0xfb,0x00,0x00,0x00,0x06,0x01,0x00,0x00,0x47,0x01,0x00,0x00,
-0x52,0x01,0x00,0x00,0x3a,0x02,0x00,0x00,0x83,0x02,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
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-0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
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-0x38,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
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-0x32,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
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-0x06,0x00,0x00,0x00,0x3e,0x02,0x00,0x00,0x35,0x02,0x00,0x00,
-0x3d,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x40,0x02,0x00,0x00,
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-0x06,0x00,0x00,0x00,0xa9,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xd5,0x00,0x00,0x00,0xa6,0x02,0x00,0x00,0x43,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x46,0x02,0x00,0x00,
-0xa9,0x02,0x00,0x00,0xbe,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x42,0x02,0x00,0x00,0x43,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x46,0x02,0x00,0x00,0x41,0x02,0x00,0x00,
-0x42,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x41,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x48,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x48,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xaa,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x41,0x02,0x00,0x00,
-0xa4,0x02,0x00,0x00,0x4b,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0x4e,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
-0x61,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x4a,0x02,0x00,0x00,
-0x4b,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x4e,0x02,0x00,0x00,0x49,0x02,0x00,0x00,0x4a,0x02,0x00,0x00,
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-0x5a,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,0xc7,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x5b,0x02,0x00,0x00,
-0x2f,0x02,0x00,0x00,0x5a,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x5d,0x02,0x00,0x00,0x69,0x00,0x00,0x00,
-0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x5e,0x02,0x00,0x00,0x5b,0x02,0x00,0x00,0x5d,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x60,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x60,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xac,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x49,0x02,0x00,0x00,
-0xa2,0x02,0x00,0x00,0x63,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0x66,0x02,0x00,0x00,0xac,0x02,0x00,0x00,
-0xbb,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x62,0x02,0x00,0x00,
-0x63,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x66,0x02,0x00,0x00,0x61,0x02,0x00,0x00,0x62,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x61,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x68,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x68,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xae,0x02,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x61,0x02,0x00,0x00,0xa0,0x02,0x00,0x00,
-0x6b,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0x6e,0x02,0x00,0x00,0xae,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x6a,0x02,0x00,0x00,0x6b,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x6e,0x02,0x00,0x00,
-0x69,0x02,0x00,0x00,0x6a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x69,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x71,0x02,0x00,0x00,0x56,0x02,0x00,0x00,0xae,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x74,0x02,0x00,0x00,
-0x71,0x02,0x00,0x00,0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x76,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x74,0x02,0x00,0x00,0x75,0x02,0x00,0x00,0x76,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x75,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x79,0x02,0x00,0x00,0x5e,0x02,0x00,0x00,
-0xac,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x7a,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x7b,0x02,0x00,0x00,
-0x7a,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0x7c,0x02,0x00,0x00,0x79,0x02,0x00,0x00,0x7b,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x76,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x76,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0xc1,0x00,0x00,0x00,
-0x7d,0x02,0x00,0x00,0x74,0x02,0x00,0x00,0x69,0x02,0x00,0x00,
-0x7c,0x02,0x00,0x00,0x75,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x7f,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x7d,0x02,0x00,0x00,0x7e,0x02,0x00,0x00,0x7f,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7e,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x87,0x02,0x00,0x00,0x5e,0x02,0x00,0x00,
-0xac,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x89,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0x88,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x8a,0x02,0x00,0x00,
-0x89,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8b,0x02,0x00,0x00,0x87,0x02,0x00,0x00,0x8a,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8c,0x02,0x00,0x00,
-0x3e,0x02,0x00,0x00,0x8b,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8e,0x02,0x00,0x00,0x8c,0x02,0x00,0x00,
-0x56,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x90,0x02,0x00,0x00,0x8e,0x02,0x00,0x00,0xae,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x92,0x02,0x00,0x00,
-0xa9,0x02,0x00,0x00,0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x94,0x02,0x00,0x00,0x92,0x02,0x00,0x00,
-0xac,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x96,0x02,0x00,0x00,0x94,0x02,0x00,0x00,0x95,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x98,0x02,0x00,0x00,
-0xaa,0x02,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x99,0x02,0x00,0x00,0x96,0x02,0x00,0x00,
-0x98,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9b,0x02,0x00,0x00,0x99,0x02,0x00,0x00,0xae,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0xcc,0x00,0x00,0x00,0x9c,0x02,0x00,0x00,
-0xc9,0x00,0x00,0x00,0x9b,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xc3,0x00,0x00,0x00,0x9d,0x02,0x00,0x00,0x9c,0x02,0x00,0x00,
-0x41,0x00,0x06,0x00,0x11,0x01,0x00,0x00,0x9e,0x02,0x00,0x00,
-0x83,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0x90,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x9e,0x02,0x00,0x00,0x9d,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x7f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7f,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x6b,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x6b,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa0,0x02,0x00,0x00,0xae,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x68,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x6a,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x63,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x63,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,
-0xac,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x60,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x62,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x4b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x4b,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa4,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x48,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x4a,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x43,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x43,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa6,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x40,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x42,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_f32_f32_len = 10324;
-
-unsigned char matmul_f32_f32_aligned_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x17,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0xfe,0x00,0x00,0x00,0x05,0x01,0x00,0x00,0x6b,0x01,0x00,0x00,
-0x71,0x01,0x00,0x00,0x78,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
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-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x71,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0x70,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
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-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x7c,0x02,0x00,0x00,
-0x73,0x02,0x00,0x00,0x7b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
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-0x3f,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,0xe4,0x02,0x00,0x00,
-0x81,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0x84,0x02,0x00,0x00,0xe7,0x02,0x00,0x00,0xbf,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x80,0x02,0x00,0x00,0x81,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x84,0x02,0x00,0x00,
-0x7f,0x02,0x00,0x00,0x80,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7f,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x86,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x86,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xe8,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,
-0x7f,0x02,0x00,0x00,0xe2,0x02,0x00,0x00,0x89,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0x8c,0x02,0x00,0x00,
-0xe8,0x02,0x00,0x00,0x61,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x88,0x02,0x00,0x00,0x89,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x8c,0x02,0x00,0x00,0x87,0x02,0x00,0x00,
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-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x90,0x02,0x00,0x00,
-0xe8,0x02,0x00,0x00,0x62,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x91,0x02,0x00,0x00,0x67,0x02,0x00,0x00,
-0x90,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x93,0x02,0x00,0x00,0x65,0x00,0x00,0x00,0x63,0x00,0x00,0x00,
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-0x91,0x02,0x00,0x00,0x93,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x98,0x02,0x00,0x00,0xe7,0x02,0x00,0x00,
-0x05,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
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-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9b,0x02,0x00,0x00,
-0x69,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9c,0x02,0x00,0x00,0x99,0x02,0x00,0x00,
-0x9b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x9e,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x9e,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xea,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,
-0x87,0x02,0x00,0x00,0xe0,0x02,0x00,0x00,0xa1,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0xa4,0x02,0x00,0x00,
-0xea,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xa0,0x02,0x00,0x00,0xa1,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xa4,0x02,0x00,0x00,0x9f,0x02,0x00,0x00,
-0xa0,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x9f,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa6,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xec,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,
-0xde,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0xac,0x02,0x00,0x00,0xec,0x02,0x00,0x00,
-0x63,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xa8,0x02,0x00,0x00,
-0xa9,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xac,0x02,0x00,0x00,0xa7,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa7,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xaf,0x02,0x00,0x00,0x94,0x02,0x00,0x00,
-0xec,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xb2,0x02,0x00,0x00,0xaf,0x02,0x00,0x00,0x37,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xb4,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xb2,0x02,0x00,0x00,0xb3,0x02,0x00,0x00,
-0xb4,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb3,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb7,0x02,0x00,0x00,
-0x9c,0x02,0x00,0x00,0xea,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0xb8,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0xd0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xb9,0x02,0x00,0x00,0xb8,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0xba,0x02,0x00,0x00,0xb7,0x02,0x00,0x00,
-0xb9,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xb4,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb4,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0xc2,0x00,0x00,0x00,0xbb,0x02,0x00,0x00,0xb2,0x02,0x00,0x00,
-0xa7,0x02,0x00,0x00,0xba,0x02,0x00,0x00,0xb3,0x02,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xbd,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xbb,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,
-0xbd,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xbc,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc5,0x02,0x00,0x00,
-0x9c,0x02,0x00,0x00,0xea,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0xc7,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0xc6,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xc8,0x02,0x00,0x00,0xc7,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc9,0x02,0x00,0x00,0xc5,0x02,0x00,0x00,
-0xc8,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xca,0x02,0x00,0x00,0x7c,0x02,0x00,0x00,0xc9,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xcc,0x02,0x00,0x00,
-0xca,0x02,0x00,0x00,0x94,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xce,0x02,0x00,0x00,0xcc,0x02,0x00,0x00,
-0xec,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd0,0x02,0x00,0x00,0xe7,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd2,0x02,0x00,0x00,
-0xd0,0x02,0x00,0x00,0xea,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd4,0x02,0x00,0x00,0xd2,0x02,0x00,0x00,
-0xd3,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd6,0x02,0x00,0x00,0xe8,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd7,0x02,0x00,0x00,
-0xd4,0x02,0x00,0x00,0xd6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd9,0x02,0x00,0x00,0xd7,0x02,0x00,0x00,
-0xec,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,
-0xda,0x02,0x00,0x00,0xca,0x00,0x00,0x00,0xd9,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xdb,0x02,0x00,0x00,
-0xda,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0x07,0x01,0x00,0x00,
-0xdc,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,0x35,0x00,0x00,0x00,
-0xce,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0xdc,0x02,0x00,0x00,
-0xdb,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xbd,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xbd,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa9,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xde,0x02,0x00,0x00,
-0xec,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa8,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa1,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe0,0x02,0x00,0x00,0xea,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x9e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa0,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x89,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x89,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe2,0x02,0x00,0x00,0xe8,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x86,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x88,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x81,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x81,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe4,0x02,0x00,0x00,
-0xe7,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x80,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_f32_f32_aligned_len = 11432;
-
-unsigned char matmul_f32_f32_aligned_fp32_data[] = {
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-0x6b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x6a,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x6e,0x02,0x00,0x00,
-0x53,0x02,0x00,0x00,0xa1,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x6f,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0xd0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x70,0x02,0x00,0x00,0x6f,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0x71,0x02,0x00,0x00,0x6e,0x02,0x00,0x00,
-0x70,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x6b,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x6b,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0xc2,0x00,0x00,0x00,0x72,0x02,0x00,0x00,0x69,0x02,0x00,0x00,
-0x5e,0x02,0x00,0x00,0x71,0x02,0x00,0x00,0x6a,0x02,0x00,0x00,
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-0xfa,0x00,0x04,0x00,0x72,0x02,0x00,0x00,0x73,0x02,0x00,0x00,
-0x74,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x73,0x02,0x00,0x00,
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-0x7f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x81,0x02,0x00,0x00,0x33,0x02,0x00,0x00,0x80,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x83,0x02,0x00,0x00,
-0x81,0x02,0x00,0x00,0x4b,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x85,0x02,0x00,0x00,0x83,0x02,0x00,0x00,
-0xa3,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x87,0x02,0x00,0x00,0x9e,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x89,0x02,0x00,0x00,
-0x87,0x02,0x00,0x00,0xa1,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8b,0x02,0x00,0x00,0x89,0x02,0x00,0x00,
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-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8e,0x02,0x00,0x00,
-0x8b,0x02,0x00,0x00,0x8d,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x90,0x02,0x00,0x00,0x8e,0x02,0x00,0x00,
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-0x91,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0x05,0x01,0x00,0x00,
-0x93,0x02,0x00,0x00,0x78,0x02,0x00,0x00,0x35,0x00,0x00,0x00,
-0x85,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0x93,0x02,0x00,0x00,
-0x92,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x74,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x74,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x60,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x60,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x95,0x02,0x00,0x00,
-0xa3,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x5d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x58,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x58,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x97,0x02,0x00,0x00,0xa1,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x55,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x57,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x40,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x40,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x99,0x02,0x00,0x00,0x9f,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x3d,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x3f,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x38,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x38,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9b,0x02,0x00,0x00,
-0x9e,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x35,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x37,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_f32_f32_aligned_fp32_len = 10124;
-
-unsigned char matmul_f32_f32_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xd2,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
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-0x4d,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x05,0x01,0x00,0x00,
-0x44,0x01,0x00,0x00,0x4f,0x01,0x00,0x00,0x33,0x02,0x00,0x00,
-0x7c,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
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-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
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-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
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-0x48,0x00,0x04,0x00,0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
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-0x47,0x00,0x03,0x00,0x03,0x01,0x00,0x00,0x02,0x00,0x00,0x00,
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-0x96,0x00,0x00,0x00,0x21,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x27,0x02,0x00,0x00,0x5a,0x00,0x00,0x00,
-0xb8,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x28,0x02,0x00,0x00,0xa7,0x00,0x00,0x00,0x27,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x2c,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0x2b,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x2d,0x02,0x00,0x00,0x2c,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x2e,0x02,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x2d,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x32,0x02,0x00,0x00,0x48,0x00,0x00,0x00,
-0x2d,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,
-0x34,0x02,0x00,0x00,0x33,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x35,0x02,0x00,0x00,
-0x34,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x36,0x02,0x00,0x00,0x32,0x02,0x00,0x00,0x35,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x37,0x02,0x00,0x00,
-0x2e,0x02,0x00,0x00,0x36,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x39,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x39,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,
-0x3f,0x00,0x00,0x00,0xd5,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,
-0x3c,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0x3f,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,0xbe,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x3b,0x02,0x00,0x00,0x3c,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x3f,0x02,0x00,0x00,
-0x3a,0x02,0x00,0x00,0x3b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x3a,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x41,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x41,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xa3,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,
-0x3a,0x02,0x00,0x00,0x9d,0x02,0x00,0x00,0x44,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x47,0x02,0x00,0x00,
-0xa3,0x02,0x00,0x00,0x61,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x43,0x02,0x00,0x00,0x44,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x47,0x02,0x00,0x00,0x42,0x02,0x00,0x00,
-0x43,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x42,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x4b,0x02,0x00,0x00,
-0xa3,0x02,0x00,0x00,0x62,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x4c,0x02,0x00,0x00,0x22,0x02,0x00,0x00,
-0x4b,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x4e,0x02,0x00,0x00,0x65,0x00,0x00,0x00,0x63,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x4f,0x02,0x00,0x00,
-0x4c,0x02,0x00,0x00,0x4e,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x53,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,
-0xc2,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x54,0x02,0x00,0x00,0x28,0x02,0x00,0x00,0x53,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x56,0x02,0x00,0x00,
-0x69,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x57,0x02,0x00,0x00,0x54,0x02,0x00,0x00,
-0x56,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x59,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x59,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xa5,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,
-0x42,0x02,0x00,0x00,0x9b,0x02,0x00,0x00,0x5c,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x5f,0x02,0x00,0x00,
-0xa5,0x02,0x00,0x00,0xbb,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x5b,0x02,0x00,0x00,0x5c,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x5f,0x02,0x00,0x00,0x5a,0x02,0x00,0x00,
-0x5b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5a,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x61,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x61,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xa7,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x5a,0x02,0x00,0x00,
-0x99,0x02,0x00,0x00,0x64,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0x67,0x02,0x00,0x00,0xa7,0x02,0x00,0x00,
-0x63,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x63,0x02,0x00,0x00,
-0x64,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x67,0x02,0x00,0x00,0x62,0x02,0x00,0x00,0x63,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x62,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x6a,0x02,0x00,0x00,0x4f,0x02,0x00,0x00,
-0xa7,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0x6d,0x02,0x00,0x00,0x6a,0x02,0x00,0x00,0x37,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x6f,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x6d,0x02,0x00,0x00,0x6e,0x02,0x00,0x00,
-0x6f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x6e,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x72,0x02,0x00,0x00,
-0x57,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x73,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0xcf,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x74,0x02,0x00,0x00,0x73,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0x75,0x02,0x00,0x00,0x72,0x02,0x00,0x00,
-0x74,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x6f,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x6f,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0xc1,0x00,0x00,0x00,0x76,0x02,0x00,0x00,0x6d,0x02,0x00,0x00,
-0x62,0x02,0x00,0x00,0x75,0x02,0x00,0x00,0x6e,0x02,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x78,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x76,0x02,0x00,0x00,0x77,0x02,0x00,0x00,
-0x78,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x77,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x80,0x02,0x00,0x00,
-0x57,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x82,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0x81,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x83,0x02,0x00,0x00,0x82,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x84,0x02,0x00,0x00,0x80,0x02,0x00,0x00,
-0x83,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x85,0x02,0x00,0x00,0x37,0x02,0x00,0x00,0x84,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x87,0x02,0x00,0x00,
-0x85,0x02,0x00,0x00,0x4f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x89,0x02,0x00,0x00,0x87,0x02,0x00,0x00,
-0xa7,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8b,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,0xbb,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8d,0x02,0x00,0x00,
-0x8b,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8f,0x02,0x00,0x00,0x8d,0x02,0x00,0x00,
-0x8e,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x91,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x92,0x02,0x00,0x00,
-0x8f,0x02,0x00,0x00,0x91,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x94,0x02,0x00,0x00,0x92,0x02,0x00,0x00,
-0xa7,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xcc,0x00,0x00,0x00,
-0x95,0x02,0x00,0x00,0xc9,0x00,0x00,0x00,0x94,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,0x96,0x02,0x00,0x00,
-0x95,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0x10,0x01,0x00,0x00,
-0x97,0x02,0x00,0x00,0x7c,0x02,0x00,0x00,0x35,0x00,0x00,0x00,
-0x89,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0x97,0x02,0x00,0x00,
-0x96,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x78,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x78,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x64,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x64,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x99,0x02,0x00,0x00,
-0xa7,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x61,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x63,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9b,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x59,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x44,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x44,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9d,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x41,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x43,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x3c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x3c,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,
-0xa2,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x39,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x3b,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_f32_f32_fp32_len = 10208;
-
-unsigned char matmul_id_f16_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x30,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x51,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x10,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x2e,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,0x90,0x00,0x00,0x00,
-0x05,0x01,0x00,0x00,0x10,0x01,0x00,0x00,0x4e,0x01,0x00,0x00,
-0x59,0x01,0x00,0x00,0x84,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
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-0xaa,0x02,0x00,0x00,0xc0,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
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-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x4c,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x4e,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x47,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x47,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xae,0x02,0x00,0x00,
-0xbd,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x44,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x46,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xaf,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xaf,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_id_f16_len = 10788;
-
-unsigned char matmul_id_f16_aligned_data[] = {
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-0xf6,0x00,0x04,0x00,0xb9,0x02,0x00,0x00,0xb8,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xbd,0x02,0x00,0x00,
-0xb8,0x02,0x00,0x00,0xb9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xb8,0x02,0x00,0x00,0x51,0x00,0x05,0x00,0x8c,0x00,0x00,0x00,
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-0x06,0x00,0x00,0x00,0xd0,0x02,0x00,0x00,0xc8,0x02,0x00,0x00,
-0xcf,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd2,0x02,0x00,0x00,0xd0,0x02,0x00,0x00,0x97,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd4,0x02,0x00,0x00,
-0xd2,0x02,0x00,0x00,0x03,0x03,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd6,0x02,0x00,0x00,0xfa,0x02,0x00,0x00,
-0xc9,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd8,0x02,0x00,0x00,0xd6,0x02,0x00,0x00,0xfd,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xda,0x02,0x00,0x00,
-0xd8,0x02,0x00,0x00,0xd9,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xdc,0x02,0x00,0x00,0xfb,0x02,0x00,0x00,
-0x44,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdd,0x02,0x00,0x00,0xda,0x02,0x00,0x00,0xdc,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdf,0x02,0x00,0x00,
-0xdd,0x02,0x00,0x00,0x03,0x03,0x00,0x00,0x41,0x00,0x05,0x00,
-0xd9,0x00,0x00,0x00,0xe0,0x02,0x00,0x00,0xd6,0x00,0x00,0x00,
-0xdf,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xd0,0x00,0x00,0x00,
-0xe1,0x02,0x00,0x00,0xe0,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0xe2,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,
-0x15,0x00,0x00,0x00,0xd4,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xe3,0x02,0x00,0x00,0xe1,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe5,0x02,0x00,0x00,0x03,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xb7,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb9,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa4,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa4,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe7,0x02,0x00,0x00,
-0xfd,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa3,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x8c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe9,0x02,0x00,0x00,0xfb,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x89,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x84,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x84,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xeb,0x02,0x00,0x00,0xfa,0x02,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x81,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x83,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xec,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xec,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_f16_aligned_len = 11888;
-
-unsigned char matmul_id_f16_aligned_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x2e,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
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-0x8d,0x02,0x00,0x00,0xd3,0x02,0x00,0x00,0x44,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x89,0x02,0x00,0x00,0x88,0x02,0x00,0x00,
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-0x06,0x00,0x00,0x00,0xa6,0x02,0x00,0x00,0xca,0x02,0x00,0x00,
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-0xaf,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xd0,0x00,0x00,0x00,
-0xb1,0x02,0x00,0x00,0xb0,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0xb2,0x02,0x00,0x00,0xb3,0x02,0x00,0x00,0x91,0x02,0x00,0x00,
-0x15,0x00,0x00,0x00,0xa4,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xb3,0x02,0x00,0x00,0xb1,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb5,0x02,0x00,0x00,0xd3,0x02,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x87,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x89,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x74,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x74,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb7,0x02,0x00,0x00,
-0xcd,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x71,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x73,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb9,0x02,0x00,0x00,0xcb,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x59,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x54,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x54,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbb,0x02,0x00,0x00,0xca,0x02,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x51,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x53,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xbc,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xbc,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_f16_aligned_fp32_len = 10976;
-
-unsigned char matmul_id_f16_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x31,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x51,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x10,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x2e,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,0x90,0x00,0x00,0x00,
-0x05,0x01,0x00,0x00,0x10,0x01,0x00,0x00,0x4e,0x01,0x00,0x00,
-0x59,0x01,0x00,0x00,0x86,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
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-0x06,0x00,0x00,0x00,0xab,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x66,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x68,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x51,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x51,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xad,0x02,0x00,0x00,
-0xbf,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x4e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x50,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x49,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x49,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xaf,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x46,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x48,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xb0,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb0,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_f16_f32_len = 10804;
-
-unsigned char matmul_id_f16_f32_aligned_data[] = {
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-0xf9,0x00,0x02,0x00,0xf6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf6,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_id_f16_f32_aligned_len = 12048;
-
-unsigned char matmul_id_f16_f32_aligned_fp32_data[] = {
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-0x20,0x00,0x00,0x00,0x7e,0x02,0x00,0x00,0xb2,0x02,0x00,0x00,
-0x86,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0x6c,0x00,0x00,0x00,
-0x8b,0x02,0x00,0x00,0xd0,0x02,0x00,0x00,0x44,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x87,0x02,0x00,0x00,0x86,0x02,0x00,0x00,
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-0x06,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,0x96,0x02,0x00,0x00,
-0x9d,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa0,0x02,0x00,0x00,0x9e,0x02,0x00,0x00,0x65,0x02,0x00,0x00,
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-0x06,0x00,0x00,0x00,0xa4,0x02,0x00,0x00,0xc7,0x02,0x00,0x00,
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-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xad,0x02,0x00,0x00,
-0xab,0x02,0x00,0x00,0xd0,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
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-0xad,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xd0,0x00,0x00,0x00,
-0xaf,0x02,0x00,0x00,0xae,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0x76,0x01,0x00,0x00,0xb0,0x02,0x00,0x00,0x8f,0x02,0x00,0x00,
-0x15,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xb0,0x02,0x00,0x00,0xaf,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb2,0x02,0x00,0x00,0xd0,0x02,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x85,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x87,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x72,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x72,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb4,0x02,0x00,0x00,
-0xca,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x6f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x71,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb6,0x02,0x00,0x00,0xc8,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x57,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x59,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x52,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x52,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb8,0x02,0x00,0x00,0xc7,0x02,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x4f,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x51,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb9,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_f16_f32_aligned_fp32_len = 10928;
-
-unsigned char matmul_id_f16_f32_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x2d,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x10,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x1f,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0x90,0x00,0x00,0x00,0x04,0x01,0x00,0x00,0x10,0x01,0x00,0x00,
-0x4e,0x01,0x00,0x00,0x59,0x01,0x00,0x00,0x82,0x02,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0xf9,0x00,0x02,0x00,0x62,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x62,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xbd,0x02,0x00,0x00,0x20,0x00,0x00,0x00,0x4b,0x02,0x00,0x00,
-0xa7,0x02,0x00,0x00,0x65,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x6b,0x00,0x00,0x00,0x68,0x02,0x00,0x00,0xbd,0x02,0x00,0x00,
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-0x68,0x02,0x00,0x00,0x63,0x02,0x00,0x00,0x64,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x63,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
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-0x75,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x78,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x78,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xc3,0x02,0x00,0x00,0x20,0x00,0x00,0x00,
-0x71,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0x79,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,0x7e,0x02,0x00,0x00,
-0xc3,0x02,0x00,0x00,0x44,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x7a,0x02,0x00,0x00,0x79,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x7e,0x02,0x00,0x00,0x79,0x02,0x00,0x00,
-0x7a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x79,0x02,0x00,0x00,
-0x51,0x00,0x05,0x00,0x8b,0x00,0x00,0x00,0x84,0x02,0x00,0x00,
-0x76,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x71,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x85,0x02,0x00,0x00,0x84,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0x87,0x02,0x00,0x00,
-0x13,0x00,0x00,0x00,0x86,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x88,0x02,0x00,0x00,0x87,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x89,0x02,0x00,0x00,
-0x85,0x02,0x00,0x00,0x88,0x02,0x00,0x00,0x51,0x00,0x05,0x00,
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-0x06,0x00,0x00,0x00,0x90,0x02,0x00,0x00,0x8c,0x02,0x00,0x00,
-0x8f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x91,0x02,0x00,0x00,0x89,0x02,0x00,0x00,0x90,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x93,0x02,0x00,0x00,
-0x91,0x02,0x00,0x00,0x58,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x95,0x02,0x00,0x00,0x93,0x02,0x00,0x00,
-0xc3,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x97,0x02,0x00,0x00,0xba,0x02,0x00,0x00,0xc8,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x99,0x02,0x00,0x00,
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-0x9a,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9d,0x02,0x00,0x00,0xbb,0x02,0x00,0x00,0x44,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,
-0x9b,0x02,0x00,0x00,0x9d,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa0,0x02,0x00,0x00,0x9e,0x02,0x00,0x00,
-0xc3,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xd8,0x00,0x00,0x00,
-0xa1,0x02,0x00,0x00,0xd5,0x00,0x00,0x00,0xa0,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xcf,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,
-0xa1,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0x72,0x01,0x00,0x00,
-0xa3,0x02,0x00,0x00,0x82,0x02,0x00,0x00,0x15,0x00,0x00,0x00,
-0x95,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0xa3,0x02,0x00,0x00,
-0xa2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa5,0x02,0x00,0x00,0xc3,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x78,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7a,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x65,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x65,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,0xbd,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x62,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x64,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x4d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x4d,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa9,0x02,0x00,0x00,
-0xbb,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x4a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x4c,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x45,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x45,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xab,0x02,0x00,0x00,0xba,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x42,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x44,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xac,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xac,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_f16_f32_fp32_len = 10732;
-
-unsigned char matmul_id_f16_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x2e,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x10,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x1f,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0x90,0x00,0x00,0x00,0x04,0x01,0x00,0x00,0x10,0x01,0x00,0x00,
-0x4e,0x01,0x00,0x00,0x59,0x01,0x00,0x00,0x82,0x02,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x11,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x19,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1f,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x2e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x31,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x35,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x42,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x44,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x4e,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x78,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x79,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x79,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x79,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x7b,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x7b,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xa2,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xc5,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xc8,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0d,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
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-0xa2,0x02,0x00,0x00,0xa1,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0xa3,0x02,0x00,0x00,0xa4,0x02,0x00,0x00,0x82,0x02,0x00,0x00,
-0x15,0x00,0x00,0x00,0x95,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xa4,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa6,0x02,0x00,0x00,0xc4,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x78,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7a,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x65,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x65,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa8,0x02,0x00,0x00,
-0xbe,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x62,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x64,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x4d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x4d,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xaa,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x4a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x4c,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x45,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x45,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xac,0x02,0x00,0x00,0xbb,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x42,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x44,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xad,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xad,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_f16_fp32_len = 10748;
-
-unsigned char matmul_id_f32_f16_data[] = {
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-0x06,0x00,0x00,0x00,0xab,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x66,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x68,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x51,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x51,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xad,0x02,0x00,0x00,
-0xbf,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x4e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x50,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x49,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x49,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xaf,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x46,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x48,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xb0,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb0,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_f32_f16_len = 10804;
-
-unsigned char matmul_id_f32_f16_aligned_data[] = {
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-0x0d,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
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-0xaf,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf1,0x02,0x00,0x00,0x07,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xac,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xae,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x97,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x97,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf3,0x02,0x00,0x00,0x05,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x94,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x96,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x8f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x8f,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf5,0x02,0x00,0x00,
-0x04,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x8c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x8e,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xf6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf6,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_id_f32_f16_aligned_len = 12048;
-
-unsigned char matmul_id_f32_f16_aligned_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x2b,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
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-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
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-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x8b,0x02,0x00,0x00,
-0x86,0x02,0x00,0x00,0x87,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x86,0x02,0x00,0x00,0x51,0x00,0x05,0x00,0x8c,0x00,0x00,0x00,
-0x91,0x02,0x00,0x00,0x83,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
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-0x9d,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa0,0x02,0x00,0x00,0x9e,0x02,0x00,0x00,0x65,0x02,0x00,0x00,
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-0xaf,0x02,0x00,0x00,0xae,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
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-0xb0,0x02,0x00,0x00,0xaf,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb2,0x02,0x00,0x00,0xd0,0x02,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x85,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x87,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x72,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x72,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb4,0x02,0x00,0x00,
-0xca,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x6f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x71,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb6,0x02,0x00,0x00,0xc8,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x57,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x59,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x52,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x52,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb8,0x02,0x00,0x00,0xc7,0x02,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x4f,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x51,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb9,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_f32_f16_aligned_fp32_len = 10928;
-
-unsigned char matmul_id_f32_f16_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x2d,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
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-0x06,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,0xbd,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x62,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x64,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x4d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x4d,0x02,0x00,0x00,
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-0xbb,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x4a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x4c,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x45,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x45,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xab,0x02,0x00,0x00,0xba,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x42,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x44,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xac,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xac,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_f32_f16_fp32_len = 10732;
-
-unsigned char matmul_id_f32_f32_data[] = {
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-0x06,0x00,0x00,0x00,0xa9,0x02,0x00,0x00,0xc7,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x7c,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7e,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x69,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x69,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xab,0x02,0x00,0x00,
-0xc1,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x66,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x68,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x51,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x51,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xad,0x02,0x00,0x00,0xbf,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x4e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x50,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x49,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x49,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xaf,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x46,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x48,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb0,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb0,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_f32_f32_len = 10796;
-
-unsigned char matmul_id_f32_f32_aligned_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x6d,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
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-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
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-0x91,0x00,0x00,0x00,0x08,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,
-0x8e,0x01,0x00,0x00,0x94,0x01,0x00,0x00,0xd1,0x02,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
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-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
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-0x91,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x93,0x02,0x00,0x00,
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-0xfb,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_id_f32_f32_aligned_len = 12120;
-
-unsigned char matmul_id_f32_f32_aligned_fp32_data[] = {
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-0xf9,0x00,0x02,0x00,0x6b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x6b,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xad,0x02,0x00,0x00,0xc3,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x68,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x6a,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x53,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x53,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xaf,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x50,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x52,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x4b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x4b,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb1,0x02,0x00,0x00,
-0xc0,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x48,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x4a,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xb2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xb2,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_id_f32_f32_aligned_fp32_len = 10812;
-
-unsigned char matmul_id_f32_f32_fp32_data[] = {
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-0xc0,0x02,0x00,0x00,0x20,0x00,0x00,0x00,0x6e,0x02,0x00,0x00,
-0xa2,0x02,0x00,0x00,0x76,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x6b,0x00,0x00,0x00,0x7b,0x02,0x00,0x00,0xc0,0x02,0x00,0x00,
-0x44,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x77,0x02,0x00,0x00,
-0x76,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x7b,0x02,0x00,0x00,0x76,0x02,0x00,0x00,0x77,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x76,0x02,0x00,0x00,0x51,0x00,0x05,0x00,
-0x8b,0x00,0x00,0x00,0x81,0x02,0x00,0x00,0x73,0x02,0x00,0x00,
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-0x82,0x02,0x00,0x00,0x81,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
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-0x83,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x85,0x02,0x00,0x00,0x84,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
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-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8e,0x02,0x00,0x00,
-0x86,0x02,0x00,0x00,0x8d,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x90,0x02,0x00,0x00,0x8e,0x02,0x00,0x00,
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-0x92,0x02,0x00,0x00,0x90,0x02,0x00,0x00,0xc0,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x94,0x02,0x00,0x00,
-0xb7,0x02,0x00,0x00,0xc8,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x96,0x02,0x00,0x00,0x94,0x02,0x00,0x00,
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-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9a,0x02,0x00,0x00,
-0xb8,0x02,0x00,0x00,0x44,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9b,0x02,0x00,0x00,0x98,0x02,0x00,0x00,
-0x9a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9d,0x02,0x00,0x00,0x9b,0x02,0x00,0x00,0xc0,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0xd8,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,
-0xd5,0x00,0x00,0x00,0x9d,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xcf,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,0x9e,0x02,0x00,0x00,
-0x41,0x00,0x06,0x00,0x1a,0x01,0x00,0x00,0xa0,0x02,0x00,0x00,
-0x7f,0x02,0x00,0x00,0x15,0x00,0x00,0x00,0x92,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xa0,0x02,0x00,0x00,0x9f,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,
-0xc0,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x75,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x77,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x62,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x62,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa4,0x02,0x00,0x00,0xba,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x61,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x4a,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x4a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa6,0x02,0x00,0x00,0xb8,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x47,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x49,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x42,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x42,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa8,0x02,0x00,0x00,
-0xb7,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x3f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x41,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa9,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_id_f32_f32_fp32_len = 10680;
-
-unsigned char matmul_id_q2_k_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x75,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x10,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,
-0x7b,0x00,0x00,0x00,0x90,0x00,0x00,0x00,0x29,0x01,0x00,0x00,
-0x63,0x01,0x00,0x00,0x94,0x01,0x00,0x00,0x9f,0x01,0x00,0x00,
-0xcc,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
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-0x94,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x96,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x8f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf5,0x02,0x00,0x00,0x08,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x8c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8e,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xf6,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf6,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q2_k_f32_len = 11692;
-
-unsigned char matmul_id_q2_k_f32_aligned_data[] = {
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-0x1b,0x03,0x00,0x00,0x1a,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x1d,0x03,0x00,0x00,0x3f,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xf0,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf2,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xdd,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xdd,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1f,0x03,0x00,0x00,
-0x39,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xda,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xdc,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xc5,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xc5,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x21,0x03,0x00,0x00,0x37,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xc2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xc4,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xbd,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xbd,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x23,0x03,0x00,0x00,0x36,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xba,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xbc,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x24,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x24,0x03,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q2_k_f32_aligned_len = 12488;
-
-unsigned char matmul_id_q2_k_f32_aligned_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x75,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
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-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
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-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
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-0x2a,0x01,0x00,0x00,0x64,0x01,0x00,0x00,0xaf,0x01,0x00,0x00,
-0xb6,0x01,0x00,0x00,0xd1,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
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-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0x11,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x11,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x19,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x1f,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x2e,0x00,0x00,0x00,
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-0x06,0x00,0x00,0x00,0xe0,0x02,0x00,0x00,0xd8,0x02,0x00,0x00,
-0xdf,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe2,0x02,0x00,0x00,0xe0,0x02,0x00,0x00,0xa7,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe4,0x02,0x00,0x00,
-0xe2,0x02,0x00,0x00,0x16,0x03,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe6,0x02,0x00,0x00,0x0d,0x03,0x00,0x00,
-0xc9,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe8,0x02,0x00,0x00,0xe6,0x02,0x00,0x00,0x10,0x03,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xea,0x02,0x00,0x00,
-0xe8,0x02,0x00,0x00,0xe9,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xec,0x02,0x00,0x00,0x0e,0x03,0x00,0x00,
-0x44,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xed,0x02,0x00,0x00,0xea,0x02,0x00,0x00,0xec,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xef,0x02,0x00,0x00,
-0xed,0x02,0x00,0x00,0x16,0x03,0x00,0x00,0x41,0x00,0x05,0x00,
-0xd9,0x00,0x00,0x00,0xf0,0x02,0x00,0x00,0xd6,0x00,0x00,0x00,
-0xef,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xd0,0x00,0x00,0x00,
-0xf1,0x02,0x00,0x00,0xf0,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0xb8,0x01,0x00,0x00,0xf2,0x02,0x00,0x00,0xd1,0x02,0x00,0x00,
-0x15,0x00,0x00,0x00,0xe4,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xf2,0x02,0x00,0x00,0xf1,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf4,0x02,0x00,0x00,0x16,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xc7,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc9,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb4,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb4,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf6,0x02,0x00,0x00,
-0x10,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb3,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x9c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf8,0x02,0x00,0x00,0x0e,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x99,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x94,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x94,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xfa,0x02,0x00,0x00,0x0d,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x91,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x93,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xfb,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xfb,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q2_k_f32_aligned_fp32_len = 11756;
-
-unsigned char matmul_id_q2_k_f32_fp32_data[] = {
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-0x0a,0x03,0x00,0x00,0x41,0x00,0x05,0x00,0xd8,0x00,0x00,0x00,
-0xe4,0x02,0x00,0x00,0xd5,0x00,0x00,0x00,0xe3,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xcf,0x00,0x00,0x00,0xe5,0x02,0x00,0x00,
-0xe4,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0xb5,0x01,0x00,0x00,
-0xe6,0x02,0x00,0x00,0xc5,0x02,0x00,0x00,0x15,0x00,0x00,0x00,
-0xd8,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0xe6,0x02,0x00,0x00,
-0xe5,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe8,0x02,0x00,0x00,0x0a,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xbb,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xbd,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xa8,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa8,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xea,0x02,0x00,0x00,0x04,0x03,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xa5,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa7,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x90,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x90,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xec,0x02,0x00,0x00,
-0x02,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x8d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x8f,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x88,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x88,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xee,0x02,0x00,0x00,0x01,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x85,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x87,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xef,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xef,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q2_k_f32_fp32_len = 11572;
-
-unsigned char matmul_id_q3_k_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xff,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x27,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x10,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x1f,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0x90,0x00,0x00,0x00,0x44,0x01,0x00,0x00,0xb5,0x01,0x00,0x00,
-0x14,0x02,0x00,0x00,0x1f,0x02,0x00,0x00,0x4c,0x03,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
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-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x11,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x19,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
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-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x79,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x7b,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x7b,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xa2,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
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-
-};
-const uint64_t matmul_id_q3_k_f32_len = 13596;
-
-unsigned char matmul_id_q3_k_f32_aligned_data[] = {
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-0xa3,0x03,0x00,0x00,0xb2,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x3a,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x3c,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0xa4,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa4,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q3_k_f32_aligned_len = 14392;
-
-unsigned char matmul_id_q3_k_f32_aligned_fp32_data[] = {
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-0xf9,0x00,0x02,0x00,0x11,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
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-0xf8,0x00,0x02,0x00,0x7b,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q3_k_f32_aligned_fp32_len = 13660;
-
-unsigned char matmul_id_q3_k_f32_fp32_data[] = {
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-0xf9,0x00,0x02,0x00,0x25,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
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-0x06,0x00,0x00,0x00,0x6c,0x03,0x00,0x00,0x7e,0x03,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x0d,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x0f,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x08,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x08,0x03,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x6e,0x03,0x00,0x00,
-0x7d,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x05,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x07,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x6f,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x6f,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_id_q3_k_f32_fp32_len = 13476;
-
-unsigned char matmul_id_q4_0_f32_data[] = {
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-0x06,0x00,0x00,0x00,0xbe,0x02,0x00,0x00,0xde,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x91,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x93,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7e,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc0,0x02,0x00,0x00,
-0xd8,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7d,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x66,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x66,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc2,0x02,0x00,0x00,0xd6,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x63,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x65,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x5e,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x5e,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc4,0x02,0x00,0x00,0xd5,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x5b,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x5d,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xc5,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xc5,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q4_0_f32_len = 11036;
-
-unsigned char matmul_id_q4_0_f32_aligned_data[] = {
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-0x0e,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
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-0xae,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf0,0x02,0x00,0x00,0x08,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xab,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xad,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x96,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x96,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf2,0x02,0x00,0x00,0x06,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x93,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x95,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x8e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x8e,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf4,0x02,0x00,0x00,
-0x05,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x8b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x8d,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xf5,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf5,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_id_q4_0_f32_aligned_len = 11844;
-
-unsigned char matmul_id_q4_0_f32_aligned_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x43,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x10,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x2e,0x00,0x00,0x00,0x7c,0x00,0x00,0x00,0x91,0x00,0x00,0x00,
-0x12,0x01,0x00,0x00,0x33,0x01,0x00,0x00,0x7e,0x01,0x00,0x00,
-0x85,0x01,0x00,0x00,0xa1,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
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-0x06,0x00,0x00,0x00,0xb0,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
-0xaf,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb2,0x02,0x00,0x00,0xb0,0x02,0x00,0x00,0x77,0x02,0x00,0x00,
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-0x15,0x00,0x00,0x00,0xb4,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xc2,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc4,0x02,0x00,0x00,0xe4,0x02,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x97,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x99,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x84,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x84,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc6,0x02,0x00,0x00,
-0xde,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x81,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x83,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x6c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x6c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc8,0x02,0x00,0x00,0xdc,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x69,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x6b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x64,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x64,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xca,0x02,0x00,0x00,0xdb,0x02,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x61,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x63,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xcb,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xcb,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q4_0_f32_aligned_fp32_len = 11096;
-
-unsigned char matmul_id_q4_0_f32_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x3b,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x10,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x2e,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,0x90,0x00,0x00,0x00,
-0x11,0x01,0x00,0x00,0x32,0x01,0x00,0x00,0x61,0x01,0x00,0x00,
-0x6c,0x01,0x00,0x00,0x94,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
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-0xec,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x6f,0x02,0x00,0x00,0x52,0x02,0x00,0x00,0x6e,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x71,0x02,0x00,0x00,
-0x4a,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x72,0x02,0x00,0x00,0x6f,0x02,0x00,0x00,
-0x71,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x74,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x74,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xd1,0x02,0x00,0x00,0x20,0x00,0x00,0x00,
-0x5d,0x02,0x00,0x00,0xb9,0x02,0x00,0x00,0x77,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,0x7a,0x02,0x00,0x00,
-0xd1,0x02,0x00,0x00,0xc8,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x76,0x02,0x00,0x00,0x77,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x7a,0x02,0x00,0x00,0x75,0x02,0x00,0x00,
-0x76,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x75,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x7e,0x02,0x00,0x00,
-0x72,0x02,0x00,0x00,0xd1,0x02,0x00,0x00,0xae,0x00,0x05,0x00,
-0x6b,0x00,0x00,0x00,0x81,0x02,0x00,0x00,0x7e,0x02,0x00,0x00,
-0xcb,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,0x83,0x02,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x81,0x02,0x00,0x00,
-0x82,0x02,0x00,0x00,0x83,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x82,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x76,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x83,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x97,0x00,0x00,0x00,0x87,0x02,0x00,0x00,0x90,0x00,0x00,0x00,
-0x7e,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x8c,0x00,0x00,0x00,
-0x88,0x02,0x00,0x00,0x87,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x8a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x8a,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xd7,0x02,0x00,0x00,
-0x20,0x00,0x00,0x00,0x83,0x02,0x00,0x00,0xb7,0x02,0x00,0x00,
-0x8b,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,
-0x90,0x02,0x00,0x00,0xd7,0x02,0x00,0x00,0x44,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x8c,0x02,0x00,0x00,0x8b,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x90,0x02,0x00,0x00,
-0x8b,0x02,0x00,0x00,0x8c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8b,0x02,0x00,0x00,0x51,0x00,0x05,0x00,0x8b,0x00,0x00,0x00,
-0x96,0x02,0x00,0x00,0x88,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x97,0x02,0x00,0x00,
-0x96,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
-0x99,0x02,0x00,0x00,0x13,0x00,0x00,0x00,0x98,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x9a,0x02,0x00,0x00,
-0x99,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9b,0x02,0x00,0x00,0x97,0x02,0x00,0x00,0x9a,0x02,0x00,0x00,
-0x51,0x00,0x05,0x00,0x8b,0x00,0x00,0x00,0x9d,0x02,0x00,0x00,
-0x88,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x71,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,0x9d,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0xa0,0x02,0x00,0x00,
-0x13,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xa1,0x02,0x00,0x00,0xa0,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,
-0x9e,0x02,0x00,0x00,0xa1,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa3,0x02,0x00,0x00,0x9b,0x02,0x00,0x00,
-0xa2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa5,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,0x6a,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,
-0xa5,0x02,0x00,0x00,0xd7,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa9,0x02,0x00,0x00,0xce,0x02,0x00,0x00,
-0xc8,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xab,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,0xd1,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xad,0x02,0x00,0x00,
-0xab,0x02,0x00,0x00,0xac,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xaf,0x02,0x00,0x00,0xcf,0x02,0x00,0x00,
-0x44,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb0,0x02,0x00,0x00,0xad,0x02,0x00,0x00,0xaf,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb2,0x02,0x00,0x00,
-0xb0,0x02,0x00,0x00,0xd7,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0xd8,0x00,0x00,0x00,0xb3,0x02,0x00,0x00,0xd5,0x00,0x00,0x00,
-0xb2,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xcf,0x00,0x00,0x00,
-0xb4,0x02,0x00,0x00,0xb3,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0x84,0x01,0x00,0x00,0xb5,0x02,0x00,0x00,0x94,0x02,0x00,0x00,
-0x15,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xb5,0x02,0x00,0x00,0xb4,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb7,0x02,0x00,0x00,0xd7,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x8a,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x8c,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x77,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x77,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb9,0x02,0x00,0x00,
-0xd1,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x74,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x76,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xbb,0x02,0x00,0x00,0xcf,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5e,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x57,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x57,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbd,0x02,0x00,0x00,0xce,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x54,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x56,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xbe,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xbe,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q4_0_f32_fp32_len = 10916;
-
-unsigned char matmul_id_q4_1_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x43,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x10,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,
-0x7b,0x00,0x00,0x00,0x90,0x00,0x00,0x00,0x11,0x01,0x00,0x00,
-0x37,0x01,0x00,0x00,0x68,0x01,0x00,0x00,0x73,0x01,0x00,0x00,
-0xa0,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x30,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x11,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x19,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x1f,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x2e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x31,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x35,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x42,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x44,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4e,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x78,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x79,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x79,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x79,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x7b,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x7b,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xa2,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xc5,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xc8,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0c,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x0d,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x0d,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
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-0xc0,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc3,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x96,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x98,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x83,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x83,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc5,0x02,0x00,0x00,0xdd,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x80,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x82,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x6b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x6b,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc7,0x02,0x00,0x00,
-0xdb,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x68,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x6a,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x63,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x63,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc9,0x02,0x00,0x00,0xda,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x60,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x62,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xca,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xca,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q4_1_f32_len = 11104;
-
-unsigned char matmul_id_q4_1_f32_aligned_data[] = {
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-0xf1,0x02,0x00,0x00,0xf0,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf3,0x02,0x00,0x00,0x13,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xc6,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc8,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb3,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf5,0x02,0x00,0x00,
-0x0d,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb0,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb2,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x9b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9b,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf7,0x02,0x00,0x00,0x0b,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x98,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9a,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x93,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x93,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf9,0x02,0x00,0x00,0x0a,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x90,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x92,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xfa,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xfa,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q4_1_f32_aligned_len = 11912;
-
-unsigned char matmul_id_q4_1_f32_aligned_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x44,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x10,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x2e,0x00,0x00,0x00,0x7c,0x00,0x00,0x00,0x91,0x00,0x00,0x00,
-0x12,0x01,0x00,0x00,0x38,0x01,0x00,0x00,0x83,0x01,0x00,0x00,
-0x8a,0x01,0x00,0x00,0xa6,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0x3d,0x00,0x04,0x00,0xd0,0x00,0x00,0x00,0xc6,0x02,0x00,0x00,
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-0xb9,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0xc7,0x02,0x00,0x00,
-0xc6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc9,0x02,0x00,0x00,0xe9,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x9c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9e,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x89,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x89,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xcb,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x86,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x88,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x71,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x71,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xcd,0x02,0x00,0x00,
-0xe1,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x6e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x70,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x69,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x69,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xcf,0x02,0x00,0x00,0xe0,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x66,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x68,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xd0,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd0,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q4_1_f32_aligned_fp32_len = 11164;
-
-unsigned char matmul_id_q4_1_f32_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x3c,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x10,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x2e,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,0x90,0x00,0x00,0x00,
-0x11,0x01,0x00,0x00,0x37,0x01,0x00,0x00,0x66,0x01,0x00,0x00,
-0x71,0x01,0x00,0x00,0x99,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
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-0x5b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5a,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x61,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x61,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xd4,0x02,0x00,0x00,0x20,0x00,0x00,0x00,0x5a,0x02,0x00,0x00,
-0xc0,0x02,0x00,0x00,0x64,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x6b,0x00,0x00,0x00,0x67,0x02,0x00,0x00,0xd4,0x02,0x00,0x00,
-0x42,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x63,0x02,0x00,0x00,
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-0x06,0x00,0x00,0x00,0x76,0x02,0x00,0x00,0x4a,0x00,0x00,0x00,
-0xc8,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x77,0x02,0x00,0x00,0x74,0x02,0x00,0x00,0x76,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x79,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x79,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xd6,0x02,0x00,0x00,0x20,0x00,0x00,0x00,0x62,0x02,0x00,0x00,
-0xbe,0x02,0x00,0x00,0x7c,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x6b,0x00,0x00,0x00,0x7f,0x02,0x00,0x00,0xd6,0x02,0x00,0x00,
-0xc8,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x7b,0x02,0x00,0x00,
-0x7c,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x7f,0x02,0x00,0x00,0x7a,0x02,0x00,0x00,0x7b,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x83,0x02,0x00,0x00,0x77,0x02,0x00,0x00,
-0xd6,0x02,0x00,0x00,0xae,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,
-0x86,0x02,0x00,0x00,0x83,0x02,0x00,0x00,0xd0,0x02,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x88,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x86,0x02,0x00,0x00,0x87,0x02,0x00,0x00,
-0x88,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x87,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x88,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x97,0x00,0x00,0x00,
-0x8c,0x02,0x00,0x00,0x90,0x00,0x00,0x00,0x83,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x8c,0x00,0x00,0x00,0x8d,0x02,0x00,0x00,
-0x8c,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x8f,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x8f,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xdc,0x02,0x00,0x00,0x20,0x00,0x00,0x00,
-0x88,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,0x90,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,0x95,0x02,0x00,0x00,
-0xdc,0x02,0x00,0x00,0x44,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x91,0x02,0x00,0x00,0x90,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x95,0x02,0x00,0x00,0x90,0x02,0x00,0x00,
-0x91,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x90,0x02,0x00,0x00,
-0x51,0x00,0x05,0x00,0x8b,0x00,0x00,0x00,0x9b,0x02,0x00,0x00,
-0x8d,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x71,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x9c,0x02,0x00,0x00,0x9b,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,
-0x13,0x00,0x00,0x00,0x9d,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,0x9e,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa0,0x02,0x00,0x00,
-0x9c,0x02,0x00,0x00,0x9f,0x02,0x00,0x00,0x51,0x00,0x05,0x00,
-0x8b,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,0x8d,0x02,0x00,0x00,
-0x00,0x00,0x00,0x00,0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xa3,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x16,0x00,0x00,0x00,0xa5,0x02,0x00,0x00,0x13,0x00,0x00,0x00,
-0xa4,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xa6,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,
-0xa6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa8,0x02,0x00,0x00,0xa0,0x02,0x00,0x00,0xa7,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xaa,0x02,0x00,0x00,
-0xa8,0x02,0x00,0x00,0x6f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xac,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
-0xdc,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xae,0x02,0x00,0x00,0xd3,0x02,0x00,0x00,0xc8,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb0,0x02,0x00,0x00,
-0xae,0x02,0x00,0x00,0xd6,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb2,0x02,0x00,0x00,0xb0,0x02,0x00,0x00,
-0xb1,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb4,0x02,0x00,0x00,0xd4,0x02,0x00,0x00,0x44,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb5,0x02,0x00,0x00,
-0xb2,0x02,0x00,0x00,0xb4,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb7,0x02,0x00,0x00,0xb5,0x02,0x00,0x00,
-0xdc,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xd8,0x00,0x00,0x00,
-0xb8,0x02,0x00,0x00,0xd5,0x00,0x00,0x00,0xb7,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xcf,0x00,0x00,0x00,0xb9,0x02,0x00,0x00,
-0xb8,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0x89,0x01,0x00,0x00,
-0xba,0x02,0x00,0x00,0x99,0x02,0x00,0x00,0x15,0x00,0x00,0x00,
-0xac,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0xba,0x02,0x00,0x00,
-0xb9,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xbc,0x02,0x00,0x00,0xdc,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x8f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x91,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x7c,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbe,0x02,0x00,0x00,0xd6,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x79,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x64,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x64,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc0,0x02,0x00,0x00,
-0xd4,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x61,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x63,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc2,0x02,0x00,0x00,0xd3,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x59,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xc3,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc3,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q4_1_f32_fp32_len = 10984;
-
-unsigned char matmul_id_q4_k_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xb5,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x27,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x10,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x1f,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0x90,0x00,0x00,0x00,0x2b,0x01,0x00,0x00,0x83,0x01,0x00,0x00,
-0xcf,0x01,0x00,0x00,0xda,0x01,0x00,0x00,0x07,0x03,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x11,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x19,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1f,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x2e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x31,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x35,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x42,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
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-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x03,0x03,0x00,0x00,
-0xfe,0x02,0x00,0x00,0xff,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
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-0x06,0x00,0x00,0x00,0x2a,0x03,0x00,0x00,0x4a,0x03,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xfd,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xff,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xea,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xea,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x2c,0x03,0x00,0x00,
-0x44,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe7,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe9,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xd2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x2e,0x03,0x00,0x00,0x42,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xcf,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd1,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xca,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xca,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x30,0x03,0x00,0x00,0x41,0x03,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xc7,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc9,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x31,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x31,0x03,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q4_k_f32_len = 12524;
-
-unsigned char matmul_id_q4_k_f32_aligned_data[] = {
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-0xfe,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x00,0x03,0x00,0x00,
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-0xf9,0x00,0x02,0x00,0xf6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf8,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x60,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x60,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q4_k_f32_aligned_len = 13336;
-
-unsigned char matmul_id_q4_k_f32_aligned_fp32_data[] = {
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-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x2f,0x03,0x00,0x00,
-0x4f,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x02,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x04,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xef,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xef,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x31,0x03,0x00,0x00,0x49,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xec,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xee,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xd7,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd7,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x33,0x03,0x00,0x00,0x47,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xd4,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd6,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xcf,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xcf,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x35,0x03,0x00,0x00,
-0x46,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xcc,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xce,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x36,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x36,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_id_q4_k_f32_aligned_fp32_len = 12588;
-
-unsigned char matmul_id_q4_k_f32_fp32_data[] = {
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-0x5a,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x6c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x6e,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x0c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x0c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb0,0x02,0x00,0x00,0x54,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x09,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x0b,0x02,0x00,0x00,0xe0,0x00,0x04,0x00,0x0c,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe0,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xe0,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb2,0x02,0x00,0x00,
-0x39,0x03,0x00,0x00,0x4e,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xdd,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xdf,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb7,0x02,0x00,0x00,
-0x37,0x00,0x00,0x00,0x35,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb8,0x02,0x00,0x00,0xb4,0x00,0x00,0x00,
-0xb7,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xbd,0x02,0x00,0x00,0x3b,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xbe,0x02,0x00,0x00,
-0xa3,0x00,0x00,0x00,0xbd,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xc0,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xc0,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x3a,0x03,0x00,0x00,
-0x20,0x00,0x00,0x00,0xdf,0x00,0x00,0x00,0x29,0x03,0x00,0x00,
-0xc3,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,
-0xc6,0x02,0x00,0x00,0x3a,0x03,0x00,0x00,0xcb,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xc2,0x02,0x00,0x00,0xc3,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xc6,0x02,0x00,0x00,
-0xc1,0x02,0x00,0x00,0xc2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xc1,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xc8,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc8,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x3b,0x03,0x00,0x00,0x20,0x00,0x00,0x00,
-0xc1,0x02,0x00,0x00,0x27,0x03,0x00,0x00,0xcb,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,0xce,0x02,0x00,0x00,
-0x3b,0x03,0x00,0x00,0x42,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xca,0x02,0x00,0x00,0xcb,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xce,0x02,0x00,0x00,0xc9,0x02,0x00,0x00,
-0xca,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xc9,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd2,0x02,0x00,0x00,
-0x3b,0x03,0x00,0x00,0x43,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd3,0x02,0x00,0x00,0xb8,0x02,0x00,0x00,
-0xd2,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd5,0x02,0x00,0x00,0x46,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd6,0x02,0x00,0x00,
-0xd3,0x02,0x00,0x00,0xd5,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xda,0x02,0x00,0x00,0x3a,0x03,0x00,0x00,
-0x58,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdb,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,0xda,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdd,0x02,0x00,0x00,
-0x4a,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xde,0x02,0x00,0x00,0xdb,0x02,0x00,0x00,
-0xdd,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xe0,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe0,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x3d,0x03,0x00,0x00,0x20,0x00,0x00,0x00,
-0xc9,0x02,0x00,0x00,0x25,0x03,0x00,0x00,0xe3,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,0xe6,0x02,0x00,0x00,
-0x3d,0x03,0x00,0x00,0xc8,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xe2,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xe6,0x02,0x00,0x00,0xe1,0x02,0x00,0x00,
-0xe2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe1,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xea,0x02,0x00,0x00,
-0xde,0x02,0x00,0x00,0x3d,0x03,0x00,0x00,0xae,0x00,0x05,0x00,
-0x6b,0x00,0x00,0x00,0xed,0x02,0x00,0x00,0xea,0x02,0x00,0x00,
-0x37,0x03,0x00,0x00,0xf7,0x00,0x03,0x00,0xef,0x02,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xed,0x02,0x00,0x00,
-0xee,0x02,0x00,0x00,0xef,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xee,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xe2,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xef,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x97,0x00,0x00,0x00,0xf3,0x02,0x00,0x00,0x90,0x00,0x00,0x00,
-0xea,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x8c,0x00,0x00,0x00,
-0xf4,0x02,0x00,0x00,0xf3,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xf6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xf6,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x43,0x03,0x00,0x00,
-0x20,0x00,0x00,0x00,0xef,0x02,0x00,0x00,0x23,0x03,0x00,0x00,
-0xf7,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,
-0xfc,0x02,0x00,0x00,0x43,0x03,0x00,0x00,0x44,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xf8,0x02,0x00,0x00,0xf7,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xfc,0x02,0x00,0x00,
-0xf7,0x02,0x00,0x00,0xf8,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf7,0x02,0x00,0x00,0x51,0x00,0x05,0x00,0x8b,0x00,0x00,0x00,
-0x02,0x03,0x00,0x00,0xf4,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x03,0x03,0x00,0x00,
-0x02,0x03,0x00,0x00,0x41,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
-0x05,0x03,0x00,0x00,0x13,0x00,0x00,0x00,0x04,0x03,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x06,0x03,0x00,0x00,
-0x05,0x03,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x07,0x03,0x00,0x00,0x03,0x03,0x00,0x00,0x06,0x03,0x00,0x00,
-0x51,0x00,0x05,0x00,0x8b,0x00,0x00,0x00,0x09,0x03,0x00,0x00,
-0xf4,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x71,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x0a,0x03,0x00,0x00,0x09,0x03,0x00,0x00,
-0x41,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0x0c,0x03,0x00,0x00,
-0x13,0x00,0x00,0x00,0x0b,0x03,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x0d,0x03,0x00,0x00,0x0c,0x03,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x0e,0x03,0x00,0x00,
-0x0a,0x03,0x00,0x00,0x0d,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x0f,0x03,0x00,0x00,0x07,0x03,0x00,0x00,
-0x0e,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x11,0x03,0x00,0x00,0x0f,0x03,0x00,0x00,0xd6,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x13,0x03,0x00,0x00,
-0x11,0x03,0x00,0x00,0x43,0x03,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x15,0x03,0x00,0x00,0x3a,0x03,0x00,0x00,
-0xc8,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x17,0x03,0x00,0x00,0x15,0x03,0x00,0x00,0x3d,0x03,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x19,0x03,0x00,0x00,
-0x17,0x03,0x00,0x00,0x18,0x03,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x1b,0x03,0x00,0x00,0x3b,0x03,0x00,0x00,
-0x44,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x1c,0x03,0x00,0x00,0x19,0x03,0x00,0x00,0x1b,0x03,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1e,0x03,0x00,0x00,
-0x1c,0x03,0x00,0x00,0x43,0x03,0x00,0x00,0x41,0x00,0x05,0x00,
-0xd8,0x00,0x00,0x00,0x1f,0x03,0x00,0x00,0xd5,0x00,0x00,0x00,
-0x1e,0x03,0x00,0x00,0x3d,0x00,0x04,0x00,0xcf,0x00,0x00,0x00,
-0x20,0x03,0x00,0x00,0x1f,0x03,0x00,0x00,0x41,0x00,0x06,0x00,
-0xf0,0x01,0x00,0x00,0x21,0x03,0x00,0x00,0x00,0x03,0x00,0x00,
-0x15,0x00,0x00,0x00,0x13,0x03,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x21,0x03,0x00,0x00,0x20,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x23,0x03,0x00,0x00,0x43,0x03,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xf6,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf8,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe3,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x25,0x03,0x00,0x00,
-0x3d,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe0,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe2,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xcb,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xcb,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x27,0x03,0x00,0x00,0x3b,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xc8,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xca,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xc3,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc3,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x29,0x03,0x00,0x00,0x3a,0x03,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xc0,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc2,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x2a,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x2a,0x03,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q4_k_f32_fp32_len = 12404;
-
-unsigned char matmul_id_q5_0_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x6c,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x10,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,
-0x7b,0x00,0x00,0x00,0x90,0x00,0x00,0x00,0x12,0x01,0x00,0x00,
-0x5a,0x01,0x00,0x00,0x8b,0x01,0x00,0x00,0x96,0x01,0x00,0x00,
-0xc3,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
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-
-};
-const uint64_t matmul_id_q5_0_f32_len = 11532;
-
-unsigned char matmul_id_q5_0_f32_aligned_data[] = {
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-0x16,0x03,0x00,0x00,0x38,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xeb,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xd6,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x18,0x03,0x00,0x00,0x32,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xd3,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd5,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xbe,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xbe,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1a,0x03,0x00,0x00,
-0x30,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xbb,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xbd,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xb6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xb6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x1c,0x03,0x00,0x00,0x2f,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xb3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xb5,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x1d,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x1d,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q5_0_f32_aligned_len = 12340;
-
-unsigned char matmul_id_q5_0_f32_aligned_fp32_data[] = {
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-0xac,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0x6c,0x00,0x00,0x00,
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-0x8d,0x00,0x00,0x00,0xbd,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,
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-0x0e,0x03,0x00,0x00,0x20,0x00,0x00,0x00,0xb8,0x02,0x00,0x00,
-0xec,0x02,0x00,0x00,0xc0,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x6c,0x00,0x00,0x00,0xc5,0x02,0x00,0x00,0x0e,0x03,0x00,0x00,
-0x44,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xc1,0x02,0x00,0x00,
-0xc0,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
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-0x8c,0x00,0x00,0x00,0xcb,0x02,0x00,0x00,0xbd,0x02,0x00,0x00,
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-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd8,0x02,0x00,0x00,
-0xd0,0x02,0x00,0x00,0xd7,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xda,0x02,0x00,0x00,0xd8,0x02,0x00,0x00,
-0x9f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdc,0x02,0x00,0x00,0xda,0x02,0x00,0x00,0x0e,0x03,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xde,0x02,0x00,0x00,
-0x05,0x03,0x00,0x00,0xc9,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
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-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe4,0x02,0x00,0x00,
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-0x06,0x00,0x00,0x00,0xe5,0x02,0x00,0x00,0xe2,0x02,0x00,0x00,
-0xe4,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe7,0x02,0x00,0x00,0xe5,0x02,0x00,0x00,0x0e,0x03,0x00,0x00,
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-0xd6,0x00,0x00,0x00,0xe7,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xd0,0x00,0x00,0x00,0xe9,0x02,0x00,0x00,0xe8,0x02,0x00,0x00,
-0x41,0x00,0x06,0x00,0xaf,0x01,0x00,0x00,0xea,0x02,0x00,0x00,
-0xc9,0x02,0x00,0x00,0x15,0x00,0x00,0x00,0xdc,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xea,0x02,0x00,0x00,0xe9,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xec,0x02,0x00,0x00,
-0x0e,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xbf,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xc1,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xac,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xac,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xee,0x02,0x00,0x00,0x08,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xab,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x94,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x94,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf0,0x02,0x00,0x00,0x06,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x91,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x93,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x8c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x8c,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf2,0x02,0x00,0x00,
-0x05,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x89,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x8b,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xf3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf3,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_id_q5_0_f32_aligned_fp32_len = 11592;
-
-unsigned char matmul_id_q5_0_f32_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x65,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x10,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x2e,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,0x90,0x00,0x00,0x00,
-0x12,0x01,0x00,0x00,0x5a,0x01,0x00,0x00,0x89,0x01,0x00,0x00,
-0x94,0x01,0x00,0x00,0xbc,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
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-0xf8,0x00,0x02,0x00,0xc7,0x01,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x0c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe0,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
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-0xf9,0x00,0x02,0x00,0xdd,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
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-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x74,0x02,0x00,0x00,
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-0xc5,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x7a,0x02,0x00,0x00,0xa3,0x00,0x00,0x00,0x79,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x7c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7c,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xf8,0x02,0x00,0x00,0x20,0x00,0x00,0x00,0xdf,0x00,0x00,0x00,
-0xe5,0x02,0x00,0x00,0x7f,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x6b,0x00,0x00,0x00,0x82,0x02,0x00,0x00,0xf8,0x02,0x00,0x00,
-0xcb,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x7e,0x02,0x00,0x00,
-0x7f,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x82,0x02,0x00,0x00,0x7d,0x02,0x00,0x00,0x7e,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7d,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x84,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x84,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xf9,0x02,0x00,0x00,
-0x20,0x00,0x00,0x00,0x7d,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,
-0x87,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,
-0x8a,0x02,0x00,0x00,0xf9,0x02,0x00,0x00,0x42,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x86,0x02,0x00,0x00,0x87,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x8a,0x02,0x00,0x00,
-0x85,0x02,0x00,0x00,0x86,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x85,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8e,0x02,0x00,0x00,0xf9,0x02,0x00,0x00,0x43,0x00,0x00,0x00,
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-0x74,0x02,0x00,0x00,0x8e,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
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-0x92,0x02,0x00,0x00,0x8f,0x02,0x00,0x00,0x91,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x96,0x02,0x00,0x00,
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-0x06,0x00,0x00,0x00,0x97,0x02,0x00,0x00,0x7a,0x02,0x00,0x00,
-0x96,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x99,0x02,0x00,0x00,0x4a,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9a,0x02,0x00,0x00,
-0x97,0x02,0x00,0x00,0x99,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x9c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x9c,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xfb,0x02,0x00,0x00,
-0x20,0x00,0x00,0x00,0x85,0x02,0x00,0x00,0xe1,0x02,0x00,0x00,
-0x9f,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,
-0xa2,0x02,0x00,0x00,0xfb,0x02,0x00,0x00,0xc8,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x9e,0x02,0x00,0x00,0x9f,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xa2,0x02,0x00,0x00,
-0x9d,0x02,0x00,0x00,0x9e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9d,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa6,0x02,0x00,0x00,0x9a,0x02,0x00,0x00,0xfb,0x02,0x00,0x00,
-0xae,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,0xa9,0x02,0x00,0x00,
-0xa6,0x02,0x00,0x00,0xf5,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xab,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xa9,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0xab,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xaa,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x9e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xab,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x97,0x00,0x00,0x00,0xaf,0x02,0x00,0x00,
-0x90,0x00,0x00,0x00,0xa6,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x8c,0x00,0x00,0x00,0xb0,0x02,0x00,0x00,0xaf,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xb2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xb2,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x01,0x03,0x00,0x00,0x20,0x00,0x00,0x00,0xab,0x02,0x00,0x00,
-0xdf,0x02,0x00,0x00,0xb3,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x6b,0x00,0x00,0x00,0xb8,0x02,0x00,0x00,0x01,0x03,0x00,0x00,
-0x44,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xb4,0x02,0x00,0x00,
-0xb3,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xb8,0x02,0x00,0x00,0xb3,0x02,0x00,0x00,0xb4,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb3,0x02,0x00,0x00,0x51,0x00,0x05,0x00,
-0x8b,0x00,0x00,0x00,0xbe,0x02,0x00,0x00,0xb0,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xbf,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x16,0x00,0x00,0x00,0xc1,0x02,0x00,0x00,0x13,0x00,0x00,0x00,
-0xc0,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xc2,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc3,0x02,0x00,0x00,0xbf,0x02,0x00,0x00,
-0xc2,0x02,0x00,0x00,0x51,0x00,0x05,0x00,0x8b,0x00,0x00,0x00,
-0xc5,0x02,0x00,0x00,0xb0,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xc6,0x02,0x00,0x00,
-0xc5,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
-0xc8,0x02,0x00,0x00,0x13,0x00,0x00,0x00,0xc7,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xc9,0x02,0x00,0x00,
-0xc8,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xca,0x02,0x00,0x00,0xc6,0x02,0x00,0x00,0xc9,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xcb,0x02,0x00,0x00,
-0xc3,0x02,0x00,0x00,0xca,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xcd,0x02,0x00,0x00,0xcb,0x02,0x00,0x00,
-0x92,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xcf,0x02,0x00,0x00,0xcd,0x02,0x00,0x00,0x01,0x03,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd1,0x02,0x00,0x00,
-0xf8,0x02,0x00,0x00,0xc8,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd3,0x02,0x00,0x00,0xd1,0x02,0x00,0x00,
-0xfb,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd5,0x02,0x00,0x00,0xd3,0x02,0x00,0x00,0xd4,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd7,0x02,0x00,0x00,
-0xf9,0x02,0x00,0x00,0x44,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd8,0x02,0x00,0x00,0xd5,0x02,0x00,0x00,
-0xd7,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xda,0x02,0x00,0x00,0xd8,0x02,0x00,0x00,0x01,0x03,0x00,0x00,
-0x41,0x00,0x05,0x00,0xd8,0x00,0x00,0x00,0xdb,0x02,0x00,0x00,
-0xd5,0x00,0x00,0x00,0xda,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xcf,0x00,0x00,0x00,0xdc,0x02,0x00,0x00,0xdb,0x02,0x00,0x00,
-0x41,0x00,0x06,0x00,0xac,0x01,0x00,0x00,0xdd,0x02,0x00,0x00,
-0xbc,0x02,0x00,0x00,0x15,0x00,0x00,0x00,0xcf,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xdd,0x02,0x00,0x00,0xdc,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdf,0x02,0x00,0x00,
-0x01,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb4,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x9f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe1,0x02,0x00,0x00,0xfb,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x9c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9e,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x87,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x87,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe3,0x02,0x00,0x00,0xf9,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x84,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x86,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7f,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe5,0x02,0x00,0x00,
-0xf8,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7e,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe6,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_id_q5_0_f32_fp32_len = 11412;
-
-unsigned char matmul_id_q5_1_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x64,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x10,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,
-0x7b,0x00,0x00,0x00,0x90,0x00,0x00,0x00,0x11,0x01,0x00,0x00,
-0x56,0x01,0x00,0x00,0x87,0x01,0x00,0x00,0x92,0x01,0x00,0x00,
-0xbf,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
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-0xe2,0x02,0x00,0x00,0x04,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xb5,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xb7,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xa2,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe4,0x02,0x00,0x00,0xfe,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x9f,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa1,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x8a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x8a,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe6,0x02,0x00,0x00,
-0xfc,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x87,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x89,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x82,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x82,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe8,0x02,0x00,0x00,0xfb,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x7f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x81,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xe9,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe9,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q5_1_f32_len = 11428;
-
-unsigned char matmul_id_q5_1_f32_aligned_data[] = {
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-0xb0,0x00,0x05,0x00,0x6c,0x00,0x00,0x00,0xd5,0x02,0x00,0x00,
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-0x06,0x00,0x00,0x00,0x12,0x03,0x00,0x00,0x34,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xe5,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe7,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xd2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xd2,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x14,0x03,0x00,0x00,
-0x2e,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xcf,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xd1,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xba,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xba,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x16,0x03,0x00,0x00,0x2c,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xb7,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xb9,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xb2,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x18,0x03,0x00,0x00,0x2b,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xaf,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb1,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x19,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x19,0x03,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q5_1_f32_aligned_len = 12236;
-
-unsigned char matmul_id_q5_1_f32_aligned_fp32_data[] = {
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-0x06,0x00,0x00,0x00,0xea,0x02,0x00,0x00,0x04,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xa5,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa7,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
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-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xec,0x02,0x00,0x00,
-0x02,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x8d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x8f,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x88,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x88,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xee,0x02,0x00,0x00,0x01,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x85,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x87,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xef,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xef,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q5_1_f32_aligned_fp32_len = 11488;
-
-unsigned char matmul_id_q5_1_f32_fp32_data[] = {
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-0xdf,0x00,0x00,0x00,0xe1,0x02,0x00,0x00,0x7b,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,0x7e,0x02,0x00,0x00,
-0xf4,0x02,0x00,0x00,0xcb,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x7a,0x02,0x00,0x00,0x7b,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
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-0x7a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x79,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x80,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x80,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xf5,0x02,0x00,0x00,0x20,0x00,0x00,0x00,0x79,0x02,0x00,0x00,
-0xdf,0x02,0x00,0x00,0x83,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x6b,0x00,0x00,0x00,0x86,0x02,0x00,0x00,0xf5,0x02,0x00,0x00,
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-0x76,0x02,0x00,0x00,0x92,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
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-0x96,0x02,0x00,0x00,0x93,0x02,0x00,0x00,0x95,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x98,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x98,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xf7,0x02,0x00,0x00,0x20,0x00,0x00,0x00,0x81,0x02,0x00,0x00,
-0xdd,0x02,0x00,0x00,0x9b,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x6b,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,0xf7,0x02,0x00,0x00,
-0xc8,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x9a,0x02,0x00,0x00,
-0x9b,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x9e,0x02,0x00,0x00,0x99,0x02,0x00,0x00,0x9a,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x99,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,0x96,0x02,0x00,0x00,
-0xf7,0x02,0x00,0x00,0xae,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,
-0xa5,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,0xf1,0x02,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xa7,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xa5,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,
-0xa7,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa6,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x9a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa7,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x97,0x00,0x00,0x00,
-0xab,0x02,0x00,0x00,0x90,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x8c,0x00,0x00,0x00,0xac,0x02,0x00,0x00,
-0xab,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xae,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xae,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xfd,0x02,0x00,0x00,0x20,0x00,0x00,0x00,
-0xa7,0x02,0x00,0x00,0xdb,0x02,0x00,0x00,0xaf,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,0xb4,0x02,0x00,0x00,
-0xfd,0x02,0x00,0x00,0x44,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xb0,0x02,0x00,0x00,0xaf,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xb4,0x02,0x00,0x00,0xaf,0x02,0x00,0x00,
-0xb0,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xaf,0x02,0x00,0x00,
-0x51,0x00,0x05,0x00,0x8b,0x00,0x00,0x00,0xba,0x02,0x00,0x00,
-0xac,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x71,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xbb,0x02,0x00,0x00,0xba,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0xbd,0x02,0x00,0x00,
-0x13,0x00,0x00,0x00,0xbc,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xbe,0x02,0x00,0x00,0xbd,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xbf,0x02,0x00,0x00,
-0xbb,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,0x51,0x00,0x05,0x00,
-0x8b,0x00,0x00,0x00,0xc1,0x02,0x00,0x00,0xac,0x02,0x00,0x00,
-0x00,0x00,0x00,0x00,0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xc2,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x16,0x00,0x00,0x00,0xc4,0x02,0x00,0x00,0x13,0x00,0x00,0x00,
-0xc3,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xc5,0x02,0x00,0x00,0xc4,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc6,0x02,0x00,0x00,0xc2,0x02,0x00,0x00,
-0xc5,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc7,0x02,0x00,0x00,0xbf,0x02,0x00,0x00,0xc6,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc9,0x02,0x00,0x00,
-0xc7,0x02,0x00,0x00,0x8e,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xcb,0x02,0x00,0x00,0xc9,0x02,0x00,0x00,
-0xfd,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xcd,0x02,0x00,0x00,0xf4,0x02,0x00,0x00,0xc8,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xcf,0x02,0x00,0x00,
-0xcd,0x02,0x00,0x00,0xf7,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd1,0x02,0x00,0x00,0xcf,0x02,0x00,0x00,
-0xd0,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd3,0x02,0x00,0x00,0xf5,0x02,0x00,0x00,0x44,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd4,0x02,0x00,0x00,
-0xd1,0x02,0x00,0x00,0xd3,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd6,0x02,0x00,0x00,0xd4,0x02,0x00,0x00,
-0xfd,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xd8,0x00,0x00,0x00,
-0xd7,0x02,0x00,0x00,0xd5,0x00,0x00,0x00,0xd6,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xcf,0x00,0x00,0x00,0xd8,0x02,0x00,0x00,
-0xd7,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0xa8,0x01,0x00,0x00,
-0xd9,0x02,0x00,0x00,0xb8,0x02,0x00,0x00,0x15,0x00,0x00,0x00,
-0xcb,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0xd9,0x02,0x00,0x00,
-0xd8,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdb,0x02,0x00,0x00,0xfd,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xae,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xb0,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x9b,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x9b,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xdd,0x02,0x00,0x00,0xf7,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x98,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x9a,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x83,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x83,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdf,0x02,0x00,0x00,
-0xf5,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x80,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x82,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7b,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe1,0x02,0x00,0x00,0xf4,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x78,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7a,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xe2,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe2,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q5_1_f32_fp32_len = 11308;
-
-unsigned char matmul_id_q5_k_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xda,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x27,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x10,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x1f,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0x90,0x00,0x00,0x00,0x38,0x01,0x00,0x00,0x8e,0x01,0x00,0x00,
-0xf4,0x01,0x00,0x00,0xff,0x01,0x00,0x00,0x2c,0x03,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x11,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x19,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1f,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
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-0x06,0x00,0x00,0x00,0x51,0x03,0x00,0x00,0x69,0x03,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x0c,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x0e,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
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-0x67,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xf4,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xf6,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xef,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xef,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x55,0x03,0x00,0x00,0x66,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xec,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xee,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x56,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x56,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q5_k_f32_len = 13048;
-
-unsigned char matmul_id_q5_k_f32_aligned_data[] = {
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-0x85,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_id_q5_k_f32_aligned_len = 13860;
-
-unsigned char matmul_id_q5_k_f32_aligned_fp32_data[] = {
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-0x6e,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x11,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x13,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xfc,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xfc,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x58,0x03,0x00,0x00,0x6c,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xf9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xfb,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xf4,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf4,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x5a,0x03,0x00,0x00,0x6b,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xf1,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf3,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x5b,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x5b,0x03,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q5_k_f32_aligned_fp32_len = 13112;
-
-unsigned char matmul_id_q5_k_f32_fp32_data[] = {
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-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x91,0x02,0x00,0x00,
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-0x2e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x30,0x02,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x0c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0xa0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xe0,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe0,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd7,0x02,0x00,0x00,0x5e,0x03,0x00,0x00,
-0x4e,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xdd,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xdf,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
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-0x35,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdd,0x02,0x00,0x00,0xb4,0x00,0x00,0x00,0xdc,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe2,0x02,0x00,0x00,
-0x3b,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe3,0x02,0x00,0x00,0xa3,0x00,0x00,0x00,
-0xe2,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xe5,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe5,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x5f,0x03,0x00,0x00,0x20,0x00,0x00,0x00,
-0xdf,0x00,0x00,0x00,0x4e,0x03,0x00,0x00,0xe8,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,0xeb,0x02,0x00,0x00,
-0x5f,0x03,0x00,0x00,0xcb,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xe7,0x02,0x00,0x00,0xe8,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xeb,0x02,0x00,0x00,0xe6,0x02,0x00,0x00,
-0xe7,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe6,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xed,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xed,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x60,0x03,0x00,0x00,0x20,0x00,0x00,0x00,0xe6,0x02,0x00,0x00,
-0x4c,0x03,0x00,0x00,0xf0,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x6b,0x00,0x00,0x00,0xf3,0x02,0x00,0x00,0x60,0x03,0x00,0x00,
-0x42,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xef,0x02,0x00,0x00,
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-0xf8,0x00,0x02,0x00,0xee,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf7,0x02,0x00,0x00,0x60,0x03,0x00,0x00,
-0x43,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf8,0x02,0x00,0x00,0xdd,0x02,0x00,0x00,0xf7,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xfa,0x02,0x00,0x00,
-0x46,0x00,0x00,0x00,0x44,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xfb,0x02,0x00,0x00,0xf8,0x02,0x00,0x00,
-0xfa,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xff,0x02,0x00,0x00,0x5f,0x03,0x00,0x00,0x7d,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x00,0x03,0x00,0x00,
-0xe3,0x02,0x00,0x00,0xff,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x02,0x03,0x00,0x00,0x4a,0x00,0x00,0x00,
-0xc8,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x03,0x03,0x00,0x00,0x00,0x03,0x00,0x00,0x02,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x05,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x05,0x03,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x62,0x03,0x00,0x00,0x20,0x00,0x00,0x00,0xee,0x02,0x00,0x00,
-0x4a,0x03,0x00,0x00,0x08,0x03,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x6b,0x00,0x00,0x00,0x0b,0x03,0x00,0x00,0x62,0x03,0x00,0x00,
-0xc8,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x07,0x03,0x00,0x00,
-0x08,0x03,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x0b,0x03,0x00,0x00,0x06,0x03,0x00,0x00,0x07,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x06,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x0f,0x03,0x00,0x00,0x03,0x03,0x00,0x00,
-0x62,0x03,0x00,0x00,0xae,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,
-0x12,0x03,0x00,0x00,0x0f,0x03,0x00,0x00,0x5c,0x03,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x14,0x03,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x12,0x03,0x00,0x00,0x13,0x03,0x00,0x00,
-0x14,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x13,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x07,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x14,0x03,0x00,0x00,0x41,0x00,0x05,0x00,0x97,0x00,0x00,0x00,
-0x18,0x03,0x00,0x00,0x90,0x00,0x00,0x00,0x0f,0x03,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x8c,0x00,0x00,0x00,0x19,0x03,0x00,0x00,
-0x18,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0x1b,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x1b,0x03,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x68,0x03,0x00,0x00,0x20,0x00,0x00,0x00,
-0x14,0x03,0x00,0x00,0x48,0x03,0x00,0x00,0x1c,0x03,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,0x21,0x03,0x00,0x00,
-0x68,0x03,0x00,0x00,0x44,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x1d,0x03,0x00,0x00,0x1c,0x03,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x21,0x03,0x00,0x00,0x1c,0x03,0x00,0x00,
-0x1d,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x1c,0x03,0x00,0x00,
-0x51,0x00,0x05,0x00,0x8b,0x00,0x00,0x00,0x27,0x03,0x00,0x00,
-0x19,0x03,0x00,0x00,0x01,0x00,0x00,0x00,0x71,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x28,0x03,0x00,0x00,0x27,0x03,0x00,0x00,
-0x41,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0x2a,0x03,0x00,0x00,
-0x13,0x00,0x00,0x00,0x29,0x03,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x2b,0x03,0x00,0x00,0x2a,0x03,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x2c,0x03,0x00,0x00,
-0x28,0x03,0x00,0x00,0x2b,0x03,0x00,0x00,0x51,0x00,0x05,0x00,
-0x8b,0x00,0x00,0x00,0x2e,0x03,0x00,0x00,0x19,0x03,0x00,0x00,
-0x00,0x00,0x00,0x00,0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x2f,0x03,0x00,0x00,0x2e,0x03,0x00,0x00,0x41,0x00,0x05,0x00,
-0x16,0x00,0x00,0x00,0x31,0x03,0x00,0x00,0x13,0x00,0x00,0x00,
-0x30,0x03,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x32,0x03,0x00,0x00,0x31,0x03,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x33,0x03,0x00,0x00,0x2f,0x03,0x00,0x00,
-0x32,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x34,0x03,0x00,0x00,0x2c,0x03,0x00,0x00,0x33,0x03,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x36,0x03,0x00,0x00,
-0x34,0x03,0x00,0x00,0xfb,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x38,0x03,0x00,0x00,0x36,0x03,0x00,0x00,
-0x68,0x03,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x3a,0x03,0x00,0x00,0x5f,0x03,0x00,0x00,0xc8,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x3c,0x03,0x00,0x00,
-0x3a,0x03,0x00,0x00,0x62,0x03,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x3e,0x03,0x00,0x00,0x3c,0x03,0x00,0x00,
-0x3d,0x03,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x40,0x03,0x00,0x00,0x60,0x03,0x00,0x00,0x44,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x41,0x03,0x00,0x00,
-0x3e,0x03,0x00,0x00,0x40,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x43,0x03,0x00,0x00,0x41,0x03,0x00,0x00,
-0x68,0x03,0x00,0x00,0x41,0x00,0x05,0x00,0xd8,0x00,0x00,0x00,
-0x44,0x03,0x00,0x00,0xd5,0x00,0x00,0x00,0x43,0x03,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xcf,0x00,0x00,0x00,0x45,0x03,0x00,0x00,
-0x44,0x03,0x00,0x00,0x41,0x00,0x06,0x00,0x15,0x02,0x00,0x00,
-0x46,0x03,0x00,0x00,0x25,0x03,0x00,0x00,0x15,0x00,0x00,0x00,
-0x38,0x03,0x00,0x00,0x3e,0x00,0x03,0x00,0x46,0x03,0x00,0x00,
-0x45,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x48,0x03,0x00,0x00,0x68,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x1b,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x1d,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0x08,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x08,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x4a,0x03,0x00,0x00,0x62,0x03,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x05,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x07,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xf0,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xf0,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x4c,0x03,0x00,0x00,
-0x60,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xed,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xef,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe8,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe8,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x4e,0x03,0x00,0x00,0x5f,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe5,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe7,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x4f,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x4f,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q5_k_f32_fp32_len = 12928;
-
-unsigned char matmul_id_q6_k_f32_data[] = {
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-0xd3,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,
-0xd6,0x02,0x00,0x00,0x2b,0x03,0x00,0x00,0xc8,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xd2,0x02,0x00,0x00,0xd3,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xd6,0x02,0x00,0x00,
-0xd1,0x02,0x00,0x00,0xd2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
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-0x8c,0x00,0x00,0x00,0xe4,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,
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-0x31,0x03,0x00,0x00,0x20,0x00,0x00,0x00,0xdf,0x02,0x00,0x00,
-0x13,0x03,0x00,0x00,0xe7,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x6b,0x00,0x00,0x00,0xec,0x02,0x00,0x00,0x31,0x03,0x00,0x00,
-0x44,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xe8,0x02,0x00,0x00,
-0xe7,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xec,0x02,0x00,0x00,0xe7,0x02,0x00,0x00,0xe8,0x02,0x00,0x00,
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-0x8b,0x00,0x00,0x00,0xf2,0x02,0x00,0x00,0xe4,0x02,0x00,0x00,
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-0xf4,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
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-0xfe,0x02,0x00,0x00,0xfa,0x02,0x00,0x00,0xfd,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xff,0x02,0x00,0x00,
-0xf7,0x02,0x00,0x00,0xfe,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x01,0x03,0x00,0x00,0xff,0x02,0x00,0x00,
-0xc6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x03,0x03,0x00,0x00,0x01,0x03,0x00,0x00,0x31,0x03,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x05,0x03,0x00,0x00,
-0x28,0x03,0x00,0x00,0xc8,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
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-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x0b,0x03,0x00,0x00,
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-0xcf,0x00,0x00,0x00,0x10,0x03,0x00,0x00,0x0f,0x03,0x00,0x00,
-0x41,0x00,0x06,0x00,0xdb,0x01,0x00,0x00,0x11,0x03,0x00,0x00,
-0xf0,0x02,0x00,0x00,0x15,0x00,0x00,0x00,0x03,0x03,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x11,0x03,0x00,0x00,0x10,0x03,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x13,0x03,0x00,0x00,
-0x31,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe8,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xd3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd3,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x15,0x03,0x00,0x00,0x2b,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xd0,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd2,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xbb,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xbb,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x17,0x03,0x00,0x00,0x29,0x03,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xb8,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xba,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb3,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x19,0x03,0x00,0x00,
-0x28,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb0,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb2,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x1a,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x1a,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_id_q6_k_f32_len = 12216;
-
-unsigned char matmul_id_q6_k_f32_aligned_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xba,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x27,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
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-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
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-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
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-0x57,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe8,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe1,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x47,0x03,0x00,0x00,0x56,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xde,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe0,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x48,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x48,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q6_k_f32_aligned_len = 13012;
-
-unsigned char matmul_id_q6_k_f32_aligned_fp32_data[] = {
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-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q6_k_f32_aligned_fp32_len = 12280;
-
-unsigned char matmul_id_q6_k_f32_fp32_data[] = {
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-0xae,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,0xd6,0x02,0x00,0x00,
-0xd3,0x02,0x00,0x00,0x1e,0x03,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xd8,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xd6,0x02,0x00,0x00,0xd7,0x02,0x00,0x00,0xd8,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd7,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xcb,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xd8,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x97,0x00,0x00,0x00,0xdc,0x02,0x00,0x00,
-0x90,0x00,0x00,0x00,0xd3,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x8c,0x00,0x00,0x00,0xdd,0x02,0x00,0x00,0xdc,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xdf,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xdf,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x2a,0x03,0x00,0x00,0x20,0x00,0x00,0x00,0xd8,0x02,0x00,0x00,
-0x0c,0x03,0x00,0x00,0xe0,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x6b,0x00,0x00,0x00,0xe5,0x02,0x00,0x00,0x2a,0x03,0x00,0x00,
-0x44,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xe1,0x02,0x00,0x00,
-0xe0,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xe5,0x02,0x00,0x00,0xe0,0x02,0x00,0x00,0xe1,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe0,0x02,0x00,0x00,0x51,0x00,0x05,0x00,
-0x8b,0x00,0x00,0x00,0xeb,0x02,0x00,0x00,0xdd,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xec,0x02,0x00,0x00,0xeb,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x16,0x00,0x00,0x00,0xee,0x02,0x00,0x00,0x13,0x00,0x00,0x00,
-0xed,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xef,0x02,0x00,0x00,0xee,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf0,0x02,0x00,0x00,0xec,0x02,0x00,0x00,
-0xef,0x02,0x00,0x00,0x51,0x00,0x05,0x00,0x8b,0x00,0x00,0x00,
-0xf2,0x02,0x00,0x00,0xdd,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xf3,0x02,0x00,0x00,
-0xf2,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
-0xf5,0x02,0x00,0x00,0x13,0x00,0x00,0x00,0xf4,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xf6,0x02,0x00,0x00,
-0xf5,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf7,0x02,0x00,0x00,0xf3,0x02,0x00,0x00,0xf6,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf8,0x02,0x00,0x00,
-0xf0,0x02,0x00,0x00,0xf7,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xfa,0x02,0x00,0x00,0xf8,0x02,0x00,0x00,
-0xbf,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xfc,0x02,0x00,0x00,0xfa,0x02,0x00,0x00,0x2a,0x03,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xfe,0x02,0x00,0x00,
-0x21,0x03,0x00,0x00,0xc8,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x00,0x03,0x00,0x00,0xfe,0x02,0x00,0x00,
-0x24,0x03,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x02,0x03,0x00,0x00,0x00,0x03,0x00,0x00,0x01,0x03,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x04,0x03,0x00,0x00,
-0x22,0x03,0x00,0x00,0x44,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x05,0x03,0x00,0x00,0x02,0x03,0x00,0x00,
-0x04,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x07,0x03,0x00,0x00,0x05,0x03,0x00,0x00,0x2a,0x03,0x00,0x00,
-0x41,0x00,0x05,0x00,0xd8,0x00,0x00,0x00,0x08,0x03,0x00,0x00,
-0xd5,0x00,0x00,0x00,0x07,0x03,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xcf,0x00,0x00,0x00,0x09,0x03,0x00,0x00,0x08,0x03,0x00,0x00,
-0x41,0x00,0x06,0x00,0xd9,0x01,0x00,0x00,0x0a,0x03,0x00,0x00,
-0xe9,0x02,0x00,0x00,0x15,0x00,0x00,0x00,0xfc,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x0a,0x03,0x00,0x00,0x09,0x03,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x0c,0x03,0x00,0x00,
-0x2a,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xdf,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe1,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xcc,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xcc,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x0e,0x03,0x00,0x00,0x24,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xc9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xcb,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xb4,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb4,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x10,0x03,0x00,0x00,0x22,0x03,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xb1,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb3,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xac,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xac,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x12,0x03,0x00,0x00,
-0x21,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xab,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x13,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x13,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_id_q6_k_f32_fp32_len = 12096;
-
-unsigned char matmul_id_q8_0_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x3f,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x10,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,
-0x7b,0x00,0x00,0x00,0x90,0x00,0x00,0x00,0x14,0x01,0x00,0x00,
-0x32,0x01,0x00,0x00,0x63,0x01,0x00,0x00,0x6e,0x01,0x00,0x00,
-0x9c,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x30,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x11,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x19,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x1f,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x2e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x31,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x35,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x42,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x44,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4e,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x78,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x79,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x79,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x79,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x7b,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x7b,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xa2,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xc5,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xc8,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0f,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x10,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x10,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x11,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x12,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x12,0x01,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x14,0x01,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x14,0x01,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x3f,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x40,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x6b,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x6c,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x6c,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
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-0x7c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7e,0x02,0x00,0x00,
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-0xf9,0x00,0x02,0x00,0x64,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x66,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,
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-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x5c,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x5e,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xc6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xc6,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q8_0_f32_len = 11060;
-
-unsigned char matmul_id_q8_0_f32_aligned_data[] = {
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-0x06,0x00,0x00,0x00,0xef,0x02,0x00,0x00,0x0f,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xc2,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc4,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xaf,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xaf,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf1,0x02,0x00,0x00,
-0x09,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xac,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xae,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x97,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x97,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf3,0x02,0x00,0x00,0x07,0x03,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x94,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x96,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x8f,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x8f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf5,0x02,0x00,0x00,0x06,0x03,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x8c,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x8e,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xf6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xf6,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q8_0_f32_aligned_len = 11888;
-
-unsigned char matmul_id_q8_0_f32_aligned_fp32_data[] = {
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-0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x11,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
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-0x47,0x00,0x04,0x00,0x1f,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
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-0xf9,0x00,0x02,0x00,0x6a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x6a,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
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-0xf9,0x00,0x02,0x00,0x82,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x82,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xdf,0x02,0x00,0x00,0x20,0x00,0x00,0x00,0x6b,0x02,0x00,0x00,
-0xc7,0x02,0x00,0x00,0x85,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x6c,0x00,0x00,0x00,0x88,0x02,0x00,0x00,0xdf,0x02,0x00,0x00,
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-0x88,0x02,0x00,0x00,0x83,0x02,0x00,0x00,0x84,0x02,0x00,0x00,
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-0x95,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x98,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x98,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xe5,0x02,0x00,0x00,0x20,0x00,0x00,0x00,
-0x91,0x02,0x00,0x00,0xc5,0x02,0x00,0x00,0x99,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x6c,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,
-0xe5,0x02,0x00,0x00,0x44,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x9a,0x02,0x00,0x00,0x99,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x9e,0x02,0x00,0x00,0x99,0x02,0x00,0x00,
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-0x51,0x00,0x05,0x00,0x8c,0x00,0x00,0x00,0xa4,0x02,0x00,0x00,
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-0x41,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,
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-0x06,0x00,0x00,0x00,0xa8,0x02,0x00,0x00,0xa7,0x02,0x00,0x00,
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-0x06,0x00,0x00,0x00,0xb0,0x02,0x00,0x00,0xac,0x02,0x00,0x00,
-0xaf,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb1,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,0xb0,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb3,0x02,0x00,0x00,
-0xb1,0x02,0x00,0x00,0x78,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb5,0x02,0x00,0x00,0xb3,0x02,0x00,0x00,
-0xe5,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb7,0x02,0x00,0x00,0xdc,0x02,0x00,0x00,0xc9,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb9,0x02,0x00,0x00,
-0xb7,0x02,0x00,0x00,0xdf,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
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-0xba,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xbd,0x02,0x00,0x00,0xdd,0x02,0x00,0x00,0x44,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xbe,0x02,0x00,0x00,
-0xbb,0x02,0x00,0x00,0xbd,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc0,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,
-0xe5,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xd9,0x00,0x00,0x00,
-0xc1,0x02,0x00,0x00,0xd6,0x00,0x00,0x00,0xc0,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xd0,0x00,0x00,0x00,0xc2,0x02,0x00,0x00,
-0xc1,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0x88,0x01,0x00,0x00,
-0xc3,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,0x15,0x00,0x00,0x00,
-0xb5,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0xc3,0x02,0x00,0x00,
-0xc2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc5,0x02,0x00,0x00,0xe5,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x98,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9a,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x85,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x85,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc7,0x02,0x00,0x00,0xdf,0x02,0x00,0x00,
-0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x82,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x84,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x6d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x6d,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc9,0x02,0x00,0x00,
-0xdd,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x6a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x6c,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x65,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x65,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xcb,0x02,0x00,0x00,0xdc,0x02,0x00,0x00,0x9b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x62,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x64,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xcc,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xcc,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q8_0_f32_aligned_fp32_len = 11140;
-
-unsigned char matmul_id_q8_0_f32_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x38,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x16,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x10,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x2e,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,0x90,0x00,0x00,0x00,
-0x14,0x01,0x00,0x00,0x32,0x01,0x00,0x00,0x61,0x01,0x00,0x00,
-0x6c,0x01,0x00,0x00,0x95,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x11,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x19,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x1f,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x2e,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x31,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x35,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x42,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x44,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4e,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
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-0xb0,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,0x7b,0x02,0x00,0x00,
-0xd2,0x02,0x00,0x00,0xc8,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x77,0x02,0x00,0x00,0x78,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x7b,0x02,0x00,0x00,0x76,0x02,0x00,0x00,
-0x77,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x76,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x7f,0x02,0x00,0x00,
-0x73,0x02,0x00,0x00,0xd2,0x02,0x00,0x00,0xae,0x00,0x05,0x00,
-0x6b,0x00,0x00,0x00,0x82,0x02,0x00,0x00,0x7f,0x02,0x00,0x00,
-0xcc,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,0x84,0x02,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x82,0x02,0x00,0x00,
-0x83,0x02,0x00,0x00,0x84,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x83,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x77,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x84,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x97,0x00,0x00,0x00,0x88,0x02,0x00,0x00,0x90,0x00,0x00,0x00,
-0x7f,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x8c,0x00,0x00,0x00,
-0x89,0x02,0x00,0x00,0x88,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x8b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x8b,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xd8,0x02,0x00,0x00,
-0x20,0x00,0x00,0x00,0x84,0x02,0x00,0x00,0xb8,0x02,0x00,0x00,
-0x8c,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0x6b,0x00,0x00,0x00,
-0x91,0x02,0x00,0x00,0xd8,0x02,0x00,0x00,0x44,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x8d,0x02,0x00,0x00,0x8c,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x91,0x02,0x00,0x00,
-0x8c,0x02,0x00,0x00,0x8d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8c,0x02,0x00,0x00,0x51,0x00,0x05,0x00,0x8b,0x00,0x00,0x00,
-0x97,0x02,0x00,0x00,0x89,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x98,0x02,0x00,0x00,
-0x97,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
-0x9a,0x02,0x00,0x00,0x13,0x00,0x00,0x00,0x99,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x9b,0x02,0x00,0x00,
-0x9a,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9c,0x02,0x00,0x00,0x98,0x02,0x00,0x00,0x9b,0x02,0x00,0x00,
-0x51,0x00,0x05,0x00,0x8b,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,
-0x89,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x71,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,0x9e,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0xa1,0x02,0x00,0x00,
-0x13,0x00,0x00,0x00,0xa0,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,0xa1,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa3,0x02,0x00,0x00,
-0x9f,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa4,0x02,0x00,0x00,0x9c,0x02,0x00,0x00,
-0xa3,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa6,0x02,0x00,0x00,0xa4,0x02,0x00,0x00,0x6b,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa8,0x02,0x00,0x00,
-0xa6,0x02,0x00,0x00,0xd8,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xaa,0x02,0x00,0x00,0xcf,0x02,0x00,0x00,
-0xc8,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xac,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0xd2,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xae,0x02,0x00,0x00,
-0xac,0x02,0x00,0x00,0xad,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb0,0x02,0x00,0x00,0xd0,0x02,0x00,0x00,
-0x44,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb1,0x02,0x00,0x00,0xae,0x02,0x00,0x00,0xb0,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb3,0x02,0x00,0x00,
-0xb1,0x02,0x00,0x00,0xd8,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0xd8,0x00,0x00,0x00,0xb4,0x02,0x00,0x00,0xd5,0x00,0x00,0x00,
-0xb3,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xcf,0x00,0x00,0x00,
-0xb5,0x02,0x00,0x00,0xb4,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0x85,0x01,0x00,0x00,0xb6,0x02,0x00,0x00,0x95,0x02,0x00,0x00,
-0x15,0x00,0x00,0x00,0xa8,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xb6,0x02,0x00,0x00,0xb5,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb8,0x02,0x00,0x00,0xd8,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x8b,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x8d,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x78,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x78,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xba,0x02,0x00,0x00,
-0xd2,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x75,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x77,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x60,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x60,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xbc,0x02,0x00,0x00,0xd0,0x02,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5f,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x58,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x58,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbe,0x02,0x00,0x00,0xcf,0x02,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x55,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x57,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xbf,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xbf,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_id_q8_0_f32_fp32_len = 10940;
-
-unsigned char matmul_q2_k_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x4e,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x1f,0x01,0x00,0x00,0x58,0x01,0x00,0x00,
-0x8b,0x01,0x00,0x00,0x96,0x01,0x00,0x00,0x80,0x02,0x00,0x00,
-0xc9,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x38,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4d,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x50,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x54,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x61,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xa6,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xb8,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xbb,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x17,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x18,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1b,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1b,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1b,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x50,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1c,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x1d,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1d,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x1d,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x1f,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x1f,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x65,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x66,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x93,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x94,0x01,0x00,0x00,
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-0xa7,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
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-0xbb,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xbf,0x02,0x00,0x00,0xa4,0x02,0x00,0x00,0xf6,0x02,0x00,0x00,
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-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0xc2,0x02,0x00,0x00,
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-0xd4,0x02,0x00,0x00,0xd2,0x02,0x00,0x00,0x9c,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd6,0x02,0x00,0x00,
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-0x06,0x00,0x00,0x00,0xd8,0x02,0x00,0x00,0xf3,0x02,0x00,0x00,
-0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xda,0x02,0x00,0x00,0xd8,0x02,0x00,0x00,0xf6,0x02,0x00,0x00,
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-0xc5,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xc5,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xb1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xb1,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe6,0x02,0x00,0x00,0xf8,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xae,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xb0,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xa9,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa9,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe8,0x02,0x00,0x00,0xf6,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xa6,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa8,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x91,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x91,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xea,0x02,0x00,0x00,
-0xf4,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x8e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x90,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x89,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x89,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xec,0x02,0x00,0x00,0xf3,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x86,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x88,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q2_k_f32_len = 11220;
-
-unsigned char matmul_q2_k_f32_aligned_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
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-0xf9,0x00,0x02,0x00,0xc7,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xc7,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x17,0x03,0x00,0x00,0x3f,0x00,0x00,0x00,0xb0,0x02,0x00,0x00,
-0x09,0x03,0x00,0x00,0xca,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0xcd,0x02,0x00,0x00,0x17,0x03,0x00,0x00,
-0xbc,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xc9,0x02,0x00,0x00,
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-0xd8,0x02,0x00,0x00,0xbd,0x02,0x00,0x00,0x19,0x03,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0xdb,0x02,0x00,0x00,
-0xd8,0x02,0x00,0x00,0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xdd,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xdb,0x02,0x00,0x00,0xdc,0x02,0x00,0x00,0xdd,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xdc,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe0,0x02,0x00,0x00,0xc5,0x02,0x00,0x00,
-0x17,0x03,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0xe1,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xe2,0x02,0x00,0x00,
-0xe1,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xe3,0x02,0x00,0x00,0xe0,0x02,0x00,0x00,0xe2,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xdd,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xdd,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0xc2,0x00,0x00,0x00,
-0xe4,0x02,0x00,0x00,0xdb,0x02,0x00,0x00,0xd0,0x02,0x00,0x00,
-0xe3,0x02,0x00,0x00,0xdc,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xe6,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xe4,0x02,0x00,0x00,0xe5,0x02,0x00,0x00,0xe6,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe5,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xee,0x02,0x00,0x00,0xc5,0x02,0x00,0x00,
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-0xf0,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xef,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xf1,0x02,0x00,0x00,
-0xf0,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf2,0x02,0x00,0x00,0xee,0x02,0x00,0x00,0xf1,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf3,0x02,0x00,0x00,
-0xa5,0x02,0x00,0x00,0xf2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf5,0x02,0x00,0x00,0xf3,0x02,0x00,0x00,
-0xbd,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf7,0x02,0x00,0x00,0xf5,0x02,0x00,0x00,0x19,0x03,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf9,0x02,0x00,0x00,
-0x14,0x03,0x00,0x00,0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xfb,0x02,0x00,0x00,0xf9,0x02,0x00,0x00,
-0x17,0x03,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xfd,0x02,0x00,0x00,0xfb,0x02,0x00,0x00,0xfc,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xff,0x02,0x00,0x00,
-0x15,0x03,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x00,0x03,0x00,0x00,0xfd,0x02,0x00,0x00,
-0xff,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x02,0x03,0x00,0x00,0x00,0x03,0x00,0x00,0x19,0x03,0x00,0x00,
-0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,0x03,0x03,0x00,0x00,
-0xca,0x00,0x00,0x00,0x02,0x03,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xc4,0x00,0x00,0x00,0x04,0x03,0x00,0x00,0x03,0x03,0x00,0x00,
-0x41,0x00,0x06,0x00,0x97,0x01,0x00,0x00,0x05,0x03,0x00,0x00,
-0xea,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0xf7,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x05,0x03,0x00,0x00,0x04,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe6,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xd2,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x07,0x03,0x00,0x00,0x19,0x03,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xcf,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd1,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xca,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xca,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x09,0x03,0x00,0x00,
-0x17,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xc7,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xc9,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xb2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xb2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x0b,0x03,0x00,0x00,0x15,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xaf,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xb1,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xaa,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xaa,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x0d,0x03,0x00,0x00,0x14,0x03,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xa7,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa9,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q2_k_f32_aligned_len = 11800;
-
-unsigned char matmul_q2_k_f32_aligned_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x3e,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x20,0x01,0x00,0x00,
-0x59,0x01,0x00,0x00,0x8c,0x01,0x00,0x00,0x93,0x01,0x00,0x00,
-0x78,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
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-0x80,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7f,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x86,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x86,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xec,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x7f,0x02,0x00,0x00,
-0xe2,0x02,0x00,0x00,0x89,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0x8c,0x02,0x00,0x00,0xec,0x02,0x00,0x00,
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-0x06,0x00,0x00,0x00,0x9b,0x02,0x00,0x00,0x69,0x00,0x00,0x00,
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-0xf9,0x00,0x02,0x00,0x9e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9e,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xee,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x87,0x02,0x00,0x00,
-0xe0,0x02,0x00,0x00,0xa1,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0xa4,0x02,0x00,0x00,0xee,0x02,0x00,0x00,
-0xbc,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xa0,0x02,0x00,0x00,
-0xa1,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xa4,0x02,0x00,0x00,0x9f,0x02,0x00,0x00,0xa0,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x9f,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa6,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xf0,0x02,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,0xde,0x02,0x00,0x00,
-0xa9,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
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-0xf6,0x00,0x04,0x00,0xa8,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,
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-0xa7,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa7,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xaf,0x02,0x00,0x00,0x94,0x02,0x00,0x00,0xf0,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0xb2,0x02,0x00,0x00,
-0xaf,0x02,0x00,0x00,0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xb4,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xb2,0x02,0x00,0x00,0xb3,0x02,0x00,0x00,0xb4,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb3,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb7,0x02,0x00,0x00,0x9c,0x02,0x00,0x00,
-0xee,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0xb8,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xb9,0x02,0x00,0x00,
-0xb8,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xba,0x02,0x00,0x00,0xb7,0x02,0x00,0x00,0xb9,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xb4,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xb4,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0xc2,0x00,0x00,0x00,
-0xbb,0x02,0x00,0x00,0xb2,0x02,0x00,0x00,0xa7,0x02,0x00,0x00,
-0xba,0x02,0x00,0x00,0xb3,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xbd,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xbb,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,0xbd,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xbc,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc5,0x02,0x00,0x00,0x9c,0x02,0x00,0x00,
-0xee,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0xc7,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xc6,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xc8,0x02,0x00,0x00,
-0xc7,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc9,0x02,0x00,0x00,0xc5,0x02,0x00,0x00,0xc8,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xca,0x02,0x00,0x00,
-0x7c,0x02,0x00,0x00,0xc9,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xcc,0x02,0x00,0x00,0xca,0x02,0x00,0x00,
-0x94,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xce,0x02,0x00,0x00,0xcc,0x02,0x00,0x00,0xf0,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd0,0x02,0x00,0x00,
-0xeb,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd2,0x02,0x00,0x00,0xd0,0x02,0x00,0x00,
-0xee,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd4,0x02,0x00,0x00,0xd2,0x02,0x00,0x00,0xd3,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd6,0x02,0x00,0x00,
-0xec,0x02,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd7,0x02,0x00,0x00,0xd4,0x02,0x00,0x00,
-0xd6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd9,0x02,0x00,0x00,0xd7,0x02,0x00,0x00,0xf0,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,0xda,0x02,0x00,0x00,
-0xca,0x00,0x00,0x00,0xd9,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xc4,0x00,0x00,0x00,0xdb,0x02,0x00,0x00,0xda,0x02,0x00,0x00,
-0x41,0x00,0x06,0x00,0x95,0x01,0x00,0x00,0xdc,0x02,0x00,0x00,
-0xc1,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0xce,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xdc,0x02,0x00,0x00,0xdb,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xbd,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xbd,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xa9,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa9,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xde,0x02,0x00,0x00,0xf0,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xa6,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa8,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa1,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe0,0x02,0x00,0x00,
-0xee,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x9e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa0,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x89,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x89,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe2,0x02,0x00,0x00,0xec,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x86,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x88,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x81,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x81,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe4,0x02,0x00,0x00,0xeb,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x7e,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x80,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q2_k_f32_aligned_fp32_len = 11068;
-
-unsigned char matmul_q2_k_f32_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x47,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x1f,0x01,0x00,0x00,
-0x58,0x01,0x00,0x00,0x89,0x01,0x00,0x00,0x94,0x01,0x00,0x00,
-0x79,0x02,0x00,0x00,0xc2,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x12,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x38,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x3e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4d,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x50,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x54,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
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-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x92,0x02,0x00,0x00,
-0x68,0x02,0x00,0x00,0x91,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x94,0x02,0x00,0x00,0x65,0x00,0x00,0x00,
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-0x95,0x02,0x00,0x00,0x92,0x02,0x00,0x00,0x94,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x99,0x02,0x00,0x00,
-0xec,0x02,0x00,0x00,0x08,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9a,0x02,0x00,0x00,0x6e,0x02,0x00,0x00,
-0x99,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9c,0x02,0x00,0x00,0x69,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9d,0x02,0x00,0x00,
-0x9a,0x02,0x00,0x00,0x9c,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x9f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x9f,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xef,0x02,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x88,0x02,0x00,0x00,0xe1,0x02,0x00,0x00,
-0xa2,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0xa5,0x02,0x00,0x00,0xef,0x02,0x00,0x00,0xbb,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xa1,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xa5,0x02,0x00,0x00,
-0xa0,0x02,0x00,0x00,0xa1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa0,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xa7,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa7,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xf1,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xa0,0x02,0x00,0x00,0xdf,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0xad,0x02,0x00,0x00,
-0xf1,0x02,0x00,0x00,0x63,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xa9,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xad,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
-0xa9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa8,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb0,0x02,0x00,0x00,
-0x95,0x02,0x00,0x00,0xf1,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0xb3,0x02,0x00,0x00,0xb0,0x02,0x00,0x00,
-0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0xb5,0x02,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xb3,0x02,0x00,0x00,
-0xb4,0x02,0x00,0x00,0xb5,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xb4,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb8,0x02,0x00,0x00,0x9d,0x02,0x00,0x00,0xef,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0xb9,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xba,0x02,0x00,0x00,0xb9,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0xbb,0x02,0x00,0x00,
-0xb8,0x02,0x00,0x00,0xba,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb5,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb5,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0xc1,0x00,0x00,0x00,0xbc,0x02,0x00,0x00,
-0xb3,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,0xbb,0x02,0x00,0x00,
-0xb4,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,0xbe,0x02,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xbc,0x02,0x00,0x00,
-0xbd,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xbd,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc6,0x02,0x00,0x00,0x9d,0x02,0x00,0x00,0xef,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0xc8,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0xc7,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xc9,0x02,0x00,0x00,0xc8,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xca,0x02,0x00,0x00,
-0xc6,0x02,0x00,0x00,0xc9,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xcb,0x02,0x00,0x00,0x7d,0x02,0x00,0x00,
-0xca,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xcd,0x02,0x00,0x00,0xcb,0x02,0x00,0x00,0x95,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xcf,0x02,0x00,0x00,
-0xcd,0x02,0x00,0x00,0xf1,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd1,0x02,0x00,0x00,0xec,0x02,0x00,0x00,
-0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd3,0x02,0x00,0x00,0xd1,0x02,0x00,0x00,0xef,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd5,0x02,0x00,0x00,
-0xd3,0x02,0x00,0x00,0xd4,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd7,0x02,0x00,0x00,0xed,0x02,0x00,0x00,
-0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd8,0x02,0x00,0x00,0xd5,0x02,0x00,0x00,0xd7,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xda,0x02,0x00,0x00,
-0xd8,0x02,0x00,0x00,0xf1,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0xcc,0x00,0x00,0x00,0xdb,0x02,0x00,0x00,0xc9,0x00,0x00,0x00,
-0xda,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,
-0xdc,0x02,0x00,0x00,0xdb,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0x9f,0x01,0x00,0x00,0xdd,0x02,0x00,0x00,0xc2,0x02,0x00,0x00,
-0x35,0x00,0x00,0x00,0xcf,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xdd,0x02,0x00,0x00,0xdc,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xbe,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xbe,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xaa,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xaa,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdf,0x02,0x00,0x00,0xf1,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa7,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa9,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xa2,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe1,0x02,0x00,0x00,0xef,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x9f,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa1,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x8a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x8a,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe3,0x02,0x00,0x00,
-0xed,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x87,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x89,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x82,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x82,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe5,0x02,0x00,0x00,0xec,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x7f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x81,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q2_k_f32_fp32_len = 11100;
-
-unsigned char matmul_q3_k_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xa7,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0x3a,0x01,0x00,0x00,0xaa,0x01,0x00,0x00,0x0b,0x02,0x00,0x00,
-0x16,0x02,0x00,0x00,0x00,0x03,0x00,0x00,0x49,0x03,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x38,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x4d,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x50,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x54,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xa6,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xb8,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xbb,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x31,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x32,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x34,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
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-0xf8,0x00,0x02,0x00,0x11,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x6a,0x03,0x00,0x00,0x70,0x03,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x0e,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x10,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x09,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x09,0x03,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x6c,0x03,0x00,0x00,
-0x6f,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x06,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x08,0x03,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q3_k_f32_len = 13124;
-
-unsigned char matmul_q3_k_f32_aligned_data[] = {
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-0x52,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
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-0x51,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0x4a,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x4a,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x89,0x03,0x00,0x00,0x93,0x03,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x47,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x49,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x32,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x32,0x03,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8b,0x03,0x00,0x00,
-0x91,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x2f,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x31,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x2a,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x2a,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8d,0x03,0x00,0x00,0x90,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x27,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x29,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q3_k_f32_aligned_len = 13704;
-
-unsigned char matmul_q3_k_f32_aligned_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x9c,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
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-0x5c,0x03,0x00,0x00,0x5b,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x3d,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x3d,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x29,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x29,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x5e,0x03,0x00,0x00,0x6c,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x26,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x28,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0x21,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x21,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x60,0x03,0x00,0x00,0x6a,0x03,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x1e,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x20,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x09,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x09,0x03,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x62,0x03,0x00,0x00,
-0x68,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x06,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x08,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x01,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x01,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x64,0x03,0x00,0x00,0x67,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xfe,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x00,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q3_k_f32_aligned_fp32_len = 12972;
-
-unsigned char matmul_q3_k_f32_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xa0,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x3a,0x01,0x00,0x00,0xaa,0x01,0x00,0x00,
-0x09,0x02,0x00,0x00,0x14,0x02,0x00,0x00,0xf9,0x02,0x00,0x00,
-0x42,0x03,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0x4b,0x03,0x00,0x00,0x15,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
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-0x51,0x03,0x00,0x00,0x6b,0x03,0x00,0x00,0x84,0x00,0x05,0x00,
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-0x4f,0x03,0x00,0x00,0x3e,0x00,0x03,0x00,0x5d,0x03,0x00,0x00,
-0x5c,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0x3e,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x3e,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x2a,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x2a,0x03,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x5f,0x03,0x00,0x00,
-0x6d,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x27,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x29,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x22,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x22,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x61,0x03,0x00,0x00,0x6b,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x1f,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x21,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0x0a,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x0a,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x63,0x03,0x00,0x00,0x69,0x03,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x07,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x09,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x02,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x02,0x03,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x65,0x03,0x00,0x00,
-0x68,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xff,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x01,0x03,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q3_k_f32_fp32_len = 13004;
-
-unsigned char matmul_q4_0_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x1b,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x07,0x01,0x00,0x00,0x27,0x01,0x00,0x00,
-0x5a,0x01,0x00,0x00,0x65,0x01,0x00,0x00,0x4f,0x02,0x00,0x00,
-0x98,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0x60,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb9,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5f,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x58,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x58,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbb,0x02,0x00,0x00,0xc0,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x55,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x57,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q4_0_f32_len = 10564;
-
-unsigned char matmul_q4_0_f32_aligned_data[] = {
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-0x17,0x00,0x00,0x00,0xb2,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0xd0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xb3,0x02,0x00,0x00,0xb2,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0xb4,0x02,0x00,0x00,0xb1,0x02,0x00,0x00,
-0xb3,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xae,0x02,0x00,0x00,
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-0xf7,0x00,0x03,0x00,0xb7,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
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-0xc4,0x02,0x00,0x00,0x76,0x02,0x00,0x00,0xc3,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc6,0x02,0x00,0x00,
-0xc4,0x02,0x00,0x00,0x8e,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc8,0x02,0x00,0x00,0xc6,0x02,0x00,0x00,
-0xe8,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xca,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xcc,0x02,0x00,0x00,
-0xca,0x02,0x00,0x00,0xe6,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
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-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd1,0x02,0x00,0x00,
-0xce,0x02,0x00,0x00,0xd0,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
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-0xd4,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0x67,0x01,0x00,0x00,
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-0xd5,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xb7,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb7,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa3,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd8,0x02,0x00,0x00,
-0xe8,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa0,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa2,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x9b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9b,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xda,0x02,0x00,0x00,0xe6,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x98,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9a,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x83,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x83,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xdc,0x02,0x00,0x00,0xe4,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x80,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x82,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xde,0x02,0x00,0x00,
-0xe3,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x78,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7a,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q4_0_f32_aligned_len = 11156;
-
-unsigned char matmul_q4_0_f32_aligned_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x0c,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
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-0x48,0x02,0x00,0x00,0x91,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
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-0xeb,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0xed,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x8b,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8b,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x2f,0x02,0x00,0x00,0xd2,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x88,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8a,0x01,0x00,0x00,0xe0,0x00,0x04,0x00,0x0c,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x80,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
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-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x31,0x02,0x00,0x00,
-0xb8,0x02,0x00,0x00,0x6d,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xd4,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xd6,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x36,0x02,0x00,0x00,
-0x56,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x37,0x02,0x00,0x00,0x97,0x00,0x00,0x00,
-0x36,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x3c,0x02,0x00,0x00,0x5a,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x3d,0x02,0x00,0x00,
-0xa8,0x00,0x00,0x00,0x3c,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x41,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0x40,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x42,0x02,0x00,0x00,0x41,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x43,0x02,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x42,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x47,0x02,0x00,0x00,0x48,0x00,0x00,0x00,0x42,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,0x49,0x02,0x00,0x00,
-0x48,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x4a,0x02,0x00,0x00,0x49,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x4b,0x02,0x00,0x00,
-0x47,0x02,0x00,0x00,0x4a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x4c,0x02,0x00,0x00,0x43,0x02,0x00,0x00,
-0x4b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x4e,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x4e,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xb9,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xd6,0x00,0x00,0x00,0xb4,0x02,0x00,0x00,0x51,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0x54,0x02,0x00,0x00,
-0xb9,0x02,0x00,0x00,0xbf,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x50,0x02,0x00,0x00,0x51,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x54,0x02,0x00,0x00,0x4f,0x02,0x00,0x00,
-0x50,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x4f,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x56,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x56,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xba,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x4f,0x02,0x00,0x00,
-0xb2,0x02,0x00,0x00,0x59,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0x5c,0x02,0x00,0x00,0xba,0x02,0x00,0x00,
-0x61,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x58,0x02,0x00,0x00,
-0x59,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x5c,0x02,0x00,0x00,0x57,0x02,0x00,0x00,0x58,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x57,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x60,0x02,0x00,0x00,0xba,0x02,0x00,0x00,
-0x62,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x61,0x02,0x00,0x00,0x37,0x02,0x00,0x00,0x60,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x63,0x02,0x00,0x00,
-0x65,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x64,0x02,0x00,0x00,0x61,0x02,0x00,0x00,
-0x63,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x68,0x02,0x00,0x00,0xb9,0x02,0x00,0x00,0xd7,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x69,0x02,0x00,0x00,
-0x3d,0x02,0x00,0x00,0x68,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x6b,0x02,0x00,0x00,0x69,0x00,0x00,0x00,
-0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x6c,0x02,0x00,0x00,0x69,0x02,0x00,0x00,0x6b,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x6e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x6e,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xbc,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x57,0x02,0x00,0x00,
-0xb0,0x02,0x00,0x00,0x71,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0x74,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,
-0xbc,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x70,0x02,0x00,0x00,
-0x71,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x74,0x02,0x00,0x00,0x6f,0x02,0x00,0x00,0x70,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x6f,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x76,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x76,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xbe,0x02,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x6f,0x02,0x00,0x00,0xae,0x02,0x00,0x00,
-0x79,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0x7c,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x78,0x02,0x00,0x00,0x79,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x7c,0x02,0x00,0x00,
-0x77,0x02,0x00,0x00,0x78,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x77,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x7f,0x02,0x00,0x00,0x64,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0x82,0x02,0x00,0x00,
-0x7f,0x02,0x00,0x00,0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x84,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x82,0x02,0x00,0x00,0x83,0x02,0x00,0x00,0x84,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x83,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x87,0x02,0x00,0x00,0x6c,0x02,0x00,0x00,
-0xbc,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x88,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x89,0x02,0x00,0x00,
-0x88,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0x8a,0x02,0x00,0x00,0x87,0x02,0x00,0x00,0x89,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x84,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x84,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0xc2,0x00,0x00,0x00,
-0x8b,0x02,0x00,0x00,0x82,0x02,0x00,0x00,0x77,0x02,0x00,0x00,
-0x8a,0x02,0x00,0x00,0x83,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x8d,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x8b,0x02,0x00,0x00,0x8c,0x02,0x00,0x00,0x8d,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x8c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x95,0x02,0x00,0x00,0x6c,0x02,0x00,0x00,
-0xbc,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x97,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0x96,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x98,0x02,0x00,0x00,
-0x97,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x99,0x02,0x00,0x00,0x95,0x02,0x00,0x00,0x98,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9a,0x02,0x00,0x00,
-0x4c,0x02,0x00,0x00,0x99,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9c,0x02,0x00,0x00,0x9a,0x02,0x00,0x00,
-0x64,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9e,0x02,0x00,0x00,0x9c,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa0,0x02,0x00,0x00,
-0xb9,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,0xa0,0x02,0x00,0x00,
-0xbc,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa4,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa6,0x02,0x00,0x00,
-0xba,0x02,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,0xa4,0x02,0x00,0x00,
-0xa6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa9,0x02,0x00,0x00,0xa7,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,0xaa,0x02,0x00,0x00,
-0xca,0x00,0x00,0x00,0xa9,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xc4,0x00,0x00,0x00,0xab,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
-0x41,0x00,0x06,0x00,0x64,0x01,0x00,0x00,0xac,0x02,0x00,0x00,
-0x91,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xac,0x02,0x00,0x00,0xab,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x8d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8d,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x79,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x79,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xae,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x76,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x78,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x71,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x71,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb0,0x02,0x00,0x00,
-0xbc,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x6e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x70,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x59,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x59,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb2,0x02,0x00,0x00,0xba,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x56,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x58,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x51,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x51,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb4,0x02,0x00,0x00,0xb9,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x4e,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x50,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q4_0_f32_aligned_fp32_len = 10408;
-
-unsigned char matmul_q4_0_f32_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x14,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
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-0x71,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x74,0x02,0x00,0x00,0x6f,0x02,0x00,0x00,0x70,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x6f,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x76,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x76,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xbe,0x02,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x6f,0x02,0x00,0x00,0xae,0x02,0x00,0x00,
-0x79,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0x7c,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x78,0x02,0x00,0x00,0x79,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x7c,0x02,0x00,0x00,
-0x77,0x02,0x00,0x00,0x78,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x77,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x7f,0x02,0x00,0x00,0x64,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x82,0x02,0x00,0x00,
-0x7f,0x02,0x00,0x00,0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x84,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x82,0x02,0x00,0x00,0x83,0x02,0x00,0x00,0x84,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x83,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x87,0x02,0x00,0x00,0x6c,0x02,0x00,0x00,
-0xbc,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x88,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x89,0x02,0x00,0x00,
-0x88,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0x8a,0x02,0x00,0x00,0x87,0x02,0x00,0x00,0x89,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x84,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x84,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0xc1,0x00,0x00,0x00,
-0x8b,0x02,0x00,0x00,0x82,0x02,0x00,0x00,0x77,0x02,0x00,0x00,
-0x8a,0x02,0x00,0x00,0x83,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x8d,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x8b,0x02,0x00,0x00,0x8c,0x02,0x00,0x00,0x8d,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x8c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x95,0x02,0x00,0x00,0x6c,0x02,0x00,0x00,
-0xbc,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x97,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0x96,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x98,0x02,0x00,0x00,
-0x97,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x99,0x02,0x00,0x00,0x95,0x02,0x00,0x00,0x98,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9a,0x02,0x00,0x00,
-0x4c,0x02,0x00,0x00,0x99,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9c,0x02,0x00,0x00,0x9a,0x02,0x00,0x00,
-0x64,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9e,0x02,0x00,0x00,0x9c,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa0,0x02,0x00,0x00,
-0xb9,0x02,0x00,0x00,0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,0xa0,0x02,0x00,0x00,
-0xbc,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa4,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa6,0x02,0x00,0x00,
-0xba,0x02,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,0xa4,0x02,0x00,0x00,
-0xa6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa9,0x02,0x00,0x00,0xa7,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0xcc,0x00,0x00,0x00,0xaa,0x02,0x00,0x00,
-0xc9,0x00,0x00,0x00,0xa9,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xc3,0x00,0x00,0x00,0xab,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
-0x41,0x00,0x06,0x00,0x6e,0x01,0x00,0x00,0xac,0x02,0x00,0x00,
-0x91,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xac,0x02,0x00,0x00,0xab,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x8d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8d,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x79,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x79,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xae,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x76,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x78,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x71,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x71,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb0,0x02,0x00,0x00,
-0xbc,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x6e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x70,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x59,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x59,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb2,0x02,0x00,0x00,0xba,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x56,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x58,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x51,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x51,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb4,0x02,0x00,0x00,0xb9,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x4e,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x50,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q4_0_f32_fp32_len = 10444;
-
-unsigned char matmul_q4_1_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xf5,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x07,0x01,0x00,0x00,0x2c,0x01,0x00,0x00,
-0x5f,0x01,0x00,0x00,0x6a,0x01,0x00,0x00,0x54,0x02,0x00,0x00,
-0x9d,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x38,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4d,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x50,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x54,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x61,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xa6,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xb8,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xbb,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x02,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x03,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x03,0x01,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x04,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x05,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x05,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x05,0x01,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x07,0x01,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x07,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x39,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x3a,0x01,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x67,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x68,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x68,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
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-0x84,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x7d,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7d,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbc,0x02,0x00,0x00,0xc8,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x7a,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7c,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x65,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x65,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xbe,0x02,0x00,0x00,
-0xc6,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x62,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x64,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5d,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc0,0x02,0x00,0x00,0xc5,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5c,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q4_1_f32_len = 10632;
-
-unsigned char matmul_q4_1_f32_aligned_data[] = {
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-0xf9,0x00,0x02,0x00,0xbc,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xbc,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xa8,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa8,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xdd,0x02,0x00,0x00,0xed,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xa5,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa7,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa0,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa0,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdf,0x02,0x00,0x00,
-0xeb,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x9d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x9f,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x88,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x88,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe1,0x02,0x00,0x00,0xe9,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x85,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x87,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x80,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x80,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe3,0x02,0x00,0x00,0xe8,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x7d,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7f,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q4_1_f32_aligned_len = 11224;
-
-unsigned char matmul_q4_1_f32_aligned_fp32_data[] = {
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-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xbf,0x02,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x54,0x02,0x00,0x00,0xb7,0x02,0x00,0x00,
-0x5e,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0x61,0x02,0x00,0x00,0xbf,0x02,0x00,0x00,0x61,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x5d,0x02,0x00,0x00,0x5e,0x02,0x00,0x00,
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-0x73,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x73,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xc1,0x02,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x5c,0x02,0x00,0x00,0xb5,0x02,0x00,0x00,
-0x76,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0x79,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x75,0x02,0x00,0x00,0x76,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x79,0x02,0x00,0x00,
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-0x69,0x02,0x00,0x00,0xc3,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0x87,0x02,0x00,0x00,0x84,0x02,0x00,0x00,
-0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x89,0x02,0x00,0x00,
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-0x88,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8c,0x02,0x00,0x00,0x71,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x8d,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x8e,0x02,0x00,0x00,0x8d,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0x8f,0x02,0x00,0x00,
-0x8c,0x02,0x00,0x00,0x8e,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x89,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x89,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0xc2,0x00,0x00,0x00,0x90,0x02,0x00,0x00,
-0x87,0x02,0x00,0x00,0x7c,0x02,0x00,0x00,0x8f,0x02,0x00,0x00,
-0x88,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,0x92,0x02,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x90,0x02,0x00,0x00,
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-0x91,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9a,0x02,0x00,0x00,0x71,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x9c,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0x9b,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x9d,0x02,0x00,0x00,0x9c,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,
-0x9a,0x02,0x00,0x00,0x9d,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,0x51,0x02,0x00,0x00,
-0x9e,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa1,0x02,0x00,0x00,0x9f,0x02,0x00,0x00,0x69,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa3,0x02,0x00,0x00,
-0xa1,0x02,0x00,0x00,0xc3,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa5,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,
-0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa7,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa9,0x02,0x00,0x00,
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-0x06,0x00,0x00,0x00,0xab,0x02,0x00,0x00,0xbf,0x02,0x00,0x00,
-0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xac,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,0xab,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xae,0x02,0x00,0x00,
-0xac,0x02,0x00,0x00,0xc3,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0xcd,0x00,0x00,0x00,0xaf,0x02,0x00,0x00,0xca,0x00,0x00,0x00,
-0xae,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,
-0xb0,0x02,0x00,0x00,0xaf,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0x69,0x01,0x00,0x00,0xb1,0x02,0x00,0x00,0x96,0x02,0x00,0x00,
-0x35,0x00,0x00,0x00,0xa3,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xb1,0x02,0x00,0x00,0xb0,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x92,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x92,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x7e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7e,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb3,0x02,0x00,0x00,0xc3,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7d,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x76,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x76,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb5,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x73,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x75,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x5e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5e,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb7,0x02,0x00,0x00,
-0xbf,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x5b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5d,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x56,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x56,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb9,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x53,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x55,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q4_1_f32_aligned_fp32_len = 10476;
-
-unsigned char matmul_q4_1_f32_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xee,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x07,0x01,0x00,0x00,
-0x2c,0x01,0x00,0x00,0x5d,0x01,0x00,0x00,0x68,0x01,0x00,0x00,
-0x4d,0x02,0x00,0x00,0x96,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
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-0x06,0x00,0x00,0x00,0x8e,0x02,0x00,0x00,0x8d,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x8f,0x02,0x00,0x00,
-0x8c,0x02,0x00,0x00,0x8e,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x89,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x89,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0xc1,0x00,0x00,0x00,0x90,0x02,0x00,0x00,
-0x87,0x02,0x00,0x00,0x7c,0x02,0x00,0x00,0x8f,0x02,0x00,0x00,
-0x88,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,0x92,0x02,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x90,0x02,0x00,0x00,
-0x91,0x02,0x00,0x00,0x92,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x91,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9a,0x02,0x00,0x00,0x71,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,
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-0x14,0x00,0x00,0x00,0x9b,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x9d,0x02,0x00,0x00,0x9c,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,
-0x9a,0x02,0x00,0x00,0x9d,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,0x51,0x02,0x00,0x00,
-0x9e,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa1,0x02,0x00,0x00,0x9f,0x02,0x00,0x00,0x69,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa3,0x02,0x00,0x00,
-0xa1,0x02,0x00,0x00,0xc3,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa5,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,
-0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa7,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa9,0x02,0x00,0x00,
-0xa7,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xab,0x02,0x00,0x00,0xbf,0x02,0x00,0x00,
-0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xac,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,0xab,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xae,0x02,0x00,0x00,
-0xac,0x02,0x00,0x00,0xc3,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0xcc,0x00,0x00,0x00,0xaf,0x02,0x00,0x00,0xc9,0x00,0x00,0x00,
-0xae,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,
-0xb0,0x02,0x00,0x00,0xaf,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0x73,0x01,0x00,0x00,0xb1,0x02,0x00,0x00,0x96,0x02,0x00,0x00,
-0x35,0x00,0x00,0x00,0xa3,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xb1,0x02,0x00,0x00,0xb0,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x92,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x92,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x7e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7e,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb3,0x02,0x00,0x00,0xc3,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7d,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x76,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x76,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb5,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x73,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x75,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x5e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5e,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb7,0x02,0x00,0x00,
-0xbf,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x5b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5d,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x56,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x56,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb9,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x53,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x55,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q4_1_f32_fp32_len = 10512;
-
-unsigned char matmul_q4_k_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x8d,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0x21,0x01,0x00,0x00,0x78,0x01,0x00,0x00,0xc6,0x01,0x00,0x00,
-0xd1,0x01,0x00,0x00,0xbb,0x02,0x00,0x00,0x04,0x03,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
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-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
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-0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xb8,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xbb,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1b,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x1c,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1d,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1d,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1d,0x01,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
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-0x47,0x00,0x04,0x00,0xd1,0x01,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xd1,0x01,0x00,0x00,
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-0xb5,0x02,0x00,0x00,0xb4,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb6,0x02,0x00,0x00,0x0f,0x00,0x00,0x00,
-0xb5,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xba,0x02,0x00,0x00,0x48,0x00,0x00,0x00,0xb5,0x02,0x00,0x00,
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-0x06,0x00,0x00,0x00,0xbd,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xbe,0x02,0x00,0x00,
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-0xf8,0x00,0x02,0x00,0xc1,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
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-0xd5,0x00,0x00,0x00,0x27,0x03,0x00,0x00,0xc4,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0xc7,0x02,0x00,0x00,
-0x2c,0x03,0x00,0x00,0xbe,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xc3,0x02,0x00,0x00,0xc4,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xc7,0x02,0x00,0x00,0xc2,0x02,0x00,0x00,
-0xc3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xc2,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xc9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xc9,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x2d,0x03,0x00,0x00,0x3f,0x00,0x00,0x00,0xc2,0x02,0x00,0x00,
-0x25,0x03,0x00,0x00,0xcc,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0xcf,0x02,0x00,0x00,0x2d,0x03,0x00,0x00,
-0x61,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xcb,0x02,0x00,0x00,
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-0xcf,0x02,0x00,0x00,0xca,0x02,0x00,0x00,0xcb,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xca,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd3,0x02,0x00,0x00,0x2d,0x03,0x00,0x00,
-0x62,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd4,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0xd3,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd6,0x02,0x00,0x00,
-0x65,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
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-0xd6,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdb,0x02,0x00,0x00,0x2c,0x03,0x00,0x00,0x48,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdc,0x02,0x00,0x00,
-0xb0,0x02,0x00,0x00,0xdb,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xde,0x02,0x00,0x00,0x69,0x00,0x00,0x00,
-0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdf,0x02,0x00,0x00,0xdc,0x02,0x00,0x00,0xde,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe1,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x2f,0x03,0x00,0x00,0x3f,0x00,0x00,0x00,0xca,0x02,0x00,0x00,
-0x23,0x03,0x00,0x00,0xe4,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0xe7,0x02,0x00,0x00,0x2f,0x03,0x00,0x00,
-0xbb,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xe3,0x02,0x00,0x00,
-0xe4,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xe7,0x02,0x00,0x00,0xe2,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe2,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe9,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x31,0x03,0x00,0x00,
-0x3f,0x00,0x00,0x00,0xe2,0x02,0x00,0x00,0x21,0x03,0x00,0x00,
-0xec,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0xef,0x02,0x00,0x00,0x31,0x03,0x00,0x00,0x63,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xeb,0x02,0x00,0x00,0xec,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xef,0x02,0x00,0x00,
-0xea,0x02,0x00,0x00,0xeb,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xea,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf2,0x02,0x00,0x00,0xd7,0x02,0x00,0x00,0x31,0x03,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0xf5,0x02,0x00,0x00,
-0xf2,0x02,0x00,0x00,0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xf7,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xf5,0x02,0x00,0x00,0xf6,0x02,0x00,0x00,0xf7,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xfa,0x02,0x00,0x00,0xdf,0x02,0x00,0x00,
-0x2f,0x03,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0xfb,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xfc,0x02,0x00,0x00,
-0xfb,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0xfd,0x02,0x00,0x00,0xfa,0x02,0x00,0x00,0xfc,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xf7,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf7,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0xc1,0x00,0x00,0x00,
-0xfe,0x02,0x00,0x00,0xf5,0x02,0x00,0x00,0xea,0x02,0x00,0x00,
-0xfd,0x02,0x00,0x00,0xf6,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xfe,0x02,0x00,0x00,0xff,0x02,0x00,0x00,0x00,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xff,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x08,0x03,0x00,0x00,0xdf,0x02,0x00,0x00,
-0x2f,0x03,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x0a,0x03,0x00,0x00,0x14,0x00,0x00,0x00,0x09,0x03,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0b,0x03,0x00,0x00,
-0x0a,0x03,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x0c,0x03,0x00,0x00,0x08,0x03,0x00,0x00,0x0b,0x03,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x0d,0x03,0x00,0x00,
-0xbf,0x02,0x00,0x00,0x0c,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x0f,0x03,0x00,0x00,0x0d,0x03,0x00,0x00,
-0xd7,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x11,0x03,0x00,0x00,0x0f,0x03,0x00,0x00,0x31,0x03,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x13,0x03,0x00,0x00,
-0x2c,0x03,0x00,0x00,0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x15,0x03,0x00,0x00,0x13,0x03,0x00,0x00,
-0x2f,0x03,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x17,0x03,0x00,0x00,0x15,0x03,0x00,0x00,0x16,0x03,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x19,0x03,0x00,0x00,
-0x2d,0x03,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x1a,0x03,0x00,0x00,0x17,0x03,0x00,0x00,
-0x19,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x1c,0x03,0x00,0x00,0x1a,0x03,0x00,0x00,0x31,0x03,0x00,0x00,
-0x41,0x00,0x05,0x00,0xcc,0x00,0x00,0x00,0x1d,0x03,0x00,0x00,
-0xc9,0x00,0x00,0x00,0x1c,0x03,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xc3,0x00,0x00,0x00,0x1e,0x03,0x00,0x00,0x1d,0x03,0x00,0x00,
-0x41,0x00,0x06,0x00,0xdc,0x01,0x00,0x00,0x1f,0x03,0x00,0x00,
-0x04,0x03,0x00,0x00,0x35,0x00,0x00,0x00,0x11,0x03,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x1f,0x03,0x00,0x00,0x1e,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x00,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x00,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0xec,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xec,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x21,0x03,0x00,0x00,0x31,0x03,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xe9,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xeb,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe4,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe4,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x23,0x03,0x00,0x00,
-0x2f,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe3,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xcc,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xcc,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x25,0x03,0x00,0x00,0x2d,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xc9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xcb,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xc4,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc4,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x27,0x03,0x00,0x00,0x2c,0x03,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xc1,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc3,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q4_k_f32_len = 12052;
-
-unsigned char matmul_q4_k_f32_aligned_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xa7,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0x22,0x01,0x00,0x00,0x79,0x01,0x00,0x00,0xc9,0x01,0x00,0x00,
-0xd1,0x01,0x00,0x00,0xdd,0x02,0x00,0x00,0x26,0x03,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
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-0x0e,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x43,0x03,0x00,0x00,0x53,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,
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-0x0d,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0x06,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x06,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x45,0x03,0x00,0x00,0x51,0x03,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x03,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x05,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xee,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xee,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x47,0x03,0x00,0x00,
-0x4f,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xeb,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xed,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x49,0x03,0x00,0x00,0x4e,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe5,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q4_k_f32_aligned_len = 12648;
-
-unsigned char matmul_q4_k_f32_aligned_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x7d,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
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-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xf3,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf5,0x01,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x0c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0xeb,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xd7,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd7,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9c,0x02,0x00,0x00,0x23,0x03,0x00,0x00,0x6d,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xd4,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd6,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa1,0x02,0x00,0x00,0x56,0x00,0x00,0x00,0x54,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,
-0x97,0x00,0x00,0x00,0xa1,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,0x5a,0x00,0x00,0x00,
-0xb9,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa8,0x02,0x00,0x00,0xa8,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0xac,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0xab,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xad,0x02,0x00,0x00,0xac,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xae,0x02,0x00,0x00,
-0x0f,0x00,0x00,0x00,0xad,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb2,0x02,0x00,0x00,0x48,0x00,0x00,0x00,
-0xad,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,
-0xb4,0x02,0x00,0x00,0xb3,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xb5,0x02,0x00,0x00,
-0xb4,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb6,0x02,0x00,0x00,0xb2,0x02,0x00,0x00,0xb5,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb7,0x02,0x00,0x00,
-0xae,0x02,0x00,0x00,0xb6,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb9,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x24,0x03,0x00,0x00,
-0x3f,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,0x1f,0x03,0x00,0x00,
-0xbc,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xbf,0x02,0x00,0x00,0x24,0x03,0x00,0x00,0xbf,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xbb,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xbf,0x02,0x00,0x00,
-0xba,0x02,0x00,0x00,0xbb,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xba,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xc1,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc1,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x25,0x03,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xba,0x02,0x00,0x00,0x1d,0x03,0x00,0x00,0xc4,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0xc7,0x02,0x00,0x00,
-0x25,0x03,0x00,0x00,0x61,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xc3,0x02,0x00,0x00,0xc4,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xc7,0x02,0x00,0x00,0xc2,0x02,0x00,0x00,
-0xc3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xc2,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xcb,0x02,0x00,0x00,
-0x25,0x03,0x00,0x00,0x62,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xcc,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,
-0xcb,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xce,0x02,0x00,0x00,0x65,0x00,0x00,0x00,0x63,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xcf,0x02,0x00,0x00,
-0xcc,0x02,0x00,0x00,0xce,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd3,0x02,0x00,0x00,0x24,0x03,0x00,0x00,
-0x42,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd4,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,0xd3,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd6,0x02,0x00,0x00,
-0x69,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd7,0x02,0x00,0x00,0xd4,0x02,0x00,0x00,
-0xd6,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xd9,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd9,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x27,0x03,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xc2,0x02,0x00,0x00,0x1b,0x03,0x00,0x00,0xdc,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0xdf,0x02,0x00,0x00,
-0x27,0x03,0x00,0x00,0xbc,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xdb,0x02,0x00,0x00,0xdc,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xdf,0x02,0x00,0x00,0xda,0x02,0x00,0x00,
-0xdb,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xda,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe1,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x29,0x03,0x00,0x00,0x3f,0x00,0x00,0x00,0xda,0x02,0x00,0x00,
-0x19,0x03,0x00,0x00,0xe4,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0xe7,0x02,0x00,0x00,0x29,0x03,0x00,0x00,
-0x63,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xe3,0x02,0x00,0x00,
-0xe4,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xe7,0x02,0x00,0x00,0xe2,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xea,0x02,0x00,0x00,0xcf,0x02,0x00,0x00,
-0x29,0x03,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xed,0x02,0x00,0x00,0xea,0x02,0x00,0x00,0x37,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xef,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xed,0x02,0x00,0x00,0xee,0x02,0x00,0x00,
-0xef,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xee,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf2,0x02,0x00,0x00,
-0xd7,0x02,0x00,0x00,0x27,0x03,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0xf3,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0xd0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xf4,0x02,0x00,0x00,0xf3,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0xf5,0x02,0x00,0x00,0xf2,0x02,0x00,0x00,
-0xf4,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xef,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xef,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0xc2,0x00,0x00,0x00,0xf6,0x02,0x00,0x00,0xed,0x02,0x00,0x00,
-0xe2,0x02,0x00,0x00,0xf5,0x02,0x00,0x00,0xee,0x02,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xf8,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xf6,0x02,0x00,0x00,0xf7,0x02,0x00,0x00,
-0xf8,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xf7,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x00,0x03,0x00,0x00,
-0xd7,0x02,0x00,0x00,0x27,0x03,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x02,0x03,0x00,0x00,0x14,0x00,0x00,0x00,
-0x01,0x03,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x03,0x03,0x00,0x00,0x02,0x03,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x04,0x03,0x00,0x00,0x00,0x03,0x00,0x00,
-0x03,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x05,0x03,0x00,0x00,0xb7,0x02,0x00,0x00,0x04,0x03,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x07,0x03,0x00,0x00,
-0x05,0x03,0x00,0x00,0xcf,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x09,0x03,0x00,0x00,0x07,0x03,0x00,0x00,
-0x29,0x03,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x0b,0x03,0x00,0x00,0x24,0x03,0x00,0x00,0xbc,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x0d,0x03,0x00,0x00,
-0x0b,0x03,0x00,0x00,0x27,0x03,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x0f,0x03,0x00,0x00,0x0d,0x03,0x00,0x00,
-0x0e,0x03,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x11,0x03,0x00,0x00,0x25,0x03,0x00,0x00,0x63,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x12,0x03,0x00,0x00,
-0x0f,0x03,0x00,0x00,0x11,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x14,0x03,0x00,0x00,0x12,0x03,0x00,0x00,
-0x29,0x03,0x00,0x00,0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,
-0x15,0x03,0x00,0x00,0xca,0x00,0x00,0x00,0x14,0x03,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0x16,0x03,0x00,0x00,
-0x15,0x03,0x00,0x00,0x41,0x00,0x06,0x00,0xcf,0x01,0x00,0x00,
-0x17,0x03,0x00,0x00,0xfc,0x02,0x00,0x00,0x35,0x00,0x00,0x00,
-0x09,0x03,0x00,0x00,0x3e,0x00,0x03,0x00,0x17,0x03,0x00,0x00,
-0x16,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0xf8,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf8,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe4,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe4,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x19,0x03,0x00,0x00,
-0x29,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe3,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xdc,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xdc,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x1b,0x03,0x00,0x00,0x27,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xd9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xdb,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xc4,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc4,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x1d,0x03,0x00,0x00,0x25,0x03,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xc1,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc3,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xbc,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xbc,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1f,0x03,0x00,0x00,
-0x24,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xbb,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q4_k_f32_aligned_fp32_len = 11900;
-
-unsigned char matmul_q4_k_f32_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x86,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x21,0x01,0x00,0x00,0x78,0x01,0x00,0x00,
-0xc4,0x01,0x00,0x00,0xcf,0x01,0x00,0x00,0xb4,0x02,0x00,0x00,
-0xfd,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
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-0xb8,0x02,0x00,0x00,0x05,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x08,0x03,0x00,0x00,0x06,0x03,0x00,0x00,
-0xd0,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x0a,0x03,0x00,0x00,0x08,0x03,0x00,0x00,0x2a,0x03,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x0c,0x03,0x00,0x00,
-0x25,0x03,0x00,0x00,0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x0e,0x03,0x00,0x00,0x0c,0x03,0x00,0x00,
-0x28,0x03,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
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-0x06,0x00,0x00,0x00,0x13,0x03,0x00,0x00,0x10,0x03,0x00,0x00,
-0x12,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x15,0x03,0x00,0x00,0x13,0x03,0x00,0x00,0x2a,0x03,0x00,0x00,
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-0xc9,0x00,0x00,0x00,0x15,0x03,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xc3,0x00,0x00,0x00,0x17,0x03,0x00,0x00,0x16,0x03,0x00,0x00,
-0x41,0x00,0x06,0x00,0xda,0x01,0x00,0x00,0x18,0x03,0x00,0x00,
-0xfd,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0x0a,0x03,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x18,0x03,0x00,0x00,0x17,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xf9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf9,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xe5,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe5,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x1a,0x03,0x00,0x00,0x2a,0x03,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xe2,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe4,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xdd,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xdd,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1c,0x03,0x00,0x00,
-0x28,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xda,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xdc,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xc5,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xc5,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x1e,0x03,0x00,0x00,0x26,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xc2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xc4,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xbd,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xbd,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x20,0x03,0x00,0x00,0x25,0x03,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xba,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xbc,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q4_k_f32_fp32_len = 11932;
-
-unsigned char matmul_q5_0_f32_data[] = {
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-0x46,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
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-0xf9,0x00,0x02,0x00,0xa9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa9,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xde,0x02,0x00,0x00,0xf0,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa8,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xa1,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa1,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe0,0x02,0x00,0x00,0xee,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x9e,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa0,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
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-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe2,0x02,0x00,0x00,
-0xec,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x86,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x88,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x81,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x81,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe4,0x02,0x00,0x00,0xeb,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x7e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x80,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q5_0_f32_len = 11076;
-
-unsigned char matmul_q5_0_f32_aligned_data[] = {
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-0xd5,0x02,0x00,0x00,0xd6,0x02,0x00,0x00,0xd7,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xda,0x02,0x00,0x00,0xbf,0x02,0x00,0x00,
-0x11,0x03,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0xdb,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xdc,0x02,0x00,0x00,
-0xdb,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xdd,0x02,0x00,0x00,0xda,0x02,0x00,0x00,0xdc,0x02,0x00,0x00,
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-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xed,0x02,0x00,0x00,
-0x9f,0x02,0x00,0x00,0xec,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xef,0x02,0x00,0x00,0xed,0x02,0x00,0x00,
-0xb7,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf1,0x02,0x00,0x00,0xef,0x02,0x00,0x00,0x13,0x03,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf3,0x02,0x00,0x00,
-0x0e,0x03,0x00,0x00,0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf5,0x02,0x00,0x00,0xf3,0x02,0x00,0x00,
-0x11,0x03,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
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-0xf9,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
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-0xf9,0x00,0x02,0x00,0xe0,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe0,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xcc,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xcc,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x01,0x03,0x00,0x00,0x13,0x03,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xc9,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xcb,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xc4,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xc4,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x03,0x03,0x00,0x00,
-0x11,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xc1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xc3,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xac,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xac,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x05,0x03,0x00,0x00,0x0f,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xab,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xa4,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa4,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x07,0x03,0x00,0x00,0x0e,0x03,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xa1,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa3,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q5_0_f32_aligned_len = 11668;
-
-unsigned char matmul_q5_0_f32_aligned_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x37,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
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-0x51,0x01,0x00,0x00,0x84,0x01,0x00,0x00,0x8b,0x01,0x00,0x00,
-0x71,0x02,0x00,0x00,0xba,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
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-0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xcb,0x02,0x00,0x00,0xc9,0x02,0x00,0x00,0xe7,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xcd,0x02,0x00,0x00,
-0xcb,0x02,0x00,0x00,0xcc,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xcf,0x02,0x00,0x00,0xe5,0x02,0x00,0x00,
-0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd0,0x02,0x00,0x00,0xcd,0x02,0x00,0x00,0xcf,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd2,0x02,0x00,0x00,
-0xd0,0x02,0x00,0x00,0xe9,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0xcd,0x00,0x00,0x00,0xd3,0x02,0x00,0x00,0xca,0x00,0x00,0x00,
-0xd2,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,
-0xd4,0x02,0x00,0x00,0xd3,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0x8d,0x01,0x00,0x00,0xd5,0x02,0x00,0x00,0xba,0x02,0x00,0x00,
-0x35,0x00,0x00,0x00,0xc7,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xd5,0x02,0x00,0x00,0xd4,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb6,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd7,0x02,0x00,0x00,0xe9,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x9f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa1,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x9a,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x9a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd9,0x02,0x00,0x00,0xe7,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x97,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x99,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x82,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x82,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdb,0x02,0x00,0x00,
-0xe5,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x81,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x7a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdd,0x02,0x00,0x00,0xe4,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x77,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x79,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q5_0_f32_aligned_fp32_len = 10920;
-
-unsigned char matmul_q5_0_f32_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x3f,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x09,0x01,0x00,0x00,
-0x50,0x01,0x00,0x00,0x81,0x01,0x00,0x00,0x8c,0x01,0x00,0x00,
-0x71,0x02,0x00,0x00,0xba,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
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-0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
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-0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x12,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x38,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
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-0x47,0x00,0x04,0x00,0x02,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x04,0x01,0x00,0x00,
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-0x05,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0x82,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x82,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdb,0x02,0x00,0x00,
-0xe5,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x81,0x02,0x00,0x00,
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-0xdd,0x02,0x00,0x00,0xe4,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x77,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x79,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q5_0_f32_fp32_len = 10956;
-
-unsigned char matmul_q5_1_f32_data[] = {
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-0x9f,0x02,0x00,0x00,0xe9,0x02,0x00,0x00,0xbb,0x00,0x00,0x00,
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-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0xb5,0x02,0x00,0x00,
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-0xd2,0x02,0x00,0x00,0xeb,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0xcc,0x00,0x00,0x00,0xd5,0x02,0x00,0x00,0xc9,0x00,0x00,0x00,
-0xd4,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,
-0xd6,0x02,0x00,0x00,0xd5,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0x94,0x01,0x00,0x00,0xd7,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,
-0x35,0x00,0x00,0x00,0xc9,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xd7,0x02,0x00,0x00,0xd6,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb8,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb8,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa4,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa4,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd9,0x02,0x00,0x00,0xeb,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa3,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x9c,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x9c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xdb,0x02,0x00,0x00,0xe9,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x99,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x9b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x84,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x84,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdd,0x02,0x00,0x00,
-0xe7,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x81,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x83,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x7c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdf,0x02,0x00,0x00,0xe6,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x79,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7b,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q5_1_f32_len = 10956;
-
-unsigned char matmul_q5_1_f32_aligned_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x39,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x08,0x01,0x00,0x00,0x4c,0x01,0x00,0x00,
-0x81,0x01,0x00,0x00,0x89,0x01,0x00,0x00,0x96,0x02,0x00,0x00,
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-0xf9,0x00,0x02,0x00,0xa7,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa7,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x00,0x03,0x00,0x00,0x0a,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa4,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa6,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x9f,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x9f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x02,0x03,0x00,0x00,0x09,0x03,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x9c,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x9e,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q5_1_f32_aligned_len = 11548;
-
-unsigned char matmul_q5_1_f32_aligned_fp32_data[] = {
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-0xd0,0x02,0x00,0x00,0xcf,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb1,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x9d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9d,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd2,0x02,0x00,0x00,0xe4,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x9a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9c,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x95,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x95,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd4,0x02,0x00,0x00,0xe2,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x92,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x94,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7d,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd6,0x02,0x00,0x00,
-0xe0,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7c,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x75,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x75,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd8,0x02,0x00,0x00,0xdf,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x72,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x74,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q5_1_f32_aligned_fp32_len = 10800;
-
-unsigned char matmul_q5_1_f32_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x0f,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x07,0x01,0x00,0x00,
-0x4b,0x01,0x00,0x00,0x7c,0x01,0x00,0x00,0x87,0x01,0x00,0x00,
-0x6c,0x02,0x00,0x00,0xb5,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
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-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x85,0x02,0x00,0x00,
-0x5b,0x02,0x00,0x00,0x84,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
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-0x8f,0x02,0x00,0x00,0x69,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,
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-0x8d,0x02,0x00,0x00,0x8f,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x92,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x92,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xe2,0x02,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x7b,0x02,0x00,0x00,0xd4,0x02,0x00,0x00,
-0x95,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0x98,0x02,0x00,0x00,0xe2,0x02,0x00,0x00,0xbb,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x94,0x02,0x00,0x00,0x95,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x98,0x02,0x00,0x00,
-0x93,0x02,0x00,0x00,0x94,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x93,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x9a,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x9a,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xe4,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,
-0x93,0x02,0x00,0x00,0xd2,0x02,0x00,0x00,0x9d,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0xa0,0x02,0x00,0x00,
-0xe4,0x02,0x00,0x00,0x63,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x9c,0x02,0x00,0x00,0x9d,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xa0,0x02,0x00,0x00,0x9b,0x02,0x00,0x00,
-0x9c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x9b,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa3,0x02,0x00,0x00,
-0x88,0x02,0x00,0x00,0xe4,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0xa6,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,
-0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0xa8,0x02,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xa6,0x02,0x00,0x00,
-0xa7,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa7,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xab,0x02,0x00,0x00,0x90,0x02,0x00,0x00,0xe2,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0xac,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xad,0x02,0x00,0x00,0xac,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0xae,0x02,0x00,0x00,
-0xab,0x02,0x00,0x00,0xad,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa8,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa8,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0xc1,0x00,0x00,0x00,0xaf,0x02,0x00,0x00,
-0xa6,0x02,0x00,0x00,0x9b,0x02,0x00,0x00,0xae,0x02,0x00,0x00,
-0xa7,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,0xb1,0x02,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xaf,0x02,0x00,0x00,
-0xb0,0x02,0x00,0x00,0xb1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xb0,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb9,0x02,0x00,0x00,0x90,0x02,0x00,0x00,0xe2,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0xbb,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0xba,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xbc,0x02,0x00,0x00,0xbb,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xbd,0x02,0x00,0x00,
-0xb9,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbe,0x02,0x00,0x00,0x70,0x02,0x00,0x00,
-0xbd,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc0,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,0x88,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc2,0x02,0x00,0x00,
-0xc0,0x02,0x00,0x00,0xe4,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc4,0x02,0x00,0x00,0xdf,0x02,0x00,0x00,
-0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc6,0x02,0x00,0x00,0xc4,0x02,0x00,0x00,0xe2,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc8,0x02,0x00,0x00,
-0xc6,0x02,0x00,0x00,0xc7,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xca,0x02,0x00,0x00,0xe0,0x02,0x00,0x00,
-0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xcb,0x02,0x00,0x00,0xc8,0x02,0x00,0x00,0xca,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xcd,0x02,0x00,0x00,
-0xcb,0x02,0x00,0x00,0xe4,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0xcc,0x00,0x00,0x00,0xce,0x02,0x00,0x00,0xc9,0x00,0x00,0x00,
-0xcd,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,
-0xcf,0x02,0x00,0x00,0xce,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0x92,0x01,0x00,0x00,0xd0,0x02,0x00,0x00,0xb5,0x02,0x00,0x00,
-0x35,0x00,0x00,0x00,0xc2,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xd0,0x02,0x00,0x00,0xcf,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb1,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x9d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9d,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd2,0x02,0x00,0x00,0xe4,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x9a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9c,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x95,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x95,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd4,0x02,0x00,0x00,0xe2,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x92,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x94,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7d,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd6,0x02,0x00,0x00,
-0xe0,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7c,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x75,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x75,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd8,0x02,0x00,0x00,0xdf,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x72,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x74,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q5_1_f32_fp32_len = 10836;
-
-unsigned char matmul_q5_k_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xb2,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0x2e,0x01,0x00,0x00,0x83,0x01,0x00,0x00,0xeb,0x01,0x00,0x00,
-0xf6,0x01,0x00,0x00,0xe0,0x02,0x00,0x00,0x29,0x03,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x38,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x4d,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x50,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x54,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xa6,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xb8,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xbb,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x27,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x28,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x29,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
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-0xe8,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q5_k_f32_len = 12576;
-
-unsigned char matmul_q5_k_f32_aligned_data[] = {
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-0x30,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x32,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x2b,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x2b,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x6a,0x03,0x00,0x00,0x76,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x28,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
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-0xf8,0x00,0x02,0x00,0x13,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x6c,0x03,0x00,0x00,0x74,0x03,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x10,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x12,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x0b,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x0b,0x03,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x6e,0x03,0x00,0x00,
-0x73,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x08,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x0a,0x03,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q5_k_f32_aligned_len = 13172;
-
-unsigned char matmul_q5_k_f32_aligned_fp32_data[] = {
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-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q5_k_f32_aligned_fp32_len = 12424;
-
-unsigned char matmul_q5_k_f32_fp32_data[] = {
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-0x05,0x03,0x00,0x00,0x4d,0x03,0x00,0x00,0xbb,0x00,0x00,0x00,
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-0xc1,0x00,0x00,0x00,0x13,0x03,0x00,0x00,0x10,0x03,0x00,0x00,
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-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x19,0x03,0x00,0x00,
-0x14,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
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-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x1c,0x03,0x00,0x00,
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-0x2a,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x2d,0x03,0x00,0x00,0x2b,0x03,0x00,0x00,0xf5,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x2f,0x03,0x00,0x00,
-0x2d,0x03,0x00,0x00,0x4f,0x03,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x31,0x03,0x00,0x00,0x4a,0x03,0x00,0x00,
-0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x33,0x03,0x00,0x00,0x31,0x03,0x00,0x00,0x4d,0x03,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x35,0x03,0x00,0x00,
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-0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x38,0x03,0x00,0x00,0x35,0x03,0x00,0x00,0x37,0x03,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x3a,0x03,0x00,0x00,
-0x38,0x03,0x00,0x00,0x4f,0x03,0x00,0x00,0x41,0x00,0x05,0x00,
-0xcc,0x00,0x00,0x00,0x3b,0x03,0x00,0x00,0xc9,0x00,0x00,0x00,
-0x3a,0x03,0x00,0x00,0x3d,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,
-0x3c,0x03,0x00,0x00,0x3b,0x03,0x00,0x00,0x41,0x00,0x06,0x00,
-0xff,0x01,0x00,0x00,0x3d,0x03,0x00,0x00,0x22,0x03,0x00,0x00,
-0x35,0x00,0x00,0x00,0x2f,0x03,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x3d,0x03,0x00,0x00,0x3c,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x1e,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x1e,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x0a,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x0a,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x3f,0x03,0x00,0x00,0x4f,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x07,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x09,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0x02,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x02,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x41,0x03,0x00,0x00,0x4d,0x03,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xff,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x01,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xea,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xea,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x43,0x03,0x00,0x00,
-0x4b,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe7,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe9,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x45,0x03,0x00,0x00,0x4a,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xdf,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe1,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q5_k_f32_fp32_len = 12456;
-
-unsigned char matmul_q6_k_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x43,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
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-0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0x33,0x01,0x00,0x00,0x44,0x01,0x00,0x00,0xaf,0x01,0x00,0x00,
-0xba,0x01,0x00,0x00,0xa4,0x02,0x00,0x00,0xed,0x02,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
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-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x38,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x4d,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x50,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x54,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
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-0x14,0x00,0x00,0x00,0x9c,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
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-0xa7,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa8,0x02,0x00,0x00,
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-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x13,0x03,0x00,0x00,
-0x3f,0x00,0x00,0x00,0xd5,0x00,0x00,0x00,0x10,0x03,0x00,0x00,
-0xad,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
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-0xf6,0x00,0x04,0x00,0xac,0x02,0x00,0x00,0xad,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xb0,0x02,0x00,0x00,
-0xab,0x02,0x00,0x00,0xac,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xab,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xb2,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb2,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x14,0x03,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xab,0x02,0x00,0x00,0x0e,0x03,0x00,0x00,0xb5,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0xb8,0x02,0x00,0x00,
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-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc7,0x02,0x00,0x00,
-0x69,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
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-0xc7,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xca,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xca,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x16,0x03,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xb3,0x02,0x00,0x00,0x0c,0x03,0x00,0x00,0xcd,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0xd0,0x02,0x00,0x00,
-0x16,0x03,0x00,0x00,0xbb,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xcc,0x02,0x00,0x00,0xcd,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xd0,0x02,0x00,0x00,0xcb,0x02,0x00,0x00,
-0xcc,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xcb,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xd2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd2,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x18,0x03,0x00,0x00,0x3f,0x00,0x00,0x00,0xcb,0x02,0x00,0x00,
-0x0a,0x03,0x00,0x00,0xd5,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0xd8,0x02,0x00,0x00,0x18,0x03,0x00,0x00,
-0x63,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xd4,0x02,0x00,0x00,
-0xd5,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xd8,0x02,0x00,0x00,0xd3,0x02,0x00,0x00,0xd4,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd3,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xdb,0x02,0x00,0x00,0xc0,0x02,0x00,0x00,
-0x18,0x03,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
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-0xfa,0x00,0x04,0x00,0xde,0x02,0x00,0x00,0xdf,0x02,0x00,0x00,
-0xe0,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xdf,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe3,0x02,0x00,0x00,
-0xc8,0x02,0x00,0x00,0x16,0x03,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0xe4,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0xcf,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xe5,0x02,0x00,0x00,0xe4,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0xe6,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,
-0xe5,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xe0,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe0,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0xc1,0x00,0x00,0x00,0xe7,0x02,0x00,0x00,0xde,0x02,0x00,0x00,
-0xd3,0x02,0x00,0x00,0xe6,0x02,0x00,0x00,0xdf,0x02,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xe9,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xe7,0x02,0x00,0x00,0xe8,0x02,0x00,0x00,
-0xe9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe8,0x02,0x00,0x00,
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-0x17,0x00,0x00,0x00,0xf3,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0xf2,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xf4,0x02,0x00,0x00,0xf3,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf5,0x02,0x00,0x00,0xf1,0x02,0x00,0x00,
-0xf4,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf6,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,0xf5,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf8,0x02,0x00,0x00,
-0xf6,0x02,0x00,0x00,0xc0,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xfa,0x02,0x00,0x00,0xf8,0x02,0x00,0x00,
-0x18,0x03,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xfc,0x02,0x00,0x00,0x13,0x03,0x00,0x00,0xbb,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xfe,0x02,0x00,0x00,
-0xfc,0x02,0x00,0x00,0x16,0x03,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x00,0x03,0x00,0x00,0xfe,0x02,0x00,0x00,
-0xff,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x02,0x03,0x00,0x00,0x14,0x03,0x00,0x00,0x63,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x03,0x03,0x00,0x00,
-0x00,0x03,0x00,0x00,0x02,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x05,0x03,0x00,0x00,0x03,0x03,0x00,0x00,
-0x18,0x03,0x00,0x00,0x41,0x00,0x05,0x00,0xcc,0x00,0x00,0x00,
-0x06,0x03,0x00,0x00,0xc9,0x00,0x00,0x00,0x05,0x03,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,0x07,0x03,0x00,0x00,
-0x06,0x03,0x00,0x00,0x41,0x00,0x06,0x00,0xc5,0x01,0x00,0x00,
-0x08,0x03,0x00,0x00,0xed,0x02,0x00,0x00,0x35,0x00,0x00,0x00,
-0xfa,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0x08,0x03,0x00,0x00,
-0x07,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0xe9,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe9,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xd5,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xd5,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x0a,0x03,0x00,0x00,
-0x18,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xd2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xd4,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xcd,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xcd,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x0c,0x03,0x00,0x00,0x16,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xca,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xcc,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xb5,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb5,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x0e,0x03,0x00,0x00,0x14,0x03,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xb2,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb4,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xad,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xad,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x10,0x03,0x00,0x00,
-0x13,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xaa,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xac,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q6_k_f32_len = 11744;
-
-unsigned char matmul_q6_k_f32_aligned_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x64,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
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-0xf1,0x02,0x00,0x00,0x37,0x03,0x00,0x00,0xbc,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xed,0x02,0x00,0x00,0xee,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xf1,0x02,0x00,0x00,
-0xec,0x02,0x00,0x00,0xed,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xec,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xf3,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf3,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x39,0x03,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xec,0x02,0x00,0x00,0x2b,0x03,0x00,0x00,0xf6,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0xf9,0x02,0x00,0x00,
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-0xf5,0x02,0x00,0x00,0xf6,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
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-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xfc,0x02,0x00,0x00,
-0xe1,0x02,0x00,0x00,0x39,0x03,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0xff,0x02,0x00,0x00,0xfc,0x02,0x00,0x00,
-0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x01,0x03,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xff,0x02,0x00,0x00,
-0x00,0x03,0x00,0x00,0x01,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x00,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x04,0x03,0x00,0x00,0xe9,0x02,0x00,0x00,0x37,0x03,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x05,0x03,0x00,0x00,
-0x14,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
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-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0x07,0x03,0x00,0x00,
-0x04,0x03,0x00,0x00,0x06,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
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-0xf5,0x00,0x07,0x00,0xc2,0x00,0x00,0x00,0x08,0x03,0x00,0x00,
-0xff,0x02,0x00,0x00,0xf4,0x02,0x00,0x00,0x07,0x03,0x00,0x00,
-0x00,0x03,0x00,0x00,0xf7,0x00,0x03,0x00,0x0a,0x03,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x08,0x03,0x00,0x00,
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-0x09,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
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-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x14,0x03,0x00,0x00,
-0x14,0x00,0x00,0x00,0x13,0x03,0x00,0x00,0x3d,0x00,0x04,0x00,
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-0x06,0x00,0x00,0x00,0x17,0x03,0x00,0x00,0xc9,0x02,0x00,0x00,
-0x16,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x19,0x03,0x00,0x00,0x17,0x03,0x00,0x00,0xe1,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1b,0x03,0x00,0x00,
-0x19,0x03,0x00,0x00,0x39,0x03,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x1d,0x03,0x00,0x00,0x34,0x03,0x00,0x00,
-0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x1f,0x03,0x00,0x00,0x1d,0x03,0x00,0x00,0x37,0x03,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x21,0x03,0x00,0x00,
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-0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x24,0x03,0x00,0x00,0x21,0x03,0x00,0x00,0x23,0x03,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x26,0x03,0x00,0x00,
-0x24,0x03,0x00,0x00,0x39,0x03,0x00,0x00,0x41,0x00,0x05,0x00,
-0xcd,0x00,0x00,0x00,0x27,0x03,0x00,0x00,0xca,0x00,0x00,0x00,
-0x26,0x03,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,
-0x28,0x03,0x00,0x00,0x27,0x03,0x00,0x00,0x41,0x00,0x06,0x00,
-0xbb,0x01,0x00,0x00,0x29,0x03,0x00,0x00,0x0e,0x03,0x00,0x00,
-0x35,0x00,0x00,0x00,0x1b,0x03,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x29,0x03,0x00,0x00,0x28,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x0a,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x0a,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xf6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x2b,0x03,0x00,0x00,0x39,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xf3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf5,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xee,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xee,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x2d,0x03,0x00,0x00,0x37,0x03,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xeb,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xed,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xd6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xd6,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x2f,0x03,0x00,0x00,
-0x35,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xd3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xd5,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xce,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xce,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x31,0x03,0x00,0x00,0x34,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xcb,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xcd,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q6_k_f32_aligned_len = 12324;
-
-unsigned char matmul_q6_k_f32_aligned_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x3b,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x34,0x01,0x00,0x00,0x45,0x01,0x00,0x00,
-0xaf,0x01,0x00,0x00,0xb6,0x01,0x00,0x00,0x9c,0x02,0x00,0x00,
-0xe5,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x38,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,
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-0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
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-0x47,0x00,0x04,0x00,0xb9,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xbc,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x2b,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x2c,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x2e,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x30,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x80,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x30,0x01,0x00,0x00,0x02,0x00,0x00,0x00,
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-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x32,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x34,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x34,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
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-0xbf,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xa4,0x02,0x00,0x00,
-0xa5,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xa8,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,0xa4,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa3,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xaa,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xaa,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x0c,0x03,0x00,0x00,
-0x3f,0x00,0x00,0x00,0xa3,0x02,0x00,0x00,0x06,0x03,0x00,0x00,
-0xad,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xb0,0x02,0x00,0x00,0x0c,0x03,0x00,0x00,0x61,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xac,0x02,0x00,0x00,0xad,0x02,0x00,0x00,
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-0xb4,0x02,0x00,0x00,0x0c,0x03,0x00,0x00,0x62,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb5,0x02,0x00,0x00,
-0x8b,0x02,0x00,0x00,0xb4,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb7,0x02,0x00,0x00,0x65,0x00,0x00,0x00,
-0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb8,0x02,0x00,0x00,0xb5,0x02,0x00,0x00,0xb7,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xbc,0x02,0x00,0x00,
-0x0b,0x03,0x00,0x00,0x2b,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbd,0x02,0x00,0x00,0x91,0x02,0x00,0x00,
-0xbc,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xbf,0x02,0x00,0x00,0x69,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc0,0x02,0x00,0x00,
-0xbd,0x02,0x00,0x00,0xbf,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xc2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xc2,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x0e,0x03,0x00,0x00,
-0x3f,0x00,0x00,0x00,0xab,0x02,0x00,0x00,0x04,0x03,0x00,0x00,
-0xc5,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xc8,0x02,0x00,0x00,0x0e,0x03,0x00,0x00,0xbc,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xc4,0x02,0x00,0x00,0xc5,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xc8,0x02,0x00,0x00,
-0xc3,0x02,0x00,0x00,0xc4,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xc3,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xca,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xca,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x10,0x03,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xc3,0x02,0x00,0x00,0x02,0x03,0x00,0x00,0xcd,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0xd0,0x02,0x00,0x00,
-0x10,0x03,0x00,0x00,0x63,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xcc,0x02,0x00,0x00,0xcd,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xd0,0x02,0x00,0x00,0xcb,0x02,0x00,0x00,
-0xcc,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xcb,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd3,0x02,0x00,0x00,
-0xb8,0x02,0x00,0x00,0x10,0x03,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0xd6,0x02,0x00,0x00,0xd3,0x02,0x00,0x00,
-0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0xd8,0x02,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xd6,0x02,0x00,0x00,
-0xd7,0x02,0x00,0x00,0xd8,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd7,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdb,0x02,0x00,0x00,0xc0,0x02,0x00,0x00,0x0e,0x03,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0xdc,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xdd,0x02,0x00,0x00,0xdc,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0xde,0x02,0x00,0x00,
-0xdb,0x02,0x00,0x00,0xdd,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xd8,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xd8,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0xc2,0x00,0x00,0x00,0xdf,0x02,0x00,0x00,
-0xd6,0x02,0x00,0x00,0xcb,0x02,0x00,0x00,0xde,0x02,0x00,0x00,
-0xd7,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,0xe1,0x02,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xdf,0x02,0x00,0x00,
-0xe0,0x02,0x00,0x00,0xe1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe0,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe9,0x02,0x00,0x00,0xc0,0x02,0x00,0x00,0x0e,0x03,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0xeb,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0xea,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xec,0x02,0x00,0x00,0xeb,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xed,0x02,0x00,0x00,
-0xe9,0x02,0x00,0x00,0xec,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xee,0x02,0x00,0x00,0xa0,0x02,0x00,0x00,
-0xed,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf0,0x02,0x00,0x00,0xee,0x02,0x00,0x00,0xb8,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf2,0x02,0x00,0x00,
-0xf0,0x02,0x00,0x00,0x10,0x03,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf4,0x02,0x00,0x00,0x0b,0x03,0x00,0x00,
-0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf6,0x02,0x00,0x00,0xf4,0x02,0x00,0x00,0x0e,0x03,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf8,0x02,0x00,0x00,
-0xf6,0x02,0x00,0x00,0xf7,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xfa,0x02,0x00,0x00,0x0c,0x03,0x00,0x00,
-0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xfb,0x02,0x00,0x00,0xf8,0x02,0x00,0x00,0xfa,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xfd,0x02,0x00,0x00,
-0xfb,0x02,0x00,0x00,0x10,0x03,0x00,0x00,0x41,0x00,0x05,0x00,
-0xcd,0x00,0x00,0x00,0xfe,0x02,0x00,0x00,0xca,0x00,0x00,0x00,
-0xfd,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,
-0xff,0x02,0x00,0x00,0xfe,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0xb8,0x01,0x00,0x00,0x00,0x03,0x00,0x00,0xe5,0x02,0x00,0x00,
-0x35,0x00,0x00,0x00,0xf2,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x00,0x03,0x00,0x00,0xff,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe1,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xcd,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xcd,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x02,0x03,0x00,0x00,0x10,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xca,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xcc,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xc5,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc5,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x04,0x03,0x00,0x00,0x0e,0x03,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xc2,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc4,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xad,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xad,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x06,0x03,0x00,0x00,
-0x0c,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xaa,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xac,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa5,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa5,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x08,0x03,0x00,0x00,0x0b,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa4,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q6_k_f32_aligned_fp32_len = 11592;
-
-unsigned char matmul_q6_k_f32_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x3c,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x33,0x01,0x00,0x00,0x44,0x01,0x00,0x00,
-0xad,0x01,0x00,0x00,0xb8,0x01,0x00,0x00,0x9d,0x02,0x00,0x00,
-0xe6,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x38,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4d,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x50,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
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-0x06,0x00,0x00,0x00,0x84,0x02,0x00,0x00,0x25,0x03,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xdd,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xdf,0x01,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x0c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0xd5,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xd6,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
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-0x8b,0x02,0x00,0x00,0x56,0x00,0x00,0x00,0x54,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8c,0x02,0x00,0x00,
-0x96,0x00,0x00,0x00,0x8b,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x91,0x02,0x00,0x00,0x5a,0x00,0x00,0x00,
-0xb8,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x92,0x02,0x00,0x00,0xa7,0x00,0x00,0x00,0x91,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x96,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0x95,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x97,0x02,0x00,0x00,0x96,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x98,0x02,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x97,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9c,0x02,0x00,0x00,0x48,0x00,0x00,0x00,
-0x97,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,
-0x9e,0x02,0x00,0x00,0x9d,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,
-0x9e,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa0,0x02,0x00,0x00,0x9c,0x02,0x00,0x00,0x9f,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa1,0x02,0x00,0x00,
-0x98,0x02,0x00,0x00,0xa0,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa3,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x0c,0x03,0x00,0x00,
-0x3f,0x00,0x00,0x00,0xd5,0x00,0x00,0x00,0x09,0x03,0x00,0x00,
-0xa6,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0xa9,0x02,0x00,0x00,0x0c,0x03,0x00,0x00,0xbe,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xa5,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xa9,0x02,0x00,0x00,
-0xa4,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa4,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xab,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xab,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x0d,0x03,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xa4,0x02,0x00,0x00,0x07,0x03,0x00,0x00,0xae,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0xb1,0x02,0x00,0x00,
-0x0d,0x03,0x00,0x00,0x61,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xad,0x02,0x00,0x00,0xae,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xb1,0x02,0x00,0x00,0xac,0x02,0x00,0x00,
-0xad,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xac,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb5,0x02,0x00,0x00,
-0x0d,0x03,0x00,0x00,0x62,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb6,0x02,0x00,0x00,0x8c,0x02,0x00,0x00,
-0xb5,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb8,0x02,0x00,0x00,0x65,0x00,0x00,0x00,0x63,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb9,0x02,0x00,0x00,
-0xb6,0x02,0x00,0x00,0xb8,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbd,0x02,0x00,0x00,0x0c,0x03,0x00,0x00,
-0x2c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xbe,0x02,0x00,0x00,0x92,0x02,0x00,0x00,0xbd,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc0,0x02,0x00,0x00,
-0x69,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc1,0x02,0x00,0x00,0xbe,0x02,0x00,0x00,
-0xc0,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xc3,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc3,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x0f,0x03,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xac,0x02,0x00,0x00,0x05,0x03,0x00,0x00,0xc6,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0xc9,0x02,0x00,0x00,
-0x0f,0x03,0x00,0x00,0xbb,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xc5,0x02,0x00,0x00,0xc6,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xc9,0x02,0x00,0x00,0xc4,0x02,0x00,0x00,
-0xc5,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xc4,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xcb,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xcb,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x11,0x03,0x00,0x00,0x3f,0x00,0x00,0x00,0xc4,0x02,0x00,0x00,
-0x03,0x03,0x00,0x00,0xce,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0xd1,0x02,0x00,0x00,0x11,0x03,0x00,0x00,
-0x63,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xcd,0x02,0x00,0x00,
-0xce,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xd1,0x02,0x00,0x00,0xcc,0x02,0x00,0x00,0xcd,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xcc,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd4,0x02,0x00,0x00,0xb9,0x02,0x00,0x00,
-0x11,0x03,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0xd7,0x02,0x00,0x00,0xd4,0x02,0x00,0x00,0x37,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xd9,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xd7,0x02,0x00,0x00,0xd8,0x02,0x00,0x00,
-0xd9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xd8,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdc,0x02,0x00,0x00,
-0xc1,0x02,0x00,0x00,0x0f,0x03,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0xdd,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0xcf,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xde,0x02,0x00,0x00,0xdd,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0xdf,0x02,0x00,0x00,0xdc,0x02,0x00,0x00,
-0xde,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xd9,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd9,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
-0xc1,0x00,0x00,0x00,0xe0,0x02,0x00,0x00,0xd7,0x02,0x00,0x00,
-0xcc,0x02,0x00,0x00,0xdf,0x02,0x00,0x00,0xd8,0x02,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xe2,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xe0,0x02,0x00,0x00,0xe1,0x02,0x00,0x00,
-0xe2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe1,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xea,0x02,0x00,0x00,
-0xc1,0x02,0x00,0x00,0x0f,0x03,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0xec,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0xeb,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xed,0x02,0x00,0x00,0xec,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xee,0x02,0x00,0x00,0xea,0x02,0x00,0x00,
-0xed,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xef,0x02,0x00,0x00,0xa1,0x02,0x00,0x00,0xee,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf1,0x02,0x00,0x00,
-0xef,0x02,0x00,0x00,0xb9,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf3,0x02,0x00,0x00,0xf1,0x02,0x00,0x00,
-0x11,0x03,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf5,0x02,0x00,0x00,0x0c,0x03,0x00,0x00,0xbb,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf7,0x02,0x00,0x00,
-0xf5,0x02,0x00,0x00,0x0f,0x03,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf9,0x02,0x00,0x00,0xf7,0x02,0x00,0x00,
-0xf8,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xfb,0x02,0x00,0x00,0x0d,0x03,0x00,0x00,0x63,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xfc,0x02,0x00,0x00,
-0xf9,0x02,0x00,0x00,0xfb,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xfe,0x02,0x00,0x00,0xfc,0x02,0x00,0x00,
-0x11,0x03,0x00,0x00,0x41,0x00,0x05,0x00,0xcc,0x00,0x00,0x00,
-0xff,0x02,0x00,0x00,0xc9,0x00,0x00,0x00,0xfe,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,0x00,0x03,0x00,0x00,
-0xff,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0xc3,0x01,0x00,0x00,
-0x01,0x03,0x00,0x00,0xe6,0x02,0x00,0x00,0x35,0x00,0x00,0x00,
-0xf3,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0x01,0x03,0x00,0x00,
-0x00,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0xe2,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe2,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xce,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xce,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x03,0x03,0x00,0x00,
-0x11,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xcb,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xcd,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xc6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xc6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x05,0x03,0x00,0x00,0x0f,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xc3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xc5,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xae,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xae,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x07,0x03,0x00,0x00,0x0d,0x03,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xab,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xad,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa6,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x09,0x03,0x00,0x00,
-0x0c,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa5,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q6_k_f32_fp32_len = 11624;
-
-unsigned char matmul_q8_0_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xf1,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x0a,0x01,0x00,0x00,0x28,0x01,0x00,0x00,
-0x5b,0x01,0x00,0x00,0x66,0x01,0x00,0x00,0x50,0x02,0x00,0x00,
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-0x79,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x79,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb8,0x02,0x00,0x00,
-0xc4,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x76,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x78,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x61,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x61,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xba,0x02,0x00,0x00,0xc2,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x60,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x59,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x59,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbc,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x56,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x58,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q8_0_f32_len = 10588;
-
-unsigned char matmul_q8_0_f32_aligned_data[] = {
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-0x99,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xe7,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x82,0x02,0x00,0x00,
-0xdb,0x02,0x00,0x00,0x9c,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,0xe7,0x02,0x00,0x00,
-0xbc,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x9b,0x02,0x00,0x00,
-0x9c,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x9f,0x02,0x00,0x00,0x9a,0x02,0x00,0x00,0x9b,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x9a,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa1,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xe9,0x02,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x9a,0x02,0x00,0x00,0xd9,0x02,0x00,0x00,
-0xa4,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xa7,0x02,0x00,0x00,0xe9,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xa3,0x02,0x00,0x00,0xa4,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xa7,0x02,0x00,0x00,
-0xa2,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xaa,0x02,0x00,0x00,0x8f,0x02,0x00,0x00,0xe9,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0xad,0x02,0x00,0x00,
-0xaa,0x02,0x00,0x00,0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xaf,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xad,0x02,0x00,0x00,0xae,0x02,0x00,0x00,0xaf,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xae,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb2,0x02,0x00,0x00,0x97,0x02,0x00,0x00,
-0xe7,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0xb3,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xb4,0x02,0x00,0x00,
-0xb3,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xb5,0x02,0x00,0x00,0xb2,0x02,0x00,0x00,0xb4,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xaf,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xaf,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0xc2,0x00,0x00,0x00,
-0xb6,0x02,0x00,0x00,0xad,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,
-0xb5,0x02,0x00,0x00,0xae,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xb8,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xb6,0x02,0x00,0x00,0xb7,0x02,0x00,0x00,0xb8,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb7,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc0,0x02,0x00,0x00,0x97,0x02,0x00,0x00,
-0xe7,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0xc2,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xc1,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xc3,0x02,0x00,0x00,
-0xc2,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc4,0x02,0x00,0x00,0xc0,0x02,0x00,0x00,0xc3,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc5,0x02,0x00,0x00,
-0x77,0x02,0x00,0x00,0xc4,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc7,0x02,0x00,0x00,0xc5,0x02,0x00,0x00,
-0x8f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc9,0x02,0x00,0x00,0xc7,0x02,0x00,0x00,0xe9,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xcb,0x02,0x00,0x00,
-0xe4,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xcd,0x02,0x00,0x00,0xcb,0x02,0x00,0x00,
-0xe7,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xcf,0x02,0x00,0x00,0xcd,0x02,0x00,0x00,0xce,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd1,0x02,0x00,0x00,
-0xe5,0x02,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd2,0x02,0x00,0x00,0xcf,0x02,0x00,0x00,
-0xd1,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd4,0x02,0x00,0x00,0xd2,0x02,0x00,0x00,0xe9,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,0xd5,0x02,0x00,0x00,
-0xca,0x00,0x00,0x00,0xd4,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xc4,0x00,0x00,0x00,0xd6,0x02,0x00,0x00,0xd5,0x02,0x00,0x00,
-0x41,0x00,0x06,0x00,0x68,0x01,0x00,0x00,0xd7,0x02,0x00,0x00,
-0xbc,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0xc9,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xd7,0x02,0x00,0x00,0xd6,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xb8,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xb8,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xa4,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa4,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd9,0x02,0x00,0x00,0xe9,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xa1,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa3,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x9c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x9c,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdb,0x02,0x00,0x00,
-0xe7,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x99,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x9b,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x84,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x84,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdd,0x02,0x00,0x00,0xe5,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x81,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x83,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x7c,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xdf,0x02,0x00,0x00,0xe4,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x79,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q8_0_f32_aligned_len = 11200;
-
-unsigned char matmul_q8_0_f32_aligned_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xea,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x0b,0x01,0x00,0x00,
-0x29,0x01,0x00,0x00,0x5c,0x01,0x00,0x00,0x63,0x01,0x00,0x00,
-0x49,0x02,0x00,0x00,0x92,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x12,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x38,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x3e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4d,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x50,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x54,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x63,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xa7,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xb9,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xbc,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x06,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x07,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x07,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x08,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x09,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x09,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x09,0x01,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x01,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x01,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x34,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x35,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x60,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
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-0x7a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xaf,0x02,0x00,0x00,0xbf,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x77,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x79,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x72,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x72,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb1,0x02,0x00,0x00,0xbd,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x6f,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x71,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x5a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5a,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb3,0x02,0x00,0x00,
-0xbb,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x57,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x59,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x52,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x52,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb5,0x02,0x00,0x00,0xba,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x4f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x51,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t matmul_q8_0_f32_aligned_fp32_len = 10452;
-
-unsigned char matmul_q8_0_f32_fp32_data[] = {
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-0xba,0x02,0x00,0x00,0xbe,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x51,0x02,0x00,0x00,0x52,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x55,0x02,0x00,0x00,0x50,0x02,0x00,0x00,
-0x51,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x50,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x57,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x57,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xbb,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x50,0x02,0x00,0x00,
-0xb3,0x02,0x00,0x00,0x5a,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0x5d,0x02,0x00,0x00,0xbb,0x02,0x00,0x00,
-0x61,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x59,0x02,0x00,0x00,
-0x5a,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x5d,0x02,0x00,0x00,0x58,0x02,0x00,0x00,0x59,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x58,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x61,0x02,0x00,0x00,0xbb,0x02,0x00,0x00,
-0x62,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x62,0x02,0x00,0x00,0x38,0x02,0x00,0x00,0x61,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x64,0x02,0x00,0x00,
-0x65,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x65,0x02,0x00,0x00,0x62,0x02,0x00,0x00,
-0x64,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x69,0x02,0x00,0x00,0xba,0x02,0x00,0x00,0xd8,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x6a,0x02,0x00,0x00,
-0x3e,0x02,0x00,0x00,0x69,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x6c,0x02,0x00,0x00,0x69,0x00,0x00,0x00,
-0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x6d,0x02,0x00,0x00,0x6a,0x02,0x00,0x00,0x6c,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x6f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x6f,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xbd,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x58,0x02,0x00,0x00,
-0xb1,0x02,0x00,0x00,0x72,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0x75,0x02,0x00,0x00,0xbd,0x02,0x00,0x00,
-0xbb,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x71,0x02,0x00,0x00,
-0x72,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x75,0x02,0x00,0x00,0x70,0x02,0x00,0x00,0x71,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x70,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x77,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x77,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xbf,0x02,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x70,0x02,0x00,0x00,0xaf,0x02,0x00,0x00,
-0x7a,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0x7d,0x02,0x00,0x00,0xbf,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x79,0x02,0x00,0x00,0x7a,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x7d,0x02,0x00,0x00,
-0x78,0x02,0x00,0x00,0x79,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x78,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x80,0x02,0x00,0x00,0x65,0x02,0x00,0x00,0xbf,0x02,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x83,0x02,0x00,0x00,
-0x80,0x02,0x00,0x00,0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x85,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x83,0x02,0x00,0x00,0x84,0x02,0x00,0x00,0x85,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x84,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x88,0x02,0x00,0x00,0x6d,0x02,0x00,0x00,
-0xbd,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x89,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x8a,0x02,0x00,0x00,
-0x89,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0x8b,0x02,0x00,0x00,0x88,0x02,0x00,0x00,0x8a,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x85,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x85,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0xc1,0x00,0x00,0x00,
-0x8c,0x02,0x00,0x00,0x83,0x02,0x00,0x00,0x78,0x02,0x00,0x00,
-0x8b,0x02,0x00,0x00,0x84,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x8e,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x8c,0x02,0x00,0x00,0x8d,0x02,0x00,0x00,0x8e,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x8d,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x96,0x02,0x00,0x00,0x6d,0x02,0x00,0x00,
-0xbd,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x98,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0x97,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x99,0x02,0x00,0x00,
-0x98,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9a,0x02,0x00,0x00,0x96,0x02,0x00,0x00,0x99,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9b,0x02,0x00,0x00,
-0x4d,0x02,0x00,0x00,0x9a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9d,0x02,0x00,0x00,0x9b,0x02,0x00,0x00,
-0x65,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9f,0x02,0x00,0x00,0x9d,0x02,0x00,0x00,0xbf,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa1,0x02,0x00,0x00,
-0xba,0x02,0x00,0x00,0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa3,0x02,0x00,0x00,0xa1,0x02,0x00,0x00,
-0xbd,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa5,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,0xa4,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,
-0xbb,0x02,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa8,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,
-0xa7,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xaa,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,0xbf,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0xcc,0x00,0x00,0x00,0xab,0x02,0x00,0x00,
-0xc9,0x00,0x00,0x00,0xaa,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xc3,0x00,0x00,0x00,0xac,0x02,0x00,0x00,0xab,0x02,0x00,0x00,
-0x41,0x00,0x06,0x00,0x6f,0x01,0x00,0x00,0xad,0x02,0x00,0x00,
-0x92,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xad,0x02,0x00,0x00,0xac,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x8e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8e,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x7a,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xaf,0x02,0x00,0x00,0xbf,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x77,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x79,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x72,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x72,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb1,0x02,0x00,0x00,
-0xbd,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x6f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x71,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb3,0x02,0x00,0x00,0xbb,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x57,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x59,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x52,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x52,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb5,0x02,0x00,0x00,0xba,0x02,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x4f,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x51,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_q8_0_f32_fp32_len = 10468;
-
-unsigned char mul_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x67,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x17,0x00,0x00,0x00,0x2f,0x01,0x00,0x00,0x3f,0x01,0x00,0x00,
-0x4b,0x01,0x00,0x00,0x56,0x01,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x3c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x44,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x48,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,
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-0x80,0x01,0x00,0x00,0x77,0x01,0x00,0x00,0x82,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x86,0x01,0x00,0x00,0x33,0x01,0x00,0x00,
-0x83,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8b,0x01,0x00,0x00,0x74,0x01,0x00,0x00,0x77,0x01,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8c,0x01,0x00,0x00,
-0x86,0x01,0x00,0x00,0x8b,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x90,0x01,0x00,0x00,0x8c,0x01,0x00,0x00,
-0x74,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x93,0x01,0x00,0x00,0x90,0x01,0x00,0x00,0x77,0x01,0x00,0x00,
-0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x98,0x01,0x00,0x00,
-0x86,0x01,0x00,0x00,0x93,0x01,0x00,0x00,0x86,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9b,0x01,0x00,0x00,0x98,0x01,0x00,0x00,
-0x77,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa4,0x01,0x00,0x00,0x9b,0x01,0x00,0x00,0x77,0x01,0x00,0x00,
-0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa5,0x01,0x00,0x00,
-0x98,0x01,0x00,0x00,0xa4,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1a,0x00,0x00,0x00,0xa7,0x01,0x00,0x00,0x17,0x00,0x00,0x00,
-0x15,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xa8,0x01,0x00,0x00,0xa7,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa9,0x01,0x00,0x00,0x79,0x01,0x00,0x00,
-0xa8,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,
-0xab,0x01,0x00,0x00,0x17,0x00,0x00,0x00,0x1a,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xac,0x01,0x00,0x00,
-0xab,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xad,0x01,0x00,0x00,0x8c,0x01,0x00,0x00,0xac,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xae,0x01,0x00,0x00,
-0xa9,0x01,0x00,0x00,0xad,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1a,0x00,0x00,0x00,0xb0,0x01,0x00,0x00,0x17,0x00,0x00,0x00,
-0x20,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xb1,0x01,0x00,0x00,0xb0,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb2,0x01,0x00,0x00,0x9b,0x01,0x00,0x00,
-0xb1,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb3,0x01,0x00,0x00,0xae,0x01,0x00,0x00,0xb2,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0xb5,0x01,0x00,0x00,
-0x17,0x00,0x00,0x00,0x26,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xb6,0x01,0x00,0x00,0xb5,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb7,0x01,0x00,0x00,
-0xa5,0x01,0x00,0x00,0xb6,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb8,0x01,0x00,0x00,0xb3,0x01,0x00,0x00,
-0xb7,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x47,0x01,0x00,0x00,0x42,0x01,0x00,0x00,0xb8,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0xc2,0x01,0x00,0x00,
-0x17,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xc3,0x01,0x00,0x00,0xc2,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0xc4,0x01,0x00,0x00,
-0x17,0x00,0x00,0x00,0x1d,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xc5,0x01,0x00,0x00,0xc4,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc6,0x01,0x00,0x00,
-0xc3,0x01,0x00,0x00,0xc5,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1a,0x00,0x00,0x00,0xc7,0x01,0x00,0x00,0x17,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xc8,0x01,0x00,0x00,0xc7,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc9,0x01,0x00,0x00,0xc6,0x01,0x00,0x00,
-0xc8,0x01,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xca,0x01,0x00,0x00,0x33,0x01,0x00,0x00,0xc9,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xce,0x01,0x00,0x00,
-0xca,0x01,0x00,0x00,0xc3,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd1,0x01,0x00,0x00,0xce,0x01,0x00,0x00,
-0xc5,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd4,0x01,0x00,0x00,0xd1,0x01,0x00,0x00,0xc8,0x01,0x00,0x00,
-0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd7,0x01,0x00,0x00,
-0x33,0x01,0x00,0x00,0xd4,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xdc,0x01,0x00,0x00,0xc5,0x01,0x00,0x00,
-0xc8,0x01,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdd,0x01,0x00,0x00,0xd7,0x01,0x00,0x00,0xdc,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe1,0x01,0x00,0x00,
-0xdd,0x01,0x00,0x00,0xc5,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe4,0x01,0x00,0x00,0xe1,0x01,0x00,0x00,
-0xc8,0x01,0x00,0x00,0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe9,0x01,0x00,0x00,0xd7,0x01,0x00,0x00,0xe4,0x01,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xec,0x01,0x00,0x00,
-0xe9,0x01,0x00,0x00,0xc8,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf5,0x01,0x00,0x00,0xec,0x01,0x00,0x00,
-0xc8,0x01,0x00,0x00,0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf6,0x01,0x00,0x00,0xe9,0x01,0x00,0x00,0xf5,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0xf8,0x01,0x00,0x00,
-0x17,0x00,0x00,0x00,0x58,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xf9,0x01,0x00,0x00,0xf8,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xfa,0x01,0x00,0x00,
-0xca,0x01,0x00,0x00,0xf9,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1a,0x00,0x00,0x00,0xfc,0x01,0x00,0x00,0x17,0x00,0x00,0x00,
-0x5d,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xfd,0x01,0x00,0x00,0xfc,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xfe,0x01,0x00,0x00,0xdd,0x01,0x00,0x00,
-0xfd,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xff,0x01,0x00,0x00,0xfa,0x01,0x00,0x00,0xfe,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0x01,0x02,0x00,0x00,
-0x17,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x02,0x02,0x00,0x00,0x01,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x03,0x02,0x00,0x00,
-0xec,0x01,0x00,0x00,0x02,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x04,0x02,0x00,0x00,0xff,0x01,0x00,0x00,
-0x03,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,
-0x06,0x02,0x00,0x00,0x17,0x00,0x00,0x00,0x69,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x07,0x02,0x00,0x00,
-0x06,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x08,0x02,0x00,0x00,0xf6,0x01,0x00,0x00,0x07,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x09,0x02,0x00,0x00,
-0x04,0x02,0x00,0x00,0x08,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0x50,0x01,0x00,0x00,0x51,0x01,0x00,0x00,0x4b,0x01,0x00,0x00,
-0x34,0x01,0x00,0x00,0x09,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x14,0x00,0x00,0x00,0x52,0x01,0x00,0x00,0x51,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0x49,0x02,0x00,0x00,
-0x17,0x00,0x00,0x00,0xad,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x4a,0x02,0x00,0x00,0x49,0x02,0x00,0x00,
-0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x4b,0x02,0x00,0x00,
-0xca,0x01,0x00,0x00,0x4a,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1a,0x00,0x00,0x00,0x4c,0x02,0x00,0x00,0x17,0x00,0x00,0x00,
-0xb1,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x4d,0x02,0x00,0x00,0x4c,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x4e,0x02,0x00,0x00,0x4b,0x02,0x00,0x00,
-0x4d,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,
-0x50,0x02,0x00,0x00,0x17,0x00,0x00,0x00,0xb6,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x51,0x02,0x00,0x00,
-0x50,0x02,0x00,0x00,0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x52,0x02,0x00,0x00,0xdd,0x01,0x00,0x00,0x51,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0x53,0x02,0x00,0x00,
-0x17,0x00,0x00,0x00,0xba,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x54,0x02,0x00,0x00,0x53,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x55,0x02,0x00,0x00,
-0x52,0x02,0x00,0x00,0x54,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x56,0x02,0x00,0x00,0x4e,0x02,0x00,0x00,
-0x55,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,
-0x58,0x02,0x00,0x00,0x17,0x00,0x00,0x00,0xc0,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x59,0x02,0x00,0x00,
-0x58,0x02,0x00,0x00,0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x5a,0x02,0x00,0x00,0xec,0x01,0x00,0x00,0x59,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0x5b,0x02,0x00,0x00,
-0x17,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x5c,0x02,0x00,0x00,0x5b,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x5d,0x02,0x00,0x00,
-0x5a,0x02,0x00,0x00,0x5c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x5e,0x02,0x00,0x00,0x56,0x02,0x00,0x00,
-0x5d,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,
-0x60,0x02,0x00,0x00,0x17,0x00,0x00,0x00,0xca,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x61,0x02,0x00,0x00,
-0x60,0x02,0x00,0x00,0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x62,0x02,0x00,0x00,0xf6,0x01,0x00,0x00,0x61,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0x63,0x02,0x00,0x00,
-0x17,0x00,0x00,0x00,0xce,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x64,0x02,0x00,0x00,0x63,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x65,0x02,0x00,0x00,
-0x62,0x02,0x00,0x00,0x64,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x66,0x02,0x00,0x00,0x5e,0x02,0x00,0x00,
-0x65,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0x50,0x01,0x00,0x00,
-0x5b,0x01,0x00,0x00,0x56,0x01,0x00,0x00,0x34,0x01,0x00,0x00,
-0x66,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x14,0x00,0x00,0x00,
-0x5c,0x01,0x00,0x00,0x5b,0x01,0x00,0x00,0x85,0x00,0x05,0x00,
-0x14,0x00,0x00,0x00,0x5d,0x01,0x00,0x00,0x52,0x01,0x00,0x00,
-0x5c,0x01,0x00,0x00,0x41,0x00,0x06,0x00,0x50,0x01,0x00,0x00,
-0x5e,0x01,0x00,0x00,0x3f,0x01,0x00,0x00,0x34,0x01,0x00,0x00,
-0x47,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x5e,0x01,0x00,0x00,
-0x5d,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x62,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x62,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_f32_len = 4276;
-
-unsigned char mul_mat_vec_f16_f16_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
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-0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,0xd2,0x00,0x00,0x00,
-0xd1,0x00,0x00,0x00,0x73,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
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-0x47,0x01,0x00,0x00,0x6a,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
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-0xfa,0x00,0x04,0x00,0xe5,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,
-0xe1,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xe0,0x00,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x95,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,
-0x78,0x00,0x00,0x00,0x47,0x01,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xea,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
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-0x47,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x89,0x00,0x00,0x00,
-0xef,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0xee,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,
-0xef,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xf2,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,0x81,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x8a,0x00,0x00,0x00,
-0xf3,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xea,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xea,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x70,0x00,0x00,0x00,0x70,0x00,0x00,0x00,0xdc,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe2,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe2,0x00,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf7,0x00,0x00,0x00,0x47,0x01,0x00,0x00,0xf5,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xdf,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe1,0x00,0x00,0x00,0xaa,0x00,0x05,0x00,0x95,0x00,0x00,0x00,
-0xf9,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x6a,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xfb,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xf9,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,
-0xfb,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xfa,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x02,0x01,0x00,0x00,
-0x33,0x01,0x00,0x00,0x74,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x89,0x00,0x00,0x00,0x03,0x01,0x00,0x00,0x86,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x04,0x01,0x00,0x00,0x03,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x05,0x01,0x00,0x00,0x06,0x01,0x00,0x00,0xff,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x02,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x06,0x01,0x00,0x00,0x04,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xfb,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xfb,0x00,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_f16_f16_f32_len = 3716;
-
-unsigned char mul_mat_vec_f16_f32_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
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-0x3a,0x00,0x00,0x00,0x3b,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x12,0x01,0x00,0x00,0x11,0x01,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x13,0x01,0x00,0x00,
-0x0f,0x01,0x00,0x00,0x12,0x01,0x00,0x00,0x89,0x00,0x05,0x00,
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-0x06,0x00,0x00,0x00,0x1e,0x01,0x00,0x00,0x1d,0x01,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1f,0x01,0x00,0x00,
-0x17,0x01,0x00,0x00,0x1e,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x3c,0x00,0x00,0x00,0x21,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x53,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x22,0x01,0x00,0x00,0x21,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x23,0x01,0x00,0x00,0x1b,0x01,0x00,0x00,
-0x22,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x25,0x01,0x00,0x00,0x23,0x01,0x00,0x00,0x1f,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x3c,0x00,0x00,0x00,0x27,0x01,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x5a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x28,0x01,0x00,0x00,0x27,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x29,0x01,0x00,0x00,
-0x25,0x01,0x00,0x00,0x28,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x3c,0x00,0x00,0x00,0x2b,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x5f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x2c,0x01,0x00,0x00,0x2b,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x2d,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,
-0x2c,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x3c,0x00,0x00,0x00,
-0x2f,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0x64,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x30,0x01,0x00,0x00,
-0x2f,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x31,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,0x30,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x89,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,
-0x86,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x8a,0x00,0x00,0x00,0x88,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x8c,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x8c,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x44,0x01,0x00,0x00,
-0x6a,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0xda,0x00,0x00,0x00,
-0x8d,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x3c,0x00,0x00,0x00,
-0x92,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x93,0x00,0x00,0x00,
-0x92,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x94,0x00,0x00,0x00,0x93,0x00,0x00,0x00,0x83,0x00,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x95,0x00,0x00,0x00,0x96,0x00,0x00,0x00,
-0x44,0x01,0x00,0x00,0x94,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x8e,0x00,0x00,0x00,0x8d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x96,0x00,0x00,0x00,0x8d,0x00,0x00,0x00,
-0x8e,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x8d,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x99,0x00,0x00,0x00,
-0x44,0x01,0x00,0x00,0x83,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9b,0x00,0x00,0x00,0x70,0x00,0x00,0x00,
-0x78,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9c,0x00,0x00,0x00,0x99,0x00,0x00,0x00,0x9b,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa1,0x00,0x00,0x00,
-0x74,0x00,0x00,0x00,0x93,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa3,0x00,0x00,0x00,0xa1,0x00,0x00,0x00,
-0x9c,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa4,0x00,0x00,0x00,0xa3,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,
-0x9c,0x00,0x00,0x00,0x27,0x00,0x00,0x00,0x86,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa8,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xad,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb1,0x00,0x00,0x00,
-0x29,0x01,0x00,0x00,0x27,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x36,0x01,0x00,0x00,0xb1,0x00,0x00,0x00,
-0xa4,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x20,0x00,0x00,0x00,
-0x37,0x01,0x00,0x00,0x1a,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x36,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x38,0x01,0x00,0x00,0x37,0x01,0x00,0x00,0x73,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x39,0x01,0x00,0x00,0x38,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x3d,0x01,0x00,0x00,
-0x36,0x01,0x00,0x00,0x27,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x20,0x00,0x00,0x00,0x3e,0x01,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x3d,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x16,0x00,0x00,0x00,0x3f,0x01,0x00,0x00,0x3e,0x01,0x00,0x00,
-0x73,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x40,0x01,0x00,0x00,
-0x3f,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc2,0x00,0x00,0x00,0x2d,0x01,0x00,0x00,0xad,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,
-0xc2,0x00,0x00,0x00,0xa8,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0xc5,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xc4,0x00,0x00,0x00,0x27,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0xc5,0x00,0x00,0x00,0xd1,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xd2,0x00,0x00,0x00,0xd1,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xd3,0x00,0x00,0x00,
-0x40,0x01,0x00,0x00,0xd2,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,
-0x08,0x00,0x00,0x00,0xd4,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0x39,0x01,0x00,0x00,0xc7,0x00,0x00,0x00,
-0xd3,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xd6,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,0x81,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0xd7,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,
-0xd4,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x8a,0x00,0x00,0x00,
-0xd7,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xda,0x00,0x00,0x00,0x44,0x01,0x00,0x00,0x70,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x8c,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8e,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,0x70,0x00,0x00,0x00,
-0x70,0x00,0x00,0x00,0xdb,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xde,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xde,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x45,0x01,0x00,0x00,
-0xdd,0x00,0x00,0x00,0x8e,0x00,0x00,0x00,0xf6,0x00,0x00,0x00,
-0xe1,0x00,0x00,0x00,0xac,0x00,0x05,0x00,0x95,0x00,0x00,0x00,
-0xe4,0x00,0x00,0x00,0x45,0x01,0x00,0x00,0x6a,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xe0,0x00,0x00,0x00,0xe1,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xe4,0x00,0x00,0x00,
-0xdf,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xdf,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,0x95,0x00,0x00,0x00,
-0xe7,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x45,0x01,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xe9,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xe7,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,
-0xe9,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xe8,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0x78,0x00,0x00,0x00,0x45,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x89,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
-0xed,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xef,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,
-0xf1,0x00,0x00,0x00,0xef,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x8a,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe9,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xe9,0x00,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x70,0x00,0x00,0x00,0x70,0x00,0x00,0x00,
-0xdb,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xe1,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe1,0x00,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf6,0x00,0x00,0x00,0x45,0x01,0x00,0x00,
-0xf4,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xde,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe0,0x00,0x00,0x00,0xaa,0x00,0x05,0x00,
-0x95,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,0x78,0x00,0x00,0x00,
-0x6a,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0xfa,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xf8,0x00,0x00,0x00,
-0xf9,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf9,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x01,0x01,0x00,0x00,0x31,0x01,0x00,0x00,0x74,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x89,0x00,0x00,0x00,0x02,0x01,0x00,0x00,
-0x86,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x03,0x01,0x00,0x00,0x02,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0xc5,0x00,0x00,0x00,0x04,0x01,0x00,0x00,
-0xfe,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x01,0x01,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x04,0x01,0x00,0x00,0x03,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xfa,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xfa,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t mul_mat_vec_f16_f32_f32_len = 3684;
-
-unsigned char mul_mat_vec_f32_f16_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x44,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
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-0x06,0x00,0x00,0x00,0x17,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,
-0x12,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x39,0x00,0x00,0x00,
-0x19,0x01,0x00,0x00,0x37,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x1a,0x01,0x00,0x00,
-0x19,0x01,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x1b,0x01,0x00,0x00,0x13,0x01,0x00,0x00,0x1a,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x39,0x00,0x00,0x00,0x1d,0x01,0x00,0x00,
-0x37,0x00,0x00,0x00,0x4a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x1e,0x01,0x00,0x00,0x1d,0x01,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1f,0x01,0x00,0x00,
-0x17,0x01,0x00,0x00,0x1e,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x39,0x00,0x00,0x00,0x21,0x01,0x00,0x00,0x37,0x00,0x00,0x00,
-0x50,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x22,0x01,0x00,0x00,0x21,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x23,0x01,0x00,0x00,0x1b,0x01,0x00,0x00,
-0x22,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x25,0x01,0x00,0x00,0x23,0x01,0x00,0x00,0x1f,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x39,0x00,0x00,0x00,0x27,0x01,0x00,0x00,
-0x37,0x00,0x00,0x00,0x57,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x28,0x01,0x00,0x00,0x27,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x29,0x01,0x00,0x00,
-0x25,0x01,0x00,0x00,0x28,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x39,0x00,0x00,0x00,0x2b,0x01,0x00,0x00,0x37,0x00,0x00,0x00,
-0x5c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x2c,0x01,0x00,0x00,0x2b,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x2d,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,
-0x2c,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x39,0x00,0x00,0x00,
-0x2f,0x01,0x00,0x00,0x37,0x00,0x00,0x00,0x61,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x30,0x01,0x00,0x00,
-0x2f,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x31,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,0x30,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x86,0x00,0x00,0x00,0x87,0x00,0x00,0x00,
-0x83,0x00,0x00,0x00,0x75,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x87,0x00,0x00,0x00,0x85,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x89,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x89,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x42,0x01,0x00,0x00,
-0x67,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0xda,0x00,0x00,0x00,
-0x8a,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x39,0x00,0x00,0x00,
-0x8f,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x90,0x00,0x00,0x00,
-0x8f,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x91,0x00,0x00,0x00,0x90,0x00,0x00,0x00,0x80,0x00,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x92,0x00,0x00,0x00,0x93,0x00,0x00,0x00,
-0x42,0x01,0x00,0x00,0x91,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x8b,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x93,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,
-0x8b,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x8a,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x96,0x00,0x00,0x00,
-0x42,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x98,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x75,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x99,0x00,0x00,0x00,0x96,0x00,0x00,0x00,0x98,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9e,0x00,0x00,0x00,
-0x71,0x00,0x00,0x00,0x90,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,0x9e,0x00,0x00,0x00,
-0x99,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa1,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa4,0x00,0x00,0x00,
-0x99,0x00,0x00,0x00,0x25,0x00,0x00,0x00,0x86,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,0xa4,0x00,0x00,0x00,
-0x25,0x00,0x00,0x00,0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xaa,0x00,0x00,0x00,0x99,0x00,0x00,0x00,0xa4,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xae,0x00,0x00,0x00,
-0x29,0x01,0x00,0x00,0x25,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x36,0x01,0x00,0x00,0xae,0x00,0x00,0x00,
-0xa1,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x1f,0x00,0x00,0x00,
-0x37,0x01,0x00,0x00,0x19,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x36,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x38,0x01,0x00,0x00,0x37,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x3c,0x01,0x00,0x00,0x36,0x01,0x00,0x00,
-0x25,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x1f,0x00,0x00,0x00,
-0x3d,0x01,0x00,0x00,0x19,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x3c,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x3e,0x01,0x00,0x00,0x3d,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc0,0x00,0x00,0x00,0x2d,0x01,0x00,0x00,
-0xaa,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc2,0x00,0x00,0x00,0xc0,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0xc3,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,
-0xbd,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0xc2,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xb9,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,
-0xc4,0x00,0x00,0x00,0x73,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xc6,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0xc2,0x00,0x00,0x00,
-0x25,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0xc3,0x00,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0xcf,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xb9,0x00,0x00,0x00,
-0xd1,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x73,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xd2,0x00,0x00,0x00,0xd1,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xd3,0x00,0x00,0x00,
-0x3e,0x01,0x00,0x00,0xd2,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,
-0x08,0x00,0x00,0x00,0xd4,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0x38,0x01,0x00,0x00,0xc6,0x00,0x00,0x00,
-0xd3,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xd6,0x00,0x00,0x00,0x87,0x00,0x00,0x00,0x81,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0xd7,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,
-0xd4,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x87,0x00,0x00,0x00,
-0xd7,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xda,0x00,0x00,0x00,0x42,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x89,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8b,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0xdb,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xde,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xde,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x43,0x01,0x00,0x00,
-0xdd,0x00,0x00,0x00,0x8b,0x00,0x00,0x00,0xf6,0x00,0x00,0x00,
-0xe1,0x00,0x00,0x00,0xac,0x00,0x05,0x00,0x92,0x00,0x00,0x00,
-0xe4,0x00,0x00,0x00,0x43,0x01,0x00,0x00,0x67,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xe0,0x00,0x00,0x00,0xe1,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xe4,0x00,0x00,0x00,
-0xdf,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xdf,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,0x92,0x00,0x00,0x00,
-0xe7,0x00,0x00,0x00,0x75,0x00,0x00,0x00,0x43,0x01,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xe9,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xe7,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,
-0xe9,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xe8,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0x75,0x00,0x00,0x00,0x43,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x86,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0x83,0x00,0x00,0x00,
-0xed,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xef,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,0x87,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,
-0xf1,0x00,0x00,0x00,0xef,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x87,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe9,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xe9,0x00,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0xdb,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xe1,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe1,0x00,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf6,0x00,0x00,0x00,0x43,0x01,0x00,0x00,
-0xf4,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xde,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe0,0x00,0x00,0x00,0xaa,0x00,0x05,0x00,
-0x92,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,0x75,0x00,0x00,0x00,
-0x67,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0xfa,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xf8,0x00,0x00,0x00,
-0xf9,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf9,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x01,0x01,0x00,0x00,0x31,0x01,0x00,0x00,0x71,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x86,0x00,0x00,0x00,0x02,0x01,0x00,0x00,
-0x83,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x03,0x01,0x00,0x00,0x02,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0x1f,0x00,0x00,0x00,0x04,0x01,0x00,0x00,
-0xfe,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x01,0x01,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x04,0x01,0x00,0x00,0x03,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xfa,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xfa,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t mul_mat_vec_f32_f16_f32_len = 3684;
-
-unsigned char mul_mat_vec_f32_f32_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x40,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0e,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x2f,0x00,0x00,0x00,0x37,0x00,0x00,0x00,
-0x66,0x00,0x00,0x00,0x6a,0x00,0x00,0x00,0x73,0x00,0x00,0x00,
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-0x37,0x00,0x00,0x00,0x4a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x1a,0x01,0x00,0x00,0x19,0x01,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1b,0x01,0x00,0x00,
-0x13,0x01,0x00,0x00,0x1a,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x39,0x00,0x00,0x00,0x1d,0x01,0x00,0x00,0x37,0x00,0x00,0x00,
-0x50,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x1e,0x01,0x00,0x00,0x1d,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x1f,0x01,0x00,0x00,0x17,0x01,0x00,0x00,
-0x1e,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x21,0x01,0x00,0x00,0x1f,0x01,0x00,0x00,0x1b,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x39,0x00,0x00,0x00,0x23,0x01,0x00,0x00,
-0x37,0x00,0x00,0x00,0x57,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x24,0x01,0x00,0x00,0x23,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x25,0x01,0x00,0x00,
-0x21,0x01,0x00,0x00,0x24,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x39,0x00,0x00,0x00,0x27,0x01,0x00,0x00,0x37,0x00,0x00,0x00,
-0x5c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x28,0x01,0x00,0x00,0x27,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x29,0x01,0x00,0x00,0x0b,0x01,0x00,0x00,
-0x28,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x39,0x00,0x00,0x00,
-0x2b,0x01,0x00,0x00,0x37,0x00,0x00,0x00,0x61,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x2c,0x01,0x00,0x00,
-0x2b,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x2d,0x01,0x00,0x00,0x0b,0x01,0x00,0x00,0x2c,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x86,0x00,0x00,0x00,0x87,0x00,0x00,0x00,
-0x83,0x00,0x00,0x00,0x75,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x87,0x00,0x00,0x00,0x85,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x89,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x89,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x3e,0x01,0x00,0x00,
-0x67,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,
-0x8a,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x39,0x00,0x00,0x00,
-0x8f,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x90,0x00,0x00,0x00,
-0x8f,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x91,0x00,0x00,0x00,0x90,0x00,0x00,0x00,0x80,0x00,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x92,0x00,0x00,0x00,0x93,0x00,0x00,0x00,
-0x3e,0x01,0x00,0x00,0x91,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x8b,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x93,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,
-0x8b,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x8a,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x96,0x00,0x00,0x00,
-0x3e,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x98,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x75,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x99,0x00,0x00,0x00,0x96,0x00,0x00,0x00,0x98,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9e,0x00,0x00,0x00,
-0x71,0x00,0x00,0x00,0x90,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,0x9e,0x00,0x00,0x00,
-0x99,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa1,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa4,0x00,0x00,0x00,
-0x99,0x00,0x00,0x00,0x25,0x00,0x00,0x00,0x86,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,0xa4,0x00,0x00,0x00,
-0x25,0x00,0x00,0x00,0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xaa,0x00,0x00,0x00,0x99,0x00,0x00,0x00,0xa4,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xae,0x00,0x00,0x00,
-0x25,0x01,0x00,0x00,0x25,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x32,0x01,0x00,0x00,0xae,0x00,0x00,0x00,
-0xa1,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x1f,0x00,0x00,0x00,
-0x33,0x01,0x00,0x00,0x19,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x32,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x34,0x01,0x00,0x00,0x33,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x38,0x01,0x00,0x00,0x32,0x01,0x00,0x00,
-0x25,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x1f,0x00,0x00,0x00,
-0x39,0x01,0x00,0x00,0x19,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x38,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x3a,0x01,0x00,0x00,0x39,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0x29,0x01,0x00,0x00,
-0xaa,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc1,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x1f,0x00,0x00,0x00,0xc2,0x00,0x00,0x00,
-0xbc,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0xc1,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,
-0xc2,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xcc,0x00,0x00,0x00,0xc1,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x1f,0x00,0x00,0x00,0xcd,0x00,0x00,0x00,
-0xbc,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xce,0x00,0x00,0x00,
-0xcd,0x00,0x00,0x00,0x85,0x00,0x05,0x00,0x08,0x00,0x00,0x00,
-0xcf,0x00,0x00,0x00,0x3a,0x01,0x00,0x00,0xce,0x00,0x00,0x00,
-0x0c,0x00,0x08,0x00,0x08,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x34,0x01,0x00,0x00,
-0xc3,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xd2,0x00,0x00,0x00,0x87,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xd3,0x00,0x00,0x00,
-0xd2,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x87,0x00,0x00,0x00,0xd3,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,0x3e,0x01,0x00,0x00,
-0x6d,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x89,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x8b,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x6d,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0xd7,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xda,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xda,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x3f,0x01,0x00,0x00,0xd9,0x00,0x00,0x00,0x8b,0x00,0x00,0x00,
-0xf2,0x00,0x00,0x00,0xdd,0x00,0x00,0x00,0xac,0x00,0x05,0x00,
-0x92,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,0x3f,0x01,0x00,0x00,
-0x67,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xdc,0x00,0x00,0x00,
-0xdd,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xe0,0x00,0x00,0x00,0xdb,0x00,0x00,0x00,0xdc,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xdb,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x92,0x00,0x00,0x00,0xe3,0x00,0x00,0x00,0x75,0x00,0x00,0x00,
-0x3f,0x01,0x00,0x00,0xf7,0x00,0x03,0x00,0xe5,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xe3,0x00,0x00,0x00,
-0xe4,0x00,0x00,0x00,0xe5,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe4,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe9,0x00,0x00,0x00,0x75,0x00,0x00,0x00,0x3f,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x86,0x00,0x00,0x00,0xea,0x00,0x00,0x00,
-0x83,0x00,0x00,0x00,0xe9,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,0xea,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0x87,0x00,0x00,0x00,0x81,0x00,0x05,0x00,0x08,0x00,0x00,0x00,
-0xee,0x00,0x00,0x00,0xed,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x87,0x00,0x00,0x00,0xee,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe5,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe5,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0xd7,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xdd,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xdd,0x00,0x00,0x00,
-0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,
-0x3f,0x01,0x00,0x00,0xf0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xda,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xdc,0x00,0x00,0x00,
-0xaa,0x00,0x05,0x00,0x92,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,
-0x75,0x00,0x00,0x00,0x67,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xf6,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xf4,0x00,0x00,0x00,0xf5,0x00,0x00,0x00,0xf6,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf5,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,0x2d,0x01,0x00,0x00,
-0x71,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x86,0x00,0x00,0x00,
-0xfe,0x00,0x00,0x00,0x83,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xff,0x00,0x00,0x00,
-0xfe,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x1f,0x00,0x00,0x00,
-0x00,0x01,0x00,0x00,0xfa,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0xfd,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x00,0x01,0x00,0x00,
-0xff,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xf6,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf6,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_f32_f32_f32_len = 3616;
-
-unsigned char mul_mat_vec_id_f16_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x22,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x43,0x00,0x00,0x00,
-0x58,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,0x65,0x00,0x00,0x00,
-0x75,0x00,0x00,0x00,0xae,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x17,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x18,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x18,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x18,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
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-0x06,0x00,0x00,0x00,0x06,0x01,0x00,0x00,0xfa,0x00,0x00,0x00,
-0x05,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x45,0x00,0x00,0x00,
-0x07,0x01,0x00,0x00,0x43,0x00,0x00,0x00,0x4e,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x08,0x01,0x00,0x00,
-0x07,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x09,0x01,0x00,0x00,0x06,0x01,0x00,0x00,0x08,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x45,0x00,0x00,0x00,0x0b,0x01,0x00,0x00,
-0x43,0x00,0x00,0x00,0x53,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x0c,0x01,0x00,0x00,0x0b,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x0d,0x01,0x00,0x00,
-0xfa,0x00,0x00,0x00,0x0c,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x78,0x00,0x00,0x00,0x79,0x00,0x00,0x00,0x75,0x00,0x00,0x00,
-0x67,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x79,0x00,0x00,0x00,
-0x77,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x7b,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7b,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x20,0x01,0x00,0x00,0x59,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0xc9,0x00,0x00,0x00,0x7c,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x45,0x00,0x00,0x00,0x81,0x00,0x00,0x00,
-0x43,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x82,0x00,0x00,0x00,0x81,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x83,0x00,0x00,0x00,
-0x82,0x00,0x00,0x00,0x72,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x84,0x00,0x00,0x00,0x85,0x00,0x00,0x00,0x20,0x01,0x00,0x00,
-0x83,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x7d,0x00,0x00,0x00,
-0x7c,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x85,0x00,0x00,0x00,0x7c,0x00,0x00,0x00,0x7d,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7c,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x88,0x00,0x00,0x00,0x20,0x01,0x00,0x00,
-0x72,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8a,0x00,0x00,0x00,0x5f,0x00,0x00,0x00,0x67,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8b,0x00,0x00,0x00,
-0x88,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x90,0x00,0x00,0x00,0x63,0x00,0x00,0x00,
-0x82,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x92,0x00,0x00,0x00,0x90,0x00,0x00,0x00,0x8b,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x93,0x00,0x00,0x00,
-0x92,0x00,0x00,0x00,0x27,0x00,0x00,0x00,0x89,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x96,0x00,0x00,0x00,0x8b,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x97,0x00,0x00,0x00,0x96,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,
-0x8b,0x00,0x00,0x00,0x96,0x00,0x00,0x00,0x86,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,0x02,0x01,0x00,0x00,
-0x27,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x12,0x01,0x00,0x00,0xa0,0x00,0x00,0x00,0x93,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x20,0x00,0x00,0x00,0x13,0x01,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x12,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,0x14,0x01,0x00,0x00,
-0x13,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x15,0x01,0x00,0x00,0x14,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x19,0x01,0x00,0x00,0x12,0x01,0x00,0x00,
-0x27,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x20,0x00,0x00,0x00,
-0x1a,0x01,0x00,0x00,0x1a,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x19,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x1b,0x01,0x00,0x00,0x1a,0x01,0x00,0x00,0x73,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x1c,0x01,0x00,0x00,0x1b,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb1,0x00,0x00,0x00,
-0x09,0x01,0x00,0x00,0x9c,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb3,0x00,0x00,0x00,0xb1,0x00,0x00,0x00,
-0x97,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0xb4,0x00,0x00,0x00,
-0xb5,0x00,0x00,0x00,0xae,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0xb3,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xb6,0x00,0x00,0x00,0xb5,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0xb3,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0xb4,0x00,0x00,0x00,
-0xc0,0x00,0x00,0x00,0xae,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0xbf,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xc1,0x00,0x00,0x00,0xc0,0x00,0x00,0x00,0x85,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0xc2,0x00,0x00,0x00,0x1c,0x01,0x00,0x00,
-0xc1,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,0x08,0x00,0x00,0x00,
-0xc3,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x15,0x01,0x00,0x00,0xb6,0x00,0x00,0x00,0xc2,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,
-0x79,0x00,0x00,0x00,0x81,0x00,0x05,0x00,0x08,0x00,0x00,0x00,
-0xc6,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x79,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc9,0x00,0x00,0x00,
-0x20,0x01,0x00,0x00,0x5f,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x7b,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x7d,0x00,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x5f,0x00,0x00,0x00,0x5f,0x00,0x00,0x00,
-0xca,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xcd,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xcd,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x21,0x01,0x00,0x00,0xcc,0x00,0x00,0x00,
-0x7d,0x00,0x00,0x00,0xe5,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xac,0x00,0x05,0x00,0x84,0x00,0x00,0x00,0xd3,0x00,0x00,0x00,
-0x21,0x01,0x00,0x00,0x59,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xcf,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xd3,0x00,0x00,0x00,0xce,0x00,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xce,0x00,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x84,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,
-0x67,0x00,0x00,0x00,0x21,0x01,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xd8,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xd6,0x00,0x00,0x00,0xd7,0x00,0x00,0x00,0xd8,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd7,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xdc,0x00,0x00,0x00,0x67,0x00,0x00,0x00,
-0x21,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x78,0x00,0x00,0x00,
-0xdd,0x00,0x00,0x00,0x75,0x00,0x00,0x00,0xdc,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xde,0x00,0x00,0x00,
-0xdd,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xe0,0x00,0x00,0x00,0x79,0x00,0x00,0x00,0x81,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0xe1,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,
-0xde,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x79,0x00,0x00,0x00,
-0xe1,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xd8,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd8,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x5f,0x00,0x00,0x00,0x5f,0x00,0x00,0x00,0xca,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xd0,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd0,0x00,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe5,0x00,0x00,0x00,0x21,0x01,0x00,0x00,0xe3,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xcd,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xcf,0x00,0x00,0x00,0xaa,0x00,0x05,0x00,0x84,0x00,0x00,0x00,
-0xe7,0x00,0x00,0x00,0x67,0x00,0x00,0x00,0x59,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xe9,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xe7,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,
-0xe9,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xe8,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,
-0x0d,0x01,0x00,0x00,0x63,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x78,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,0x75,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xf2,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0xb4,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xf3,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe9,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xe9,0x00,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_id_f16_f32_len = 3608;
-
-unsigned char mul_mat_vec_id_f32_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x1c,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x2f,0x00,0x00,0x00,0x37,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x55,0x00,0x00,0x00,0x59,0x00,0x00,0x00,
-0x62,0x00,0x00,0x00,0x72,0x00,0x00,0x00,0xab,0x00,0x00,0x00,
-0xe9,0x00,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x17,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x17,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x19,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x19,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x2f,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x34,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x35,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x35,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x35,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x37,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x37,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
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-0xf8,0x00,0x02,0x00,0x78,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x1a,0x01,0x00,0x00,0x56,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0x79,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x42,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x7f,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x80,0x00,0x00,0x00,
-0x7f,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x81,0x00,0x00,0x00,0x82,0x00,0x00,0x00,0x1a,0x01,0x00,0x00,
-0x80,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x7a,0x00,0x00,0x00,
-0x79,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x82,0x00,0x00,0x00,0x79,0x00,0x00,0x00,0x7a,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x79,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x85,0x00,0x00,0x00,0x1a,0x01,0x00,0x00,
-0x6f,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x87,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,0x64,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x88,0x00,0x00,0x00,
-0x85,0x00,0x00,0x00,0x87,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8d,0x00,0x00,0x00,0x60,0x00,0x00,0x00,
-0x7f,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8f,0x00,0x00,0x00,0x8d,0x00,0x00,0x00,0x88,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x90,0x00,0x00,0x00,
-0x8f,0x00,0x00,0x00,0x25,0x00,0x00,0x00,0x89,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x93,0x00,0x00,0x00,0x88,0x00,0x00,0x00,
-0x25,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x94,0x00,0x00,0x00,0x93,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x99,0x00,0x00,0x00,
-0x88,0x00,0x00,0x00,0x93,0x00,0x00,0x00,0x86,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,
-0x25,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x0e,0x01,0x00,0x00,0x9d,0x00,0x00,0x00,0x90,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x1f,0x00,0x00,0x00,0x0f,0x01,0x00,0x00,
-0x19,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x0e,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x10,0x01,0x00,0x00,
-0x0f,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x14,0x01,0x00,0x00,0x0e,0x01,0x00,0x00,0x25,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x1f,0x00,0x00,0x00,0x15,0x01,0x00,0x00,
-0x19,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x14,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x16,0x01,0x00,0x00,
-0x15,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xae,0x00,0x00,0x00,0x05,0x01,0x00,0x00,0x99,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb0,0x00,0x00,0x00,
-0xae,0x00,0x00,0x00,0x94,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x1f,0x00,0x00,0x00,0xb1,0x00,0x00,0x00,0xab,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0xb0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xb2,0x00,0x00,0x00,0xb1,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,
-0xb0,0x00,0x00,0x00,0x25,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x1f,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0xab,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,
-0x16,0x01,0x00,0x00,0xbd,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,
-0x08,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0x10,0x01,0x00,0x00,0xb2,0x00,0x00,0x00,
-0xbe,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xc1,0x00,0x00,0x00,0x76,0x00,0x00,0x00,0x81,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0xc2,0x00,0x00,0x00,0xc1,0x00,0x00,0x00,
-0xbf,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x76,0x00,0x00,0x00,
-0xc2,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc5,0x00,0x00,0x00,0x1a,0x01,0x00,0x00,0x5c,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x78,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7a,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,0x5c,0x00,0x00,0x00,
-0x5c,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xc9,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xc9,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x1b,0x01,0x00,0x00,
-0xc8,0x00,0x00,0x00,0x7a,0x00,0x00,0x00,0xe1,0x00,0x00,0x00,
-0xcc,0x00,0x00,0x00,0xac,0x00,0x05,0x00,0x81,0x00,0x00,0x00,
-0xcf,0x00,0x00,0x00,0x1b,0x01,0x00,0x00,0x56,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xcb,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xcf,0x00,0x00,0x00,
-0xca,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xca,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,0x81,0x00,0x00,0x00,
-0xd2,0x00,0x00,0x00,0x64,0x00,0x00,0x00,0x1b,0x01,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xd4,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xd2,0x00,0x00,0x00,0xd3,0x00,0x00,0x00,
-0xd4,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xd3,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd8,0x00,0x00,0x00,
-0x64,0x00,0x00,0x00,0x1b,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x75,0x00,0x00,0x00,0xd9,0x00,0x00,0x00,0x72,0x00,0x00,0x00,
-0xd8,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xda,0x00,0x00,0x00,0xd9,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xdc,0x00,0x00,0x00,0x76,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xdd,0x00,0x00,0x00,
-0xdc,0x00,0x00,0x00,0xda,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x76,0x00,0x00,0x00,0xdd,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xd4,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xd4,0x00,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x5c,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,
-0xc6,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xcc,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xcc,0x00,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe1,0x00,0x00,0x00,0x1b,0x01,0x00,0x00,
-0xdf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xc9,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xcb,0x00,0x00,0x00,0xaa,0x00,0x05,0x00,
-0x81,0x00,0x00,0x00,0xe3,0x00,0x00,0x00,0x64,0x00,0x00,0x00,
-0x56,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0xe5,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xe3,0x00,0x00,0x00,
-0xe4,0x00,0x00,0x00,0xe5,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe4,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xec,0x00,0x00,0x00,0x09,0x01,0x00,0x00,0x60,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x75,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0x72,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x1f,0x00,0x00,0x00,0xef,0x00,0x00,0x00,
-0xe9,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0xec,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xef,0x00,0x00,0x00,0xee,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe5,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe5,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t mul_mat_vec_id_f32_f32_len = 3540;
-
-unsigned char mul_mat_vec_id_q2_k_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x1b,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x5d,0x00,0x00,0x00,
-0x83,0x00,0x00,0x00,0xa8,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,
-0xf2,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x18,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x19,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x19,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x23,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x23,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x23,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x23,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x23,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x3a,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x5d,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x9f,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xa1,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
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-0x83,0x00,0x00,0x00,0xe2,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x80,0x00,0x00,0x00,0xe4,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x8a,0x00,0x00,0x00,0xe5,0x02,0x00,0x00,
-0x83,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x80,0x00,0x00,0x00,0xe6,0x02,0x00,0x00,0xe5,0x02,0x00,0x00,
-0x81,0x00,0x05,0x00,0x80,0x00,0x00,0x00,0xe7,0x02,0x00,0x00,
-0xe6,0x02,0x00,0x00,0xe4,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xe5,0x02,0x00,0x00,0xe7,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xde,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xde,0x02,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x41,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0xd1,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xd6,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd6,0x02,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xea,0x02,0x00,0x00,0x13,0x03,0x00,0x00,
-0xe1,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xd3,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd5,0x02,0x00,0x00,0xaa,0x00,0x05,0x00,
-0x95,0x00,0x00,0x00,0xec,0x02,0x00,0x00,0x60,0x00,0x00,0x00,
-0x3b,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0xee,0x02,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xec,0x02,0x00,0x00,
-0xed,0x02,0x00,0x00,0xee,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xed,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf5,0x02,0x00,0x00,0x11,0x03,0x00,0x00,0x45,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x8a,0x00,0x00,0x00,0xf6,0x02,0x00,0x00,
-0x83,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x80,0x00,0x00,0x00,0xf7,0x02,0x00,0x00,0xf6,0x02,0x00,0x00,
-0x41,0x00,0x06,0x00,0xcd,0x00,0x00,0x00,0xf8,0x02,0x00,0x00,
-0xf2,0x02,0x00,0x00,0x1c,0x00,0x00,0x00,0xf5,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xf8,0x02,0x00,0x00,0xf7,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xee,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xee,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t mul_mat_vec_id_q2_k_f32_len = 8412;
-
-unsigned char mul_mat_vec_id_q3_k_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x63,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x5d,0x00,0x00,0x00,
-0x8b,0x00,0x00,0x00,0xb3,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,
-0x3e,0x03,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x18,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x19,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x19,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x23,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x23,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x23,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x23,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x23,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x3a,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x5d,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xa9,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xab,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xad,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xaf,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xaf,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0xaf,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xaf,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x6c,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xb0,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0xb1,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0xb1,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0xb1,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xb3,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xb3,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xc5,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0xc6,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0xc6,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0xc6,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xc8,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xc8,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x3b,0x03,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x3c,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x3c,0x03,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x3c,0x03,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x3e,0x03,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x3e,0x03,0x00,0x00,0x21,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x45,0x03,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0x0f,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x10,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x10,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x17,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x18,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x19,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x1a,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x17,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x1e,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x17,0x00,0x00,0x00,
-0x1e,0x00,0x0b,0x00,0x23,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x24,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x24,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x17,0x00,0x00,0x00,
-0x26,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x27,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x17,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x17,0x00,0x00,0x00,
-0x30,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x17,0x00,0x00,0x00,0x35,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x10,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x3b,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x10,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x53,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x10,0x00,0x00,0x00,0x5d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x67,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x6e,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x17,0x00,0x00,0x00,0x71,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x72,0x00,0x00,0x00,
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-0xee,0x00,0x00,0x00,0x6f,0x00,0x04,0x00,0x88,0x00,0x00,0x00,
-0xe7,0x02,0x00,0x00,0xe6,0x02,0x00,0x00,0x85,0x00,0x05,0x00,
-0x88,0x00,0x00,0x00,0xe8,0x02,0x00,0x00,0xcb,0x02,0x00,0x00,
-0xe7,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x6e,0x00,0x00,0x00,
-0xf2,0x02,0x00,0x00,0x14,0x02,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x6e,0x00,0x00,0x00,0xf3,0x02,0x00,0x00,0xf2,0x02,0x00,0x00,
-0xab,0x01,0x00,0x00,0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xf4,0x02,0x00,0x00,0xf3,0x02,0x00,0x00,0x7c,0x00,0x04,0x00,
-0x17,0x00,0x00,0x00,0xf5,0x02,0x00,0x00,0xf4,0x02,0x00,0x00,
-0xc7,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0xf6,0x02,0x00,0x00,
-0xf5,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x6e,0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x21,0x02,0x00,0x00,
-0xc7,0x00,0x05,0x00,0x6e,0x00,0x00,0x00,0x03,0x03,0x00,0x00,
-0x00,0x03,0x00,0x00,0xdc,0x01,0x00,0x00,0x71,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x04,0x03,0x00,0x00,0x03,0x03,0x00,0x00,
-0x7c,0x00,0x04,0x00,0x17,0x00,0x00,0x00,0x05,0x03,0x00,0x00,
-0x04,0x03,0x00,0x00,0xab,0x00,0x05,0x00,0xa0,0x00,0x00,0x00,
-0x06,0x03,0x00,0x00,0x05,0x03,0x00,0x00,0x1c,0x00,0x00,0x00,
-0xa9,0x00,0x06,0x00,0x17,0x00,0x00,0x00,0x07,0x03,0x00,0x00,
-0x06,0x03,0x00,0x00,0x1c,0x00,0x00,0x00,0x26,0x00,0x00,0x00,
-0x82,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x08,0x03,0x00,0x00,
-0xf6,0x02,0x00,0x00,0x07,0x03,0x00,0x00,0x6f,0x00,0x04,0x00,
-0x88,0x00,0x00,0x00,0x09,0x03,0x00,0x00,0x08,0x03,0x00,0x00,
-0x0c,0x00,0x08,0x00,0x88,0x00,0x00,0x00,0x0b,0x03,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0xe8,0x02,0x00,0x00,
-0x09,0x03,0x00,0x00,0xc1,0x02,0x00,0x00,0x81,0x00,0x05,0x00,
-0x88,0x00,0x00,0x00,0x0d,0x03,0x00,0x00,0x62,0x03,0x00,0x00,
-0x0b,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x0f,0x03,0x00,0x00,0x61,0x03,0x00,0x00,0x71,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xbe,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xc0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x88,0x00,0x00,0x00,
-0x18,0x03,0x00,0x00,0x93,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,
-0x88,0x00,0x00,0x00,0x19,0x03,0x00,0x00,0x01,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0xba,0x00,0x00,0x00,0x62,0x03,0x00,0x00,
-0x18,0x03,0x00,0x00,0x3e,0x00,0x03,0x00,0x93,0x00,0x00,0x00,
-0x19,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0x9c,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x9c,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x1c,0x03,0x00,0x00,0x5e,0x03,0x00,0x00,
-0x41,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x99,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x9b,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x41,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0x1d,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x1f,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x1f,0x03,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x5f,0x03,0x00,0x00,0x8c,0x00,0x00,0x00,0x9b,0x00,0x00,0x00,
-0x36,0x03,0x00,0x00,0x22,0x03,0x00,0x00,0xac,0x00,0x05,0x00,
-0xa0,0x00,0x00,0x00,0x25,0x03,0x00,0x00,0x5f,0x03,0x00,0x00,
-0x3b,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x21,0x03,0x00,0x00,
-0x22,0x03,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x25,0x03,0x00,0x00,0x20,0x03,0x00,0x00,0x21,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x20,0x03,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xa0,0x00,0x00,0x00,0x28,0x03,0x00,0x00,0x60,0x00,0x00,0x00,
-0x5f,0x03,0x00,0x00,0xf7,0x00,0x03,0x00,0x2a,0x03,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x28,0x03,0x00,0x00,
-0x29,0x03,0x00,0x00,0x2a,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x29,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x2e,0x03,0x00,0x00,0x60,0x00,0x00,0x00,0x5f,0x03,0x00,0x00,
-0x41,0x00,0x05,0x00,0x92,0x00,0x00,0x00,0x2f,0x03,0x00,0x00,
-0x8b,0x00,0x00,0x00,0x2e,0x03,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x88,0x00,0x00,0x00,0x30,0x03,0x00,0x00,0x2f,0x03,0x00,0x00,
-0x41,0x00,0x05,0x00,0x92,0x00,0x00,0x00,0x31,0x03,0x00,0x00,
-0x8b,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x88,0x00,0x00,0x00,0x32,0x03,0x00,0x00,0x31,0x03,0x00,0x00,
-0x81,0x00,0x05,0x00,0x88,0x00,0x00,0x00,0x33,0x03,0x00,0x00,
-0x32,0x03,0x00,0x00,0x30,0x03,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x31,0x03,0x00,0x00,0x33,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x2a,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x2a,0x03,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x41,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0x1d,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0x22,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x22,0x03,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x36,0x03,0x00,0x00,0x5f,0x03,0x00,0x00,
-0x71,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x1f,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x21,0x03,0x00,0x00,0xaa,0x00,0x05,0x00,
-0xa0,0x00,0x00,0x00,0x38,0x03,0x00,0x00,0x60,0x00,0x00,0x00,
-0x3b,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x3a,0x03,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x38,0x03,0x00,0x00,
-0x39,0x03,0x00,0x00,0x3a,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x39,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x41,0x03,0x00,0x00,0x5d,0x03,0x00,0x00,0x45,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x92,0x00,0x00,0x00,0x42,0x03,0x00,0x00,
-0x8b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x88,0x00,0x00,0x00,0x43,0x03,0x00,0x00,0x42,0x03,0x00,0x00,
-0x41,0x00,0x06,0x00,0xd0,0x00,0x00,0x00,0x44,0x03,0x00,0x00,
-0x3e,0x03,0x00,0x00,0x1c,0x00,0x00,0x00,0x41,0x03,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x44,0x03,0x00,0x00,0x43,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x3a,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x3a,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t mul_mat_vec_id_q3_k_f32_len = 10020;
-
-unsigned char mul_mat_vec_id_q4_0_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x44,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x47,0x00,0x00,0x00,
-0x50,0x00,0x00,0x00,0x59,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x71,0x00,0x00,0x00,0x7a,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,
-0xc3,0x00,0x00,0x00,0x01,0x01,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x1b,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1c,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1d,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x1e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x1e,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x20,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x20,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x47,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4d,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x4e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4e,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x4e,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x50,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x50,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x57,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x57,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x57,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x57,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x57,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x6d,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x71,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x7a,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x87,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xc0,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xc1,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xc1,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xc3,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xfe,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xff,0x00,0x00,0x00,
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-0x87,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9f,0x00,0x00,0x00,0x74,0x00,0x00,0x00,0x7c,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,
-0x9d,0x00,0x00,0x00,0x9f,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,0x78,0x00,0x00,0x00,
-0x97,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa7,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa9,0x00,0x00,0x00,
-0xa7,0x00,0x00,0x00,0xa8,0x00,0x00,0x00,0x89,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xac,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,
-0xa8,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xad,0x00,0x00,0x00,0xac,0x00,0x00,0x00,0x74,0x00,0x00,0x00,
-0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb2,0x00,0x00,0x00,
-0xa0,0x00,0x00,0x00,0xac,0x00,0x00,0x00,0x86,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb6,0x00,0x00,0x00,0x16,0x01,0x00,0x00,
-0xa8,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x28,0x01,0x00,0x00,0xb6,0x00,0x00,0x00,0xa9,0x00,0x00,0x00,
-0x41,0x00,0x07,0x00,0x26,0x00,0x00,0x00,0x29,0x01,0x00,0x00,
-0x20,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x28,0x01,0x00,0x00,
-0x22,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x18,0x00,0x00,0x00,
-0x2a,0x01,0x00,0x00,0x29,0x01,0x00,0x00,0x73,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x2b,0x01,0x00,0x00,0x2a,0x01,0x00,0x00,
-0x41,0x00,0x08,0x00,0x30,0x00,0x00,0x00,0x30,0x01,0x00,0x00,
-0x20,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x28,0x01,0x00,0x00,
-0x2e,0x00,0x00,0x00,0xad,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x19,0x00,0x00,0x00,0x31,0x01,0x00,0x00,0x30,0x01,0x00,0x00,
-0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x32,0x01,0x00,0x00,
-0x31,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x34,0x01,0x00,0x00,0x32,0x01,0x00,0x00,0x35,0x00,0x00,0x00,
-0x70,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x35,0x01,0x00,0x00,
-0x34,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x37,0x01,0x00,0x00,0x32,0x01,0x00,0x00,0x39,0x00,0x00,0x00,
-0x70,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x38,0x01,0x00,0x00,
-0x37,0x01,0x00,0x00,0x50,0x00,0x05,0x00,0x09,0x00,0x00,0x00,
-0x39,0x01,0x00,0x00,0x35,0x01,0x00,0x00,0x38,0x01,0x00,0x00,
-0x83,0x00,0x05,0x00,0x09,0x00,0x00,0x00,0x3b,0x01,0x00,0x00,
-0x39,0x01,0x00,0x00,0x43,0x01,0x00,0x00,0x8e,0x00,0x05,0x00,
-0x09,0x00,0x00,0x00,0x3d,0x01,0x00,0x00,0x3b,0x01,0x00,0x00,
-0x2b,0x01,0x00,0x00,0x51,0x00,0x05,0x00,0x08,0x00,0x00,0x00,
-0xbf,0x00,0x00,0x00,0x3d,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,
-0x1d,0x01,0x00,0x00,0xb2,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,
-0xad,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0xc9,0x00,0x00,0x00,
-0xca,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0xc8,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xcb,0x00,0x00,0x00,0xca,0x00,0x00,0x00,0x51,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0xce,0x00,0x00,0x00,0x3d,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd4,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0xc9,0x00,0x00,0x00,0xd5,0x00,0x00,0x00,
-0xc3,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0xd4,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,
-0xd5,0x00,0x00,0x00,0x85,0x00,0x05,0x00,0x08,0x00,0x00,0x00,
-0xd7,0x00,0x00,0x00,0xce,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,
-0x0c,0x00,0x08,0x00,0x08,0x00,0x00,0x00,0xd8,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,
-0xcb,0x00,0x00,0x00,0xd7,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xda,0x00,0x00,0x00,0x8e,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xdb,0x00,0x00,0x00,
-0xda,0x00,0x00,0x00,0xd8,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x8e,0x00,0x00,0x00,0xdb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xde,0x00,0x00,0x00,0x40,0x01,0x00,0x00,
-0x74,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x90,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x92,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x74,0x00,0x00,0x00,0x74,0x00,0x00,0x00,0xdf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe2,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe2,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x41,0x01,0x00,0x00,0xe1,0x00,0x00,0x00,0x92,0x00,0x00,0x00,
-0xf9,0x00,0x00,0x00,0xe5,0x00,0x00,0x00,0xac,0x00,0x05,0x00,
-0x99,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,0x41,0x01,0x00,0x00,
-0x6e,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xe4,0x00,0x00,0x00,
-0xe5,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xe8,0x00,0x00,0x00,0xe3,0x00,0x00,0x00,0xe4,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xe3,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x99,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,0x7c,0x00,0x00,0x00,
-0x41,0x01,0x00,0x00,0xf7,0x00,0x03,0x00,0xed,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xeb,0x00,0x00,0x00,
-0xec,0x00,0x00,0x00,0xed,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xec,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf1,0x00,0x00,0x00,0x7c,0x00,0x00,0x00,0x41,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x8d,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,
-0x8a,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xf5,0x00,0x00,0x00,
-0x8e,0x00,0x00,0x00,0x81,0x00,0x05,0x00,0x08,0x00,0x00,0x00,
-0xf6,0x00,0x00,0x00,0xf5,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x8e,0x00,0x00,0x00,0xf6,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xed,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xed,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,0x74,0x00,0x00,0x00,
-0x74,0x00,0x00,0x00,0xdf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe5,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xe5,0x00,0x00,0x00,
-0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,
-0x41,0x01,0x00,0x00,0x2e,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe2,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xe4,0x00,0x00,0x00,
-0xaa,0x00,0x05,0x00,0x99,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,
-0x7c,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xfd,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xfb,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xfc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x04,0x01,0x00,0x00,0x21,0x01,0x00,0x00,
-0x78,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x8d,0x00,0x00,0x00,
-0x05,0x01,0x00,0x00,0x8a,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x06,0x01,0x00,0x00,
-0x05,0x01,0x00,0x00,0x41,0x00,0x06,0x00,0xc9,0x00,0x00,0x00,
-0x07,0x01,0x00,0x00,0x01,0x01,0x00,0x00,0x22,0x00,0x00,0x00,
-0x04,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x07,0x01,0x00,0x00,
-0x06,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0xfd,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xfd,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_id_q4_0_f32_len = 4000;
-
-unsigned char mul_mat_vec_id_q4_1_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x51,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
-0x58,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x74,0x00,0x00,0x00,
-0x78,0x00,0x00,0x00,0x81,0x00,0x00,0x00,0x91,0x00,0x00,0x00,
-0xca,0x00,0x00,0x00,0x08,0x01,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x1b,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1c,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1c,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x1d,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x1e,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x1e,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x20,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x20,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4f,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x55,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x56,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x56,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x56,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x58,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x58,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x5f,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x5f,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x5f,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x5f,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
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-0x61,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x27,0x01,0x00,0x00,0x26,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x28,0x01,0x00,0x00,
-0x15,0x01,0x00,0x00,0x27,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x94,0x00,0x00,0x00,0x95,0x00,0x00,0x00,0x91,0x00,0x00,0x00,
-0x83,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x95,0x00,0x00,0x00,
-0x93,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x97,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x97,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x4f,0x01,0x00,0x00,0x75,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0xe5,0x00,0x00,0x00,0x98,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x62,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,
-0x61,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x9e,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9f,0x00,0x00,0x00,
-0x9e,0x00,0x00,0x00,0x8e,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xa0,0x00,0x00,0x00,0xa1,0x00,0x00,0x00,0x4f,0x01,0x00,0x00,
-0x9f,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x99,0x00,0x00,0x00,
-0x98,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xa1,0x00,0x00,0x00,0x98,0x00,0x00,0x00,0x99,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x98,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa4,0x00,0x00,0x00,0x4f,0x01,0x00,0x00,
-0x8e,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa6,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,0x83,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,
-0xa4,0x00,0x00,0x00,0xa6,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xac,0x00,0x00,0x00,0x7f,0x00,0x00,0x00,
-0x9e,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xae,0x00,0x00,0x00,0xac,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb0,0x00,0x00,0x00,
-0xae,0x00,0x00,0x00,0xaf,0x00,0x00,0x00,0x89,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb3,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,
-0xaf,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb4,0x00,0x00,0x00,0xb3,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,
-0xa7,0x00,0x00,0x00,0xb3,0x00,0x00,0x00,0x86,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0x1d,0x01,0x00,0x00,
-0xaf,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x30,0x01,0x00,0x00,0xbd,0x00,0x00,0x00,0xb0,0x00,0x00,0x00,
-0x41,0x00,0x07,0x00,0x26,0x00,0x00,0x00,0x31,0x01,0x00,0x00,
-0x20,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x30,0x01,0x00,0x00,
-0x22,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x18,0x00,0x00,0x00,
-0x32,0x01,0x00,0x00,0x31,0x01,0x00,0x00,0x73,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x33,0x01,0x00,0x00,0x32,0x01,0x00,0x00,
-0x41,0x00,0x07,0x00,0x26,0x00,0x00,0x00,0x37,0x01,0x00,0x00,
-0x20,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x30,0x01,0x00,0x00,
-0x2e,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x18,0x00,0x00,0x00,
-0x38,0x01,0x00,0x00,0x37,0x01,0x00,0x00,0x73,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x39,0x01,0x00,0x00,0x38,0x01,0x00,0x00,
-0x41,0x00,0x08,0x00,0x38,0x00,0x00,0x00,0x3e,0x01,0x00,0x00,
-0x20,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x30,0x01,0x00,0x00,
-0x36,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x19,0x00,0x00,0x00,0x3f,0x01,0x00,0x00,0x3e,0x01,0x00,0x00,
-0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x40,0x01,0x00,0x00,
-0x3f,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x42,0x01,0x00,0x00,0x40,0x01,0x00,0x00,0x3d,0x00,0x00,0x00,
-0x70,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x43,0x01,0x00,0x00,
-0x42,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x45,0x01,0x00,0x00,0x40,0x01,0x00,0x00,0x41,0x00,0x00,0x00,
-0x70,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x46,0x01,0x00,0x00,
-0x45,0x01,0x00,0x00,0x50,0x00,0x05,0x00,0x09,0x00,0x00,0x00,
-0x47,0x01,0x00,0x00,0x43,0x01,0x00,0x00,0x46,0x01,0x00,0x00,
-0x8e,0x00,0x05,0x00,0x09,0x00,0x00,0x00,0x49,0x01,0x00,0x00,
-0x47,0x01,0x00,0x00,0x33,0x01,0x00,0x00,0x50,0x00,0x05,0x00,
-0x09,0x00,0x00,0x00,0x4b,0x01,0x00,0x00,0x39,0x01,0x00,0x00,
-0x39,0x01,0x00,0x00,0x81,0x00,0x05,0x00,0x09,0x00,0x00,0x00,
-0x4c,0x01,0x00,0x00,0x49,0x01,0x00,0x00,0x4b,0x01,0x00,0x00,
-0x51,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,
-0x4c,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xcd,0x00,0x00,0x00,0x24,0x01,0x00,0x00,
-0xb9,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xcd,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0xd0,0x00,0x00,0x00,0xd1,0x00,0x00,0x00,
-0xca,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xd2,0x00,0x00,0x00,
-0xd1,0x00,0x00,0x00,0x51,0x00,0x05,0x00,0x08,0x00,0x00,0x00,
-0xd5,0x00,0x00,0x00,0x4c,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdb,0x00,0x00,0x00,
-0xcf,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0xd0,0x00,0x00,0x00,0xdc,0x00,0x00,0x00,0xca,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0xdb,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xdd,0x00,0x00,0x00,0xdc,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xde,0x00,0x00,0x00,
-0xd5,0x00,0x00,0x00,0xdd,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,
-0x08,0x00,0x00,0x00,0xdf,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,0xd2,0x00,0x00,0x00,
-0xde,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xe1,0x00,0x00,0x00,0x95,0x00,0x00,0x00,0x81,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0xe2,0x00,0x00,0x00,0xe1,0x00,0x00,0x00,
-0xdf,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x95,0x00,0x00,0x00,
-0xe2,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe5,0x00,0x00,0x00,0x4f,0x01,0x00,0x00,0x7b,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x97,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x99,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,0x7b,0x00,0x00,0x00,
-0x7b,0x00,0x00,0x00,0xe6,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe9,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xe9,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x50,0x01,0x00,0x00,
-0xe8,0x00,0x00,0x00,0x99,0x00,0x00,0x00,0x00,0x01,0x00,0x00,
-0xec,0x00,0x00,0x00,0xac,0x00,0x05,0x00,0xa0,0x00,0x00,0x00,
-0xef,0x00,0x00,0x00,0x50,0x01,0x00,0x00,0x75,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xeb,0x00,0x00,0x00,0xec,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xef,0x00,0x00,0x00,
-0xea,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xea,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,0xa0,0x00,0x00,0x00,
-0xf2,0x00,0x00,0x00,0x83,0x00,0x00,0x00,0x50,0x01,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xf4,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xf2,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,
-0xf4,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xf3,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,
-0x83,0x00,0x00,0x00,0x50,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x94,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,0x91,0x00,0x00,0x00,
-0xf8,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xfa,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0x95,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,
-0xfc,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x95,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xf4,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xf4,0x00,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x7b,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0xe6,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xec,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xec,0x00,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x50,0x01,0x00,0x00,
-0x2e,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xe9,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xeb,0x00,0x00,0x00,0xaa,0x00,0x05,0x00,
-0xa0,0x00,0x00,0x00,0x02,0x01,0x00,0x00,0x83,0x00,0x00,0x00,
-0x75,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x04,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x02,0x01,0x00,0x00,
-0x03,0x01,0x00,0x00,0x04,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x03,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x0b,0x01,0x00,0x00,0x28,0x01,0x00,0x00,0x7f,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x94,0x00,0x00,0x00,0x0c,0x01,0x00,0x00,
-0x91,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x0d,0x01,0x00,0x00,0x0c,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0xd0,0x00,0x00,0x00,0x0e,0x01,0x00,0x00,
-0x08,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x0b,0x01,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x0e,0x01,0x00,0x00,0x0d,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x04,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x04,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t mul_mat_vec_id_q4_1_f32_len = 4068;
-
-unsigned char mul_mat_vec_id_q4_k_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xce,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x5d,0x00,0x00,0x00,
-0x89,0x00,0x00,0x00,0xb2,0x00,0x00,0x00,0x25,0x02,0x00,0x00,
-0xa9,0x03,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
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-0x60,0x00,0x00,0x00,0xca,0x03,0x00,0x00,0x41,0x00,0x05,0x00,
-0x90,0x00,0x00,0x00,0x9a,0x03,0x00,0x00,0x89,0x00,0x00,0x00,
-0x99,0x03,0x00,0x00,0x3d,0x00,0x04,0x00,0x86,0x00,0x00,0x00,
-0x9b,0x03,0x00,0x00,0x9a,0x03,0x00,0x00,0x41,0x00,0x05,0x00,
-0x90,0x00,0x00,0x00,0x9c,0x03,0x00,0x00,0x89,0x00,0x00,0x00,
-0x60,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x86,0x00,0x00,0x00,
-0x9d,0x03,0x00,0x00,0x9c,0x03,0x00,0x00,0x81,0x00,0x05,0x00,
-0x86,0x00,0x00,0x00,0x9e,0x03,0x00,0x00,0x9d,0x03,0x00,0x00,
-0x9b,0x03,0x00,0x00,0x3e,0x00,0x03,0x00,0x9c,0x03,0x00,0x00,
-0x9e,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0x95,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x95,0x03,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x41,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0x88,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x8d,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8d,0x03,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa1,0x03,0x00,0x00,0xca,0x03,0x00,0x00,0xc6,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x8a,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8c,0x03,0x00,0x00,0xaa,0x00,0x05,0x00,0x9b,0x00,0x00,0x00,
-0xa3,0x03,0x00,0x00,0x60,0x00,0x00,0x00,0x3b,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xa5,0x03,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xa3,0x03,0x00,0x00,0xa4,0x03,0x00,0x00,
-0xa5,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0xa4,0x03,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xac,0x03,0x00,0x00,
-0xc8,0x03,0x00,0x00,0x45,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x90,0x00,0x00,0x00,0xad,0x03,0x00,0x00,0x89,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x86,0x00,0x00,0x00,
-0xae,0x03,0x00,0x00,0xad,0x03,0x00,0x00,0x41,0x00,0x06,0x00,
-0x29,0x02,0x00,0x00,0xaf,0x03,0x00,0x00,0xa9,0x03,0x00,0x00,
-0x1c,0x00,0x00,0x00,0xac,0x03,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xaf,0x03,0x00,0x00,0xae,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa5,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0xa5,0x03,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_id_q4_k_f32_len = 9944;
-
-unsigned char mul_mat_vec_id_q5_0_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x98,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x78,0x00,0x00,0x00,
-0x80,0x00,0x00,0x00,0x89,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,
-0x9f,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0xb7,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0x2e,0x01,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x1b,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x1e,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1f,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1f,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1f,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x20,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x23,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x23,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x78,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x7d,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x7e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7e,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x7e,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x80,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x80,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x87,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x87,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x87,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x87,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x87,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x87,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x87,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x87,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x87,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x87,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x9c,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x9f,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xa7,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xb4,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xed,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xee,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xee,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xee,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xf0,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xf0,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x2b,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x2c,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x2c,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x2c,0x01,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x2e,0x01,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x2e,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x35,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x36,0x01,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0x08,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0x09,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x16,0x00,0x03,0x00,0x18,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x19,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,
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-0x15,0x00,0x04,0x00,0x1c,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
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-0x06,0x00,0x00,0x00,0x73,0x01,0x00,0x00,0x72,0x01,0x00,0x00,
-0x1d,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,0x24,0x00,0x00,0x00,
-0x74,0x01,0x00,0x00,0x73,0x01,0x00,0x00,0x41,0x00,0x08,0x00,
-0x57,0x00,0x00,0x00,0x7a,0x01,0x00,0x00,0x23,0x00,0x00,0x00,
-0x25,0x00,0x00,0x00,0x57,0x01,0x00,0x00,0x55,0x00,0x00,0x00,
-0xda,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x1c,0x00,0x00,0x00,
-0x7b,0x01,0x00,0x00,0x7a,0x01,0x00,0x00,0x71,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x7c,0x01,0x00,0x00,0x7b,0x01,0x00,0x00,
-0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x7e,0x01,0x00,0x00,
-0x7c,0x01,0x00,0x00,0x5c,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x81,0x01,0x00,0x00,0x6e,0x01,0x00,0x00,
-0xc5,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x82,0x01,0x00,0x00,
-0x7e,0x01,0x00,0x00,0x81,0x01,0x00,0x00,0x70,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x83,0x01,0x00,0x00,0x82,0x01,0x00,0x00,
-0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x85,0x01,0x00,0x00,
-0x7c,0x01,0x00,0x00,0x45,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x88,0x01,0x00,0x00,0x74,0x01,0x00,0x00,
-0xc5,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x89,0x01,0x00,0x00,
-0x85,0x01,0x00,0x00,0x88,0x01,0x00,0x00,0x70,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x8a,0x01,0x00,0x00,0x89,0x01,0x00,0x00,
-0x50,0x00,0x05,0x00,0x09,0x00,0x00,0x00,0x8b,0x01,0x00,0x00,
-0x83,0x01,0x00,0x00,0x8a,0x01,0x00,0x00,0x83,0x00,0x05,0x00,
-0x09,0x00,0x00,0x00,0x8d,0x01,0x00,0x00,0x8b,0x01,0x00,0x00,
-0x97,0x01,0x00,0x00,0x8e,0x00,0x05,0x00,0x09,0x00,0x00,0x00,
-0x8f,0x01,0x00,0x00,0x8d,0x01,0x00,0x00,0x5a,0x01,0x00,0x00,
-0x51,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xec,0x00,0x00,0x00,
-0x8f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0x4a,0x01,0x00,0x00,
-0xdf,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf5,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0xda,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0xf6,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0x25,0x00,0x00,0x00,0xf5,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,
-0xf7,0x00,0x00,0x00,0x51,0x00,0x05,0x00,0x08,0x00,0x00,0x00,
-0xfb,0x00,0x00,0x00,0x8f,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x01,0x01,0x00,0x00,
-0xf5,0x00,0x00,0x00,0x1d,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0xf6,0x00,0x00,0x00,0x02,0x01,0x00,0x00,0xf0,0x00,0x00,0x00,
-0x25,0x00,0x00,0x00,0x01,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x03,0x01,0x00,0x00,0x02,0x01,0x00,0x00,
-0x85,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0x04,0x01,0x00,0x00,
-0xfb,0x00,0x00,0x00,0x03,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,
-0x08,0x00,0x00,0x00,0x05,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0xec,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,
-0x04,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x07,0x01,0x00,0x00,0xbb,0x00,0x00,0x00,0x81,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0x08,0x01,0x00,0x00,0x07,0x01,0x00,0x00,
-0x05,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0xbb,0x00,0x00,0x00,
-0x08,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x0b,0x01,0x00,0x00,0x94,0x01,0x00,0x00,0x1a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xbd,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xbf,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x0c,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x0f,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x0f,0x01,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x95,0x01,0x00,0x00,
-0x0e,0x01,0x00,0x00,0xbf,0x00,0x00,0x00,0x26,0x01,0x00,0x00,
-0x12,0x01,0x00,0x00,0xac,0x00,0x05,0x00,0xc6,0x00,0x00,0x00,
-0x15,0x01,0x00,0x00,0x95,0x01,0x00,0x00,0x5e,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x11,0x01,0x00,0x00,0x12,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x15,0x01,0x00,0x00,
-0x10,0x01,0x00,0x00,0x11,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x10,0x01,0x00,0x00,0xb0,0x00,0x05,0x00,0xc6,0x00,0x00,0x00,
-0x18,0x01,0x00,0x00,0xa9,0x00,0x00,0x00,0x95,0x01,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x1a,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x18,0x01,0x00,0x00,0x19,0x01,0x00,0x00,
-0x1a,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x19,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1e,0x01,0x00,0x00,
-0xa9,0x00,0x00,0x00,0x95,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0xba,0x00,0x00,0x00,0x1f,0x01,0x00,0x00,0xb7,0x00,0x00,0x00,
-0x1e,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x20,0x01,0x00,0x00,0x1f,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x22,0x01,0x00,0x00,0xbb,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0x23,0x01,0x00,0x00,
-0x22,0x01,0x00,0x00,0x20,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xbb,0x00,0x00,0x00,0x23,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x1a,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x1a,0x01,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x0c,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x12,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x12,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x26,0x01,0x00,0x00,0x95,0x01,0x00,0x00,
-0x31,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x0f,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x11,0x01,0x00,0x00,0xaa,0x00,0x05,0x00,
-0xc6,0x00,0x00,0x00,0x28,0x01,0x00,0x00,0xa9,0x00,0x00,0x00,
-0x5e,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x2a,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x28,0x01,0x00,0x00,
-0x29,0x01,0x00,0x00,0x2a,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x29,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x31,0x01,0x00,0x00,0x4e,0x01,0x00,0x00,0xa5,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0xba,0x00,0x00,0x00,0x32,0x01,0x00,0x00,
-0xb7,0x00,0x00,0x00,0x25,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x33,0x01,0x00,0x00,0x32,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0xf6,0x00,0x00,0x00,0x34,0x01,0x00,0x00,
-0x2e,0x01,0x00,0x00,0x25,0x00,0x00,0x00,0x31,0x01,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x34,0x01,0x00,0x00,0x33,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x2a,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x2a,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t mul_mat_vec_id_q5_0_f32_len = 4512;
-
-unsigned char mul_mat_vec_id_q5_1_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x90,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x73,0x00,0x00,0x00,
-0x7b,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x96,0x00,0x00,0x00,
-0x99,0x00,0x00,0x00,0xa2,0x00,0x00,0x00,0xb2,0x00,0x00,0x00,
-0xeb,0x00,0x00,0x00,0x29,0x01,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x1b,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1c,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1c,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1c,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x1d,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x1e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x1e,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x20,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x20,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x73,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x78,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x79,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x79,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x79,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x7b,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x7b,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x82,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x82,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x82,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x82,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x82,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x82,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x82,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x82,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x82,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x82,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x96,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x99,0x00,0x00,0x00,
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-0x8e,0x01,0x00,0x00,0x59,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
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-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,
-0x9c,0x00,0x00,0x00,0xa4,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,
-0xc7,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xcd,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xcd,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,0x86,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd1,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,
-0xd0,0x00,0x00,0x00,0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd4,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd5,0x00,0x00,0x00,
-0xd4,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,0x82,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xda,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,
-0xd4,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xde,0x00,0x00,0x00,0x3e,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x53,0x01,0x00,0x00,
-0xde,0x00,0x00,0x00,0xd1,0x00,0x00,0x00,0x41,0x00,0x07,0x00,
-0x26,0x00,0x00,0x00,0x54,0x01,0x00,0x00,0x20,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x53,0x01,0x00,0x00,0x22,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x18,0x00,0x00,0x00,0x55,0x01,0x00,0x00,
-0x54,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x56,0x01,0x00,0x00,0x55,0x01,0x00,0x00,0x41,0x00,0x07,0x00,
-0x26,0x00,0x00,0x00,0x5a,0x01,0x00,0x00,0x20,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x53,0x01,0x00,0x00,0x2e,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x18,0x00,0x00,0x00,0x5b,0x01,0x00,0x00,
-0x5a,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x5c,0x01,0x00,0x00,0x5b,0x01,0x00,0x00,0x41,0x00,0x07,0x00,
-0x37,0x00,0x00,0x00,0x60,0x01,0x00,0x00,0x20,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x53,0x01,0x00,0x00,0x36,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x61,0x01,0x00,0x00,
-0x60,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x64,0x01,0x00,0x00,0x61,0x01,0x00,0x00,0xd5,0x00,0x00,0x00,
-0xc4,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x65,0x01,0x00,0x00,
-0x64,0x01,0x00,0x00,0x40,0x00,0x00,0x00,0xc7,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x66,0x01,0x00,0x00,0x65,0x01,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,0x21,0x00,0x00,0x00,
-0x67,0x01,0x00,0x00,0x66,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x6a,0x01,0x00,0x00,0xd5,0x00,0x00,0x00,
-0x46,0x00,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x6b,0x01,0x00,0x00,0x61,0x01,0x00,0x00,0x6a,0x01,0x00,0x00,
-0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x6c,0x01,0x00,0x00,
-0x6b,0x01,0x00,0x00,0x1a,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,
-0x21,0x00,0x00,0x00,0x6d,0x01,0x00,0x00,0x6c,0x01,0x00,0x00,
-0x41,0x00,0x08,0x00,0x52,0x00,0x00,0x00,0x73,0x01,0x00,0x00,
-0x20,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x53,0x01,0x00,0x00,
-0x50,0x00,0x00,0x00,0xd5,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x19,0x00,0x00,0x00,0x74,0x01,0x00,0x00,0x73,0x01,0x00,0x00,
-0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x75,0x01,0x00,0x00,
-0x74,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x77,0x01,0x00,0x00,0x75,0x01,0x00,0x00,0x57,0x00,0x00,0x00,
-0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x7a,0x01,0x00,0x00,
-0x67,0x01,0x00,0x00,0xc5,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x7b,0x01,0x00,0x00,0x77,0x01,0x00,0x00,0x7a,0x01,0x00,0x00,
-0x70,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x7c,0x01,0x00,0x00,
-0x7b,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x7e,0x01,0x00,0x00,0x75,0x01,0x00,0x00,0x40,0x00,0x00,0x00,
-0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x81,0x01,0x00,0x00,
-0x6d,0x01,0x00,0x00,0xc5,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x82,0x01,0x00,0x00,0x7e,0x01,0x00,0x00,0x81,0x01,0x00,0x00,
-0x70,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x83,0x01,0x00,0x00,
-0x82,0x01,0x00,0x00,0x50,0x00,0x05,0x00,0x09,0x00,0x00,0x00,
-0x84,0x01,0x00,0x00,0x7c,0x01,0x00,0x00,0x83,0x01,0x00,0x00,
-0x8e,0x00,0x05,0x00,0x09,0x00,0x00,0x00,0x86,0x01,0x00,0x00,
-0x84,0x01,0x00,0x00,0x56,0x01,0x00,0x00,0x50,0x00,0x05,0x00,
-0x09,0x00,0x00,0x00,0x88,0x01,0x00,0x00,0x5c,0x01,0x00,0x00,
-0x5c,0x01,0x00,0x00,0x81,0x00,0x05,0x00,0x09,0x00,0x00,0x00,
-0x89,0x01,0x00,0x00,0x86,0x01,0x00,0x00,0x88,0x01,0x00,0x00,
-0x51,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,
-0x89,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0x45,0x01,0x00,0x00,
-0xda,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0xd5,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0xf1,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,
-0xeb,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,
-0xf2,0x00,0x00,0x00,0x51,0x00,0x05,0x00,0x08,0x00,0x00,0x00,
-0xf6,0x00,0x00,0x00,0x89,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0xf1,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xff,0x00,0x00,0x00,
-0xf6,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,
-0x08,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,
-0xff,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x02,0x01,0x00,0x00,0xb6,0x00,0x00,0x00,0x81,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0x03,0x01,0x00,0x00,0x02,0x01,0x00,0x00,
-0x00,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0xb6,0x00,0x00,0x00,
-0x03,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x06,0x01,0x00,0x00,0x8e,0x01,0x00,0x00,0x9c,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xb8,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xba,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,0x9c,0x00,0x00,0x00,
-0x9c,0x00,0x00,0x00,0x07,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x0a,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x0a,0x01,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x8f,0x01,0x00,0x00,
-0x09,0x01,0x00,0x00,0xba,0x00,0x00,0x00,0x21,0x01,0x00,0x00,
-0x0d,0x01,0x00,0x00,0xac,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0x10,0x01,0x00,0x00,0x8f,0x01,0x00,0x00,0x59,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x0c,0x01,0x00,0x00,0x0d,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x10,0x01,0x00,0x00,
-0x0b,0x01,0x00,0x00,0x0c,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x0b,0x01,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0x13,0x01,0x00,0x00,0xa4,0x00,0x00,0x00,0x8f,0x01,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x15,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x13,0x01,0x00,0x00,0x14,0x01,0x00,0x00,
-0x15,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x14,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x19,0x01,0x00,0x00,
-0xa4,0x00,0x00,0x00,0x8f,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0xb5,0x00,0x00,0x00,0x1a,0x01,0x00,0x00,0xb2,0x00,0x00,0x00,
-0x19,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x1b,0x01,0x00,0x00,0x1a,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x1d,0x01,0x00,0x00,0xb6,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0x1e,0x01,0x00,0x00,
-0x1d,0x01,0x00,0x00,0x1b,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xb6,0x00,0x00,0x00,0x1e,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x15,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x15,0x01,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x9c,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,
-0x07,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x0d,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x0d,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x21,0x01,0x00,0x00,0x8f,0x01,0x00,0x00,
-0x2e,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x0a,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x0c,0x01,0x00,0x00,0xaa,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0x23,0x01,0x00,0x00,0xa4,0x00,0x00,0x00,
-0x59,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x25,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x23,0x01,0x00,0x00,
-0x24,0x01,0x00,0x00,0x25,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x24,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x2c,0x01,0x00,0x00,0x49,0x01,0x00,0x00,0xa0,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0xb5,0x00,0x00,0x00,0x2d,0x01,0x00,0x00,
-0xb2,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x2e,0x01,0x00,0x00,0x2d,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0xf1,0x00,0x00,0x00,0x2f,0x01,0x00,0x00,
-0x29,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x2c,0x01,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x2f,0x01,0x00,0x00,0x2e,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x25,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x25,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t mul_mat_vec_id_q5_1_f32_len = 4392;
-
-unsigned char mul_mat_vec_id_q5_k_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xb9,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
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-0x3d,0x00,0x04,0x00,0x93,0x00,0x00,0x00,0xe1,0x03,0x00,0x00,
-0x4d,0x02,0x00,0x00,0x81,0x00,0x05,0x00,0x93,0x00,0x00,0x00,
-0xe2,0x03,0x00,0x00,0xdb,0x03,0x00,0x00,0xe1,0x03,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x93,0x00,0x00,0x00,0xe8,0x03,0x00,0x00,
-0x67,0x02,0x00,0x00,0x81,0x00,0x05,0x00,0x93,0x00,0x00,0x00,
-0xe9,0x03,0x00,0x00,0xe2,0x03,0x00,0x00,0xe8,0x03,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x93,0x00,0x00,0x00,0xef,0x03,0x00,0x00,
-0x81,0x02,0x00,0x00,0x81,0x00,0x05,0x00,0x93,0x00,0x00,0x00,
-0xf0,0x03,0x00,0x00,0xe9,0x03,0x00,0x00,0xef,0x03,0x00,0x00,
-0x70,0x00,0x04,0x00,0x93,0x00,0x00,0x00,0xf2,0x03,0x00,0x00,
-0xf8,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x93,0x00,0x00,0x00,
-0xf9,0x03,0x00,0x00,0x9c,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x93,0x00,0x00,0x00,0xff,0x03,0x00,0x00,0xb6,0x02,0x00,0x00,
-0x81,0x00,0x05,0x00,0x93,0x00,0x00,0x00,0x00,0x04,0x00,0x00,
-0xf9,0x03,0x00,0x00,0xff,0x03,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x93,0x00,0x00,0x00,0x06,0x04,0x00,0x00,0xd2,0x02,0x00,0x00,
-0x81,0x00,0x05,0x00,0x93,0x00,0x00,0x00,0x07,0x04,0x00,0x00,
-0x00,0x04,0x00,0x00,0x06,0x04,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x93,0x00,0x00,0x00,0x0d,0x04,0x00,0x00,0xee,0x02,0x00,0x00,
-0x81,0x00,0x05,0x00,0x93,0x00,0x00,0x00,0x0e,0x04,0x00,0x00,
-0x07,0x04,0x00,0x00,0x0d,0x04,0x00,0x00,0x70,0x00,0x04,0x00,
-0x93,0x00,0x00,0x00,0x10,0x04,0x00,0x00,0x07,0x01,0x00,0x00,
-0x85,0x00,0x05,0x00,0x93,0x00,0x00,0x00,0x11,0x04,0x00,0x00,
-0x0e,0x04,0x00,0x00,0x10,0x04,0x00,0x00,0x0c,0x00,0x08,0x00,
-0x93,0x00,0x00,0x00,0x12,0x04,0x00,0x00,0x01,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0xf0,0x03,0x00,0x00,0xf2,0x03,0x00,0x00,
-0x11,0x04,0x00,0x00,0x3d,0x00,0x04,0x00,0x93,0x00,0x00,0x00,
-0x17,0x04,0x00,0x00,0x09,0x03,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x93,0x00,0x00,0x00,0x1d,0x04,0x00,0x00,0x21,0x03,0x00,0x00,
-0x81,0x00,0x05,0x00,0x93,0x00,0x00,0x00,0x1e,0x04,0x00,0x00,
-0x17,0x04,0x00,0x00,0x1d,0x04,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x93,0x00,0x00,0x00,0x24,0x04,0x00,0x00,0x3b,0x03,0x00,0x00,
-0x81,0x00,0x05,0x00,0x93,0x00,0x00,0x00,0x25,0x04,0x00,0x00,
-0x1e,0x04,0x00,0x00,0x24,0x04,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x93,0x00,0x00,0x00,0x2b,0x04,0x00,0x00,0x55,0x03,0x00,0x00,
-0x81,0x00,0x05,0x00,0x93,0x00,0x00,0x00,0x2c,0x04,0x00,0x00,
-0x25,0x04,0x00,0x00,0x2b,0x04,0x00,0x00,0x70,0x00,0x04,0x00,
-0x93,0x00,0x00,0x00,0x2e,0x04,0x00,0x00,0x5c,0x01,0x00,0x00,
-0x0c,0x00,0x08,0x00,0x93,0x00,0x00,0x00,0x30,0x04,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x2c,0x04,0x00,0x00,
-0x2e,0x04,0x00,0x00,0x12,0x04,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x93,0x00,0x00,0x00,0x36,0x04,0x00,0x00,0x70,0x03,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x93,0x00,0x00,0x00,0x3c,0x04,0x00,0x00,
-0x89,0x03,0x00,0x00,0x81,0x00,0x05,0x00,0x93,0x00,0x00,0x00,
-0x3d,0x04,0x00,0x00,0x36,0x04,0x00,0x00,0x3c,0x04,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x93,0x00,0x00,0x00,0x43,0x04,0x00,0x00,
-0xa4,0x03,0x00,0x00,0x81,0x00,0x05,0x00,0x93,0x00,0x00,0x00,
-0x44,0x04,0x00,0x00,0x3d,0x04,0x00,0x00,0x43,0x04,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x93,0x00,0x00,0x00,0x4a,0x04,0x00,0x00,
-0xbf,0x03,0x00,0x00,0x81,0x00,0x05,0x00,0x93,0x00,0x00,0x00,
-0x4b,0x04,0x00,0x00,0x44,0x04,0x00,0x00,0x4a,0x04,0x00,0x00,
-0x70,0x00,0x04,0x00,0x93,0x00,0x00,0x00,0x4d,0x04,0x00,0x00,
-0x78,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,0x93,0x00,0x00,0x00,
-0x4f,0x04,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x4b,0x04,0x00,0x00,0x4d,0x04,0x00,0x00,0x30,0x04,0x00,0x00,
-0x70,0x00,0x04,0x00,0x93,0x00,0x00,0x00,0x57,0x04,0x00,0x00,
-0xdc,0x00,0x00,0x00,0x70,0x00,0x04,0x00,0x93,0x00,0x00,0x00,
-0x5b,0x04,0x00,0x00,0xea,0x00,0x00,0x00,0x85,0x00,0x05,0x00,
-0x93,0x00,0x00,0x00,0x5c,0x04,0x00,0x00,0x04,0x03,0x00,0x00,
-0x5b,0x04,0x00,0x00,0x0c,0x00,0x08,0x00,0x93,0x00,0x00,0x00,
-0x5d,0x04,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x96,0x02,0x00,0x00,0x57,0x04,0x00,0x00,0x5c,0x04,0x00,0x00,
-0x70,0x00,0x04,0x00,0x93,0x00,0x00,0x00,0x60,0x04,0x00,0x00,
-0x24,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,0x93,0x00,0x00,0x00,
-0x62,0x04,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x6a,0x03,0x00,0x00,0x60,0x04,0x00,0x00,0x5d,0x04,0x00,0x00,
-0x70,0x00,0x04,0x00,0x93,0x00,0x00,0x00,0x65,0x04,0x00,0x00,
-0x40,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,0x93,0x00,0x00,0x00,
-0x67,0x04,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0xd5,0x03,0x00,0x00,0x65,0x04,0x00,0x00,0x62,0x04,0x00,0x00,
-0x85,0x00,0x05,0x00,0x93,0x00,0x00,0x00,0x6b,0x04,0x00,0x00,
-0xcd,0x00,0x00,0x00,0x4f,0x04,0x00,0x00,0x7f,0x00,0x04,0x00,
-0x93,0x00,0x00,0x00,0xb8,0x04,0x00,0x00,0x6b,0x04,0x00,0x00,
-0x0c,0x00,0x08,0x00,0x93,0x00,0x00,0x00,0x6c,0x04,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,
-0x67,0x04,0x00,0x00,0xb8,0x04,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x93,0x00,0x00,0x00,0x6e,0x04,0x00,0x00,0x9e,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x93,0x00,0x00,0x00,0x6f,0x04,0x00,0x00,
-0x6e,0x04,0x00,0x00,0x6c,0x04,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x9e,0x00,0x00,0x00,0x6f,0x04,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x72,0x04,0x00,0x00,0xb4,0x04,0x00,0x00,
-0x41,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xa1,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa3,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x41,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0x73,0x04,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x75,0x04,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x75,0x04,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xb5,0x04,0x00,0x00,0x97,0x00,0x00,0x00,0xa3,0x00,0x00,0x00,
-0x8c,0x04,0x00,0x00,0x78,0x04,0x00,0x00,0xac,0x00,0x05,0x00,
-0xa8,0x00,0x00,0x00,0x7b,0x04,0x00,0x00,0xb5,0x04,0x00,0x00,
-0x3b,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x77,0x04,0x00,0x00,
-0x78,0x04,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x7b,0x04,0x00,0x00,0x76,0x04,0x00,0x00,0x77,0x04,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x76,0x04,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xa8,0x00,0x00,0x00,0x7e,0x04,0x00,0x00,0x60,0x00,0x00,0x00,
-0xb5,0x04,0x00,0x00,0xf7,0x00,0x03,0x00,0x80,0x04,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x7e,0x04,0x00,0x00,
-0x7f,0x04,0x00,0x00,0x80,0x04,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7f,0x04,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x84,0x04,0x00,0x00,0x60,0x00,0x00,0x00,0xb5,0x04,0x00,0x00,
-0x41,0x00,0x05,0x00,0x9d,0x00,0x00,0x00,0x85,0x04,0x00,0x00,
-0x96,0x00,0x00,0x00,0x84,0x04,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x93,0x00,0x00,0x00,0x86,0x04,0x00,0x00,0x85,0x04,0x00,0x00,
-0x41,0x00,0x05,0x00,0x9d,0x00,0x00,0x00,0x87,0x04,0x00,0x00,
-0x96,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x93,0x00,0x00,0x00,0x88,0x04,0x00,0x00,0x87,0x04,0x00,0x00,
-0x81,0x00,0x05,0x00,0x93,0x00,0x00,0x00,0x89,0x04,0x00,0x00,
-0x88,0x04,0x00,0x00,0x86,0x04,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x87,0x04,0x00,0x00,0x89,0x04,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x80,0x04,0x00,0x00,0xf8,0x00,0x02,0x00,0x80,0x04,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x41,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0x73,0x04,0x00,0x00,0xf9,0x00,0x02,0x00,0x78,0x04,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x78,0x04,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8c,0x04,0x00,0x00,0xb5,0x04,0x00,0x00,
-0x89,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x75,0x04,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x77,0x04,0x00,0x00,0xaa,0x00,0x05,0x00,
-0xa8,0x00,0x00,0x00,0x8e,0x04,0x00,0x00,0x60,0x00,0x00,0x00,
-0x3b,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x90,0x04,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x8e,0x04,0x00,0x00,
-0x8f,0x04,0x00,0x00,0x90,0x04,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8f,0x04,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x97,0x04,0x00,0x00,0xb3,0x04,0x00,0x00,0x45,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x9d,0x00,0x00,0x00,0x98,0x04,0x00,0x00,
-0x96,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x93,0x00,0x00,0x00,0x99,0x04,0x00,0x00,0x98,0x04,0x00,0x00,
-0x41,0x00,0x06,0x00,0x33,0x02,0x00,0x00,0x9a,0x04,0x00,0x00,
-0x94,0x04,0x00,0x00,0x1c,0x00,0x00,0x00,0x97,0x04,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x9a,0x04,0x00,0x00,0x99,0x04,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x90,0x04,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x90,0x04,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t mul_mat_vec_id_q5_k_f32_len = 12816;
-
-unsigned char mul_mat_vec_id_q6_k_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xf8,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x5d,0x00,0x00,0x00,
-0x8f,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,0xc9,0x00,0x00,0x00,
-0xda,0x01,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x18,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x19,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x19,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x19,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
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-0xf8,0x00,0x02,0x00,0xbe,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd2,0x01,0x00,0x00,0xfb,0x01,0x00,0x00,
-0xf2,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xbb,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xbd,0x01,0x00,0x00,0xaa,0x00,0x05,0x00,
-0xa1,0x00,0x00,0x00,0xd4,0x01,0x00,0x00,0x60,0x00,0x00,0x00,
-0x3b,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0xd6,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xd4,0x01,0x00,0x00,
-0xd5,0x01,0x00,0x00,0xd6,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd5,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdd,0x01,0x00,0x00,0xf9,0x01,0x00,0x00,0x45,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x96,0x00,0x00,0x00,0xde,0x01,0x00,0x00,
-0x8f,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x8c,0x00,0x00,0x00,0xdf,0x01,0x00,0x00,0xde,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0xd1,0x00,0x00,0x00,0xe0,0x01,0x00,0x00,
-0xda,0x01,0x00,0x00,0x1c,0x00,0x00,0x00,0xdd,0x01,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xe0,0x01,0x00,0x00,0xdf,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xd6,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd6,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t mul_mat_vec_id_q6_k_f32_len = 11760;
-
-unsigned char mul_mat_vec_id_q8_0_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x41,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x46,0x00,0x00,0x00,
-0x4e,0x00,0x00,0x00,0x57,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,
-0x70,0x00,0x00,0x00,0x79,0x00,0x00,0x00,0x89,0x00,0x00,0x00,
-0xc1,0x00,0x00,0x00,0xff,0x00,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x1b,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1c,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1d,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x1e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x1e,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x20,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x20,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x46,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4b,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x4c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4c,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x4c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4e,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x4e,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x55,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x55,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x55,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x55,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x55,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x55,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x55,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x55,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x55,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x55,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x6c,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x70,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x79,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x86,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xbe,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xbf,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xbf,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xbf,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xc1,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xc1,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xfc,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xfd,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xfd,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xfd,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xff,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xff,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x06,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x07,0x01,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0x08,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0x09,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x16,0x00,0x03,0x00,0x18,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x19,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,
-0x1b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x1e,0x00,0x04,0x00,0x1c,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0x1d,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0x1e,0x00,0x00,0x00,
-0x1d,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x1f,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x1f,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x21,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x21,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
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-0x2b,0x00,0x04,0x00,0x21,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x2f,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x17,0x00,0x04,0x00,0x44,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x45,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x44,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x45,0x00,0x00,0x00,0x46,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x47,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
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-0x21,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0x4c,0x00,0x00,0x00,
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-0x0c,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
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-0x21,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x21,0x00,0x00,0x00,0x67,0x00,0x00,0x00,
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-0x45,0x00,0x00,0x00,0x79,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
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-0xfa,0x00,0x04,0x00,0xe6,0x00,0x00,0x00,0xe1,0x00,0x00,0x00,
-0xe2,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xe1,0x00,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x98,0x00,0x00,0x00,0xe9,0x00,0x00,0x00,
-0x7b,0x00,0x00,0x00,0x40,0x01,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xeb,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xe9,0x00,0x00,0x00,0xea,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xea,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xef,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0x40,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x8c,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0x89,0x00,0x00,0x00,0xef,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xf3,0x00,0x00,0x00,0x8d,0x00,0x00,0x00,0x81,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,
-0xf1,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x8d,0x00,0x00,0x00,
-0xf4,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xeb,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xeb,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x73,0x00,0x00,0x00,0x73,0x00,0x00,0x00,0xdd,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe3,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe3,0x00,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf7,0x00,0x00,0x00,0x40,0x01,0x00,0x00,0x2d,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe0,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe2,0x00,0x00,0x00,0xaa,0x00,0x05,0x00,0x98,0x00,0x00,0x00,
-0xf9,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xfb,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xf9,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,
-0xfb,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xfa,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x02,0x01,0x00,0x00,
-0x1f,0x01,0x00,0x00,0x77,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x8c,0x00,0x00,0x00,0x03,0x01,0x00,0x00,0x89,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x04,0x01,0x00,0x00,0x03,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0xc7,0x00,0x00,0x00,0x05,0x01,0x00,0x00,0xff,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x02,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x05,0x01,0x00,0x00,0x04,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xfb,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xfb,0x00,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_id_q8_0_f32_len = 3956;
-
-unsigned char mul_mat_vec_nc_f16_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xb3,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0c,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x1d,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0x6f,0x00,0x00,0x00,0x7a,0x00,0x00,0x00,0xab,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1b,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1b,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1b,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x1b,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x6c,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x6d,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x6d,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x6d,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x6f,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x6f,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x77,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x78,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x78,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x78,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x7a,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x7a,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xa8,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0xa9,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0xa9,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0xa9,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xab,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xab,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xb0,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x1e,0x00,0x09,0x00,0x1b,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x1c,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x1c,0x00,0x00,0x00,0x1d,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x1e,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x1e,0x00,0x00,0x00,
-0x1f,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x20,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x1e,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x1e,0x00,0x00,0x00,
-0x29,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0x34,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x35,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x1c,0x00,0x04,0x00,0x36,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
-0x35,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x37,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x36,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x37,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x34,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x3b,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x14,0x00,0x02,0x00,
-0x46,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x1e,0x00,0x00,0x00,
-0x57,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x1e,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x16,0x00,0x03,0x00,0x6b,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0x6c,0x00,0x00,0x00,0x6b,0x00,0x00,0x00,
-0x1e,0x00,0x03,0x00,0x6d,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x6e,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x6e,0x00,0x00,0x00,
-0x6f,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x71,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x6b,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0x77,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
-0x1e,0x00,0x03,0x00,0x78,0x00,0x00,0x00,0x77,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x79,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x78,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x79,0x00,0x00,0x00,
-0x7a,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x7c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
-0x08,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x1e,0x00,0x00,0x00,
-0x89,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0xa8,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0xa9,0x00,0x00,0x00,0xa8,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0xaa,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0xa9,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0xaa,0x00,0x00,0x00,0xab,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x2c,0x00,0x06,0x00,0x09,0x00,0x00,0x00,
-0xb0,0x00,0x00,0x00,0x35,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x12,0x00,0x00,0x00,0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x0d,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
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-0x26,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x20,0x00,0x00,0x00,
-0x2a,0x00,0x00,0x00,0x1d,0x00,0x00,0x00,0x29,0x00,0x00,0x00,
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-0x50,0x00,0x00,0x00,0x51,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x50,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x40,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x51,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
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-0x71,0x00,0x00,0x00,0x72,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,
-0x25,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x6b,0x00,0x00,0x00,0x73,0x00,0x00,0x00,0x72,0x00,0x00,0x00,
-0x73,0x00,0x04,0x00,0x34,0x00,0x00,0x00,0x74,0x00,0x00,0x00,
-0x73,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x7c,0x00,0x00,0x00,
-0x7d,0x00,0x00,0x00,0x7a,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0x68,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x34,0x00,0x00,0x00,
-0x7e,0x00,0x00,0x00,0x7d,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x34,0x00,0x00,0x00,0x81,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,
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-0x3c,0x00,0x00,0x00,0x82,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x41,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x41,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x85,0x00,0x00,0x00,
-0xb1,0x00,0x00,0x00,0x35,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x3e,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x40,0x00,0x00,0x00,
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-0x86,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x8a,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x8a,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x1e,0x00,0x00,0x00,0xb2,0x00,0x00,0x00,0x89,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0xa3,0x00,0x00,0x00,0x8d,0x00,0x00,0x00,
-0xad,0x00,0x05,0x00,0x46,0x00,0x00,0x00,0x90,0x00,0x00,0x00,
-0xb2,0x00,0x00,0x00,0x25,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x8c,0x00,0x00,0x00,0x8d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x90,0x00,0x00,0x00,0x8b,0x00,0x00,0x00,
-0x8c,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x8b,0x00,0x00,0x00,
-0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x93,0x00,0x00,0x00,
-0xb2,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,0x46,0x00,0x00,0x00,
-0x94,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x93,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x96,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x94,0x00,0x00,0x00,0x95,0x00,0x00,0x00,
-0x96,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x95,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9b,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x93,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x3b,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0x9b,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x34,0x00,0x00,0x00,
-0x9d,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x34,0x00,0x00,0x00,0x9f,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x34,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,
-0x9f,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x3c,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x96,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x96,0x00,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x16,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x86,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x8d,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x8d,0x00,0x00,0x00,0xc3,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0xa3,0x00,0x00,0x00,0xb2,0x00,0x00,0x00,
-0x29,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x8a,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x8c,0x00,0x00,0x00,0xaa,0x00,0x05,0x00,
-0x46,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0xa7,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xa5,0x00,0x00,0x00,
-0xa6,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa6,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x3b,0x00,0x00,0x00,
-0xad,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x34,0x00,0x00,0x00,0xae,0x00,0x00,0x00,
-0xad,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x7c,0x00,0x00,0x00,
-0xaf,0x00,0x00,0x00,0xab,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0x33,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0xaf,0x00,0x00,0x00,
-0xae,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xa7,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa7,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_nc_f16_f32_len = 2824;
-
-unsigned char mul_mat_vec_p021_f16_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xbc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0c,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x1d,0x00,0x00,0x00,0x36,0x00,0x00,0x00,
-0x66,0x00,0x00,0x00,0x79,0x00,0x00,0x00,0xb0,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1b,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1b,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x1b,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x63,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x64,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x64,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x64,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x66,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x66,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x76,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
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-0x95,0x00,0x00,0x00,0xb7,0x00,0x00,0x00,0x29,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x91,0x00,0x00,0x00,0x92,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x95,0x00,0x00,0x00,
-0x90,0x00,0x00,0x00,0x91,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x90,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x98,0x00,0x00,0x00,0xb7,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x44,0x00,0x00,0x00,0x99,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x98,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x9b,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x99,0x00,0x00,0x00,
-0x9a,0x00,0x00,0x00,0x9b,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9a,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa0,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x98,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x39,0x00,0x00,0x00,0xa1,0x00,0x00,0x00,
-0x36,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x32,0x00,0x00,0x00,0xa2,0x00,0x00,0x00,0xa1,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x32,0x00,0x00,0x00,0xa4,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x81,0x00,0x05,0x00,0x32,0x00,0x00,0x00,
-0xa5,0x00,0x00,0x00,0xa4,0x00,0x00,0x00,0xa2,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x3a,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x9b,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x9b,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x8b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x92,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x92,0x00,0x00,0x00,
-0xc3,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,0xa8,0x00,0x00,0x00,
-0xb7,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x8f,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x91,0x00,0x00,0x00,
-0xaa,0x00,0x05,0x00,0x44,0x00,0x00,0x00,0xaa,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xac,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xaa,0x00,0x00,0x00,0xab,0x00,0x00,0x00,0xac,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xab,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x39,0x00,0x00,0x00,0xb2,0x00,0x00,0x00,0x36,0x00,0x00,0x00,
-0x29,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x32,0x00,0x00,0x00,
-0xb3,0x00,0x00,0x00,0xb2,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x7b,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,0xb0,0x00,0x00,0x00,
-0x29,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xb4,0x00,0x00,0x00,0xb3,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xac,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xac,0x00,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_p021_f16_f32_len = 2768;
-
-unsigned char mul_mat_vec_q2_k_f16_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x50,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
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-0x01,0x00,0x00,0x00,0x0f,0x00,0x0e,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x4a,0x00,0x00,0x00,
-0x4e,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x94,0x00,0x00,0x00,
-0xb9,0x00,0x00,0x00,0xd7,0x00,0x00,0x00,0x13,0x03,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x11,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x18,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x18,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x18,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x18,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4a,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x6e,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xb0,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xb2,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xb5,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0xb5,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
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-0x06,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
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-0x48,0x00,0x05,0x00,0xb7,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0xb7,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xb9,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xb9,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xd4,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0xd5,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0xd5,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0xd5,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xd7,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xd7,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x10,0x03,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x11,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x03,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
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-0x47,0x00,0x04,0x00,0x13,0x03,0x00,0x00,0x21,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1b,0x03,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0x0f,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x10,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x10,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
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-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
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-0x19,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
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-0x06,0x03,0x00,0x00,0x08,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xff,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xff,0x02,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x51,0x00,0x00,0x00,0x51,0x00,0x00,0x00,
-0xf2,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xf7,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf7,0x02,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x0b,0x03,0x00,0x00,0x48,0x03,0x00,0x00,
-0xf3,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xf4,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf6,0x02,0x00,0x00,0xaa,0x00,0x05,0x00,
-0xa6,0x00,0x00,0x00,0x0d,0x03,0x00,0x00,0x71,0x00,0x00,0x00,
-0x4b,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x0f,0x03,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x0d,0x03,0x00,0x00,
-0x0e,0x03,0x00,0x00,0x0f,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x0e,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x16,0x03,0x00,0x00,0x46,0x03,0x00,0x00,0x55,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x9b,0x00,0x00,0x00,0x17,0x03,0x00,0x00,
-0x94,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x91,0x00,0x00,0x00,0x18,0x03,0x00,0x00,0x17,0x03,0x00,0x00,
-0x41,0x00,0x06,0x00,0x19,0x03,0x00,0x00,0x1a,0x03,0x00,0x00,
-0x13,0x03,0x00,0x00,0x61,0x00,0x00,0x00,0x16,0x03,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x1a,0x03,0x00,0x00,0x18,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x0f,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x0f,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t mul_mat_vec_q2_k_f16_f32_len = 8760;
-
-unsigned char mul_mat_vec_q2_k_f32_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x40,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
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-0xf5,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0xaf,0x00,0x00,0x00,
-0xc6,0x02,0x00,0x00,0xfd,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,
-0xaf,0x00,0x00,0x00,0xc7,0x02,0x00,0x00,0xc6,0x02,0x00,0x00,
-0x3b,0x00,0x00,0x00,0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xc8,0x02,0x00,0x00,0xc7,0x02,0x00,0x00,0x7c,0x00,0x04,0x00,
-0x1b,0x00,0x00,0x00,0xc9,0x02,0x00,0x00,0xc8,0x02,0x00,0x00,
-0xc7,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,0xca,0x02,0x00,0x00,
-0xc9,0x02,0x00,0x00,0xec,0x00,0x00,0x00,0x6f,0x00,0x04,0x00,
-0x91,0x00,0x00,0x00,0xcb,0x02,0x00,0x00,0xca,0x02,0x00,0x00,
-0x0c,0x00,0x08,0x00,0x91,0x00,0x00,0x00,0xcd,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0xbf,0x02,0x00,0x00,
-0xcb,0x02,0x00,0x00,0xb6,0x02,0x00,0x00,0x81,0x00,0x05,0x00,
-0x91,0x00,0x00,0x00,0xcf,0x02,0x00,0x00,0x3c,0x03,0x00,0x00,
-0xcd,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,
-0xd1,0x02,0x00,0x00,0x3a,0x03,0x00,0x00,0xf3,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xcd,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xcf,0x00,0x00,0x00,0x85,0x00,0x05,0x00,0x91,0x00,0x00,0x00,
-0xdb,0x02,0x00,0x00,0xc8,0x00,0x00,0x00,0x3c,0x03,0x00,0x00,
-0x7f,0x00,0x04,0x00,0x91,0x00,0x00,0x00,0x3f,0x03,0x00,0x00,
-0xdb,0x02,0x00,0x00,0x0c,0x00,0x08,0x00,0x91,0x00,0x00,0x00,
-0xdc,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0xc1,0x00,0x00,0x00,0x3b,0x03,0x00,0x00,0x3f,0x03,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x91,0x00,0x00,0x00,0xde,0x02,0x00,0x00,
-0x9c,0x00,0x00,0x00,0x81,0x00,0x05,0x00,0x91,0x00,0x00,0x00,
-0xdf,0x02,0x00,0x00,0xde,0x02,0x00,0x00,0xdc,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x9c,0x00,0x00,0x00,0xdf,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa2,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa2,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe2,0x02,0x00,0x00,0x37,0x03,0x00,0x00,0x51,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x9f,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa1,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,0x51,0x00,0x00,0x00,
-0x51,0x00,0x00,0x00,0xe3,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe5,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xe5,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x38,0x03,0x00,0x00,
-0x95,0x00,0x00,0x00,0xa1,0x00,0x00,0x00,0xfc,0x02,0x00,0x00,
-0xe8,0x02,0x00,0x00,0xac,0x00,0x05,0x00,0xa6,0x00,0x00,0x00,
-0xeb,0x02,0x00,0x00,0x38,0x03,0x00,0x00,0x4b,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xe7,0x02,0x00,0x00,0xe8,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xeb,0x02,0x00,0x00,
-0xe6,0x02,0x00,0x00,0xe7,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe6,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xa6,0x00,0x00,0x00,
-0xee,0x02,0x00,0x00,0x71,0x00,0x00,0x00,0x38,0x03,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xf0,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xee,0x02,0x00,0x00,0xef,0x02,0x00,0x00,
-0xf0,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xef,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf4,0x02,0x00,0x00,
-0x71,0x00,0x00,0x00,0x38,0x03,0x00,0x00,0x41,0x00,0x05,0x00,
-0x9b,0x00,0x00,0x00,0xf5,0x02,0x00,0x00,0x94,0x00,0x00,0x00,
-0xf4,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x91,0x00,0x00,0x00,
-0xf6,0x02,0x00,0x00,0xf5,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x9b,0x00,0x00,0x00,0xf7,0x02,0x00,0x00,0x94,0x00,0x00,0x00,
-0x71,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x91,0x00,0x00,0x00,
-0xf8,0x02,0x00,0x00,0xf7,0x02,0x00,0x00,0x81,0x00,0x05,0x00,
-0x91,0x00,0x00,0x00,0xf9,0x02,0x00,0x00,0xf8,0x02,0x00,0x00,
-0xf6,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0xf7,0x02,0x00,0x00,
-0xf9,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xf0,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf0,0x02,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x51,0x00,0x00,0x00,0x51,0x00,0x00,0x00,0xe3,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe8,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe8,0x02,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xfc,0x02,0x00,0x00,0x38,0x03,0x00,0x00,0xf3,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xe5,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xe7,0x02,0x00,0x00,0xaa,0x00,0x05,0x00,0xa6,0x00,0x00,0x00,
-0xfe,0x02,0x00,0x00,0x71,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xfe,0x02,0x00,0x00,0xff,0x02,0x00,0x00,
-0x00,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0xff,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x07,0x03,0x00,0x00,
-0x36,0x03,0x00,0x00,0x55,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x9b,0x00,0x00,0x00,0x08,0x03,0x00,0x00,0x94,0x00,0x00,0x00,
-0x61,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x91,0x00,0x00,0x00,
-0x09,0x03,0x00,0x00,0x08,0x03,0x00,0x00,0x41,0x00,0x06,0x00,
-0xdf,0x00,0x00,0x00,0x0a,0x03,0x00,0x00,0x04,0x03,0x00,0x00,
-0x61,0x00,0x00,0x00,0x07,0x03,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x0a,0x03,0x00,0x00,0x09,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x00,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x00,0x03,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_q2_k_f32_f32_len = 8504;
-
-unsigned char mul_mat_vec_q3_k_f16_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x8c,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0e,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x4a,0x00,0x00,0x00,
-0x4e,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,
-0xc4,0x00,0x00,0x00,0xdb,0x00,0x00,0x00,0x53,0x03,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x11,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x18,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x18,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x18,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x18,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4a,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x6e,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xba,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xbc,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xbe,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xc0,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xc0,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0xc0,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xc0,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x6c,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xc1,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0xc2,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0xc2,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xc4,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xd8,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0xd9,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0xd9,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0xd9,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xdb,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xdb,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x50,0x03,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x51,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x51,0x03,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x51,0x03,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x53,0x03,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x53,0x03,0x00,0x00,0x21,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x5b,0x03,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
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-0x32,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0x37,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x37,0x03,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x4b,0x03,0x00,0x00,0x88,0x03,0x00,0x00,
-0x82,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x34,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x36,0x03,0x00,0x00,0xaa,0x00,0x05,0x00,
-0xb1,0x00,0x00,0x00,0x4d,0x03,0x00,0x00,0x71,0x00,0x00,0x00,
-0x4b,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x4f,0x03,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x4d,0x03,0x00,0x00,
-0x4e,0x03,0x00,0x00,0x4f,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x4e,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x56,0x03,0x00,0x00,0x86,0x03,0x00,0x00,0x55,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0xa3,0x00,0x00,0x00,0x57,0x03,0x00,0x00,
-0x9c,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x99,0x00,0x00,0x00,0x58,0x03,0x00,0x00,0x57,0x03,0x00,0x00,
-0x41,0x00,0x06,0x00,0x59,0x03,0x00,0x00,0x5a,0x03,0x00,0x00,
-0x53,0x03,0x00,0x00,0x61,0x00,0x00,0x00,0x56,0x03,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x5a,0x03,0x00,0x00,0x58,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x4f,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x4f,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t mul_mat_vec_q3_k_f16_f32_len = 10176;
-
-unsigned char mul_mat_vec_q3_k_f32_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x84,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
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-0x0c,0x00,0x08,0x00,0x99,0x00,0x00,0x00,0x27,0x03,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,
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-0xfa,0x00,0x04,0x00,0x33,0x03,0x00,0x00,0x2e,0x03,0x00,0x00,
-0x2f,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x2e,0x03,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xb1,0x00,0x00,0x00,0x36,0x03,0x00,0x00,
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-0x51,0x00,0x00,0x00,0x2b,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x30,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x30,0x03,0x00,0x00,
-0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x44,0x03,0x00,0x00,
-0x80,0x03,0x00,0x00,0x82,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x2d,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x2f,0x03,0x00,0x00,
-0xaa,0x00,0x05,0x00,0xb1,0x00,0x00,0x00,0x46,0x03,0x00,0x00,
-0x71,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x48,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x46,0x03,0x00,0x00,0x47,0x03,0x00,0x00,0x48,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x47,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x4f,0x03,0x00,0x00,0x7e,0x03,0x00,0x00,
-0x55,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0xa3,0x00,0x00,0x00,
-0x50,0x03,0x00,0x00,0x9c,0x00,0x00,0x00,0x61,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x99,0x00,0x00,0x00,0x51,0x03,0x00,0x00,
-0x50,0x03,0x00,0x00,0x41,0x00,0x06,0x00,0xe3,0x00,0x00,0x00,
-0x52,0x03,0x00,0x00,0x4c,0x03,0x00,0x00,0x61,0x00,0x00,0x00,
-0x4f,0x03,0x00,0x00,0x3e,0x00,0x03,0x00,0x52,0x03,0x00,0x00,
-0x51,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0x48,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x48,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_q3_k_f32_f32_len = 10048;
-
-unsigned char mul_mat_vec_q4_0_f16_f32_data[] = {
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-0x56,0x01,0x00,0x00,0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x58,0x01,0x00,0x00,0x57,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x5a,0x01,0x00,0x00,0x58,0x01,0x00,0x00,
-0x35,0x00,0x00,0x00,0x70,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x5b,0x01,0x00,0x00,0x5a,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x5d,0x01,0x00,0x00,0x58,0x01,0x00,0x00,
-0x39,0x00,0x00,0x00,0x70,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x5e,0x01,0x00,0x00,0x5d,0x01,0x00,0x00,0x50,0x00,0x05,0x00,
-0x09,0x00,0x00,0x00,0x5f,0x01,0x00,0x00,0x5b,0x01,0x00,0x00,
-0x5e,0x01,0x00,0x00,0x83,0x00,0x05,0x00,0x09,0x00,0x00,0x00,
-0x61,0x01,0x00,0x00,0x5f,0x01,0x00,0x00,0x69,0x01,0x00,0x00,
-0x8e,0x00,0x05,0x00,0x09,0x00,0x00,0x00,0x63,0x01,0x00,0x00,
-0x61,0x01,0x00,0x00,0x51,0x01,0x00,0x00,0x51,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x63,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd7,0x00,0x00,0x00,0x43,0x01,0x00,0x00,0xc3,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd9,0x00,0x00,0x00,
-0xd7,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x26,0x00,0x00,0x00,0xda,0x00,0x00,0x00,0xd4,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0xd9,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x18,0x00,0x00,0x00,0xdb,0x00,0x00,0x00,0xda,0x00,0x00,0x00,
-0x73,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xdc,0x00,0x00,0x00,
-0xdb,0x00,0x00,0x00,0x51,0x00,0x05,0x00,0x08,0x00,0x00,0x00,
-0xdf,0x00,0x00,0x00,0x63,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe5,0x00,0x00,0x00,
-0xd9,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x26,0x00,0x00,0x00,0xe6,0x00,0x00,0x00,0xd4,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0xe5,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x18,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,0xe6,0x00,0x00,0x00,
-0x73,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,
-0xe7,0x00,0x00,0x00,0x85,0x00,0x05,0x00,0x08,0x00,0x00,0x00,
-0xe9,0x00,0x00,0x00,0xdf,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,
-0x0c,0x00,0x08,0x00,0x08,0x00,0x00,0x00,0xea,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xdc,0x00,0x00,0x00,0xe9,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xec,0x00,0x00,0x00,0x9f,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0xec,0x00,0x00,0x00,0xea,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x9f,0x00,0x00,0x00,0xed,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,0x66,0x01,0x00,0x00,
-0x85,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xa1,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa3,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x85,0x00,0x00,0x00,0x85,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xf4,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf4,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x67,0x01,0x00,0x00,0xf3,0x00,0x00,0x00,0xa3,0x00,0x00,0x00,
-0x0b,0x01,0x00,0x00,0xf7,0x00,0x00,0x00,0xac,0x00,0x05,0x00,
-0xaa,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x67,0x01,0x00,0x00,
-0x7f,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xf6,0x00,0x00,0x00,
-0xf7,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xfa,0x00,0x00,0x00,0xf5,0x00,0x00,0x00,0xf6,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf5,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xaa,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,0x8d,0x00,0x00,0x00,
-0x67,0x01,0x00,0x00,0xf7,0x00,0x03,0x00,0xff,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xfd,0x00,0x00,0x00,
-0xfe,0x00,0x00,0x00,0xff,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xfe,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x03,0x01,0x00,0x00,0x8d,0x00,0x00,0x00,0x67,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x9e,0x00,0x00,0x00,0x04,0x01,0x00,0x00,
-0x9b,0x00,0x00,0x00,0x03,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x05,0x01,0x00,0x00,0x04,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x07,0x01,0x00,0x00,
-0x9f,0x00,0x00,0x00,0x81,0x00,0x05,0x00,0x08,0x00,0x00,0x00,
-0x08,0x01,0x00,0x00,0x07,0x01,0x00,0x00,0x05,0x01,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x9f,0x00,0x00,0x00,0x08,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xff,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xff,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,0x85,0x00,0x00,0x00,
-0x85,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xf7,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xf7,0x00,0x00,0x00,
-0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x0b,0x01,0x00,0x00,
-0x67,0x01,0x00,0x00,0x2e,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xf4,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xf6,0x00,0x00,0x00,
-0xaa,0x00,0x05,0x00,0xaa,0x00,0x00,0x00,0x0d,0x01,0x00,0x00,
-0x8d,0x00,0x00,0x00,0x7f,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x0f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x0d,0x01,0x00,0x00,0x0e,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x0e,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x16,0x01,0x00,0x00,0x47,0x01,0x00,0x00,
-0x89,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x9e,0x00,0x00,0x00,
-0x17,0x01,0x00,0x00,0x9b,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x18,0x01,0x00,0x00,
-0x17,0x01,0x00,0x00,0x41,0x00,0x06,0x00,0x19,0x01,0x00,0x00,
-0x1a,0x01,0x00,0x00,0x13,0x01,0x00,0x00,0x22,0x00,0x00,0x00,
-0x16,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x1a,0x01,0x00,0x00,
-0x18,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x0f,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x0f,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_q4_0_f16_f32_len = 4108;
-
-unsigned char mul_mat_vec_q4_0_f32_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x68,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0e,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x47,0x00,0x00,0x00,
-0x50,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,0x82,0x00,0x00,0x00,
-0x8b,0x00,0x00,0x00,0x9b,0x00,0x00,0x00,0xd4,0x00,0x00,0x00,
-0x12,0x01,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1c,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x1d,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x12,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x1e,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x1e,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x20,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x20,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x47,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4e,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4e,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4e,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4e,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4e,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4e,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4e,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4e,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4e,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4e,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4e,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x4e,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x7e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x82,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x8b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x98,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xd1,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xd2,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xd2,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xd2,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xd4,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xd4,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0f,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x10,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x10,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x10,0x01,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x12,0x01,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
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-0x64,0x01,0x00,0x00,0xa9,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xa3,0x00,0x00,0x00,0xa2,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xab,0x00,0x00,0x00,0xa2,0x00,0x00,0x00,
-0xa3,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xa2,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xae,0x00,0x00,0x00,
-0x64,0x01,0x00,0x00,0x98,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
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-0x8d,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
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-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb6,0x00,0x00,0x00,
-0x89,0x00,0x00,0x00,0xa8,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,0xb6,0x00,0x00,0x00,
-0xb1,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xba,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,
-0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,
-0xb1,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,0x86,0x00,0x05,0x00,
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-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,
-0x3d,0x01,0x00,0x00,0xb9,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x4c,0x01,0x00,0x00,0xc7,0x00,0x00,0x00,
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-0x73,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x4f,0x01,0x00,0x00,
-0x4e,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x30,0x00,0x00,0x00,
-0x54,0x01,0x00,0x00,0x20,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x4c,0x01,0x00,0x00,0x2e,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x19,0x00,0x00,0x00,0x55,0x01,0x00,0x00,
-0x54,0x01,0x00,0x00,0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x56,0x01,0x00,0x00,0x55,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x58,0x01,0x00,0x00,0x56,0x01,0x00,0x00,
-0x35,0x00,0x00,0x00,0x70,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x59,0x01,0x00,0x00,0x58,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x5b,0x01,0x00,0x00,0x56,0x01,0x00,0x00,
-0x39,0x00,0x00,0x00,0x70,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x5c,0x01,0x00,0x00,0x5b,0x01,0x00,0x00,0x50,0x00,0x05,0x00,
-0x09,0x00,0x00,0x00,0x5d,0x01,0x00,0x00,0x59,0x01,0x00,0x00,
-0x5c,0x01,0x00,0x00,0x83,0x00,0x05,0x00,0x09,0x00,0x00,0x00,
-0x5f,0x01,0x00,0x00,0x5d,0x01,0x00,0x00,0x67,0x01,0x00,0x00,
-0x8e,0x00,0x05,0x00,0x09,0x00,0x00,0x00,0x61,0x01,0x00,0x00,
-0x5f,0x01,0x00,0x00,0x4f,0x01,0x00,0x00,0x51,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x61,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xd7,0x00,0x00,0x00,0x41,0x01,0x00,0x00,0xc3,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd9,0x00,0x00,0x00,
-0xd7,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0xda,0x00,0x00,0x00,0xdb,0x00,0x00,0x00,0xd4,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0xd9,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0xdc,0x00,0x00,0x00,0xdb,0x00,0x00,0x00,
-0x51,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0xdf,0x00,0x00,0x00,
-0x61,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe5,0x00,0x00,0x00,0xd9,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0xda,0x00,0x00,0x00,
-0xe6,0x00,0x00,0x00,0xd4,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0xe5,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0xe7,0x00,0x00,0x00,0xe6,0x00,0x00,0x00,0x85,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,0xdf,0x00,0x00,0x00,
-0xe7,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,0x08,0x00,0x00,0x00,
-0xe9,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xdc,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
-0x9f,0x00,0x00,0x00,0x81,0x00,0x05,0x00,0x08,0x00,0x00,0x00,
-0xec,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,0xe9,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x9f,0x00,0x00,0x00,0xec,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xef,0x00,0x00,0x00,
-0x64,0x01,0x00,0x00,0x85,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa1,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xa3,0x00,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x85,0x00,0x00,0x00,0x85,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xf3,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf3,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x65,0x01,0x00,0x00,0xf2,0x00,0x00,0x00,
-0xa3,0x00,0x00,0x00,0x0a,0x01,0x00,0x00,0xf6,0x00,0x00,0x00,
-0xac,0x00,0x05,0x00,0xaa,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,
-0x65,0x01,0x00,0x00,0x7f,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xf5,0x00,0x00,0x00,0xf6,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xf9,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,
-0xf5,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xf4,0x00,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xaa,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,
-0x8d,0x00,0x00,0x00,0x65,0x01,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xfe,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xfc,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xfd,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x02,0x01,0x00,0x00,0x8d,0x00,0x00,0x00,
-0x65,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x9e,0x00,0x00,0x00,
-0x03,0x01,0x00,0x00,0x9b,0x00,0x00,0x00,0x02,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x04,0x01,0x00,0x00,
-0x03,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x06,0x01,0x00,0x00,0x9f,0x00,0x00,0x00,0x81,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0x07,0x01,0x00,0x00,0x06,0x01,0x00,0x00,
-0x04,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x9f,0x00,0x00,0x00,
-0x07,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0xfe,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xfe,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x85,0x00,0x00,0x00,0x85,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xf6,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf6,0x00,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x0a,0x01,0x00,0x00,0x65,0x01,0x00,0x00,0x2e,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xf3,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf5,0x00,0x00,0x00,0xaa,0x00,0x05,0x00,0xaa,0x00,0x00,0x00,
-0x0c,0x01,0x00,0x00,0x8d,0x00,0x00,0x00,0x7f,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x0e,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x0c,0x01,0x00,0x00,0x0d,0x01,0x00,0x00,
-0x0e,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x0d,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x15,0x01,0x00,0x00,
-0x45,0x01,0x00,0x00,0x89,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x9e,0x00,0x00,0x00,0x16,0x01,0x00,0x00,0x9b,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x17,0x01,0x00,0x00,0x16,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0xda,0x00,0x00,0x00,0x18,0x01,0x00,0x00,0x12,0x01,0x00,0x00,
-0x22,0x00,0x00,0x00,0x15,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x18,0x01,0x00,0x00,0x17,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x0e,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x0e,0x01,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_q4_0_f32_f32_len = 4076;
-
-unsigned char mul_mat_vec_q4_1_f16_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x78,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
-0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0e,0x00,
-0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
-0x00,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
-0x58,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,
-0x93,0x00,0x00,0x00,0xa3,0x00,0x00,0x00,0xdc,0x00,0x00,0x00,
-0x1b,0x01,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x1c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1c,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x1c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x1d,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x1e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x1e,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x20,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x20,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4f,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x56,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x56,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x56,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x56,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x56,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x56,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
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-0x87,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xfe,0x00,0x00,0x00,
-0xff,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x02,0x01,0x00,0x00,0xfd,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,
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-0xb2,0x00,0x00,0x00,0x05,0x01,0x00,0x00,0x95,0x00,0x00,0x00,
-0x77,0x01,0x00,0x00,0xf7,0x00,0x03,0x00,0x07,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x05,0x01,0x00,0x00,
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-0x0b,0x01,0x00,0x00,0x95,0x00,0x00,0x00,0x77,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0xa6,0x00,0x00,0x00,0x0c,0x01,0x00,0x00,
-0xa3,0x00,0x00,0x00,0x0b,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x0d,0x01,0x00,0x00,0x0c,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x0f,0x01,0x00,0x00,
-0xa7,0x00,0x00,0x00,0x81,0x00,0x05,0x00,0x08,0x00,0x00,0x00,
-0x10,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,0x0d,0x01,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xa7,0x00,0x00,0x00,0x10,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x07,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x07,0x01,0x00,0x00,0xe0,0x00,0x04,0x00,0x8d,0x00,0x00,0x00,
-0x8d,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xff,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xff,0x00,0x00,0x00,
-0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x13,0x01,0x00,0x00,
-0x77,0x01,0x00,0x00,0x2e,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xfc,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xfe,0x00,0x00,0x00,
-0xaa,0x00,0x05,0x00,0xb2,0x00,0x00,0x00,0x15,0x01,0x00,0x00,
-0x95,0x00,0x00,0x00,0x87,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x17,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x15,0x01,0x00,0x00,0x16,0x01,0x00,0x00,0x17,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x16,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x1e,0x01,0x00,0x00,0x4f,0x01,0x00,0x00,
-0x91,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0xa6,0x00,0x00,0x00,
-0x1f,0x01,0x00,0x00,0xa3,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x20,0x01,0x00,0x00,
-0x1f,0x01,0x00,0x00,0x41,0x00,0x06,0x00,0x21,0x01,0x00,0x00,
-0x22,0x01,0x00,0x00,0x1b,0x01,0x00,0x00,0x22,0x00,0x00,0x00,
-0x1e,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x22,0x01,0x00,0x00,
-0x20,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x17,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x17,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_q4_1_f16_f32_len = 4192;
-
-unsigned char mul_mat_vec_q4_1_f32_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
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-0x04,0x01,0x00,0x00,0x05,0x01,0x00,0x00,0x06,0x01,0x00,0x00,
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-0x75,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0xa6,0x00,0x00,0x00,
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-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x0c,0x01,0x00,0x00,
-0x0b,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x0e,0x01,0x00,0x00,0xa7,0x00,0x00,0x00,0x81,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0x0f,0x01,0x00,0x00,0x0e,0x01,0x00,0x00,
-0x0c,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0xa7,0x00,0x00,0x00,
-0x0f,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x06,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x06,0x01,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x8d,0x00,0x00,0x00,0x8d,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xfe,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xfe,0x00,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x12,0x01,0x00,0x00,0x75,0x01,0x00,0x00,0x2e,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xfb,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xfd,0x00,0x00,0x00,0xaa,0x00,0x05,0x00,0xb2,0x00,0x00,0x00,
-0x14,0x01,0x00,0x00,0x95,0x00,0x00,0x00,0x87,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x16,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x14,0x01,0x00,0x00,0x15,0x01,0x00,0x00,
-0x16,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x15,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1d,0x01,0x00,0x00,
-0x4d,0x01,0x00,0x00,0x91,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0xa6,0x00,0x00,0x00,0x1e,0x01,0x00,0x00,0xa3,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x1f,0x01,0x00,0x00,0x1e,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0xe2,0x00,0x00,0x00,0x20,0x01,0x00,0x00,0x1a,0x01,0x00,0x00,
-0x22,0x00,0x00,0x00,0x1d,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x20,0x01,0x00,0x00,0x1f,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x16,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x16,0x01,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_q4_1_f32_f32_len = 4160;
-
-unsigned char mul_mat_vec_q4_k_f16_f32_data[] = {
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-0x48,0x00,0x05,0x00,0x35,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
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-0x0f,0x04,0x00,0x00,0xf7,0x00,0x03,0x00,0xc6,0x03,0x00,0x00,
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-0xe0,0x00,0x04,0x00,0x51,0x00,0x00,0x00,0x51,0x00,0x00,0x00,
-0xb9,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0xbe,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xbe,0x03,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd2,0x03,0x00,0x00,0x0f,0x04,0x00,0x00,
-0xd7,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xbb,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xbd,0x03,0x00,0x00,0xaa,0x00,0x05,0x00,
-0xac,0x00,0x00,0x00,0xd4,0x03,0x00,0x00,0x71,0x00,0x00,0x00,
-0x4b,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0xd6,0x03,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xd4,0x03,0x00,0x00,
-0xd5,0x03,0x00,0x00,0xd6,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd5,0x03,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdd,0x03,0x00,0x00,0x0d,0x04,0x00,0x00,0x55,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0xa1,0x00,0x00,0x00,0xde,0x03,0x00,0x00,
-0x9a,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x97,0x00,0x00,0x00,0xdf,0x03,0x00,0x00,0xde,0x03,0x00,0x00,
-0x41,0x00,0x06,0x00,0xe0,0x03,0x00,0x00,0xe1,0x03,0x00,0x00,
-0xda,0x03,0x00,0x00,0x61,0x00,0x00,0x00,0xdd,0x03,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xe1,0x03,0x00,0x00,0xdf,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xd6,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd6,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t mul_mat_vec_q4_k_f16_f32_len = 10548;
-
-unsigned char mul_mat_vec_q4_k_f32_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xf3,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0e,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x4a,0x00,0x00,0x00,
-0x4e,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xc3,0x00,0x00,0x00,0x37,0x02,0x00,0x00,0xbb,0x03,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x11,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x18,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
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-0xa5,0x03,0x00,0x00,0xa6,0x03,0x00,0x00,0xa7,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xa6,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
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-0xae,0x03,0x00,0x00,0x81,0x00,0x05,0x00,0x97,0x00,0x00,0x00,
-0xb0,0x03,0x00,0x00,0xaf,0x03,0x00,0x00,0xad,0x03,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xae,0x03,0x00,0x00,0xb0,0x03,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa7,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa7,0x03,0x00,0x00,0xe0,0x00,0x04,0x00,0x51,0x00,0x00,0x00,
-0x51,0x00,0x00,0x00,0x9a,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x9f,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x9f,0x03,0x00,0x00,
-0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb3,0x03,0x00,0x00,
-0xef,0x03,0x00,0x00,0xd7,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x9c,0x03,0x00,0x00,0xf8,0x00,0x02,0x00,0x9e,0x03,0x00,0x00,
-0xaa,0x00,0x05,0x00,0xac,0x00,0x00,0x00,0xb5,0x03,0x00,0x00,
-0x71,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xb7,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xb5,0x03,0x00,0x00,0xb6,0x03,0x00,0x00,0xb7,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb6,0x03,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbe,0x03,0x00,0x00,0xed,0x03,0x00,0x00,
-0x55,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0xa1,0x00,0x00,0x00,
-0xbf,0x03,0x00,0x00,0x9a,0x00,0x00,0x00,0x61,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x97,0x00,0x00,0x00,0xc0,0x03,0x00,0x00,
-0xbf,0x03,0x00,0x00,0x41,0x00,0x06,0x00,0x3b,0x02,0x00,0x00,
-0xc1,0x03,0x00,0x00,0xbb,0x03,0x00,0x00,0x61,0x00,0x00,0x00,
-0xbe,0x03,0x00,0x00,0x3e,0x00,0x03,0x00,0xc1,0x03,0x00,0x00,
-0xc0,0x03,0x00,0x00,0xf9,0x00,0x02,0x00,0xb7,0x03,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb7,0x03,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_q4_k_f32_f32_len = 10036;
-
-unsigned char mul_mat_vec_q5_0_f16_f32_data[] = {
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-0xd8,0x00,0x00,0x00,0x28,0x01,0x00,0x00,0xbc,0x01,0x00,0x00,
-0x5e,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x24,0x01,0x00,0x00,
-0x25,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x28,0x01,0x00,0x00,0x23,0x01,0x00,0x00,0x24,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x23,0x01,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xd8,0x00,0x00,0x00,0x2b,0x01,0x00,0x00,0xbb,0x00,0x00,0x00,
-0xbc,0x01,0x00,0x00,0xf7,0x00,0x03,0x00,0x2d,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x2b,0x01,0x00,0x00,
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-0x3e,0x00,0x03,0x00,0xcd,0x00,0x00,0x00,0x36,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x2d,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x2d,0x01,0x00,0x00,0xe0,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x1f,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x25,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x25,0x01,0x00,0x00,
-0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x39,0x01,0x00,0x00,
-0xbc,0x01,0x00,0x00,0x31,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x22,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x24,0x01,0x00,0x00,
-0xaa,0x00,0x05,0x00,0xd8,0x00,0x00,0x00,0x3b,0x01,0x00,0x00,
-0xbb,0x00,0x00,0x00,0x5e,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x3d,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x3b,0x01,0x00,0x00,0x3c,0x01,0x00,0x00,0x3d,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x3c,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x44,0x01,0x00,0x00,0x75,0x01,0x00,0x00,
-0xb7,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0xcc,0x00,0x00,0x00,
-0x45,0x01,0x00,0x00,0xc9,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x46,0x01,0x00,0x00,
-0x45,0x01,0x00,0x00,0x41,0x00,0x06,0x00,0x47,0x01,0x00,0x00,
-0x48,0x01,0x00,0x00,0x41,0x01,0x00,0x00,0x25,0x00,0x00,0x00,
-0x44,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x48,0x01,0x00,0x00,
-0x46,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x3d,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x3d,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_q5_0_f16_f32_len = 4636;
-
-unsigned char mul_mat_vec_q5_0_f32_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xbd,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
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-0x40,0x01,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,
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-0x16,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
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-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x21,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x23,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x23,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x78,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7e,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7e,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7e,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7e,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7e,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x7e,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x7e,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x7e,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
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-0x31,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x34,0x01,0x00,0x00,0xcd,0x00,0x00,0x00,0x81,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0x35,0x01,0x00,0x00,0x34,0x01,0x00,0x00,
-0x32,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0xcd,0x00,0x00,0x00,
-0x35,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x2c,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x2c,0x01,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x1a,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x1e,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x24,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x24,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x38,0x01,0x00,0x00,0xba,0x01,0x00,0x00,0x31,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x21,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x23,0x01,0x00,0x00,0xaa,0x00,0x05,0x00,0xd8,0x00,0x00,0x00,
-0x3a,0x01,0x00,0x00,0xbb,0x00,0x00,0x00,0x5e,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x3c,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x3a,0x01,0x00,0x00,0x3b,0x01,0x00,0x00,
-0x3c,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x3b,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x43,0x01,0x00,0x00,
-0x73,0x01,0x00,0x00,0xb7,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0xcc,0x00,0x00,0x00,0x44,0x01,0x00,0x00,0xc9,0x00,0x00,0x00,
-0x25,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x45,0x01,0x00,0x00,0x44,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x08,0x01,0x00,0x00,0x46,0x01,0x00,0x00,0x40,0x01,0x00,0x00,
-0x25,0x00,0x00,0x00,0x43,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x46,0x01,0x00,0x00,0x45,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x3c,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x3c,0x01,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_q5_0_f32_f32_len = 4604;
-
-unsigned char mul_mat_vec_q5_1_f16_f32_data[] = {
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-0xaf,0x00,0x00,0x00,0xaf,0x00,0x00,0x00,0x1b,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x21,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x21,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x35,0x01,0x00,0x00,0xb7,0x01,0x00,0x00,0x2e,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x1e,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x20,0x01,0x00,0x00,0xaa,0x00,0x05,0x00,0xd4,0x00,0x00,0x00,
-0x37,0x01,0x00,0x00,0xb7,0x00,0x00,0x00,0x59,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x39,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x37,0x01,0x00,0x00,0x38,0x01,0x00,0x00,
-0x39,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x38,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x40,0x01,0x00,0x00,
-0x71,0x01,0x00,0x00,0xb3,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0xc8,0x00,0x00,0x00,0x41,0x01,0x00,0x00,0xc5,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x42,0x01,0x00,0x00,0x41,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x43,0x01,0x00,0x00,0x44,0x01,0x00,0x00,0x3d,0x01,0x00,0x00,
-0x22,0x00,0x00,0x00,0x40,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x44,0x01,0x00,0x00,0x42,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x39,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x39,0x01,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_q5_1_f16_f32_len = 4532;
-
-unsigned char mul_mat_vec_q5_1_f32_f32_data[] = {
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-0xb6,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
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-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
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-0x47,0x00,0x04,0x00,0xc2,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xfb,0x00,0x00,0x00,
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-0xfc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0xfc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
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-
-};
-const uint64_t mul_mat_vec_q5_1_f32_f32_len = 4500;
-
-unsigned char mul_mat_vec_q5_k_f16_f32_data[] = {
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-0xae,0x00,0x00,0x00,0xb7,0x04,0x00,0x00,0xa7,0x00,0x00,0x00,
-0xb6,0x04,0x00,0x00,0x3d,0x00,0x04,0x00,0xa4,0x00,0x00,0x00,
-0xb8,0x04,0x00,0x00,0xb7,0x04,0x00,0x00,0x41,0x00,0x05,0x00,
-0xae,0x00,0x00,0x00,0xb9,0x04,0x00,0x00,0xa7,0x00,0x00,0x00,
-0x71,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xa4,0x00,0x00,0x00,
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-0xa4,0x00,0x00,0x00,0xbb,0x04,0x00,0x00,0xba,0x04,0x00,0x00,
-0xb8,0x04,0x00,0x00,0x3e,0x00,0x03,0x00,0xb9,0x04,0x00,0x00,
-0xbb,0x04,0x00,0x00,0xf9,0x00,0x02,0x00,0xb2,0x04,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xb2,0x04,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x51,0x00,0x00,0x00,0x51,0x00,0x00,0x00,0xa5,0x04,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xaa,0x04,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xaa,0x04,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xbe,0x04,0x00,0x00,0xfb,0x04,0x00,0x00,0x9a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa7,0x04,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa9,0x04,0x00,0x00,0xaa,0x00,0x05,0x00,0xb9,0x00,0x00,0x00,
-0xc0,0x04,0x00,0x00,0x71,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xc2,0x04,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xc0,0x04,0x00,0x00,0xc1,0x04,0x00,0x00,
-0xc2,0x04,0x00,0x00,0xf8,0x00,0x02,0x00,0xc1,0x04,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc9,0x04,0x00,0x00,
-0xf9,0x04,0x00,0x00,0x55,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0xae,0x00,0x00,0x00,0xca,0x04,0x00,0x00,0xa7,0x00,0x00,0x00,
-0x61,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xa4,0x00,0x00,0x00,
-0xcb,0x04,0x00,0x00,0xca,0x04,0x00,0x00,0x41,0x00,0x06,0x00,
-0xcc,0x04,0x00,0x00,0xcd,0x04,0x00,0x00,0xc6,0x04,0x00,0x00,
-0x61,0x00,0x00,0x00,0xc9,0x04,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xcd,0x04,0x00,0x00,0xcb,0x04,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xc2,0x04,0x00,0x00,0xf8,0x00,0x02,0x00,0xc2,0x04,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_q5_k_f16_f32_len = 13436;
-
-unsigned char mul_mat_vec_q5_k_f32_f32_data[] = {
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-0xdf,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
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-0x06,0x00,0x00,0x00,0x9f,0x04,0x00,0x00,0xdb,0x04,0x00,0x00,
-0x9a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x88,0x04,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x8a,0x04,0x00,0x00,0xaa,0x00,0x05,0x00,
-0xb9,0x00,0x00,0x00,0xa1,0x04,0x00,0x00,0x71,0x00,0x00,0x00,
-0x4b,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0xa3,0x04,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xa1,0x04,0x00,0x00,
-0xa2,0x04,0x00,0x00,0xa3,0x04,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa2,0x04,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xaa,0x04,0x00,0x00,0xd9,0x04,0x00,0x00,0x55,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0xae,0x00,0x00,0x00,0xab,0x04,0x00,0x00,
-0xa7,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0xa4,0x00,0x00,0x00,0xac,0x04,0x00,0x00,0xab,0x04,0x00,0x00,
-0x41,0x00,0x06,0x00,0x46,0x02,0x00,0x00,0xad,0x04,0x00,0x00,
-0xa7,0x04,0x00,0x00,0x61,0x00,0x00,0x00,0xaa,0x04,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xad,0x04,0x00,0x00,0xac,0x04,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa3,0x04,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa3,0x04,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t mul_mat_vec_q5_k_f32_f32_len = 12924;
-
-unsigned char mul_mat_vec_q6_k_f16_f32_data[] = {
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-0x6f,0x00,0x04,0x00,0x9d,0x00,0x00,0x00,0xf4,0x03,0x00,0x00,
-0xf3,0x03,0x00,0x00,0x0c,0x00,0x08,0x00,0x9d,0x00,0x00,0x00,
-0xf6,0x03,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0xdc,0x03,0x00,0x00,0xf4,0x03,0x00,0x00,0xce,0x03,0x00,0x00,
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-0xca,0x00,0x00,0x00,0xfb,0x03,0x00,0x00,0xdb,0x00,0x00,0x00,
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-0xc0,0x00,0x00,0x00,0xfc,0x03,0x00,0x00,0xfb,0x03,0x00,0x00,
-0x73,0x00,0x04,0x00,0x9d,0x00,0x00,0x00,0xfd,0x03,0x00,0x00,
-0xfc,0x03,0x00,0x00,0x3d,0x00,0x04,0x00,0xbe,0x00,0x00,0x00,
-0x01,0x04,0x00,0x00,0x97,0x01,0x00,0x00,0x6f,0x00,0x04,0x00,
-0x9d,0x00,0x00,0x00,0x02,0x04,0x00,0x00,0x01,0x04,0x00,0x00,
-0x85,0x00,0x05,0x00,0x9d,0x00,0x00,0x00,0x03,0x04,0x00,0x00,
-0xfd,0x03,0x00,0x00,0x02,0x04,0x00,0x00,0x85,0x00,0x05,0x00,
-0x9d,0x00,0x00,0x00,0x04,0x04,0x00,0x00,0x03,0x04,0x00,0x00,
-0xcd,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xbb,0x00,0x00,0x00,
-0x0a,0x04,0x00,0x00,0xb9,0x03,0x00,0x00,0xc2,0x00,0x05,0x00,
-0xbb,0x00,0x00,0x00,0x0b,0x04,0x00,0x00,0x0a,0x04,0x00,0x00,
-0x3b,0x00,0x00,0x00,0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x0c,0x04,0x00,0x00,0x0b,0x04,0x00,0x00,0x7c,0x00,0x04,0x00,
-0x1b,0x00,0x00,0x00,0x0d,0x04,0x00,0x00,0x0c,0x04,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xbb,0x00,0x00,0x00,0x12,0x04,0x00,0x00,
-0x9a,0x03,0x00,0x00,0xc2,0x00,0x05,0x00,0xbb,0x00,0x00,0x00,
-0x13,0x04,0x00,0x00,0x12,0x04,0x00,0x00,0x45,0x00,0x00,0x00,
-0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x14,0x04,0x00,0x00,
-0x13,0x04,0x00,0x00,0x7c,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,
-0x15,0x04,0x00,0x00,0x14,0x04,0x00,0x00,0xc7,0x00,0x05,0x00,
-0x1b,0x00,0x00,0x00,0x16,0x04,0x00,0x00,0x15,0x04,0x00,0x00,
-0xc9,0x00,0x00,0x00,0xc4,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,
-0x17,0x04,0x00,0x00,0x16,0x04,0x00,0x00,0x3b,0x00,0x00,0x00,
-0xc5,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,0x18,0x04,0x00,0x00,
-0x0d,0x04,0x00,0x00,0x17,0x04,0x00,0x00,0x72,0x00,0x04,0x00,
-0xbe,0x00,0x00,0x00,0x19,0x04,0x00,0x00,0x18,0x04,0x00,0x00,
-0x72,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,0x1a,0x04,0x00,0x00,
-0x19,0x04,0x00,0x00,0x82,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,
-0x1b,0x04,0x00,0x00,0x1a,0x04,0x00,0x00,0x14,0x01,0x00,0x00,
-0x6f,0x00,0x04,0x00,0x9d,0x00,0x00,0x00,0x1c,0x04,0x00,0x00,
-0x1b,0x04,0x00,0x00,0x0c,0x00,0x08,0x00,0x9d,0x00,0x00,0x00,
-0x1e,0x04,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x04,0x04,0x00,0x00,0x1c,0x04,0x00,0x00,0xf6,0x03,0x00,0x00,
-0x81,0x00,0x05,0x00,0x9d,0x00,0x00,0x00,0x1f,0x04,0x00,0x00,
-0x77,0x03,0x00,0x00,0x1e,0x04,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x9d,0x00,0x00,0x00,0xc9,0x01,0x00,0x00,0xa8,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x9d,0x00,0x00,0x00,0xca,0x01,0x00,0x00,
-0xc9,0x01,0x00,0x00,0x1f,0x04,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xa8,0x00,0x00,0x00,0xca,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xcd,0x01,0x00,0x00,0x23,0x02,0x00,0x00,
-0x51,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xab,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xad,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x51,0x00,0x00,0x00,0x51,0x00,0x00,0x00,0xce,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xd0,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd0,0x01,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x24,0x02,0x00,0x00,0xa1,0x00,0x00,0x00,0xad,0x00,0x00,0x00,
-0xe7,0x01,0x00,0x00,0xd3,0x01,0x00,0x00,0xac,0x00,0x05,0x00,
-0xb2,0x00,0x00,0x00,0xd6,0x01,0x00,0x00,0x24,0x02,0x00,0x00,
-0x4b,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xd2,0x01,0x00,0x00,
-0xd3,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xd6,0x01,0x00,0x00,0xd1,0x01,0x00,0x00,0xd2,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd1,0x01,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xb2,0x00,0x00,0x00,0xd9,0x01,0x00,0x00,0x71,0x00,0x00,0x00,
-0x24,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,0xdb,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xd9,0x01,0x00,0x00,
-0xda,0x01,0x00,0x00,0xdb,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xda,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdf,0x01,0x00,0x00,0x71,0x00,0x00,0x00,0x24,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0xa7,0x00,0x00,0x00,0xe0,0x01,0x00,0x00,
-0xa0,0x00,0x00,0x00,0xdf,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x9d,0x00,0x00,0x00,0xe1,0x01,0x00,0x00,0xe0,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0xa7,0x00,0x00,0x00,0xe2,0x01,0x00,0x00,
-0xa0,0x00,0x00,0x00,0x71,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x9d,0x00,0x00,0x00,0xe3,0x01,0x00,0x00,0xe2,0x01,0x00,0x00,
-0x81,0x00,0x05,0x00,0x9d,0x00,0x00,0x00,0xe4,0x01,0x00,0x00,
-0xe3,0x01,0x00,0x00,0xe1,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xe2,0x01,0x00,0x00,0xe4,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xdb,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0xdb,0x01,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x51,0x00,0x00,0x00,0x51,0x00,0x00,0x00,
-0xce,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0xd3,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd3,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe7,0x01,0x00,0x00,0x24,0x02,0x00,0x00,
-0x05,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0xd0,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd2,0x01,0x00,0x00,0xaa,0x00,0x05,0x00,
-0xb2,0x00,0x00,0x00,0xe9,0x01,0x00,0x00,0x71,0x00,0x00,0x00,
-0x4b,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0xeb,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xe9,0x01,0x00,0x00,
-0xea,0x01,0x00,0x00,0xeb,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xea,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xf2,0x01,0x00,0x00,0x22,0x02,0x00,0x00,0x55,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0xa7,0x00,0x00,0x00,0xf3,0x01,0x00,0x00,
-0xa0,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x9d,0x00,0x00,0x00,0xf4,0x01,0x00,0x00,0xf3,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0xf5,0x01,0x00,0x00,0xf6,0x01,0x00,0x00,
-0xef,0x01,0x00,0x00,0x61,0x00,0x00,0x00,0xf2,0x01,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xf6,0x01,0x00,0x00,0xf4,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xeb,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xeb,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t mul_mat_vec_q6_k_f16_f32_len = 12108;
-
-unsigned char mul_mat_vec_q6_k_f32_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x1d,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,
-0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0e,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x4a,0x00,0x00,0x00,
-0x4e,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,
-0xc5,0x00,0x00,0x00,0xdb,0x00,0x00,0x00,0xec,0x01,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x11,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x18,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x18,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x18,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x18,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x18,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4a,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x6e,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xbc,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xbd,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xbf,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x80,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0xc0,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xc1,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0xd0,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xc2,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0xd2,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0xc3,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0xc3,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0xc3,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xc5,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xc5,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
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-0x3d,0x00,0x04,0x00,0xbb,0x00,0x00,0x00,0xfa,0x03,0x00,0x00,
-0xab,0x03,0x00,0x00,0xc2,0x00,0x05,0x00,0xbb,0x00,0x00,0x00,
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-0x9d,0x00,0x00,0x00,0x0c,0x04,0x00,0x00,0x0b,0x04,0x00,0x00,
-0x0c,0x00,0x08,0x00,0x9d,0x00,0x00,0x00,0x0e,0x04,0x00,0x00,
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-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xd3,0x01,0x00,0x00,
-0xce,0x01,0x00,0x00,0xcf,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xce,0x01,0x00,0x00,0xb0,0x00,0x05,0x00,0xb2,0x00,0x00,0x00,
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-0xf7,0x00,0x03,0x00,0xd8,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xd6,0x01,0x00,0x00,0xd7,0x01,0x00,0x00,
-0xd8,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0xd7,0x01,0x00,0x00,
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-0xa7,0x00,0x00,0x00,0xdd,0x01,0x00,0x00,0xa0,0x00,0x00,0x00,
-0xdc,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x9d,0x00,0x00,0x00,
-0xde,0x01,0x00,0x00,0xdd,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0xa7,0x00,0x00,0x00,0xdf,0x01,0x00,0x00,0xa0,0x00,0x00,0x00,
-0x71,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x9d,0x00,0x00,0x00,
-0xe0,0x01,0x00,0x00,0xdf,0x01,0x00,0x00,0x81,0x00,0x05,0x00,
-0x9d,0x00,0x00,0x00,0xe1,0x01,0x00,0x00,0xe0,0x01,0x00,0x00,
-0xde,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0xdf,0x01,0x00,0x00,
-0xe1,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0xd8,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd8,0x01,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x51,0x00,0x00,0x00,0x51,0x00,0x00,0x00,0xcb,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xd0,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd0,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xe4,0x01,0x00,0x00,0x20,0x02,0x00,0x00,0x05,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xcd,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xcf,0x01,0x00,0x00,0xaa,0x00,0x05,0x00,0xb2,0x00,0x00,0x00,
-0xe6,0x01,0x00,0x00,0x71,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xe8,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xe6,0x01,0x00,0x00,0xe7,0x01,0x00,0x00,
-0xe8,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0xe7,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xef,0x01,0x00,0x00,
-0x1e,0x02,0x00,0x00,0x55,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0xa7,0x00,0x00,0x00,0xf0,0x01,0x00,0x00,0xa0,0x00,0x00,0x00,
-0x61,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x9d,0x00,0x00,0x00,
-0xf1,0x01,0x00,0x00,0xf0,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0xe3,0x00,0x00,0x00,0xf2,0x01,0x00,0x00,0xec,0x01,0x00,0x00,
-0x61,0x00,0x00,0x00,0xef,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xf2,0x01,0x00,0x00,0xf1,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe8,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0xe8,0x01,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_q6_k_f32_f32_len = 11852;
-
-unsigned char mul_mat_vec_q8_0_f16_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
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-0x05,0x01,0x00,0x00,0x9e,0x00,0x00,0x00,0x81,0x00,0x05,0x00,
-0x08,0x00,0x00,0x00,0x06,0x01,0x00,0x00,0x05,0x01,0x00,0x00,
-0x03,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x9e,0x00,0x00,0x00,
-0x06,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0xfd,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xfd,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x84,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xef,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xf5,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf5,0x00,0x00,0x00,0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x09,0x01,0x00,0x00,0x66,0x01,0x00,0x00,0x2d,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xf2,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf4,0x00,0x00,0x00,0xaa,0x00,0x05,0x00,0xa9,0x00,0x00,0x00,
-0x0b,0x01,0x00,0x00,0x8c,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x0d,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x0b,0x01,0x00,0x00,0x0c,0x01,0x00,0x00,
-0x0d,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x0c,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x14,0x01,0x00,0x00,
-0x45,0x01,0x00,0x00,0x88,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x9d,0x00,0x00,0x00,0x15,0x01,0x00,0x00,0x9a,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x16,0x01,0x00,0x00,0x15,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x17,0x01,0x00,0x00,0x18,0x01,0x00,0x00,0x11,0x01,0x00,0x00,
-0x22,0x00,0x00,0x00,0x14,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x18,0x01,0x00,0x00,0x16,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x0d,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x0d,0x01,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t mul_mat_vec_q8_0_f16_f32_len = 4064;
-
-unsigned char mul_mat_vec_q8_0_f32_f32_data[] = {
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-0x65,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
-0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
-0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
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-0x8a,0x00,0x00,0x00,0x9a,0x00,0x00,0x00,0xd2,0x00,0x00,0x00,
-0x10,0x01,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
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-0x47,0x00,0x04,0x00,0x46,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
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-0x48,0x00,0x05,0x00,0x4c,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4c,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4c,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4c,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4c,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x4c,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4c,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xd0,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xd0,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xd0,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xd2,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
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-0x08,0x00,0x00,0x00,0xea,0x00,0x00,0x00,0xe9,0x00,0x00,0x00,
-0xe7,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x9e,0x00,0x00,0x00,
-0xea,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xed,0x00,0x00,0x00,0x63,0x01,0x00,0x00,0x84,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xa0,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa2,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,0x84,0x00,0x00,0x00,
-0x84,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xf1,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xf1,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x64,0x01,0x00,0x00,
-0xf0,0x00,0x00,0x00,0xa2,0x00,0x00,0x00,0x08,0x01,0x00,0x00,
-0xf4,0x00,0x00,0x00,0xac,0x00,0x05,0x00,0xa9,0x00,0x00,0x00,
-0xf7,0x00,0x00,0x00,0x64,0x01,0x00,0x00,0x7e,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xf3,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xf7,0x00,0x00,0x00,
-0xf2,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf2,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,0xa9,0x00,0x00,0x00,
-0xfa,0x00,0x00,0x00,0x8c,0x00,0x00,0x00,0x64,0x01,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xfc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xfa,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,
-0xfc,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xfb,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x00,0x01,0x00,0x00,
-0x8c,0x00,0x00,0x00,0x64,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x9d,0x00,0x00,0x00,0x01,0x01,0x00,0x00,0x9a,0x00,0x00,0x00,
-0x00,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x08,0x00,0x00,0x00,
-0x02,0x01,0x00,0x00,0x01,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x04,0x01,0x00,0x00,0x9e,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x08,0x00,0x00,0x00,0x05,0x01,0x00,0x00,
-0x04,0x01,0x00,0x00,0x02,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x9e,0x00,0x00,0x00,0x05,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xfc,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xfc,0x00,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x84,0x00,0x00,0x00,0x84,0x00,0x00,0x00,
-0xee,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xf4,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf4,0x00,0x00,0x00,0xc2,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x08,0x01,0x00,0x00,0x64,0x01,0x00,0x00,
-0x2d,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xf1,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf3,0x00,0x00,0x00,0xaa,0x00,0x05,0x00,
-0xa9,0x00,0x00,0x00,0x0a,0x01,0x00,0x00,0x8c,0x00,0x00,0x00,
-0x7e,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x0c,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x0a,0x01,0x00,0x00,
-0x0b,0x01,0x00,0x00,0x0c,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x0b,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x13,0x01,0x00,0x00,0x43,0x01,0x00,0x00,0x88,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x9d,0x00,0x00,0x00,0x14,0x01,0x00,0x00,
-0x9a,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x08,0x00,0x00,0x00,0x15,0x01,0x00,0x00,0x14,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0xd8,0x00,0x00,0x00,0x16,0x01,0x00,0x00,
-0x10,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x13,0x01,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x16,0x01,0x00,0x00,0x15,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x0c,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x0c,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t mul_mat_vec_q8_0_f32_f32_len = 4032;
-
-unsigned char norm_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xb8,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0b,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x29,0x00,0x00,0x00,0x36,0x00,0x00,0x00,0x9a,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x27,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x27,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x27,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x27,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x27,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x33,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x34,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x34,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x34,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x36,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x36,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x97,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x98,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x98,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x98,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x9a,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x9a,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xb0,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0x14,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x1c,0x00,0x04,0x00,0x17,0x00,0x00,0x00,
-0x15,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x18,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x17,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x18,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x14,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x2c,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x1d,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x15,0x00,0x00,0x00,0x1e,0x00,0x06,0x00,
-0x27,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x28,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x28,0x00,0x00,0x00,0x29,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x2a,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x2a,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x2c,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x14,0x00,0x02,0x00,0x2f,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0x33,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x1e,0x00,0x03,0x00,0x34,0x00,0x00,0x00,0x33,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x35,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x34,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x35,0x00,0x00,0x00,
-0x36,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x3d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x42,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x4b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x52,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x53,0x00,0x00,0x00,
-0x08,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x2a,0x00,0x00,0x00,
-0x56,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x2a,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x2a,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x87,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x97,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x98,0x00,0x00,0x00,0x97,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x99,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x98,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x99,0x00,0x00,0x00,0x9a,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x2c,0x00,0x06,0x00,0x09,0x00,0x00,0x00,
-0xb0,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,
-0x4b,0x00,0x00,0x00,0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x0d,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x0d,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1d,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x1e,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x21,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x21,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xb1,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x51,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x2c,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,
-0x29,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x2f,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0xb1,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x23,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x30,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x22,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0xb1,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x3d,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x36,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,
-0x3c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x14,0x00,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x42,0x00,0x00,0x00,0x43,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x14,0x00,0x00,0x00,0x44,0x00,0x00,0x00,0x43,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x14,0x00,0x00,0x00,0x45,0x00,0x00,0x00,
-0x44,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x43,0x00,0x00,0x00,0x45,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x42,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x14,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,
-0x0c,0x00,0x08,0x00,0x14,0x00,0x00,0x00,0x4e,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x4c,0x00,0x00,0x00,0x4e,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x51,0x00,0x00,0x00,0xb1,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x21,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x23,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x52,0x00,0x00,0x00,0x52,0x00,0x00,0x00,0x53,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x57,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x57,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x2a,0x00,0x00,0x00,
-0xb2,0x00,0x00,0x00,0x56,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x71,0x00,0x00,0x00,0x5a,0x00,0x00,0x00,0xad,0x00,0x05,0x00,
-0x2f,0x00,0x00,0x00,0x5d,0x00,0x00,0x00,0xb2,0x00,0x00,0x00,
-0x2b,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x59,0x00,0x00,0x00,
-0x5a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x5d,0x00,0x00,0x00,0x58,0x00,0x00,0x00,0x59,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x58,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0xb2,0x00,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x2f,0x00,0x00,0x00,0x61,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x63,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x61,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x63,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x62,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x68,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x60,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x1d,0x00,0x00,0x00,
-0x69,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x68,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x6a,0x00,0x00,0x00,
-0x69,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x6c,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,0x81,0x00,0x05,0x00,
-0x15,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,
-0x6a,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x1e,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x63,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x63,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x52,0x00,0x00,0x00,0x52,0x00,0x00,0x00,0x53,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5a,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5a,0x00,0x00,0x00,0xc3,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,
-0x71,0x00,0x00,0x00,0xb2,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x57,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x59,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x42,0x00,0x00,0x00,
-0x73,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x14,0x00,0x00,0x00,
-0x74,0x00,0x00,0x00,0x73,0x00,0x00,0x00,0x70,0x00,0x04,0x00,
-0x14,0x00,0x00,0x00,0x77,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,
-0x88,0x00,0x05,0x00,0x14,0x00,0x00,0x00,0x78,0x00,0x00,0x00,
-0x74,0x00,0x00,0x00,0x77,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x42,0x00,0x00,0x00,0x7a,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x2b,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x14,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,0x7a,0x00,0x00,0x00,
-0x88,0x00,0x05,0x00,0x14,0x00,0x00,0x00,0x7f,0x00,0x00,0x00,
-0x7b,0x00,0x00,0x00,0x77,0x00,0x00,0x00,0x7f,0x00,0x04,0x00,
-0x14,0x00,0x00,0x00,0xb7,0x00,0x00,0x00,0x78,0x00,0x00,0x00,
-0x0c,0x00,0x08,0x00,0x14,0x00,0x00,0x00,0x83,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0xb7,0x00,0x00,0x00,
-0x78,0x00,0x00,0x00,0x7f,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x87,0x00,0x00,0x00,0x88,0x00,0x00,0x00,0x29,0x00,0x00,0x00,
-0x86,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x14,0x00,0x00,0x00,
-0x89,0x00,0x00,0x00,0x88,0x00,0x00,0x00,0x81,0x00,0x05,0x00,
-0x14,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,0x83,0x00,0x00,0x00,
-0x89,0x00,0x00,0x00,0x0c,0x00,0x06,0x00,0x14,0x00,0x00,0x00,
-0x8b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x8a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x8e,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x8e,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xb3,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x59,0x00,0x00,0x00,0xaf,0x00,0x00,0x00,0x8f,0x00,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x2f,0x00,0x00,0x00,0x96,0x00,0x00,0x00,
-0xb3,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x90,0x00,0x00,0x00,0x8f,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x96,0x00,0x00,0x00,0x8f,0x00,0x00,0x00,
-0x90,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x8f,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9e,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,0x9e,0x00,0x00,0x00,
-0xb3,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x3d,0x00,0x00,0x00,
-0xa7,0x00,0x00,0x00,0x36,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,
-0xa0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x14,0x00,0x00,0x00,
-0xa8,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0x83,0x00,0x05,0x00,
-0x14,0x00,0x00,0x00,0xaa,0x00,0x00,0x00,0xa8,0x00,0x00,0x00,
-0x78,0x00,0x00,0x00,0x85,0x00,0x05,0x00,0x14,0x00,0x00,0x00,
-0xac,0x00,0x00,0x00,0xaa,0x00,0x00,0x00,0x8b,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x3d,0x00,0x00,0x00,0xad,0x00,0x00,0x00,
-0x9a,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xad,0x00,0x00,0x00,0xac,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xaf,0x00,0x00,0x00,
-0xb3,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x8e,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x90,0x00,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t norm_f32_len = 2624;
-
-unsigned char relu_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x34,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x09,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x12,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1f,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x20,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x22,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x22,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x24,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x25,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x25,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x25,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x27,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x27,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x31,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x11,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x1e,0x00,0x06,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x13,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x13,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x17,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x14,0x00,0x02,0x00,0x1a,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x1f,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x20,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x21,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x21,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0x24,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0x25,0x00,0x00,0x00,
-0x24,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x26,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x25,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x26,0x00,0x00,0x00,0x27,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x29,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x2f,0x00,0x00,0x00,0x00,0x02,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2c,0x00,0x06,0x00,0x09,0x00,0x00,0x00,
-0x31,0x00,0x00,0x00,0x2f,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x30,0x00,0x00,0x00,0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x32,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfb,0x00,0x03,0x00,
-0x0c,0x00,0x00,0x00,0x33,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x33,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0xae,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x1d,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x1d,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x1c,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x32,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x1d,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x29,0x00,0x00,0x00,
-0x2a,0x00,0x00,0x00,0x27,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
-0x2b,0x00,0x00,0x00,0x2a,0x00,0x00,0x00,0x0c,0x00,0x07,0x00,
-0x11,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x29,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x2e,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x32,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x32,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t relu_f32_len = 1212;
-
-unsigned char rms_norm_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x9e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0b,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x85,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x25,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x25,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x25,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x25,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x25,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x31,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x32,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x32,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x32,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x34,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x34,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x82,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x83,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x83,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x83,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x85,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x85,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x9a,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0x14,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x15,0x00,0x00,0x00,0x00,0x02,0x00,0x00,
-0x1c,0x00,0x04,0x00,0x16,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x15,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x17,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x17,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x14,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x1e,0x00,0x06,0x00,
-0x25,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x26,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x26,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x28,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x28,0x00,0x00,0x00,0x29,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x2a,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x14,0x00,0x02,0x00,0x2d,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0x31,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x1e,0x00,0x03,0x00,0x32,0x00,0x00,0x00,0x31,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x33,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x33,0x00,0x00,0x00,
-0x34,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x3b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x48,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x49,0x00,0x00,0x00,0x08,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x28,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,0x00,0x01,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x28,0x00,0x00,0x00,0x65,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x28,0x00,0x00,0x00,
-0x71,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x72,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0x82,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x1e,0x00,0x03,0x00,0x83,0x00,0x00,0x00,0x82,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x84,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x83,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x84,0x00,0x00,0x00,
-0x85,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x99,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2c,0x00,0x06,0x00,0x09,0x00,0x00,0x00,0x9a,0x00,0x00,0x00,
-0x15,0x00,0x00,0x00,0x99,0x00,0x00,0x00,0x99,0x00,0x00,0x00,
-0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x05,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,
-0x12,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x12,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x1c,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x1f,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x1f,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x9b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x47,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x2a,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x29,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x2d,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,0x9b,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x21,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x2e,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x20,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x9b,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x3b,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,
-0x34,0x00,0x00,0x00,0x29,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x14,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,
-0x3c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x14,0x00,0x00,0x00,
-0x43,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,
-0x14,0x00,0x00,0x00,0x44,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,
-0x43,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x1c,0x00,0x00,0x00,
-0x44,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x47,0x00,0x00,0x00,0x9b,0x00,0x00,0x00,0x15,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x1f,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x21,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,0x48,0x00,0x00,0x00,
-0x48,0x00,0x00,0x00,0x49,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x4d,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x4d,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x28,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,
-0x4c,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x67,0x00,0x00,0x00,
-0x50,0x00,0x00,0x00,0xad,0x00,0x05,0x00,0x2d,0x00,0x00,0x00,
-0x53,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,0x29,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x4f,0x00,0x00,0x00,0x50,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x53,0x00,0x00,0x00,
-0x4e,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x4e,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x56,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x2d,0x00,0x00,0x00,0x57,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x56,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x59,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x57,0x00,0x00,0x00,
-0x58,0x00,0x00,0x00,0x59,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x58,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x5e,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x56,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,0x5f,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x5e,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x14,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x5f,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x14,0x00,0x00,0x00,0x62,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x81,0x00,0x05,0x00,0x14,0x00,0x00,0x00,
-0x63,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x60,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x1c,0x00,0x00,0x00,0x63,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x59,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x59,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,0x48,0x00,0x00,0x00,
-0x48,0x00,0x00,0x00,0x49,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x50,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x50,0x00,0x00,0x00,
-0xc3,0x00,0x05,0x00,0x28,0x00,0x00,0x00,0x67,0x00,0x00,0x00,
-0x9c,0x00,0x00,0x00,0x65,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x4d,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x4f,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,0x69,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x29,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x14,0x00,0x00,0x00,0x6a,0x00,0x00,0x00,0x69,0x00,0x00,0x00,
-0x70,0x00,0x04,0x00,0x14,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x88,0x00,0x05,0x00,0x14,0x00,0x00,0x00,
-0x6e,0x00,0x00,0x00,0x6a,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x72,0x00,0x00,0x00,0x73,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0x71,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x14,0x00,0x00,0x00,0x74,0x00,0x00,0x00,0x73,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x14,0x00,0x00,0x00,0x75,0x00,0x00,0x00,
-0x6e,0x00,0x00,0x00,0x74,0x00,0x00,0x00,0x0c,0x00,0x06,0x00,
-0x14,0x00,0x00,0x00,0x76,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x75,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x79,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x79,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x98,0x00,0x00,0x00,
-0x7a,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,0x2d,0x00,0x00,0x00,
-0x81,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0x7b,0x00,0x00,0x00,0x7a,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x81,0x00,0x00,0x00,
-0x7a,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7a,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x89,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8b,0x00,0x00,0x00,
-0x89,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x3b,0x00,0x00,0x00,0x93,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
-0x29,0x00,0x00,0x00,0x8b,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x14,0x00,0x00,0x00,0x94,0x00,0x00,0x00,0x93,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x14,0x00,0x00,0x00,0x95,0x00,0x00,0x00,
-0x76,0x00,0x00,0x00,0x94,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x3b,0x00,0x00,0x00,0x96,0x00,0x00,0x00,0x85,0x00,0x00,0x00,
-0x29,0x00,0x00,0x00,0x8b,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x96,0x00,0x00,0x00,0x95,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x98,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,
-0x15,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x79,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x7b,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t rms_norm_f32_len = 2344;
-
-unsigned char rope_neox_f16_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x50,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0b,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,
-0x67,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,0x90,0x00,0x00,0x00,
-0xb1,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x00,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x28,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x29,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x29,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x29,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x29,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x67,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x87,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x88,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x88,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x88,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x8a,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x8a,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x8d,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x8e,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x8e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x8e,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x90,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x90,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xae,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xaf,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xaf,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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-0xb6,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x72,0x00,0x00,0x00,0xc2,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,
-0xc1,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x07,0x00,0x00,0x00,
-0xc3,0x00,0x00,0x00,0xc2,0x00,0x00,0x00,0xab,0x00,0x05,0x00,
-0x3b,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,
-0x6e,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0xc7,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,
-0xc6,0x00,0x00,0x00,0xd1,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xc6,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0xce,0x00,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0xa5,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xc7,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xd1,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xc7,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xc7,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x4a,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,
-0x1f,0x00,0x00,0x00,0xd1,0x00,0x00,0x00,0x88,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd5,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,
-0x4a,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x2e,0x00,0x00,0x00,
-0x13,0x01,0x00,0x00,0x2b,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x14,0x01,0x00,0x00,
-0x13,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x2e,0x00,0x00,0x00,
-0x15,0x01,0x00,0x00,0x2b,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x16,0x01,0x00,0x00,
-0x15,0x01,0x00,0x00,0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x17,0x01,0x00,0x00,0x16,0x01,0x00,0x00,0xd5,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x2e,0x00,0x00,0x00,0x19,0x01,0x00,0x00,
-0x2b,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x1a,0x01,0x00,0x00,0x19,0x01,0x00,0x00,
-0xb7,0x00,0x05,0x00,0x3b,0x00,0x00,0x00,0x1b,0x01,0x00,0x00,
-0x1a,0x01,0x00,0x00,0x20,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x34,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x1b,0x01,0x00,0x00,0x1c,0x01,0x00,0x00,0x34,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x1c,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x2e,0x00,0x00,0x00,0x1d,0x01,0x00,0x00,0x2b,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x1e,0x01,0x00,0x00,0x1d,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0x2e,0x00,0x00,0x00,0x1f,0x01,0x00,0x00,
-0x2b,0x00,0x00,0x00,0x40,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x01,0x00,0x00,
-0x1f,0x01,0x00,0x00,0x70,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x41,0x01,0x00,0x00,0xa5,0x00,0x00,0x00,0x83,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x42,0x01,0x00,0x00,0x41,0x01,0x00,0x00,
-0x1e,0x01,0x00,0x00,0x83,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x43,0x01,0x00,0x00,0x20,0x01,0x00,0x00,0x1e,0x01,0x00,0x00,
-0x0c,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x44,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x43,0x01,0x00,0x00,0x88,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x45,0x01,0x00,0x00,0x42,0x01,0x00,0x00,0x44,0x01,0x00,0x00,
-0x0c,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x47,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x45,0x01,0x00,0x00,0x0c,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x48,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0x1f,0x00,0x00,0x00,0x47,0x01,0x00,0x00,0x83,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x49,0x01,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x48,0x01,0x00,0x00,0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x24,0x01,0x00,0x00,0x49,0x01,0x00,0x00,0x1a,0x01,0x00,0x00,
-0x83,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x4e,0x01,0x00,0x00,
-0x48,0x01,0x00,0x00,0x1f,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,
-0x06,0x00,0x00,0x00,0x27,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0x4e,0x01,0x00,0x00,0x1a,0x01,0x00,0x00,
-0x1f,0x00,0x00,0x00,0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x2a,0x01,0x00,0x00,0xd5,0x00,0x00,0x00,0x24,0x01,0x00,0x00,
-0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,0x2b,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x17,0x01,0x00,0x00,
-0x27,0x01,0x00,0x00,0x2a,0x01,0x00,0x00,0x88,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x2e,0x01,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x16,0x01,0x00,0x00,0x0c,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x2f,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x2e,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,
-0x31,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x52,0x00,0x00,0x00,0x2f,0x01,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x33,0x01,0x00,0x00,
-0x14,0x01,0x00,0x00,0x31,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x34,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x34,0x01,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x4c,0x01,0x00,0x00,
-0x14,0x01,0x00,0x00,0xc7,0x00,0x00,0x00,0x33,0x01,0x00,0x00,
-0x1c,0x01,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x4b,0x01,0x00,0x00,0x17,0x01,0x00,0x00,0xc7,0x00,0x00,0x00,
-0x2b,0x01,0x00,0x00,0x1c,0x01,0x00,0x00,0x0c,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x36,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x4b,0x01,0x00,0x00,0x85,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x38,0x01,0x00,0x00,0x36,0x01,0x00,0x00,
-0x4c,0x01,0x00,0x00,0x0c,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x3a,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
-0x4b,0x01,0x00,0x00,0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x3c,0x01,0x00,0x00,0x3a,0x01,0x00,0x00,0x4c,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0x93,0x00,0x00,0x00,0xe1,0x00,0x00,0x00,
-0x90,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0xa6,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x86,0x00,0x00,0x00,0xe2,0x00,0x00,0x00,
-0xe1,0x00,0x00,0x00,0x73,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xe3,0x00,0x00,0x00,0xe2,0x00,0x00,0x00,0x86,0x00,0x05,0x00,
-0x07,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0x17,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x07,0x00,0x00,0x00,
-0xe9,0x00,0x00,0x00,0xa6,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x93,0x00,0x00,0x00,0xea,0x00,0x00,0x00,
-0x90,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0xe9,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x86,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
-0xea,0x00,0x00,0x00,0x73,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xec,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,0x85,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,0xec,0x00,0x00,0x00,
-0x3c,0x01,0x00,0x00,0x7f,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x4f,0x01,0x00,0x00,0xf4,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,
-0x06,0x00,0x00,0x00,0xf5,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0xe3,0x00,0x00,0x00,0x38,0x01,0x00,0x00,
-0x4f,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x86,0x00,0x00,0x00,
-0xf6,0x00,0x00,0x00,0xf5,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x93,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,
-0x41,0x00,0x00,0x00,0xa6,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xf7,0x00,0x00,0x00,0xf6,0x00,0x00,0x00,0x85,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x02,0x01,0x00,0x00,0xec,0x00,0x00,0x00,
-0x38,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,
-0x03,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0xe3,0x00,0x00,0x00,0x3c,0x01,0x00,0x00,0x02,0x01,0x00,0x00,
-0x73,0x00,0x04,0x00,0x86,0x00,0x00,0x00,0x04,0x01,0x00,0x00,
-0x03,0x01,0x00,0x00,0x41,0x00,0x06,0x00,0x93,0x00,0x00,0x00,
-0x05,0x01,0x00,0x00,0x8a,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0xe9,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x05,0x01,0x00,0x00,
-0x04,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x08,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x08,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t rope_neox_f16_len = 3952;
-
-unsigned char rope_neox_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x4a,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0b,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x2b,0x00,0x00,0x00,0x67,0x00,0x00,0x00,0x89,0x00,0x00,0x00,
-0x8f,0x00,0x00,0x00,0xb0,0x00,0x00,0x00,0xca,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x28,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x29,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x29,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x29,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x29,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x67,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x86,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
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-0xab,0x00,0x00,0x00,0x70,0x00,0x00,0x00,0xaa,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0xb2,0x00,0x00,0x00,0xb3,0x00,0x00,0x00,
-0xb0,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0xab,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x2c,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,
-0xb3,0x00,0x00,0x00,0x6f,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xb5,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x2e,0x00,0x00,0x00,0xb7,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,
-0xb6,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xb8,0x00,0x00,0x00,0xb7,0x00,0x00,0x00,0x70,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xba,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,
-0xba,0x00,0x00,0x00,0x47,0x01,0x00,0x00,0x0c,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,
-0xb5,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x72,0x00,0x00,0x00,0xc1,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,
-0xc0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x07,0x00,0x00,0x00,
-0xc2,0x00,0x00,0x00,0xc1,0x00,0x00,0x00,0xab,0x00,0x05,0x00,
-0x3b,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0xc2,0x00,0x00,0x00,
-0x6e,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0xc6,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,
-0xc5,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xc5,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x92,0x00,0x00,0x00,
-0xcd,0x00,0x00,0x00,0xca,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0xa4,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xce,0x00,0x00,0x00,0xcd,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xc6,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xcf,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xc6,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xc6,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x44,0x01,0x00,0x00,0xce,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,
-0x1f,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x88,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd3,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,
-0x44,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x2e,0x00,0x00,0x00,
-0x0d,0x01,0x00,0x00,0x2b,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0e,0x01,0x00,0x00,
-0x0d,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x2e,0x00,0x00,0x00,
-0x0f,0x01,0x00,0x00,0x2b,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x10,0x01,0x00,0x00,
-0x0f,0x01,0x00,0x00,0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x11,0x01,0x00,0x00,0x10,0x01,0x00,0x00,0xd3,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x2e,0x00,0x00,0x00,0x13,0x01,0x00,0x00,
-0x2b,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x14,0x01,0x00,0x00,0x13,0x01,0x00,0x00,
-0xb7,0x00,0x05,0x00,0x3b,0x00,0x00,0x00,0x15,0x01,0x00,0x00,
-0x14,0x01,0x00,0x00,0x20,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x2e,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x15,0x01,0x00,0x00,0x16,0x01,0x00,0x00,0x2e,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x16,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x2e,0x00,0x00,0x00,0x17,0x01,0x00,0x00,0x2b,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x18,0x01,0x00,0x00,0x17,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0x2e,0x00,0x00,0x00,0x19,0x01,0x00,0x00,
-0x2b,0x00,0x00,0x00,0x40,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x1a,0x01,0x00,0x00,
-0x19,0x01,0x00,0x00,0x70,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x3b,0x01,0x00,0x00,0xa4,0x00,0x00,0x00,0x83,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x3c,0x01,0x00,0x00,0x3b,0x01,0x00,0x00,
-0x18,0x01,0x00,0x00,0x83,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x3d,0x01,0x00,0x00,0x1a,0x01,0x00,0x00,0x18,0x01,0x00,0x00,
-0x0c,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x3e,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x3d,0x01,0x00,0x00,0x88,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x3f,0x01,0x00,0x00,0x3c,0x01,0x00,0x00,0x3e,0x01,0x00,0x00,
-0x0c,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x41,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x3f,0x01,0x00,0x00,0x0c,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x42,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0x1f,0x00,0x00,0x00,0x41,0x01,0x00,0x00,0x83,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x43,0x01,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x42,0x01,0x00,0x00,0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x1e,0x01,0x00,0x00,0x43,0x01,0x00,0x00,0x14,0x01,0x00,0x00,
-0x83,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x48,0x01,0x00,0x00,
-0x42,0x01,0x00,0x00,0x1f,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,
-0x06,0x00,0x00,0x00,0x21,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0x48,0x01,0x00,0x00,0x14,0x01,0x00,0x00,
-0x1f,0x00,0x00,0x00,0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x24,0x01,0x00,0x00,0xd3,0x00,0x00,0x00,0x1e,0x01,0x00,0x00,
-0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,0x25,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x11,0x01,0x00,0x00,
-0x21,0x01,0x00,0x00,0x24,0x01,0x00,0x00,0x88,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x28,0x01,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x10,0x01,0x00,0x00,0x0c,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x29,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x28,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,
-0x2b,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x52,0x00,0x00,0x00,0x29,0x01,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x2d,0x01,0x00,0x00,
-0x0e,0x01,0x00,0x00,0x2b,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x2e,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x2e,0x01,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x46,0x01,0x00,0x00,
-0x0e,0x01,0x00,0x00,0xc6,0x00,0x00,0x00,0x2d,0x01,0x00,0x00,
-0x16,0x01,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x45,0x01,0x00,0x00,0x11,0x01,0x00,0x00,0xc6,0x00,0x00,0x00,
-0x25,0x01,0x00,0x00,0x16,0x01,0x00,0x00,0x0c,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x30,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x45,0x01,0x00,0x00,0x85,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x32,0x01,0x00,0x00,0x30,0x01,0x00,0x00,
-0x46,0x01,0x00,0x00,0x0c,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x34,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
-0x45,0x01,0x00,0x00,0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x36,0x01,0x00,0x00,0x34,0x01,0x00,0x00,0x46,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0x92,0x00,0x00,0x00,0xdf,0x00,0x00,0x00,
-0x8f,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,
-0xdf,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x07,0x00,0x00,0x00,
-0xe5,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,0x17,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x07,0x00,0x00,0x00,0xe6,0x00,0x00,0x00,
-0xa5,0x00,0x00,0x00,0xe5,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x92,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,0x8f,0x00,0x00,0x00,
-0x41,0x00,0x00,0x00,0xe6,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,
-0xe8,0x00,0x00,0x00,0x36,0x01,0x00,0x00,0x7f,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x49,0x01,0x00,0x00,0xf0,0x00,0x00,0x00,
-0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,
-0x32,0x01,0x00,0x00,0x49,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x92,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,0x89,0x00,0x00,0x00,
-0x41,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xf2,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,0x85,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,
-0x32,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,
-0xfe,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0xe0,0x00,0x00,0x00,0x36,0x01,0x00,0x00,0xfd,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x92,0x00,0x00,0x00,0xff,0x00,0x00,0x00,
-0x89,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0xe6,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xff,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x02,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x02,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t rope_neox_f32_len = 3852;
-
-unsigned char rope_norm_f16_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x49,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0b,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,
-0x67,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,0x90,0x00,0x00,0x00,
-0xb0,0x00,0x00,0x00,0xca,0x00,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x00,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x28,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x29,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x29,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x29,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
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-0x41,0x00,0x06,0x00,0x93,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,
-0x8a,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0x98,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x9d,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x01,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x7e,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x07,0x00,0x00,0x00,
-0xa3,0x00,0x00,0x00,0x70,0x00,0x00,0x00,0x74,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x07,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,
-0xa3,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x72,0x00,0x00,0x00,0xa9,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,
-0xa8,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x07,0x00,0x00,0x00,
-0xaa,0x00,0x00,0x00,0xa9,0x00,0x00,0x00,0x86,0x00,0x05,0x00,
-0x07,0x00,0x00,0x00,0xab,0x00,0x00,0x00,0x70,0x00,0x00,0x00,
-0xaa,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0xb2,0x00,0x00,0x00,
-0xb3,0x00,0x00,0x00,0xb0,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0xab,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x2c,0x00,0x00,0x00,
-0xb4,0x00,0x00,0x00,0xb3,0x00,0x00,0x00,0x6f,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xb5,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x2e,0x00,0x00,0x00,0xb7,0x00,0x00,0x00,
-0x2b,0x00,0x00,0x00,0xb6,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,0xb7,0x00,0x00,0x00,
-0x70,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xba,0x00,0x00,0x00,
-0x6c,0x00,0x00,0x00,0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xbc,0x00,0x00,0x00,0xba,0x00,0x00,0x00,0x46,0x01,0x00,0x00,
-0x0c,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,
-0xbc,0x00,0x00,0x00,0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xbe,0x00,0x00,0x00,0xb5,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x72,0x00,0x00,0x00,0xc1,0x00,0x00,0x00,
-0x2b,0x00,0x00,0x00,0xc0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x07,0x00,0x00,0x00,0xc2,0x00,0x00,0x00,0xc1,0x00,0x00,0x00,
-0xab,0x00,0x05,0x00,0x3b,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,
-0xc2,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xc6,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xc3,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xc5,0x00,0x00,0x00,0x86,0x00,0x05,0x00,
-0x07,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,
-0x17,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0xcd,0x00,0x00,0x00,
-0xce,0x00,0x00,0x00,0xca,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0xcc,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xcf,0x00,0x00,0x00,0xce,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xc6,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xc6,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xc6,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x43,0x01,0x00,0x00,0xcf,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,
-0x1f,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x88,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xd4,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,
-0x43,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x2e,0x00,0x00,0x00,
-0x0c,0x01,0x00,0x00,0x2b,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0d,0x01,0x00,0x00,
-0x0c,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x2e,0x00,0x00,0x00,
-0x0e,0x01,0x00,0x00,0x2b,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0f,0x01,0x00,0x00,
-0x0e,0x01,0x00,0x00,0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x10,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,0xd4,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x2e,0x00,0x00,0x00,0x12,0x01,0x00,0x00,
-0x2b,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x13,0x01,0x00,0x00,0x12,0x01,0x00,0x00,
-0xb7,0x00,0x05,0x00,0x3b,0x00,0x00,0x00,0x14,0x01,0x00,0x00,
-0x13,0x01,0x00,0x00,0x20,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x2d,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x14,0x01,0x00,0x00,0x15,0x01,0x00,0x00,0x2d,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x15,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x2e,0x00,0x00,0x00,0x16,0x01,0x00,0x00,0x2b,0x00,0x00,0x00,
-0x40,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x17,0x01,0x00,0x00,0x16,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0x2e,0x00,0x00,0x00,0x18,0x01,0x00,0x00,
-0x2b,0x00,0x00,0x00,0x40,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x19,0x01,0x00,0x00,
-0x18,0x01,0x00,0x00,0x86,0x00,0x05,0x00,0x07,0x00,0x00,0x00,
-0x39,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0x17,0x00,0x00,0x00,
-0x70,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x3a,0x01,0x00,0x00,
-0x39,0x01,0x00,0x00,0x83,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x3b,0x01,0x00,0x00,0x3a,0x01,0x00,0x00,0x17,0x01,0x00,0x00,
-0x83,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x3c,0x01,0x00,0x00,
-0x19,0x01,0x00,0x00,0x17,0x01,0x00,0x00,0x0c,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x3d,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x3c,0x01,0x00,0x00,
-0x88,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x3e,0x01,0x00,0x00,
-0x3b,0x01,0x00,0x00,0x3d,0x01,0x00,0x00,0x0c,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x40,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x3e,0x01,0x00,0x00,
-0x0c,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x41,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x25,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x40,0x01,0x00,0x00,0x83,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x42,0x01,0x00,0x00,0x1f,0x00,0x00,0x00,0x41,0x01,0x00,0x00,
-0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1d,0x01,0x00,0x00,
-0x42,0x01,0x00,0x00,0x13,0x01,0x00,0x00,0x83,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x47,0x01,0x00,0x00,0x41,0x01,0x00,0x00,
-0x1f,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,
-0x20,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x47,0x01,0x00,0x00,0x13,0x01,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x23,0x01,0x00,0x00,
-0xd4,0x00,0x00,0x00,0x1d,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,
-0x06,0x00,0x00,0x00,0x24,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0x10,0x01,0x00,0x00,0x20,0x01,0x00,0x00,
-0x23,0x01,0x00,0x00,0x88,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x27,0x01,0x00,0x00,0x1f,0x00,0x00,0x00,0x0f,0x01,0x00,0x00,
-0x0c,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x28,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x27,0x01,0x00,0x00,
-0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,0x2a,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x52,0x00,0x00,0x00,
-0x28,0x01,0x00,0x00,0x1f,0x00,0x00,0x00,0x85,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x2c,0x01,0x00,0x00,0x0d,0x01,0x00,0x00,
-0x2a,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x2d,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x2d,0x01,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x45,0x01,0x00,0x00,0x0d,0x01,0x00,0x00,
-0xc6,0x00,0x00,0x00,0x2c,0x01,0x00,0x00,0x15,0x01,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x44,0x01,0x00,0x00,
-0x10,0x01,0x00,0x00,0xc6,0x00,0x00,0x00,0x24,0x01,0x00,0x00,
-0x15,0x01,0x00,0x00,0x0c,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x2f,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,
-0x44,0x01,0x00,0x00,0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x31,0x01,0x00,0x00,0x2f,0x01,0x00,0x00,0x45,0x01,0x00,0x00,
-0x0c,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x33,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x44,0x01,0x00,0x00,
-0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x35,0x01,0x00,0x00,
-0x33,0x01,0x00,0x00,0x45,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x93,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,0x90,0x00,0x00,0x00,
-0x41,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x86,0x00,0x00,0x00,0xe1,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,
-0x73,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xe2,0x00,0x00,0x00,
-0xe1,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x07,0x00,0x00,0x00,
-0xe5,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,0x68,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x93,0x00,0x00,0x00,0xe6,0x00,0x00,0x00,
-0x90,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0xe5,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x86,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,
-0xe6,0x00,0x00,0x00,0x73,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xe8,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,0x85,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,
-0x35,0x01,0x00,0x00,0x7f,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x48,0x01,0x00,0x00,0xf0,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,
-0x06,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0xe2,0x00,0x00,0x00,0x31,0x01,0x00,0x00,
-0x48,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x86,0x00,0x00,0x00,
-0xf2,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x93,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,
-0x41,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xf3,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,0x85,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,
-0x31,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,
-0xfc,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0xe2,0x00,0x00,0x00,0x35,0x01,0x00,0x00,0xfb,0x00,0x00,0x00,
-0x73,0x00,0x04,0x00,0x86,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,
-0xfc,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x93,0x00,0x00,0x00,
-0xfe,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0xe5,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0xfe,0x00,0x00,0x00,
-0xfd,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x01,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x01,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t rope_norm_f16_len = 3952;
-
-unsigned char rope_norm_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x43,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
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-0xf9,0x00,0x02,0x00,0xfb,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xfb,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t rope_norm_f32_len = 3852;
-
-unsigned char scale_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x9c,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x09,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0xd7,0x00,0x00,0x00,
-0xe3,0x00,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x38,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x40,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x44,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x12,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x48,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xc7,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xd4,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xd5,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xd5,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xd5,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xd7,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xd7,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xe0,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xe1,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xe1,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xe1,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xe3,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xe3,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xf3,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,
-0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x11,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x1e,0x00,0x16,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x13,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x17,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x55,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x5a,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x66,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x6f,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x72,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x76,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0xad,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0xb2,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0xbe,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0xc5,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0xc6,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0xc5,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0xc6,0x00,0x00,0x00,
-0xc7,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0xc9,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0xcc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x14,0x00,0x02,0x00,
-0xcf,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0xd4,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0xd5,0x00,0x00,0x00,
-0xd4,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xd6,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0xd5,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0xd6,0x00,0x00,0x00,0xd7,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xd8,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0xe0,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0xe1,0x00,0x00,0x00,
-0xe0,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xe2,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0xe1,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0xe2,0x00,0x00,0x00,0xe3,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0xe8,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0xeb,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0xec,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xf2,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2c,0x00,0x06,0x00,
-0xc5,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,
-0xf2,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,0x36,0x00,0x05,0x00,
-0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xf4,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfb,0x00,0x03,0x00,0xc8,0x00,0x00,0x00,0xf5,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf5,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0xc9,0x00,0x00,0x00,0xca,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,
-0xc8,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xcb,0x00,0x00,0x00,0xca,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0xcd,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0xcc,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xce,0x00,0x00,0x00,0xcd,0x00,0x00,0x00,0xae,0x00,0x05,0x00,
-0xcf,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,
-0xce,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0xd2,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xd0,0x00,0x00,0x00,
-0xd1,0x00,0x00,0x00,0xd2,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd1,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xf4,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xd2,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0xd9,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0xd8,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xda,0x00,0x00,0x00,0xd9,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x03,0x01,0x00,0x00,0x14,0x00,0x00,0x00,
-0x6f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x04,0x01,0x00,0x00,0x03,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x05,0x01,0x00,0x00,0x14,0x00,0x00,0x00,
-0x72,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x06,0x01,0x00,0x00,0x05,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x07,0x01,0x00,0x00,0x04,0x01,0x00,0x00,
-0x06,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x08,0x01,0x00,0x00,0x14,0x00,0x00,0x00,0x76,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x09,0x01,0x00,0x00,
-0x08,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x0a,0x01,0x00,0x00,0x07,0x01,0x00,0x00,0x09,0x01,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x0b,0x01,0x00,0x00,
-0xcb,0x00,0x00,0x00,0x0a,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x0f,0x01,0x00,0x00,0x0b,0x01,0x00,0x00,
-0x04,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x12,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,0x06,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x15,0x01,0x00,0x00,
-0x12,0x01,0x00,0x00,0x09,0x01,0x00,0x00,0x82,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x18,0x01,0x00,0x00,0xcb,0x00,0x00,0x00,
-0x15,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x1d,0x01,0x00,0x00,0x06,0x01,0x00,0x00,0x09,0x01,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1e,0x01,0x00,0x00,
-0x18,0x01,0x00,0x00,0x1d,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x22,0x01,0x00,0x00,0x1e,0x01,0x00,0x00,
-0x06,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x25,0x01,0x00,0x00,0x22,0x01,0x00,0x00,0x09,0x01,0x00,0x00,
-0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x2a,0x01,0x00,0x00,
-0x18,0x01,0x00,0x00,0x25,0x01,0x00,0x00,0x86,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x2d,0x01,0x00,0x00,0x2a,0x01,0x00,0x00,
-0x09,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x36,0x01,0x00,0x00,0x2d,0x01,0x00,0x00,0x09,0x01,0x00,0x00,
-0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x37,0x01,0x00,0x00,
-0x2a,0x01,0x00,0x00,0x36,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x39,0x01,0x00,0x00,0x14,0x00,0x00,0x00,
-0xad,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x3a,0x01,0x00,0x00,0x39,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x3b,0x01,0x00,0x00,0x0b,0x01,0x00,0x00,
-0x3a,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x3d,0x01,0x00,0x00,0x14,0x00,0x00,0x00,0xb2,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x3e,0x01,0x00,0x00,
-0x3d,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x3f,0x01,0x00,0x00,0x1e,0x01,0x00,0x00,0x3e,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x40,0x01,0x00,0x00,
-0x3b,0x01,0x00,0x00,0x3f,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x42,0x01,0x00,0x00,0x14,0x00,0x00,0x00,
-0xb8,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x43,0x01,0x00,0x00,0x42,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x44,0x01,0x00,0x00,0x2d,0x01,0x00,0x00,
-0x43,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x45,0x01,0x00,0x00,0x40,0x01,0x00,0x00,0x44,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x47,0x01,0x00,0x00,
-0x14,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x48,0x01,0x00,0x00,0x47,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x49,0x01,0x00,0x00,
-0x37,0x01,0x00,0x00,0x48,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x4a,0x01,0x00,0x00,0x45,0x01,0x00,0x00,
-0x49,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xdf,0x00,0x00,0x00,0xda,0x00,0x00,0x00,0x4a,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x54,0x01,0x00,0x00,
-0x14,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x55,0x01,0x00,0x00,0x54,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x56,0x01,0x00,0x00,
-0x14,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x57,0x01,0x00,0x00,0x56,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x58,0x01,0x00,0x00,
-0x55,0x01,0x00,0x00,0x57,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x59,0x01,0x00,0x00,0x14,0x00,0x00,0x00,
-0x1e,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x5a,0x01,0x00,0x00,0x59,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x5b,0x01,0x00,0x00,0x58,0x01,0x00,0x00,
-0x5a,0x01,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x5c,0x01,0x00,0x00,0xcb,0x00,0x00,0x00,0x5b,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x60,0x01,0x00,0x00,
-0x5c,0x01,0x00,0x00,0x55,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x63,0x01,0x00,0x00,0x60,0x01,0x00,0x00,
-0x57,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x66,0x01,0x00,0x00,0x63,0x01,0x00,0x00,0x5a,0x01,0x00,0x00,
-0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x69,0x01,0x00,0x00,
-0xcb,0x00,0x00,0x00,0x66,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x6e,0x01,0x00,0x00,0x57,0x01,0x00,0x00,
-0x5a,0x01,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x6f,0x01,0x00,0x00,0x69,0x01,0x00,0x00,0x6e,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x73,0x01,0x00,0x00,
-0x6f,0x01,0x00,0x00,0x57,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x76,0x01,0x00,0x00,0x73,0x01,0x00,0x00,
-0x5a,0x01,0x00,0x00,0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x7b,0x01,0x00,0x00,0x69,0x01,0x00,0x00,0x76,0x01,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x7e,0x01,0x00,0x00,
-0x7b,0x01,0x00,0x00,0x5a,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x87,0x01,0x00,0x00,0x7e,0x01,0x00,0x00,
-0x5a,0x01,0x00,0x00,0x82,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x88,0x01,0x00,0x00,0x7b,0x01,0x00,0x00,0x87,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x8a,0x01,0x00,0x00,
-0x14,0x00,0x00,0x00,0x55,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x8b,0x01,0x00,0x00,0x8a,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8c,0x01,0x00,0x00,
-0x5c,0x01,0x00,0x00,0x8b,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x8e,0x01,0x00,0x00,0x14,0x00,0x00,0x00,
-0x5a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x8f,0x01,0x00,0x00,0x8e,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x90,0x01,0x00,0x00,0x6f,0x01,0x00,0x00,
-0x8f,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x91,0x01,0x00,0x00,0x8c,0x01,0x00,0x00,0x90,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x93,0x01,0x00,0x00,
-0x14,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x94,0x01,0x00,0x00,0x93,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x95,0x01,0x00,0x00,
-0x7e,0x01,0x00,0x00,0x94,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x96,0x01,0x00,0x00,0x91,0x01,0x00,0x00,
-0x95,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x98,0x01,0x00,0x00,0x14,0x00,0x00,0x00,0x66,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x99,0x01,0x00,0x00,
-0x98,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9a,0x01,0x00,0x00,0x88,0x01,0x00,0x00,0x99,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9b,0x01,0x00,0x00,
-0x96,0x01,0x00,0x00,0x9a,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0xe8,0x00,0x00,0x00,0xe9,0x00,0x00,0x00,0xe3,0x00,0x00,0x00,
-0xcc,0x00,0x00,0x00,0x9b,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x11,0x00,0x00,0x00,0xea,0x00,0x00,0x00,0xe9,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0xec,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x11,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0xef,0x00,0x00,0x00,
-0xea,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0xe8,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,0xd7,0x00,0x00,0x00,
-0xcc,0x00,0x00,0x00,0xdf,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xf0,0x00,0x00,0x00,0xef,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xf4,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xf4,0x00,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t scale_f32_len = 3320;
-
-unsigned char silu_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x3b,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x09,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x12,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x21,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x22,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x24,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x24,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x29,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x2a,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x2a,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x2c,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x2c,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x38,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x11,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x1e,0x00,0x06,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x13,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x13,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x17,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x14,0x00,0x02,0x00,0x1a,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x21,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x22,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x26,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x29,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x2a,0x00,0x00,0x00,0x29,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x2b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x2a,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x2b,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
-0x2f,0x00,0x00,0x00,0x00,0x00,0x80,0x3f,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x36,0x00,0x00,0x00,0x00,0x02,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x37,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2c,0x00,0x06,0x00,0x09,0x00,0x00,0x00,
-0x38,0x00,0x00,0x00,0x36,0x00,0x00,0x00,0x37,0x00,0x00,0x00,
-0x37,0x00,0x00,0x00,0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x39,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfb,0x00,0x03,0x00,
-0x0c,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x3a,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x0e,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0xae,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x1d,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x1d,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x1c,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x39,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x1d,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x26,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x27,0x00,0x00,0x00,0x7f,0x00,0x04,0x00,
-0x11,0x00,0x00,0x00,0x31,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x0c,0x00,0x06,0x00,0x11,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x31,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x33,0x00,0x00,0x00,
-0x2f,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x88,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x33,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x26,0x00,0x00,0x00,
-0x35,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x35,0x00,0x00,0x00,
-0x34,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x39,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x39,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,
-0x38,0x00,0x01,0x00,
-};
-const uint64_t silu_f32_len = 1264;
-
-unsigned char soft_max_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x6f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0c,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x77,0x00,0x00,0x00,0x8f,0x00,0x00,0x00,0xa2,0x00,0x00,0x00,
-0x0c,0x01,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x11,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x17,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x74,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x75,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x75,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x75,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x77,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x77,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x8c,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x8d,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x8d,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x8d,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x8f,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x8f,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x09,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x0a,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x0a,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0c,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0c,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x52,0x01,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0x16,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x1e,0x00,0x09,0x00,
-0x17,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x18,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x17,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x18,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x1a,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x1c,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x80,0x3f,0x2b,0x00,0x04,0x00,
-0x1a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x24,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x14,0x00,0x02,0x00,
-0x28,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
-0x33,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
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-0x0c,0x01,0x00,0x00,0x64,0x00,0x00,0x00,0x4a,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,0x4d,0x01,0x00,0x00,
-0x4c,0x01,0x00,0x00,0x88,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
-0x4e,0x01,0x00,0x00,0x4d,0x01,0x00,0x00,0x2f,0x01,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x4c,0x01,0x00,0x00,0x4e,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x34,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x34,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x51,0x01,0x00,0x00,0x66,0x01,0x00,0x00,0x9d,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x31,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x33,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t soft_max_f32_len = 4836;
-
-unsigned char soft_max_f32_f16_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x73,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0c,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x77,0x00,0x00,0x00,
-0x90,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,0x10,0x01,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x17,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x74,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x75,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x75,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x75,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x77,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x77,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x8d,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x8e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x8e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x8e,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x90,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x90,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0d,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x0e,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x0e,0x01,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x10,0x01,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x10,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x56,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,
-0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,0x09,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x16,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x1e,0x00,0x09,0x00,0x17,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x18,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x18,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x1c,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x16,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x80,0x3f,0x2b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x24,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x16,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x14,0x00,0x02,0x00,0x28,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,0x33,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x1a,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x4e,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x1a,0x00,0x00,0x00,0x64,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0x74,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x1e,0x00,0x03,0x00,0x75,0x00,0x00,0x00,0x74,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x76,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x75,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x76,0x00,0x00,0x00,
-0x77,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x7e,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,0x81,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x8c,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0x8d,0x00,0x00,0x00,
-0x8c,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0x8e,0x00,0x00,0x00,
-0x8d,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x8f,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x8e,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x8f,0x00,0x00,0x00,0x90,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x97,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x8c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xa0,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x1c,0x00,0x04,0x00,
-0xa3,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0xa0,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0xa4,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0xa3,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0xa4,0x00,0x00,0x00,
-0xa5,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0xa8,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xaa,0x00,0x00,0x00,
-0x08,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
-0xad,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x0d,0x01,0x00,0x00,0x16,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x0e,0x01,0x00,0x00,0x0d,0x01,0x00,0x00,0x20,0x00,0x04,0x00,
-0x0f,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x0e,0x01,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x0f,0x01,0x00,0x00,0x10,0x01,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x2c,0x00,0x06,0x00,0x09,0x00,0x00,0x00,
-0x56,0x01,0x00,0x00,0xa0,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,
-0x4b,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x72,0x01,0x00,0x00,0x00,0x00,0x80,0xff,0x36,0x00,0x05,0x00,
-0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1c,0x00,0x00,0x00,0x1d,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,0x1d,0x00,0x00,0x00,
-0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x24,0x00,0x00,0x00,0x25,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x26,0x00,0x00,0x00,0x25,0x00,0x00,0x00,0xba,0x00,0x05,0x00,
-0x28,0x00,0x00,0x00,0x29,0x00,0x00,0x00,0x26,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x2b,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x29,0x00,0x00,0x00,
-0x2a,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x2a,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x30,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1c,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
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-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,
-0xe6,0x00,0x00,0x00,0xda,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0x7e,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,0x77,0x00,0x00,0x00,
-0x64,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x16,0x00,0x00,0x00,0xec,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x24,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x81,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x16,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0xac,0x00,0x05,0x00,0x28,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,
-0x1e,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0xf5,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0xf2,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,0x01,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf4,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x66,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xfc,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0xda,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x97,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,
-0x90,0x00,0x00,0x00,0x64,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x8c,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,
-0xfd,0x00,0x00,0x00,0x73,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0xff,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,0x85,0x00,0x05,0x00,
-0x16,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x5c,0x01,0x00,0x00,
-0xff,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xf5,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x01,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xf5,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xf5,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x16,0x00,0x00,0x00,0x65,0x01,0x00,0x00,
-0x00,0x01,0x00,0x00,0xf4,0x00,0x00,0x00,0x27,0x00,0x00,0x00,
-0x01,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,0x16,0x00,0x00,0x00,
-0x03,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0xec,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0x65,0x01,0x00,0x00,
-0x83,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0x05,0x01,0x00,0x00,
-0x03,0x01,0x00,0x00,0xca,0x00,0x00,0x00,0x0c,0x00,0x06,0x00,
-0x16,0x00,0x00,0x00,0x06,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x05,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x16,0x00,0x00,0x00,0x0a,0x01,0x00,0x00,0xa9,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0x0b,0x01,0x00,0x00,
-0x0a,0x01,0x00,0x00,0x06,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xa9,0x00,0x00,0x00,0x0b,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x7e,0x00,0x00,0x00,0x13,0x01,0x00,0x00,0x10,0x01,0x00,0x00,
-0x64,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x13,0x01,0x00,0x00,0x06,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xd1,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xd1,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x15,0x01,0x00,0x00,
-0x61,0x01,0x00,0x00,0xa0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xce,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xd0,0x00,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x4e,0x00,0x00,0x00,0x4e,0x00,0x00,0x00,
-0xaa,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x17,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x17,0x01,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x1a,0x00,0x00,0x00,0x69,0x01,0x00,0x00,0xad,0x00,0x00,0x00,
-0xd0,0x00,0x00,0x00,0x30,0x01,0x00,0x00,0x1a,0x01,0x00,0x00,
-0xad,0x00,0x05,0x00,0x28,0x00,0x00,0x00,0x1d,0x01,0x00,0x00,
-0x69,0x01,0x00,0x00,0x64,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x19,0x01,0x00,0x00,0x1a,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x1d,0x01,0x00,0x00,0x18,0x01,0x00,0x00,
-0x19,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x18,0x01,0x00,0x00,
-0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x01,0x00,0x00,
-0x69,0x01,0x00,0x00,0xb0,0x00,0x05,0x00,0x28,0x00,0x00,0x00,
-0x21,0x01,0x00,0x00,0x0f,0x00,0x00,0x00,0x20,0x01,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x23,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x21,0x01,0x00,0x00,0x22,0x01,0x00,0x00,
-0x23,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x22,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x28,0x01,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x20,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0xa8,0x00,0x00,0x00,0x29,0x01,0x00,0x00,0xa5,0x00,0x00,0x00,
-0x28,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x2a,0x01,0x00,0x00,0x29,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x16,0x00,0x00,0x00,0x2c,0x01,0x00,0x00,0xa9,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0x2d,0x01,0x00,0x00,
-0x2c,0x01,0x00,0x00,0x2a,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xa9,0x00,0x00,0x00,0x2d,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x23,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x23,0x01,0x00,0x00,
-0xe0,0x00,0x04,0x00,0x4e,0x00,0x00,0x00,0x4e,0x00,0x00,0x00,
-0xaa,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x1a,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x1a,0x01,0x00,0x00,0xc3,0x00,0x05,0x00,
-0x1a,0x00,0x00,0x00,0x30,0x01,0x00,0x00,0x69,0x01,0x00,0x00,
-0x1b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x17,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x19,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x16,0x00,0x00,0x00,0x33,0x01,0x00,0x00,0xc9,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x35,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x35,0x01,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x6a,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x19,0x01,0x00,0x00,
-0x55,0x01,0x00,0x00,0x38,0x01,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x28,0x00,0x00,0x00,0x3d,0x01,0x00,0x00,0x6a,0x01,0x00,0x00,
-0x66,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x37,0x01,0x00,0x00,
-0x38,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x3d,0x01,0x00,0x00,0x36,0x01,0x00,0x00,0x37,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x36,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x41,0x01,0x00,0x00,0x6a,0x01,0x00,0x00,
-0x0f,0x00,0x00,0x00,0xae,0x00,0x05,0x00,0x28,0x00,0x00,0x00,
-0x45,0x01,0x00,0x00,0x41,0x01,0x00,0x00,0x66,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x47,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x45,0x01,0x00,0x00,0x46,0x01,0x00,0x00,
-0x47,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x46,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x37,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x47,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x4c,0x01,0x00,0x00,0x13,0x00,0x00,0x00,0x66,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x4e,0x01,0x00,0x00,
-0x4c,0x01,0x00,0x00,0x41,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x7e,0x00,0x00,0x00,0x50,0x01,0x00,0x00,0x10,0x01,0x00,0x00,
-0x64,0x00,0x00,0x00,0x4e,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x16,0x00,0x00,0x00,0x51,0x01,0x00,0x00,0x50,0x01,0x00,0x00,
-0x88,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0x52,0x01,0x00,0x00,
-0x51,0x01,0x00,0x00,0x33,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x50,0x01,0x00,0x00,0x52,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x38,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x38,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x55,0x01,0x00,0x00,
-0x6a,0x01,0x00,0x00,0xa0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x35,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x37,0x01,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t soft_max_f32_f16_len = 4904;
-
-unsigned char split_k_reduce_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x50,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x09,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x41,0x00,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x11,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x11,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x2d,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x2e,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x2e,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x2e,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x30,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x30,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x3f,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x3f,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x3f,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x41,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x41,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x47,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,
-0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,0x09,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x1e,0x00,0x04,0x00,0x11,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x12,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x12,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x14,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x14,0x00,0x00,0x00,
-0x15,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x16,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x14,0x00,0x02,0x00,0x19,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0x1e,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x1e,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x14,0x00,0x00,0x00,0x29,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0x2d,0x00,0x00,0x00,
-0x1e,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0x2e,0x00,0x00,0x00,
-0x2d,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x2f,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x2f,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x37,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x1e,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0x3e,0x00,0x00,0x00,
-0x1e,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0x3f,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x40,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x40,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x45,0x00,0x00,0x00,
-0x00,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x46,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2c,0x00,0x06,0x00,
-0x09,0x00,0x00,0x00,0x47,0x00,0x00,0x00,0x45,0x00,0x00,0x00,
-0x46,0x00,0x00,0x00,0x46,0x00,0x00,0x00,0x36,0x00,0x05,0x00,
-0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x48,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfb,0x00,0x03,0x00,0x0c,0x00,0x00,0x00,0x49,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x49,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x0d,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x16,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x15,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0xae,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x1c,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x1b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x48,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x1c,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x23,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x23,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x1e,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x3b,0x00,0x00,0x00,
-0x24,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x4e,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x3d,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x16,0x00,0x00,0x00,0x2a,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x29,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x2b,0x00,0x00,0x00,0x2a,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x19,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x4e,0x00,0x00,0x00,
-0x2b,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x25,0x00,0x00,0x00,
-0x24,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x2c,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x25,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x24,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x4e,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x36,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x37,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0x30,0x00,0x00,0x00,0x15,0x00,0x00,0x00,0x36,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x1e,0x00,0x00,0x00,0x39,0x00,0x00,0x00,
-0x38,0x00,0x00,0x00,0x81,0x00,0x05,0x00,0x1e,0x00,0x00,0x00,
-0x3b,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x39,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,
-0x4e,0x00,0x00,0x00,0x29,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x23,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x25,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x37,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0x41,0x00,0x00,0x00,0x15,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x44,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x48,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x48,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t split_k_reduce_len = 1416;
-
-unsigned char sqr_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x9c,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x09,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0xd9,0x00,0x00,0x00,
-0xe4,0x00,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x38,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x40,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x12,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x44,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
-0x12,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x48,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xc7,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xd6,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xd7,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xd7,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xd7,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xd9,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xd9,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xe1,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xe2,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xe2,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xe2,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xe4,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xe4,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xf3,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,
-0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x11,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x1e,0x00,0x16,0x00,0x12,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x13,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x17,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
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-0x14,0x00,0x00,0x00,0xad,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x8b,0x01,0x00,0x00,0x8a,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8c,0x01,0x00,0x00,
-0x5c,0x01,0x00,0x00,0x8b,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x8e,0x01,0x00,0x00,0x14,0x00,0x00,0x00,
-0xb2,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x8f,0x01,0x00,0x00,0x8e,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x90,0x01,0x00,0x00,0x6f,0x01,0x00,0x00,
-0x8f,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x91,0x01,0x00,0x00,0x8c,0x01,0x00,0x00,0x90,0x01,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x93,0x01,0x00,0x00,
-0x14,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x94,0x01,0x00,0x00,0x93,0x01,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x95,0x01,0x00,0x00,
-0x7e,0x01,0x00,0x00,0x94,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x96,0x01,0x00,0x00,0x91,0x01,0x00,0x00,
-0x95,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x98,0x01,0x00,0x00,0x14,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x99,0x01,0x00,0x00,
-0x98,0x01,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9a,0x01,0x00,0x00,0x88,0x01,0x00,0x00,0x99,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9b,0x01,0x00,0x00,
-0x96,0x01,0x00,0x00,0x9a,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xec,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,
-0x9b,0x01,0x00,0x00,0x85,0x00,0x05,0x00,0x11,0x00,0x00,0x00,
-0xef,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0xde,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,
-0xe4,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,0xec,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xf0,0x00,0x00,0x00,0xef,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xf4,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xf4,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t sqr_f32_len = 3252;
-
-unsigned char sum_rows_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x76,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0b,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0x33,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,
-0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x25,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x25,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x25,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x25,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x25,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x30,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x31,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x31,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x31,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x33,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x33,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x69,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x6a,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x6a,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x6a,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x6c,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x6c,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x71,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x73,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,
-0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,0x09,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x14,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x15,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,
-0x16,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x15,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x17,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x17,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x14,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x1b,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x1e,0x00,0x06,0x00,0x25,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x26,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x25,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x26,0x00,0x00,0x00,0x27,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x28,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x28,0x00,0x00,0x00,
-0x29,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x2a,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x14,0x00,0x02,0x00,0x2d,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x30,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x31,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x32,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x31,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x32,0x00,0x00,0x00,0x33,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x3a,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x43,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0x08,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x28,0x00,0x00,0x00,
-0x47,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x15,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x28,0x00,0x00,0x00,
-0x48,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x28,0x00,0x00,0x00,0x49,0x00,0x00,0x00,0x87,0x00,0x00,0x00,
-0x47,0x00,0x00,0x00,0x48,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x28,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0x69,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x1e,0x00,0x03,0x00,0x6a,0x00,0x00,0x00,0x69,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x6b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x6a,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x6b,0x00,0x00,0x00,
-0x6c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x32,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x71,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x72,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00,
-0x73,0x00,0x00,0x00,0x71,0x00,0x00,0x00,0x72,0x00,0x00,0x00,
-0x72,0x00,0x00,0x00,0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x0d,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x0d,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x1b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x1c,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x1f,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x1f,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x74,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x42,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,
-0x27,0x00,0x00,0x00,0x29,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x2d,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,
-0x74,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x21,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x2e,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x20,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x37,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x37,0x00,0x00,0x00,
-0x74,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x3a,0x00,0x00,0x00,
-0x3b,0x00,0x00,0x00,0x33,0x00,0x00,0x00,0x29,0x00,0x00,0x00,
-0x39,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x14,0x00,0x00,0x00,
-0x3c,0x00,0x00,0x00,0x3b,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x81,0x00,0x05,0x00,0x14,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x1c,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x42,0x00,0x00,0x00,0x74,0x00,0x00,0x00,
-0x15,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x1f,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x21,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x43,0x00,0x00,0x00,0x43,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x4a,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x4a,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x28,0x00,0x00,0x00,
-0x75,0x00,0x00,0x00,0x49,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x64,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0xad,0x00,0x05,0x00,
-0x2d,0x00,0x00,0x00,0x50,0x00,0x00,0x00,0x75,0x00,0x00,0x00,
-0x29,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x4c,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x50,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x4b,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x53,0x00,0x00,0x00,0x75,0x00,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x2d,0x00,0x00,0x00,0x54,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x53,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x56,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x54,0x00,0x00,0x00,0x55,0x00,0x00,0x00,0x56,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x55,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x5b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,
-0x53,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,
-0x5c,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x5b,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x14,0x00,0x00,0x00,0x5d,0x00,0x00,0x00,
-0x5c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x14,0x00,0x00,0x00,
-0x5f,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x81,0x00,0x05,0x00,
-0x14,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x5f,0x00,0x00,0x00,
-0x5d,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x1c,0x00,0x00,0x00,
-0x60,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x56,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x56,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,
-0x43,0x00,0x00,0x00,0x43,0x00,0x00,0x00,0x44,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x4d,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x4d,0x00,0x00,0x00,0xc3,0x00,0x05,0x00,0x28,0x00,0x00,0x00,
-0x64,0x00,0x00,0x00,0x75,0x00,0x00,0x00,0x62,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x4a,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x4c,0x00,0x00,0x00,0xaa,0x00,0x05,0x00,0x2d,0x00,0x00,0x00,
-0x66,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x68,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x66,0x00,0x00,0x00,0x67,0x00,0x00,0x00,
-0x68,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x67,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1b,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x29,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x14,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x3a,0x00,0x00,0x00,0x70,0x00,0x00,0x00,
-0x6c,0x00,0x00,0x00,0x29,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x70,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x68,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x68,0x00,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t sum_rows_f32_len = 2112;
diff --git a/ggml/src/vulkan-shaders/CMakeLists.txt b/ggml/src/vulkan-shaders/CMakeLists.txt
new file mode 100644
index 0000000000000..41551e0094d4a
--- /dev/null
+++ b/ggml/src/vulkan-shaders/CMakeLists.txt
@@ -0,0 +1,5 @@
+
+set(TARGET vulkan-shaders-gen)
+add_executable(${TARGET} vulkan-shaders-gen.cpp)
+install(TARGETS ${TARGET} RUNTIME)
+target_compile_features(${TARGET} PRIVATE cxx_std_11)
diff --git a/ggml/src/vulkan-shaders/vulkan-shaders-gen.cpp b/ggml/src/vulkan-shaders/vulkan-shaders-gen.cpp
new file mode 100644
index 0000000000000..fa231c0ec1688
--- /dev/null
+++ b/ggml/src/vulkan-shaders/vulkan-shaders-gen.cpp
@@ -0,0 +1,524 @@
+
+
+#include 
+#include 
+#include 
+#include 
+#include 
+#include 
+#include 
+#include 
+#include 
+#include 
+#include 
+#include 
+#include 
+#include 
+#include 
+#include 
+#include 
+#include 
+
+#ifdef _WIN32
+    #include 
+    #include  // For _mkdir on Windows
+#else
+    #include 
+    #include 
+    #include 
+#endif
+
+#define ASYNCIO_CONCURRENCY 64
+
+std::mutex lock;
+std::vector> shader_fnames;
+
+std::string GLSLC = "glslc";
+std::string input_dir = "vulkan-shaders";
+std::string output_dir = "/tmp";
+std::string target_hpp = "ggml-vulkan-shaders.hpp";
+std::string target_cpp = "ggml-vulkan-shaders.cpp";
+bool no_clean = false;
+
+const std::vector type_names = {
+    "f32",
+    "f16",
+    "q4_0",
+    "q4_1",
+    "q5_0",
+    "q5_1",
+    "q8_0",
+    "q2_k",
+    "q3_k",
+    "q4_k",
+    "q5_k",
+    "q6_k"
+};
+
+void execute_command(const std::string& command, std::string& stdout_str, std::string& stderr_str) {
+#ifdef _WIN32
+    HANDLE stdout_read, stdout_write;
+    HANDLE stderr_read, stderr_write;
+    SECURITY_ATTRIBUTES sa = { sizeof(SECURITY_ATTRIBUTES), NULL, TRUE };
+
+    if (!CreatePipe(&stdout_read, &stdout_write, &sa, 0) ||
+        !SetHandleInformation(stdout_read, HANDLE_FLAG_INHERIT, 0)) {
+        throw std::runtime_error("Failed to create stdout pipe");
+    }
+
+    if (!CreatePipe(&stderr_read, &stderr_write, &sa, 0) ||
+        !SetHandleInformation(stderr_read, HANDLE_FLAG_INHERIT, 0)) {
+        throw std::runtime_error("Failed to create stderr pipe");
+    }
+
+    PROCESS_INFORMATION pi;
+    STARTUPINFOA si = { sizeof(STARTUPINFOA) };
+    si.dwFlags = STARTF_USESTDHANDLES;
+    si.hStdOutput = stdout_write;
+    si.hStdError = stderr_write;
+
+    std::vector cmd(command.begin(), command.end());
+    cmd.push_back('\0');
+
+    if (!CreateProcessA(NULL, cmd.data(), NULL, NULL, TRUE, 0, NULL, NULL, &si, &pi)) {
+        throw std::runtime_error("Failed to create process");
+    }
+
+    CloseHandle(stdout_write);
+    CloseHandle(stderr_write);
+
+    std::array buffer;
+    DWORD bytes_read;
+
+    while (ReadFile(stdout_read, buffer.data(), buffer.size(), &bytes_read, NULL) && bytes_read > 0) {
+        stdout_str.append(buffer.data(), bytes_read);
+    }
+
+    while (ReadFile(stderr_read, buffer.data(), buffer.size(), &bytes_read, NULL) && bytes_read > 0) {
+        stderr_str.append(buffer.data(), bytes_read);
+    }
+
+    CloseHandle(stdout_read);
+    CloseHandle(stderr_read);
+    WaitForSingleObject(pi.hProcess, INFINITE);
+    CloseHandle(pi.hProcess);
+    CloseHandle(pi.hThread);
+#else
+int stdout_pipe[2];
+    int stderr_pipe[2];
+
+    if (pipe(stdout_pipe) != 0 || pipe(stderr_pipe) != 0) {
+        throw std::runtime_error("Failed to create pipes");
+    }
+
+    pid_t pid = fork();
+    if (pid < 0) {
+        throw std::runtime_error("Failed to fork process");
+    }
+
+    if (pid == 0) {
+        close(stdout_pipe[0]);
+        close(stderr_pipe[0]);
+        dup2(stdout_pipe[1], STDOUT_FILENO);
+        dup2(stderr_pipe[1], STDERR_FILENO);
+        close(stdout_pipe[1]);
+        close(stderr_pipe[1]);
+        execl("/bin/sh", "sh", "-c", command.c_str(), (char*) nullptr);
+        _exit(EXIT_FAILURE);
+    } else {
+        close(stdout_pipe[1]);
+        close(stderr_pipe[1]);
+
+        std::array buffer;
+        ssize_t bytes_read;
+
+        while ((bytes_read = read(stdout_pipe[0], buffer.data(), buffer.size())) > 0) {
+            stdout_str.append(buffer.data(), bytes_read);
+        }
+
+        while ((bytes_read = read(stderr_pipe[0], buffer.data(), buffer.size())) > 0) {
+            stderr_str.append(buffer.data(), bytes_read);
+        }
+
+        close(stdout_pipe[0]);
+        close(stderr_pipe[0]);
+        waitpid(pid, nullptr, 0);
+    }
+#endif
+}
+
+bool directory_exists(const std::string& path) {
+    struct stat info;
+    if (stat(path.c_str(), &info) != 0) {
+        return false; // Path doesn't exist or can't be accessed
+    }
+    return (info.st_mode & S_IFDIR) != 0; // Check if it is a directory
+}
+
+bool create_directory(const std::string& path) {
+#ifdef _WIN32
+    return _mkdir(path.c_str()) == 0 || errno == EEXIST; // EEXIST means the directory already exists
+#else
+    return mkdir(path.c_str(), 0755) == 0 || errno == EEXIST; // 0755 is the directory permissions
+#endif
+}
+
+std::string to_uppercase(const std::string& input) {
+    std::string result = input;
+    for (char& c : result) {
+        c = std::toupper(c);
+    }
+    return result;
+}
+
+bool string_ends_with(const std::string& str, const std::string& suffix) {
+    if (suffix.size() > str.size()) {
+        return false;
+    }
+    return std::equal(suffix.rbegin(), suffix.rend(), str.rbegin());
+}
+
+#ifdef _WIN32
+    static const char path_separator = '\\';
+#else
+    static const char path_separator = '/';
+#endif
+
+std::string join_paths(const std::string& path1, const std::string& path2) {
+    return path1 + path_separator + path2;
+}
+
+std::string basename(const std::string &path) {
+    return path.substr(path.find_last_of("/\\") + 1);
+}
+
+void string_to_spv(const std::string& _name, const std::string& in_fname, const std::map& defines, bool fp16 = true) {
+    std::string name = _name + (fp16 ? "" : "_fp32");
+    std::string out_fname = join_paths(output_dir, name + ".spv");
+    std::string in_path = join_paths(input_dir, in_fname);
+
+    std::vector cmd = {GLSLC, "-fshader-stage=compute", "--target-env=vulkan1.2", "-O", in_path, "-o", out_fname};
+    for (const auto& define : defines) {
+        cmd.push_back("-D" + define.first + "=" + define.second);
+    }
+
+    std::string command;
+    for (const auto& part : cmd) {
+        command += part + " ";
+    }
+
+    std::string stdout_str, stderr_str;
+    try {
+        // std::cout << "Executing command: ";
+        // for (const auto& part : cmd) {
+        //     std::cout << part << " ";
+        // }
+        // std::cout << std::endl;
+
+        execute_command(command, stdout_str, stderr_str);
+        if (!stderr_str.empty()) {
+            std::cerr << "cannot compile " << name << "\n\n" << command << "\n\n" << stderr_str << std::endl;
+            return;
+        }
+
+        std::lock_guard guard(lock);
+        shader_fnames.push_back(std::make_pair(name, out_fname));
+    } catch (const std::exception& e) {
+        std::cerr << "Error executing command for " << name << ": " << e.what() << std::endl;
+    }
+}
+
+std::map merge_maps(const std::map& a, const std::map& b) {
+    std::map result = a;
+    result.insert(b.begin(), b.end());
+    return result;
+}
+
+void matmul_shaders(std::vector>& tasks, bool fp16, bool matmul_id) {
+    std::string load_vec = fp16 ? "8" : "4";
+    std::string aligned_b_type_f32 = fp16 ? "mat2x4" : "vec4";
+    std::string aligned_b_type_f16 = fp16 ? "f16mat2x4" : "f16vec4";
+
+    std::map base_dict = {{"FLOAT_TYPE", fp16 ? "float16_t" : "float"}};
+    std::string shader_name = "matmul";
+
+    if (matmul_id) {
+        base_dict["MUL_MAT_ID"] = "1";
+        shader_name = "matmul_id";
+    }
+
+    if (fp16) {
+        base_dict["FLOAT16"] = "1";
+    }
+
+    // Shaders with f16 B_TYPE
+    tasks.push_back(std::async(std::launch::async, [=] {
+        string_to_spv(shader_name + "_f32_f16", "mul_mm.comp", merge_maps(base_dict, {{"DATA_A_F32", "1"}, {"B_TYPE", "float16_t"}, {"D_TYPE", "float"}}), fp16);
+    }));
+    tasks.push_back(std::async(std::launch::async, [=] {
+        string_to_spv(shader_name + "_f32_f16_aligned", "mul_mm.comp", merge_maps(base_dict, {{"DATA_A_F32", "1"}, {"LOAD_VEC_A", load_vec}, {"LOAD_VEC_B", load_vec}, {"B_TYPE", aligned_b_type_f16}, {"D_TYPE", "float"}}), fp16);
+    }));
+
+    tasks.push_back(std::async(std::launch::async, [=] {
+        string_to_spv(shader_name + "_f16", "mul_mm.comp", merge_maps(base_dict, {{"DATA_A_F16", "1"}, {"B_TYPE", "float16_t"}, {"D_TYPE", "float"}}), fp16);
+    }));
+    tasks.push_back(std::async(std::launch::async, [=] {
+        string_to_spv(shader_name + "_f16_aligned", "mul_mm.comp", merge_maps(base_dict, {{"DATA_A_F16", "1"}, {"LOAD_VEC_A", load_vec}, {"LOAD_VEC_B", load_vec}, {"B_TYPE", aligned_b_type_f16}, {"D_TYPE", "float"}}), fp16);
+    }));
+
+    for (const auto& tname : type_names) {
+        std::string data_a_key = "DATA_A_" + to_uppercase(tname);
+        std::string load_vec_a = (tname == "f32" || tname == "f16") ? load_vec : "2";
+        tasks.push_back(std::async(std::launch::async, [=] {
+            string_to_spv(shader_name + "_" + tname + "_f32", "mul_mm.comp", merge_maps(base_dict, {{data_a_key, "1"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}}), fp16);
+        }));
+        tasks.push_back(std::async(std::launch::async, [=] {
+            string_to_spv(shader_name + "_" + tname + "_f32_aligned", "mul_mm.comp", merge_maps(base_dict, {{data_a_key, "2"}, {"LOAD_VEC_A", load_vec_a}, {"LOAD_VEC_B", load_vec}, {"B_TYPE", aligned_b_type_f32}, {"D_TYPE", "float"}}), fp16);
+        }));
+    }
+}
+
+void process_shaders(std::vector>& tasks) {
+    std::cout << "ggml_vulkan: Generating and compiling shaders to SPIR-V" << std::endl;
+    std::map base_dict = {{"FLOAT_TYPE", "float"}};
+
+    for (const auto& fp16 : {false, true}) {
+        matmul_shaders(tasks, fp16, false);
+        matmul_shaders(tasks, fp16, true);
+    }
+
+    for (const auto& tname : type_names) {
+        // mul mat vec
+        std::string data_a_key = "DATA_A_" + to_uppercase(tname);
+        std::string shader = (string_ends_with(tname, "_k")) ? "mul_mat_vec_" + tname + ".comp" : "mul_mat_vec.comp";
+
+        tasks.push_back(std::async(std::launch::async, [=] {
+            string_to_spv("mul_mat_vec_" + tname + "_f32_f32", shader, merge_maps(base_dict, {{data_a_key, "1"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}}));
+        }));
+        tasks.push_back(std::async(std::launch::async, [=] {
+            string_to_spv("mul_mat_vec_" + tname + "_f16_f32", shader, merge_maps(base_dict, {{data_a_key, "1"}, {"B_TYPE", "float16_t"}, {"D_TYPE", "float"}}));
+        }));
+
+        tasks.push_back(std::async(std::launch::async, [=] {
+            string_to_spv("mul_mat_vec_id_" + tname + "_f32", shader, merge_maps(base_dict, {{"MUL_MAT_ID", "1"}, {data_a_key, "1"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}}));
+        }));
+
+        // Dequant shaders
+        if (tname != "f16") {
+            tasks.push_back(std::async(std::launch::async, [=] {
+                string_to_spv("dequant_" + tname, "dequant_" + tname + ".comp", merge_maps(base_dict, {{data_a_key, "1"}, {"D_TYPE", "float16_t"}}));
+            }));
+        }
+
+        if (!string_ends_with(tname, "_k")) {
+            shader = (tname == "f32" || tname == "f16") ? "get_rows.comp" : "get_rows_quant.comp";
+
+            if (tname == "f16") {
+                tasks.push_back(std::async(std::launch::async, [=] {
+                    string_to_spv("get_rows_" + tname, shader, {{data_a_key, "1"}, {"B_TYPE", "int"}, {"D_TYPE", "float16_t"}, {"OPTIMIZATION_ERROR_WORKAROUND", "1"}});
+                }));
+            } else {
+                tasks.push_back(std::async(std::launch::async, [=] {
+                    string_to_spv("get_rows_" + tname, shader, {{data_a_key, "1"}, {"B_TYPE", "int"}, {"D_TYPE", "float16_t"}});
+                }));
+            }
+            tasks.push_back(std::async(std::launch::async, [=] {
+                string_to_spv("get_rows_" + tname + "_f32", shader, {{data_a_key, "1"}, {"B_TYPE", "int"}, {"D_TYPE", "float"}});
+            }));
+        }
+    }
+
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("mul_mat_vec_p021_f16_f32", "mul_mat_vec_p021.comp", {{"A_TYPE", "float16_t"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}});
+    }));
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("mul_mat_vec_nc_f16_f32", "mul_mat_vec_nc.comp", {{"A_TYPE", "float16_t"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}});
+    }));
+
+    // Norms
+    tasks.push_back(std::async(std::launch::async, [=] {
+        string_to_spv("norm_f32", "norm.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"D_TYPE", "float"}}));
+    }));
+    tasks.push_back(std::async(std::launch::async, [=] {
+        string_to_spv("rms_norm_f32", "rms_norm.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"D_TYPE", "float"}}));
+    }));
+
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("cpy_f32_f32", "copy.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
+    }));
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("cpy_f32_f16", "copy.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float16_t"}});
+    }));
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("cpy_f16_f16", "copy.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}, {"OPTIMIZATION_ERROR_WORKAROUND", "1"}});
+    }));
+
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("add_f32", "add.comp", {{"A_TYPE", "float"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}, {"FLOAT_TYPE", "float"}});
+    }));
+
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("split_k_reduce", "mul_mat_split_k_reduce.comp", {});
+    }));
+
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("mul_f32", "mul.comp", {{"A_TYPE", "float"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}, {"FLOAT_TYPE", "float"}});
+    }));
+
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("div_f32", "div.comp", {{"A_TYPE", "float"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}, {"FLOAT_TYPE", "float"}});
+    }));
+
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("scale_f32", "scale.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}, {"FLOAT_TYPE", "float"}});
+    }));
+
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("sqr_f32", "square.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}, {"FLOAT_TYPE", "float"}});
+    }));
+
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("clamp_f32", "clamp.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}, {"FLOAT_TYPE", "float"}});
+    }));
+
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("gelu_f32", "gelu.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
+    }));
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("silu_f32", "silu.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
+    }));
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("relu_f32", "relu.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
+    }));
+
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("diag_mask_inf_f32", "diag_mask_inf.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
+    }));
+
+    tasks.push_back(std::async(std::launch::async, [=] {
+        string_to_spv("soft_max_f32", "soft_max.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}}));
+    }));
+    tasks.push_back(std::async(std::launch::async, [=] {
+        string_to_spv("soft_max_f32_f16", "soft_max.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"B_TYPE", "float16_t"}, {"D_TYPE", "float"}}));
+    }));
+
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("rope_norm_f32", "rope_norm.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
+    }));
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("rope_norm_f16", "rope_norm.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});
+    }));
+
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("rope_neox_f32", "rope_neox.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
+    }));
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("rope_neox_f16", "rope_neox.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});
+    }));
+
+    tasks.push_back(std::async(std::launch::async, [] {
+        string_to_spv("argsort_f32", "argsort.comp", {{"A_TYPE", "float"}});
+    }));
+
+    tasks.push_back(std::async(std::launch::async, [=] {
+        string_to_spv("sum_rows_f32", "sum_rows.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"D_TYPE", "float"}}));
+    }));
+}
+
+void write_output_files() {
+    FILE* hdr = fopen(target_hpp.c_str(), "w");
+    FILE* src = fopen(target_cpp.c_str(), "w");
+
+    fprintf(hdr, "#include \n\n");
+    fprintf(src, "#include \"%s\"\n\n", basename(target_hpp).c_str());
+
+    for (const auto& pair : shader_fnames) {
+        const std::string& name = pair.first;
+        const std::string& path = pair.second;
+        FILE* spv = fopen(path.c_str(), "rb");
+        if (!spv) {
+            std::cerr << "Error opening SPIR-V file: " << path << "\n";
+            continue;
+        }
+
+        fseek(spv, 0, SEEK_END);
+        size_t size = ftell(spv);
+        fseek(spv, 0, SEEK_SET);
+
+        std::vector data(size);
+        size_t read_size = fread(data.data(), 1, size, spv);
+        fclose(spv);
+        if (read_size != size) {
+            std::cerr << "Error reading SPIR-V file: " << path << "\n";
+            continue;
+        }
+
+        fprintf(hdr, "extern unsigned char %s_data[%zu];\n", name.c_str(), size);
+        fprintf(hdr, "const uint64_t %s_len = %zu;\n\n", name.c_str(), size);
+
+        fprintf(src, "unsigned char %s_data[%zu] = {\n", name.c_str(), size);
+        for (size_t i = 0; i < size; ++i) {
+            fprintf(src, "0x%02x,", data[i]);
+            if ((i + 1) % 12 == 0) fprintf(src, "\n");
+        }
+        fprintf(src, "\n};\n\n");
+
+        if (!no_clean) {
+            std::remove(path.c_str());
+        }
+    }
+
+    fclose(hdr);
+    fclose(src);
+}
+
+int main(int argc, char** argv) {
+    std::map args;
+    for (int i = 1; i < argc; i += 2) {
+        if (i + 1 < argc) {
+            args[argv[i]] = argv[i + 1];
+        }
+    }
+
+    if (args.find("--glslc") != args.end()) {
+        GLSLC = args["--glslc"]; // Path to glslc
+    }
+    if (args.find("--input-dir") != args.end()) {
+        input_dir = args["--input-dir"]; // Directory containing shader sources
+    }
+    if (args.find("--output-dir") != args.end()) {
+        output_dir = args["--output-dir"]; // Directory for containing SPIR-V output
+    }
+    if (args.find("--target-hpp") != args.end()) {
+        target_hpp = args["--target-hpp"]; // Path to generated header file
+    }
+    if (args.find("--target-cpp") != args.end()) {
+        target_cpp = args["--target-cpp"]; // Path to generated cpp file
+    }
+    if (args.find("--no-clean") != args.end()) {
+        no_clean = true; // Keep temporary SPIR-V files in output-dir after build
+    }
+
+    if (!directory_exists(input_dir)) {
+        std::cerr << "\"" << input_dir << "\" must be a valid directory containing shader sources" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    if (!directory_exists(output_dir)) {
+        if (!create_directory(output_dir)) {
+            std::cerr << "Error creating output directory: " << output_dir << "\n";
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::vector> tasks;
+    process_shaders(tasks);
+
+    for (auto& task : tasks) {
+        task.get();
+    }
+
+    write_output_files();
+
+    return EXIT_SUCCESS;
+}

From fa79495bb4897953a75607addd9d2cdd2ec63222 Mon Sep 17 00:00:00 2001
From: compilade 
Date: Sat, 13 Jul 2024 23:35:10 -0400
Subject: [PATCH 178/326] llama : fix pre-tokenization of non-special added
 tokens (#8228)

* llama : fix mpt and olmo pre-tokenizer

* llama : pre-tokenize non-special user-defined tokens first

* llama : fix detection of control-like user-defined tokens

* convert_hf : identify which user-defined tokens are control tokens

Only used in _set_vocab_gpt2() for now.

* convert_hf : identify more added control tokens for SPM tokenziers

This makes Gemma and Gemma-2 tokenize pretty much EVERYTHING correctly,
including HTML tags and consecutive spaces,
but it unfortunately requires model re-conversion.

There seems to be a weird behavior of the HF tokenizer for Gemma,
which prefers to use the 16-space token over more lengthy space tokens,
while using the SentencePiece tokenizer does not do this.
(the implementation in llama.cpp has the same behavior as SentencePiece)

* llama : fix wrong pre-tokenization of byte tokens

* llama : fix Viking pre-tokenizer regex

The order was previously wrong, which caused errors in some tests.

* llama : fix command-r detokenization

* convert_hf : reduce usages of the UNKNOWN token type

* llama : add UNKNOWN tokens in the special tokens cache

* convert_hf : reduce usages of UNKNOWN for InternLM2

This makes the changes from #8321 more consistent
with the other changes made here.

* test-tokenizer-random : reduce potential confilcts with #8379

* test-tokenizer-random : add a failing edge case for falcon
---
 convert_hf_to_gguf.py          | 112 +++++++++++++++++++++------------
 src/llama.cpp                  |  29 +++++----
 tests/test-tokenizer-0.cpp     |   4 +-
 tests/test-tokenizer-random.py |   7 ++-
 4 files changed, 91 insertions(+), 61 deletions(-)

diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py
index cf930be17a6e0..af82cd6cd05c9 100755
--- a/convert_hf_to_gguf.py
+++ b/convert_hf_to_gguf.py
@@ -373,6 +373,29 @@ def from_model_architecture(cls, arch: str) -> type[Model]:
         except KeyError:
             raise NotImplementedError(f'Architecture {arch!r} not supported!') from None
 
+    def does_token_look_special(self, token: str | bytes) -> bool:
+        if isinstance(token, (bytes, bytearray)):
+            token_text = token.decode(encoding="utf-8")
+        elif isinstance(token, memoryview):
+            token_text = token.tobytes().decode(encoding="utf-8")
+        else:
+            token_text = token
+
+        # Some models mark some added tokens which ought to be control tokens as not special.
+        # (e.g. command-r, command-r-plus, deepseek-coder, gemma{,-2})
+        seems_special = token_text in (
+            "",  # deepseek-coder
+            "", "<2mass>", "[@BOS@]",  # gemma{,-2}
+        )
+
+        seems_special = seems_special or (token_text.startswith("<|") and token_text.endswith("|>"))
+        seems_special = seems_special or (token_text.startswith("<｜") and token_text.endswith("｜>"))  # deepseek-coder
+
+        # TODO: should these be marked as UNUSED instead? (maybe not)
+        seems_special = seems_special or (token_text.startswith(""))  # gemma{,-2}
+
+        return seems_special
+
     # used for GPT-2 BPE and WordPiece vocabs
     def get_vocab_base(self) -> tuple[list[str], list[int], str]:
         tokens: list[str] = []
@@ -391,16 +414,18 @@ def get_vocab_base(self) -> tuple[list[str], list[int], str]:
         for i in range(vocab_size):
             if i not in reverse_vocab:
                 tokens.append(f"[PAD{i}]")
-                toktypes.append(gguf.TokenType.USER_DEFINED)
-            elif reverse_vocab[i] in added_vocab:
-                tokens.append(reverse_vocab[i])
-                if tokenizer.added_tokens_decoder[i].special:
-                    toktypes.append(gguf.TokenType.CONTROL)
-                else:
-                    toktypes.append(gguf.TokenType.USER_DEFINED)
+                toktypes.append(gguf.TokenType.UNUSED)
             else:
-                tokens.append(reverse_vocab[i])
-                toktypes.append(gguf.TokenType.NORMAL)
+                token: str = reverse_vocab[i]
+                if token in added_vocab:
+                    if tokenizer.added_tokens_decoder[i].special or self.does_token_look_special(token):
+                        toktypes.append(gguf.TokenType.CONTROL)
+                    else:
+                        token = token.replace(b"\xe2\x96\x81".decode("utf-8"), " ")  # pre-normalize user-defined spaces
+                        toktypes.append(gguf.TokenType.USER_DEFINED)
+                else:
+                    toktypes.append(gguf.TokenType.NORMAL)
+                tokens.append(token)
 
         return tokens, toktypes, tokpre
 
@@ -559,7 +584,7 @@ def _set_vocab_qwen(self):
         for i in range(vocab_size):
             if i not in reverse_vocab:
                 tokens.append(f"[PAD{i}]")
-                toktypes.append(gguf.TokenType.USER_DEFINED)
+                toktypes.append(gguf.TokenType.UNUSED)
             elif reverse_vocab[i] in added_vocab:
                 tokens.append(reverse_vocab[i])
                 toktypes.append(gguf.TokenType.CONTROL)
@@ -609,7 +634,7 @@ def _create_vocab_sentencepiece(self):
 
         tokens: list[bytes] = [f"[PAD{i}]".encode("utf-8") for i in range(vocab_size)]
         scores: list[float] = [-10000.0] * vocab_size
-        toktypes: list[int] = [SentencePieceTokenTypes.UNKNOWN] * vocab_size
+        toktypes: list[int] = [SentencePieceTokenTypes.UNUSED] * vocab_size
 
         for token_id in range(tokenizer.vocab_size()):
             piece = tokenizer.IdToPiece(token_id)
@@ -644,6 +669,25 @@ def _create_vocab_sentencepiece(self):
                     scores[token_id] = -1000.0
                     toktypes[token_id] = SentencePieceTokenTypes.USER_DEFINED
 
+        tokenizer_config_file = self.dir_model / 'tokenizer_config.json'
+        if tokenizer_config_file.is_file():
+            with open(tokenizer_config_file, "r", encoding="utf-8") as f:
+                tokenizer_config_json = json.load(f)
+                added_tokens_decoder = tokenizer_config_json.get("added_tokens_decoder", {})
+                for token_id, token_data in added_tokens_decoder.items():
+                    token_id = int(token_id)
+                    token: str = token_data["content"]
+                    if toktypes[token_id] != SentencePieceTokenTypes.UNUSED:
+                        assert tokens[token_id] == token.encode("utf-8")
+                    if token_data.get("special") or self.does_token_look_special(token):
+                        toktypes[token_id] = SentencePieceTokenTypes.CONTROL
+                    else:
+                        token = token.replace(b"\xe2\x96\x81".decode("utf-8"), " ")  # pre-normalize user-defined spaces
+                        toktypes[token_id] = SentencePieceTokenTypes.USER_DEFINED
+
+                    scores[token_id] = -1000.0
+                    tokens[token_id] = token.encode("utf-8")
+
         if vocab_size > len(tokens):
             pad_count = vocab_size - len(tokens)
             logger.debug(f"Padding vocab with {pad_count} token(s) - [PAD1] through [PAD{pad_count}]")
@@ -1266,7 +1310,7 @@ def set_vocab(self):
         if (self.dir_model / "tokenizer.json").is_file():
             self._set_vocab_gpt2()
         else:
-            # StableLM 2 1.6B uses a vocab in a similar format to Qwen's vocab
+            # StableLM 2 1.6B used to have a vocab in a similar format to Qwen's vocab
             self._set_vocab_qwen()
 
     def set_gguf_parameters(self):
@@ -1578,7 +1622,6 @@ def set_gguf_parameters(self):
         self.gguf_writer.add_rope_freq_base(attn_config["rope_theta"])
 
         self.gguf_writer.add_clamp_kqv(attn_config["clip_qkv"])
-        self.gguf_writer.add_file_type(self.ftype)
 
         self.gguf_writer.add_expert_count(ffn_config["moe_num_experts"])
         self.gguf_writer.add_expert_used_count(ffn_config["moe_top_k"])
@@ -1872,7 +1915,7 @@ def set_vocab(self):
 
         tokens: list[bytes] = [f"[PAD{i}]".encode("utf-8") for i in range(vocab_size)]
         scores: list[float] = [-10000.0] * vocab_size
-        toktypes: list[int] = [SentencePieceTokenTypes.UNKNOWN] * vocab_size
+        toktypes: list[int] = [SentencePieceTokenTypes.UNUSED] * vocab_size
 
         for token_id in range(tokenizer.vocab_size()):
 
@@ -1917,7 +1960,7 @@ def set_vocab(self):
                 for token_id, foken_data in added_tokens_decoder.items():
                     token_id = int(token_id)
                     token = foken_data["content"].encode("utf-8")
-                    if toktypes[token_id] != SentencePieceTokenTypes.UNKNOWN:
+                    if toktypes[token_id] != SentencePieceTokenTypes.UNUSED:
                         assert tokens[token_id] == token
                     tokens[token_id] = token
                     scores[token_id] = -1000.0
@@ -1933,7 +1976,7 @@ def set_vocab(self):
                 for foken_data in added_tokens:
                     token_id = int(foken_data["id"])
                     token = foken_data["content"].encode("utf-8")
-                    if toktypes[token_id] != SentencePieceTokenTypes.UNKNOWN:
+                    if toktypes[token_id] != SentencePieceTokenTypes.UNUSED:
                         assert tokens[token_id] == token
                     tokens[token_id] = token
                     scores[token_id] = -1000.0
@@ -2145,7 +2188,7 @@ def set_vocab(self):
                 toktype = SentencePieceTokenTypes.BYTE
             # take care of ununsed raw token
             if piece.startswith('[UNUSED'):
-                toktype = SentencePieceTokenTypes.UNKNOWN
+                toktype = SentencePieceTokenTypes.UNUSED
 
             tokens.append(text)
             scores.append(score)
@@ -2175,7 +2218,7 @@ def set_vocab(self):
                     if token == chat_eos_token:
                         chat_eos_token_id = token_id
                     token = token.encode("utf-8")
-                    if toktypes[token_id] != SentencePieceTokenTypes.UNKNOWN:
+                    if toktypes[token_id] != SentencePieceTokenTypes.UNUSED:
                         assert(tokens[token_id] == token)
                     tokens[token_id] = token
                     scores[token_id] = -1000.0
@@ -2194,7 +2237,7 @@ def set_vocab(self):
                     if token == chat_eos_token:
                         chat_eos_token_id = token_id
                     token = token.encode("utf-8")
-                    if toktypes[token_id] != SentencePieceTokenTypes.UNKNOWN:
+                    if toktypes[token_id] != SentencePieceTokenTypes.UNUSED:
                         assert(tokens[token_id] == token)
                     tokens[token_id] = token
                     scores[token_id] = -1000.0
@@ -2434,19 +2477,7 @@ class Gemma2Model(Model):
     model_arch = gguf.MODEL_ARCH.GEMMA2
 
     def set_vocab(self):
-        tokens, scores, toktypes = self._create_vocab_sentencepiece()
-        # hack: This is required so that we can properly use start/end-of-turn for chat template
-        for i in range(108):
-            # including , , 
-            toktypes[i] = SentencePieceTokenTypes.CONTROL
-        self.gguf_writer.add_tokenizer_model("llama")
-        self.gguf_writer.add_tokenizer_pre("default")
-        self.gguf_writer.add_token_list(tokens)
-        self.gguf_writer.add_token_scores(scores)
-        self.gguf_writer.add_token_types(toktypes)
-
-        special_vocab = gguf.SpecialVocab(self.dir_model, n_vocab=len(tokens))
-        special_vocab.add_to_gguf(self.gguf_writer)
+        self._set_vocab_sentencepiece()
 
         self.gguf_writer.add_add_space_prefix(False)
 
@@ -2770,7 +2801,7 @@ def set_vocab(self):
 
         tokens: list[bytes] = [f"[PAD{i}]".encode("utf-8") for i in range(vocab_size)]
         scores: list[float] = [-10000.0] * vocab_size
-        toktypes: list[int] = [SentencePieceTokenTypes.UNKNOWN] * vocab_size
+        toktypes: list[int] = [SentencePieceTokenTypes.UNUSED] * vocab_size
 
         for token_id in range(tokenizer.vocab_size()):
 
@@ -3025,7 +3056,7 @@ def set_vocab(self):
 
         tokens: list[bytes] = [f"[PAD{i}]".encode("utf-8") for i in range(vocab_size)]
         scores: list[float] = [-10000.0] * vocab_size
-        toktypes: list[int] = [SentencePieceTokenTypes.UNKNOWN] * vocab_size
+        toktypes: list[int] = [SentencePieceTokenTypes.UNUSED] * vocab_size
 
         for token_id in range(tokenizer.vocab_size()):
             piece = tokenizer.IdToPiece(token_id)
@@ -3243,15 +3274,14 @@ def set_vocab_chatglm3(self):
             if len(piece) != 0 and token_id < tokenizer.tokenizer.sp_model.vocab_size():
                 score = tokenizer.tokenizer.sp_model.get_score(token_id)
 
-            if len(piece) == 0:
-                text = f"[PAD{token_id}]".encode("utf-8")
-
             if token_id >= tokenizer.tokenizer.sp_model.vocab_size():
                 if piece in special_tokens:
-                    # show special tokens in prompt
-                    toktype = SentencePieceTokenTypes.USER_DEFINED
+                    toktype = SentencePieceTokenTypes.CONTROL
+                elif len(piece) == 0:
+                    text = f"[PAD{token_id}]".encode("utf-8")
+                    toktype = SentencePieceTokenTypes.UNUSED
                 else:
-                    toktype = SentencePieceTokenTypes.UNKNOWN
+                    toktype = SentencePieceTokenTypes.USER_DEFINED
                 tokens.append(text)
                 scores.append(score)
                 toktypes.append(toktype)
@@ -3340,7 +3370,7 @@ def set_vocab(self):
         for i in range(vocab_size):
             if i not in reverse_vocab:
                 tokens.append(f"[PAD{i}]")
-                toktypes.append(gguf.TokenType.USER_DEFINED)
+                toktypes.append(gguf.TokenType.UNUSED)
             elif reverse_vocab[i] in added_vocab:
                 tokens.append(reverse_vocab[i])
                 if tokenizer.added_tokens_decoder[i].special:
diff --git a/src/llama.cpp b/src/llama.cpp
index 59b76a6d80cdf..77d34dca280fc 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -5419,6 +5419,7 @@ static void llm_load_vocab(
             } else if (
                 tokenizer_pre == "command-r") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_COMMAND_R;
+                vocab.tokenizer_clean_spaces = false;
             } else if (
                 tokenizer_pre == "qwen2") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_QWEN2;
@@ -5652,7 +5653,7 @@ static void llm_load_vocab(
     // build special tokens cache
     {
         for (llama_vocab::id id = 0; id < (llama_vocab::id)n_vocab; ++id) {
-            if (!(vocab.id_to_token[id].attr & LLAMA_TOKEN_ATTR_NORMAL)) {
+            if (vocab.id_to_token[id].attr & (LLAMA_TOKEN_ATTR_CONTROL | LLAMA_TOKEN_ATTR_USER_DEFINED | LLAMA_TOKEN_ATTR_UNKNOWN)) {
                 vocab.cache_special_tokens.push_back(id);
             }
         }
@@ -15411,17 +15412,6 @@ struct llm_tokenizer_bpe {
                     "[0-9][0-9][0-9]",
                 };
                 break;
-            case LLAMA_VOCAB_PRE_TYPE_MPT:
-                // TODO: MPT pre-tokenization regexes are unknown
-                //       the following are close, but not exact. run the following:
-                //       ./bin/test-tokenizer-0 ../models/ggml-vocab-mpt.gguf
-                GGML_ASSERT("MPT pre-tokenization regexes are unknown - fixes needed");
-                regex_exprs = {
-                    "\\s?\\p{L}+",
-                    "\\s?\\p{P}+",
-                    "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)",
-                };
-                break;
             case LLAMA_VOCAB_PRE_TYPE_STARCODER:
             case LLAMA_VOCAB_PRE_TYPE_REFACT:
             case LLAMA_VOCAB_PRE_TYPE_COMMAND_R:
@@ -15431,6 +15421,7 @@ struct llm_tokenizer_bpe {
                 };
                 break;
             case LLAMA_VOCAB_PRE_TYPE_GPT2:
+            case LLAMA_VOCAB_PRE_TYPE_MPT:
             case LLAMA_VOCAB_PRE_TYPE_OLMO:
             case LLAMA_VOCAB_PRE_TYPE_JAIS:
                 regex_exprs = {
@@ -15457,8 +15448,8 @@ struct llm_tokenizer_bpe {
                 break;
             case LLAMA_VOCAB_PRE_TYPE_VIKING:
                 regex_exprs = {
-                    "\\p{N}",
                     " ?[^(\\s|.,!?…。，、।۔،)]+",
+                    "\\p{N}",
                 };
                 break;
             default:
@@ -16178,12 +16169,20 @@ struct fragment_buffer_variant {
 
 // #define PRETOKENIZERDEBUG
 
-static void tokenizer_st_partition(const llama_vocab & vocab, std::forward_list & buffer) {
+static void tokenizer_st_partition(const llama_vocab & vocab, std::forward_list & buffer, bool parse_special) {
     // for each special token
     for (const llama_vocab::id special_id : vocab.cache_special_tokens) {
         const auto & data = vocab.id_to_token[special_id];
         const auto & special_token = data.text;
 
+        if (!parse_special && (data.attr & (LLAMA_TOKEN_ATTR_CONTROL | LLAMA_TOKEN_ATTR_UNKNOWN))) {
+            // Ignore control and unknown tokens when parse_special == false
+            continue;
+            // User-defined tokens are still pre-tokenized before everything else
+            // ref: https://github.com/huggingface/tokenizers/blob/fdd26ba9a3f0c133427aab0423888cbde91362d7/tokenizers/src/tokenizer/mod.rs#L726
+            // This is mostly relevant for neox-style tokenizers (mpt, olmo, stablelm, etc.)
+        }
+
         // for each text fragment
         std::forward_list::iterator it = buffer.begin();
         while (it != buffer.end()) {
@@ -16296,7 +16295,7 @@ static std::vector llama_tokenize_internal(const llama_vocab &
 
     if (!raw_text.empty()) {
         fragment_buffer.emplace_front(raw_text, 0, raw_text.length());
-        if (parse_special) tokenizer_st_partition(vocab, fragment_buffer);
+        tokenizer_st_partition(vocab, fragment_buffer, parse_special);
     }
 
     switch (vocab.type) {
diff --git a/tests/test-tokenizer-0.cpp b/tests/test-tokenizer-0.cpp
index 1f04b6f34ad7e..d3d21331bfd3d 100644
--- a/tests/test-tokenizer-0.cpp
+++ b/tests/test-tokenizer-0.cpp
@@ -195,7 +195,7 @@ int main(int argc, char **argv) {
     const bool add_special = false;
 
     for (const auto & test_kv : k_tests) {
-        const std::vector res = llama_tokenize(ctx, test_kv.first, add_special, true);
+        const std::vector res = llama_tokenize(ctx, test_kv.first, add_special, false);
 
         printf("\n");
         printf("src: '%s'\n", test_kv.first.c_str());
@@ -253,7 +253,7 @@ int main(int argc, char **argv) {
         {
             const auto t_start = ggml_time_us();
 
-            res = llama_tokenize(ctx, text, add_special, true);
+            res = llama_tokenize(ctx, text, add_special, false);
 
             const auto t_end = ggml_time_us();
 
diff --git a/tests/test-tokenizer-random.py b/tests/test-tokenizer-random.py
index c50a8ca32f657..9ebe6c89185a3 100644
--- a/tests/test-tokenizer-random.py
+++ b/tests/test-tokenizer-random.py
@@ -20,7 +20,7 @@
 from typing_extensions import Buffer
 
 import cffi
-from transformers import AutoTokenizer
+from transformers import AutoTokenizer, PreTrainedTokenizer
 
 
 logger = logging.getLogger("test-tokenizer-random")
@@ -129,7 +129,7 @@ def decode(self, ids: list[int]) -> str:
 class TokenizerGroundtruth (Tokenizer):
 
     def __init__(self, dir_tokenizer: str):
-        self.model = AutoTokenizer.from_pretrained(dir_tokenizer)
+        self.model: PreTrainedTokenizer = AutoTokenizer.from_pretrained(dir_tokenizer)
         # guess BOS and EOS
         ids = self.encode("a")
         assert 1 <= len(ids) <= 3
@@ -143,7 +143,7 @@ def __init__(self, dir_tokenizer: str):
         self.vocab = list(sorted(self.vocab))
         # tokens and lists
         self.special_tokens = list(self.model.all_special_tokens)
-        self.added_tokens   = list(self.model.added_tokens_encoder)
+        self.added_tokens   = self.model.batch_decode(self.model.added_tokens_encoder.values(), skip_special_tokens=False)
         self.bos_token = self.model.bos_token
         self.eos_token = self.model.eos_token
 
@@ -232,6 +232,7 @@ def generator_custom_text_edge_cases() -> Iterator[str]:
         'a\na',            # bert fail
         '"`',              # falcon
         ' \u2e4e',         # falcon
+        '\n\x0b  ',        # falcon
         'a\xa0\xa0\x00b',  # jina-v2-es
         'one ',      # jina-v2-es   lstrip=true
         'a  b',        # rstrip phi-3

From e236528e7628a0e59751eee9addf21fc3c33d376 Mon Sep 17 00:00:00 2001
From: Brian 
Date: Sun, 14 Jul 2024 16:47:14 +1000
Subject: [PATCH 179/326] gguf_hash.py: Add sha256 (#8470)

* gguf_hash.py: Add sha256

* gguf_hash.py: rename string UUIDv5 --> uuid

* Apply suggestions from code review

Co-authored-by: compilade 

---------

Co-authored-by: compilade 
---
 gguf-py/scripts/gguf_hash.py | 27 +++++++++++++++++++--------
 1 file changed, 19 insertions(+), 8 deletions(-)

diff --git a/gguf-py/scripts/gguf_hash.py b/gguf-py/scripts/gguf_hash.py
index 770b79a93471c..ee34d09bfe7ef 100755
--- a/gguf-py/scripts/gguf_hash.py
+++ b/gguf-py/scripts/gguf_hash.py
@@ -27,8 +27,9 @@
 
 # For more information about what field.parts and field.data represent,
 # please see the comments in the modify_gguf.py example.
-def gguf_hash(reader: GGUFReader, filename: str, disable_progress_bar) -> None:
+def gguf_hash(reader: GGUFReader, filename: str, disable_progress_bar: bool, no_layer: bool) -> None:
     sha1 = hashlib.sha1()
+    sha256 = hashlib.sha256()
     uuidv5_sha1 = hashlib.sha1()
     uuidv5_sha1.update(UUID_NAMESPACE_LLAMA_CPP.bytes)
 
@@ -50,7 +51,7 @@ def gguf_hash(reader: GGUFReader, filename: str, disable_progress_bar) -> None:
     bar = tqdm(desc="Hashing", total=total_weights, unit="weights", unit_scale=True, disable=disable_progress_bar)
 
     # Hashing Process
-    for n, tensor in enumerate(reader.tensors, 1):
+    for tensor in reader.tensors:
 
         # We don't need these
         if tensor.name.endswith((".attention.masked_bias", ".attention.bias", ".rotary_emb.inv_freq")):
@@ -62,29 +63,39 @@ def gguf_hash(reader: GGUFReader, filename: str, disable_progress_bar) -> None:
             sum_weights_in_tensor *= dim
         bar.update(sum_weights_in_tensor)
 
-        sha1_layer = hashlib.sha1()
-        sha1_layer.update(tensor.data.data)
+        if not no_layer:
+
+            sha1_layer = hashlib.sha1()
+            sha1_layer.update(tensor.data.data)
+            print("sha1      {0}  {1}:{2}".format(sha1_layer.hexdigest(), filename, tensor.name)) # noqa: NP100
+
+            sha256_layer = hashlib.sha256()
+            sha256_layer.update(tensor.data.data)
+            print("sha256    {0}  {1}:{2}".format(sha256_layer.hexdigest(), filename, tensor.name)) # noqa: NP100
+
         sha1.update(tensor.data.data)
+        sha256.update(tensor.data.data)
         uuidv5_sha1.update(tensor.data.data)
-        print("sha1    {0}  {1}:{2}".format(sha1_layer.hexdigest(), filename, tensor.name)) # noqa: NP100
 
     # Flush Hash Progress Bar
     bar.close()
 
     # Display Hash Output
-    print("sha1    {0}  {1}".format(sha1.hexdigest(), filename)) # noqa: NP100
-    print("UUIDv5  {0}  {1}".format(uuid.UUID(bytes=uuidv5_sha1.digest()[:16], version=5), filename)) # noqa: NP100
+    print("sha1      {0}  {1}".format(sha1.hexdigest(), filename)) # noqa: NP100
+    print("sha256    {0}  {1}".format(sha256.hexdigest(), filename)) # noqa: NP100
+    print("uuid      {0}  {1}".format(uuid.UUID(bytes=uuidv5_sha1.digest()[:16], version=5), filename)) # noqa: NP100
 
 
 def main() -> None:
     parser = argparse.ArgumentParser(description="Dump GGUF file metadata")
     parser.add_argument("model",         type=str,            help="GGUF format model filename")
+    parser.add_argument("--no-layer",    action="store_true", help="exclude per layer hash")
     parser.add_argument("--verbose",     action="store_true", help="increase output verbosity")
     parser.add_argument("--progressbar", action="store_true", help="enable progressbar")
     args = parser.parse_args(None if len(sys.argv) > 1 else ["--help"])
     logging.basicConfig(level=logging.DEBUG if args.verbose else logging.INFO)
     reader = GGUFReader(args.model, 'r')
-    gguf_hash(reader, args.model, not args.progressbar)
+    gguf_hash(reader, args.model, not args.progressbar, args.no_layer)
 
 
 if __name__ == '__main__':

From 73cf442e7bc9baca7b3e213b261551812f1676c9 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Sun, 14 Jul 2024 14:05:09 +0300
Subject: [PATCH 180/326] llama : fix Gemma-2 Query scaling factors (#8473)

* 9B - query_pre_attn_scalar = 256 not 224

See https://github.com/google/gemma_pytorch/commit/03e657582d17cb5a8617ebf333c1c16f3694670e

Gemma 9b should use 256 and not 224 (self.config.hidden_size // self.config.num_attention_heads)

* llama : fix Gemma-2 Query scaling factor

ggml-ci

---------

Co-authored-by: Daniel Han 
---
 convert_hf_to_gguf.py | 5 -----
 src/llama.cpp         | 7 ++++++-
 2 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py
index af82cd6cd05c9..42dace219f20f 100755
--- a/convert_hf_to_gguf.py
+++ b/convert_hf_to_gguf.py
@@ -2504,11 +2504,6 @@ def set_gguf_parameters(self):
         )
         self.gguf_writer.add_sliding_window(self.hparams["sliding_window"])
 
-        # sanity check
-        attn_scalar = self.hparams["query_pre_attn_scalar"]
-        if attn_scalar != hparams["hidden_size"] / hparams["num_attention_heads"]:
-            raise ValueError("query_pre_attn_scalar must be equal to n_embd / n_head")
-
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         del bid  # unused
 
diff --git a/src/llama.cpp b/src/llama.cpp
index 77d34dca280fc..400a4232beeb0 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -11680,7 +11680,12 @@ struct llm_build_context {
                         ext_factor, attn_factor, beta_fast, beta_slow);
                 cb(Qcur, "Qcur", il);
 
-                Qcur = ggml_scale(ctx0, Qcur, 1.0f / sqrtf(float(n_embd / n_head)));
+                // ref: https://github.com/google/gemma_pytorch/commit/03e657582d17cb5a8617ebf333c1c16f3694670e
+                switch (model.type) {
+                    case e_model::MODEL_9B:  Qcur = ggml_scale(ctx0, Qcur, 1.0f / sqrtf(float(n_embd_head_k)));   break;
+                    case e_model::MODEL_27B: Qcur = ggml_scale(ctx0, Qcur, 1.0f / sqrtf(float(n_embd / n_head))); break;
+                    default: GGML_ASSERT(false);
+                };
                 cb(Qcur, "Qcur_scaled", il);
 
                 Kcur = ggml_rope_ext(

From aaab2419eaa17ab3aa38f4ba49c7eea406999e99 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Sun, 14 Jul 2024 18:54:02 +0300
Subject: [PATCH 181/326] flake.lock: Update (#8475)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Flake lock file updates:

• Updated input 'nixpkgs':
    'github:NixOS/nixpkgs/9f4128e00b0ae8ec65918efeba59db998750ead6?narHash=sha256-rwz8NJZV%2B387rnWpTYcXaRNvzUSnnF9aHONoJIYmiUQ%3D' (2024-07-03)
  → 'github:NixOS/nixpkgs/7e7c39ea35c5cdd002cd4588b03a3fb9ece6fad9?narHash=sha256-EYekUHJE2gxeo2pM/zM9Wlqw1Uw2XTJXOSAO79ksc4Y%3D' (2024-07-12)

Co-authored-by: github-actions[bot] 
---
 flake.lock | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/flake.lock b/flake.lock
index 5001fbf912c5c..3e5125dde3b14 100644
--- a/flake.lock
+++ b/flake.lock
@@ -20,11 +20,11 @@
     },
     "nixpkgs": {
       "locked": {
-        "lastModified": 1720031269,
-        "narHash": "sha256-rwz8NJZV+387rnWpTYcXaRNvzUSnnF9aHONoJIYmiUQ=",
+        "lastModified": 1720768451,
+        "narHash": "sha256-EYekUHJE2gxeo2pM/zM9Wlqw1Uw2XTJXOSAO79ksc4Y=",
         "owner": "NixOS",
         "repo": "nixpkgs",
-        "rev": "9f4128e00b0ae8ec65918efeba59db998750ead6",
+        "rev": "7e7c39ea35c5cdd002cd4588b03a3fb9ece6fad9",
         "type": "github"
       },
       "original": {

From 090fca7a073efe9ad3dd2b9ac12491a4f20ac957 Mon Sep 17 00:00:00 2001
From: compilade 
Date: Sun, 14 Jul 2024 19:51:21 -0400
Subject: [PATCH 182/326] pydantic : replace uses of __annotations__ with
 get_type_hints (#8474)

* pydantic : replace uses of __annotations__ with get_type_hints

* pydantic : fix Python 3.9 and 3.10 support
---
 examples/pydantic_models_to_grammar.py        | 77 +++++++++++--------
 .../pydantic_models_to_grammar_examples.py    |  2 +
 requirements/requirements-pydantic.txt        |  1 +
 3 files changed, 46 insertions(+), 34 deletions(-)

diff --git a/examples/pydantic_models_to_grammar.py b/examples/pydantic_models_to_grammar.py
index d8145710ce250..93e5dcb6c3855 100644
--- a/examples/pydantic_models_to_grammar.py
+++ b/examples/pydantic_models_to_grammar.py
@@ -6,7 +6,7 @@
 from copy import copy
 from enum import Enum
 from inspect import getdoc, isclass
-from typing import TYPE_CHECKING, Any, Callable, List, Optional, Union, get_args, get_origin
+from typing import TYPE_CHECKING, Any, Callable, List, Optional, Union, get_args, get_origin, get_type_hints
 
 from docstring_parser import parse
 from pydantic import BaseModel, create_model
@@ -53,35 +53,38 @@ class PydanticDataType(Enum):
 
 
 def map_pydantic_type_to_gbnf(pydantic_type: type[Any]) -> str:
-    if isclass(pydantic_type) and issubclass(pydantic_type, str):
+    origin_type = get_origin(pydantic_type)
+    origin_type = pydantic_type if origin_type is None else origin_type
+
+    if isclass(origin_type) and issubclass(origin_type, str):
         return PydanticDataType.STRING.value
-    elif isclass(pydantic_type) and issubclass(pydantic_type, bool):
+    elif isclass(origin_type) and issubclass(origin_type, bool):
         return PydanticDataType.BOOLEAN.value
-    elif isclass(pydantic_type) and issubclass(pydantic_type, int):
+    elif isclass(origin_type) and issubclass(origin_type, int):
         return PydanticDataType.INTEGER.value
-    elif isclass(pydantic_type) and issubclass(pydantic_type, float):
+    elif isclass(origin_type) and issubclass(origin_type, float):
         return PydanticDataType.FLOAT.value
-    elif isclass(pydantic_type) and issubclass(pydantic_type, Enum):
+    elif isclass(origin_type) and issubclass(origin_type, Enum):
         return PydanticDataType.ENUM.value
 
-    elif isclass(pydantic_type) and issubclass(pydantic_type, BaseModel):
-        return format_model_and_field_name(pydantic_type.__name__)
-    elif get_origin(pydantic_type) is list:
+    elif isclass(origin_type) and issubclass(origin_type, BaseModel):
+        return format_model_and_field_name(origin_type.__name__)
+    elif origin_type is list:
         element_type = get_args(pydantic_type)[0]
         return f"{map_pydantic_type_to_gbnf(element_type)}-list"
-    elif get_origin(pydantic_type) is set:
+    elif origin_type is set:
         element_type = get_args(pydantic_type)[0]
         return f"{map_pydantic_type_to_gbnf(element_type)}-set"
-    elif get_origin(pydantic_type) is Union:
+    elif origin_type is Union:
         union_types = get_args(pydantic_type)
         union_rules = [map_pydantic_type_to_gbnf(ut) for ut in union_types]
         return f"union-{'-or-'.join(union_rules)}"
-    elif get_origin(pydantic_type) is Optional:
+    elif origin_type is Optional:
         element_type = get_args(pydantic_type)[0]
         return f"optional-{map_pydantic_type_to_gbnf(element_type)}"
-    elif isclass(pydantic_type):
-        return f"{PydanticDataType.CUSTOM_CLASS.value}-{format_model_and_field_name(pydantic_type.__name__)}"
-    elif get_origin(pydantic_type) is dict:
+    elif isclass(origin_type):
+        return f"{PydanticDataType.CUSTOM_CLASS.value}-{format_model_and_field_name(origin_type.__name__)}"
+    elif origin_type is dict:
         key_type, value_type = get_args(pydantic_type)
         return f"custom-dict-key-type-{format_model_and_field_name(map_pydantic_type_to_gbnf(key_type))}-value-type-{format_model_and_field_name(map_pydantic_type_to_gbnf(value_type))}"
     else:
@@ -118,7 +121,7 @@ def get_members_structure(cls, rule_name):
         # Modify this comprehension
         members = [
             f'  "\\"{name}\\"" ":"  {map_pydantic_type_to_gbnf(param_type)}'
-            for name, param_type in cls.__annotations__.items()
+            for name, param_type in get_type_hints(cls).items()
             if name != "self"
         ]
 
@@ -297,17 +300,20 @@ def generate_gbnf_rule_for_type(
     field_name = format_model_and_field_name(field_name)
     gbnf_type = map_pydantic_type_to_gbnf(field_type)
 
-    if isclass(field_type) and issubclass(field_type, BaseModel):
+    origin_type = get_origin(field_type)
+    origin_type = field_type if origin_type is None else origin_type
+
+    if isclass(origin_type) and issubclass(origin_type, BaseModel):
         nested_model_name = format_model_and_field_name(field_type.__name__)
         nested_model_rules, _ = generate_gbnf_grammar(field_type, processed_models, created_rules)
         rules.extend(nested_model_rules)
         gbnf_type, rules = nested_model_name, rules
-    elif isclass(field_type) and issubclass(field_type, Enum):
+    elif isclass(origin_type) and issubclass(origin_type, Enum):
         enum_values = [f'"\\"{e.value}\\""' for e in field_type]  # Adding escaped quotes
         enum_rule = f"{model_name}-{field_name} ::= {' | '.join(enum_values)}"
         rules.append(enum_rule)
         gbnf_type, rules = model_name + "-" + field_name, rules
-    elif get_origin(field_type) == list:  # Array
+    elif origin_type is list:  # Array
         element_type = get_args(field_type)[0]
         element_rule_name, additional_rules = generate_gbnf_rule_for_type(
             model_name, f"{field_name}-element", element_type, is_optional, processed_models, created_rules
@@ -317,7 +323,7 @@ def generate_gbnf_rule_for_type(
         rules.append(array_rule)
         gbnf_type, rules = model_name + "-" + field_name, rules
 
-    elif get_origin(field_type) == set or field_type == set:  # Array
+    elif origin_type is set:  # Array
         element_type = get_args(field_type)[0]
         element_rule_name, additional_rules = generate_gbnf_rule_for_type(
             model_name, f"{field_name}-element", element_type, is_optional, processed_models, created_rules
@@ -371,7 +377,7 @@ def generate_gbnf_rule_for_type(
             gbnf_type = f"{model_name}-{field_name}-optional"
         else:
             gbnf_type = f"{model_name}-{field_name}-union"
-    elif isclass(field_type) and issubclass(field_type, str):
+    elif isclass(origin_type) and issubclass(origin_type, str):
         if field_info and hasattr(field_info, "json_schema_extra") and field_info.json_schema_extra is not None:
             triple_quoted_string = field_info.json_schema_extra.get("triple_quoted_string", False)
             markdown_string = field_info.json_schema_extra.get("markdown_code_block", False)
@@ -387,8 +393,8 @@ def generate_gbnf_rule_for_type(
             gbnf_type = PydanticDataType.STRING.value
 
     elif (
-        isclass(field_type)
-        and issubclass(field_type, float)
+        isclass(origin_type)
+        and issubclass(origin_type, float)
         and field_info
         and hasattr(field_info, "json_schema_extra")
         and field_info.json_schema_extra is not None
@@ -413,8 +419,8 @@ def generate_gbnf_rule_for_type(
         )
 
     elif (
-        isclass(field_type)
-        and issubclass(field_type, int)
+        isclass(origin_type)
+        and issubclass(origin_type, int)
         and field_info
         and hasattr(field_info, "json_schema_extra")
         and field_info.json_schema_extra is not None
@@ -462,7 +468,7 @@ def generate_gbnf_grammar(model: type[BaseModel], processed_models: set[type[Bas
     if not issubclass(model, BaseModel):
         # For non-Pydantic classes, generate model_fields from __annotations__ or __init__
         if hasattr(model, "__annotations__") and model.__annotations__:
-            model_fields = {name: (typ, ...) for name, typ in model.__annotations__.items()}  # pyright: ignore[reportGeneralTypeIssues]
+            model_fields = {name: (typ, ...) for name, typ in get_type_hints(model).items()}
         else:
             init_signature = inspect.signature(model.__init__)
             parameters = init_signature.parameters
@@ -470,7 +476,7 @@ def generate_gbnf_grammar(model: type[BaseModel], processed_models: set[type[Bas
                             name != "self"}
     else:
         # For Pydantic models, use model_fields and check for ellipsis (required fields)
-        model_fields = model.__annotations__
+        model_fields = get_type_hints(model)
 
     model_rule_parts = []
     nested_rules = []
@@ -706,7 +712,7 @@ def generate_markdown_documentation(
         else:
             documentation += f"  Fields:\n"  # noqa: F541
         if isclass(model) and issubclass(model, BaseModel):
-            for name, field_type in model.__annotations__.items():
+            for name, field_type in get_type_hints(model).items():
                 # if name == "markdown_code_block":
                 #    continue
                 if get_origin(field_type) == list:
@@ -754,14 +760,17 @@ def generate_field_markdown(
     field_info = model.model_fields.get(field_name)
     field_description = field_info.description if field_info and field_info.description else ""
 
-    if get_origin(field_type) == list:
+    origin_type = get_origin(field_type)
+    origin_type = field_type if origin_type is None else origin_type
+
+    if origin_type == list:
         element_type = get_args(field_type)[0]
         field_text = f"{indent}{field_name} ({format_model_and_field_name(field_type.__name__)} of {format_model_and_field_name(element_type.__name__)})"
         if field_description != "":
             field_text += ":\n"
         else:
             field_text += "\n"
-    elif get_origin(field_type) == Union:
+    elif origin_type == Union:
         element_types = get_args(field_type)
         types = []
         for element_type in element_types:
@@ -792,9 +801,9 @@ def generate_field_markdown(
             example_text = f"'{field_example}'" if isinstance(field_example, str) else field_example
             field_text += f"{indent}  Example: {example_text}\n"
 
-    if isclass(field_type) and issubclass(field_type, BaseModel):
+    if isclass(origin_type) and issubclass(origin_type, BaseModel):
         field_text += f"{indent}  Details:\n"
-        for name, type_ in field_type.__annotations__.items():
+        for name, type_ in get_type_hints(field_type).items():
             field_text += generate_field_markdown(name, type_, field_type, depth + 2)
 
     return field_text
@@ -855,7 +864,7 @@ def generate_text_documentation(
 
         if isclass(model) and issubclass(model, BaseModel):
             documentation_fields = ""
-            for name, field_type in model.__annotations__.items():
+            for name, field_type in get_type_hints(model).items():
                 # if name == "markdown_code_block":
                 #    continue
                 if get_origin(field_type) == list:
@@ -948,7 +957,7 @@ def generate_field_text(
 
     if isclass(field_type) and issubclass(field_type, BaseModel):
         field_text += f"{indent}  Details:\n"
-        for name, type_ in field_type.__annotations__.items():
+        for name, type_ in get_type_hints(field_type).items():
             field_text += generate_field_text(name, type_, field_type, depth + 2)
 
     return field_text
diff --git a/examples/pydantic_models_to_grammar_examples.py b/examples/pydantic_models_to_grammar_examples.py
index 8e7f46cf99a43..504ed98df64f2 100644
--- a/examples/pydantic_models_to_grammar_examples.py
+++ b/examples/pydantic_models_to_grammar_examples.py
@@ -20,6 +20,8 @@ def create_completion(prompt, grammar):
     response = requests.post("http://127.0.0.1:8080/completion", headers=headers, json=data)
     data = response.json()
 
+    assert data.get("error") is None, data
+
     print(data["content"])
     return data["content"]
 
diff --git a/requirements/requirements-pydantic.txt b/requirements/requirements-pydantic.txt
index 2f9455b147d68..bdd423e07ea36 100644
--- a/requirements/requirements-pydantic.txt
+++ b/requirements/requirements-pydantic.txt
@@ -1,2 +1,3 @@
 docstring_parser~=0.15
 pydantic~=2.6.3
+requests

From bda62d7999caa8c222b6c354ac1e7c7442508539 Mon Sep 17 00:00:00 2001
From: 0cc4m 
Date: Mon, 15 Jul 2024 09:38:52 +0200
Subject: [PATCH 183/326] Vulkan MMQ Fix (#8479)

* Fix incoherence by adding missing LOAD_VEC_A parameter

* Fix Vulkan op result checker build error
---
 ggml/src/ggml-vulkan.cpp                       | 16 ++++++++--------
 ggml/src/vulkan-shaders/vulkan-shaders-gen.cpp |  4 ++--
 2 files changed, 10 insertions(+), 10 deletions(-)

diff --git a/ggml/src/ggml-vulkan.cpp b/ggml/src/ggml-vulkan.cpp
index 101781ede4b4f..8efe32329693e 100644
--- a/ggml/src/ggml-vulkan.cpp
+++ b/ggml/src/ggml-vulkan.cpp
@@ -6561,7 +6561,7 @@ static void ggml_vk_print_tensor(ggml_backend_vk_context * ctx, const ggml_tenso
         ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) tensor->extra;
 
         vk_buffer buffer_gpu = extra->buffer_gpu.lock();
-        ggml_vk_buffer_read(ctx, buffer_gpu, extra->offset + tensor->view_offs, tensor_data, tensor_size);
+        ggml_vk_buffer_read(buffer_gpu, extra->offset + tensor->view_offs, tensor_data, tensor_size);
     }
 
     std::cerr << "TENSOR CHECK " << name << " (" << tensor->name << "): " << ggml_op_name(tensor->op) << std::endl;
@@ -6645,7 +6645,7 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_tensor *
                 for (int i3 = 0; i3 < src0->ne[3]; i3++) {
                     for (int i2 = 0; i2 < src0->ne[2]; i2++) {
                         const int idx = i3*src0->ne[2] + i2;
-                        ggml_vk_buffer_read(ctx, buffer_gpu, offset + idx * src0->nb[2], ((char *)src0_clone->data + idx * src0_clone->nb[2]), src0->ne[1] * src0->nb[1]);
+                        ggml_vk_buffer_read(buffer_gpu, offset + idx * src0->nb[2], ((char *)src0_clone->data + idx * src0_clone->nb[2]), src0->ne[1] * src0->nb[1]);
                     }
                 }
 
@@ -6658,7 +6658,7 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_tensor *
                 if (offset + src0_size >= buffer_gpu->size) {
                     src0_size = buffer_gpu->size - offset;
                 }
-                ggml_vk_buffer_read(ctx, buffer_gpu, offset, src0_clone->data, src0_size);
+                ggml_vk_buffer_read(buffer_gpu, offset, src0_clone->data, src0_size);
                 memcpy(src0_clone->nb, src0->nb, sizeof(size_t) * GGML_MAX_DIMS);
             }
         } else {
@@ -6687,7 +6687,7 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_tensor *
                 for (int i3 = 0; i3 < src1->ne[3]; i3++) {
                     for (int i2 = 0; i2 < src1->ne[2]; i2++) {
                         const int idx = i3*src1->ne[2] + i2;
-                        ggml_vk_buffer_read(ctx, buffer_gpu, offset + idx * src1->nb[2], ((char *)src1_clone->data + idx * src1_clone->nb[2]), src1->ne[1] * src1->nb[1]);
+                        ggml_vk_buffer_read(buffer_gpu, offset + idx * src1->nb[2], ((char *)src1_clone->data + idx * src1_clone->nb[2]), src1->ne[1] * src1->nb[1]);
                     }
                 }
 
@@ -6700,7 +6700,7 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_tensor *
                 if (offset + src1_size >= buffer_gpu->size) {
                     src1_size = buffer_gpu->size - offset;
                 }
-                ggml_vk_buffer_read(ctx, buffer_gpu, offset, src1_clone->data, src1_size);
+                ggml_vk_buffer_read(buffer_gpu, offset, src1_clone->data, src1_size);
                 memcpy(src1_clone->nb, src1->nb, sizeof(size_t) * GGML_MAX_DIMS);
             }
         } else {
@@ -6745,7 +6745,7 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_tensor *
                 for (int i3 = 0; i3 < src2->ne[3]; i3++) {
                     for (int i2 = 0; i2 < src2->ne[2]; i2++) {
                         const int idx = i3*src2->ne[2] + i2;
-                        ggml_vk_buffer_read(ctx, buffer_gpu, offset + idx * src2->nb[2], ((char *)src2_clone->data + idx * src2_clone->nb[2]), src2->ne[1] * src2->nb[1]);
+                        ggml_vk_buffer_read(buffer_gpu, offset + idx * src2->nb[2], ((char *)src2_clone->data + idx * src2_clone->nb[2]), src2->ne[1] * src2->nb[1]);
                     }
                 }
 
@@ -6758,7 +6758,7 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_tensor *
                 if (offset + src2_size >= buffer_gpu->size) {
                     src2_size = buffer_gpu->size - offset;
                 }
-                ggml_vk_buffer_read(ctx, buffer_gpu, offset, src2_clone->data, src2_size);
+                ggml_vk_buffer_read(buffer_gpu, offset, src2_clone->data, src2_size);
                 memcpy(src2_clone->nb, src2->nb, sizeof(size_t) * GGML_MAX_DIMS);
             }
         } else {
@@ -6922,7 +6922,7 @@ static void ggml_vk_check_results_1(ggml_backend_vk_context * ctx, ggml_tensor *
             tensor_size = buffer_gpu->size - (extra->offset + tensor->view_offs);
         }
 
-        ggml_vk_buffer_read(ctx, buffer_gpu, extra->offset + tensor->view_offs, tensor_data, tensor_size);
+        ggml_vk_buffer_read(buffer_gpu, extra->offset + tensor->view_offs, tensor_data, tensor_size);
     }
 
     float first_error_result = -1.0f;
diff --git a/ggml/src/vulkan-shaders/vulkan-shaders-gen.cpp b/ggml/src/vulkan-shaders/vulkan-shaders-gen.cpp
index fa231c0ec1688..3038d647f10f3 100644
--- a/ggml/src/vulkan-shaders/vulkan-shaders-gen.cpp
+++ b/ggml/src/vulkan-shaders/vulkan-shaders-gen.cpp
@@ -270,10 +270,10 @@ void matmul_shaders(std::vector>& tasks, bool fp16, bool matmu
         std::string data_a_key = "DATA_A_" + to_uppercase(tname);
         std::string load_vec_a = (tname == "f32" || tname == "f16") ? load_vec : "2";
         tasks.push_back(std::async(std::launch::async, [=] {
-            string_to_spv(shader_name + "_" + tname + "_f32", "mul_mm.comp", merge_maps(base_dict, {{data_a_key, "1"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}}), fp16);
+            string_to_spv(shader_name + "_" + tname + "_f32", "mul_mm.comp", merge_maps(base_dict, {{data_a_key, "1"}, {"LOAD_VEC_A", load_vec_a}, {"B_TYPE", "float"}, {"D_TYPE", "float"}}), fp16);
         }));
         tasks.push_back(std::async(std::launch::async, [=] {
-            string_to_spv(shader_name + "_" + tname + "_f32_aligned", "mul_mm.comp", merge_maps(base_dict, {{data_a_key, "2"}, {"LOAD_VEC_A", load_vec_a}, {"LOAD_VEC_B", load_vec}, {"B_TYPE", aligned_b_type_f32}, {"D_TYPE", "float"}}), fp16);
+            string_to_spv(shader_name + "_" + tname + "_f32_aligned", "mul_mm.comp", merge_maps(base_dict, {{data_a_key, "1"}, {"LOAD_VEC_A", load_vec_a}, {"LOAD_VEC_B", load_vec}, {"B_TYPE", aligned_b_type_f32}, {"D_TYPE", "float"}}), fp16);
         }));
     }
 }

From 3dfda05956befb350745c5c2f7134d06adfe8724 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Mon, 15 Jul 2024 14:10:39 +0300
Subject: [PATCH 184/326] llama : de-duplicate deepseek2 norm

---
 src/llama.cpp | 15 +++++----------
 1 file changed, 5 insertions(+), 10 deletions(-)

diff --git a/src/llama.cpp b/src/llama.cpp
index 400a4232beeb0..ddf0262d443b0 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -12873,12 +12873,12 @@ struct llm_build_context {
             struct ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpSA);
             cb(ffn_inp, "ffn_inp", il);
 
-            if ((uint32_t) il < hparams.n_layer_dense_lead) {
-                cur = llm_build_norm(ctx0, ffn_inp, hparams,
-                        model.layers[il].ffn_norm, NULL,
-                        LLM_NORM_RMS, cb, il);
-                cb(cur, "ffn_norm", il);
+            cur = llm_build_norm(ctx0, ffn_inp, hparams,
+                    model.layers[il].ffn_norm, NULL,
+                    LLM_NORM_RMS, cb, il);
+            cb(cur, "ffn_norm", il);
 
+            if ((uint32_t) il < hparams.n_layer_dense_lead) {
                 cur = llm_build_ffn(ctx0, cur,
                         model.layers[il].ffn_up,   NULL, NULL,
                         model.layers[il].ffn_gate, NULL, NULL,
@@ -12888,11 +12888,6 @@ struct llm_build_context {
                 cb(cur, "ffn_out", il);
             } else {
                 // MoE branch
-                cur = llm_build_norm(ctx0, ffn_inp, hparams,
-                        model.layers[il].ffn_norm, NULL,
-                        LLM_NORM_RMS, cb, il);
-                cb(cur, "ffn_norm", il);
-
                 ggml_tensor * moe_out =
                         llm_build_moe_ffn(ctx0, cur,
                             model.layers[il].ffn_gate_inp,

From 16bdfa42acb09175e88cf97e9d9e4e48f616d120 Mon Sep 17 00:00:00 2001
From: "Meng, Hengyu" 
Date: Mon, 15 Jul 2024 19:32:15 +0800
Subject: [PATCH 185/326] [SYCL] add concat through dim 1/2 (#8483)

* add concat through dim 1/2
---
 ggml/src/ggml-sycl.cpp         |  67 +----------
 ggml/src/ggml-sycl/backend.hpp |   1 +
 ggml/src/ggml-sycl/concat.cpp  | 195 +++++++++++++++++++++++++++++++++
 ggml/src/ggml-sycl/concat.hpp  |  21 ++++
 4 files changed, 218 insertions(+), 66 deletions(-)
 create mode 100644 ggml/src/ggml-sycl/concat.cpp
 create mode 100644 ggml/src/ggml-sycl/concat.hpp

diff --git a/ggml/src/ggml-sycl.cpp b/ggml/src/ggml-sycl.cpp
index 5a890237f2453..36518ff93b034 100644
--- a/ggml/src/ggml-sycl.cpp
+++ b/ggml/src/ggml-sycl.cpp
@@ -291,29 +291,6 @@ static void sqr_f32(const float * x, float * dst, const int k,
     dst[i] = x[i] * x[i];
 }
 
-static void concat_f32(const float  *x,const float  *y, float *dst, const int ne0, const int ne02,
-                       const sycl::nd_item<3> &item_ct1) {
-    int nidx = item_ct1.get_local_id(2) +
-               item_ct1.get_group(2) * item_ct1.get_local_range(2);
-    if (nidx >= ne0) {
-        return;
-    }
-    // operation
-    int offset_dst = nidx + item_ct1.get_group(1) * ne0 +
-                     item_ct1.get_group(0) * ne0 * item_ct1.get_group_range(1);
-    if (item_ct1.get_group(0) < ne02) { // src0
-        int offset_src =
-            nidx + item_ct1.get_group(1) * ne0 +
-            item_ct1.get_group(0) * ne0 * item_ct1.get_group_range(1);
-            dst[offset_dst] = x[offset_src];
-    } else {
-        int offset_src =
-            nidx + item_ct1.get_group(1) * ne0 +
-            (item_ct1.get_group(0) - ne02) * ne0 * item_ct1.get_group_range(1);
-            dst[offset_dst] = y[offset_src];
-    }
-}
-
 static void upscale_f32(const float  *x, float *dst, const int nb00, const int nb01,
                         const int nb02, const int nb03, const int ne10, const int ne11,
                         const int ne12, const int ne13, const float sf0, const float sf1,
@@ -1347,20 +1324,6 @@ static void sqr_f32_sycl(const float *x, float *dst, const int k,
         });
 }
 
-static void concat_f32_sycl(const float *x, const float *y, float *dst,
-                            const int ne0, int ne1, int ne2, int ne02,
-                            queue_ptr stream) {
-    int num_blocks = (ne0 + SYCL_CONCAT_BLOCK_SIZE - 1) / SYCL_CONCAT_BLOCK_SIZE;
-    sycl::range<3> gridDim(ne2, ne1, num_blocks);
-    stream->parallel_for(
-        sycl::nd_range<3>(gridDim *
-                              sycl::range<3>(1, 1, SYCL_CONCAT_BLOCK_SIZE),
-                          sycl::range<3>(1, 1, SYCL_CONCAT_BLOCK_SIZE)),
-        [=](sycl::nd_item<3> item_ct1) {
-            concat_f32(x, y, dst, ne0, ne02, item_ct1);
-        });
-}
-
 static void upscale_f32_sycl(const float *x, float *dst, const int nb00, const int nb01,
                              const int nb02, const int nb03, const int ne10, const int ne11,
                              const int ne12, const int ne13, const float sf0, const float sf1,
@@ -2429,28 +2392,6 @@ inline void ggml_sycl_op_sqr(ggml_backend_sycl_context & ctx, const ggml_tensor
     (void) src1_dd;
 }
 
-inline void ggml_sycl_op_concat(ggml_backend_sycl_context & ctx, const ggml_tensor *src0,
-                                const ggml_tensor *src1, ggml_tensor *dst,
-                                const float *src0_dd, const float *src1_dd,
-                                float *dst_dd,
-                                const queue_ptr &main_stream) {
-#pragma message("TODO: generalize concat kernel for dim != 2")
-#pragma message("      https://github.com/ggerganov/llama.cpp/pull/7563")
-    int dim = dst->op_params[0];
-    GGML_ASSERT(dim == 2);
-
-    GGML_ASSERT(src0->type == GGML_TYPE_F32);
-    GGML_ASSERT(src1->type == GGML_TYPE_F32);
-    GGML_ASSERT(dst->type == GGML_TYPE_F32);
-
-    for (int i3 = 0; i3 < dst->ne[3]; i3++) {
-        concat_f32_sycl(src0_dd + i3 * (src0->nb[3] / 4), src1_dd + i3 * (src1->nb[3] / 4), dst_dd + i3 * (dst->nb[3] / 4), dst->ne[0], dst->ne[1], dst->ne[2], src0->ne[2], main_stream);
-    }
-
-    (void) src1;
-    (void) dst;
-}
-
 inline void ggml_sycl_op_upscale(ggml_backend_sycl_context & ctx, const ggml_tensor *src0,
                                  const ggml_tensor *src1, ggml_tensor *dst,
                                  const float *src0_dd, const float *src1_dd,
@@ -3359,12 +3300,6 @@ static void ggml_sycl_group_norm(ggml_backend_sycl_context & ctx, const ggml_ten
     GGML_SYCL_DEBUG("call %s done\n", __func__);
 }
 
-static void ggml_sycl_concat(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
-    GGML_SYCL_DEBUG("call %s\n", __func__);
-    ggml_sycl_op_flatten(ctx, src0, src1, dst, ggml_sycl_op_concat);
-    GGML_SYCL_DEBUG("call %s done\n", __func__);
-}
-
 static void ggml_sycl_upscale(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
     GGML_SYCL_DEBUG("call %s\n", __func__);
     ggml_sycl_op_flatten(ctx, src0, src1, dst, ggml_sycl_op_upscale);
@@ -4101,7 +4036,7 @@ bool ggml_sycl_compute_forward(ggml_backend_sycl_context & ctx, struct ggml_tens
             func = ggml_sycl_group_norm;
             break;
         case GGML_OP_CONCAT:
-            func = ggml_sycl_concat;
+            func = ggml_sycl_op_concat;
             break;
         case GGML_OP_UPSCALE:
             func = ggml_sycl_upscale;
diff --git a/ggml/src/ggml-sycl/backend.hpp b/ggml/src/ggml-sycl/backend.hpp
index 2a789edfc909d..067181de3836c 100644
--- a/ggml/src/ggml-sycl/backend.hpp
+++ b/ggml/src/ggml-sycl/backend.hpp
@@ -13,6 +13,7 @@
 #ifndef GGML_SYCL_BACKEND_HPP
 #define GGML_SYCL_BACKEND_HPP
 
+#include "concat.hpp"
 #include "common.hpp"
 #include "convert.hpp"
 #include "dequantize.hpp"
diff --git a/ggml/src/ggml-sycl/concat.cpp b/ggml/src/ggml-sycl/concat.cpp
new file mode 100644
index 0000000000000..632eedb9d42b8
--- /dev/null
+++ b/ggml/src/ggml-sycl/concat.cpp
@@ -0,0 +1,195 @@
+//
+// MIT license
+// Copyright (C) 2024 Intel Corporation
+// SPDX-License-Identifier: MIT
+//
+
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+
+#include "concat.hpp"
+#include "common.hpp"
+
+static void concat_f32_dim0(const float *x, const float *y, float *dst,
+                            const int ne0, const int ne00,
+                            const sycl::nd_item<3> &item_ct1) {
+  int nidx = item_ct1.get_local_id(2) +
+             item_ct1.get_group(2) * item_ct1.get_local_range(2);
+  if (nidx >= ne0) {
+    return;
+  }
+  // operation
+  int offset_dst = nidx + item_ct1.get_group(1) * ne0 +
+                   item_ct1.get_group(0) * ne0 * item_ct1.get_group_range(1);
+  if (nidx < ne00) { // src0
+    int offset_src = nidx + item_ct1.get_group(1) * ne00 +
+                     item_ct1.get_group(0) * ne00 * item_ct1.get_group_range(1);
+    dst[offset_dst] = x[offset_src];
+  } else {
+    int offset_src =
+        nidx - ne00 + item_ct1.get_group(1) * (ne0 - ne00) +
+        item_ct1.get_group(0) * (ne0 - ne00) * item_ct1.get_group_range(1);
+    dst[offset_dst] = y[offset_src];
+  }
+}
+
+static void concat_f32_dim1(const float *x, const float *y, float *dst,
+                            const int ne0, const int ne01,
+                            const sycl::nd_item<3> &item_ct1) {
+  int nidx = item_ct1.get_local_id(2) +
+             item_ct1.get_group(2) * item_ct1.get_local_range(2);
+  if (nidx >= ne0) {
+    return;
+  }
+  // operation
+  int offset_dst = nidx + item_ct1.get_group(1) * ne0 +
+                   item_ct1.get_group(0) * ne0 * item_ct1.get_group_range(1);
+  if (item_ct1.get_group(1) < ne01) { // src0
+    int offset_src =
+        nidx + item_ct1.get_group(1) * ne0 + item_ct1.get_group(0) * ne0 * ne01;
+    dst[offset_dst] = x[offset_src];
+  } else {
+    int offset_src =
+        nidx + (item_ct1.get_group(1) - ne01) * ne0 +
+        item_ct1.get_group(0) * ne0 * (item_ct1.get_group_range(1) - ne01);
+    dst[offset_dst] = y[offset_src];
+  }
+}
+
+static void concat_f32_dim2(const float *x, const float *y, float *dst,
+                            const int ne0, const int ne02,
+                            const sycl::nd_item<3> &item_ct1) {
+  int nidx = item_ct1.get_local_id(2) +
+             item_ct1.get_group(2) * item_ct1.get_local_range(2);
+  if (nidx >= ne0) {
+    return;
+  }
+  // operation
+  int offset_dst = nidx + item_ct1.get_group(1) * ne0 +
+                   item_ct1.get_group(0) * ne0 * item_ct1.get_group_range(1);
+  if (item_ct1.get_group(0) < ne02) { // src0
+    int offset_src = nidx + item_ct1.get_group(1) * ne0 +
+                     item_ct1.get_group(0) * ne0 * item_ct1.get_group_range(1);
+    dst[offset_dst] = x[offset_src];
+  } else {
+    int offset_src =
+        nidx + item_ct1.get_group(1) * ne0 +
+        (item_ct1.get_group(0) - ne02) * ne0 * item_ct1.get_group_range(1);
+    dst[offset_dst] = y[offset_src];
+  }
+}
+
+static void concat_f32_sycl(const float *x, const float *y, float *dst,
+                            int ne00, int ne01, int ne02, int ne0, int ne1,
+                            int ne2, int dim, queue_ptr stream) {
+  int num_blocks = (ne0 + SYCL_CONCAT_BLOCK_SIZE - 1) / SYCL_CONCAT_BLOCK_SIZE;
+  sycl::range<3> gridDim(ne2, ne1, num_blocks);
+  switch (dim) {
+  case 0:
+    stream->parallel_for(
+        sycl::nd_range<3>(gridDim *
+                              sycl::range<3>(1, 1, SYCL_CONCAT_BLOCK_SIZE),
+                          sycl::range<3>(1, 1, SYCL_CONCAT_BLOCK_SIZE)),
+        [=](sycl::nd_item<3> item_ct1) {
+          concat_f32_dim0(x, y, dst, ne0, ne00, item_ct1);
+        });
+    break;
+  case 1:
+    stream->parallel_for(
+        sycl::nd_range<3>(gridDim *
+                              sycl::range<3>(1, 1, SYCL_CONCAT_BLOCK_SIZE),
+                          sycl::range<3>(1, 1, SYCL_CONCAT_BLOCK_SIZE)),
+        [=](sycl::nd_item<3> item_ct1) {
+          concat_f32_dim1(x, y, dst, ne0, ne01, item_ct1);
+        });
+    break;
+  default:
+    stream->parallel_for(
+        sycl::nd_range<3>(gridDim *
+                              sycl::range<3>(1, 1, SYCL_CONCAT_BLOCK_SIZE),
+                          sycl::range<3>(1, 1, SYCL_CONCAT_BLOCK_SIZE)),
+        [=](sycl::nd_item<3> item_ct1) {
+          concat_f32_dim2(x, y, dst, ne0, ne02, item_ct1);
+        });
+    break;
+  }
+}
+
+// non-contiguous kernel (slow)
+static void concat_f32_sycl_non_cont(
+    queue_ptr stream, const char *src0, const char *src1, char *dst,
+    int64_t ne00, int64_t ne01, int64_t ne02, int64_t ne03, uint64_t nb00,
+    uint64_t nb01, uint64_t nb02, uint64_t nb03, int64_t /*ne10*/,
+    int64_t /*ne11*/, int64_t /*ne12*/, int64_t /*ne13*/, uint64_t nb10,
+    uint64_t nb11, uint64_t nb12, uint64_t nb13, int64_t ne0, int64_t ne1,
+    int64_t ne2, int64_t ne3, uint64_t nb0, uint64_t nb1, uint64_t nb2,
+    uint64_t nb3, int32_t dim) {
+  sycl::range<3> gridDim(ne3, ne2, ne1);
+  stream->parallel_for(
+      sycl::nd_range<3>(gridDim, sycl::range<3>(1, 1, 1)),
+      [=](sycl::nd_item<3> item_ct1) {
+        int64_t i3 = item_ct1.get_group(0);
+        int64_t i2 = item_ct1.get_group(1);
+        int64_t i1 = item_ct1.get_group(2);
+
+        int64_t o[4] = {0, 0, 0, 0};
+        o[dim] = dim == 0 ? ne00 : (dim == 1 ? ne01 : (dim == 2 ? ne02 : ne03));
+
+        const float *x;
+
+        for (int i0 = item_ct1.get_local_id(2); i0 < ne0;
+             i0 += item_ct1.get_local_range(2)) {
+          if (i0 < ne00 && i1 < ne01 && i2 < ne02 && i3 < ne03) {
+            x = (const float *)(src0 + (i3)*nb03 + (i2)*nb02 + (i1)*nb01 +
+                                (i0)*nb00);
+          } else {
+            x = (const float *)(src1 + (i3 - o[3]) * nb13 + (i2 - o[2]) * nb12 +
+                                (i1 - o[1]) * nb11 + (i0 - o[0]) * nb10);
+          }
+
+          float *y = (float *)(dst + i3 * nb3 + i2 * nb2 + i1 * nb1 + i0 * nb0);
+
+          *y = *x;
+        }
+      });
+}
+
+void ggml_sycl_op_concat(ggml_backend_sycl_context & ctx, const ggml_tensor *src0,
+                                const ggml_tensor *src1, ggml_tensor *dst) {
+  queue_ptr stream = ctx.stream();
+
+  const int32_t dim = ((int32_t *)dst->op_params)[0];
+
+  if (ggml_is_contiguous(src0) && ggml_is_contiguous(src1)) {
+    const float *src0_d = (const float *)src0->data;
+    const float *src1_d = (const float *)src1->data;
+
+    float *dst_d = (float *)dst->data;
+
+    if (dim != 3) {
+      for (int i3 = 0; i3 < dst->ne[3]; i3++) {
+        concat_f32_sycl(
+            src0_d + i3 * (src0->nb[3] / 4), src1_d + i3 * (src1->nb[3] / 4),
+            dst_d + i3 * (dst->nb[3] / 4), src0->ne[0], src0->ne[1],
+            src0->ne[2], dst->ne[0], dst->ne[1], dst->ne[2], dim, stream);
+      }
+    } else {
+      const size_t size0 = ggml_nbytes(src0);
+      const size_t size1 = ggml_nbytes(src1);
+
+      SYCL_CHECK(CHECK_TRY_ERROR(stream->memcpy(dst_d, src0_d, size0).wait()));
+      SYCL_CHECK(CHECK_TRY_ERROR(
+          stream->memcpy(dst_d + size0 / 4, src1_d, size1).wait()));
+    }
+  } else
+    concat_f32_sycl_non_cont(
+        stream, (const char *)src0->data, (const char *)src1->data,
+        (char *)dst->data, src0->ne[0], src0->ne[1], src0->ne[2], src0->ne[3],
+        src0->nb[0], src0->nb[1], src0->nb[2], src0->nb[3], src1->ne[0],
+        src1->ne[1], src1->ne[2], src1->ne[3], src1->nb[0], src1->nb[1],
+        src1->nb[2], src1->nb[3], dst->ne[0], dst->ne[1], dst->ne[2],
+        dst->ne[3], dst->nb[0], dst->nb[1], dst->nb[2], dst->nb[3], dim);
+}
diff --git a/ggml/src/ggml-sycl/concat.hpp b/ggml/src/ggml-sycl/concat.hpp
new file mode 100644
index 0000000000000..5a04feaab6b0a
--- /dev/null
+++ b/ggml/src/ggml-sycl/concat.hpp
@@ -0,0 +1,21 @@
+//
+// MIT license
+// Copyright (C) 2024 Intel Corporation
+// SPDX-License-Identifier: MIT
+//
+
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+
+#ifndef GGML_SYCL_CONCAT_HPP
+#define GGML_SYCL_CONCAT_HPP
+
+#include "common.hpp"
+
+void ggml_sycl_op_concat(ggml_backend_sycl_context & ctx, const ggml_tensor *src0,
+                                const ggml_tensor *src1, ggml_tensor *dst);
+
+#endif // GGML_SYCL_CONCAT_HPP

From fc690b018e459012cd82c37f1343e9bb658987d1 Mon Sep 17 00:00:00 2001
From: NikolaiLyssogor <59844691+NikolaiLyssogor@users.noreply.github.com>
Date: Mon, 15 Jul 2024 04:46:39 -0700
Subject: [PATCH 186/326] docs: fix links in development docs [no ci] (#8481)

Fixes a few links to within the repo that were broken in the reorganization of the
documentation in #8325.
---
 docs/development/HOWTO-add-model.md              | 16 ++++++++--------
 .../token_generation_performance_tips.md         |  2 +-
 2 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/docs/development/HOWTO-add-model.md b/docs/development/HOWTO-add-model.md
index 2712b66c17533..04c5ccbbe60c3 100644
--- a/docs/development/HOWTO-add-model.md
+++ b/docs/development/HOWTO-add-model.md
@@ -9,15 +9,15 @@ Adding a model requires few steps:
 After following these steps, you can open PR.
 
 Also, it is important to check that the examples and main ggml backends (CUDA, METAL, CPU) are working with the new architecture, especially:
-- [main](../examples/main)
-- [imatrix](../examples/imatrix)
-- [quantize](../examples/quantize)
-- [server](../examples/server)
+- [main](/examples/main/)
+- [imatrix](/examples/imatrix/)
+- [quantize](/examples/quantize/)
+- [server](/examples/server/)
 
 ### 1. Convert the model to GGUF
 
 This step is done in python with a `convert` script using the [gguf](https://pypi.org/project/gguf/) library.
-Depending on the model architecture, you can use either [convert_hf_to_gguf.py](../convert_hf_to_gguf.py) or [examples/convert_legacy_llama.py](../examples/convert_legacy_llama.py) (for `llama/llama2` models in `.pth` format).
+Depending on the model architecture, you can use either [convert_hf_to_gguf.py](/convert_hf_to_gguf.py) or [examples/convert_legacy_llama.py](/examples/convert_legacy_llama.py) (for `llama/llama2` models in `.pth` format).
 
 The convert script reads the model configuration, tokenizer, tensor names+data and converts them to GGUF metadata and tensors.
 
@@ -31,7 +31,7 @@ class MyModel(Model):
     model_arch = gguf.MODEL_ARCH.GROK
 ```
 
-2. Define the layout of the GGUF tensors in [constants.py](../gguf-py/gguf/constants.py)
+2. Define the layout of the GGUF tensors in [constants.py](/gguf-py/gguf/constants.py)
 
 Add an enum entry in `MODEL_ARCH`, the model human friendly name in `MODEL_ARCH_NAMES` and the GGUF tensor names in `MODEL_TENSORS`.
 
@@ -54,7 +54,7 @@ Example for `falcon` model:
 
 As a general rule, before adding a new tensor name to GGUF, be sure the equivalent naming does not already exist.
 
-Once you have found the GGUF tensor name equivalent, add it to the [tensor_mapping.py](../gguf-py/gguf/tensor_mapping.py) file.
+Once you have found the GGUF tensor name equivalent, add it to the [tensor_mapping.py](/gguf-py/gguf/tensor_mapping.py) file.
 
 If the tensor name is part of a repetitive layer/block, the key word `bid` substitutes it.
 
@@ -100,7 +100,7 @@ Have a look at existing implementation like `build_llama`, `build_dbrx` or `buil
 
 When implementing a new graph, please note that the underlying `ggml` backends might not support them all, support for missing backend operations can be added in another PR.
 
-Note: to debug the inference graph: you can use [llama-eval-callback](../examples/eval-callback).
+Note: to debug the inference graph: you can use [llama-eval-callback](/examples/eval-callback/).
 
 ## GGUF specification
 
diff --git a/docs/development/token_generation_performance_tips.md b/docs/development/token_generation_performance_tips.md
index c0840cad57fb3..41b7232c976b3 100644
--- a/docs/development/token_generation_performance_tips.md
+++ b/docs/development/token_generation_performance_tips.md
@@ -1,7 +1,7 @@
 # Token generation performance troubleshooting
 
 ## Verifying that the model is running on the GPU with CUDA
-Make sure you compiled llama with the correct env variables according to [this guide](../README.md#CUDA), so that llama accepts the `-ngl N` (or `--n-gpu-layers N`) flag. When running llama, you may configure `N` to be very large, and llama will offload the maximum possible number of layers to the GPU, even if it's less than the number you configured. For example:
+Make sure you compiled llama with the correct env variables according to [this guide](/docs/build.md#cuda), so that llama accepts the `-ngl N` (or `--n-gpu-layers N`) flag. When running llama, you may configure `N` to be very large, and llama will offload the maximum possible number of layers to the GPU, even if it's less than the number you configured. For example:
 ```shell
 ./llama-cli -m "path/to/model.gguf" -ngl 200000 -p "Please sir, may I have some "
 ```

From 9104bc20edf47f74dc49379b7d61d0c6e85a4882 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Mon, 15 Jul 2024 14:54:58 +0300
Subject: [PATCH 187/326] common : add --no-cont-batching arg (#6358)

---
 common/common.cpp | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/common/common.cpp b/common/common.cpp
index 1e5fc30dd458a..9035c359267a7 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -797,6 +797,10 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
         params.cont_batching = true;
         return true;
     }
+    if (arg == "-nocb" || arg == "--no-cont-batching") {
+        params.cont_batching = false;
+        return true;
+    }
     if (arg == "-fa" || arg == "--flash-attn") {
         params.flash_attn = true;
         return true;
@@ -1538,6 +1542,7 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
     options.push_back({ "*",           "-np,   --parallel N",           "number of parallel sequences to decode (default: %d)", params.n_parallel });
     options.push_back({ "*",           "-ns,   --sequences N",          "number of sequences to decode (default: %d)", params.n_sequences });
     options.push_back({ "*",           "-cb,   --cont-batching",        "enable continuous batching (a.k.a dynamic batching) (default: %s)", params.cont_batching ? "enabled" : "disabled" });
+    options.push_back({ "*",           "-nocb, --no-cont-batching",     "disable continuous batching" });
 
     options.push_back({ "multi-modality" });
     options.push_back({ "*",           "       --mmproj FILE",          "path to a multimodal projector file for LLaVA. see examples/llava/README.md" });

From f17f39ff9cb71fa7b0eda0c649bb0ce9b2d8a6b8 Mon Sep 17 00:00:00 2001
From: M-A 
Date: Mon, 15 Jul 2024 08:04:56 -0400
Subject: [PATCH 188/326] server: update README.md with llama-server --help
 output [no ci] (#8472)

The README.md had a stale information. In particular, the --ctx-size
"defaults to 512" confused me and I had to check the code to confirm
this was false. This the server is evolving rapidly, it's probably
better to keep the source of truth at a single place (in the source) and
generate the README.md based on that.

Did:

    make llama-server
    ./llama-server --help > t.txt
    vimdiff t.txt examples/server/README.md

I copied the content inside a backquote block. I would have preferred
proper text but it would require a fair amount of surgery to make the
current output compatible with markdown. A follow up could be to
automate this process with a script.

No functional change.
---
 examples/server/README.md | 338 +++++++++++++++++++++++++++++++-------
 1 file changed, 275 insertions(+), 63 deletions(-)

diff --git a/examples/server/README.md b/examples/server/README.md
index cb45ee06dd0a0..d7487ec1b5b7e 100644
--- a/examples/server/README.md
+++ b/examples/server/README.md
@@ -15,69 +15,281 @@ Set of LLM REST APIs and a simple web front end to interact with llama.cpp.
 
 The project is under active development, and we are [looking for feedback and contributors](https://github.com/ggerganov/llama.cpp/issues/4216).
 
-**Command line options:**
-
-- `-v`, `--verbose`: Enable verbose server output. When using the `/completion` endpoint, this includes the tokenized prompt, the full request and the full response.
-- `-t N`, `--threads N`: Set the number of threads to use by CPU layers during generation. Not used by model layers that are offloaded to GPU. This option has no effect when using the maximum number of GPU layers. Default: `std::thread::hardware_concurrency()` (number of CPU cores).
-- `-tb N, --threads-batch N`: Set the number of threads to use by CPU layers during batch and prompt processing (>= 32 tokens). This option has no effect if a GPU is available. Default: `--threads`.
-- `--threads-http N`: Number of threads in the http server pool to process requests. Default: `max(std::thread::hardware_concurrency() - 1, --parallel N + 2)`
-- `-m FNAME`, `--model FNAME`: Specify the path to the LLaMA model file (e.g., `models/7B/ggml-model.gguf`).
-- `-mu MODEL_URL --model-url MODEL_URL`: Specify a remote http url to download the file. Default: unused
-- `-hfr REPO, --hf-repo REPO`: Hugging Face model repository. Default: unused
-- `-hff FILE, --hf-file FILE`: Hugging Face model file. Default: unused
-- `-a ALIAS`, `--alias ALIAS`: Set an alias for the model. The alias will be returned in API responses.
-- `-c N`, `--ctx-size N`: Set the size of the prompt context. The default is `512`, but LLaMA models were built with a context of `2048`, which will provide better results for longer input/inference. The size may differ in other models, for example, baichuan models were build with a context of `4096`.
-- `-ngl N`, `--n-gpu-layers N`: When compiled with GPU support, this option allows offloading some layers to the GPU for computation. Generally results in increased performance.
-- `-mg i, --main-gpu i`: When using multiple GPUs, this option controls which GPU is used for small tensors for which the overhead of splitting the computation across all GPUs is not worthwhile. The GPU in question will use slightly more VRAM to store a scratch buffer for temporary results. By default, GPU `0` is used.
-- `-ts SPLIT, --tensor-split SPLIT`: When using multiple GPUs, this option controls how large tensors should be split across all GPUs. `SPLIT` is a comma-separated list of non-negative values that assigns the proportion of data that each GPU should get in order. For example, "3,2" will assign 60% of the data to GPU 0 and 40% to GPU 1. By default, the data is split in proportion to VRAM, but this may not be optimal for performance.
-- `-b N`, `--batch-size N`: Set the batch size for prompt processing. Default: `2048`
-- `-ub N`, `--ubatch-size N`: Physical maximum batch size. Default: `512`
-- `--mlock`: Lock the model in memory, preventing it from being swapped out when memory-mapped.
-- `--no-mmap`: Do not memory-map the model. By default, models are mapped into memory, which allows the system to load only the necessary parts of the model as needed.
-- `--numa STRATEGY`: Attempt one of the below optimization strategies that may help on some NUMA systems
-- `--numa distribute`: Spread execution evenly over all nodes
-- `--numa isolate`: Only spawn threads on CPUs on the node that execution started on
-- `--numa numactl`: Use the CPU map provided by numactl. If run without this previously, it is recommended to drop the system page cache before using this. See https://github.com/ggerganov/llama.cpp/issues/1437
-- `--numa`: Attempt optimizations that may help on some NUMA systems.
-- `--lora FNAME`: Apply a LoRA (Low-Rank Adaptation) adapter to the model (implies --no-mmap). This allows you to adapt the pretrained model to specific tasks or domains.
-- `--lora-base FNAME`: Optional model to use as a base for the layers modified by the LoRA adapter. This flag is used in conjunction with the `--lora` flag, and specifies the base model for the adaptation.
-- `-to N`, `--timeout N`: Server read/write timeout in seconds. Default `600`
-- `--host`: Set the hostname or ip address to listen. Default `127.0.0.1`
-- `--port`: Set the port to listen. Default: `8080`
-- `--path`: Path from which to serve static files. Default: disabled
-- `--api-key`: Set an api key for request authorization. By default, the server responds to every request. With an api key set, the requests must have the Authorization header set with the api key as Bearer token. May be used multiple times to enable multiple valid keys.
-- `--api-key-file`: Path to file containing api keys delimited by new lines. If set, requests must include one of the keys for access. May be used in conjunction with `--api-key`s.
-- `--embeddings`: Enable embedding vector output and the OAI compatible endpoint /v1/embeddings. Physical batch size (`--ubatch-size`) must be carefully defined. Default: disabled
-- `-np N`, `--parallel N`: Set the number of slots for process requests. Default: `1`. Values > 1 will allow for higher throughput with multiple parallel requests but the results will **not** be deterministic due to differences in rounding error.
-- `-cb`, `--cont-batching`: Enable continuous batching (a.k.a dynamic batching).  Default: disabled
-- `-spf FNAME`, `--system-prompt-file FNAME` Set a file to load a system prompt (initial prompt of all slots). This is useful for chat applications. [See more](#change-system-prompt-on-runtime)
-- `--mmproj MMPROJ_FILE`: Path to a multimodal projector file for LLaVA.
-- `--grp-attn-n`: Set the group attention factor to extend context size through self-extend. Used together with group attention width `--grp-attn-w`. Default: `1`, which is disabled.
-- `--grp-attn-w`: Set the group attention width to extend context size through self-extend.  Used together with group attention factor `--grp-attn-n`. Default: `512`
-- `-n N, --n-predict N`: Set the maximum tokens to predict. Default: `-1`
-- `--slots-endpoint-disable`: To disable slots state monitoring endpoint. Slots state may contain user data, prompts included.
-- `--metrics`: enable prometheus `/metrics` compatible endpoint. Default: disabled
-- `--slot-save-path PATH`: Specifies the path where the state of slots (the prompt cache) can be stored. If not provided, the slot management endpoints will be disabled.
-- `--chat-template JINJA_TEMPLATE`: Set custom jinja chat template. This parameter accepts a string, not a file name.  Default: template taken from model's metadata. We only support [some pre-defined templates](https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template)
-- `--log-disable`: Output logs to stdout only, not to `llama.log`. Default: enabled
-- `--log-format FORMAT`: Define the log output to FORMAT: json or text Default: `json`
-- `--rope-scaling` : RoPE scaling method. Defaults to linear unless otherwise specified by the model. Options are `none`, `linear`, `yarn`
-- `--rope-freq-base N` : RoPE frequency base (default: loaded from model)
-- `--rope-freq-scale N`: RoPE frequency scaling factor, expands context by a factor of 1/N (e.g. 0.25)
-- `--yarn-ext-factor N` : YaRN: extrapolation mix factor (Default: 1.0, 0.0 = full interpolation)
-- `--yarn-attn-factor N` : YaRN: scale sqrt(t) or attention magnitude (default: 1.0)
-- `--yarn-beta-slow N`: YaRN: High correction dim or alpha (default: 1.0)
-- `--yarn-beta-fast N`: YaRN: low correction dim or beta (default: 32.0)
-- `--pooling` : Pooling type for embeddings, use model default if unspecified. Options are `none`, `mean`, `cls`
-- `-dt N`, `--defrag-thold N`: KV cache defragmentation threshold (default: -1.0, < 0 = disabled)
-- `-fa`, `--flash-attn` : enable flash attention (default: disabled).
-- `-ctk TYPE`, `--cache-type-k TYPE` : KV cache data type for K (default: `f16`, options `f32`, `f16`, `q8_0`, `q4_0`, `q4_1`, `iq4_nl`, `q5_0`, or `q5_1`)
-- `-ctv TYPE`, `--cache-type-v TYPE` : KV cache type for V (default `f16`, see `-ctk` for options)
-- `--spm-infill` : Use Suffix/Prefix/Middle pattern for infill (instead of Prefix/Suffix/Middle) as some models prefer this.
-
-**If compiled with `LLAMA_SERVER_SSL=ON`**
-- `--ssl-key-file FNAME`: path to file a PEM-encoded SSL private key
-- `--ssl-cert-file FNAME`: path to file a PEM-encoded SSL certificate
+## Usage
+
+```
+usage: ./llama-server [options]
+
+general:
+
+  -h,    --help, --usage          print usage and exit
+         --version                show version and build info
+  -v,    --verbose                print verbose information
+         --verbosity N            set specific verbosity level (default: 0)
+         --verbose-prompt         print a verbose prompt before generation (default: false)
+         --no-display-prompt      don't print prompt at generation (default: false)
+  -co,   --color                  colorise output to distinguish prompt and user input from generations (default: false)
+  -s,    --seed SEED              RNG seed (default: -1, use random seed for < 0)
+  -t,    --threads N              number of threads to use during generation (default: 8)
+  -tb,   --threads-batch N        number of threads to use during batch and prompt processing (default: same as --threads)
+  -td,   --threads-draft N        number of threads to use during generation (default: same as --threads)
+  -tbd,  --threads-batch-draft N  number of threads to use during batch and prompt processing (default: same as --threads-draft)
+         --draft N                number of tokens to draft for speculative decoding (default: 5)
+  -ps,   --p-split N              speculative decoding split probability (default: 0.1)
+  -lcs,  --lookup-cache-static FNAME
+                                  path to static lookup cache to use for lookup decoding (not updated by generation)
+  -lcd,  --lookup-cache-dynamic FNAME
+                                  path to dynamic lookup cache to use for lookup decoding (updated by generation)
+  -c,    --ctx-size N             size of the prompt context (default: 0, 0 = loaded from model)
+  -n,    --predict N              number of tokens to predict (default: -1, -1 = infinity, -2 = until context filled)
+  -b,    --batch-size N           logical maximum batch size (default: 2048)
+  -ub,   --ubatch-size N          physical maximum batch size (default: 512)
+         --keep N                 number of tokens to keep from the initial prompt (default: 0, -1 = all)
+         --chunks N               max number of chunks to process (default: -1, -1 = all)
+  -fa,   --flash-attn             enable Flash Attention (default: disabled)
+  -p,    --prompt PROMPT          prompt to start generation with
+                                  in conversation mode, this will be used as system prompt
+                                  (default: '')
+  -f,    --file FNAME             a file containing the prompt (default: none)
+         --in-file FNAME          an input file (repeat to specify multiple files)
+  -bf,   --binary-file FNAME      binary file containing the prompt (default: none)
+  -e,    --escape                 process escapes sequences (\n, \r, \t, \', \", \\) (default: true)
+         --no-escape              do not process escape sequences
+  -ptc,  --print-token-count N    print token count every N tokens (default: -1)
+         --prompt-cache FNAME     file to cache prompt state for faster startup (default: none)
+         --prompt-cache-all       if specified, saves user input and generations to cache as well
+                                  not supported with --interactive or other interactive options
+         --prompt-cache-ro        if specified, uses the prompt cache but does not update it
+  -r,    --reverse-prompt PROMPT  halt generation at PROMPT, return control in interactive mode
+                                  can be specified more than once for multiple prompts
+  -sp,   --special                special tokens output enabled (default: false)
+  -cnv,  --conversation           run in conversation mode, does not print special tokens and suffix/prefix
+                                  if suffix/prefix are not specified, default chat template will be used
+                                  (default: false)
+  -i,    --interactive            run in interactive mode (default: false)
+  -if,   --interactive-first      run in interactive mode and wait for input right away (default: false)
+  -mli,  --multiline-input        allows you to write or paste multiple lines without ending each in '\'
+         --in-prefix-bos          prefix BOS to user inputs, preceding the `--in-prefix` string
+         --in-prefix STRING       string to prefix user inputs with (default: empty)
+         --in-suffix STRING       string to suffix after user inputs with (default: empty)
+         --spm-infill             use Suffix/Prefix/Middle pattern for infill (instead of Prefix/Suffix/Middle) as some models prefer this. (default: disabled)
+
+sampling:
+
+         --samplers SAMPLERS      samplers that will be used for generation in the order, separated by ';'
+                                  (default: top_k;tfs_z;typical_p;top_p;min_p;temperature)
+         --sampling-seq SEQUENCE  simplified sequence for samplers that will be used (default: kfypmt)
+         --ignore-eos             ignore end of stream token and continue generating (implies --logit-bias EOS-inf)
+         --penalize-nl            penalize newline tokens (default: false)
+         --temp N                 temperature (default: 0.8)
+         --top-k N                top-k sampling (default: 40, 0 = disabled)
+         --top-p N                top-p sampling (default: 0.9, 1.0 = disabled)
+         --min-p N                min-p sampling (default: 0.1, 0.0 = disabled)
+         --tfs N                  tail free sampling, parameter z (default: 1.0, 1.0 = disabled)
+         --typical N              locally typical sampling, parameter p (default: 1.0, 1.0 = disabled)
+         --repeat-last-n N        last n tokens to consider for penalize (default: 64, 0 = disabled, -1 = ctx_size)
+         --repeat-penalty N       penalize repeat sequence of tokens (default: 1.0, 1.0 = disabled)
+         --presence-penalty N     repeat alpha presence penalty (default: 0.0, 0.0 = disabled)
+         --frequency-penalty N    repeat alpha frequency penalty (default: 0.0, 0.0 = disabled)
+         --dynatemp-range N       dynamic temperature range (default: 0.0, 0.0 = disabled)
+         --dynatemp-exp N         dynamic temperature exponent (default: 1.0)
+         --mirostat N             use Mirostat sampling.
+                                  Top K, Nucleus, Tail Free and Locally Typical samplers are ignored if used.
+                                  (default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)
+         --mirostat-lr N          Mirostat learning rate, parameter eta (default: 0.1)
+         --mirostat-ent N         Mirostat target entropy, parameter tau (default: 5.0)
+         -l TOKEN_ID(+/-)BIAS     modifies the likelihood of token appearing in the completion,
+                                  i.e. `--logit-bias 15043+1` to increase likelihood of token ' Hello',
+                                  or `--logit-bias 15043-1` to decrease likelihood of token ' Hello'
+         --cfg-negative-prompt PROMPT
+                                  negative prompt to use for guidance (default: '')
+         --cfg-negative-prompt-file FNAME
+                                  negative prompt file to use for guidance
+         --cfg-scale N            strength of guidance (default: 1.0, 1.0 = disable)
+         --chat-template JINJA_TEMPLATE
+                                  set custom jinja chat template (default: template taken from model's metadata)
+                                  if suffix/prefix are specified, template will be disabled
+                                  only commonly used templates are accepted:
+                                  https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template
+
+grammar:
+
+         --grammar GRAMMAR        BNF-like grammar to constrain generations (see samples in grammars/ dir) (default: '')
+         --grammar-file FNAME     file to read grammar from
+  -j,    --json-schema SCHEMA     JSON schema to constrain generations (https://json-schema.org/), e.g. `{}` for any JSON object
+                                  For schemas w/ external $refs, use --grammar + example/json_schema_to_grammar.py instead
+
+embedding:
+
+         --pooling {none,mean,cls,last}
+                                  pooling type for embeddings, use model default if unspecified
+         --attention {causal,non-causal}
+                                  attention type for embeddings, use model default if unspecified
+
+context hacking:
+
+         --rope-scaling {none,linear,yarn}
+                                  RoPE frequency scaling method, defaults to linear unless specified by the model
+         --rope-scale N           RoPE context scaling factor, expands context by a factor of N
+         --rope-freq-base N       RoPE base frequency, used by NTK-aware scaling (default: loaded from model)
+         --rope-freq-scale N      RoPE frequency scaling factor, expands context by a factor of 1/N
+         --yarn-orig-ctx N        YaRN: original context size of model (default: 0 = model training context size)
+         --yarn-ext-factor N      YaRN: extrapolation mix factor (default: -1.0, 0.0 = full interpolation)
+         --yarn-attn-factor N     YaRN: scale sqrt(t) or attention magnitude (default: 1.0)
+         --yarn-beta-slow N       YaRN: high correction dim or alpha (default: 1.0)
+         --yarn-beta-fast N       YaRN: low correction dim or beta (default: 32.0)
+  -gan,  --grp-attn-n N           group-attention factor (default: 1)
+  -gaw,  --grp-attn-w N           group-attention width (default: 512.0)
+  -dkvc, --dump-kv-cache          verbose print of the KV cache
+  -nkvo, --no-kv-offload          disable KV offload
+  -ctk,  --cache-type-k TYPE      KV cache data type for K (default: f16)
+  -ctv,  --cache-type-v TYPE      KV cache data type for V (default: f16)
+
+perplexity:
+
+         --all-logits             return logits for all tokens in the batch (default: false)
+         --hellaswag              compute HellaSwag score over random tasks from datafile supplied with -f
+         --hellaswag-tasks N      number of tasks to use when computing the HellaSwag score (default: 400)
+         --winogrande             compute Winogrande score over random tasks from datafile supplied with -f
+         --winogrande-tasks N     number of tasks to use when computing the Winogrande score (default: 0)
+         --multiple-choice        compute multiple choice score over random tasks from datafile supplied with -f
+         --multiple-choice-tasks N
+                                  number of tasks to use when computing the multiple choice score (default: 0)
+         --kl-divergence          computes KL-divergence to logits provided via --kl-divergence-base
+         --ppl-stride N           stride for perplexity calculation (default: 0)
+         --ppl-output-type {0,1}  output type for perplexity calculation (default: 0)
+
+parallel:
+
+  -dt,   --defrag-thold N         KV cache defragmentation threshold (default: -1.0, < 0 - disabled)
+  -np,   --parallel N             number of parallel sequences to decode (default: 1)
+  -ns,   --sequences N            number of sequences to decode (default: 1)
+  -cb,   --cont-batching          enable continuous batching (a.k.a dynamic batching) (default: enabled)
+
+multi-modality:
+
+         --mmproj FILE            path to a multimodal projector file for LLaVA. see examples/llava/README.md
+         --image FILE             path to an image file. use with multimodal models. Specify multiple times for batching
+
+backend:
+
+         --rpc SERVERS            comma separated list of RPC servers
+         --mlock                  force system to keep model in RAM rather than swapping or compressing
+         --no-mmap                do not memory-map model (slower load but may reduce pageouts if not using mlock)
+         --numa TYPE              attempt optimizations that help on some NUMA systems
+                                    - distribute: spread execution evenly over all nodes
+                                    - isolate: only spawn threads on CPUs on the node that execution started on
+                                    - numactl: use the CPU map provided by numactl
+                                  if run without this previously, it is recommended to drop the system page cache before using this
+                                  see https://github.com/ggerganov/llama.cpp/issues/1437
+
+model:
+
+         --check-tensors          check model tensor data for invalid values (default: false)
+         --override-kv KEY=TYPE:VALUE
+                                  advanced option to override model metadata by key. may be specified multiple times.
+                                  types: int, float, bool, str. example: --override-kv tokenizer.ggml.add_bos_token=bool:false
+         --lora FNAME             apply LoRA adapter (implies --no-mmap)
+         --lora-scaled FNAME S    apply LoRA adapter with user defined scaling S (implies --no-mmap)
+         --lora-base FNAME        optional model to use as a base for the layers modified by the LoRA adapter
+         --control-vector FNAME   add a control vector
+                                  note: this argument can be repeated to add multiple control vectors
+         --control-vector-scaled FNAME SCALE
+                                  add a control vector with user defined scaling SCALE
+                                  note: this argument can be repeated to add multiple scaled control vectors
+         --control-vector-layer-range START END
+                                  layer range to apply the control vector(s) to, start and end inclusive
+  -m,    --model FNAME            model path (default: models/$filename with filename from --hf-file
+                                  or --model-url if set, otherwise models/7B/ggml-model-f16.gguf)
+  -md,   --model-draft FNAME      draft model for speculative decoding (default: unused)
+  -mu,   --model-url MODEL_URL    model download url (default: unused)
+  -hfr,  --hf-repo REPO           Hugging Face model repository (default: unused)
+  -hff,  --hf-file FILE           Hugging Face model file (default: unused)
+  -hft,  --hf-token TOKEN         Hugging Face access token (default: value from HF_TOKEN environment variable)
+
+retrieval:
+
+         --context-file FNAME     file to load context from (repeat to specify multiple files)
+         --chunk-size N           minimum length of embedded text chunks (default: 64)
+         --chunk-separator STRING 
+                                  separator between chunks (default: '
+                                  ')
+
+passkey:
+
+         --junk N                 number of times to repeat the junk text (default: 250)
+         --pos N                  position of the passkey in the junk text (default: -1)
+
+imatrix:
+
+  -o,    --output FNAME           output file (default: 'imatrix.dat')
+         --output-frequency N     output the imatrix every N iterations (default: 10)
+         --save-frequency N       save an imatrix copy every N iterations (default: 0)
+         --process-output         collect data for the output tensor (default: false)
+         --no-ppl                 do not compute perplexity (default: true)
+         --chunk N                start processing the input from chunk N (default: 0)
+
+bench:
+
+  -pps                            is the prompt shared across parallel sequences (default: false)
+  -npp n0,n1,...                  number of prompt tokens
+  -ntg n0,n1,...                  number of text generation tokens
+  -npl n0,n1,...                  number of parallel prompts
+
+embedding:
+
+         --embd-normalize         normalisation for embendings (default: 2) (-1=none, 0=max absolute int16, 1=taxicab, 2=euclidean, >2=p-norm)
+         --embd-output-format     empty = default, "array" = [[],[]...], "json" = openai style, "json+" = same "json" + cosine similarity matrix
+         --embd-separator         separator of embendings (default \n) for example "<#sep#>"
+
+server:
+
+         --host HOST              ip address to listen (default: 127.0.0.1)
+         --port PORT              port to listen (default: 8080)
+         --path PATH              path to serve static files from (default: )
+         --embedding(s)           enable embedding endpoint (default: disabled)
+         --api-key KEY            API key to use for authentication (default: none)
+         --api-key-file FNAME     path to file containing API keys (default: none)
+         --ssl-key-file FNAME     path to file a PEM-encoded SSL private key
+         --ssl-cert-file FNAME    path to file a PEM-encoded SSL certificate
+         --timeout N              server read/write timeout in seconds (default: 600)
+         --threads-http N         number of threads used to process HTTP requests (default: -1)
+         --system-prompt-file FNAME
+                                  set a file to load a system prompt (initial prompt of all slots), this is useful for chat applications
+         --log-format {text,json} 
+                                  log output format: json or text (default: json)
+         --metrics                enable prometheus compatible metrics endpoint (default: disabled)
+         --no-slots               disables slots monitoring endpoint (default: enabled)
+         --slot-save-path PATH    path to save slot kv cache (default: disabled)
+         --chat-template JINJA_TEMPLATE
+                                  set custom jinja chat template (default: template taken from model's metadata)
+                                  only commonly used templates are accepted:
+                                  https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template
+  -sps,  --slot-prompt-similarity SIMILARITY
+                                  how much the prompt of a request must match the prompt of a slot in order to use that slot (default: 0.50, 0.0 = disabled)
+
+
+logging:
+
+         --simple-io              use basic IO for better compatibility in subprocesses and limited consoles
+  -ld,   --logdir LOGDIR          path under which to save YAML logs (no logging if unset)
+         --log-test               Run simple logging test
+         --log-disable            Disable trace logs
+         --log-enable             Enable trace logs
+         --log-file FNAME         Specify a log filename (without extension)
+         --log-new                Create a separate new log file on start. Each log file will have unique name: "..log"
+         --log-append             Don't truncate the old log file.
+
+cvector:
+
+  -o,    --output FNAME           output file (default: 'control_vector.gguf')
+         --positive-file FNAME    positive prompts file, one prompt per line (default: 'examples/cvector-generator/positive.txt')
+         --negative-file FNAME    negative prompts file, one prompt per line (default: 'examples/cvector-generator/negative.txt')
+         --pca-batch N            batch size used for PCA. Larger batch runs faster, but uses more memory (default: 100)
+         --pca-iter N             number of iterations used for PCA (default: 1000)
+         --method {pca,mean}      dimensionality reduction method to be used (default: pca)
+```
+
 
 ## Build
 

From 8fac431b0692e88cdc55250f29f8d4386be82c5d Mon Sep 17 00:00:00 2001
From: Daniel Bevenius 
Date: Mon, 15 Jul 2024 14:48:17 +0200
Subject: [PATCH 189/326] ggml : suppress unknown pragma 'GCC' on windows
 (#8460)

This commit adds a macro guard to pragma GCC to avoid the following
warning on windows:

```console
C:\llama.cpp\ggml\src\ggml-aarch64.c(17,9): warning C4068:
unknown pragma 'GCC' [C:\lama.cpp\build\ggml\src\ggml.vcxproj]
```
---
 ggml/src/ggml-aarch64.c | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/ggml/src/ggml-aarch64.c b/ggml/src/ggml-aarch64.c
index 40838cf4ffdcf..26535b1c432ba 100644
--- a/ggml/src/ggml-aarch64.c
+++ b/ggml/src/ggml-aarch64.c
@@ -14,7 +14,9 @@
 
 #include "ggml-aarch64.h"
 
+#if defined(__GNUC__)
 #pragma GCC diagnostic ignored "-Woverlength-strings"
+#endif
 
 #define UNUSED GGML_UNUSED
 

From 4db8f60fe79a391e82b0464013ada123baced96a Mon Sep 17 00:00:00 2001
From: Xuan Son Nguyen 
Date: Mon, 15 Jul 2024 19:23:10 +0200
Subject: [PATCH 190/326] fix ci (#8494)

---
 examples/server/README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/server/README.md b/examples/server/README.md
index d7487ec1b5b7e..e477d1501f976 100644
--- a/examples/server/README.md
+++ b/examples/server/README.md
@@ -211,7 +211,7 @@ retrieval:
 
          --context-file FNAME     file to load context from (repeat to specify multiple files)
          --chunk-size N           minimum length of embedded text chunks (default: 64)
-         --chunk-separator STRING 
+         --chunk-separator STRING
                                   separator between chunks (default: '
                                   ')
 
@@ -256,7 +256,7 @@ server:
          --threads-http N         number of threads used to process HTTP requests (default: -1)
          --system-prompt-file FNAME
                                   set a file to load a system prompt (initial prompt of all slots), this is useful for chat applications
-         --log-format {text,json} 
+         --log-format {text,json}
                                   log output format: json or text (default: json)
          --metrics                enable prometheus compatible metrics endpoint (default: disabled)
          --no-slots               disables slots monitoring endpoint (default: enabled)

From 97bdd26eee11fe109dec00de75690ceef61c03f2 Mon Sep 17 00:00:00 2001
From: Xuan Son Nguyen 
Date: Mon, 15 Jul 2024 20:50:47 +0200
Subject: [PATCH 191/326] Refactor lora adapter support (#8332)

* lora: load to devide buft

* add patch tensor function

* correct tensor patch

* llama_lora_adapter_apply

* correct ggml_backend_tensor_copy

* add llm_build_mm

* fix auto merge

* update based on review comments

* add convert script

* no more transpose A

* add f16 convert

* add metadata check

* add sanity check

* fix ftype

* add requirements

* fix requirements

* fix outfile

* conversion: only allow selected models

* fix types

* cuda : do not use dmmv if the tensor does not have enough cols

* llama : lora fixes

* do not disable mmap with lora

Co-authored-by: slaren 

* llm_build_lora_mm_id

* convert_lora : MoE LoRA conversion support

* convert_lora : prefer safetensors, similarly to convert_hf

* convert_hf : simplify modify_tensors for InternLM2

* convert_lora : lazy conversion

* llama : load and use alpha from LoRA adapters

* llama : use llm_build_lora_mm in most model graphs

* auto scale

* Revert "auto scale"

This reverts commit 42415a4874e0f963e4aca6796ea5dfb97cd17464.

* remove redundant params

* Apply suggestions from code review

Co-authored-by: slaren 

* change kv metadata

* move add_type to __init__

* convert_hf : move add_type to main()

* convert_lora : use the GGUFWriter from Model instead of overwriting it

---------

Co-authored-by: slaren 
Co-authored-by: Francis Couture-Harpin 
---
 common/common.cpp                             |  13 +-
 convert_hf_to_gguf.py                         |  34 +-
 convert_lora_to_gguf.py                       | 374 +++++++
 ggml/src/ggml-cuda.cu                         |   3 +-
 ggml/src/ggml.c                               |   4 +-
 gguf-py/gguf/constants.py                     |  10 +
 gguf-py/gguf/gguf_writer.py                   |   3 +
 gguf-py/gguf/quants.py                        |   2 +-
 include/llama.h                               |  37 +-
 requirements.txt                              |   1 +
 .../requirements-convert_lora_to_gguf.txt     |   2 +
 src/llama.cpp                                 | 972 +++++++++---------
 12 files changed, 944 insertions(+), 511 deletions(-)
 create mode 100755 convert_lora_to_gguf.py
 create mode 100644 requirements/requirements-convert_lora_to_gguf.txt

diff --git a/common/common.cpp b/common/common.cpp
index 9035c359267a7..dbb724fbbbcff 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -685,7 +685,6 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
     if (arg == "--lora") {
         CHECK_ARG
         params.lora_adapter.emplace_back(argv[i], 1.0f);
-        params.use_mmap = false;
         return true;
     }
     if (arg == "--lora-scaled") {
@@ -693,7 +692,6 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
         const char* lora_adapter = argv[i];
         CHECK_ARG
         params.lora_adapter.emplace_back(lora_adapter, std::stof(argv[i]));
-        params.use_mmap = false;
         return true;
     }
     if (arg == "--lora-base") {
@@ -2089,19 +2087,14 @@ std::tuple llama_init_from_gpt_par
     for (unsigned int i = 0; i < params.lora_adapter.size(); ++i) {
         const std::string & lora_adapter = std::get<0>(params.lora_adapter[i]);
         float lora_scale = std::get<1>(params.lora_adapter[i]);
-        int err = llama_model_apply_lora_from_file(model,
-                                             lora_adapter.c_str(),
-                                             lora_scale,
-                                             ((i > 0) || params.lora_base.empty())
-                                                ? NULL
-                                                : params.lora_base.c_str(),
-                                             params.n_threads);
-        if (err != 0) {
+        auto adapter = llama_lora_adapter_init(model, lora_adapter.c_str());
+        if (adapter == nullptr) {
             fprintf(stderr, "%s: error: failed to apply lora adapter\n", __func__);
             llama_free(lctx);
             llama_free_model(model);
             return std::make_tuple(nullptr, nullptr);
         }
+        llama_lora_adapter_set(lctx, adapter, lora_scale);
     }
 
     if (params.ignore_eos) {
diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py
index 42dace219f20f..a755b0a60bf0a 100755
--- a/convert_hf_to_gguf.py
+++ b/convert_hf_to_gguf.py
@@ -2264,13 +2264,6 @@ def set_vocab(self):
 
         special_vocab.add_to_gguf(self.gguf_writer)
 
-    def _hf_permute_qk(self, weights, n_head: int, n_head_kv: int):
-        if n_head_kv is not None and n_head != n_head_kv:
-            n_head = n_head_kv
-        return (weights.reshape(n_head, 2, weights.shape[0] // n_head // 2, *weights.shape[1:])
-                .swapaxes(1, 2)
-                .reshape(weights.shape))
-
     def set_gguf_parameters(self):
         self.gguf_writer.add_name("InternLM2")
         self.gguf_writer.add_context_length(self.hparams["max_position_embeddings"])
@@ -2290,26 +2283,22 @@ def set_gguf_parameters(self):
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         num_heads = self.hparams["num_attention_heads"]
         num_kv_heads = self.hparams["num_key_value_heads"]
-        hidden_size = self.hparams["hidden_size"]
+        n_embd = self.hparams["hidden_size"]
         q_per_kv = num_heads // num_kv_heads
-        head_dim = hidden_size // num_heads
+        head_dim = n_embd // num_heads
         num_groups = num_heads // q_per_kv
 
-        qkv_pattern = r"model\.layers\.(\d+)\.attention\.wqkv"
-
-        if re.match(qkv_pattern, name):
-            bid = re.findall(qkv_pattern, name)[0]
+        if bid is not None and f"model.layers.{bid}.attention.wqkv" in name:
             qkv = data_torch
-            # qkv = rearrange(qkv.T, " o (g n i) ->o g n i", g=num_groups, n=q_per_kv + 2, i=head_dim)
-            qkv = qkv.T.reshape((-1, num_groups, q_per_kv + 2, head_dim))
-            q, k, v = qkv[..., : q_per_kv, :], qkv[..., q_per_kv: q_per_kv + 1, :], qkv[..., q_per_kv + 1: q_per_kv + 2, :]
+
+            qkv = qkv.reshape((num_groups, q_per_kv + 2, head_dim, n_embd))
+            q, k, v = qkv[:, : q_per_kv], qkv[:, -2], qkv[:, -1]
+
             # The model weights of q and k equire additional reshape.
-            # q = self._hf_permute_qk(rearrange(q, " o g n i ->  o (g n i)").T, num_heads, num_heads)
-            q = self._hf_permute_qk(q.reshape((q.shape[0], -1)).T, num_heads, num_heads)
-            # k = self._hf_permute_qk(rearrange(k, " o g n i ->  o (g n i)").T, num_heads, num_kv_heads)
-            k = self._hf_permute_qk(k.reshape((k.shape[0], -1)).T, num_heads, num_kv_heads)
-            # v = rearrange(v, " o g n i ->  o (g n i)").T
-            v = v.reshape((v.shape[0], -1)).T
+            q = LlamaModel.permute(q.reshape((-1, q.shape[-1])), num_heads, num_heads)
+            k = LlamaModel.permute(k.reshape((-1, k.shape[-1])), num_heads, num_kv_heads)
+            v = v.reshape((-1, v.shape[-1]))
+
             return [
                 (self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_Q, bid), q),
                 (self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_K, bid), k),
@@ -3585,6 +3574,7 @@ def main() -> None:
                                      small_first_shard=args.no_tensor_first_split)
 
         logger.info("Set model parameters")
+        model_instance.gguf_writer.add_type(gguf.GGUFType.MODEL)
         model_instance.set_gguf_parameters()
 
         logger.info("Set model tokenizer")
diff --git a/convert_lora_to_gguf.py b/convert_lora_to_gguf.py
new file mode 100755
index 0000000000000..4bb939d45d6bd
--- /dev/null
+++ b/convert_lora_to_gguf.py
@@ -0,0 +1,374 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+import logging
+import argparse
+import os
+import sys
+import json
+from math import prod
+from pathlib import Path
+from typing import TYPE_CHECKING, Any, Callable, Iterable, Iterator, Sequence, SupportsIndex, cast
+
+import torch
+
+if TYPE_CHECKING:
+    from torch import Tensor
+
+if 'NO_LOCAL_GGUF' not in os.environ:
+    sys.path.insert(1, str(Path(__file__).parent / 'gguf-py'))
+import gguf
+
+# reuse model definitions from convert_hf_to_gguf.py
+from convert_hf_to_gguf import LazyTorchTensor, Model
+
+logger = logging.getLogger("lora-to-gguf")
+
+
+@dataclass
+class PartialLoraTensor:
+    A: Tensor | None = None
+    B: Tensor | None = None
+
+
+# magic to support tensor shape modifications and splitting
+class LoraTorchTensor:
+    _lora_A: Tensor  # (n_rank, row_size)
+    _lora_B: Tensor  # (col_size, n_rank)
+    _rank: int
+
+    def __init__(self, A: Tensor, B: Tensor):
+        assert len(A.shape) == len(B.shape)
+        assert A.shape[-2] == B.shape[-1]
+        if A.dtype != B.dtype:
+            A = A.to(torch.float32)
+            B = B.to(torch.float32)
+        self._lora_A = A
+        self._lora_B = B
+        self._rank = B.shape[-1]
+
+    def get_lora_A_B(self) -> tuple[Tensor, Tensor]:
+        return (self._lora_A, self._lora_B)
+
+    def __getitem__(
+        self,
+        indices: (
+            SupportsIndex
+            | slice
+            | tuple[SupportsIndex | slice | Tensor, ...]  # TODO: add ellipsis in the type signature
+        ),
+    ) -> LoraTorchTensor:
+        shape = self.shape
+        if isinstance(indices, SupportsIndex):
+            if len(shape) > 2:
+                return LoraTorchTensor(self._lora_A[indices], self._lora_B[indices])
+            else:
+                raise NotImplementedError  # can't return a vector
+        elif isinstance(indices, slice):
+            if len(shape) > 2:
+                return LoraTorchTensor(self._lora_A[indices], self._lora_B[indices])
+            else:
+                return LoraTorchTensor(self._lora_A, self._lora_B[indices])
+        elif isinstance(indices, tuple):
+            assert len(indices) > 0
+            if indices[-1] is Ellipsis:
+                return self[indices[:-1]]
+            # expand ellipsis
+            indices = tuple(
+                u
+                for v in (
+                    (
+                        (slice(None, None) for _ in range(len(indices) - 1))
+                        if i is Ellipsis
+                        else (i,)
+                    )
+                    for i in indices
+                )
+                for u in v
+            )
+
+            if len(indices) < len(shape):
+                indices = (*indices, *(slice(None, None) for _ in range(len(indices), len(shape))))
+
+            # TODO: make sure this is correct
+            indices_A = (
+                *(
+                    (
+                        j.__index__() % self._lora_A.shape[i]
+                        if isinstance(j, SupportsIndex)
+                        else slice(None, None)
+                    )
+                    for i, j in enumerate(indices[:-2])
+                ),
+                slice(None, None),
+                indices[-1],
+            )
+            indices_B = indices[:-1]
+            return LoraTorchTensor(self._lora_A[indices_A], self._lora_B[indices_B])
+        else:
+            raise NotImplementedError  # unknown indice type
+
+    @property
+    def dtype(self) -> torch.dtype:
+        assert self._lora_A.dtype == self._lora_B.dtype
+        return self._lora_A.dtype
+
+    @property
+    def shape(self) -> tuple[int, ...]:
+        assert len(self._lora_A.shape) == len(self._lora_B.shape)
+        return (*self._lora_B.shape[:-1], self._lora_A.shape[-1])
+
+    def size(self, dim=None):
+        assert dim is None
+        return self.shape
+
+    def reshape(self, *shape: int | tuple[int, ...]) -> LoraTorchTensor:
+        if isinstance(shape[0], tuple):
+            new_shape: tuple[int, ...] = shape[0]
+        else:
+            new_shape = cast(tuple[int, ...], shape)
+        orig_shape = self.shape
+        if len(new_shape) < 2:
+            raise NotImplementedError  # can't become a vector
+
+        # expand -1 in the shape
+        if any(dim == -1 for dim in new_shape):
+            n_elems = prod(orig_shape)
+            n_new_elems = prod(dim if dim != -1 else 1 for dim in new_shape)
+            assert n_elems % n_new_elems == 0
+            new_shape = (*(dim if dim != -1 else n_elems // n_new_elems for dim in new_shape),)
+
+        if new_shape[-1] != orig_shape[-1]:
+            raise NotImplementedError  # can't reshape the row size trivially
+
+        shape_A = (*(1 for _ in new_shape[:-2]), self._rank, orig_shape[-1])
+        shape_B = (*new_shape[:-1], self._rank)
+        return LoraTorchTensor(
+            self._lora_A.reshape(shape_A),
+            self._lora_B.reshape(shape_B),
+        )
+
+    def reshape_as(self, other: Tensor) -> LoraTorchTensor:
+        return self.reshape(*other.shape)
+
+    def view(self, *size: int) -> LoraTorchTensor:
+        return self.reshape(*size)
+
+    def permute(self, *dims: int) -> LoraTorchTensor:
+        shape = self.shape
+        dims = tuple(dim - len(shape) if dim >= 0 else dim for dim in dims)
+        if dims[-1] == -1:
+            # TODO: support higher dimensional A shapes bigger than 1
+            assert all(dim == 1 for dim in self._lora_A.shape[:-2])
+            return LoraTorchTensor(self._lora_A, self._lora_B.permute(*dims))
+        if len(shape) == 2 and dims[-1] == -2 and dims[-2] == -1:
+            return LoraTorchTensor(self._lora_B.permute(*dims), self._lora_A.permute(*dims))
+        else:
+            # TODO: compose the above two
+            raise NotImplementedError
+
+    def transpose(self, dim0: int, dim1: int) -> LoraTorchTensor:
+        shape = self.shape
+        dims = [i for i in range(len(shape))]
+        dims[dim0], dims[dim1] = dims[dim1], dims[dim0]
+        return self.permute(*dims)
+
+    def swapaxes(self, axis0: int, axis1: int) -> LoraTorchTensor:
+        return self.transpose(axis0, axis1)
+
+    def to(self, *args, **kwargs):
+        return LoraTorchTensor(self._lora_A.to(*args, **kwargs), self._lora_B.to(*args, **kwargs))
+
+    @classmethod
+    def __torch_function__(cls, func: Callable, types, args=(), kwargs=None):
+        del types  # unused
+
+        if kwargs is None:
+            kwargs = {}
+
+        if func is torch.permute:
+            return type(args[0]).permute(*args, **kwargs)
+        elif func is torch.reshape:
+            return type(args[0]).reshape(*args, **kwargs)
+        elif func is torch.stack:
+            assert isinstance(args[0], Sequence)
+            dim = kwargs.get("dim", 0)
+            assert dim == 0
+            return LoraTorchTensor(
+                torch.stack([a._lora_A for a in args[0]], dim),
+                torch.stack([b._lora_B for b in args[0]], dim),
+            )
+        elif func is torch.cat:
+            assert isinstance(args[0], Sequence)
+            dim = kwargs.get("dim", 0)
+            assert dim == 0
+            if len(args[0][0].shape) > 2:
+                return LoraTorchTensor(
+                    torch.cat([a._lora_A for a in args[0]], dim),
+                    torch.cat([b._lora_B for b in args[0]], dim),
+                )
+            elif all(torch.equal(args[0][0]._lora_A, t._lora_A) for t in args[0][1:]):
+                return LoraTorchTensor(
+                    args[0][0]._lora_A,
+                    torch.cat([b._lora_B for b in args[0]], dim),
+                )
+            else:
+                raise NotImplementedError
+        else:
+            raise NotImplementedError
+
+
+def get_base_tensor_name(lora_tensor_name: str) -> str:
+    base_name = lora_tensor_name.replace("base_model.model.", "")
+    base_name = base_name.replace(".lora_A.weight", ".weight")
+    base_name = base_name.replace(".lora_B.weight", ".weight")
+    return base_name
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(
+        description="Convert a huggingface PEFT LoRA adapter to a GGML compatible file")
+    parser.add_argument(
+        "--outfile", type=Path,
+        help="path to write to; default: based on input. {ftype} will be replaced by the outtype.",
+    )
+    parser.add_argument(
+        "--outtype", type=str, choices=["f32", "f16", "bf16", "q8_0", "auto"], default="f16",
+        help="output format - use f32 for float32, f16 for float16, bf16 for bfloat16, q8_0 for Q8_0, auto for the highest-fidelity 16-bit float type depending on the first loaded tensor type",
+    )
+    parser.add_argument(
+        "--bigendian", action="store_true",
+        help="model is executed on big endian machine",
+    )
+    parser.add_argument(
+        "--no-lazy", action="store_true",
+        help="use more RAM by computing all outputs before writing (use in case lazy evaluation is broken)",
+    )
+    parser.add_argument(
+        "--verbose", action="store_true",
+        help="increase output verbosity",
+    )
+    parser.add_argument(
+        "--base", type=Path, required=True,
+        help="directory containing base model file",
+    )
+    parser.add_argument(
+        "lora_path", type=Path,
+        help="directory containing LoRA adapter file",
+    )
+
+    return parser.parse_args()
+
+
+if __name__ == '__main__':
+    args = parse_args()
+    logging.basicConfig(level=logging.DEBUG if args.verbose else logging.INFO)
+
+    ftype_map: dict[str, gguf.LlamaFileType] = {
+        "f32": gguf.LlamaFileType.ALL_F32,
+        "f16": gguf.LlamaFileType.MOSTLY_F16,
+        "bf16": gguf.LlamaFileType.MOSTLY_BF16,
+        "q8_0": gguf.LlamaFileType.MOSTLY_Q8_0,
+        "auto": gguf.LlamaFileType.GUESSED,
+    }
+
+    ftype = ftype_map[args.outtype]
+
+    dir_base_model: Path = args.base
+    dir_lora: Path = args.lora_path
+    lora_config = dir_lora / "adapter_config.json"
+    input_model = dir_lora / "adapter_model.safetensors"
+
+    if args.outfile is not None:
+        fname_out = args.outfile
+    else:
+        # output in the same directory as the model by default
+        fname_out = dir_lora / 'ggml-lora-{ftype}.gguf'
+
+    if os.path.exists(input_model):
+        # lazy import load_file only if lora is in safetensors format.
+        from safetensors.torch import load_file
+
+        lora_model = load_file(input_model, device="cpu")
+    else:
+        input_model = os.path.join(dir_lora, "adapter_model.bin")
+        lora_model = torch.load(input_model, map_location="cpu", weights_only=True)
+
+    # load base model
+    logger.info(f"Loading base model: {dir_base_model.name}")
+    hparams = Model.load_hparams(dir_base_model)
+    with torch.inference_mode():
+        try:
+            model_class = Model.from_model_architecture(hparams["architectures"][0])
+        except NotImplementedError:
+            logger.error(f"Model {hparams['architectures'][0]} is not supported")
+            sys.exit(1)
+
+        class LoraModel(model_class):
+            model_arch = model_class.model_arch
+
+            def get_tensors(self) -> Iterator[tuple[str, Tensor]]:
+                tensor_map: dict[str, PartialLoraTensor] = {}
+
+                for name, tensor in lora_model.items():
+                    if self.lazy:
+                        tensor = LazyTorchTensor.from_eager(tensor)
+                    base_name = get_base_tensor_name(name)
+                    is_lora_a = ".lora_A.weight" in name
+                    is_lora_b = ".lora_B.weight" in name
+                    if not is_lora_a and not is_lora_b:
+                        if ".base_layer.weight" in name:
+                            continue
+                        logger.error(f"Unexpected name '{name}': Not a lora_A or lora_B tensor")
+                        sys.exit(1)
+
+                    if base_name in tensor_map:
+                        if is_lora_a:
+                            tensor_map[base_name].A = tensor
+                        else:
+                            tensor_map[base_name].B = tensor
+                    else:
+                        if is_lora_a:
+                            tensor_map[base_name] = PartialLoraTensor(A=tensor)
+                        else:
+                            tensor_map[base_name] = PartialLoraTensor(B=tensor)
+
+                for name, tensor in tensor_map.items():
+                    assert tensor.A is not None
+                    assert tensor.B is not None
+                    yield (name, cast(torch.Tensor, LoraTorchTensor(tensor.A, tensor.B)))
+
+            def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+                dest = super().modify_tensors(data_torch, name, bid)
+                for dest_name, dest_data in dest:
+                    assert isinstance(dest_data, LoraTorchTensor)
+                    lora_a, lora_b = dest_data.get_lora_A_B()
+
+                    yield (dest_name + ".lora_a", lora_a)
+                    yield (dest_name + ".lora_b", lora_b)
+
+        model_instance = LoraModel(
+            dir_base_model,
+            ftype,
+            fname_out,
+            is_big_endian=args.bigendian,
+            use_temp_file=False,
+            eager=args.no_lazy,
+            model_name=None,
+        )
+
+        with open(lora_config, "r") as f:
+            lparams: dict[str, Any] = json.load(f)
+
+        alpha = lparams["lora_alpha"]
+
+        model_instance.gguf_writer.add_string(gguf.Keys.General.TYPE, gguf.GGUFType.ADAPTER)
+        model_instance.gguf_writer.add_string(gguf.Keys.Adapter.TYPE, "lora")
+        model_instance.gguf_writer.add_float32(gguf.Keys.Adapter.LORA_ALPHA, float(alpha))
+        model_instance.gguf_writer.add_quantization_version(gguf.GGML_QUANT_VERSION)
+        logger.info("Exporting model...")
+        model_instance.write()
+        logger.info(f"Model successfully exported to {model_instance.fname_out}")
diff --git a/ggml/src/ggml-cuda.cu b/ggml/src/ggml-cuda.cu
index ed784ea1c2024..39e345b668bc1 100644
--- a/ggml/src/ggml-cuda.cu
+++ b/ggml/src/ggml-cuda.cu
@@ -1876,7 +1876,8 @@ static void ggml_cuda_mul_mat(ggml_backend_cuda_context & ctx, const ggml_tensor
 
     bool use_dequantize_mul_mat_vec = (ggml_is_quantized(src0->type) || src0->type == GGML_TYPE_F16)
         && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32
-        && src0->ne[0] % GGML_CUDA_DMMV_X == 0 && src1->ne[1] == 1;
+        && src0->ne[0] % GGML_CUDA_DMMV_X == 0 && src0->ne[0] >= GGML_CUDA_DMMV_X*2
+        && src1->ne[1] == 1;
     bool          use_mul_mat_vec_q =  ggml_is_quantized(src0->type)
         && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32
         && src1->ne[1] <= MMVQ_MAX_BATCH_SIZE;
diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c
index 9a54147871847..60b3c5e7a12d3 100644
--- a/ggml/src/ggml.c
+++ b/ggml/src/ggml.c
@@ -19478,7 +19478,7 @@ void ggml_graph_dump_dot(const struct ggml_cgraph * gb, const struct ggml_cgraph
 
     fprintf(fp, "digraph G {\n");
     fprintf(fp, "  newrank = true;\n");
-    fprintf(fp, "  rankdir = LR;\n");
+    fprintf(fp, "  rankdir = TB;\n");
 
     for (int i = 0; i < gb->n_nodes; i++) {
         struct ggml_tensor * node = gb->nodes[i];
@@ -19540,7 +19540,7 @@ void ggml_graph_dump_dot(const struct ggml_cgraph * gb, const struct ggml_cgraph
         }
 
         fprintf(fp, "CONST %d [%" PRId64 ", %" PRId64 "]", i, node->ne[0], node->ne[1]);
-        if (ggml_nelements(node) < 5) {
+        if (ggml_nelements(node) < 5 && node->data != NULL) {
             fprintf(fp, " | (");
             for (int j = 0; j < ggml_nelements(node); j++) {
                 if (node->type == GGML_TYPE_I8 || node->type == GGML_TYPE_I16 || node->type == GGML_TYPE_I32) {
diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py
index a95a44237e348..5eb3df706e6e2 100644
--- a/gguf-py/gguf/constants.py
+++ b/gguf-py/gguf/constants.py
@@ -19,6 +19,7 @@
 
 class Keys:
     class General:
+        TYPE                 = "general.type"
         ARCHITECTURE         = "general.architecture"
         QUANTIZATION_VERSION = "general.quantization_version"
         ALIGNMENT            = "general.alignment"
@@ -120,11 +121,20 @@ class Tokenizer:
         MIDDLE_ID            = "tokenizer.ggml.middle_token_id"
         EOT_ID               = "tokenizer.ggml.eot_token_id"
 
+    class Adapter:
+        TYPE       = "adapter.type"
+        LORA_ALPHA = "adapter.lora.alpha"
+
 #
 # recommended mapping of model tensor names for storage in gguf
 #
 
 
+class GGUFType:
+    MODEL   = "model"
+    ADAPTER = "adapter"
+
+
 class MODEL_ARCH(IntEnum):
     LLAMA        = auto()
     FALCON       = auto()
diff --git a/gguf-py/gguf/gguf_writer.py b/gguf-py/gguf/gguf_writer.py
index cf95541629032..b0197961d46a8 100644
--- a/gguf-py/gguf/gguf_writer.py
+++ b/gguf-py/gguf/gguf_writer.py
@@ -424,6 +424,9 @@ def close(self) -> None:
                 fout.close()
             self.fout = None
 
+    def add_type(self, type_name: str) -> None:
+        self.add_string(Keys.General.TYPE, type_name)
+
     def add_architecture(self) -> None:
         self.add_string(Keys.General.ARCHITECTURE, self.arch)
 
diff --git a/gguf-py/gguf/quants.py b/gguf-py/gguf/quants.py
index b22eec1661ce7..16e0a9aaa8a8b 100644
--- a/gguf-py/gguf/quants.py
+++ b/gguf-py/gguf/quants.py
@@ -43,7 +43,7 @@ def __apply_over_grouped_rows(func: Callable[[np.ndarray], np.ndarray], arr: np.
         osize *= dim
     out = np.empty(shape=osize, dtype=otype)
     # compute over groups of 16 rows (arbitrary, but seems good for performance)
-    n_groups = rows.shape[0] // 16
+    n_groups = (rows.shape[0] // 16) or 1
     np.concatenate([func(group).ravel() for group in np.array_split(rows, n_groups)], axis=0, out=out)
     return out.reshape(oshape)
 
diff --git a/include/llama.h b/include/llama.h
index 3970c3aebcd62..c57d21f0c70b9 100644
--- a/include/llama.h
+++ b/include/llama.h
@@ -411,6 +411,9 @@ extern "C" {
         const char * content;
     } llama_chat_message;
 
+    // lora adapter
+    struct llama_lora_adapter;
+
     // Helpers for getting default parameters
     LLAMA_API struct llama_model_params llama_model_default_params(void);
     LLAMA_API struct llama_context_params llama_context_default_params(void);
@@ -510,18 +513,28 @@ extern "C" {
             const char * fname_out,
             const llama_model_quantize_params * params);
 
-    // Apply a LoRA adapter to a loaded model
-    // path_base_model is the path to a higher quality model to use as a base for
-    // the layers modified by the adapter. Can be NULL to use the current loaded model.
-    // The model needs to be reloaded before applying a new adapter, otherwise the adapter
-    // will be applied on top of the previous one
-    // Returns 0 on success
-    LLAMA_API int32_t llama_model_apply_lora_from_file(
-            const struct llama_model * model,
-                          const char * path_lora,
-                               float   scale,
-                          const char * path_base_model,
-                             int32_t   n_threads);
+    // Load a LoRA adapter from file
+    // The loaded adapter will be associated to the given model, and will be free when the model is deleted
+    LLAMA_API struct llama_lora_adapter * llama_lora_adapter_init(
+            struct llama_model * model,
+            const char * path_lora);
+
+    // Add a loaded LoRA adapter to given context
+    // This will not modify model's weight
+    LLAMA_API int32_t llama_lora_adapter_set(
+            struct llama_context * ctx,
+            struct llama_lora_adapter * adapter,
+            float scale);
+
+    // Remove a LoRA adapter from given context
+    // Return -1 if the adapter is not present in the context
+    LLAMA_API int32_t llama_lora_adapter_remove(
+            struct llama_context * ctx,
+            struct llama_lora_adapter * adapter);
+
+    // Manually free a LoRA adapter
+    // Note: loaded adapters will be free when the associated model is deleted
+    LLAMA_API void llama_lora_adapter_free(struct llama_lora_adapter * adapter);
 
     // Apply a loaded control vector to a llama_context, or if data is NULL, clear
     // the currently loaded vector.
diff --git a/requirements.txt b/requirements.txt
index 52456c2e6fd24..9e190ae27de38 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -9,3 +9,4 @@
 -r ./requirements/requirements-convert_hf_to_gguf.txt
 -r ./requirements/requirements-convert_hf_to_gguf_update.txt
 -r ./requirements/requirements-convert_llama_ggml_to_gguf.txt
+-r ./requirements/requirements-convert_lora_to_gguf.txt
diff --git a/requirements/requirements-convert_lora_to_gguf.txt b/requirements/requirements-convert_lora_to_gguf.txt
new file mode 100644
index 0000000000000..5758076c41dc1
--- /dev/null
+++ b/requirements/requirements-convert_lora_to_gguf.txt
@@ -0,0 +1,2 @@
+-r ./requirements-convert_hf_to_gguf.txt
+--extra-index-url https://download.pytorch.org/whl/cpu
diff --git a/src/llama.cpp b/src/llama.cpp
index ddf0262d443b0..07bb427135d8c 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -287,6 +287,7 @@ static const std::map LLM_ARCH_NAMES = {
 };
 
 enum llm_kv {
+    LLM_KV_GENERAL_TYPE,
     LLM_KV_GENERAL_ARCHITECTURE,
     LLM_KV_GENERAL_QUANTIZATION_VERSION,
     LLM_KV_GENERAL_ALIGNMENT,
@@ -377,9 +378,13 @@ enum llm_kv {
     LLM_KV_TOKENIZER_SUFFIX_ID,
     LLM_KV_TOKENIZER_MIDDLE_ID,
     LLM_KV_TOKENIZER_EOT_ID,
+
+    LLM_KV_ADAPTER_TYPE,
+    LLM_KV_ADAPTER_LORA_ALPHA,
 };
 
 static const std::map LLM_KV_NAMES = {
+    { LLM_KV_GENERAL_TYPE,                  "general.type"                          },
     { LLM_KV_GENERAL_ARCHITECTURE,          "general.architecture"                  },
     { LLM_KV_GENERAL_QUANTIZATION_VERSION,  "general.quantization_version"          },
     { LLM_KV_GENERAL_ALIGNMENT,             "general.alignment"                     },
@@ -470,6 +475,9 @@ static const std::map LLM_KV_NAMES = {
     { LLM_KV_TOKENIZER_SUFFIX_ID,            "tokenizer.ggml.suffix_token_id"          },
     { LLM_KV_TOKENIZER_MIDDLE_ID,            "tokenizer.ggml.middle_token_id"          },
     { LLM_KV_TOKENIZER_EOT_ID,               "tokenizer.ggml.eot_token_id"             },
+
+    { LLM_KV_ADAPTER_TYPE,                  "adapter.type"       },
+    { LLM_KV_ADAPTER_LORA_ALPHA,            "adapter.lora.alpha" },
 };
 
 struct LLM_KV {
@@ -2703,6 +2711,9 @@ struct llama_model {
     int64_t t_load_us = 0;
     int64_t t_start_us = 0;
 
+    // keep track of loaded lora adapters
+    std::set lora_adapters;
+
     ~llama_model() {
         for (struct ggml_context * ctx : ctxs) {
             ggml_free(ctx);
@@ -2715,6 +2726,9 @@ struct llama_model {
 #endif
             ggml_backend_buffer_free(buf);
         }
+        while (!lora_adapters.empty()) {
+            llama_lora_adapter_free(*lora_adapters.begin());
+        }
     }
 };
 
@@ -2819,6 +2833,52 @@ struct llama_context {
 
     // control vectors
     struct llama_control_vector cvec;
+
+    // lora adapters and scales
+    std::unordered_map lora_adapters;
+};
+
+struct llama_lora_weight {
+    struct ggml_tensor * a = nullptr;
+    struct ggml_tensor * b = nullptr;
+    llama_lora_weight() = default;
+    llama_lora_weight(struct ggml_tensor * a, struct ggml_tensor * b): a(a), b(b) {}
+};
+
+struct llama_lora_adapter {
+    struct llama_model * base_model;
+    // map tensor name to lora_a_b
+    std::unordered_map ab_map;
+    std::vector ctxs;
+    std::vector bufs;
+
+    float alpha;
+
+    llama_lora_adapter(struct llama_model * base_model): base_model(base_model) {
+        base_model->lora_adapters.insert(this);
+    }
+
+    llama_lora_weight * get_weight(struct ggml_tensor * w) {
+        std::string name(w->name);
+        auto pos = ab_map.find(name);
+        if (ab_map.find(name) != ab_map.end()) {
+            return &pos->second;
+        }
+        return nullptr;
+    }
+
+    ~llama_lora_adapter() {
+        for (struct ggml_context * ctx : ctxs) {
+            ggml_free(ctx);
+        }
+        for (ggml_backend_buffer_t buf : bufs) {
+            ggml_backend_buffer_free(buf);
+        }
+        auto pos = base_model->lora_adapters.find(this);
+        if (pos != base_model->lora_adapters.end()) {
+            base_model->lora_adapters.erase(pos);
+        }
+    }
 };
 
 static size_t llama_get_device_count(const llama_model & model) {
@@ -7809,6 +7869,58 @@ static void llm_build_kv_store(
     ggml_build_forward_expand(graph, ggml_cpy(ctx, v_cur, v_cache_view));
 }
 
+// do mat_mul, while optionally apply lora
+static struct ggml_tensor * llm_build_lora_mm(
+        struct llama_context & lctx,
+         struct ggml_context * ctx0,
+          struct ggml_tensor * w,
+          struct ggml_tensor * cur) {
+    struct ggml_tensor * res = ggml_mul_mat(ctx0, w, cur);
+    for (auto & it : lctx.lora_adapters) {
+        struct llama_lora_weight * lora = it.first->get_weight(w);
+        if (lora == nullptr) {
+            continue;
+        }
+        const float alpha = it.first->alpha;
+        const float rank  = (float) lora->b->ne[0];
+        const float scale = alpha ? it.second * alpha / rank : it.second;
+        struct ggml_tensor * ab_cur = ggml_mul_mat(
+            ctx0, lora->b,
+            ggml_mul_mat(ctx0, lora->a, cur)
+        );
+        ab_cur = ggml_scale(ctx0, ab_cur, scale);
+        res = ggml_add(ctx0, res, ab_cur);
+    }
+    return res;
+}
+
+// do mat_mul_id, while optionally apply lora
+static struct ggml_tensor * llm_build_lora_mm_id(
+        struct llama_context & lctx,
+         struct ggml_context * ctx0,
+          struct ggml_tensor * w,   // struct ggml_tensor * as
+          struct ggml_tensor * cur, // struct ggml_tensor * b
+          struct ggml_tensor * ids) {
+    struct ggml_tensor * res = ggml_mul_mat_id(ctx0, w, cur, ids);
+    for (auto & it : lctx.lora_adapters) {
+        struct llama_lora_weight * lora = it.first->get_weight(w);
+        if (lora == nullptr) {
+            continue;
+        }
+        const float alpha = it.first->alpha;
+        const float rank  = (float) lora->b->ne[0];
+        const float scale = alpha ? it.second * alpha / rank : it.second;
+        struct ggml_tensor * ab_cur = ggml_mul_mat_id(
+            ctx0, lora->b,
+            ggml_mul_mat_id(ctx0, lora->a, cur, ids),
+            ids
+        );
+        ab_cur = ggml_scale(ctx0, ab_cur, scale);
+        res = ggml_add(ctx0, res, ab_cur);
+    }
+    return res;
+}
+
 static struct ggml_tensor * llm_build_norm(
         struct ggml_context * ctx,
          struct ggml_tensor * cur,
@@ -7843,6 +7955,7 @@ static struct ggml_tensor * llm_build_norm(
 
 static struct ggml_tensor * llm_build_ffn(
         struct ggml_context * ctx,
+       struct llama_context & lctx,
          struct ggml_tensor * cur,
          struct ggml_tensor * up,
          struct ggml_tensor * up_b,
@@ -7858,7 +7971,7 @@ static struct ggml_tensor * llm_build_ffn(
           llm_ffn_gate_type   type_gate,
          const llm_build_cb & cb,
                         int   il) {
-    struct ggml_tensor * tmp = up ? ggml_mul_mat(ctx, up, cur) : cur;
+    struct ggml_tensor * tmp = up ? llm_build_lora_mm(lctx, ctx, up, cur) : cur;
     cb(tmp, "ffn_up", il);
 
     if (up_b) {
@@ -7875,12 +7988,12 @@ static struct ggml_tensor * llm_build_ffn(
         switch (type_gate) {
             case LLM_FFN_SEQ:
                 {
-                    cur = ggml_mul_mat(ctx, gate, tmp);
+                    cur = llm_build_lora_mm(lctx, ctx, gate, tmp);
                     cb(cur, "ffn_gate", il);
                 } break;
             case LLM_FFN_PAR:
                 {
-                    cur = ggml_mul_mat(ctx, gate, cur);
+                    cur = llm_build_lora_mm(lctx, ctx, gate, cur);
                     cb(cur, "ffn_gate", il);
                 } break;
         }
@@ -7948,7 +8061,7 @@ static struct ggml_tensor * llm_build_ffn(
     }
 
     if (down) {
-        cur = ggml_mul_mat(ctx, down, cur);
+        cur = llm_build_lora_mm(lctx, ctx, down, cur);
     }
 
     if (down_b) {
@@ -7969,6 +8082,7 @@ static struct ggml_tensor * llm_build_ffn(
 
 static struct ggml_tensor * llm_build_moe_ffn(
         struct ggml_context * ctx,
+       struct llama_context & lctx,
          struct ggml_tensor * cur,
          struct ggml_tensor * gate_inp,
          struct ggml_tensor * up_exps,
@@ -7985,7 +8099,7 @@ static struct ggml_tensor * llm_build_moe_ffn(
     int64_t n_embd = cur->ne[0];
     int64_t n_tokens = cur->ne[1];
 
-    ggml_tensor * logits = ggml_mul_mat(ctx, gate_inp, cur); // [n_expert, n_tokens]
+    ggml_tensor * logits = llm_build_lora_mm(lctx, ctx, gate_inp, cur); // [n_expert, n_tokens]
     cb(logits, "ffn_moe_logits", il);
 
     ggml_tensor * probs = ggml_soft_max(ctx, logits); // [n_expert, n_tokens]
@@ -8017,10 +8131,10 @@ static struct ggml_tensor * llm_build_moe_ffn(
     }
 
     cur = ggml_reshape_3d(ctx, cur, n_embd, 1, n_tokens);
-    ggml_tensor * up = ggml_mul_mat_id(ctx, up_exps, cur, selected_experts); // [n_ff, n_expert_used, n_tokens]
+    ggml_tensor * up = llm_build_lora_mm_id(lctx, ctx, up_exps, cur, selected_experts); // [n_ff, n_expert_used, n_tokens]
     cb(up, "ffn_moe_up", il);
 
-    ggml_tensor * gate = ggml_mul_mat_id(ctx, gate_exps, cur, selected_experts); // [n_ff, n_expert_used, n_tokens]
+    ggml_tensor * gate = llm_build_lora_mm_id(lctx, ctx, gate_exps, cur, selected_experts); // [n_ff, n_expert_used, n_tokens]
     cb(gate, "ffn_moe_gate", il);
 
     switch (type_op) {
@@ -8041,7 +8155,7 @@ static struct ggml_tensor * llm_build_moe_ffn(
     ggml_tensor * par = ggml_mul(ctx, up, gate); // [n_ff, n_expert_used, n_tokens]
     cb(par, "ffn_moe_gate_par", il);
 
-    ggml_tensor * experts = ggml_mul_mat_id(ctx, down_exps, par, selected_experts); // [n_embd, n_expert_used, n_tokens]
+    ggml_tensor * experts = llm_build_lora_mm_id(lctx, ctx, down_exps, par, selected_experts); // [n_embd, n_expert_used, n_tokens]
     cb(experts, "ffn_moe_down", il);
 
     experts = ggml_mul(ctx, experts, weights);
@@ -8069,9 +8183,7 @@ static struct ggml_tensor * llm_build_moe_ffn(
 
 static struct ggml_tensor * llm_build_kqv(
         struct ggml_context * ctx,
-          const llama_model & model,
-        const llama_hparams & hparams,
-        const llama_cparams & cparams,
+       struct llama_context & lctx,
        const llama_kv_cache & kv,
          struct ggml_cgraph * graph,
          struct ggml_tensor * wo,
@@ -8083,6 +8195,10 @@ static struct ggml_tensor * llm_build_kqv(
                     float     kq_scale,
          const llm_build_cb & cb,
                     int       il) {
+    const llama_model   & model   = lctx.model;
+    const llama_hparams & hparams = lctx.model.hparams;
+    const llama_cparams & cparams = lctx.cparams;
+
     const int64_t n_ctx         = cparams.n_ctx;
     const int64_t n_head        = hparams.n_head(il);
     const int64_t n_head_kv     = hparams.n_head_kv(il);
@@ -8181,7 +8297,7 @@ static struct ggml_tensor * llm_build_kqv(
     ggml_build_forward_expand(graph, cur);
 
     if (wo) {
-        cur = ggml_mul_mat(ctx, wo, cur);
+        cur = llm_build_lora_mm(lctx, ctx, wo, cur);
     }
 
     if (wo_b) {
@@ -8197,9 +8313,7 @@ static struct ggml_tensor * llm_build_kqv(
 
 static struct ggml_tensor * llm_build_kv(
         struct ggml_context * ctx,
-          const llama_model & model,
-        const llama_hparams & hparams,
-        const llama_cparams & cparams,
+       struct llama_context & lctx,
        const llama_kv_cache & kv,
          struct ggml_cgraph * graph,
          struct ggml_tensor * wo,
@@ -8214,6 +8328,8 @@ static struct ggml_tensor * llm_build_kv(
                     float     kq_scale,
          const llm_build_cb & cb,
                     int       il) {
+    const llama_hparams & hparams = lctx.model.hparams;
+    const llama_cparams & cparams = lctx.cparams;
 
     // these nodes are added to the graph together so that they are not reordered
     // by doing so, the number of splits in the graph is reduced
@@ -8225,7 +8341,7 @@ static struct ggml_tensor * llm_build_kv(
 
     struct ggml_tensor * cur;
 
-    cur  = llm_build_kqv(ctx, model, hparams, cparams, kv, graph, wo, wo_b,
+    cur  = llm_build_kqv(ctx, lctx, kv, graph, wo, wo_b,
             q_cur, kq_mask, n_tokens, n_kv, kq_scale, cb, il);
     cb(cur, "kqv_out", il);
 
@@ -8687,21 +8803,21 @@ struct llm_build_context {
             // self-attention
             {
                 // compute Q and K and RoPE them
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
                 if (model.layers[il].bq) {
                     Qcur = ggml_add(ctx0, Qcur, model.layers[il].bq);
                     cb(Qcur, "Qcur", il);
                 }
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
                 if (model.layers[il].bk) {
                     Kcur = ggml_add(ctx0, Kcur, model.layers[il].bk);
                     cb(Kcur, "Kcur", il);
                 }
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
                 if (model.layers[il].bv) {
                     Vcur = ggml_add(ctx0, Vcur, model.layers[il].bv);
@@ -8722,7 +8838,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, model.layers[il].bo,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -8745,7 +8861,7 @@ struct llm_build_context {
                         LLM_NORM_RMS, cb, il);
                 cb(cur, "ffn_norm", il);
 
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,
                         model.layers[il].ffn_gate, model.layers[il].ffn_gate_b, NULL,
                         model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,
@@ -8759,7 +8875,7 @@ struct llm_build_context {
                         LLM_NORM_RMS, cb, il);
                 cb(cur, "ffn_norm", il);
 
-                cur = llm_build_moe_ffn(ctx0, cur,
+                cur = llm_build_moe_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_gate_inp,
                         model.layers[il].ffn_up_exps,
                         model.layers[il].ffn_gate_exps,
@@ -8789,7 +8905,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -8825,13 +8941,13 @@ struct llm_build_context {
 
             // self-attention
             {
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
 
                 switch (model.type) {
@@ -8857,7 +8973,7 @@ struct llm_build_context {
                 cb(Qcur, "Qcur", il);
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, NULL,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -8879,7 +8995,7 @@ struct llm_build_context {
                         LLM_NORM_RMS, cb, il);
                 cb(cur, "ffn_norm", il);
 
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   NULL, NULL,
                         model.layers[il].ffn_gate, NULL, NULL,
                         model.layers[il].ffn_down, NULL, NULL,
@@ -8904,7 +9020,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -8940,13 +9056,13 @@ struct llm_build_context {
 
             // self-attention
             {
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
 
                 Qcur = ggml_rope_ext(
@@ -8962,7 +9078,7 @@ struct llm_build_context {
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Kcur, "Kcur", il);
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, NULL,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -8984,7 +9100,7 @@ struct llm_build_context {
                         LLM_NORM_RMS, cb, il);
                 cb(cur, "ffn_norm", il);
 
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   NULL, NULL,
                         model.layers[il].ffn_gate, NULL, NULL,
                         model.layers[il].ffn_down, NULL, NULL,
@@ -9007,7 +9123,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -9056,7 +9172,7 @@ struct llm_build_context {
                     cur = attn_norm;
                 }
 
-                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
+                cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wqkv, cur);
                 cb(cur, "wqkv", il);
 
                 struct ggml_tensor * Qcur = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, n_embd,     n_tokens, cur->nb[1], 0*sizeof(float)*(n_embd)));
@@ -9083,7 +9199,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, NULL,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -9100,7 +9216,7 @@ struct llm_build_context {
 
             // feed forward
             {
-                cur = llm_build_ffn(ctx0, attn_norm, // !! use the attn norm, not the result
+                cur = llm_build_ffn(ctx0, lctx, attn_norm, // !! use the attn norm, not the result
                         model.layers[il].ffn_up,   NULL, NULL,
                         NULL,                      NULL, NULL,
                         model.layers[il].ffn_down, NULL, NULL,
@@ -9127,7 +9243,7 @@ struct llm_build_context {
                 LLM_NORM, cb, -1);
         cb(cur, "result_norm", -1);
 
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -9172,21 +9288,21 @@ struct llm_build_context {
             // self-attention
             {
                 // compute Q and K and RoPE them
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
                 if (model.layers[il].bq) {
                     Qcur = ggml_add(ctx0, Qcur, model.layers[il].bq);
                     cb(Qcur, "Qcur", il);
                 }
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
                 if (model.layers[il].bk) {
                     Kcur = ggml_add(ctx0, Kcur, model.layers[il].bk);
                     cb(Kcur, "Kcur", il);
                 }
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
                 if (model.layers[il].bv) {
                     Vcur = ggml_add(ctx0, Vcur, model.layers[il].bv);
@@ -9207,7 +9323,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, model.layers[il].bo,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f, cb, il);
             }
@@ -9239,7 +9355,7 @@ struct llm_build_context {
                     LLM_NORM_RMS, cb, il);
             cb(cur, "ffn_norm", il);
 
-            cur = llm_build_moe_ffn(ctx0, cur,
+            cur = llm_build_moe_ffn(ctx0, lctx, cur,
                     model.layers[il].ffn_gate_inp,
                     model.layers[il].ffn_up_exps,
                     model.layers[il].ffn_gate_exps,
@@ -9278,7 +9394,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
 
         // Grok
         // multiply logits by output_multiplier_scale of 0.5773502691896257
@@ -9329,7 +9445,7 @@ struct llm_build_context {
                 struct ggml_tensor * Kcur = nullptr;
                 struct ggml_tensor * Vcur = nullptr;
 
-                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
+                cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wqkv, cur);
                 cb(cur, "wqkv", il);
 
                 cur = ggml_clamp(ctx0, cur, -hparams.f_clamp_kqv, hparams.f_clamp_kqv);
@@ -9357,7 +9473,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, NULL,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -9380,7 +9496,7 @@ struct llm_build_context {
                                  LLM_NORM, cb, il);
             cb(cur, "attn_out_norm", il);
 
-            cur = llm_build_moe_ffn(ctx0, cur,
+            cur = llm_build_moe_ffn(ctx0, lctx, cur,
                     model.layers[il].ffn_gate_inp,
                     model.layers[il].ffn_up_exps,
                     model.layers[il].ffn_gate_exps,
@@ -9409,7 +9525,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
 
         cb(cur, "result_output", -1);
 
@@ -9451,7 +9567,7 @@ struct llm_build_context {
 
             // self-attention
             {
-                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
+                cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wqkv, cur);
                 cb(cur, "wqkv", il);
 
                 cur = ggml_add(ctx0, cur, model.layers[il].bqkv);
@@ -9467,7 +9583,7 @@ struct llm_build_context {
 
                 Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, model.layers[il].bo,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -9491,7 +9607,7 @@ struct llm_build_context {
                         LLM_NORM, cb, il);
                 cb(cur, "ffn_norm", il);
 
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,
                         NULL,                      NULL,                        NULL,
                         model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,
@@ -9514,7 +9630,7 @@ struct llm_build_context {
                 LLM_NORM, cb, -1);
         cb(cur, "result_norm", -1);
 
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -9546,13 +9662,13 @@ struct llm_build_context {
 
             // self-attention
             {
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
 
                 Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens);
@@ -9561,7 +9677,7 @@ struct llm_build_context {
                 Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head,    n_tokens);
                 cb(Qcur, "Qcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, NULL,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -9583,7 +9699,7 @@ struct llm_build_context {
                         LLM_NORM_RMS, cb, il);
                 cb(cur, "ffn_norm", il);
 
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   NULL, NULL,
                         model.layers[il].ffn_gate, NULL, NULL,
                         model.layers[il].ffn_down, NULL, NULL,
@@ -9608,7 +9724,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -9660,7 +9776,7 @@ struct llm_build_context {
 
             // self-attention
             if (model.arch == LLM_ARCH_BERT || model.arch == LLM_ARCH_JINA_BERT_V2) {
-                Qcur = ggml_add(ctx0, ggml_mul_mat(ctx0, model.layers[il].wq, cur), model.layers[il].bq);
+                Qcur = ggml_add(ctx0, llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur), model.layers[il].bq);
                 cb(Qcur, "Qcur", il);
 
                 if (model.layers[il].attn_q_norm) {
@@ -9670,7 +9786,7 @@ struct llm_build_context {
                             LLM_NORM, cb, il);
                 }
 
-                Kcur = ggml_add(ctx0, ggml_mul_mat(ctx0, model.layers[il].wk, cur), model.layers[il].bk);
+                Kcur = ggml_add(ctx0, llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur), model.layers[il].bk);
                 cb(Kcur, "Kcur", il);
 
                 if (model.layers[il].attn_k_norm) {
@@ -9679,14 +9795,14 @@ struct llm_build_context {
                             model.layers[il].attn_k_norm_b,
                             LLM_NORM, cb, il);
                 }
-                Vcur = ggml_add(ctx0, ggml_mul_mat(ctx0, model.layers[il].wv, cur), model.layers[il].bv);
+                Vcur = ggml_add(ctx0, llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur), model.layers[il].bv);
                 cb(Vcur, "Vcur", il);
 
                 Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head,    n_tokens);
                 Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens);
             } else {
                 // compute Q and K and RoPE them
-                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
+                cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wqkv, cur);
                 cb(cur, "wqkv", il);
 
                 Qcur = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, n_embd,     n_tokens, cur->nb[1], 0*sizeof(float)*(n_embd)));
@@ -9735,7 +9851,7 @@ struct llm_build_context {
 
             ggml_build_forward_expand(gf, cur);
 
-            cur = ggml_mul_mat(ctx0, model.layers[il].wo, cur);
+            cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wo, cur);
             if (model.layers[il].bo) {
                 cb(cur, "kqv_wo", il);
             }
@@ -9768,21 +9884,21 @@ struct llm_build_context {
 
             // feed-forward network
             if (model.arch == LLM_ARCH_BERT) {
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,
                         NULL,                      NULL,                        NULL,
                         model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,
                         NULL,
                         LLM_FFN_GELU, LLM_FFN_SEQ, cb, il);
             } else if (model.arch == LLM_ARCH_JINA_BERT_V2) {
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   NULL,                        NULL,
                         model.layers[il].ffn_gate, NULL,                        NULL,
                         model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,
                         NULL,
                         LLM_FFN_GELU, LLM_FFN_PAR, cb, il);
             } else {
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   NULL, NULL,
                         model.layers[il].ffn_gate, NULL, NULL,
                         model.layers[il].ffn_down, NULL, NULL,
@@ -9840,7 +9956,7 @@ struct llm_build_context {
 
             // self-attention
             {
-                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
+                cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wqkv, cur);
                 cb(cur, "wqkv", il);
 
                 cur = ggml_add(ctx0, cur, model.layers[il].bqkv);
@@ -9856,7 +9972,7 @@ struct llm_build_context {
 
                 Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, model.layers[il].bo,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -9880,7 +9996,7 @@ struct llm_build_context {
                         LLM_NORM, cb, il);
                 cb(cur, "ffn_norm", il);
 
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,
                         NULL,                      NULL,                        NULL,
                         model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,
@@ -9903,7 +10019,7 @@ struct llm_build_context {
                 LLM_NORM, cb, -1);
         cb(cur, "result_norm", -1);
 
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -9950,7 +10066,7 @@ struct llm_build_context {
             {
                 cur = attn_norm;
 
-                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
+                cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wqkv, cur);
                 cb(cur, "wqkv", il);
 
                 if (model.layers[il].bqkv){
@@ -9988,13 +10104,13 @@ struct llm_build_context {
                     Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head,    n_tokens);
                     Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens);
 
-                    cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                    cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                             model.layers[il].wo, model.layers[il].bo,
                             Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
                 } else {
                     Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens);
 
-                    cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                    cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                             model.layers[il].wo, model.layers[il].bo,
                             Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
                 }
@@ -10018,7 +10134,7 @@ struct llm_build_context {
                         model.layers[il].ffn_norm_b,
                         LLM_NORM, cb, il);
                 cb(cur, "ffn_norm", il);
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,
                         NULL,                      NULL,                        NULL,
                         model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,
@@ -10043,7 +10159,7 @@ struct llm_build_context {
                 LLM_NORM, cb, -1);
         cb(cur, "result_norm", -1);
 
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -10083,21 +10199,21 @@ struct llm_build_context {
             // self-attention
             {
                 // compute Q and K and RoPE them
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
                 if (model.layers[il].bq) {
                     Qcur = ggml_add(ctx0, Qcur, model.layers[il].bq);
                     cb(Qcur, "Qcur", il);
                 }
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
                 if (model.layers[il].bk) {
                     Kcur = ggml_add(ctx0, Kcur, model.layers[il].bk);
                     cb(Kcur, "Kcur", il);
                 }
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
                 if (model.layers[il].bv) {
                     Vcur = ggml_add(ctx0, Vcur, model.layers[il].bv);
@@ -10139,7 +10255,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, NULL,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -10167,7 +10283,7 @@ struct llm_build_context {
                     // parallel residual
                     cur = inpSA;
                 }
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   NULL, NULL,
                         model.layers[il].ffn_gate, NULL, NULL,
                         model.layers[il].ffn_down, NULL, NULL,
@@ -10193,7 +10309,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -10228,7 +10344,7 @@ struct llm_build_context {
 
             // self-attention
             {
-                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
+                cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wqkv, cur);
                 cb(cur, "wqkv", il);
 
                 cur = ggml_add(ctx0, cur, model.layers[il].bqkv);
@@ -10258,7 +10374,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, NULL,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -10280,7 +10396,7 @@ struct llm_build_context {
                         LLM_NORM_RMS, cb, il);
                 cb(cur, "ffn_norm", il);
 
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   NULL, NULL,
                         model.layers[il].ffn_gate, NULL, NULL,
                         model.layers[il].ffn_down, NULL, NULL,
@@ -10305,7 +10421,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -10343,17 +10459,17 @@ struct llm_build_context {
             // self-attention
             {
                 // compute Q and K and RoPE them
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
                 Qcur = ggml_add(ctx0, Qcur, model.layers[il].bq);
                 cb(Qcur, "Qcur", il);
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
                 Kcur = ggml_add(ctx0, Kcur, model.layers[il].bk);
                 cb(Kcur, "Kcur", il);
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
                 Vcur = ggml_add(ctx0, Vcur, model.layers[il].bv);
                 cb(Vcur, "Vcur", il);
@@ -10372,7 +10488,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, model.layers[il].bo,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -10393,7 +10509,7 @@ struct llm_build_context {
                     LLM_NORM_RMS, cb, il);
             cb(cur, "ffn_norm", il);
 
-            cur = llm_build_ffn(ctx0, cur,
+            cur = llm_build_ffn(ctx0, lctx, cur,
                     model.layers[il].ffn_up,   NULL, NULL,
                     model.layers[il].ffn_gate, NULL, NULL,
                     model.layers[il].ffn_down, NULL, NULL,
@@ -10417,7 +10533,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -10458,17 +10574,17 @@ struct llm_build_context {
             // self_attention
             {
                 // compute Q and K and RoPE them
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
                 Qcur = ggml_add(ctx0, Qcur, model.layers[il].bq);
                 cb(Qcur, "Qcur", il);
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
                 Kcur = ggml_add(ctx0, Kcur, model.layers[il].bk);
                 cb(Kcur, "Kcur", il);
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
                 Vcur = ggml_add(ctx0, Vcur, model.layers[il].bv);
                 cb(Vcur, "Vcur", il);
@@ -10487,7 +10603,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, model.layers[il].bo,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -10510,7 +10626,7 @@ struct llm_build_context {
             cb(cur, "ffn_norm", il);
 
             ggml_tensor * moe_out =
-                    llm_build_moe_ffn(ctx0, cur,
+                    llm_build_moe_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_gate_inp,
                         model.layers[il].ffn_up_exps,
                         model.layers[il].ffn_gate_exps,
@@ -10523,14 +10639,14 @@ struct llm_build_context {
 
             // FFN shared expert
             {
-                ggml_tensor * cur_gate_inp = ggml_mul_mat(ctx0, model.layers[il].ffn_gate_inp_shexp, cur);
+                ggml_tensor * cur_gate_inp = llm_build_lora_mm(lctx, ctx0, model.layers[il].ffn_gate_inp_shexp, cur);
                 cb(cur_gate_inp, "ffn_shexp_gate_inp", il);
 
                 // sigmoid
                 ggml_tensor * cur_gate = ggml_div(ctx0, ggml_silu(ctx0, cur_gate_inp), cur_gate_inp);
                 cb(cur_gate, "ffn_shexp_gate", il);
 
-                ggml_tensor * cur_ffn = llm_build_ffn(ctx0, cur,
+                ggml_tensor * cur_ffn = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up_shexp,   NULL, NULL,
                         model.layers[il].ffn_gate_shexp, NULL, NULL,
                         model.layers[il].ffn_down_shexp, NULL, NULL,
@@ -10563,7 +10679,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -10605,7 +10721,7 @@ struct llm_build_context {
                 struct ggml_tensor * Vcur = nullptr;
 
                 if (model.layers[il].wqkv) {
-                    cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, attn_norm_output);
+                    cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wqkv, attn_norm_output);
                     cb(cur, "wqkv", il);
 
                     cur = ggml_add(ctx0, cur, model.layers[il].bqkv);
@@ -10615,9 +10731,9 @@ struct llm_build_context {
                     Kcur = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, n_embd_gqa, n_tokens, cur->nb[1], 1*sizeof(float)*(n_embd)));
                     Vcur = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, n_embd_gqa, n_tokens, cur->nb[1], 1*sizeof(float)*(n_embd + n_embd_gqa)));
                 } else {
-                    Qcur = ggml_add(ctx0, ggml_mul_mat(ctx0, model.layers[il].wq, attn_norm_output), model.layers[il].bq);
-                    Kcur = ggml_add(ctx0, ggml_mul_mat(ctx0, model.layers[il].wk, attn_norm_output), model.layers[il].bk);
-                    Vcur = ggml_add(ctx0, ggml_mul_mat(ctx0, model.layers[il].wv, attn_norm_output), model.layers[il].bv);
+                    Qcur = ggml_add(ctx0, llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, attn_norm_output), model.layers[il].bq);
+                    Kcur = ggml_add(ctx0, llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, attn_norm_output), model.layers[il].bk);
+                    Vcur = ggml_add(ctx0, llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, attn_norm_output), model.layers[il].bv);
                 }
 
                 cb(Qcur, "Qcur", il);
@@ -10644,7 +10760,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, model.layers[il].bo,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f, cb, il);
             }
@@ -10659,7 +10775,7 @@ struct llm_build_context {
 
             // FF
             {
-                ffn_output = llm_build_ffn(ctx0, attn_norm_output,
+                ffn_output = llm_build_ffn(ctx0, lctx, attn_norm_output,
                         model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,
                         NULL,                      NULL,                        NULL,
                         model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,
@@ -10683,7 +10799,7 @@ struct llm_build_context {
                 LLM_NORM, cb, -1);
         cb(cur, "result_norm", -1);
 
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output_no_bias", -1);
 
         cur = ggml_add(ctx0, cur, model.output_b);
@@ -10729,7 +10845,7 @@ struct llm_build_context {
                 struct ggml_tensor * Vcur = nullptr;
 
                 if (model.layers[il].wqkv) {
-                    cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, attn_norm_output);
+                    cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wqkv, attn_norm_output);
                     cb(cur, "wqkv", il);
 
                     Qcur = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, n_embd,     n_tokens, cur->nb[1], 0 * sizeof(float) * (n_embd)));
@@ -10737,9 +10853,9 @@ struct llm_build_context {
                     Vcur = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, n_embd_gqa, n_tokens, cur->nb[1], 1 * sizeof(float) * (n_embd + n_embd_gqa)));
                 }
                 else {
-                    Qcur = ggml_add(ctx0, ggml_mul_mat(ctx0, model.layers[il].wq, attn_norm_output), model.layers[il].bq);
-                    Kcur = ggml_add(ctx0, ggml_mul_mat(ctx0, model.layers[il].wk, attn_norm_output), model.layers[il].bk);
-                    Vcur = ggml_add(ctx0, ggml_mul_mat(ctx0, model.layers[il].wv, attn_norm_output), model.layers[il].bv);
+                    Qcur = ggml_add(ctx0, llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, attn_norm_output), model.layers[il].bq);
+                    Kcur = ggml_add(ctx0, llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, attn_norm_output), model.layers[il].bk);
+                    Vcur = ggml_add(ctx0, llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, attn_norm_output), model.layers[il].bv);
                 }
 
                 cb(Qcur, "Qcur", il);
@@ -10764,7 +10880,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, model.layers[il].bo,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f, cb, il);
             }
@@ -10788,7 +10904,7 @@ struct llm_build_context {
             // special-case: the up and gate tensors are merged into a single tensor
             // TOOD: support into llm_build_ffn
             {
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   NULL, NULL,
                         NULL,                      NULL, NULL,
                         model.layers[il].ffn_down, NULL, NULL,
@@ -10811,7 +10927,7 @@ struct llm_build_context {
             LLM_NORM_RMS, cb, -1);
         cb(cur, "result_norm", -1);
 
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -10851,13 +10967,13 @@ struct llm_build_context {
             // self-attention
             {
                 // compute Q and K and RoPE them
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
 
                 Qcur = ggml_rope_ext(
@@ -10872,7 +10988,7 @@ struct llm_build_context {
                         ext_factor, attn_factor, beta_fast, beta_slow);
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, NULL,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -10890,7 +11006,7 @@ struct llm_build_context {
 
             // feed-forward network
             {
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   NULL, NULL,
                         model.layers[il].ffn_gate, NULL, NULL,
                         model.layers[il].ffn_down, NULL, NULL,
@@ -10916,7 +11032,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -10958,7 +11074,7 @@ struct llm_build_context {
 
             // self-attention
             {
-                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
+                cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wqkv, cur);
                 cb(cur, "wqkv", il);
 
                 cur = ggml_add(ctx0, cur, model.layers[il].bqkv);
@@ -10974,7 +11090,7 @@ struct llm_build_context {
 
                 Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, model.layers[il].bo,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -10998,7 +11114,7 @@ struct llm_build_context {
                         LLM_NORM, cb, il);
                 cb(cur, "ffn_norm", il);
 
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,
                         NULL,                      NULL,                        NULL,
                         model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,
@@ -11021,7 +11137,7 @@ struct llm_build_context {
                 LLM_NORM, cb, -1);
         cb(cur, "result_norm", -1);
 
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -11057,7 +11173,7 @@ struct llm_build_context {
 
             // self-attention
             {
-                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
+                cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wqkv, cur);
                 cb(cur, "wqkv", il);
 
                 cur = ggml_add(ctx0, cur, model.layers[il].bqkv);
@@ -11085,7 +11201,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, model.layers[il].bo,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -11109,7 +11225,7 @@ struct llm_build_context {
                         LLM_NORM, cb, il);
                 cb(cur, "ffn_norm", il);
 
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,
                         NULL,                      NULL,                        NULL,
                         model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,
@@ -11132,7 +11248,7 @@ struct llm_build_context {
                 LLM_NORM, cb, -1);
         cb(cur, "result_norm", -1);
 
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -11170,21 +11286,21 @@ struct llm_build_context {
             // self-attention
             {
                 // compute Q and K and RoPE them
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
                 // if (model.layers[il].bq) {
                 //     Qcur = ggml_add(ctx0, Qcur, model.layers[il].bq);
                 //     cb(Qcur, "Qcur", il);
                 // }
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
                 // if (model.layers[il].bk) {
                 //     Kcur = ggml_add(ctx0, Kcur, model.layers[il].bk);
                 //     cb(Kcur, "Kcur", il);
                 // }
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
                 // if (model.layers[il].bv) {
                 //     Vcur = ggml_add(ctx0, Vcur, model.layers[il].bv);
@@ -11205,7 +11321,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, NULL,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -11226,7 +11342,7 @@ struct llm_build_context {
                     LLM_NORM, cb, il);
             cb(cur, "ffn_norm", il);
 
-            cur = llm_build_ffn(ctx0, cur,
+            cur = llm_build_ffn(ctx0, lctx, cur,
                     model.layers[il].ffn_up,   NULL, NULL,
                     model.layers[il].ffn_gate, NULL, NULL,
                     model.layers[il].ffn_down, NULL, NULL,
@@ -11250,7 +11366,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -11288,21 +11404,21 @@ struct llm_build_context {
             // self-attention
             {
                 // compute Q and K and RoPE them
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
                 if (model.layers[il].bq) {
                     Qcur = ggml_add(ctx0, Qcur, model.layers[il].bq);
                     cb(Qcur, "Qcur", il);
                 }
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
                 if (model.layers[il].bk) {
                     Kcur = ggml_add(ctx0, Kcur, model.layers[il].bk);
                     cb(Kcur, "Kcur", il);
                 }
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
                 if (model.layers[il].bv) {
                     Vcur = ggml_add(ctx0, Vcur, model.layers[il].bv);
@@ -11323,7 +11439,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, model.layers[il].bo,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -11344,7 +11460,7 @@ struct llm_build_context {
                     LLM_NORM_RMS, cb, il);
             cb(cur, "ffn_norm", il);
 
-            cur = llm_build_ffn(ctx0, cur,
+            cur = llm_build_ffn(ctx0, lctx, cur,
                     model.layers[il].ffn_up,   NULL, NULL,
                     model.layers[il].ffn_gate, NULL, NULL,
                     model.layers[il].ffn_down, NULL, NULL,
@@ -11368,7 +11484,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -11419,21 +11535,21 @@ struct llm_build_context {
             // self-attention
             {
                 // compute Q and K and RoPE them
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
                 if (model.layers[il].bq) {
                     Qcur = ggml_add(ctx0, Qcur, model.layers[il].bq);
                     cb(Qcur, "Qcur", il);
                 }
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
                 if (model.layers[il].bk) {
                     Kcur = ggml_add(ctx0, Kcur, model.layers[il].bk);
                     cb(Kcur, "Kcur", il);
                 }
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
                 if (model.layers[il].bv) {
                     Vcur = ggml_add(ctx0, Vcur, model.layers[il].bv);
@@ -11454,7 +11570,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, model.layers[il].bo,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -11481,7 +11597,7 @@ struct llm_build_context {
                         LLM_NORM_RMS, cb, il);
                 cb(cur, "ffn_norm", il);
 
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   NULL, NULL,
                         model.layers[il].ffn_gate, NULL, NULL,
                         model.layers[il].ffn_down, NULL, NULL,
@@ -11515,7 +11631,7 @@ struct llm_build_context {
         cb(cur, "lmhead_scaling", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -11552,13 +11668,13 @@ struct llm_build_context {
             // self-attention
             {
                 // compute Q and K and RoPE them
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
 
                 Qcur = ggml_rope_ext(
@@ -11576,7 +11692,7 @@ struct llm_build_context {
                         ext_factor, attn_factor, beta_fast, beta_slow);
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, NULL,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f, cb, il);
             }
@@ -11598,7 +11714,7 @@ struct llm_build_context {
 
             // feed-forward network
             {
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   NULL, NULL,
                         model.layers[il].ffn_gate, NULL, NULL,
                         model.layers[il].ffn_down, NULL, NULL,
@@ -11623,7 +11739,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -11665,13 +11781,13 @@ struct llm_build_context {
             // self-attention
             {
                 // compute Q and K and RoPE them
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
 
                 Qcur = ggml_rope_ext(
@@ -11694,7 +11810,7 @@ struct llm_build_context {
                         ext_factor, attn_factor, beta_fast, beta_slow);
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, NULL,
                         Kcur, Vcur, Qcur, KQ_mask_l, n_tokens, kv_head, n_kv, 1.0f, cb, il);
             }
@@ -11721,7 +11837,7 @@ struct llm_build_context {
 
             // feed-forward network
             {
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   NULL, NULL,
                         model.layers[il].ffn_gate, NULL, NULL,
                         model.layers[il].ffn_down, NULL, NULL,
@@ -11751,7 +11867,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
 
         // final logit soft-capping
         cur = ggml_scale(ctx0, cur, 1.0f / hparams.f_final_logit_softcapping);
@@ -11796,21 +11912,21 @@ struct llm_build_context {
             // self-attention
             {
                 // compute Q and K and RoPE them
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
                 if (model.layers[il].bq) {
                     Qcur = ggml_add(ctx0, Qcur, model.layers[il].bq);
                     cb(Qcur, "Qcur", il);
                 }
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
                 if (model.layers[il].bk) {
                     Kcur = ggml_add(ctx0, Kcur, model.layers[il].bk);
                     cb(Kcur, "Kcur", il);
                 }
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
                 if (model.layers[il].bv) {
                     Vcur = ggml_add(ctx0, Vcur, model.layers[il].bv);
@@ -11831,7 +11947,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, model.layers[il].bo,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -11853,7 +11969,7 @@ struct llm_build_context {
                     LLM_NORM, cb, il);
             cb(cur, "ffn_norm", il);
 
-            cur = llm_build_ffn(ctx0, cur,
+            cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,
                         NULL,                      NULL,                        NULL,
                         model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,
@@ -11877,7 +11993,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -11929,7 +12045,7 @@ struct llm_build_context {
             cb(cur, "attn_norm", il);
 
             // {n_embd, 2*d_inner} * {n_embd, n_tokens} => {2*d_inner, n_tokens}
-            struct ggml_tensor * xz = ggml_mul_mat(ctx0, model.layers[il].ssm_in, cur);
+            struct ggml_tensor * xz = llm_build_lora_mm(lctx, ctx0, model.layers[il].ssm_in, cur);
             // split the above in two
             // => {d_inner, n_tokens}
             struct ggml_tensor * x = ggml_view_2d(ctx0, xz, d_inner, xz->ne[1], xz->nb[1], 0);
@@ -11968,14 +12084,14 @@ struct llm_build_context {
             // ssm
             {
                 // {d_inner, dt_rank + 2*d_state} * {d_inner, n_tokens} => {dt_rank + 2*d_state, n_tokens}
-                struct ggml_tensor * x_db = ggml_mul_mat(ctx0, model.layers[il].ssm_x, x);
+                struct ggml_tensor * x_db = llm_build_lora_mm(lctx, ctx0, model.layers[il].ssm_x, x);
                 // split
                 struct ggml_tensor * dt = ggml_view_2d(ctx0, x_db, dt_rank, n_tokens, x_db->nb[1], 0);
                 struct ggml_tensor * B  = ggml_view_2d(ctx0, x_db, d_state, n_tokens, x_db->nb[1], ggml_element_size(x_db)*dt_rank);
                 struct ggml_tensor * C  = ggml_view_2d(ctx0, x_db, d_state, n_tokens, x_db->nb[1], ggml_element_size(x_db)*(dt_rank+d_state));
 
                 // {dt_rank, d_inner} * {dt_rank, n_tokens} => {d_inner, n_tokens}
-                dt = ggml_mul_mat(ctx0, model.layers[il].ssm_dt, dt);
+                dt = llm_build_lora_mm(lctx, ctx0, model.layers[il].ssm_dt, dt);
                 dt = ggml_add(ctx0, dt, model.layers[il].ssm_dt_b);
 
                 // Custom operator to optimize the parallel associative scan
@@ -12006,7 +12122,7 @@ struct llm_build_context {
                 y = ggml_mul(ctx0, y, ggml_silu(ctx0, z));
 
                 // {d_inner, n_embd} * {d_inner, n_tokens} => {n_embd, n_tokens}
-                cur = ggml_mul_mat(ctx0, model.layers[il].ssm_out, y);
+                cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].ssm_out, y);
             }
 
             // residual
@@ -12025,7 +12141,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -12064,21 +12180,21 @@ struct llm_build_context {
             // self-attention
             {
                 // compute Q and K and RoPE them
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
                 if (model.layers[il].bq) {
                     Qcur = ggml_add(ctx0, Qcur, model.layers[il].bq);
                     cb(Qcur, "Qcur", il);
                 }
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
                 if (model.layers[il].bk) {
                     Kcur = ggml_add(ctx0, Kcur, model.layers[il].bk);
                     cb(Kcur, "Kcur", il);
                 }
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
                 if (model.layers[il].bv) {
                     Vcur = ggml_add(ctx0, Vcur, model.layers[il].bv);
@@ -12124,7 +12240,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, model.layers[il].bo,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -12141,7 +12257,7 @@ struct llm_build_context {
 
             // feed-forward network
             {
-                cur = llm_build_ffn(ctx0, ffn_inp,
+                cur = llm_build_ffn(ctx0, lctx, ffn_inp,
                         model.layers[il].ffn_up,   NULL, NULL,
                         model.layers[il].ffn_gate, NULL, NULL,
                         model.layers[il].ffn_down, NULL, NULL,
@@ -12168,7 +12284,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
 
         if (f_logit_scale) {
             cur = ggml_scale(ctx0, cur, f_logit_scale);
@@ -12221,21 +12337,21 @@ struct llm_build_context {
             // self-attention
             {
                 // compute Q and K and RoPE them
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
                 if (hparams.f_clamp_kqv > 0.0f) {
                     Qcur = ggml_clamp(ctx0, Qcur, -hparams.f_clamp_kqv, hparams.f_clamp_kqv);
                     cb(Qcur, "Qcur", il);
                 }
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
                 if (hparams.f_clamp_kqv > 0.0f) {
                     Kcur = ggml_clamp(ctx0, Kcur, -hparams.f_clamp_kqv, hparams.f_clamp_kqv);
                     cb(Kcur, "Kcur", il);
                 }
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
                 if (hparams.f_clamp_kqv > 0.0f) {
                     Vcur = ggml_clamp(ctx0, Vcur, -hparams.f_clamp_kqv, hparams.f_clamp_kqv);
@@ -12256,7 +12372,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, nullptr,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -12278,7 +12394,7 @@ struct llm_build_context {
                     LLM_NORM, cb, il);
             cb(cur, "ffn_norm", il);
 
-            cur = llm_build_ffn(ctx0, cur,
+            cur = llm_build_ffn(ctx0, lctx, cur,
                     model.layers[il].ffn_up,   NULL, NULL,
                     model.layers[il].ffn_gate, NULL, NULL,
                     model.layers[il].ffn_down, NULL, NULL,
@@ -12304,7 +12420,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -12344,7 +12460,7 @@ struct llm_build_context {
 
             // self-attention
             {
-                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
+                cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wqkv, cur);
                 cb(cur, "wqkv", il);
 
                 cur = ggml_reshape_3d(ctx0, cur, n_embd_head_k, n_head_qkv, n_tokens);
@@ -12383,7 +12499,7 @@ struct llm_build_context {
                 Vcur = ggml_reshape_2d(ctx0, Vcur, n_embd_head * n_head_kv, n_tokens);
                 cb(Qcur, "Vcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, NULL,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -12405,7 +12521,7 @@ struct llm_build_context {
                         LLM_NORM_RMS, cb, il);
                 cb(cur, "ffn_norm", il);
 
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   NULL, NULL,
                         model.layers[il].ffn_gate, NULL, NULL,
                         model.layers[il].ffn_down, NULL, NULL,
@@ -12429,7 +12545,7 @@ struct llm_build_context {
                 LLM_NORM_RMS, cb, -1);
         cb(cur, "result_norm", -1);
 
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -12464,7 +12580,7 @@ struct llm_build_context {
 
             // self-attention
             {
-                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
+                cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wqkv, cur);
                 cb(cur, "wqkv", il);
 
                 cur = ggml_add(ctx0, cur, model.layers[il].bqkv);
@@ -12492,7 +12608,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, model.layers[il].bo,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -12517,7 +12633,7 @@ struct llm_build_context {
                         LLM_NORM, cb, il);
                 cb(cur, "ffn_norm", il);
 
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,
                         NULL,                      NULL,                        NULL,
                         model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,
@@ -12548,7 +12664,7 @@ struct llm_build_context {
                         LLM_NORM, cb, il);
                 cb(cur, "ffn_norm", il);
 
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,
                         NULL,                      NULL,                        NULL,
                         model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,
@@ -12571,7 +12687,7 @@ struct llm_build_context {
                 LLM_NORM, cb, -1);
         cb(cur, "result_norm", -1);
 
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -12612,13 +12728,13 @@ struct llm_build_context {
             // self-attention
             {
                 // compute Q and K and RoPE them
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 cb(Qcur, "Qcur", il);
 
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 cb(Kcur, "Kcur", il);
 
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
 
                 Qcur = ggml_rope_ext(
@@ -12635,7 +12751,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, NULL,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
             }
@@ -12657,7 +12773,7 @@ struct llm_build_context {
                     LLM_NORM_RMS, cb, il);
             cb(cur, "ffn_norm", il);
 
-            cur = llm_build_ffn(ctx0, cur,
+            cur = llm_build_ffn(ctx0, lctx, cur,
                     model.layers[il].ffn_up,   NULL, NULL,
                     model.layers[il].ffn_gate, NULL, NULL,
                     model.layers[il].ffn_down, NULL, NULL,
@@ -12674,7 +12790,7 @@ struct llm_build_context {
                     LLM_NORM_RMS, cb, il);
             cb(cur, "ffn_norm_exps", il);
 
-            cur = llm_build_moe_ffn(ctx0, cur,
+            cur = llm_build_moe_ffn(ctx0, lctx, cur,
                     model.layers[il].ffn_gate_inp,
                     model.layers[il].ffn_up_exps,
                     model.layers[il].ffn_gate_exps,
@@ -12703,7 +12819,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -12857,7 +12973,7 @@ struct llm_build_context {
                 struct ggml_tensor * k_states = ggml_concat(ctx0, k_nope, ggml_repeat(ctx0, k_pe, q_pe), 0);
                 cb(k_states, "k_states", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, NULL,
                         k_states, v_states, q_states, KQ_mask, n_tokens, kv_head, n_kv, kq_scale, cb, il);
             }
@@ -12879,7 +12995,7 @@ struct llm_build_context {
             cb(cur, "ffn_norm", il);
 
             if ((uint32_t) il < hparams.n_layer_dense_lead) {
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   NULL, NULL,
                         model.layers[il].ffn_gate, NULL, NULL,
                         model.layers[il].ffn_down, NULL, NULL,
@@ -12889,7 +13005,7 @@ struct llm_build_context {
             } else {
                 // MoE branch
                 ggml_tensor * moe_out =
-                        llm_build_moe_ffn(ctx0, cur,
+                        llm_build_moe_ffn(ctx0, lctx, cur,
                             model.layers[il].ffn_gate_inp,
                             model.layers[il].ffn_up_exps,
                             model.layers[il].ffn_gate_exps,
@@ -12902,7 +13018,7 @@ struct llm_build_context {
 
                 // FFN shared expert
                 {
-                    ggml_tensor * ffn_shexp = llm_build_ffn(ctx0, cur,
+                    ggml_tensor * ffn_shexp = llm_build_ffn(ctx0, lctx, cur,
                             model.layers[il].ffn_up_shexp,   NULL, NULL,
                             model.layers[il].ffn_gate_shexp, NULL, NULL,
                             model.layers[il].ffn_down_shexp, NULL, NULL,
@@ -12967,7 +13083,7 @@ struct llm_build_context {
             // self-attention
             {
                 // compute Q and K and RoPE them
-                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                struct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);
                 Qcur = ggml_mul(ctx0, Qcur, model.layers[il].wq_scale);
                 cb(Qcur, "Qcur", il);
                 if (model.layers[il].bq) {
@@ -12976,7 +13092,7 @@ struct llm_build_context {
                 }
 
                 // B1.K
-                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);
                 Kcur = ggml_mul(ctx0, Kcur, model.layers[il].wk_scale);
                 cb(Kcur, "Kcur", il);
                 if (model.layers[il].bk) {
@@ -12985,7 +13101,7 @@ struct llm_build_context {
                 }
 
                 // B1.V
-                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);
                 Vcur = ggml_mul(ctx0, Vcur, model.layers[il].wv_scale);
                 cb(Vcur, "Vcur", il);
                 if (model.layers[il].bv) {
@@ -13007,7 +13123,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         NULL, NULL,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
 
@@ -13016,7 +13132,7 @@ struct llm_build_context {
                         LLM_NORM_RMS, cb, il);
                 cb(cur, "attn_sub_norm", il);
 
-                cur = ggml_mul_mat(ctx0, model.layers[il].wo, cur);
+                cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wo, cur);
                 cur = ggml_mul(ctx0, cur, model.layers[il].wo_scale);
                 if (model.layers[il].bo) {
                     cur = ggml_add(ctx0, cur, model.layers[il].bo);
@@ -13040,7 +13156,7 @@ struct llm_build_context {
                     LLM_NORM_RMS, cb, il);
             cb(cur, "ffn_norm", il);
 
-            cur = llm_build_ffn(ctx0, cur,
+            cur = llm_build_ffn(ctx0, lctx, cur,
                     model.layers[il].ffn_up,   NULL, model.layers[il].ffn_up_scale,
                     model.layers[il].ffn_gate, NULL, model.layers[il].ffn_gate_scale,
                     NULL,                      NULL, NULL,
@@ -13053,7 +13169,7 @@ struct llm_build_context {
                             LLM_NORM_RMS, cb, il);
             cb(cur, "ffn_sub_norm", il);
 
-            cur = ggml_mul_mat(ctx0, model.layers[il].ffn_down, cur);
+            cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].ffn_down, cur);
             cur = ggml_mul(ctx0, cur, model.layers[il].ffn_down_scale);
             cb(cur, "ffn_down", il);
 
@@ -13072,7 +13188,7 @@ struct llm_build_context {
         cb(cur, "result_norm", -1);
 
         // lm_head
-        cur = ggml_mul_mat(ctx0, model.tok_embd, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.tok_embd, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -13174,7 +13290,7 @@ struct llm_build_context {
                     cb(cur, "ffn_norm", il);
 
                     // T5 uses relu, flan-T5 uses gelu-gated
-                    cur = llm_build_ffn(ctx0, cur,
+                    cur = llm_build_ffn(ctx0, lctx, cur,
                             model.layers[il].ffn_up_enc,   NULL, NULL,
                             model.layers[il].ffn_gate_enc, NULL, NULL,
                             model.layers[il].ffn_down_enc, NULL, NULL,
@@ -13354,7 +13470,7 @@ struct llm_build_context {
                     cb(cur, "ffn_norm", il);
 
                     // T5 uses relu, flan-T5 uses gelu-gated
-                    cur = llm_build_ffn(ctx0, cur,
+                    cur = llm_build_ffn(ctx0, lctx, cur,
                             model.layers[il].ffn_up,   NULL, NULL,
                             model.layers[il].ffn_gate, NULL, NULL,
                             model.layers[il].ffn_down, NULL, NULL,
@@ -13420,7 +13536,7 @@ struct llm_build_context {
 
             // self-attention
             {
-                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
+                cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wqkv, cur);
                 cb(cur, "wqkv", il);
 
                 cur = ggml_add(ctx0, cur, model.layers[il].bqkv);
@@ -13436,7 +13552,7 @@ struct llm_build_context {
 
                 Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, model.layers[il].bo,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/float(n_embd_head), cb, il);
             }
@@ -13460,7 +13576,7 @@ struct llm_build_context {
                         LLM_NORM, cb, il);
                 cb(cur, "ffn_norm", il);
 
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,
                         model.layers[il].ffn_gate, model.layers[il].ffn_gate_b, NULL,
                         model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,
@@ -13479,7 +13595,7 @@ struct llm_build_context {
                 LLM_NORM, cb, -1);
         cb(cur, "result_norm", -1);
 
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
 
         cb(cur, "result_output", -1);
 
@@ -13521,7 +13637,7 @@ struct llm_build_context {
                 struct ggml_tensor * Kcur = nullptr;
                 struct ggml_tensor * Vcur = nullptr;
 
-                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
+                cur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wqkv, cur);
                 cb(cur, "wqkv", il);
 
                 cur = ggml_add(ctx0, cur, model.layers[il].bqkv);
@@ -13549,7 +13665,7 @@ struct llm_build_context {
                 );
                 cb(Kcur, "Kcur_rope", il);
 
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                cur = llm_build_kv(ctx0, lctx, kv_self, gf,
                         model.layers[il].wo, NULL,
                         Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
 
@@ -13574,7 +13690,7 @@ struct llm_build_context {
                         LLM_NORM_RMS, cb, il);
                 cb(cur, "ffn_norm", il);
 
-                cur = llm_build_ffn(ctx0, cur,
+                cur = llm_build_ffn(ctx0, lctx, cur,
                         model.layers[il].ffn_up,   NULL, NULL,
                         NULL,                      NULL, NULL,
                         model.layers[il].ffn_down, NULL, NULL,
@@ -13594,7 +13710,7 @@ struct llm_build_context {
                 LLM_NORM_RMS, cb, -1);
         cb(cur, "result_norm", -1);
 
-        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cur = llm_build_lora_mm(lctx, ctx0, model.output, cur);
         cb(cur, "result_output", -1);
 
         ggml_build_forward_expand(gf, cur);
@@ -18458,282 +18574,210 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
     }
 }
 
-static int llama_apply_lora_from_file_internal(
-    const struct llama_model & model, const char * path_lora, float scale, const char * path_base_model, int n_threads
-) {
-    LLAMA_LOG_INFO("%s: applying lora adapter from '%s' - please wait ...\n", __func__, path_lora);
-
-    const int64_t t_start_lora_us = ggml_time_us();
-
-    llama_file fin(path_lora, "rb");
-
-    // verify magic and version
-    {
-        uint32_t magic = fin.read_u32();
-        if (magic != LLAMA_FILE_MAGIC_GGLA) {
-            LLAMA_LOG_ERROR("%s: bad file magic\n", __func__);
-            return 1;
-        }
-
-        uint32_t format_version = fin.read_u32();
-        if (format_version != 1) {
-            LLAMA_LOG_ERROR("%s: unsupported file version\n", __func__ );
-            return 1;
-        }
-    }
-
-    int32_t lora_r = fin.read_u32();
-    int32_t lora_alpha = fin.read_u32();
-    float scaling = scale * (float)lora_alpha / (float)lora_r;
-
-    LLAMA_LOG_INFO("%s: r = %d, alpha = %d, scaling = %.2f\n", __func__, lora_r, lora_alpha, scaling);
+static void llama_lora_adapter_init_internal(struct llama_model * model, const char * path_lora, struct llama_lora_adapter & adapter) {
+    LLAMA_LOG_INFO("%s: loading lora adapter from '%s' ...\n", __func__, path_lora);
 
-    // load base model
-    std::unique_ptr ml;
-    if (path_base_model) {
-        LLAMA_LOG_INFO("%s: loading base model from '%s'\n", __func__, path_base_model);
-        ml.reset(new llama_model_loader(path_base_model, /*use_mmap*/ true, /*check_tensors*/ false, /*kv_overrides*/ nullptr));
-        ml->init_mappings(/*prefetch*/ false); // no prefetching
-    }
-
-    struct tensor_meta {
-        std::string name;
-        ggml_type type;
-        int32_t ne[2];
-        size_t offset;
+    ggml_context * ctx = nullptr;
+    struct gguf_init_params meta_gguf_params = {
+        /* .no_alloc = */ true,
+        /* .ctx      = */ &ctx,
     };
-    std::map tensor_meta_map;
-
-    // load all tensor meta
-    while (true) {
-        if (fin.tell() == fin.size) {
-            // eof
-            break;
-        }
-
-        int32_t n_dims;
-        int32_t name_len;
-        int32_t ftype;
-
-        fin.read_raw(&n_dims, sizeof(n_dims));
-        fin.read_raw(&name_len, sizeof(name_len));
-        fin.read_raw(&ftype, sizeof(ftype));
-
-        if (n_dims != 1 && n_dims != 2) {
-            LLAMA_LOG_ERROR("%s: unsupported tensor dimension %d\n", __func__, n_dims);
-            return 1;
-        }
+    struct gguf_context * ctx_gguf = gguf_init_from_file(path_lora, meta_gguf_params);
+    if (!ctx_gguf) {
+        throw std::runtime_error("failed to load lora adapter file from " + std::string(path_lora));
+    }
 
-        int32_t ne[2] = { 1, 1 };
-        for (int i = 0; i < n_dims; ++i) {
-            fin.read_raw(&ne[i], sizeof(ne[i]));
-        }
+    // check metadata
+    {
+        auto get_kv_str = [&](const std::string & key) -> std::string {
+            int id = gguf_find_key(ctx_gguf, key.c_str());
+            return id < 0 ? "" : std::string(gguf_get_val_str(ctx_gguf, id));
+        };
+        auto get_kv_f32 = [&](const std::string & key) -> float {
+            int id = gguf_find_key(ctx_gguf, key.c_str());
+            return id < 0 ? 0.0f : gguf_get_val_f32(ctx_gguf, id);
+        };
+        LLM_KV llm_kv = LLM_KV(LLM_ARCH_UNKNOWN);
 
-        std::string name;
-        {
-            GGML_ASSERT(name_len < GGML_MAX_NAME);
-            char buf[GGML_MAX_NAME];
-            fin.read_raw(buf, name_len);
-            name = std::string(buf, name_len);
+        auto general_type = get_kv_str(llm_kv(LLM_KV_GENERAL_TYPE));
+        if (general_type != "adapter") {
+            gguf_free(ctx_gguf);
+            throw std::runtime_error("expect general.type to be 'adapter', but got: " + general_type);
         }
 
-        // check for lora suffix
-        std::string lora_suffix;
-        if (name.length() > 6) {
-            lora_suffix = name.substr(name.length() - 6);
-        }
-        if (lora_suffix != ".loraA" && lora_suffix != ".loraB") {
-            LLAMA_LOG_ERROR("%s: error: '%s' is not a lora tensor\n", __func__, name.c_str());
-            return 1;
+        auto general_arch_str = get_kv_str(llm_kv(LLM_KV_GENERAL_ARCHITECTURE));
+        auto general_arch = llm_arch_from_string(general_arch_str);
+        if (general_arch != model->arch) {
+            gguf_free(ctx_gguf);
+            throw std::runtime_error("model arch and LoRA arch mismatch");
         }
 
-        // tensor type
-        ggml_type wtype;
-        switch (ftype) {
-            case 0: wtype = GGML_TYPE_F32;  break;
-            case 1: wtype = GGML_TYPE_F16;  break;
-            default:
-                    {
-                        LLAMA_LOG_ERROR("%s: invalid tensor data type '%d'\n",
-                                __func__, ftype);
-                        return 1;
-                    }
+        auto adapter_type = get_kv_str(llm_kv(LLM_KV_ADAPTER_TYPE));
+        if (adapter_type != "lora") {
+            gguf_free(ctx_gguf);
+            throw std::runtime_error("expect adapter.type to be 'lora', but got: " + adapter_type);
         }
 
-        // data offset
-        size_t offset = fin.tell();
-        offset = (offset + 31) & -32;
-
-        // skip tensor data
-        fin.seek(offset + ggml_row_size(wtype, ne[0]) * ne[1], SEEK_SET);
-
-        tensor_meta_map.emplace(name, tensor_meta{ name, wtype, { ne[0], ne[1] }, offset });
+        adapter.alpha = get_kv_f32(llm_kv(LLM_KV_ADAPTER_LORA_ALPHA));
     }
 
-    bool warned = false;
-    int n_tensors = 0;
-
-    // apply
-    ggml_backend_t backend_cpu = ggml_backend_cpu_init();
-    if (backend_cpu == nullptr) {
-        LLAMA_LOG_ERROR("%s: error: failed to initialize cpu backend\n", __func__);
-        return 1;
-    }
-    ggml_backend_cpu_set_n_threads(backend_cpu, n_threads);
-
-    std::vector> read_buf;
-    for (const auto & it : model.tensors_by_name) {
-        const std::string & base_name = it.first;
-        ggml_tensor * model_t = it.second;
-
-        if (tensor_meta_map.find(base_name + ".loraA") == tensor_meta_map.end() ||
-            tensor_meta_map.find(base_name + ".loraB") == tensor_meta_map.end()) {
-            continue;
-        }
-
-        tensor_meta & metaA = tensor_meta_map.at(base_name + ".loraA");
-        tensor_meta & metaB = tensor_meta_map.at(base_name + ".loraB");
+    int n_tensors = gguf_get_n_tensors(ctx_gguf);
 
-        ggml_init_params lora_init_params = {
-            /* .mem_size   */ ggml_tensor_overhead()*128 + ggml_graph_overhead(),
-            /* .mem_buffer */ nullptr,
-            /* .no_alloc   */ true,
+    // contexts for each buffer type
+    std::map ctx_map;
+    auto get_ctx_for_buft = [&](ggml_backend_buffer_type_t buft) -> ggml_context * {
+        auto it = ctx_map.find(buft);
+        if (it == ctx_map.end()) {
+            // add a new context
+            struct ggml_init_params params = {
+                /*.mem_size   =*/ n_tensors*ggml_tensor_overhead(),
+                /*.mem_buffer =*/ NULL,
+                /*.no_alloc   =*/ true,
+            };
+            ggml_context * buft_ctx = ggml_init(params);
+            ctx_map[buft] = buft_ctx;
+            return buft_ctx;
         };
-        ggml_context * lora_ctx = ggml_init(lora_init_params);
-        if (lora_ctx == nullptr) {
-            LLAMA_LOG_ERROR("%s: error: failed to initialize lora context\n", __func__);
-            ggml_backend_free(backend_cpu);
-            return 1;
-        }
-
-        // create tensors
-        ggml_tensor * loraA = ggml_new_tensor_2d(lora_ctx, metaA.type, metaA.ne[0], metaA.ne[1]);
-        ggml_tensor * loraB = ggml_new_tensor_2d(lora_ctx, metaB.type, metaB.ne[0], metaB.ne[1]);
-        ggml_set_name(loraA, metaA.name.c_str());
-        ggml_set_name(loraB, metaB.name.c_str());
+        return it->second;
+    };
 
-        ggml_tensor * base_t;
-        if (ml) {
-            if (!ml->get_tensor_meta(base_name.c_str())) {
-                LLAMA_LOG_ERROR("%s: error: tensor '%s' not found in base model\n", __func__, base_name.c_str());
-                return 1;
+    // bundle lora_a and lora_b into pairs
+    std::map ab_map;
+    auto str_endswith = [](const std::string & str, const std::string & suffix) {
+        return str.size() >= suffix.size() && str.compare(str.size()-suffix.size(), suffix.size(), suffix) == 0;
+    };
+    for (ggml_tensor * cur = ggml_get_first_tensor(ctx); cur; cur = ggml_get_next_tensor(ctx, cur)) {
+        std::string name(cur->name);
+        if (str_endswith(name, ".lora_a")) {
+            replace_all(name, ".lora_a", "");
+            if (ab_map.find(name) == ab_map.end()) {
+                ab_map[name] = llama_lora_weight(cur, nullptr);
+            } else {
+                ab_map[name].a = cur;
+            }
+        } else if (str_endswith(name, ".lora_b")) {
+            replace_all(name, ".lora_b", "");
+            if (ab_map.find(name) == ab_map.end()) {
+                ab_map[name] = llama_lora_weight(nullptr, cur);
+            } else {
+                ab_map[name].b = cur;
             }
-            base_t = ggml_dup_tensor(lora_ctx, ml->get_tensor_meta(base_name.c_str()));
         } else {
-            base_t = ggml_dup_tensor(lora_ctx, model_t);
-        }
-        ggml_set_name(base_t, base_name.c_str());
-
-        // allocate in backend buffer
-        ggml_backend_buffer_t lora_buf = ggml_backend_alloc_ctx_tensors_from_buft(lora_ctx, ggml_backend_cpu_buffer_type());
-        if (lora_buf == nullptr) {
-            LLAMA_LOG_ERROR("%s: error: failed to allocate lora tensors\n", __func__);
-            return 1;
+            gguf_free(ctx_gguf);
+            ggml_free(ctx);
+            throw std::runtime_error("LoRA tensor '" + name + "' has unexpected suffix");
         }
+    }
 
-        // load tensor data
-        auto load_tensor = [&read_buf, &fin](const tensor_meta & tensor_meta, ggml_tensor * tensor) {
-            read_buf.resize(ggml_nbytes(tensor));
-            fin.seek(tensor_meta.offset, SEEK_SET);
-            fin.read_raw(read_buf.data(), ggml_nbytes(tensor));
-            ggml_backend_tensor_set(tensor, read_buf.data(), 0, read_buf.size());
-        };
-        load_tensor(metaA, loraA);
-        load_tensor(metaB, loraB);
+    // add tensors
+    for (auto & it : ab_map) {
+        const std::string & name = it.first;
+        llama_lora_weight & w = it.second;
 
-        // load base model tensor data
-        if (ml) {
-            ml->load_data_for(base_t);
-        } else {
-            ggml_backend_tensor_copy(model_t, base_t);
+        if (!w.a || !w.b) {
+            gguf_free(ctx_gguf);
+            ggml_free(ctx);
+            throw std::runtime_error("LoRA tensor pair for '" + name + "' is missing one component");
         }
 
-        if (ggml_is_quantized(base_t->type) && !warned) {
-            LLAMA_LOG_WARN("%s: warning: using a lora adapter with a quantized model may result in poor quality, "
-                            "use a f16 or f32 base model with --lora-base\n", __func__);
-            warned = true;
+        // device buft and device ctx
+        auto * model_tensor = llama_get_model_tensor(model, name.c_str());
+        if (!model_tensor) {
+            gguf_free(ctx_gguf);
+            ggml_free(ctx);
+            throw std::runtime_error("LoRA tensor '" + name + "' does not exist in base model");
         }
-
-        if (base_t->ne[0] != loraA->ne[1] || base_t->ne[1] != loraB->ne[1]) {
-            LLAMA_LOG_ERROR("%s: incompatible tensor dimensions (%" PRId64 " and %" PRId64 ");"
-                            " are you sure that this adapter is for this model?\n", __func__, base_t->ne[0], loraA->ne[1]);
-            ggml_free(lora_ctx);
-            ggml_backend_buffer_free(lora_buf);
-            ggml_backend_free(backend_cpu);
-            return 1;
+        struct ggml_context * dev_ctx = get_ctx_for_buft(ggml_backend_buffer_get_type(model_tensor->buffer));
+        // validate tensor shape
+        if (model_tensor->ne[0] != w.a->ne[0] || model_tensor->ne[1] != w.b->ne[1]) {
+            gguf_free(ctx_gguf);
+            ggml_free(ctx);
+            throw std::runtime_error("tensor '" + name + "' has incorrect shape");
         }
+        if (w.a->ne[1] != w.b->ne[0]) {
+            gguf_free(ctx_gguf);
+            ggml_free(ctx);
+            throw std::runtime_error("lora_a tensor is not transposed (hint: adapter from \"finetune\" example is no longer supported)");
+        }
+        // save tensor to adapter
+        struct ggml_tensor * tensor_a = ggml_dup_tensor(dev_ctx, w.a);
+        struct ggml_tensor * tensor_b = ggml_dup_tensor(dev_ctx, w.b);
+        ggml_set_name(tensor_a, w.a->name);
+        ggml_set_name(tensor_b, w.b->name);
+        adapter.ab_map[name] = llama_lora_weight(tensor_a, tensor_b);
+    }
 
-        auto build_lora_graph = [&]() {
-            // w = w + BA*s
-            ggml_tensor * BA = ggml_mul_mat(lora_ctx, loraA, loraB);
-            ggml_set_name(BA, "BA");
-
-            if (scaling != 1.0f) {
-                BA = ggml_scale(lora_ctx, BA, scaling);
-                ggml_set_name(BA, "BA_scaled");
-            }
-
-            ggml_tensor * r;
-            r = ggml_add_inplace(lora_ctx, base_t, BA);
-            ggml_set_name(r, "r_add");
-
-            if (base_t->type != model_t->type) {
-                // convert the result to the model type
-                r = ggml_cast(lora_ctx, r, model_t->type);
-                ggml_set_name(r, "r_cast");
+    // allocate tensors / buffers and zero
+    {
+        adapter.ctxs.reserve(ctx_map.size());
+        adapter.bufs.reserve(ctx_map.size());
+        for (auto it : ctx_map) {
+            ggml_backend_buffer_type_t buft = it.first;
+            ggml_context * ctx_dev = it.second;
+            ggml_backend_buffer_t buf = ggml_backend_alloc_ctx_tensors_from_buft(ctx_dev, buft);
+            if (!buf) {
+                gguf_free(ctx_gguf);
+                ggml_free(ctx);
+                throw std::runtime_error("failed to allocate buffer for lora adapter\n");
             }
+            LLAMA_LOG_INFO("%s: %10s LoRA buffer size = %8.2f MiB\n", __func__, ggml_backend_buffer_name(buf), ggml_backend_buffer_get_size(buf)/1024.0/1024.0);
+            adapter.ctxs.push_back(ctx_dev);
+            adapter.bufs.push_back(buf);
+        }
+    }
 
-            return r;
+    // set tensor data
+    {
+        llama_file gguf_file(path_lora, "rb");
+        std::vector read_buf;
+        auto set_tensor = [&](struct ggml_tensor * orig, struct ggml_tensor * dev) {
+            size_t offs = gguf_get_data_offset(ctx_gguf) + gguf_get_tensor_offset(ctx_gguf, gguf_find_tensor(ctx_gguf, orig->name));
+            size_t size = ggml_nbytes(orig);
+            read_buf.resize(size);
+            gguf_file.seek(offs, SEEK_SET);
+            gguf_file.read_raw(read_buf.data(), size);
+            ggml_backend_tensor_set(dev, read_buf.data(), 0, size);
         };
-
-        ggml_cgraph * gf = ggml_new_graph(lora_ctx);
-        ggml_tensor * r = build_lora_graph();
-        ggml_build_forward_expand(gf, r);
-
-        ggml_backend_buffer_t graph_buf = ggml_backend_alloc_ctx_tensors_from_buft(lora_ctx, ggml_backend_cpu_buffer_type());
-        if (graph_buf == nullptr) {
-            LLAMA_LOG_ERROR("%s: error: failed to allocate graph tensors\n", __func__);
-            ggml_free(lora_ctx);
-            ggml_backend_buffer_free(lora_buf);
-            ggml_backend_free(backend_cpu);
-            return 1;
+        for (auto & it : adapter.ab_map) {
+            auto orig = ab_map[it.first];
+            auto dev  = it.second;
+            set_tensor(orig.a, dev.a);
+            set_tensor(orig.b, dev.b);
         }
+    }
 
-        ggml_backend_graph_compute(backend_cpu, gf);
-
-        ggml_backend_tensor_set(model_t, r->data, 0, ggml_nbytes(r));
-
-#if 0
-        // TODO: use scheduler with fallback to CPU for less copies between CPU and GPU
-        //ggml_backend_sched_t sched = ggml_backend_sched_new(backends.data(), backends.size(), GGML_DEFAULT_GRAPH_SIZE);
-
-        // sched compute
-        ggml_build_forward_expand(gf, build_graph());
-        ggml_backend_sched_init_measure(sched, gf);
-
-        // create the graph again, since the previous one was destroyed by the measure
-        ggml_graph_clear(gf);
-        ggml_build_forward_expand(gf, build_graph());
-        ggml_backend_sched_graph_compute(sched, gf);
-        ggml_backend_sched_free(sched);
-#endif
+    LLAMA_LOG_INFO("%s: loaded %ld tensors from lora file\n", __func__, adapter.ab_map.size()*2);
 
-        ggml_backend_buffer_free(lora_buf);
-        ggml_backend_buffer_free(graph_buf);
-        ggml_free(lora_ctx);
+    // free ctx for reading gguf
+    gguf_free(ctx_gguf);
+    ggml_free(ctx);
+}
 
-        n_tensors++;
-        if (n_tensors % 4 == 0) {
-            LLAMA_LOG_INFO(".");
-        }
+int32_t llama_lora_adapter_set(
+            struct llama_context * ctx,
+            struct llama_lora_adapter * adapter,
+            float scale) {
+    if (ctx->cparams.flash_attn) {
+        LLAMA_LOG_ERROR("%s: flash_attn is not compatible with LoRA\n", __func__);
+        return -1;
     }
+    ctx->lora_adapters[adapter] = scale;
+    return 0;
+}
 
-    ggml_backend_free(backend_cpu);
-
-    const int64_t t_lora_us = ggml_time_us() - t_start_lora_us;
-    LLAMA_LOG_INFO(" done (%.2f ms)\n", t_lora_us / 1000.0);
+int32_t llama_lora_adapter_remove(
+            struct llama_context * ctx,
+            struct llama_lora_adapter * adapter) {
+    auto pos = ctx->lora_adapters.find(adapter);
+    if (pos != ctx->lora_adapters.end()) {
+        ctx->lora_adapters.erase(pos);
+        return 0;
+    }
+    return -1;
+}
 
-    return 0;
+void llama_lora_adapter_free(struct llama_lora_adapter * adapter) {
+    delete adapter;
 }
 
 //
@@ -19514,12 +19558,14 @@ uint32_t llama_model_quantize(
     }
 }
 
-int32_t llama_model_apply_lora_from_file(const struct llama_model * model, const char * path_lora, float scale, const char * path_base_model, int32_t n_threads) {
+struct llama_lora_adapter * llama_lora_adapter_init(struct llama_model * model, const char * path_lora) {
     try {
-        return llama_apply_lora_from_file_internal(*model, path_lora, scale, path_base_model, n_threads);
+        struct llama_lora_adapter * adapter = new llama_lora_adapter(model);
+        llama_lora_adapter_init_internal(model, path_lora, *adapter);
+        return adapter;
     } catch (const std::exception & err) {
         LLAMA_LOG_ERROR("%s: failed to apply lora adapter: %s\n", __func__, err.what());
-        return 1;
+        return nullptr;
     }
 }
 

From 7acfd4e8d55082c1b597dfc3ffe04fb5d530c6dc Mon Sep 17 00:00:00 2001
From: compilade 
Date: Mon, 15 Jul 2024 23:13:10 -0400
Subject: [PATCH 192/326] convert_hf : faster lazy safetensors (#8482)

* convert_hf : faster lazy safetensors

This makes '--dry-run' much, much faster.

* convert_hf : fix memory leak in lazy MoE conversion

The '_lazy' queue was sometimes self-referential,
which caused reference cycles of objects old enough
to avoid garbage collection until potential memory exhaustion.
---
 convert_hf_to_gguf.py          | 48 ++++++++++++++++++++++----
 gguf-py/gguf/lazy.py           | 63 ++++++++++------------------------
 gguf-py/gguf/tensor_mapping.py | 14 ++++----
 3 files changed, 65 insertions(+), 60 deletions(-)

diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py
index a755b0a60bf0a..c2aba909706d0 100755
--- a/convert_hf_to_gguf.py
+++ b/convert_hf_to_gguf.py
@@ -148,9 +148,16 @@ def get_tensors(self) -> Iterator[tuple[str, Tensor]]:
                 tensor_names_from_parts.update(model_part.keys())
 
                 for name in model_part.keys():
-                    data = model_part.get_tensor(name) if self.is_safetensors else model_part[name]
-                    if self.lazy:
-                        data = LazyTorchTensor.from_eager(data)
+                    if self.is_safetensors:
+                        if self.lazy:
+                            data = model_part.get_slice(name)
+                            data = LazyTorchTensor.from_safetensors_slice(data)
+                        else:
+                            data = model_part.get_tensor(name)
+                    else:
+                        data = model_part[name]
+                        if self.lazy:
+                            data = LazyTorchTensor.from_eager(data)
                     yield name, data
 
         # only verify tensor name presence; it doesn't matter if they are not in the right files
@@ -3424,19 +3431,46 @@ class LazyTorchTensor(gguf.LazyBase):
         torch.float32: np.float32,
     }
 
+    # used for safetensors slices
+    # ref: https://github.com/huggingface/safetensors/blob/079781fd0dc455ba0fe851e2b4507c33d0c0d407/bindings/python/src/lib.rs#L1046
+    # TODO: uncomment U64, U32, and U16, ref: https://github.com/pytorch/pytorch/issues/58734
+    _dtype_str_map: dict[str, torch.dtype] = {
+        "F64": torch.float64,
+        "F32": torch.float32,
+        "BF16": torch.bfloat16,
+        "F16": torch.float16,
+        # "U64": torch.uint64,
+        "I64": torch.int64,
+        # "U32": torch.uint32,
+        "I32": torch.int32,
+        # "U16": torch.uint16,
+        "I16": torch.int16,
+        "U8": torch.uint8,
+        "I8": torch.int8,
+        "BOOL": torch.bool,
+        "F8_E4M3": torch.float8_e4m3fn,
+        "F8_E5M2": torch.float8_e5m2,
+    }
+
     def numpy(self) -> gguf.LazyNumpyTensor:
         dtype = self._dtype_map[self.dtype]
         return gguf.LazyNumpyTensor(
             meta=gguf.LazyNumpyTensor.meta_with_dtype_and_shape(dtype, self.shape),
-            lazy=self._lazy,
             args=(self,),
-            func=(lambda s: s[0].numpy())
+            func=(lambda s: s.numpy())
         )
 
     @classmethod
-    def meta_with_dtype_and_shape(cls, dtype: torch.dtype, shape: torch.Size) -> Tensor:
+    def meta_with_dtype_and_shape(cls, dtype: torch.dtype, shape: tuple[int, ...]) -> Tensor:
         return torch.empty(size=shape, dtype=dtype, device="meta")
 
+    @classmethod
+    def from_safetensors_slice(cls, st_slice: Any) -> Tensor:
+        dtype = cls._dtype_str_map[st_slice.get_dtype()]
+        shape: tuple[int, ...] = tuple(st_slice.get_shape())
+        lazy = cls(meta=cls.meta_with_dtype_and_shape(dtype, shape), args=(st_slice,), func=lambda s: s[:])
+        return cast(torch.Tensor, lazy)
+
     @classmethod
     def __torch_function__(cls, func, types, args=(), kwargs=None):
         del types  # unused
@@ -3447,7 +3481,7 @@ def __torch_function__(cls, func, types, args=(), kwargs=None):
         if func is torch.Tensor.numpy:
             return args[0].numpy()
 
-        return LazyTorchTensor._wrap_fn(func)(*args, **kwargs)
+        return cls._wrap_fn(func)(*args, **kwargs)
 
 
 def parse_args() -> argparse.Namespace:
diff --git a/gguf-py/gguf/lazy.py b/gguf-py/gguf/lazy.py
index 6e266f34f76ac..ac98d9a92a3e9 100644
--- a/gguf-py/gguf/lazy.py
+++ b/gguf-py/gguf/lazy.py
@@ -3,7 +3,6 @@
 
 import logging
 from typing import Any, Callable
-from collections import deque
 
 import numpy as np
 from numpy.typing import DTypeLike
@@ -74,20 +73,18 @@ class LazyBase(ABC, metaclass=LazyMeta):
     _tensor_type: type
     _meta: Any
     _data: Any | None
-    _lazy: deque[LazyBase]  # shared within a graph, to avoid deep recursion when making eager
     _args: tuple
-    _func: Callable[[tuple], Any] | None
+    _kwargs: dict[str, Any]
+    _func: Callable[[Any], Any] | None
 
-    def __init__(self, *, meta: Any, data: Any | None = None, lazy: deque[LazyBase] | None = None, args: tuple = (), func: Callable[[tuple], Any] | None = None):
+    def __init__(self, *, meta: Any, data: Any | None = None, args: tuple = (), kwargs: dict[str, Any] | None = None, func: Callable[[Any], Any] | None = None):
         super().__init__()
         self._meta = meta
         self._data = data
-        self._lazy = lazy if lazy is not None else deque()
         self._args = args
+        self._kwargs = kwargs if kwargs is not None else {}
         self._func = func
         assert self._func is not None or self._data is not None
-        if self._data is None:
-            self._lazy.append(self)
 
     def __init_subclass__(cls) -> None:
         if "_tensor_type" not in cls.__dict__:
@@ -117,6 +114,7 @@ def wrapped_fn(*args, **kwargs):
             args = ((use_self,) if use_self is not None else ()) + args
 
             meta_args = LazyBase._recurse_apply(args, lambda t: t._meta)
+            # TODO: maybe handle tensors in kwargs too
 
             if isinstance(meta_noop, bool) and not meta_noop:
                 try:
@@ -140,23 +138,7 @@ def wrapped_fn(*args, **kwargs):
                         res = cls.meta_with_dtype_and_shape(meta_noop, res.shape)
 
             if isinstance(res, cls._tensor_type):
-                class CollectSharedLazy:
-                    # emulating a static variable
-                    shared_lazy: None | deque[LazyBase] = None
-
-                    @staticmethod
-                    def collect_replace(t: LazyBase):
-                        if CollectSharedLazy.shared_lazy is None:
-                            CollectSharedLazy.shared_lazy = t._lazy
-                        else:
-                            CollectSharedLazy.shared_lazy.extend(t._lazy)
-                            t._lazy = CollectSharedLazy.shared_lazy
-
-                LazyBase._recurse_apply(args, CollectSharedLazy.collect_replace)
-
-                shared_lazy = CollectSharedLazy.shared_lazy
-
-                return cls(meta=cls.eager_to_meta(res), lazy=shared_lazy, args=args, func=lambda a: fn(*a, **kwargs))
+                return cls(meta=cls.eager_to_meta(res), args=args, kwargs=kwargs, func=fn)
             else:
                 del res  # not needed
                 # non-tensor return likely relies on the contents of the args
@@ -168,26 +150,18 @@ def collect_replace(t: LazyBase):
     @classmethod
     def to_eager(cls, t: Any) -> Any:
         def simple_to_eager(_t: LazyBase) -> Any:
-            def already_eager_to_eager(_t: LazyBase) -> Any:
-                assert _t._data is not None
+            if _t._data is not None:
                 return _t._data
 
-            while _t._data is None:
-                lt = _t._lazy.popleft()
-                if lt._data is not None:
-                    # Lazy tensor did not belong in the lazy queue.
-                    # Weirdly only happens with Bloom models...
-                    # likely because tensors aren't unique in the queue.
-                    # The final output is still the same as in eager mode,
-                    # so it's safe to ignore this.
-                    continue
-                assert lt._func is not None
-                lt._args = cls._recurse_apply(lt._args, already_eager_to_eager)
-                lt._data = lt._func(lt._args)
-                # sanity check
-                assert lt._data is not None
-                assert lt._data.dtype == lt._meta.dtype
-                assert lt._data.shape == lt._meta.shape
+            # NOTE: there's a recursion limit in Python (usually 1000)
+
+            assert _t._func is not None
+            _t._args = cls._recurse_apply(_t._args, simple_to_eager)
+            _t._data = _t._func(*_t._args, **_t._kwargs)
+            # sanity check
+            assert _t._data is not None
+            assert _t._data.dtype == _t._meta.dtype
+            assert _t._data.shape == _t._meta.shape
 
             return _t._data
 
@@ -206,7 +180,7 @@ def meta_with_dtype_and_shape(cls, dtype: Any, shape: Any) -> Any: pass
     @classmethod
     def from_eager(cls, t: Any) -> Any:
         if type(t) is cls:
-            # already eager
+            # already lazy
             return t
         elif isinstance(t, cls._tensor_type):
             return cls(meta=cls.eager_to_meta(t), data=t)
@@ -228,8 +202,7 @@ def meta_with_dtype_and_shape(cls, dtype: DTypeLike, shape: tuple[int, ...]) ->
     def astype(self, dtype, *args, **kwargs):
         meta = type(self).meta_with_dtype_and_shape(dtype, self._meta.shape)
         full_args = (self, dtype,) + args
-        # very important to pass the shared _lazy deque, or else there's an infinite loop somewhere.
-        return type(self)(meta=meta, args=full_args, lazy=self._lazy, func=(lambda a: a[0].astype(*a[1:], **kwargs)))
+        return type(self)(meta=meta, args=full_args, kwargs=kwargs, func=(lambda a, *args, **kwargs: a.astype(*args, **kwargs)))
 
     def tofile(self, *args, **kwargs):
         eager = LazyNumpyTensor.to_eager(self)
diff --git a/gguf-py/gguf/tensor_mapping.py b/gguf-py/gguf/tensor_mapping.py
index 7264240f5e17a..9aa2209e2f69f 100644
--- a/gguf-py/gguf/tensor_mapping.py
+++ b/gguf-py/gguf/tensor_mapping.py
@@ -602,14 +602,12 @@ def __init__(self, arch: MODEL_ARCH, n_blocks: int):
             for tensor, keys in self.block_mappings_cfg.items():
                 if tensor not in MODEL_TENSORS[arch]:
                     continue
-                # TODO: make this configurable
-                n_experts = 160
-                for xid in range(n_experts):
-                    tensor_name = TENSOR_NAMES[tensor].format(bid = bid, xid = xid)
-                    self.mapping[tensor_name] = (tensor, tensor_name)
-                    for key in keys:
-                        key = key.format(bid = bid, xid = xid)
-                        self.mapping[key] = (tensor, tensor_name)
+
+                tensor_name = TENSOR_NAMES[tensor].format(bid = bid)
+                self.mapping[tensor_name] = (tensor, tensor_name)
+                for key in keys:
+                    key = key.format(bid = bid)
+                    self.mapping[key] = (tensor, tensor_name)
 
     def get_type_and_name(self, key: str, try_suffixes: Sequence[str] = ()) -> tuple[MODEL_TENSOR, str] | None:
         result = self.mapping.get(key)

From 0efec57787cb8d8d76b17cd3765e6521e22c1f19 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Tue, 16 Jul 2024 10:00:30 +0300
Subject: [PATCH 193/326] llama : valign + remove unused ftype (#8502)

---
 examples/quantize/quantize.cpp | 74 +++++++++++++++++-----------------
 include/llama.h                |  2 +-
 src/llama.cpp                  | 72 ++++++++++++++++-----------------
 3 files changed, 72 insertions(+), 76 deletions(-)

diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp
index 1578c4afb5dfa..8d764725878b9 100644
--- a/examples/quantize/quantize.cpp
+++ b/examples/quantize/quantize.cpp
@@ -16,44 +16,44 @@ struct quant_option {
 };
 
 static const std::vector QUANT_OPTIONS = {
-    { "Q4_0",   LLAMA_FTYPE_MOSTLY_Q4_0,   " 4.34G, +0.4685 ppl @ Llama-3-8B",  },
-    { "Q4_1",   LLAMA_FTYPE_MOSTLY_Q4_1,   " 4.78G, +0.4511 ppl @ Llama-3-8B",  },
-    { "Q5_0",   LLAMA_FTYPE_MOSTLY_Q5_0,   " 5.21G, +0.1316 ppl @ Llama-3-8B",  },
-    { "Q5_1",   LLAMA_FTYPE_MOSTLY_Q5_1,   " 5.65G, +0.1062 ppl @ Llama-3-8B",  },
-    { "IQ2_XXS",LLAMA_FTYPE_MOSTLY_IQ2_XXS," 2.06 bpw quantization",            },
-    { "IQ2_XS", LLAMA_FTYPE_MOSTLY_IQ2_XS, " 2.31 bpw quantization",            },
-    { "IQ2_S",  LLAMA_FTYPE_MOSTLY_IQ2_S,  " 2.5  bpw quantization",            },
-    { "IQ2_M",  LLAMA_FTYPE_MOSTLY_IQ2_M,  " 2.7  bpw quantization",            },
-    { "IQ1_S",  LLAMA_FTYPE_MOSTLY_IQ1_S,  " 1.56 bpw quantization",            },
-    { "IQ1_M",  LLAMA_FTYPE_MOSTLY_IQ1_M,  " 1.75 bpw quantization",            },
-    { "Q2_K",   LLAMA_FTYPE_MOSTLY_Q2_K,   " 2.96G, +3.5199 ppl @ Llama-3-8B",  },
-    { "Q2_K_S", LLAMA_FTYPE_MOSTLY_Q2_K_S, " 2.96G, +3.1836 ppl @ Llama-3-8B",  },
-    { "IQ3_XXS",LLAMA_FTYPE_MOSTLY_IQ3_XXS," 3.06 bpw quantization",            },
-    { "IQ3_S",  LLAMA_FTYPE_MOSTLY_IQ3_S,  " 3.44 bpw quantization",            },
-    { "IQ3_M",  LLAMA_FTYPE_MOSTLY_IQ3_M,  " 3.66 bpw quantization mix",        },
-    { "Q3_K",   LLAMA_FTYPE_MOSTLY_Q3_K_M, "alias for Q3_K_M"                   },
-    { "IQ3_XS", LLAMA_FTYPE_MOSTLY_IQ3_XS, " 3.3 bpw quantization",             },
-    { "Q3_K_S", LLAMA_FTYPE_MOSTLY_Q3_K_S, " 3.41G, +1.6321 ppl @ Llama-3-8B",  },
-    { "Q3_K_M", LLAMA_FTYPE_MOSTLY_Q3_K_M, " 3.74G, +0.6569 ppl @ Llama-3-8B",  },
-    { "Q3_K_L", LLAMA_FTYPE_MOSTLY_Q3_K_L, " 4.03G, +0.5562 ppl @ Llama-3-8B",  },
-    { "IQ4_NL", LLAMA_FTYPE_MOSTLY_IQ4_NL, " 4.50 bpw non-linear quantization", },
-    { "IQ4_XS", LLAMA_FTYPE_MOSTLY_IQ4_XS, " 4.25 bpw non-linear quantization", },
-    { "Q4_K",   LLAMA_FTYPE_MOSTLY_Q4_K_M, "alias for Q4_K_M",                  },
-    { "Q4_K_S", LLAMA_FTYPE_MOSTLY_Q4_K_S, " 4.37G, +0.2689 ppl @ Llama-3-8B",  },
-    { "Q4_K_M", LLAMA_FTYPE_MOSTLY_Q4_K_M, " 4.58G, +0.1754 ppl @ Llama-3-8B",  },
-    { "Q5_K",   LLAMA_FTYPE_MOSTLY_Q5_K_M, "alias for Q5_K_M",                  },
-    { "Q5_K_S", LLAMA_FTYPE_MOSTLY_Q5_K_S, " 5.21G, +0.1049 ppl @ Llama-3-8B",  },
-    { "Q5_K_M", LLAMA_FTYPE_MOSTLY_Q5_K_M, " 5.33G, +0.0569 ppl @ Llama-3-8B",  },
-    { "Q6_K",   LLAMA_FTYPE_MOSTLY_Q6_K,   " 6.14G, +0.0217 ppl @ Llama-3-8B",  },
-    { "Q8_0",   LLAMA_FTYPE_MOSTLY_Q8_0,   " 7.96G, +0.0026 ppl @ Llama-3-8B",  },
-    { "Q4_0_4_4", LLAMA_FTYPE_MOSTLY_Q4_0_4_4, " 4.34G, +0.4685 ppl @ Llama-3-8B", },
-    { "Q4_0_4_8", LLAMA_FTYPE_MOSTLY_Q4_0_4_8, " 4.34G, +0.4685 ppl @ Llama-3-8B", },
-    { "Q4_0_8_8", LLAMA_FTYPE_MOSTLY_Q4_0_8_8, " 4.34G, +0.4685 ppl @ Llama-3-8B", },
-    { "F16",    LLAMA_FTYPE_MOSTLY_F16,    "14.00G, +0.0020 ppl @ Mistral-7B",  },
-    { "BF16",   LLAMA_FTYPE_MOSTLY_BF16,   "14.00G, -0.0050 ppl @ Mistral-7B",  },
-    { "F32",    LLAMA_FTYPE_ALL_F32,       "26.00G              @ 7B",          },
+    { "Q4_0",     LLAMA_FTYPE_MOSTLY_Q4_0,     " 4.34G, +0.4685 ppl @ Llama-3-8B",  },
+    { "Q4_1",     LLAMA_FTYPE_MOSTLY_Q4_1,     " 4.78G, +0.4511 ppl @ Llama-3-8B",  },
+    { "Q5_0",     LLAMA_FTYPE_MOSTLY_Q5_0,     " 5.21G, +0.1316 ppl @ Llama-3-8B",  },
+    { "Q5_1",     LLAMA_FTYPE_MOSTLY_Q5_1,     " 5.65G, +0.1062 ppl @ Llama-3-8B",  },
+    { "IQ2_XXS",  LLAMA_FTYPE_MOSTLY_IQ2_XXS,  " 2.06 bpw quantization",            },
+    { "IQ2_XS",   LLAMA_FTYPE_MOSTLY_IQ2_XS,   " 2.31 bpw quantization",            },
+    { "IQ2_S",    LLAMA_FTYPE_MOSTLY_IQ2_S,    " 2.5  bpw quantization",            },
+    { "IQ2_M",    LLAMA_FTYPE_MOSTLY_IQ2_M,    " 2.7  bpw quantization",            },
+    { "IQ1_S",    LLAMA_FTYPE_MOSTLY_IQ1_S,    " 1.56 bpw quantization",            },
+    { "IQ1_M",    LLAMA_FTYPE_MOSTLY_IQ1_M,    " 1.75 bpw quantization",            },
+    { "Q2_K",     LLAMA_FTYPE_MOSTLY_Q2_K,     " 2.96G, +3.5199 ppl @ Llama-3-8B",  },
+    { "Q2_K_S",   LLAMA_FTYPE_MOSTLY_Q2_K_S,   " 2.96G, +3.1836 ppl @ Llama-3-8B",  },
+    { "IQ3_XXS",  LLAMA_FTYPE_MOSTLY_IQ3_XXS,  " 3.06 bpw quantization",            },
+    { "IQ3_S",    LLAMA_FTYPE_MOSTLY_IQ3_S,    " 3.44 bpw quantization",            },
+    { "IQ3_M",    LLAMA_FTYPE_MOSTLY_IQ3_M,    " 3.66 bpw quantization mix",        },
+    { "Q3_K",     LLAMA_FTYPE_MOSTLY_Q3_K_M,   "alias for Q3_K_M"                   },
+    { "IQ3_XS",   LLAMA_FTYPE_MOSTLY_IQ3_XS,   " 3.3 bpw quantization",             },
+    { "Q3_K_S",   LLAMA_FTYPE_MOSTLY_Q3_K_S,   " 3.41G, +1.6321 ppl @ Llama-3-8B",  },
+    { "Q3_K_M",   LLAMA_FTYPE_MOSTLY_Q3_K_M,   " 3.74G, +0.6569 ppl @ Llama-3-8B",  },
+    { "Q3_K_L",   LLAMA_FTYPE_MOSTLY_Q3_K_L,   " 4.03G, +0.5562 ppl @ Llama-3-8B",  },
+    { "IQ4_NL",   LLAMA_FTYPE_MOSTLY_IQ4_NL,   " 4.50 bpw non-linear quantization", },
+    { "IQ4_XS",   LLAMA_FTYPE_MOSTLY_IQ4_XS,   " 4.25 bpw non-linear quantization", },
+    { "Q4_K",     LLAMA_FTYPE_MOSTLY_Q4_K_M,   "alias for Q4_K_M",                  },
+    { "Q4_K_S",   LLAMA_FTYPE_MOSTLY_Q4_K_S,   " 4.37G, +0.2689 ppl @ Llama-3-8B",  },
+    { "Q4_K_M",   LLAMA_FTYPE_MOSTLY_Q4_K_M,   " 4.58G, +0.1754 ppl @ Llama-3-8B",  },
+    { "Q5_K",     LLAMA_FTYPE_MOSTLY_Q5_K_M,   "alias for Q5_K_M",                  },
+    { "Q5_K_S",   LLAMA_FTYPE_MOSTLY_Q5_K_S,   " 5.21G, +0.1049 ppl @ Llama-3-8B",  },
+    { "Q5_K_M",   LLAMA_FTYPE_MOSTLY_Q5_K_M,   " 5.33G, +0.0569 ppl @ Llama-3-8B",  },
+    { "Q6_K",     LLAMA_FTYPE_MOSTLY_Q6_K,     " 6.14G, +0.0217 ppl @ Llama-3-8B",  },
+    { "Q8_0",     LLAMA_FTYPE_MOSTLY_Q8_0,     " 7.96G, +0.0026 ppl @ Llama-3-8B",  },
+    { "Q4_0_4_4", LLAMA_FTYPE_MOSTLY_Q4_0_4_4, " 4.34G, +0.4685 ppl @ Llama-3-8B",  },
+    { "Q4_0_4_8", LLAMA_FTYPE_MOSTLY_Q4_0_4_8, " 4.34G, +0.4685 ppl @ Llama-3-8B",  },
+    { "Q4_0_8_8", LLAMA_FTYPE_MOSTLY_Q4_0_8_8, " 4.34G, +0.4685 ppl @ Llama-3-8B",  },
+    { "F16",      LLAMA_FTYPE_MOSTLY_F16,      "14.00G, +0.0020 ppl @ Mistral-7B",  },
+    { "BF16",     LLAMA_FTYPE_MOSTLY_BF16,     "14.00G, -0.0050 ppl @ Mistral-7B",  },
+    { "F32",      LLAMA_FTYPE_ALL_F32,         "26.00G              @ 7B",          },
     // Note: Ensure COPY comes after F32 to avoid ftype 0 from matching.
-    { "COPY",   LLAMA_FTYPE_ALL_F32,       "only copy tensors, no quantizing",  },
+    { "COPY",     LLAMA_FTYPE_ALL_F32,         "only copy tensors, no quantizing",  },
 };
 
 static const char * const LLM_KV_QUANTIZE_IMATRIX_FILE       = "quantize.imatrix.file";
diff --git a/include/llama.h b/include/llama.h
index c57d21f0c70b9..c0fb53060eae4 100644
--- a/include/llama.h
+++ b/include/llama.h
@@ -133,7 +133,7 @@ extern "C" {
         LLAMA_FTYPE_MOSTLY_F16           = 1,  // except 1d tensors
         LLAMA_FTYPE_MOSTLY_Q4_0          = 2,  // except 1d tensors
         LLAMA_FTYPE_MOSTLY_Q4_1          = 3,  // except 1d tensors
-        LLAMA_FTYPE_MOSTLY_Q4_1_SOME_F16 = 4,  // tok_embeddings.weight and output.weight are F16
+        // LLAMA_FTYPE_MOSTLY_Q4_1_SOME_F16 = 4,  // tok_embeddings.weight and output.weight are F16
         // LLAMA_FTYPE_MOSTLY_Q4_2       = 5,  // support has been removed
         // LLAMA_FTYPE_MOSTLY_Q4_3       = 6,  // support has been removed
         LLAMA_FTYPE_MOSTLY_Q8_0          = 7,  // except 1d tensors
diff --git a/src/llama.cpp b/src/llama.cpp
index 07bb427135d8c..4a9903cc33e47 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -4510,40 +4510,36 @@ static std::string llama_model_ftype_name(llama_ftype ftype) {
     }
 
     switch (ftype) {
-        case LLAMA_FTYPE_ALL_F32:     return "all F32";
-        case LLAMA_FTYPE_MOSTLY_F16:  return "F16";
-        case LLAMA_FTYPE_MOSTLY_BF16: return "BF16";
-        case LLAMA_FTYPE_MOSTLY_Q4_0: return "Q4_0";
-        case LLAMA_FTYPE_MOSTLY_Q4_1: return "Q4_1";
-        case LLAMA_FTYPE_MOSTLY_Q4_1_SOME_F16:
-                                      return "Q4_1, some F16";
-        case LLAMA_FTYPE_MOSTLY_Q5_0: return "Q5_0";
-        case LLAMA_FTYPE_MOSTLY_Q5_1: return "Q5_1";
-        case LLAMA_FTYPE_MOSTLY_Q8_0: return "Q8_0";
-
-        // K-quants
-        case LLAMA_FTYPE_MOSTLY_Q2_K:   return "Q2_K - Medium";
-        case LLAMA_FTYPE_MOSTLY_Q2_K_S: return "Q2_K - Small";
-        case LLAMA_FTYPE_MOSTLY_Q3_K_S: return "Q3_K - Small";
-        case LLAMA_FTYPE_MOSTLY_Q3_K_M: return "Q3_K - Medium";
-        case LLAMA_FTYPE_MOSTLY_Q3_K_L: return "Q3_K - Large";
-        case LLAMA_FTYPE_MOSTLY_Q4_K_S: return "Q4_K - Small";
-        case LLAMA_FTYPE_MOSTLY_Q4_K_M: return "Q4_K - Medium";
-        case LLAMA_FTYPE_MOSTLY_Q5_K_S: return "Q5_K - Small";
-        case LLAMA_FTYPE_MOSTLY_Q5_K_M: return "Q5_K - Medium";
-        case LLAMA_FTYPE_MOSTLY_Q6_K:   return "Q6_K";
-        case LLAMA_FTYPE_MOSTLY_IQ2_XXS:return "IQ2_XXS - 2.0625 bpw";
-        case LLAMA_FTYPE_MOSTLY_IQ2_XS: return "IQ2_XS - 2.3125 bpw";
-        case LLAMA_FTYPE_MOSTLY_IQ2_S:  return "IQ2_S - 2.5 bpw";
-        case LLAMA_FTYPE_MOSTLY_IQ2_M:  return "IQ2_M - 2.7 bpw";
-        case LLAMA_FTYPE_MOSTLY_IQ3_XS: return "IQ3_XS - 3.3 bpw";
-        case LLAMA_FTYPE_MOSTLY_IQ3_XXS:return "IQ3_XXS - 3.0625 bpw";
-        case LLAMA_FTYPE_MOSTLY_IQ1_S  :return "IQ1_S - 1.5625 bpw";
-        case LLAMA_FTYPE_MOSTLY_IQ1_M  :return "IQ1_M - 1.75 bpw";
-        case LLAMA_FTYPE_MOSTLY_IQ4_NL: return "IQ4_NL - 4.5 bpw";
-        case LLAMA_FTYPE_MOSTLY_IQ4_XS: return "IQ4_XS - 4.25 bpw";
-        case LLAMA_FTYPE_MOSTLY_IQ3_S:  return "IQ3_S - 3.4375 bpw";
-        case LLAMA_FTYPE_MOSTLY_IQ3_M:  return "IQ3_S mix - 3.66 bpw";
+        case LLAMA_FTYPE_ALL_F32:         return "all F32";
+        case LLAMA_FTYPE_MOSTLY_F16:      return "F16";
+        case LLAMA_FTYPE_MOSTLY_BF16:     return "BF16";
+        case LLAMA_FTYPE_MOSTLY_Q4_0:     return "Q4_0";
+        case LLAMA_FTYPE_MOSTLY_Q4_1:     return "Q4_1";
+        case LLAMA_FTYPE_MOSTLY_Q5_0:     return "Q5_0";
+        case LLAMA_FTYPE_MOSTLY_Q5_1:     return "Q5_1";
+        case LLAMA_FTYPE_MOSTLY_Q8_0:     return "Q8_0";
+        case LLAMA_FTYPE_MOSTLY_Q2_K:     return "Q2_K - Medium";
+        case LLAMA_FTYPE_MOSTLY_Q2_K_S:   return "Q2_K - Small";
+        case LLAMA_FTYPE_MOSTLY_Q3_K_S:   return "Q3_K - Small";
+        case LLAMA_FTYPE_MOSTLY_Q3_K_M:   return "Q3_K - Medium";
+        case LLAMA_FTYPE_MOSTLY_Q3_K_L:   return "Q3_K - Large";
+        case LLAMA_FTYPE_MOSTLY_Q4_K_S:   return "Q4_K - Small";
+        case LLAMA_FTYPE_MOSTLY_Q4_K_M:   return "Q4_K - Medium";
+        case LLAMA_FTYPE_MOSTLY_Q5_K_S:   return "Q5_K - Small";
+        case LLAMA_FTYPE_MOSTLY_Q5_K_M:   return "Q5_K - Medium";
+        case LLAMA_FTYPE_MOSTLY_Q6_K:     return "Q6_K";
+        case LLAMA_FTYPE_MOSTLY_IQ2_XXS:  return "IQ2_XXS - 2.0625 bpw";
+        case LLAMA_FTYPE_MOSTLY_IQ2_XS:   return "IQ2_XS - 2.3125 bpw";
+        case LLAMA_FTYPE_MOSTLY_IQ2_S:    return "IQ2_S - 2.5 bpw";
+        case LLAMA_FTYPE_MOSTLY_IQ2_M:    return "IQ2_M - 2.7 bpw";
+        case LLAMA_FTYPE_MOSTLY_IQ3_XS:   return "IQ3_XS - 3.3 bpw";
+        case LLAMA_FTYPE_MOSTLY_IQ3_XXS:  return "IQ3_XXS - 3.0625 bpw";
+        case LLAMA_FTYPE_MOSTLY_IQ1_S:    return "IQ1_S - 1.5625 bpw";
+        case LLAMA_FTYPE_MOSTLY_IQ1_M:    return "IQ1_M - 1.75 bpw";
+        case LLAMA_FTYPE_MOSTLY_IQ4_NL:   return "IQ4_NL - 4.5 bpw";
+        case LLAMA_FTYPE_MOSTLY_IQ4_XS:   return "IQ4_XS - 4.25 bpw";
+        case LLAMA_FTYPE_MOSTLY_IQ3_S:    return "IQ3_S - 3.4375 bpw";
+        case LLAMA_FTYPE_MOSTLY_IQ3_M:    return "IQ3_S mix - 3.66 bpw";
         case LLAMA_FTYPE_MOSTLY_Q4_0_4_4: return "Q4_0_4_4";
         case LLAMA_FTYPE_MOSTLY_Q4_0_4_8: return "Q4_0_4_8";
         case LLAMA_FTYPE_MOSTLY_Q4_0_8_8: return "Q4_0_8_8";
@@ -18069,10 +18065,10 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
     //    if (ftype == LLAMA_FTYPE_MOSTLY_Q5_K_S) new_type = GGML_TYPE_Q4_K;
     //}
     bool convert_incompatible_tensor = false;
-    if (new_type == GGML_TYPE_Q2_K || new_type == GGML_TYPE_Q3_K || new_type == GGML_TYPE_Q4_K ||
-        new_type == GGML_TYPE_Q5_K || new_type == GGML_TYPE_Q6_K || new_type == GGML_TYPE_IQ4_XS ||
-        new_type == GGML_TYPE_IQ2_XS || new_type == GGML_TYPE_IQ2_XXS || new_type == GGML_TYPE_IQ2_S ||
-        new_type == GGML_TYPE_IQ3_XXS || new_type == GGML_TYPE_IQ1_S || new_type == GGML_TYPE_IQ3_S ||
+    if (new_type == GGML_TYPE_Q2_K    || new_type == GGML_TYPE_Q3_K    || new_type == GGML_TYPE_Q4_K   ||
+        new_type == GGML_TYPE_Q5_K    || new_type == GGML_TYPE_Q6_K    || new_type == GGML_TYPE_IQ4_XS ||
+        new_type == GGML_TYPE_IQ2_XS  || new_type == GGML_TYPE_IQ2_XXS || new_type == GGML_TYPE_IQ2_S  ||
+        new_type == GGML_TYPE_IQ3_XXS || new_type == GGML_TYPE_IQ1_S   || new_type == GGML_TYPE_IQ3_S  ||
         new_type == GGML_TYPE_IQ1_M) {
         int nx = tensor->ne[0];
         int ny = tensor->ne[1];

From 37b12f92ab696d70f9a65d7447ce721b094fb32e Mon Sep 17 00:00:00 2001
From: Steve Bonds 
Date: Tue, 16 Jul 2024 00:04:45 -0700
Subject: [PATCH 194/326] export-lora : handle help argument (#8497)

The --help option on export-lora isn't accepted as valid. The help still gets displayed by default, but the script exits with an error message and nonzero status.
---
 examples/export-lora/export-lora.cpp | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/examples/export-lora/export-lora.cpp b/examples/export-lora/export-lora.cpp
index 08413f57e4c3a..16f27aa77b500 100644
--- a/examples/export-lora/export-lora.cpp
+++ b/examples/export-lora/export-lora.cpp
@@ -190,6 +190,9 @@ static bool export_lora_params_parse(int argc, char ** argv, struct export_lora_
             if (params->n_threads <= 0) {
                 params->n_threads = std::thread::hardware_concurrency();
             }
+        } else if (arg == "-h" || arg == "--help") {
+            export_lora_print_usage(argc, argv, &default_params);
+            exit(0);
         } else {
             fprintf(stderr, "error: unknown argument: '%s'\n", arg.c_str());
             export_lora_print_usage(argc, argv, &default_params);

From 1666f92dcda14e002cbb08e1028f9fff341d73ad Mon Sep 17 00:00:00 2001
From: Brian 
Date: Tue, 16 Jul 2024 17:14:16 +1000
Subject: [PATCH 195/326] gguf-hash : update clib.json to point to original
 xxhash repo (#8491)

* Update clib.json to point to Cyan4973 original xxhash

Convinced Cyan4973 to add clib.json directly to his repo, so can now point the clib package directly to him now. Previously pointed to my fork with the clib.json package metadata

https://github.com/Cyan4973/xxHash/pull/954

* gguf-hash: readme update to point to Cyan4973 xxHash repo [no ci]
---
 examples/gguf-hash/README.md             | 2 +-
 examples/gguf-hash/deps/xxhash/clib.json | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/gguf-hash/README.md b/examples/gguf-hash/README.md
index 2320ffd8181b3..9871651e38ba8 100644
--- a/examples/gguf-hash/README.md
+++ b/examples/gguf-hash/README.md
@@ -201,6 +201,6 @@ Verification results for test.gguf.manifest - Success
 
 These micro c libraries dependencies was installed via the [clib c package manager](https://github.com/clibs)
 
-- https://github.com/mofosyne/xxHash (From: https://github.com/Cyan4973/xxHash)
+- https://github.com/Cyan4973/xxHash
 - https://github.com/clibs/sha1/
 - https://github.com/jb55/sha256.c
diff --git a/examples/gguf-hash/deps/xxhash/clib.json b/examples/gguf-hash/deps/xxhash/clib.json
index 0048c74dc2741..242343c5d992d 100644
--- a/examples/gguf-hash/deps/xxhash/clib.json
+++ b/examples/gguf-hash/deps/xxhash/clib.json
@@ -1,7 +1,7 @@
 {
   "name": "xxhash",
   "version": "0.8.2",
-  "repo": "mofosyne/xxhash",
+  "repo": "Cyan4973/xxhash",
   "description": "Extremely fast non-cryptographic hash algorithm",
   "keywords": ["xxhash", "hashing"],
   "license": "BSD-2-Clause",

From 5e116e8dd51775f8f1c090570be148d5d7eea6c3 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= 
Date: Tue, 16 Jul 2024 21:20:59 +0200
Subject: [PATCH 196/326] make/cmake: add missing force MMQ/cuBLAS for HIP
 (#8515)

---
 Makefile                | 8 ++++++++
 ggml/src/CMakeLists.txt | 4 ++++
 2 files changed, 12 insertions(+)

diff --git a/Makefile b/Makefile
index bec332ec57b55..4584594af4174 100644
--- a/Makefile
+++ b/Makefile
@@ -795,6 +795,14 @@ ifdef GGML_CUDA_FORCE_DMMV
 	HIPFLAGS += -DGGML_CUDA_FORCE_DMMV
 endif # GGML_CUDA_FORCE_DMMV
 
+ifdef GGML_CUDA_FORCE_MMQ
+	HIPFLAGS += -DGGML_CUDA_FORCE_MMQ
+endif # GGML_CUDA_FORCE_MMQ
+
+ifdef GGML_CUDA_FORCE_CUBLAS
+	HIPFLAGS += -DGGML_CUDA_FORCE_CUBLAS
+endif # GGML_CUDA_FORCE_CUBLAS
+
 ifdef GGML_CUDA_NO_PEER_COPY
 	HIPFLAGS += -DGGML_CUDA_NO_PEER_COPY
 endif # GGML_CUDA_NO_PEER_COPY
diff --git a/ggml/src/CMakeLists.txt b/ggml/src/CMakeLists.txt
index 41e50ad2c9e33..cbadaf4d931c3 100644
--- a/ggml/src/CMakeLists.txt
+++ b/ggml/src/CMakeLists.txt
@@ -440,6 +440,10 @@ if (GGML_HIPBLAS)
         add_compile_definitions(GGML_CUDA_FORCE_MMQ)
     endif()
 
+    if (GGML_CUDA_FORCE_CUBLAS)
+        add_compile_definitions(GGML_CUDA_FORCE_CUBLAS)
+    endif()
+
     if (GGML_CUDA_NO_PEER_COPY)
         add_compile_definitions(GGML_CUDA_NO_PEER_COPY)
     endif()

From d65a8361fed8be97389776fb94217e937ec6b03c Mon Sep 17 00:00:00 2001
From: Georgi Gerganov 
Date: Wed, 17 Jul 2024 10:32:59 +0300
Subject: [PATCH 197/326] llama : disable context-shift for DeepSeek v2 (#8501)

---
 src/llama.cpp | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/src/llama.cpp b/src/llama.cpp
index 4a9903cc33e47..89b5763dcd7f8 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -15133,6 +15133,10 @@ static void llama_kv_cache_update_internal(struct llama_context & lctx) {
 
     // apply K-shift if needed
     if (lctx.model.hparams.rope_type != LLAMA_ROPE_TYPE_NONE && lctx.kv_self.has_shift) {
+        if (lctx.model.arch == LLM_ARCH_DEEPSEEK2) { // not supported due to MLA
+            GGML_ASSERT(false && "Deepseek2 does not support K-shift");
+        }
+
         {
             ggml_backend_sched_reset(lctx.sched);
 

From da3913d8f9475b0d4bcbeb4936c724af4eade092 Mon Sep 17 00:00:00 2001
From: "Masaya, Kato" <62578291+msy-kato@users.noreply.github.com>
Date: Wed, 17 Jul 2024 16:34:28 +0900
Subject: [PATCH 198/326] batched: fix n_predict parameter (#8527)

---
 examples/batched/batched.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/batched/batched.cpp b/examples/batched/batched.cpp
index 2442e954dcc1a..53fbfb0a8cf2a 100644
--- a/examples/batched/batched.cpp
+++ b/examples/batched/batched.cpp
@@ -31,7 +31,7 @@ int main(int argc, char ** argv) {
     int n_parallel = params.n_parallel;
 
     // total length of the sequences including the prompt
-    int n_predict = 32;
+    int n_predict = params.n_predict;
 
     // init LLM
 

From 1bdd8ae19f50bc6f108fa247e90688e5c60559fc Mon Sep 17 00:00:00 2001
From: hipudding 
Date: Wed, 17 Jul 2024 19:23:50 +0800
Subject: [PATCH 199/326] [CANN] Add Ascend NPU backend (#6035)

* [CANN] Add Ascend NPU backend

Ascend is a full-stack AI computing infrastructure for industry
applications and services based on Huawei Ascend processors and
software.

CANN (Compute Architecture of Neural Networks), developped by
Huawei, is a heterogeneous computing architecture for AI.

Co-authored-by: wangshuai09 <391746016@qq.com>

* delete trailing whitespaces

* Modify the code based on review comment

* Rename LLAMA_CANN to GGML_CANN

* Make ggml-common.h private

* add ggml_cann prefix for acl funcs

* Add logging for CANN backend

* Delete Trailing whitespace

---------

Co-authored-by: wangshuai09 <391746016@qq.com>
---
 CMakeLists.txt                                |    1 +
 examples/llama-bench/llama-bench.cpp          |   15 +
 examples/llava/clip.cpp                       |    9 +
 ggml/include/ggml-cann.h                      |  125 +
 ggml/include/ggml.h                           |    3 +
 ggml/src/CMakeLists.txt                       |   69 +
 ggml/src/ggml-backend.c                       |    5 +
 ggml/src/ggml-cann.cpp                        | 2023 +++++++++++
 ggml/src/ggml-cann/.clang-format              |  168 +
 ggml/src/ggml-cann/Doxyfile                   | 2579 +++++++++++++++
 ggml/src/ggml-cann/acl_tensor.cpp             |  198 ++
 ggml/src/ggml-cann/acl_tensor.h               |  230 ++
 ggml/src/ggml-cann/aclnn_ops.cpp              | 2944 +++++++++++++++++
 ggml/src/ggml-cann/aclnn_ops.h                |  592 ++++
 ggml/src/ggml-cann/common.h                   |  282 ++
 ggml/src/ggml-cann/kernels/CMakeLists.txt     |   32 +
 ggml/src/ggml-cann/kernels/ascendc_kernels.h  |   17 +
 ggml/src/ggml-cann/kernels/dup.cpp            |  223 ++
 ggml/src/ggml-cann/kernels/get_row_f16.cpp    |  186 ++
 ggml/src/ggml-cann/kernels/get_row_f32.cpp    |  180 +
 ggml/src/ggml-cann/kernels/get_row_q4_0.cpp   |  193 ++
 ggml/src/ggml-cann/kernels/get_row_q8_0.cpp   |  191 ++
 .../ggml-cann/kernels/quantize_f16_q8_0.cpp   |  208 ++
 .../ggml-cann/kernels/quantize_f32_q8_0.cpp   |  206 ++
 ggml/src/ggml.c                               |   11 +-
 src/llama.cpp                                 |   41 +
 tests/test-backend-ops.cpp                    |   33 +-
 27 files changed, 10756 insertions(+), 8 deletions(-)
 create mode 100644 ggml/include/ggml-cann.h
 create mode 100644 ggml/src/ggml-cann.cpp
 create mode 100644 ggml/src/ggml-cann/.clang-format
 create mode 100644 ggml/src/ggml-cann/Doxyfile
 create mode 100644 ggml/src/ggml-cann/acl_tensor.cpp
 create mode 100644 ggml/src/ggml-cann/acl_tensor.h
 create mode 100644 ggml/src/ggml-cann/aclnn_ops.cpp
 create mode 100644 ggml/src/ggml-cann/aclnn_ops.h
 create mode 100644 ggml/src/ggml-cann/common.h
 create mode 100644 ggml/src/ggml-cann/kernels/CMakeLists.txt
 create mode 100644 ggml/src/ggml-cann/kernels/ascendc_kernels.h
 create mode 100644 ggml/src/ggml-cann/kernels/dup.cpp
 create mode 100644 ggml/src/ggml-cann/kernels/get_row_f16.cpp
 create mode 100644 ggml/src/ggml-cann/kernels/get_row_f32.cpp
 create mode 100644 ggml/src/ggml-cann/kernels/get_row_q4_0.cpp
 create mode 100644 ggml/src/ggml-cann/kernels/get_row_q8_0.cpp
 create mode 100644 ggml/src/ggml-cann/kernels/quantize_f16_q8_0.cpp
 create mode 100644 ggml/src/ggml-cann/kernels/quantize_f32_q8_0.cpp

diff --git a/CMakeLists.txt b/CMakeLists.txt
index 67dcf86d4fab7..7937091227ad4 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -106,6 +106,7 @@ llama_option_depr(WARNING     LLAMA_NATIVE              GGML_NATIVE)
 llama_option_depr(WARNING     LLAMA_RPC                 GGML_RPC)
 llama_option_depr(WARNING     LLAMA_SYCL                GGML_SYCL)
 llama_option_depr(WARNING     LLAMA_SYCL_F16            GGML_SYCL_F16)
+llama_option_depr(WARNING     LLAMA_CANN                GGML_CANN)
 
 #
 # build the library
diff --git a/examples/llama-bench/llama-bench.cpp b/examples/llama-bench/llama-bench.cpp
index d641a9f12b388..a6497b6e0bf82 100644
--- a/examples/llama-bench/llama-bench.cpp
+++ b/examples/llama-bench/llama-bench.cpp
@@ -23,6 +23,10 @@
 #include "ggml-cuda.h"
 #include "ggml-sycl.h"
 
+#ifdef GGML_USE_CANN
+#include "ggml-cann.h"
+#endif
+
 // utils
 static uint64_t get_time_ns() {
     using clock = std::chrono::high_resolution_clock;
@@ -120,6 +124,17 @@ static std::string get_gpu_info() {
             id += "/";
         }
     }
+#endif
+#ifdef GGML_USE_CANN
+    uint32_t count = ggml_backend_cann_get_device_count();
+    for (uint32_t i = 0; i < count; i++) {
+        char buf[128];
+        ggml_backend_cann_get_device_description(i, buf, sizeof(buf));
+        id += buf;
+        if (i < count - 1) {
+            id += "/";
+        }
+    }
 #endif
     // TODO: other backends
     return id;
diff --git a/examples/llava/clip.cpp b/examples/llava/clip.cpp
index d6882eec31e1a..d23e282fbe655 100644
--- a/examples/llava/clip.cpp
+++ b/examples/llava/clip.cpp
@@ -16,6 +16,10 @@
 #include "ggml-metal.h"
 #endif
 
+#ifdef GGML_USE_CANN
+#include "ggml-cann.h"
+#endif
+
 #define STB_IMAGE_IMPLEMENTATION
 #include "stb_image.h"
 
@@ -1001,6 +1005,11 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) {
     LOG_TEE("%s: CLIP using Metal backend\n", __func__);
 #endif
 
+#ifdef GGML_USE_CANN
+    new_clip->backend = ggml_backend_cann_init(0);
+    LOG_TEE("%s: CLIP using CANN backend\n", __func__);
+#endif
+
 
     if (!new_clip->backend) {
         new_clip->backend = ggml_backend_cpu_init();
diff --git a/ggml/include/ggml-cann.h b/ggml/include/ggml-cann.h
new file mode 100644
index 0000000000000..ca73211fea736
--- /dev/null
+++ b/ggml/include/ggml-cann.h
@@ -0,0 +1,125 @@
+/*
+ * Copyright (c) 2023-2024 The ggml authors
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
+ * IN THE SOFTWARE.
+ */
+
+#pragma once
+
+#include "ggml-backend.h"
+#include "ggml.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/**
+ * @brief Maximum number of CANN devices supported.
+ */
+#define GGML_CANN_MAX_DEVICES 16
+
+/**
+ * @brief Initializes the CANN backend for a specified device.
+ *
+ * This function initializes the CANN backend for the given device.
+ * It verifies the device index, allocates a context, and creates a backend
+ * instance.
+ *
+ * @param device The index of the device to initialize.
+ * @return A pointer to the initialized backend instance, or nullptr on failure.
+ */
+GGML_API GGML_CALL ggml_backend_t ggml_backend_cann_init(int32_t device);
+
+/**
+ * @brief Checks if a given backend is a CANN backend.
+ *
+ * This function verifies if the provided backend is a CANN backend by comparing
+ * its GUID with the CANN backend's GUID.
+ *
+ * @param backend The backend instance to check.
+ * @return True if the backend is a CANN backend, false otherwise.
+ */
+GGML_API GGML_CALL bool ggml_backend_is_cann(ggml_backend_t backend);
+
+/**
+ * @brief Retrieves the CANN buffer type for a specified device.
+ *
+ * This function initializes and returns the buffer type interface associated
+ * with the given device. It ensures thread-safe access using a mutex.
+ *
+ * @param device The device index for which to retrieve the buffer type.
+ * @return A pointer to the buffer type interface for the specified device, or
+ * nullptr if the device index is out of range.
+ */
+GGML_API GGML_CALL ggml_backend_buffer_type_t
+ggml_backend_cann_buffer_type(int32_t device);
+
+/**
+ * @brief Retrieves the number of CANN devices available.
+ *
+ * This function returns the number of CANN devices available based on
+ * information obtained from `ggml_cann_info()`.
+ *
+ * @return The number of CANN devices available.
+ */
+GGML_API GGML_CALL int32_t ggml_backend_cann_get_device_count(void);
+
+/**
+ * @brief Retrieves the description of a specific CANN device.
+ *
+ * This function sets the specified device, retrieves the SoC name,
+ * and writes it into the provided description buffer.
+ *
+ * @param device The device index to retrieve the description for.
+ * @param description Pointer to a buffer where the description will be written.
+ * @param description_size Size of the description buffer.
+ */
+GGML_API GGML_CALL void ggml_backend_cann_get_device_description(
+    int32_t device, char* description, size_t description_size);
+
+/**
+ * @brief Retrieves the memory information of a specific CANN device.
+ *
+ * This function sets the specified device, retrieves the free and total
+ * memory information of the specified type (ACL_HBM_MEM), and stores them
+ * in the provided pointers.
+ *
+ * @param device The device index to retrieve memory information for.
+ * @param free Pointer to a variable where the free memory size will be stored.
+ * @param total Pointer to a variable where the total memory size will be
+ * stored.
+ */
+GGML_API GGML_CALL void ggml_backend_cann_get_device_memory(int32_t device,
+                                                            size_t* free,
+                                                            size_t* total);
+
+/**
+ * @brief Set the logging callback for GGML.
+ *
+ * This function sets the logging callback and user data for logging.
+ *
+ * @param log_callback The logging callback to set.
+ * @param user_data User data to pass to the logging callback.
+ */
+GGML_API void ggml_backend_cann_log_set_callback(ggml_log_callback log_callback,
+                                                 void* user_data);
+
+#ifdef __cplusplus
+}
+#endif
diff --git a/ggml/include/ggml.h b/ggml/include/ggml.h
index f2145ff356cbd..2fdb9fa40274b 100644
--- a/ggml/include/ggml.h
+++ b/ggml/include/ggml.h
@@ -753,6 +753,8 @@ extern "C" {
     GGML_API bool ggml_are_same_shape (const struct ggml_tensor * t0, const struct ggml_tensor * t1);
     GGML_API bool ggml_are_same_stride(const struct ggml_tensor * t0, const struct ggml_tensor * t1);
 
+    GGML_API bool ggml_can_repeat(const struct ggml_tensor * t0, const struct ggml_tensor * t1);
+
     // use this to compute the memory overhead of a tensor
     GGML_API size_t ggml_tensor_overhead(void);
 
@@ -2397,6 +2399,7 @@ extern "C" {
     GGML_API int ggml_cpu_has_rpc        (void);
     GGML_API int ggml_cpu_has_vsx        (void);
     GGML_API int ggml_cpu_has_matmul_int8(void);
+    GGML_API int ggml_cpu_has_cann       (void);
 
     //
     // Internal types and functions exposed for tests and benchmarks
diff --git a/ggml/src/CMakeLists.txt b/ggml/src/CMakeLists.txt
index cbadaf4d931c3..3f4c66bf70fc9 100644
--- a/ggml/src/CMakeLists.txt
+++ b/ggml/src/CMakeLists.txt
@@ -770,6 +770,74 @@ if (GGML_CPU_HBM)
     target_link_libraries(ggml PUBLIC memkind)
 endif()
 
+if (GGML_CANN)
+    if ("cann${CANN_INSTALL_DIR}" STREQUAL "cann" AND DEFINED ENV{ASCEND_TOOLKIT_HOME})
+        set(CANN_INSTALL_DIR $ENV{ASCEND_TOOLKIT_HOME})
+        message(STATUS "CANN: updated CANN_INSTALL_DIR from ASCEND_TOOLKIT_HOME=$ENV{ASCEND_TOOLKIT_HOME}")
+    endif()
+
+    if (CANN_INSTALL_DIR)
+        # Only Support Linux.
+        if (GGML_CANN)
+            if (NOT UNIX)
+                set(GGML_CANN OFF)
+                message(WARNING "CANN: CANN toolkit supports unix but not ${CMAKE_SYSTEM_NAME}. Turning off GGML_CANN")
+            endif()
+        endif()
+
+        # Supported platforms: x86-64, arm64
+        if (GGML_CANN)
+            if (CMAKE_SYSTEM_PROCESSOR STREQUAL "aarch64")
+            elseif (CMAKE_SYSTEM_PROCESSOR STREQUAL "x86_64" OR CMAKE_SYSTEM_PROCESSOR STREQUAL "amd64")
+            else()
+                set(GGML_CANN OFF)
+                message(WARNING "CANN: CANN toolkit supports x86-64 and arm64 but not ${CMAKE_SYSTEM_PROCESSOR}. Turning off GGML_CANN")
+            endif()
+        endif()
+
+        # Set header and libs
+        if(GGML_CANN)
+            set(CANN_INCLUDE_DIRS
+                ${CANN_INSTALL_DIR}/include
+                ${CANN_INSTALL_DIR}/include/aclnn
+                ${CANN_INSTALL_DIR}/acllib/include
+            )
+
+            # TODO: find libs
+            link_directories(
+                ${CANN_INSTALL_DIR}/lib64
+            )
+
+            add_subdirectory(ggml-cann/kernels)
+            list(APPEND CANN_LIBRARIES
+                ascendcl
+                nnopbase
+                opapi
+                acl_op_compiler
+                ascendc_kernels
+            )
+
+            set(GGML_HEADERS_CANN "../include/ggml-cann.h")
+            file(GLOB GGML_SOURCES_CANN "ggml-cann/*.cpp")
+            list(APPEND GGML_SOURCES_CANN "ggml-cann.cpp")
+
+            message(STATUS "CANN: CANN_INCLUDE_DIRS =  ${CANN_INCLUDE_DIRS}")
+            message(STATUS "CANN: CANN_LIBRARIES =  ${CANN_LIBRARIES}")
+
+            set(GGML_EXTRA_LIBS     ${GGML_EXTRA_LIBS}     ${CANN_LIBRARIES} )
+            set(GGML_EXTRA_INCLUDES ${GGML_EXTRA_INCLUDES} ${CANN_INCLUDE_DIRS})
+            list(APPEND GGML_CDEF_PUBLIC GGML_USE_CANN)
+        endif()
+    else()
+        set(GGML_CANN OFF)
+        message(WARNING "CANN: Can't find CANN_INSTALL_DIR, do you forget to source set_var.sh. Turning off GGML_CANN")
+    endif()
+
+    if(NOT GGML_CANN)
+        message(WARNING "CANN: GGML_CANN is turned OFF, see above for details.")
+    endif()
+endif()
+
 function(get_flags CCID CCVER)
     set(C_FLAGS "")
     set(CXX_FLAGS "")
@@ -1184,6 +1252,7 @@ add_library(ggml
             ${GGML_SOURCES_ROCM}      ${GGML_HEADERS_ROCM}
             ${GGML_SOURCES_BLAS}      ${GGML_HEADERS_BLAS}
             ${GGML_SOURCES_LLAMAFILE} ${GGML_HEADERS_LLAMAFILE}
+            ${GGML_SOURCES_CANN}      ${GGML_HEADERS_CANN}
             ggml-aarch64.c            ggml-aarch64.h
             )
 
diff --git a/ggml/src/ggml-backend.c b/ggml/src/ggml-backend.c
index dbbaa3941febe..01c87efd0db6e 100644
--- a/ggml/src/ggml-backend.c
+++ b/ggml/src/ggml-backend.c
@@ -445,6 +445,11 @@ GGML_CALL static void ggml_backend_registry_init(void) {
     extern GGML_CALL void ggml_backend_kompute_reg_devices(void);
     ggml_backend_kompute_reg_devices();
 #endif
+
+#ifdef GGML_USE_CANN
+    extern GGML_CALL int ggml_backend_cann_reg_devices(void);
+    ggml_backend_cann_reg_devices();
+#endif
 }
 
 GGML_CALL void ggml_backend_register(const char * name, ggml_backend_init_fn init_fn, ggml_backend_buffer_type_t default_buffer_type, void * user_data) {
diff --git a/ggml/src/ggml-cann.cpp b/ggml/src/ggml-cann.cpp
new file mode 100644
index 0000000000000..9bf7e332a7e06
--- /dev/null
+++ b/ggml/src/ggml-cann.cpp
@@ -0,0 +1,2023 @@
+/*
+ * Copyright (c) 2023-2024 The ggml authors
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
+ * IN THE SOFTWARE.
+ */
+
+#include "ggml-cann.h"
+
+#include 
+#include 
+
+#include 
+#include 
+#include 
+#include 
+
+#include "ggml-backend-impl.h"
+#include "ggml-cann/aclnn_ops.h"
+#include "ggml-cann/common.h"
+
+#define GGML_COMMON_DECL_C
+
+#include "ggml-common.h"
+
+/**
+ * @brief Default logging callback for GGML.
+ *
+ * This function is the default logging callback that logs messages to stderr.
+ *
+ * @param level The log level.
+ * @param msg The log message.
+ * @param user_data User data passed to the callback.
+ */
+static void ggml_cann_default_log_callback(enum ggml_log_level level,
+                                           const char* msg, void* user_data) {
+    GGML_UNUSED(level);
+    GGML_UNUSED(user_data);
+    fprintf(stderr, "%s", msg);
+}
+
+ggml_log_callback ggml_cann_log_callback = ggml_cann_default_log_callback;
+void* ggml_cann_log_user_data = NULL;
+
+GGML_API void ggml_backend_cann_log_set_callback(ggml_log_callback log_callback,
+                                                 void* user_data) {
+    ggml_cann_log_callback = log_callback;
+    ggml_cann_log_user_data = user_data;
+}
+
+#define GGML_CANN_LOG_INFO(...) ggml_cann_log(GGML_LOG_LEVEL_INFO, __VA_ARGS__)
+#define GGML_CANN_LOG_WARN(...) ggml_cann_log(GGML_LOG_LEVEL_WARN, __VA_ARGS__)
+#define GGML_CANN_LOG_ERROR(...) \
+    ggml_cann_log(GGML_LOG_LEVEL_ERROR, __VA_ARGS__)
+
+GGML_ATTRIBUTE_FORMAT(2, 3)
+
+/**
+ * @brief Log a message using the current logging callback.
+ *
+ * This function formats a log message and passes it to the current logging
+ * callback.
+ *
+ * @param level The log level.
+ * @param format The format string for the log message.
+ * @param ... The arguments for the format string.
+ */
+static void ggml_cann_log(enum ggml_log_level level, const char* format, ...) {
+    if (ggml_cann_log_callback != NULL) {
+        va_list args;
+        va_start(args, format);
+        char buffer[128];
+        int len = vsnprintf(buffer, 128, format, args);
+        if (len < 128) {
+            ggml_cann_log_callback(level, buffer, ggml_cann_log_user_data);
+        } else {
+             // vsnprintf adds a null terminator
+            std::vector buffer2(len + 1);
+            va_end(args);
+            va_start(args, format);
+            vsnprintf(&buffer2[0], buffer2.size(), format, args);
+            ggml_cann_log_callback(level, buffer2.data(),
+                                   ggml_cann_log_user_data);
+        }
+        va_end(args);
+    }
+}
+
+/**
+ * @brief Handles CANN errors by printing an error message and aborting.
+ *
+ * @param stmt The statement that caused the error.
+ * @param func The function in which the error occurred.
+ * @param file The file in which the error occurred.
+ * @param line The line number where the error occurred.
+ * @param msg The error message.
+ */
+[[noreturn]] void ggml_cann_error(const char* stmt, const char* func,
+                                  const char* file, int line, const char* msg) {
+    int32_t id = -1;
+    aclrtGetDevice(&id);
+
+    GGML_CANN_LOG_ERROR("CANN error: %s\n", msg);
+    GGML_CANN_LOG_ERROR("  current device: %d, in function %s at %s:%d\n", id, func,
+            file, line);
+    GGML_CANN_LOG_ERROR("  %s\n", stmt);
+    // abort with GGML_ASSERT to get a stack trace
+    GGML_ASSERT(!"CANN error");
+}
+
+/**
+ * @brief Sets the device to be used by CANN.
+ *
+ * @param device The device ID to set.
+ */
+void ggml_cann_set_device(const int32_t device) {
+    // TODO: uncomment these lines after empty context has fixed.
+    // int current_device;
+    // ACL_CHECK(aclrtGetDevice(¤t_device));
+
+    // if (device == current_device) {
+    //   return;
+    // }
+    ACL_CHECK(aclrtSetDevice(device));
+}
+
+/**
+ * @brief Retrieves the current device ID.
+ *
+ * @return The current device ID.
+ */
+int32_t ggml_cann_get_device() {
+    int32_t id;
+    ACL_CHECK(aclrtGetDevice(&id));
+    return id;
+}
+
+/**
+ * @brief Initialize the CANN device information.
+ *
+ * This function initializes the CANN device information by obtaining the
+ * device count and setting the memory allocation granularity for each device.
+ *
+ * @return A structure containing the device information.
+ */
+static ggml_cann_device_info ggml_cann_init() {
+    ggml_cann_device_info info = {};
+
+    aclError err = aclrtGetDeviceCount((uint32_t*)&info.device_count);
+
+    if (err != ACL_SUCCESS) {
+        GGML_CANN_LOG_ERROR("%s: failed to initialize CANN: %s\n",
+                __func__, aclGetRecentErrMsg());
+        return info;
+    }
+
+    GGML_ASSERT(info.device_count <= GGML_CANN_MAX_DEVICES);
+
+    for (int id = 0; id < info.device_count; ++id) {
+        aclrtPhysicalMemProp prop = {};
+        prop.handleType = ACL_MEM_HANDLE_TYPE_NONE;
+        prop.allocationType = ACL_MEM_ALLOCATION_TYPE_PINNED;
+        prop.memAttr = ACL_HBM_MEM_HUGE;
+        prop.location.type = ACL_MEM_LOCATION_TYPE_DEVICE;
+        prop.location.id = id;
+        prop.reserve = 0;
+        ACL_CHECK(aclrtMemGetAllocationGranularity(
+            &prop, ACL_RT_MEM_ALLOC_GRANULARITY_RECOMMENDED,
+            &info.devices[id].vmm_granularity));
+    }
+
+    // TODO: add more device info later.
+    return info;
+}
+
+/**
+ * @brief Retrieve the CANN device information.
+ *
+ * This function returns a reference to a structure containing the CANN device
+ * information. The device information is initialized once and reused on
+ * subsequent calls.
+ *
+ * @return A reference to the structure containing the device information.
+ */
+const ggml_cann_device_info& ggml_cann_info() {
+    static ggml_cann_device_info info = ggml_cann_init();
+    return info;
+}
+
+//#define DEBUG_CANN_MALLOC
+/**
+ * @brief A pool of CANN buffers(legacy).
+ *
+ * This class manages a pool of CANN buffers for a specific device.
+ */
+struct ggml_cann_pool_leg : public ggml_cann_pool {
+    /**
+     * @brief The maximum number of buffers in the pool.
+     */
+    static const int MAX_BUFFERS = 256;
+
+    /**
+     * @brief The device ID associated with this buffer pool.
+     */
+    int device;
+
+    /**
+     * @brief Structure representing a CANN buffer.
+     */
+    struct ggml_cann_buffer {
+        void* ptr = nullptr;  ///< Pointer to the buffer memory.
+        size_t size = 0;      ///< Size of the buffer.
+    };
+
+    /**
+     * @brief Array of CANN buffers in the pool.
+     */
+    ggml_cann_buffer buffer_pool[MAX_BUFFERS] = {};
+
+    /**
+     * @brief Total size of all buffers in the pool.
+     */
+    size_t pool_size = 0;
+
+    /**
+     * @brief Constructor to initialize the buffer pool for a specific device.
+     *
+     * @param device The device ID to associate with this buffer pool.
+     */
+    explicit ggml_cann_pool_leg(int device) : device(device) {}
+
+    /**
+     * @brief Destructor to free all buffers in the pool.
+     */
+    ~ggml_cann_pool_leg() {
+        ggml_cann_set_device(device);
+        for (int i = 0; i < MAX_BUFFERS; ++i) {
+            ggml_cann_buffer& b = buffer_pool[i];
+            if (b.ptr != nullptr) {
+                ACL_CHECK(aclrtFree(b.ptr));
+                pool_size -= b.size;
+            }
+        }
+        GGML_ASSERT(pool_size == 0);
+    }
+
+    /**
+     * @brief Allocate a buffer of the given size.
+     *
+     * @param size The size of the buffer to allocate.
+     * @param actual_size A pointer to a variable to receive the actual size of
+     * the allocated buffer.
+     * @return A pointer to the allocated buffer.
+     */
+    void* alloc(size_t size, size_t* actual_size) override {
+#ifdef DEBUG_CANN_MALLOC
+        int nnz = 0;
+        size_t max_size = 0;
+#endif
+        size_t best_diff = 1ull << 36;
+        int ibest = -1;
+        for (int i = 0; i < MAX_BUFFERS; ++i) {
+            ggml_cann_buffer& b = buffer_pool[i];
+            if (b.ptr != nullptr) {
+#ifdef DEBUG_CANN_MALLOC
+                ++nnz;
+                if (b.size > max_size) max_size = b.size;
+#endif
+                if (b.size >= size) {
+                    size_t diff = b.size - size;
+                    if (diff < best_diff) {
+                        best_diff = diff;
+                        ibest = i;
+                        if (!best_diff) {
+                            void* ptr = b.ptr;
+                            *actual_size = b.size;
+                            b.ptr = nullptr;
+                            b.size = 0;
+                            return ptr;
+                        }
+                    }
+                }
+            }
+        }
+        if (ibest >= 0) {
+            ggml_cann_buffer& b = buffer_pool[ibest];
+            void* ptr = b.ptr;
+            *actual_size = b.size;
+            b.ptr = nullptr;
+            b.size = 0;
+            return ptr;
+        }
+        void* ptr;
+        size_t look_ahead_size = (size_t)(1.05 * size);
+        look_ahead_size = 256 * ((look_ahead_size + 255) / 256);
+        ggml_cann_set_device(device);
+        ACL_CHECK(
+            aclrtMalloc(&ptr, look_ahead_size, ACL_MEM_MALLOC_HUGE_FIRST));
+        *actual_size = look_ahead_size;
+        pool_size += look_ahead_size;
+#ifdef DEBUG_CANN_MALLOC
+        GGML_CANN_LOG_INFO(
+            "%s[%d]: %d buffers, max_size = %u MB, pool_size = %u MB, "
+            "requested %u MB\n",
+            __func__, device, nnz, (uint32_t)(max_size / 1024 / 1024),
+            (uint32_t)(pool_size / 1024 / 1024),
+            (uint32_t)(size / 1024 / 1024));
+#endif
+        return ptr;
+    }
+
+    /**
+     * @brief Free a buffer and return it to the pool.
+     *
+     * @param ptr Pointer to the buffer to free.
+     * @param size Size of the buffer to free.
+     */
+    void free(void* ptr, size_t size) override {
+        for (int i = 0; i < MAX_BUFFERS; ++i) {
+            ggml_cann_buffer& b = buffer_pool[i];
+            if (b.ptr == nullptr) {
+                b.ptr = ptr;
+                b.size = size;
+                return;
+            }
+        }
+        // memory should always buffered. these memory may still needed by
+        // tasks in stream.
+        // TODO, fix me.
+        GGML_ASSERT(!"Cann buffer pool full, increase MAX_CANN_BUFFERS\n");
+    }
+};
+
+/**
+ * @brief A pool of CANN buffers with virtual memory.
+ *
+ * This class manages a pool of CANN buffers with virtual memory for a specific
+ * device.
+ */
+struct ggml_cann_pool_vmm : public ggml_cann_pool {
+    /**
+     * @brief The maximum size of the virtual memory pool (32 GB).
+     */
+    static const size_t CANN_POOL_VMM_MAX_SIZE = 1ull << 35;  // 32 GB
+
+    /**
+     * @brief The device ID associated with this buffer pool.
+     */
+    int device;
+
+    /**
+     * @brief Pointer to the start of the virtual memory pool.
+     */
+    void* pool_addr = 0;
+
+    /**
+     * @brief Amount of virtual memory used in the pool.
+     */
+    size_t pool_used = 0;
+
+    /**
+     * @brief Total size of the virtual memory pool.
+     */
+    size_t pool_size = 0;
+
+    /**
+     * @brief Allocation granularity for the virtual memory pool.
+     */
+    size_t granularity;
+
+    /**
+     * @brief Handles for the physical memory allocated.
+     */
+    std::vector handles;
+
+    /**
+     * @brief Offsets for the mapped memory regions.
+     */
+    std::vector map_offsets;
+
+    /**
+     * @brief Constructor to initialize the buffer pool with virtual memory for
+     * a specific device.
+     *
+     * @param device The device ID to associate with this buffer pool.
+     */
+    explicit ggml_cann_pool_vmm(int device)
+        : device(device),
+          granularity(ggml_cann_info().devices[device].vmm_granularity) {}
+
+    /**
+     * @brief Destructor to free all buffers in the virtual memory pool.
+     */
+    ~ggml_cann_pool_vmm() {
+        if (pool_addr != 0) {
+            for (auto& offset : map_offsets) {
+                ACL_CHECK(aclrtUnmapMem(offset));
+            }
+            for (auto& handle : handles) {
+                ACL_CHECK(aclrtFreePhysical(handle));
+            }
+            ACL_CHECK(aclrtReleaseMemAddress(pool_addr));
+        }
+    }
+
+    /**
+     * @brief Allocate a buffer of the given size in the virtual memory pool.
+     *
+     * @param size The size of the buffer to allocate.
+     * @param actual_size A pointer to a variable to receive the actual size of
+     * the allocated buffer.
+     * @return A pointer to the allocated buffer.
+     */
+    void* alloc(size_t size, size_t* actual_size) override {
+        // round up the allocation size to the alignment to ensure that all
+        // allocations are aligned for all data types
+        const size_t alignment = 128;
+        size = alignment * ((size + alignment - 1) / alignment);
+
+        size_t avail = pool_size - pool_used;
+
+        if (size > avail) {
+            // round up to the next multiple of the granularity
+            size_t reserve_size = size - avail;
+            reserve_size =
+                granularity * ((reserve_size + granularity - 1) / granularity);
+
+            GGML_ASSERT(pool_size + reserve_size <= CANN_POOL_VMM_MAX_SIZE);
+
+            // allocate more physical memory
+            aclrtPhysicalMemProp prop = {};
+            prop.handleType = ACL_MEM_HANDLE_TYPE_NONE;
+            prop.allocationType = ACL_MEM_ALLOCATION_TYPE_PINNED;
+            prop.memAttr = ACL_HBM_MEM_HUGE;
+            prop.location.type = ACL_MEM_LOCATION_TYPE_DEVICE;
+            prop.location.id = device;
+            prop.reserve = 0;
+            aclrtDrvMemHandle handle;
+            ACL_CHECK(aclrtMallocPhysical(&handle, reserve_size, &prop, 0));
+
+            // reserve virtual address space (if not already reserved)
+            if (pool_addr == 0) {
+                ACL_CHECK(aclrtReserveMemAddress(
+                    &pool_addr, CANN_POOL_VMM_MAX_SIZE, 0, NULL, 1));
+            }
+
+            // map at the end of the pool
+            ACL_CHECK(aclrtMapMem((char*)pool_addr + pool_size, reserve_size, 0,
+                                  handle, 0));
+
+            handles.push_back(handle);
+            map_offsets.push_back((char*)pool_addr + pool_size);
+
+            // add to the pool
+            pool_size += reserve_size;
+
+            // GGML_CANN_LOG_INFO("cann pool[%d]: size increased to %llu MB (
+            // reserved %llu MB)\n",
+            //       device, (unsigned long long) (pool_size/1024/1024),
+            //       (unsigned long long) (reserve_size/1024/1024));
+        }
+
+        GGML_ASSERT(pool_addr != 0);
+
+        void* ptr = (void*)((char*)pool_addr + pool_used);
+        *actual_size = size;
+        pool_used += size;
+
+#ifdef DEBUG_CANN_MALLOC
+        GGML_CANN_LOG_INFO("cann pool[%d]: allocated %llu bytes at %llx\n", device,
+               (unsigned long long)size, (unsigned long long)ptr);
+#endif
+        return ptr;
+    }
+
+    /**
+     * @brief Free a buffer and return it to the virtual memory pool.
+     *
+     * @param ptr Pointer to the buffer to free.
+     * @param size Size of the buffer to free.
+     */
+    void free(void* ptr, size_t size) override {
+#ifdef DEBUG_CANN_MALLOC
+        GGML_CANN_LOG_INFO("cann pool[%d]: freed %llu bytes at %llx\n", device,
+               (unsigned long long)size, (unsigned long long)ptr);
+#endif
+
+        pool_used -= size;
+
+        // all deallocations must be in reverse order of the allocations
+        GGML_ASSERT(ptr == (void*)((char*)pool_addr + pool_used));
+    }
+};
+
+/**
+ * @brief Create a new CANN pool for a specific device.
+ *
+ * Factory method to create a new CANN pool object based on the device type.
+ *
+ * @param device The device ID for which to create the pool.
+ * @return A unique pointer to the created CANN pool.
+ */
+std::unique_ptr ggml_backend_cann_context::new_pool_for_device(
+    int device) {
+    // return std::unique_ptr(new ggml_cann_pool_leg(device));
+    return std::unique_ptr(new ggml_cann_pool_vmm(device));
+}
+
+// cann buffer
+/**
+ * @brief Context for managing a CANN buffer associated with a specific device.
+ *
+ * This structure holds information about a CANN buffer, including the device
+ * ID, device pointer, and a name derived from GGML_CANN_NAME and the device ID.
+ */
+struct ggml_backend_cann_buffer_context {
+    int32_t device;  ///< The device ID associated with this buffer context.
+    void* dev_ptr =
+        nullptr;  ///< Pointer to the device memory allocated for the buffer.
+
+    /**
+     * @brief Constructor to initialize the CANN buffer context.
+     *
+     * @param device The device ID associated with this buffer context.
+     * @param dev_ptr Pointer to the device memory allocated for the buffer.
+     */
+    ggml_backend_cann_buffer_context(int32_t device, void* dev_ptr)
+        : device(device),
+          dev_ptr(dev_ptr) {}
+
+    /**
+     * @brief Destructor to free the device memory allocated for the buffer.
+     */
+    ~ggml_backend_cann_buffer_context() { ACL_CHECK(aclrtFree(dev_ptr)); }
+};
+
+/**
+ * @brief Retrieve the name associated with a CANN buffer.
+ *
+ * This function returns the name of a CANN buffer, which is stored in the
+ * context of the buffer.
+ *
+ * @param buffer The CANN buffer whose name is to be retrieved.
+ * @return A pointer to a C-string containing the name of the buffer.
+ */
+
+GGML_CALL static const char* ggml_backend_cann_buffer_get_name(
+    ggml_backend_buffer_t buffer) {
+    return "CANN";
+
+    GGML_UNUSED(buffer);
+}
+
+/**
+ * @brief Check if a buffer is a CANN buffer.
+ *
+ * This function checks if a given buffer is a CANN buffer by comparing its
+ * `get_name` function pointer to `ggml_backend_cann_buffer_get_name`.
+ *
+ * @param buffer The buffer to check.
+ * @return true if the buffer is a CANN buffer, false otherwise.
+ */
+GGML_CALL static bool ggml_backend_buffer_is_cann(
+    ggml_backend_buffer_t buffer) {
+    return buffer->iface.get_name == ggml_backend_cann_buffer_get_name;
+}
+
+/**
+ * @brief Free resources associated with a CANN buffer.
+ *
+ * This function frees the resources associated with a CANN buffer, including
+ * its context.
+ *
+ * @param buffer The CANN buffer to free.
+ */
+GGML_CALL static void ggml_backend_cann_buffer_free_buffer(
+    ggml_backend_buffer_t buffer) {
+    ggml_backend_cann_buffer_context* ctx =
+        (ggml_backend_cann_buffer_context*)buffer->context;
+    delete ctx;
+}
+
+/**
+ * @brief Retrieve the base pointer of a CANN buffer.
+ *
+ * This function returns the base pointer of a CANN buffer, which points to the
+ * device memory allocated for the buffer.
+ *
+ * @param buffer The CANN buffer whose base pointer is to be retrieved.
+ * @return A pointer to the base of the device memory allocated for the buffer.
+ */
+GGML_CALL static void* ggml_backend_cann_buffer_get_base(
+    ggml_backend_buffer_t buffer) {
+    ggml_backend_cann_buffer_context* ctx =
+        (ggml_backend_cann_buffer_context*)buffer->context;
+    return ctx->dev_ptr;
+}
+
+/**
+ * @brief Transform quantized Q4.0 tensor data into a format suitable for CANN
+ * processing.
+ *
+ * This function transforms quantized Q4.0 tensor data into a format suitable
+ * for CANN processing. It extracts quantization values and scales from the
+ * source data and prepares them in a format expected by CANN operations.
+ *
+ * @param tensor Pointer to the tensor information.
+ * @param src Pointer to the source data in Q4.0 format.
+ * @param dst Pointer to the destination buffer where transformed data will be
+ * stored.
+ */
+GGML_CALL static void ggml_backend_cann_transform_q4_0(ggml_tensor* tensor,
+                                                       const void* src,
+                                                       void* dst) {
+    GGML_ASSERT(tensor->op == GGML_OP_NONE);
+
+    int64_t n_elems = ggml_nelements(tensor);
+    int64_t groups = n_elems / QK4_0;
+    size_t quant_bytes = n_elems * sizeof(uint8_t) / 2;
+
+    uint8_t* quant_offset = (uint8_t*)dst;
+    uint16_t* scale_offset = (uint16_t*)((char*)dst + quant_bytes);
+
+    for (int i = 0; i < groups; i++) {
+        const block_q4_0* group =
+            (const block_q4_0*)((const char*)src + i * sizeof(block_q4_0));
+        *scale_offset = group->d;
+        scale_offset++;
+
+        // 0-15
+        for (int j = 0; j < QK4_0 / 2; j += 2) {
+            (*quant_offset) = (group->qs[j] & 0x0F);
+            (*quant_offset) |= ((group->qs[j + 1] << 4));
+            quant_offset++;
+        }
+
+        // 16-31
+        for (int j = 0; j < QK4_0 / 2; j += 2) {
+            (*quant_offset) = (group->qs[j] >> 4);
+            (*quant_offset) |= (group->qs[j + 1] & 0xF0);
+            quant_offset++;
+        }
+    }
+
+    // put (uint4b_t -8) into int4b_t
+    for (quant_offset = (uint8_t*)dst;
+         quant_offset < (uint8_t*)dst + quant_bytes; quant_offset++) {
+        (*quant_offset) ^= 0x88;
+    }
+}
+
+/**
+ * @brief Transform CANN processed data back into quantized Q4.0 format.
+ *
+ * This function transforms CANN processed data back into quantized Q4.0 format.
+ * It reverses the transformation performed by
+ * ggml_backend_cann_transform_q4_0(), converting the data back into its
+ * original quantized form.
+ *
+ * @param tensor Pointer to the tensor information.
+ * @param src Pointer to the source buffer containing transformed data.
+ * @param dst Pointer to the destination buffer where the Q4.0 formatted data
+ * will be stored.
+ */
+GGML_CALL static void ggml_backend_cann_transform_back_q4_0(
+    const ggml_tensor* tensor, void* src, void* dst) {
+    GGML_ASSERT(tensor->op == GGML_OP_NONE);
+
+    int64_t n_elems = ggml_nelements(tensor);
+    int64_t groups = n_elems / QK4_0;
+    size_t quant_bytes = n_elems * sizeof(uint8_t) / 2;
+
+    uint8_t* quant_offset = (uint8_t*)src;
+    uint16_t* scale_offset = (uint16_t*)((char*)src + quant_bytes);
+
+    for (; quant_offset < (uint8_t*)src + quant_bytes; quant_offset++) {
+        (*quant_offset) ^= 0x88;
+    }
+    quant_offset = (uint8_t*)src;
+
+    for (int i = 0; i < groups; i++) {
+        block_q4_0* group = (block_q4_0*)((char*)dst + i * sizeof(block_q4_0));
+        group->d = *scale_offset;
+        scale_offset++;
+
+        // 0-15
+        for (int j = 0; j < QK4_0 / 2; j += 2) {
+            group->qs[j] = ((*quant_offset) & 0x0F);
+            group->qs[j + 1] = ((*quant_offset) >> 4);
+            quant_offset++;
+        }
+
+        // 16-31
+        for (int j = 0; j < QK4_0 / 2; j += 2) {
+            group->qs[j] |= ((*quant_offset) << 4);
+            group->qs[j + 1] |= ((*quant_offset) & 0xF0);
+            quant_offset++;
+        }
+    }
+}
+
+/**
+ * @brief Transform quantized Q8.0 tensor data into a format suitable for CANN
+ * processing.
+ *
+ * This function transforms quantized Q8.0 tensor data into a format suitable
+ * for CANN processing. It extracts quantization values and scales from the
+ * source data and prepares them in a format expected by CANN operations.
+ *
+ * @param tensor Pointer to the tensor information.
+ * @param src Pointer to the source data in Q8.0 format.
+ * @param dst Pointer to the destination buffer where transformed data will be
+ * stored.
+ */
+GGML_CALL static void ggml_backend_cann_transform_q8_0(ggml_tensor* tensor,
+                                                       const void* src,
+                                                       void* dst) {
+    int64_t n_elems = ggml_nelements(tensor);
+    int64_t groups = n_elems / QK8_0;
+    size_t quant_bytes = n_elems * sizeof(uint8_t);
+
+    uint8_t* quant_offset = (uint8_t*)dst;
+    uint16_t* scale_offset = (uint16_t*)((char*)dst + quant_bytes);
+
+    for (int i = 0; i < groups; i++) {
+        const block_q8_0* group =
+            (const block_q8_0*)((const char*)src + i * sizeof(block_q8_0));
+        *scale_offset = group->d;
+        scale_offset++;
+        size_t group_quant_size = QK8_0 * sizeof(uint8_t);
+        memcpy(quant_offset, group->qs, group_quant_size);
+        quant_offset += group_quant_size;
+    }
+}
+
+/**
+ * @brief Transform CANN processed data back into quantized Q8.0 format.
+ *
+ * This function transforms CANN processed data back into quantized Q8.0 format.
+ * It reverses the transformation performed by
+ * ggml_backend_cann_transform_q8_0(), converting the data back into its
+ * original quantized form.
+ *
+ * @param tensor Pointer to the tensor information.
+ * @param src Pointer to the source buffer containing transformed data.
+ * @param dst Pointer to the destination buffer where the Q8.0 formatted data
+ * will be stored.
+ */
+GGML_CALL static void ggml_backend_cann_transform_back_q8_0(
+    const ggml_tensor* tensor, const void* src, void* dst) {
+    int64_t n_elems = ggml_nelements(tensor);
+    int64_t groups = n_elems / QK8_0;
+    size_t quant_bytes = n_elems * sizeof(uint8_t);
+
+    const uint8_t* quant_offset = (const uint8_t*)src;
+    const uint16_t* scale_offset =
+        (const uint16_t*)((const char*)src + quant_bytes);
+
+    for (int i = 0; i < groups; i++) {
+        block_q8_0* group = (block_q8_0*)((char*)dst + i * sizeof(block_q8_0));
+        group->d = *scale_offset;
+        scale_offset++;
+        size_t group_quant_size = QK8_0 * sizeof(uint8_t);
+        memcpy(group->qs, quant_offset, group_quant_size);
+        quant_offset += group_quant_size;
+    }
+}
+
+/**
+ * @brief Transform tensor data based on its type for CANN processing.
+ *
+ * This function transforms tensor data based on its quantization type for CANN
+ * processing. It dispatches the transformation based on the tensor's type to
+ * specialized functions handling Q4.0 and Q8.0 formats.
+ *
+ * @param tensor Pointer to the tensor information.
+ * @param src Pointer to the source data to be transformed.
+ * @param dst Pointer to the destination buffer where transformed data will be
+ * stored.
+ */
+GGML_CALL static void ggml_backend_cann_transform(ggml_tensor* tensor,
+                                                  const void* src, void* dst) {
+    switch (tensor->type) {
+        case GGML_TYPE_Q4_0:
+            ggml_backend_cann_transform_q4_0(tensor, src, dst);
+            break;
+        case GGML_TYPE_Q8_0:
+            ggml_backend_cann_transform_q8_0(tensor, src, dst);
+            break;
+        default:
+            break;
+    }
+}
+
+/**
+ * @brief Transform CANN processed data back into tensor data based on its type.
+ *
+ * This function transforms CANN processed data back into tensor data based on
+ * its quantization type for Q4.0 and Q8.0 formats. It dispatches the
+ * transformation based on the tensor's type to specialized functions.
+ *
+ * @param tensor Pointer to the tensor information.
+ * @param src Pointer to the source data containing CANN processed data.
+ * @param dst Pointer to the destination buffer where transformed tensor data
+ * will be stored.
+ */
+GGML_CALL static void ggml_backend_cann_transform_back(
+    const ggml_tensor* tensor, void* src, void* dst) {
+    switch (tensor->type) {
+        case GGML_TYPE_Q4_0:
+            ggml_backend_cann_transform_back_q4_0(tensor, src, dst);
+            break;
+        case GGML_TYPE_Q8_0:
+            ggml_backend_cann_transform_back_q8_0(tensor, src, dst);
+            break;
+        default:
+            break;
+    }
+}
+
+/**
+ * @brief Check if transformation is needed for a given tensor type.
+ *
+ * This function checks if transformation is needed for a given tensor type
+ * to prepare data for CANN processing.
+ *
+ * @param type The tensor type to check.
+ * @return true if transformation is needed, false otherwise.
+ */
+GGML_CALL static bool need_transform(ggml_type type) {
+    switch (type) {
+        case GGML_TYPE_Q4_0:
+        case GGML_TYPE_Q8_0:
+            return true;
+        default:
+            return false;
+    }
+}
+
+/**
+ * @brief Initialize a tensor using data from a CANN buffer.
+ *
+ * This function initializes a tensor using data from a CANN buffer.
+ * It handles special cases such as views and quantization.
+ *
+ * @param buffer The CANN buffer from which to initialize the tensor.
+ * @param tensor Pointer to the tensor to be initialized.
+ */
+GGML_CALL static void ggml_backend_cann_buffer_init_tensor(
+    ggml_backend_buffer_t buffer, ggml_tensor* tensor) {
+    if (tensor->view_src != NULL && tensor->view_offs == 0) {
+        GGML_ASSERT(tensor->view_src->buffer->buft == buffer->buft);
+        return;
+    }
+
+    // TODO: can backend doesn't support quantized yet. Just leave the code
+    // here.
+    if (ggml_is_quantized(tensor->type)) {
+        // Initialize padding to 0 to avoid possible NaN values
+        size_t original_size = ggml_nbytes(tensor);
+        size_t padded_size =
+            ggml_backend_buft_get_alloc_size(buffer->buft, tensor);
+
+        if (padded_size > original_size && tensor->view_src == nullptr) {
+            size_t memset_size = padded_size - original_size;
+            ACL_CHECK(aclrtMemset((char*)tensor->data + original_size,
+                                  memset_size, 0, memset_size));
+        }
+    }
+}
+
+// TODO: need handle tensor which has paddings.
+/**
+ * @brief Set tensor data in a CANN buffer.
+ *
+ * This function sets tensor data in a CANN buffer, handling transformations
+ * if needed based on the tensor's type.
+ *
+ * @param buffer The CANN buffer where the tensor data will be set.
+ * @param tensor Pointer to the tensor whose data will be set.
+ * @param data Pointer to the source data to be copied into the tensor.
+ * @param offset Offset in the source data from where to start copying.
+ * @param size Size of the data to be copied, in bytes.
+ */
+GGML_CALL static void ggml_backend_cann_buffer_set_tensor(
+    ggml_backend_buffer_t buffer, ggml_tensor* tensor, const void* data,
+    size_t offset, size_t size) {
+    // GGML_ASSERT(size == ggml_nbytes(tensor));
+    ggml_backend_cann_buffer_context* ctx =
+        (ggml_backend_cann_buffer_context*)buffer->context;
+
+    ggml_cann_set_device(ctx->device);
+    // TODO: refer to cann(#6017), it use thread's default stream.
+    // For acl, synchronous functions use this default stream.
+    // Why aclrtSynchronizeDevice?
+
+    if (!need_transform(tensor->type)) {
+        ACL_CHECK(aclrtMemcpy(tensor->data, size, (const char*)data + offset,
+                              size, ACL_MEMCPY_HOST_TO_DEVICE));
+    } else {
+        void* transform_buffer = malloc(size);
+        ggml_backend_cann_transform(tensor, (const char*)data + offset,
+                                    transform_buffer);
+
+#ifndef NDEBUG
+        void* check_buffer = malloc(size);
+        ggml_backend_cann_transform_back(tensor, transform_buffer,
+                                         check_buffer);
+        GGML_ASSERT(memcmp((const char*)data + offset, check_buffer, size) ==
+                    0);
+        free(check_buffer);
+#endif
+        ACL_CHECK(aclrtMemcpy(tensor->data, size, transform_buffer, size,
+                              ACL_MEMCPY_HOST_TO_DEVICE));
+        free(transform_buffer);
+    }
+}
+
+/**
+ * @brief Get tensor data from a CANN buffer.
+ *
+ * This function retrieves tensor data from a CANN buffer, handling
+ * transformations if needed based on the tensor's type.
+ *
+ * @param buffer The CANN buffer from which to retrieve tensor data.
+ * @param tensor Pointer to the tensor whose data will be retrieved.
+ * @param data Pointer to the destination buffer where the tensor data will be
+ * copied.
+ * @param offset Offset in the destination buffer where to start copying.
+ * @param size Size of the data to be copied, in bytes.
+ */
+GGML_CALL static void ggml_backend_cann_buffer_get_tensor(
+    ggml_backend_buffer_t buffer, const ggml_tensor* tensor, void* data,
+    size_t offset, size_t size) {
+    GGML_ASSERT(size == ggml_nbytes(tensor));
+    ggml_backend_cann_buffer_context* ctx =
+        (ggml_backend_cann_buffer_context*)buffer->context;
+
+    ggml_cann_set_device(ctx->device);
+
+    if (!need_transform(tensor->type)) {
+        ACL_CHECK(aclrtMemcpy((char*)data + offset, size, tensor->data, size,
+                              ACL_MEMCPY_DEVICE_TO_HOST));
+    } else {
+        void* transform_buffer = malloc(size);
+        ACL_CHECK(aclrtMemcpy(transform_buffer, size, tensor->data, size,
+                              ACL_MEMCPY_DEVICE_TO_HOST));
+        ggml_backend_cann_transform_back(tensor, transform_buffer,
+                                         (char*)data + offset);
+        free(transform_buffer);
+    }
+}
+
+/**
+ * @brief Copy tensor data between CANN buffers if possible.
+ *
+ * This function copies tensor data between CANN buffers if the source and
+ * destination buffers are CANN buffers and they meet the necessary conditions
+ * (same device or devices can access each other).
+ *
+ * @param buffer The destination CANN buffer where the tensor data will be
+ * copied.
+ * @param src Pointer to the source tensor whose data will be copied.
+ * @param dst Pointer to the destination tensor where the data will be copied.
+ * @return true if the copy operation succeeded, false otherwise.
+ */
+GGML_CALL static bool ggml_backend_cann_buffer_cpy_tensor(
+    ggml_backend_buffer_t buffer, const ggml_tensor* src, ggml_tensor* dst) {
+    if (ggml_backend_buffer_is_cann(src->buffer)) {
+        ggml_backend_cann_buffer_context* src_ctx =
+            (ggml_backend_cann_buffer_context*)src->buffer->context;
+        ggml_backend_cann_buffer_context* dst_ctx =
+            (ggml_backend_cann_buffer_context*)buffer->context;
+
+        size_t memcpy_size = ggml_nbytes(src);
+        // Same device.
+        if (src_ctx->device == dst_ctx->device) {
+            ACL_CHECK(aclrtMemcpy((char*)dst->data, memcpy_size,
+                                  (const char*)src->data, memcpy_size,
+                                  ACL_MEMCPY_DEVICE_TO_DEVICE));
+            return true;
+        } else {
+            // Different device but can access by peer.
+            int32_t canAccessPeer = 0;
+            ACL_CHECK(aclrtDeviceCanAccessPeer(&canAccessPeer, src_ctx->device,
+                                               dst_ctx->device));
+            if (canAccessPeer) {
+                ggml_cann_set_device(src_ctx->device);
+                ACL_CHECK(aclrtDeviceEnablePeerAccess(dst_ctx->device, 0));
+                ACL_CHECK(aclrtMemcpy((char*)dst->data, memcpy_size,
+                                      (const char*)src->data, memcpy_size,
+                                      ACL_MEMCPY_DEVICE_TO_DEVICE));
+                return true;
+            }
+        }
+    }
+    return false;
+}
+
+/**
+ * @brief Clear a CANN buffer by setting all its memory to a specified value.
+ *
+ * This function clears a CANN buffer by setting all its memory to a specified
+ * value.
+ *
+ * @param buffer The CANN buffer to be cleared.
+ * @param value The value to which each byte in the buffer will be set.
+ */
+GGML_CALL static void ggml_backend_cann_buffer_clear(
+    ggml_backend_buffer_t buffer, uint8_t value) {
+    ggml_backend_cann_buffer_context* ctx =
+        (ggml_backend_cann_buffer_context*)buffer->context;
+
+    ggml_cann_set_device(ctx->device);
+    ACL_CHECK(aclrtMemset(ctx->dev_ptr, buffer->size, value, buffer->size));
+}
+
+/**
+ * @brief Interface for a CANN buffer in the backend.
+ *
+ * This structure defines function pointers to operations that can be performed
+ * on a CANN buffer within the backend.
+ */
+static ggml_backend_buffer_i ggml_backend_cann_buffer_interface = {
+    /* .get_name        = */ ggml_backend_cann_buffer_get_name,
+    /* .free_buffer     = */ ggml_backend_cann_buffer_free_buffer,
+    /* .get_base        = */ ggml_backend_cann_buffer_get_base,
+    /* .init_tensor     = */ ggml_backend_cann_buffer_init_tensor,
+    /* .set_tensor      = */ ggml_backend_cann_buffer_set_tensor,
+    /* .get_tensor      = */ ggml_backend_cann_buffer_get_tensor,
+    /* .cpy_tensor      = */ ggml_backend_cann_buffer_cpy_tensor,
+    /* .clear           = */ ggml_backend_cann_buffer_clear,
+    /* .reset           = */ NULL,
+};
+
+// cann buffer type
+/**
+ * @brief Structure representing context information for a specific backend
+ * buffer type.
+ */
+struct ggml_backend_cann_buffer_type_context {
+    int32_t
+        device; /**< Device identifier associated with the buffer context. */
+    std::string name; /**< Name associated with the buffer context. */
+};
+
+/**
+ * @brief Retrieves the name associated with a CANN buffer type.
+ *
+ * This function returns the descriptive name associated with the specified
+ * CANN buffer type context.
+ *
+ * @param buft Pointer to the buffer type context.
+ * @return Const pointer to the C-style string containing the name.
+ */
+GGML_CALL static const char* ggml_backend_cann_buffer_type_name(
+    ggml_backend_buffer_type_t buft) {
+    return "CANN";
+
+    GGML_UNUSED(buft);
+}
+
+/**
+ * @brief Allocates a new CANN buffer of the specified type and size.
+ *
+ * This function allocates a new CANN buffer on the specified device with the
+ * given size.
+ *
+ * @param buft Pointer to the buffer type context.
+ * @param size Size in bytes of the buffer to allocate.
+ * @return Pointer to the allocated buffer, or nullptr if allocation fails.
+ */
+GGML_CALL static ggml_backend_buffer_t
+ggml_backend_cann_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft,
+                                           size_t size) {
+    ggml_backend_cann_buffer_type_context* buft_ctx =
+        (ggml_backend_cann_buffer_type_context*)buft->context;
+
+    ggml_cann_set_device(buft_ctx->device);
+
+    size = std::max(size, (size_t)1);
+
+    void* dev_ptr;
+    aclError err = aclrtMalloc(&dev_ptr, size, ACL_MEM_MALLOC_HUGE_FIRST);
+    if (err != ACL_SUCCESS) {
+        GGML_CANN_LOG_ERROR(
+            "%s: allocating %.2f MiB on device %d: aclrtMalloc failed: %s\n",
+            __func__, size / 1024.0 / 1024.0, buft_ctx->device,
+            aclGetRecentErrMsg());
+        return nullptr;
+    }
+
+    ggml_backend_cann_buffer_context* ctx =
+        new ggml_backend_cann_buffer_context(buft_ctx->device, dev_ptr);
+
+    return ggml_backend_buffer_init(buft, ggml_backend_cann_buffer_interface,
+                                    ctx, size);
+}
+
+/**
+ * @brief Retrieves the memory alignment requirement for CANN buffers of this
+ * type.
+ *
+ * This function returns the alignment requirement in bytes for memory allocated
+ * by the CANN buffer type.
+ *
+ * @param buft Pointer to the buffer type context (unused in this
+ * implementation).
+ * @return The alignment requirement in bytes (fixed at 128 bytes for CANN
+ * buffers).
+ */
+GGML_CALL static size_t ggml_backend_cann_buffer_type_get_alignment(
+    ggml_backend_buffer_type_t buft) {
+    return 128;
+
+    GGML_UNUSED(buft);
+}
+
+/**
+ * @brief Calculates the allocation size required for a tensor in a CANN buffer.
+ *
+ * Computes the total allocation size needed for storing the tensor's data in a
+ * CANN buffer, considering any necessary padding or adjustments for quantized
+ * types.
+ *
+ * @param buft Pointer to the buffer type context (unused in this
+ * implementation).
+ * @param tensor Pointer to the tensor for which the allocation size is
+ * calculated.
+ * @return The total allocation size in bytes required for the tensor in the
+ * CANN buffer.
+ */
+GGML_CALL static size_t ggml_backend_cann_buffer_type_get_alloc_size(
+    ggml_backend_buffer_type_t buft, const ggml_tensor* tensor) {
+    size_t size = ggml_nbytes(tensor);
+    int64_t ne0 = tensor->ne[0];
+
+    // last line must bigger than 32, because every single op deal at
+    // least 32 bytes.
+    // TODO: quantized type?
+    // int64_t line_size = ne0 * ggml_element_size(tensor);
+    // int64_t line_size_align_32 = (line_size + 31) & ~31;
+    // size += (line_size_align_32 - line_size);
+
+    // TODO: not support quantized yet.
+    // TODO: consider un-continue tensor.
+    if (ggml_is_quantized(tensor->type)) {
+        if (ne0 % MATRIX_ROW_PADDING != 0) {
+            size += ggml_row_size(
+                tensor->type, MATRIX_ROW_PADDING - ne0 % MATRIX_ROW_PADDING);
+        }
+    }
+
+    return size;
+
+    GGML_UNUSED(buft);
+}
+
+/**
+ * @brief Interface for managing CANN buffer types in the GGML backend.
+ *
+ * Provides function pointers for allocating, querying properties, and managing
+ * memory for CANN buffer types in the GGML backend.
+ */
+static ggml_backend_buffer_type_i ggml_backend_cann_buffer_type_interface = {
+    /* .get_name         = */ ggml_backend_cann_buffer_type_name,
+    /* .alloc_buffer     = */ ggml_backend_cann_buffer_type_alloc_buffer,
+    /* .get_alignment    = */ ggml_backend_cann_buffer_type_get_alignment,
+    /* .get_max_size     = */ NULL,  // defaults to SIZE_MAX
+    /* .get_alloc_size   = */ ggml_backend_cann_buffer_type_get_alloc_size,
+    /* .is_host          = */ NULL,
+};
+
+/**
+ * @brief Retrieves the CANN buffer type for a specified device.
+ *
+ * This function initializes and returns the buffer type interface associated
+ * with the given device. It ensures thread-safe access using a mutex.
+ *
+ * @param device The device index for which to retrieve the buffer type.
+ * @return A pointer to the buffer type interface for the specified device, or
+ * nullptr if the device index is out of range.
+ */
+GGML_CALL ggml_backend_buffer_type_t
+ggml_backend_cann_buffer_type(int32_t device) {
+    static std::mutex mutex;
+    std::lock_guard lock(mutex);
+
+    if (device >= ggml_backend_cann_get_device_count()) {
+        return nullptr;
+    }
+
+    static ggml_backend_buffer_type
+        ggml_backend_cann_buffer_types[GGML_CANN_MAX_DEVICES];
+
+    static bool ggml_backend_cann_buffer_type_initialized = false;
+
+    if (!ggml_backend_cann_buffer_type_initialized) {
+        for (int32_t i = 0; i < GGML_CANN_MAX_DEVICES; i++) {
+            ggml_backend_cann_buffer_types[i] = {
+                /* .iface    = */ ggml_backend_cann_buffer_type_interface,
+                /* .context  = */
+                 new ggml_backend_cann_buffer_type_context{
+                    i, "CANN" + std::to_string(i)},
+            };
+        }
+        ggml_backend_cann_buffer_type_initialized = true;
+    }
+
+    return &ggml_backend_cann_buffer_types[device];
+}
+
+/**
+ * @brief Computes the forward operation for a given tensor using CANN
+ * operations.
+ *
+ * This function selects the appropriate CANN operation based on the type of
+ * operation specified in the tensor and performs the computation.
+ *
+ * @param ctx The CANN context containing necessary resources and
+ * configurations.
+ * @param dst The destination tensor where the result of the computation will be
+ * stored.
+ * @return true if the computation was successful; false otherwise.
+ */
+static bool ggml_cann_compute_forward(ggml_backend_cann_context& ctx,
+                                      struct ggml_tensor* dst) {
+    switch (dst->op) {
+        case GGML_OP_REPEAT:
+            ggml_cann_repeat(ctx, dst);
+            break;
+        case GGML_OP_GET_ROWS:
+            ggml_cann_get_rows(ctx, dst);
+            break;
+        case GGML_OP_DUP:
+            ggml_cann_dup(ctx, dst);
+            break;
+        case GGML_OP_ADD:
+            ggml_cann_add(ctx, dst);
+            break;
+        case GGML_OP_ACC:
+            ggml_cann_acc(ctx, dst);
+            break;
+        case GGML_OP_MUL:
+            ggml_cann_mul_div(ctx, dst);
+            break;
+        case GGML_OP_DIV:
+            ggml_cann_mul_div(ctx, dst);
+            break;
+        case GGML_OP_UNARY:
+            switch (ggml_get_unary_op(dst)) {
+                case GGML_UNARY_OP_GELU:
+                    ggml_cann_activation(
+                        ctx, dst);
+                    break;
+                case GGML_UNARY_OP_SILU:
+                    ggml_cann_activation(
+                        ctx, dst);
+                    break;
+                // TODO: Use faster gelu??
+                case GGML_UNARY_OP_GELU_QUICK:
+                    ggml_cann_activation(
+                        ctx, dst);
+                    break;
+                case GGML_UNARY_OP_TANH:
+                    ggml_cann_activation(
+                        ctx, dst);
+                    break;
+                case GGML_UNARY_OP_RELU:
+                    ggml_cann_activation(
+                        ctx, dst);
+                    break;
+                case GGML_UNARY_OP_HARDSIGMOID:
+                    ggml_cann_activation(ctx, dst);
+                    break;
+                case GGML_UNARY_OP_HARDSWISH:
+                    ggml_cann_activation(ctx, dst);
+                    break;
+                default:
+                    return false;
+            }
+            break;
+        case GGML_OP_NORM:
+            ggml_cann_norm(ctx, dst);
+            break;
+        case GGML_OP_GROUP_NORM:
+            ggml_cann_group_norm(ctx, dst);
+            break;
+        case GGML_OP_CONCAT:
+            ggml_cann_concat(ctx, dst);
+            break;
+        case GGML_OP_UPSCALE:
+            ggml_cann_upsample_nearest2d(ctx, dst);
+            break;
+        case GGML_OP_PAD:
+            ggml_cann_pad(ctx, dst);
+            break;
+        case GGML_OP_ARANGE:
+            ggml_cann_arange(ctx, dst);
+            break;
+        case GGML_OP_TIMESTEP_EMBEDDING:
+            ggml_cann_timestep_embedding(ctx, dst);
+            break;
+        case GGML_OP_LEAKY_RELU:
+            ggml_cann_leaky_relu(ctx, dst);
+            break;
+        case GGML_OP_RMS_NORM:
+            ggml_cann_rms_norm(ctx, dst);
+            break;
+        case GGML_OP_MUL_MAT:
+            ggml_cann_mul_mat(ctx, dst);
+            break;
+        case GGML_OP_MUL_MAT_ID:
+            return false;
+        case GGML_OP_SCALE:
+            ggml_cann_scale(ctx, dst);
+            break;
+        case GGML_OP_SQR:
+            ggml_cann_sqr(ctx, dst);
+            break;
+        case GGML_OP_CLAMP:
+            ggml_cann_clamp(ctx, dst);
+            break;
+        case GGML_OP_CPY:
+            ggml_cann_cpy(ctx, dst);
+            break;
+        case GGML_OP_CONT:
+            ggml_cann_dup(ctx, dst);
+            break;
+        case GGML_OP_NONE:
+        case GGML_OP_RESHAPE:
+        case GGML_OP_VIEW:
+        case GGML_OP_PERMUTE:
+        case GGML_OP_TRANSPOSE:
+            break;
+        case GGML_OP_DIAG_MASK_INF:
+            ggml_cann_diag_mask(ctx, dst, -INFINITY);
+            break;
+        case GGML_OP_SOFT_MAX:
+            ggml_cann_softmax(ctx, dst);
+            break;
+        case GGML_OP_ROPE:
+            ggml_cann_rope(ctx, dst);
+            break;
+        case GGML_OP_IM2COL:
+            ggml_cann_im2col(ctx, dst);
+            break;
+        case GGML_OP_POOL_2D:
+            ggml_cann_pool2d(ctx, dst);
+            break;
+        case GGML_OP_SUM_ROWS:
+            ggml_cann_sum_rows(ctx, dst);
+            break;
+        case GGML_OP_ARGSORT:
+            ggml_cann_argsort(ctx, dst);
+            break;
+        default:
+            return false;
+    }
+
+    return true;
+}
+
+// backend
+/**
+ * @brief Retrieves the name associated with the CANN backend.
+ *
+ * This function returns the name assigned to the CANN backend, which is stored
+ * in the context of the provided backend structure.
+ *
+ * @param backend Pointer to the CANN backend structure.
+ * @return A pointer to a constant string representing the backend name.
+ */
+GGML_CALL static const char* ggml_backend_cann_name(ggml_backend_t backend) {
+    ggml_backend_cann_context* cann_ctx =
+        (ggml_backend_cann_context*)backend->context;
+
+    return cann_ctx->name.c_str();
+}
+
+/**
+ * @brief Frees resources associated with the CANN backend.
+ *
+ * This function releases resources associated with the CANN backend context
+ * and resets the device associated with the backend to its initial state.
+ *
+ * @param backend Pointer to the CANN backend structure to be freed.
+ */
+GGML_CALL static void ggml_backend_cann_free(ggml_backend_t backend) {
+    ggml_backend_cann_context* cann_ctx =
+        (ggml_backend_cann_context*)backend->context;
+    ACL_CHECK(aclrtSynchronizeDevice());
+    ACL_CHECK(aclrtResetDevice(cann_ctx->device));
+
+    // finalize when last backend freed.
+    if (cann_ctx->device == ggml_backend_cann_get_device_count() - 1) {
+        ACL_CHECK(aclFinalize());
+    }
+
+    delete cann_ctx;
+    delete backend;
+}
+
+/**
+ * @brief Retrieves the default buffer type associated with the CANN backend.
+ *
+ * This function returns the buffer type specific to the device associated
+ * with the CANN backend. It is used to allocate buffers for computations
+ * performed by the backend.
+ *
+ * @param backend Pointer to the CANN backend structure.
+ * @return Pointer to the buffer type structure for the CANN backend.
+ */
+GGML_CALL static ggml_backend_buffer_type_t
+ggml_backend_cann_get_default_buffer_type(ggml_backend_t backend) {
+    ggml_backend_cann_context* cann_ctx =
+        (ggml_backend_cann_context*)backend->context;
+
+    return ggml_backend_cann_buffer_type(cann_ctx->device);
+}
+
+/**
+ * @brief Sets tensor data asynchronously in the CANN backend.
+ *
+ * This function asynchronously sets tensor data in the CANN backend. Depending
+ * on the tensor type, it may perform data transformations before copying data
+ * to the device.
+ *
+ * @param backend Pointer to the CANN backend structure.
+ * @param tensor Pointer to the tensor structure to set data for.
+ * @param data Pointer to the host data to copy to the tensor.
+ * @param offset Offset in bytes within the host data.
+ * @param size Size of the data to copy in bytes.
+ */
+GGML_CALL static void ggml_backend_cann_set_tensor_async(ggml_backend_t backend,
+                                                         ggml_tensor* tensor,
+                                                         const void* data,
+                                                         size_t offset,
+                                                         size_t size) {
+    ggml_backend_cann_context* cann_ctx =
+        (ggml_backend_cann_context*)backend->context;
+
+    if (!need_transform(tensor->type)) {
+        ACL_CHECK(aclrtMemcpyAsync(
+            tensor->data, size, (const char*)data + offset, size,
+            ACL_MEMCPY_HOST_TO_DEVICE, cann_ctx->stream()));
+    } else {
+        void* transform_buffer = malloc(size);
+        ggml_backend_cann_transform(tensor, (const char*)data + offset,
+                                    transform_buffer);
+
+#ifndef NDEBUG
+        void* check_buffer = malloc(size);
+        ggml_backend_cann_transform_back(tensor, transform_buffer,
+                                         check_buffer);
+        GGML_ASSERT(memcmp((const char*)data + offset, check_buffer, size));
+        free(check_buffer);
+#endif
+        ACL_CHECK(aclrtMemcpyAsync(tensor->data, size, transform_buffer, size,
+                                   ACL_MEMCPY_HOST_TO_DEVICE,
+                                   cann_ctx->stream()));
+        ACL_CHECK(aclrtSynchronizeStream(cann_ctx->stream()));
+        free(transform_buffer);
+    }
+}
+
+GGML_CALL static void ggml_backend_cann_get_tensor_async(
+    ggml_backend_t backend, const ggml_tensor* tensor, void* data,
+    size_t offset, size_t size) {
+    ggml_backend_cann_context* cann_ctx =
+        (ggml_backend_cann_context*)backend->context;
+    ggml_backend_buffer_t buf =
+        tensor->view_src ? tensor->view_src->buffer : tensor->buffer;
+
+    GGML_ASSERT(buf->buft == ggml_backend_cann_buffer_type(cann_ctx->device) &&
+                "unsupported buffer type");
+
+    if (!need_transform(tensor->type)) {
+        ACL_CHECK(aclrtMemcpyAsync((char*)data + offset, size, tensor->data,
+                                   size, ACL_MEMCPY_DEVICE_TO_HOST,
+                                   cann_ctx->stream()));
+    } else {
+        void* transform_buffer = malloc(size);
+        ACL_CHECK(aclrtMemcpyAsync(transform_buffer, size, tensor->data, size,
+                                   ACL_MEMCPY_DEVICE_TO_HOST,
+                                   cann_ctx->stream()));
+        ACL_CHECK(aclrtSynchronizeStream(cann_ctx->stream()));
+        ggml_backend_cann_transform_back(tensor, transform_buffer,
+                                         (char*)data + offset);
+        free(transform_buffer);
+    }
+}
+
+/**
+ * @brief Asynchronously copies tensor data between CANN backends.
+ *
+ * This function copies tensor data asynchronously between two CANN backends. It
+ * checks if both tensors reside in CANN buffers and whether the devices support
+ * peer-to-peer access for direct copying. If not, it returns false.
+ *
+ * @param backend_src Pointer to the source CANN backend structure.
+ * @param backend_dst Pointer to the destination CANN backend structure.
+ * @param src Pointer to the source tensor to copy data from.
+ * @param dst Pointer to the destination tensor to copy data to.
+ * @return true if the copy operation succeeds, false otherwise.
+ */
+GGML_CALL static bool ggml_backend_cann_cpy_tensor_async(
+    ggml_backend_t backend_src, ggml_backend_t backend_dst,
+    const ggml_tensor* src, ggml_tensor* dst) {
+    GGML_ASSERT(ggml_backend_is_cann(backend_src) ||
+                ggml_backend_is_cann(backend_dst));
+
+    if (!ggml_backend_buffer_is_cann(src->buffer) ||
+        !ggml_backend_buffer_is_cann(dst->buffer)) {
+        return false;
+    }
+
+    ggml_backend_buffer_t buf_src =
+        src->view_src ? src->view_src->buffer : src->buffer;
+    ggml_backend_buffer_t buf_dst =
+        dst->view_src ? dst->view_src->buffer : dst->buffer;
+
+    ggml_backend_cann_context* cann_ctx_src =
+        (ggml_backend_cann_context*)backend_src->context;
+    ggml_backend_cann_context* cann_ctx_dst =
+        (ggml_backend_cann_context*)backend_dst->context;
+
+    size_t copy_size = ggml_nbytes(dst);
+    if (backend_src != backend_dst) {
+        ggml_backend_cann_buffer_context* buf_ctx_src =
+            (ggml_backend_cann_buffer_context*)buf_src->context;
+        ggml_backend_cann_buffer_context* buf_ctx_dst =
+            (ggml_backend_cann_buffer_context*)buf_dst->context;
+
+        GGML_ASSERT(cann_ctx_src->device == buf_ctx_src->device);
+        GGML_ASSERT(cann_ctx_dst->device == buf_ctx_dst->device);
+
+        int32_t canAccessPeer = 0;
+        ACL_CHECK(aclrtDeviceCanAccessPeer(&canAccessPeer, cann_ctx_src->device,
+                                           cann_ctx_dst->device));
+        if (!canAccessPeer) {
+            return false;
+        }
+
+        ggml_cann_set_device(cann_ctx_src->device);
+        ACL_CHECK(aclrtDeviceEnablePeerAccess(cann_ctx_dst->device, 0));
+        ACL_CHECK(aclrtMemcpyAsync(dst->data, copy_size, src->data, copy_size,
+                                   ACL_MEMCPY_DEVICE_TO_DEVICE,
+                                   cann_ctx_dst->stream()));
+
+        // record event on src stream
+        if (!cann_ctx_src->copy_event) {
+            ACL_CHECK(aclrtCreateEvent(&cann_ctx_src->copy_event));
+        }
+
+        ACL_CHECK(
+            aclrtRecordEvent(cann_ctx_src->copy_event, cann_ctx_src->stream()));
+
+        // wait on dst stream for the copy to complete
+        ACL_CHECK(aclrtStreamWaitEvent(cann_ctx_dst->stream(),
+                                       cann_ctx_src->copy_event));
+    } else {
+        // src and dst are on the same backend
+        ACL_CHECK(aclrtMemcpyAsync(dst->data, copy_size, src->data, copy_size,
+                                   ACL_MEMCPY_DEVICE_TO_DEVICE,
+                                   cann_ctx_dst->stream()));
+    }
+
+    return true;
+}
+
+/**
+ * @brief Synchronizes a CANN backend.
+ *
+ * This function synchronizes the specified CANN backend by waiting for all
+ * operations in its associated stream to complete.
+ *
+ * @param backend Pointer to the CANN backend structure to synchronize.
+ */
+GGML_CALL static void ggml_backend_cann_synchronize(ggml_backend_t backend) {
+    ggml_backend_cann_context* cann_ctx =
+        (ggml_backend_cann_context*)backend->context;
+
+    ggml_cann_set_device(cann_ctx->device);
+
+    ACL_CHECK(aclrtSynchronizeStream(cann_ctx->stream()));
+}
+
+/**
+ * @brief Computes a computational graph using a CANN backend.
+ *
+ * This function computes the operations defined in the computational graph
+ * using the specified CANN backend.
+ *
+ * @param backend Pointer to the CANN backend structure to use for computation.
+ * @param cgraph Pointer to the computational graph structure containing nodes
+ *               representing operations to be computed.
+ * @return enum ggml_status Returns GGML_STATUS_SUCCESS if computation
+ *         completes successfully, otherwise an appropriate error status.
+ */
+GGML_CALL static enum ggml_status ggml_backend_cann_graph_compute(
+    ggml_backend_t backend, ggml_cgraph* cgraph) {
+    ggml_backend_cann_context* cann_ctx =
+        (ggml_backend_cann_context*)backend->context;
+
+    ggml_cann_set_device(cann_ctx->device);
+
+    for (int i = 0; i < cgraph->n_nodes; i++) {
+        ggml_tensor* node = cgraph->nodes[i];
+
+        if (ggml_is_empty(node) || node->op == GGML_OP_NONE) {
+            continue;
+        }
+
+        bool ok = ggml_cann_compute_forward(*cann_ctx, node);
+
+        if (!ok) {
+            GGML_CANN_LOG_ERROR("%s: error: op not supported %s (%s)\n", __func__,
+                    node->name, ggml_op_name(node->op));
+        }
+        GGML_ASSERT(ok);
+    }
+
+    return GGML_STATUS_SUCCESS;
+}
+
+/**
+ * @brief Checks if the CANN backend supports a specific operation.
+ *
+ * This function checks whether the specified operation is supported by the
+ * CANN backend.
+ *
+ * @param backend Pointer to the CANN backend structure to check support for
+ *                the operation.
+ * @param op Pointer to the tensor representing the operation to check.
+ * @return bool Returns true if the operation is supported by the backend,
+ *              otherwise false.
+ */
+GGML_CALL static bool ggml_backend_cann_supports_op(ggml_backend_t backend,
+                                                    const ggml_tensor* op) {
+    switch (op->op) {
+        case GGML_OP_UNARY:
+            switch (ggml_get_unary_op(op)) {
+                case GGML_UNARY_OP_GELU:
+                case GGML_UNARY_OP_SILU:
+                case GGML_UNARY_OP_RELU:
+                case GGML_UNARY_OP_HARDSIGMOID:
+                case GGML_UNARY_OP_HARDSWISH:
+                case GGML_UNARY_OP_GELU_QUICK:
+                case GGML_UNARY_OP_TANH:
+                    return true;
+                default:
+                    return false;
+            }
+        case GGML_OP_MUL_MAT: {
+            switch (op->src[0]->type) {
+                // case GGML_TYPE_Q4_0:
+                case GGML_TYPE_F16:
+                case GGML_TYPE_F32:
+                case GGML_TYPE_Q8_0:
+                    return true;
+                default:
+                    return false;
+            }
+        }
+        case GGML_OP_MUL_MAT_ID:
+            return false;
+        // embedding
+        case GGML_OP_GET_ROWS: {
+            switch (op->src[0]->type) {
+                case GGML_TYPE_F32:
+                case GGML_TYPE_F16:
+                case GGML_TYPE_Q4_0:
+                case GGML_TYPE_Q8_0:
+                    return true;
+                default:
+                    return false;
+            }
+        } break;
+        case GGML_OP_CPY: {
+            switch (op->type) {
+                case GGML_TYPE_F32:
+                case GGML_TYPE_F16:
+                case GGML_TYPE_Q8_0:
+                    return true;
+                default:
+                    return false;
+            }
+        }
+        case GGML_OP_DUP:
+        case GGML_OP_REPEAT:
+        case GGML_OP_CONCAT:
+        case GGML_OP_NONE:
+        case GGML_OP_RESHAPE:
+        case GGML_OP_VIEW:
+        case GGML_OP_PERMUTE:
+        case GGML_OP_TRANSPOSE:
+        case GGML_OP_NORM:
+        case GGML_OP_ADD:
+        case GGML_OP_MUL:
+        case GGML_OP_DIV:
+        case GGML_OP_RMS_NORM:
+        case GGML_OP_SCALE:
+        case GGML_OP_SQR:
+        case GGML_OP_CLAMP:
+        case GGML_OP_CONT:
+        case GGML_OP_DIAG_MASK_INF:
+        case GGML_OP_SOFT_MAX:
+        case GGML_OP_ROPE:
+        case GGML_OP_IM2COL:
+        case GGML_OP_POOL_2D:
+        case GGML_OP_SUM_ROWS:
+        case GGML_OP_ARGSORT:
+        case GGML_OP_ACC:
+        case GGML_OP_GROUP_NORM:
+        case GGML_OP_UPSCALE:
+        case GGML_OP_PAD:
+        case GGML_OP_ARANGE:
+        case GGML_OP_TIMESTEP_EMBEDDING:
+        case GGML_OP_LEAKY_RELU:
+            return true;
+        default:
+            return false;
+    }
+
+    GGML_UNUSED(backend);
+}
+
+/**
+ * @brief Checks if the backend buffer type is associated with the CANN backend.
+ *
+ * This function checks whether the provided backend buffer type is associated
+ * with the CANN backend based on the comparison of its name retrieval function
+ * pointer.
+ *
+ * @param buft Pointer to the backend buffer type to check.
+ * @return bool Returns true if the buffer type is associated with the CANN
+ * backend, otherwise false.
+ */
+static bool ggml_backend_buft_is_cann(ggml_backend_buffer_type_t buft) {
+    return buft->iface.get_name == ggml_backend_cann_buffer_type_name;
+}
+
+/**
+ * @brief Checks if the CANN backend supports a specific backend buffer type.
+ *
+ * This function determines whether the CANN backend supports the given backend
+ * buffer type by comparing the device context of the backend and buffer type.
+ * It returns true if the device associated with the buffer type matches the
+ * device associated with the backend.
+ *
+ * @param backend Pointer to the CANN backend.
+ * @param buft Pointer to the backend buffer type to check.
+ * @return bool Returns true if the CANN backend supports the buffer type,
+ *              otherwise false.
+ */
+GGML_CALL static bool ggml_backend_cann_supports_buft(
+    ggml_backend_t backend, ggml_backend_buffer_type_t buft) {
+    return buft->iface.get_name == ggml_backend_cann_buffer_type_name;
+
+    GGML_UNUSED(backend);
+}
+
+/**
+ * @brief Determines if a tensor operation should be offloaded to the CANN
+ * backend.
+ *
+ * This function checks if a given tensor operation should be offloaded to the
+ * CANN backend based on the operation type and the size of the tensor. It
+ * returns true if the second dimension (ne[1]) of the tensor is greater than or
+ * equal to the minimum batch size and the operation is not GGML_OP_GET_ROWS.
+ *
+ * @param backend Pointer to the CANN backend.
+ * @param op Pointer to the tensor operation to check.
+ * @return bool Returns true if the operation should be offloaded, otherwise
+ * false.
+ */
+GGML_CALL static bool ggml_backend_cann_offload_op(ggml_backend_t backend,
+                                                   const ggml_tensor* op) {
+    const int min_batch_size = 32;
+    GGML_UNUSED(backend);
+
+    return op->ne[1] >= min_batch_size && op->op != GGML_OP_GET_ROWS;
+}
+
+/**
+ * @brief Creates a new event for the CANN backend.
+ *
+ * This function initializes a new event for the CANN backend by setting the
+ * device and creating an ACL runtime event. The created event is then wrapped
+ * in a ggml_backend_event structure and returned.
+ *
+ * @param backend Pointer to the CANN backend.
+ * @return ggml_backend_event_t Returns a pointer to the new event structure.
+ */
+static ggml_backend_event_t ggml_backend_cann_event_new(
+    ggml_backend_t backend) {
+    ggml_backend_cann_context* cann_ctx =
+        (ggml_backend_cann_context*)backend->context;
+
+    ggml_cann_set_device(cann_ctx->device);
+
+    aclrtEvent event;
+    ACL_CHECK(aclrtCreateEvent(&event));
+
+    return new ggml_backend_event{
+        /* .backend = */ backend,
+        /* .context = */ event,
+    };
+}
+
+/**
+ * @brief Frees a CANN backend event.
+ *
+ * This function destroys the ACL runtime event associated with the given CANN
+ * backend event and then deletes the event structure itself.
+ *
+ * @param event Pointer to the event structure to be freed.
+ */
+static void ggml_backend_cann_event_free(ggml_backend_event_t event) {
+    ACL_CHECK(aclrtDestroyEvent((aclrtEvent)event->context));
+
+    delete event;
+}
+
+/**
+ * @brief Records an event on the CANN backend stream.
+ *
+ * This function records the given event on the ACL runtime stream associated
+ * with the backend context.
+ *
+ * @param event Pointer to the event structure to be recorded.
+ */
+static void ggml_backend_cann_event_record(ggml_backend_event_t event) {
+    ggml_backend_cann_context* cann_ctx =
+        (ggml_backend_cann_context*)event->backend->context;
+
+    ACL_CHECK(aclrtRecordEvent((aclrtEvent)event->context, cann_ctx->stream()));
+}
+
+/**
+ * @brief Waits for a recorded event to complete on the CANN backend stream.
+ *
+ * This function makes the given backend wait for the event to complete on its
+ * ACL runtime stream.
+ *
+ * @param backend Pointer to the backend structure.
+ * @param event Pointer to the event structure that the backend needs to wait
+ * for.
+ */
+static void ggml_backend_cann_event_wait(ggml_backend_t backend,
+                                         ggml_backend_event_t event) {
+    ggml_backend_cann_context* cann_ctx =
+        (ggml_backend_cann_context*)backend->context;
+
+    if (ggml_backend_is_cann(event->backend)) {
+        ACL_CHECK(aclrtStreamWaitEvent(cann_ctx->stream(),
+                                       (aclrtEvent)event->context));
+    } else {
+        GGML_ASSERT(false);
+    }
+}
+
+/**
+ * @brief Synchronizes the given event on the CANN backend.
+ *
+ * This function waits for the specified event to complete on the ACL runtime.
+ *
+ * @param event Pointer to the event structure to be synchronized.
+ */
+static void ggml_backend_cann_event_synchronize(ggml_backend_event_t event) {
+    ACL_CHECK(aclrtSynchronizeEvent((aclrtEvent)event->context));
+}
+
+/**
+ * @brief Structure defining the interface for the CANN backend.
+ *
+ * This structure contains function pointers for various operations
+ * supported by the CANN backend, including name retrieval, memory
+ * management, tensor operations, synchronization, and event handling.
+ */
+static ggml_backend_i ggml_backend_cann_interface = {
+    /* .get_name                = */ ggml_backend_cann_name,
+    /* .free                    = */ ggml_backend_cann_free,
+    /* .get_default_buffer_type = */ ggml_backend_cann_get_default_buffer_type,
+    /* .set_tensor_async        = */ ggml_backend_cann_set_tensor_async,
+    /* .get_tensor_async        = */ ggml_backend_cann_get_tensor_async,
+    /* .cpy_tensor_async        = */ ggml_backend_cann_cpy_tensor_async,
+    /* .synchronize             = */ ggml_backend_cann_synchronize,
+    /* .graph_plan_create       = */ NULL,
+    /* .graph_plan_free         = */ NULL,
+    /* .graph_plan_update       = */ NULL,
+    /* .graph_plan_compute      = */ NULL,
+    /* .graph_compute           = */ ggml_backend_cann_graph_compute,
+    /* .supports_op             = */ ggml_backend_cann_supports_op,
+    /* .supports_buft           = */ ggml_backend_cann_supports_buft,
+    /* .offload_op              = */ ggml_backend_cann_offload_op,
+    /* .event_new               = */ ggml_backend_cann_event_new,
+    /* .event_free              = */ ggml_backend_cann_event_free,
+    /* .event_record            = */ ggml_backend_cann_event_record,
+    /* .event_wait              = */ ggml_backend_cann_event_wait,
+    /* .event_synchronize       = */ ggml_backend_cann_event_synchronize,
+};
+
+/**
+ * @brief Return the hardcoded GUID for the CANN backend.
+ *
+ * This function returns a static GUID which uniquely identifies the CANN
+ * backend.
+ *
+ * @return A pointer to the static GUID.
+ */
+static ggml_guid_t ggml_backend_cann_guid() {
+    static ggml_guid guid = {0xa1, 0x94, 0xaf, 0xac, 0xbd, 0x4f, 0x47, 0x34,
+                             0xbe, 0x1a, 0x9e, 0x71, 0x1f, 0x9e, 0xed, 0x64};
+    return &guid;
+}
+
+GGML_CALL ggml_backend_t ggml_backend_cann_init(int32_t device) {
+    aclInit(nullptr);
+    if (device < 0 || device >= ggml_backend_cann_get_device_count()) {
+        GGML_CANN_LOG_ERROR("%s: error: invalid device %d\n", __func__, device);
+        return nullptr;
+    }
+
+    ggml_backend_cann_context* ctx = new ggml_backend_cann_context(device);
+    if (ctx == nullptr) {
+        GGML_CANN_LOG_ERROR("%s: error: failed to allocate context\n", __func__);
+        return nullptr;
+    }
+
+    ggml_backend_t cann_backend =
+        new ggml_backend{/* .guid      = */ ggml_backend_cann_guid(),
+                         /* .interface = */ ggml_backend_cann_interface,
+                         /* .context   = */ ctx};
+
+    return cann_backend;
+}
+
+GGML_CALL bool ggml_backend_is_cann(ggml_backend_t backend) {
+    return backend != NULL &&
+           ggml_guid_matches(backend->guid, ggml_backend_cann_guid());
+}
+
+GGML_CALL int32_t ggml_backend_cann_get_device_count() {
+    return ggml_cann_info().device_count;
+}
+
+GGML_CALL void ggml_backend_cann_get_device_description(
+    int32_t device, char* description, size_t description_size) {
+    ggml_cann_set_device(device);
+    const char* soc_name = aclrtGetSocName();
+    snprintf(description, description_size, "%s", soc_name);
+}
+
+GGML_CALL void ggml_backend_cann_get_device_memory(int32_t device, size_t* free,
+                                                   size_t* total) {
+    ggml_cann_set_device(device);
+    ACL_CHECK(aclrtGetMemInfo(ACL_HBM_MEM, free, total));
+}
+
+// backend registry
+/**
+ * @brief Initializes a CANN backend based on the provided parameters.
+ *
+ * This function initializes a CANN backend using the device index and then
+ * initializes the backend using `ggml_backend_cann_init`.
+ *
+ * @param params Parameters for initialization (unused in this implementation).
+ * @param user_data User data containing the device index to initialize the
+ * backend.
+ * @return ggml_backend_t The initialized CANN backend.
+ */
+GGML_CALL static ggml_backend_t ggml_backend_reg_cann_init(const char* params,
+                                                           void* user_data) {
+    ggml_backend_t cann_backend =
+        ggml_backend_cann_init((int)(intptr_t)user_data);
+    return cann_backend;
+
+    GGML_UNUSED(params);
+}
+
+extern "C" GGML_CALL int ggml_backend_cann_reg_devices();
+
+/**
+ * @brief Registers CANN (Ascend) devices as backend options.
+ *
+ * This function initializes ACL, retrieves the number of available CANN
+ * devices, and registers each device as a backend option using
+ * `ggml_backend_register`. Each device is given a unique name based on
+ * `GGML_CANN_NAME` followed by its index.
+ *
+ * @return int The number of CANN devices registered.
+ */
+GGML_CALL int ggml_backend_cann_reg_devices() {
+    uint32_t device_count = ggml_backend_cann_get_device_count();
+    // initialization
+    for (uint32_t i = 0; i < device_count; i++) {
+        char name[128];
+        snprintf(name, sizeof(name), "CANN%d", i);
+        ggml_backend_register(name, ggml_backend_reg_cann_init,
+                              ggml_backend_cann_buffer_type(i),
+                              (void*)(intptr_t)i);
+    }
+    return device_count;
+}
diff --git a/ggml/src/ggml-cann/.clang-format b/ggml/src/ggml-cann/.clang-format
new file mode 100644
index 0000000000000..2ad03d7391936
--- /dev/null
+++ b/ggml/src/ggml-cann/.clang-format
@@ -0,0 +1,168 @@
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+UseTab:          Never
+...
+
diff --git a/ggml/src/ggml-cann/Doxyfile b/ggml/src/ggml-cann/Doxyfile
new file mode 100644
index 0000000000000..2b009e8f9bd26
--- /dev/null
+++ b/ggml/src/ggml-cann/Doxyfile
@@ -0,0 +1,2579 @@
+# Doxyfile 1.8.17
+
+# This file describes the settings to be used by the documentation system
+# doxygen (www.doxygen.org) for a project.
+#
+# All text after a double hash (##) is considered a comment and is placed in
+# front of the TAG it is preceding.
+#
+# All text after a single hash (#) is considered a comment and will be ignored.
+# The format is:
+# TAG = value [value, ...]
+# For lists, items can also be appended using:
+# TAG += value [value, ...]
+# Values that contain spaces should be placed between quotes (\" \").
+
+#---------------------------------------------------------------------------
+# Project related configuration options
+#---------------------------------------------------------------------------
+
+# This tag specifies the encoding used for all characters in the configuration
+# file that follow. The default is UTF-8 which is also the encoding used for all
+# text before the first occurrence of this tag. Doxygen uses libiconv (or the
+# iconv built into libc) for the transcoding. See
+# https://www.gnu.org/software/libiconv/ for the list of possible encodings.
+# The default value is: UTF-8.
+
+DOXYFILE_ENCODING      = UTF-8
+
+# The PROJECT_NAME tag is a single word (or a sequence of words surrounded by
+# double-quotes, unless you are using Doxywizard) that should identify the
+# project for which the documentation is generated. This name is used in the
+# title of most generated pages and in a few other places.
+# The default value is: My Project.
+
+PROJECT_NAME           = "llama.cpp"
+
+# The PROJECT_NUMBER tag can be used to enter a project or revision number. This
+# could be handy for archiving the generated documentation or if some version
+# control system is used.
+
+PROJECT_NUMBER         =
+
+# Using the PROJECT_BRIEF tag one can provide an optional one line description
+# for a project that appears at the top of each page and should give viewer a
+# quick idea about the purpose of the project. Keep the description short.
+
+PROJECT_BRIEF          = "llama inference engine"
+
+# With the PROJECT_LOGO tag one can specify a logo or an icon that is included
+# in the documentation. The maximum height of the logo should not exceed 55
+# pixels and the maximum width should not exceed 200 pixels. Doxygen will copy
+# the logo to the output directory.
+
+PROJECT_LOGO           =
+
+# The OUTPUT_DIRECTORY tag is used to specify the (relative or absolute) path
+# into which the generated documentation will be written. If a relative path is
+# entered, it will be relative to the location where doxygen was started. If
+# left blank the current directory will be used.
+
+OUTPUT_DIRECTORY       = docs
+
+# If the CREATE_SUBDIRS tag is set to YES then doxygen will create 4096 sub-
+# directories (in 2 levels) under the output directory of each output format and
+# will distribute the generated files over these directories. Enabling this
+# option can be useful when feeding doxygen a huge amount of source files, where
+# putting all generated files in the same directory would otherwise causes
+# performance problems for the file system.
+# The default value is: NO.
+
+CREATE_SUBDIRS         = NO
+
+# If the ALLOW_UNICODE_NAMES tag is set to YES, doxygen will allow non-ASCII
+# characters to appear in the names of generated files. If set to NO, non-ASCII
+# characters will be escaped, for example _xE3_x81_x84 will be used for Unicode
+# U+3044.
+# The default value is: NO.
+
+ALLOW_UNICODE_NAMES    = NO
+
+# The OUTPUT_LANGUAGE tag is used to specify the language in which all
+# documentation generated by doxygen is written. Doxygen will use this
+# information to generate all constant output in the proper language.
+# Possible values are: Afrikaans, Arabic, Armenian, Brazilian, Catalan, Chinese,
+# Chinese-Traditional, Croatian, Czech, Danish, Dutch, English (United States),
+# Esperanto, Farsi (Persian), Finnish, French, German, Greek, Hungarian,
+# Indonesian, Italian, Japanese, Japanese-en (Japanese with English messages),
+# Korean, Korean-en (Korean with English messages), Latvian, Lithuanian,
+# Macedonian, Norwegian, Persian (Farsi), Polish, Portuguese, Romanian, Russian,
+# Serbian, Serbian-Cyrillic, Slovak, Slovene, Spanish, Swedish, Turkish,
+# Ukrainian and Vietnamese.
+# The default value is: English.
+
+OUTPUT_LANGUAGE        = English
+
+# The OUTPUT_TEXT_DIRECTION tag is used to specify the direction in which all
+# documentation generated by doxygen is written. Doxygen will use this
+# information to generate all generated output in the proper direction.
+# Possible values are: None, LTR, RTL and Context.
+# The default value is: None.
+
+OUTPUT_TEXT_DIRECTION  = None
+
+# If the BRIEF_MEMBER_DESC tag is set to YES, doxygen will include brief member
+# descriptions after the members that are listed in the file and class
+# documentation (similar to Javadoc). Set to NO to disable this.
+# The default value is: YES.
+
+BRIEF_MEMBER_DESC      = YES
+
+# If the REPEAT_BRIEF tag is set to YES, doxygen will prepend the brief
+# description of a member or function before the detailed description
+#
+# Note: If both HIDE_UNDOC_MEMBERS and BRIEF_MEMBER_DESC are set to NO, the
+# brief descriptions will be completely suppressed.
+# The default value is: YES.
+
+REPEAT_BRIEF           = YES
+
+# This tag implements a quasi-intelligent brief description abbreviator that is
+# used to form the text in various listings. Each string in this list, if found
+# as the leading text of the brief description, will be stripped from the text
+# and the result, after processing the whole list, is used as the annotated
+# text. Otherwise, the brief description is used as-is. If left blank, the
+# following values are used ($name is automatically replaced with the name of
+# the entity):The $name class, The $name widget, The $name file, is, provides,
+# specifies, contains, represents, a, an and the.
+
+ABBREVIATE_BRIEF       = "The $name class" \
+                         "The $name widget" \
+                         "The $name file" \
+                         is \
+                         provides \
+                         specifies \
+                         contains \
+                         represents \
+                         a \
+                         an \
+                         the
+
+# If the ALWAYS_DETAILED_SEC and REPEAT_BRIEF tags are both set to YES then
+# doxygen will generate a detailed section even if there is only a brief
+# description.
+# The default value is: NO.
+
+ALWAYS_DETAILED_SEC    = NO
+
+# If the INLINE_INHERITED_MEMB tag is set to YES, doxygen will show all
+# inherited members of a class in the documentation of that class as if those
+# members were ordinary class members. Constructors, destructors and assignment
+# operators of the base classes will not be shown.
+# The default value is: NO.
+
+INLINE_INHERITED_MEMB  = NO
+
+# If the FULL_PATH_NAMES tag is set to YES, doxygen will prepend the full path
+# before files name in the file list and in the header files. If set to NO the
+# shortest path that makes the file name unique will be used
+# The default value is: YES.
+
+FULL_PATH_NAMES        = YES
+
+# The STRIP_FROM_PATH tag can be used to strip a user-defined part of the path.
+# Stripping is only done if one of the specified strings matches the left-hand
+# part of the path. The tag can be used to show relative paths in the file list.
+# If left blank the directory from which doxygen is run is used as the path to
+# strip.
+#
+# Note that you can specify absolute paths here, but also relative paths, which
+# will be relative from the directory where doxygen is started.
+# This tag requires that the tag FULL_PATH_NAMES is set to YES.
+
+STRIP_FROM_PATH        =
+
+# The STRIP_FROM_INC_PATH tag can be used to strip a user-defined part of the
+# path mentioned in the documentation of a class, which tells the reader which
+# header file to include in order to use a class. If left blank only the name of
+# the header file containing the class definition is used. Otherwise one should
+# specify the list of include paths that are normally passed to the compiler
+# using the -I flag.
+
+STRIP_FROM_INC_PATH    =
+
+# If the SHORT_NAMES tag is set to YES, doxygen will generate much shorter (but
+# less readable) file names. This can be useful is your file systems doesn't
+# support long names like on DOS, Mac, or CD-ROM.
+# The default value is: NO.
+
+SHORT_NAMES            = NO
+
+# If the JAVADOC_AUTOBRIEF tag is set to YES then doxygen will interpret the
+# first line (until the first dot) of a Javadoc-style comment as the brief
+# description. If set to NO, the Javadoc-style will behave just like regular Qt-
+# style comments (thus requiring an explicit @brief command for a brief
+# description.)
+# The default value is: NO.
+
+JAVADOC_AUTOBRIEF      = NO
+
+# If the JAVADOC_BANNER tag is set to YES then doxygen will interpret a line
+# such as
+# /***************
+# as being the beginning of a Javadoc-style comment "banner". If set to NO, the
+# Javadoc-style will behave just like regular comments and it will not be
+# interpreted by doxygen.
+# The default value is: NO.
+
+JAVADOC_BANNER         = NO
+
+# If the QT_AUTOBRIEF tag is set to YES then doxygen will interpret the first
+# line (until the first dot) of a Qt-style comment as the brief description. If
+# set to NO, the Qt-style will behave just like regular Qt-style comments (thus
+# requiring an explicit \brief command for a brief description.)
+# The default value is: NO.
+
+QT_AUTOBRIEF           = NO
+
+# The MULTILINE_CPP_IS_BRIEF tag can be set to YES to make doxygen treat a
+# multi-line C++ special comment block (i.e. a block of //! or /// comments) as
+# a brief description. This used to be the default behavior. The new default is
+# to treat a multi-line C++ comment block as a detailed description. Set this
+# tag to YES if you prefer the old behavior instead.
+#
+# Note that setting this tag to YES also means that rational rose comments are
+# not recognized any more.
+# The default value is: NO.
+
+MULTILINE_CPP_IS_BRIEF = NO
+
+# If the INHERIT_DOCS tag is set to YES then an undocumented member inherits the
+# documentation from any documented member that it re-implements.
+# The default value is: YES.
+
+INHERIT_DOCS           = YES
+
+# If the SEPARATE_MEMBER_PAGES tag is set to YES then doxygen will produce a new
+# page for each member. If set to NO, the documentation of a member will be part
+# of the file/class/namespace that contains it.
+# The default value is: NO.
+
+SEPARATE_MEMBER_PAGES  = NO
+
+# The TAB_SIZE tag can be used to set the number of spaces in a tab. Doxygen
+# uses this value to replace tabs by spaces in code fragments.
+# Minimum value: 1, maximum value: 16, default value: 4.
+
+TAB_SIZE               = 4
+
+# This tag can be used to specify a number of aliases that act as commands in
+# the documentation. An alias has the form:
+# name=value
+# For example adding
+# "sideeffect=@par Side Effects:\n"
+# will allow you to put the command \sideeffect (or @sideeffect) in the
+# documentation, which will result in a user-defined paragraph with heading
+# "Side Effects:". You can put \n's in the value part of an alias to insert
+# newlines (in the resulting output). You can put ^^ in the value part of an
+# alias to insert a newline as if a physical newline was in the original file.
+# When you need a literal { or } or , in the value part of an alias you have to
+# escape them by means of a backslash (\), this can lead to conflicts with the
+# commands \{ and \} for these it is advised to use the version @{ and @} or use
+# a double escape (\\{ and \\})
+
+ALIASES                =
+
+# This tag can be used to specify a number of word-keyword mappings (TCL only).
+# A mapping has the form "name=value". For example adding "class=itcl::class"
+# will allow you to use the command class in the itcl::class meaning.
+
+TCL_SUBST              =
+
+# Set the OPTIMIZE_OUTPUT_FOR_C tag to YES if your project consists of C sources
+# only. Doxygen will then generate output that is more tailored for C. For
+# instance, some of the names that are used will be different. The list of all
+# members will be omitted, etc.
+# The default value is: NO.
+
+OPTIMIZE_OUTPUT_FOR_C  = NO
+
+# Set the OPTIMIZE_OUTPUT_JAVA tag to YES if your project consists of Java or
+# Python sources only. Doxygen will then generate output that is more tailored
+# for that language. For instance, namespaces will be presented as packages,
+# qualified scopes will look different, etc.
+# The default value is: NO.
+
+OPTIMIZE_OUTPUT_JAVA   = NO
+
+# Set the OPTIMIZE_FOR_FORTRAN tag to YES if your project consists of Fortran
+# sources. Doxygen will then generate output that is tailored for Fortran.
+# The default value is: NO.
+
+OPTIMIZE_FOR_FORTRAN   = NO
+
+# Set the OPTIMIZE_OUTPUT_VHDL tag to YES if your project consists of VHDL
+# sources. Doxygen will then generate output that is tailored for VHDL.
+# The default value is: NO.
+
+OPTIMIZE_OUTPUT_VHDL   = NO
+
+# Set the OPTIMIZE_OUTPUT_SLICE tag to YES if your project consists of Slice
+# sources only. Doxygen will then generate output that is more tailored for that
+# language. For instance, namespaces will be presented as modules, types will be
+# separated into more groups, etc.
+# The default value is: NO.
+
+OPTIMIZE_OUTPUT_SLICE  = NO
+
+# Doxygen selects the parser to use depending on the extension of the files it
+# parses. With this tag you can assign which parser to use for a given
+# extension. Doxygen has a built-in mapping, but you can override or extend it
+# using this tag. The format is ext=language, where ext is a file extension, and
+# language is one of the parsers supported by doxygen: IDL, Java, JavaScript,
+# Csharp (C#), C, C++, D, PHP, md (Markdown), Objective-C, Python, Slice,
+# Fortran (fixed format Fortran: FortranFixed, free formatted Fortran:
+# FortranFree, unknown formatted Fortran: Fortran. In the later case the parser
+# tries to guess whether the code is fixed or free formatted code, this is the
+# default for Fortran type files), VHDL, tcl. For instance to make doxygen treat
+# .inc files as Fortran files (default is PHP), and .f files as C (default is
+# Fortran), use: inc=Fortran f=C.
+#
+# Note: For files without extension you can use no_extension as a placeholder.
+#
+# Note that for custom extensions you also need to set FILE_PATTERNS otherwise
+# the files are not read by doxygen.
+
+EXTENSION_MAPPING      =
+
+# If the MARKDOWN_SUPPORT tag is enabled then doxygen pre-processes all comments
+# according to the Markdown format, which allows for more readable
+# documentation. See https://daringfireball.net/projects/markdown/ for details.
+# The output of markdown processing is further processed by doxygen, so you can
+# mix doxygen, HTML, and XML commands with Markdown formatting. Disable only in
+# case of backward compatibilities issues.
+# The default value is: YES.
+
+MARKDOWN_SUPPORT       = YES
+
+# When the TOC_INCLUDE_HEADINGS tag is set to a non-zero value, all headings up
+# to that level are automatically included in the table of contents, even if
+# they do not have an id attribute.
+# Note: This feature currently applies only to Markdown headings.
+# Minimum value: 0, maximum value: 99, default value: 5.
+# This tag requires that the tag MARKDOWN_SUPPORT is set to YES.
+
+TOC_INCLUDE_HEADINGS   = 5
+
+# When enabled doxygen tries to link words that correspond to documented
+# classes, or namespaces to their corresponding documentation. Such a link can
+# be prevented in individual cases by putting a % sign in front of the word or
+# globally by setting AUTOLINK_SUPPORT to NO.
+# The default value is: YES.
+
+AUTOLINK_SUPPORT       = YES
+
+# If you use STL classes (i.e. std::string, std::vector, etc.) but do not want
+# to include (a tag file for) the STL sources as input, then you should set this
+# tag to YES in order to let doxygen match functions declarations and
+# definitions whose arguments contain STL classes (e.g. func(std::string);
+# versus func(std::string) {}). This also make the inheritance and collaboration
+# diagrams that involve STL classes more complete and accurate.
+# The default value is: NO.
+
+BUILTIN_STL_SUPPORT    = NO
+
+# If you use Microsoft's C++/CLI language, you should set this option to YES to
+# enable parsing support.
+# The default value is: NO.
+
+CPP_CLI_SUPPORT        = NO
+
+# Set the SIP_SUPPORT tag to YES if your project consists of sip (see:
+# https://www.riverbankcomputing.com/software/sip/intro) sources only. Doxygen
+# will parse them like normal C++ but will assume all classes use public instead
+# of private inheritance when no explicit protection keyword is present.
+# The default value is: NO.
+
+SIP_SUPPORT            = NO
+
+# For Microsoft's IDL there are propget and propput attributes to indicate
+# getter and setter methods for a property. Setting this option to YES will make
+# doxygen to replace the get and set methods by a property in the documentation.
+# This will only work if the methods are indeed getting or setting a simple
+# type. If this is not the case, or you want to show the methods anyway, you
+# should set this option to NO.
+# The default value is: YES.
+
+IDL_PROPERTY_SUPPORT   = YES
+
+# If member grouping is used in the documentation and the DISTRIBUTE_GROUP_DOC
+# tag is set to YES then doxygen will reuse the documentation of the first
+# member in the group (if any) for the other members of the group. By default
+# all members of a group must be documented explicitly.
+# The default value is: NO.
+
+DISTRIBUTE_GROUP_DOC   = NO
+
+# If one adds a struct or class to a group and this option is enabled, then also
+# any nested class or struct is added to the same group. By default this option
+# is disabled and one has to add nested compounds explicitly via \ingroup.
+# The default value is: NO.
+
+GROUP_NESTED_COMPOUNDS = NO
+
+# Set the SUBGROUPING tag to YES to allow class member groups of the same type
+# (for instance a group of public functions) to be put as a subgroup of that
+# type (e.g. under the Public Functions section). Set it to NO to prevent
+# subgrouping. Alternatively, this can be done per class using the
+# \nosubgrouping command.
+# The default value is: YES.
+
+SUBGROUPING            = YES
+
+# When the INLINE_GROUPED_CLASSES tag is set to YES, classes, structs and unions
+# are shown inside the group in which they are included (e.g. using \ingroup)
+# instead of on a separate page (for HTML and Man pages) or section (for LaTeX
+# and RTF).
+#
+# Note that this feature does not work in combination with
+# SEPARATE_MEMBER_PAGES.
+# The default value is: NO.
+
+INLINE_GROUPED_CLASSES = NO
+
+# When the INLINE_SIMPLE_STRUCTS tag is set to YES, structs, classes, and unions
+# with only public data fields or simple typedef fields will be shown inline in
+# the documentation of the scope in which they are defined (i.e. file,
+# namespace, or group documentation), provided this scope is documented. If set
+# to NO, structs, classes, and unions are shown on a separate page (for HTML and
+# Man pages) or section (for LaTeX and RTF).
+# The default value is: NO.
+
+INLINE_SIMPLE_STRUCTS  = NO
+
+# When TYPEDEF_HIDES_STRUCT tag is enabled, a typedef of a struct, union, or
+# enum is documented as struct, union, or enum with the name of the typedef. So
+# typedef struct TypeS {} TypeT, will appear in the documentation as a struct
+# with name TypeT. When disabled the typedef will appear as a member of a file,
+# namespace, or class. And the struct will be named TypeS. This can typically be
+# useful for C code in case the coding convention dictates that all compound
+# types are typedef'ed and only the typedef is referenced, never the tag name.
+# The default value is: NO.
+
+TYPEDEF_HIDES_STRUCT   = NO
+
+# The size of the symbol lookup cache can be set using LOOKUP_CACHE_SIZE. This
+# cache is used to resolve symbols given their name and scope. Since this can be
+# an expensive process and often the same symbol appears multiple times in the
+# code, doxygen keeps a cache of pre-resolved symbols. If the cache is too small
+# doxygen will become slower. If the cache is too large, memory is wasted. The
+# cache size is given by this formula: 2^(16+LOOKUP_CACHE_SIZE). The valid range
+# is 0..9, the default is 0, corresponding to a cache size of 2^16=65536
+# symbols. At the end of a run doxygen will report the cache usage and suggest
+# the optimal cache size from a speed point of view.
+# Minimum value: 0, maximum value: 9, default value: 0.
+
+LOOKUP_CACHE_SIZE      = 0
+
+#---------------------------------------------------------------------------
+# Build related configuration options
+#---------------------------------------------------------------------------
+
+# If the EXTRACT_ALL tag is set to YES, doxygen will assume all entities in
+# documentation are documented, even if no documentation was available. Private
+# class members and static file members will be hidden unless the
+# EXTRACT_PRIVATE respectively EXTRACT_STATIC tags are set to YES.
+# Note: This will also disable the warnings about undocumented members that are
+# normally produced when WARNINGS is set to YES.
+# The default value is: NO.
+
+EXTRACT_ALL            = YES
+
+# If the EXTRACT_PRIVATE tag is set to YES, all private members of a class will
+# be included in the documentation.
+# The default value is: NO.
+
+EXTRACT_PRIVATE        = YES
+
+# If the EXTRACT_PRIV_VIRTUAL tag is set to YES, documented private virtual
+# methods of a class will be included in the documentation.
+# The default value is: NO.
+
+EXTRACT_PRIV_VIRTUAL   = YES
+
+# If the EXTRACT_PACKAGE tag is set to YES, all members with package or internal
+# scope will be included in the documentation.
+# The default value is: NO.
+
+EXTRACT_PACKAGE        = YES
+
+# If the EXTRACT_STATIC tag is set to YES, all static members of a file will be
+# included in the documentation.
+# The default value is: NO.
+
+EXTRACT_STATIC         = YES
+
+# If the EXTRACT_LOCAL_CLASSES tag is set to YES, classes (and structs) defined
+# locally in source files will be included in the documentation. If set to NO,
+# only classes defined in header files are included. Does not have any effect
+# for Java sources.
+# The default value is: YES.
+
+EXTRACT_LOCAL_CLASSES  = YES
+
+# This flag is only useful for Objective-C code. If set to YES, local methods,
+# which are defined in the implementation section but not in the interface are
+# included in the documentation. If set to NO, only methods in the interface are
+# included.
+# The default value is: NO.
+
+EXTRACT_LOCAL_METHODS  = YES
+
+# If this flag is set to YES, the members of anonymous namespaces will be
+# extracted and appear in the documentation as a namespace called
+# 'anonymous_namespace{file}', where file will be replaced with the base name of
+# the file that contains the anonymous namespace. By default anonymous namespace
+# are hidden.
+# The default value is: NO.
+
+EXTRACT_ANON_NSPACES   = NO
+
+# If the HIDE_UNDOC_MEMBERS tag is set to YES, doxygen will hide all
+# undocumented members inside documented classes or files. If set to NO these
+# members will be included in the various overviews, but no documentation
+# section is generated. This option has no effect if EXTRACT_ALL is enabled.
+# The default value is: NO.
+
+HIDE_UNDOC_MEMBERS     = NO
+
+# If the HIDE_UNDOC_CLASSES tag is set to YES, doxygen will hide all
+# undocumented classes that are normally visible in the class hierarchy. If set
+# to NO, these classes will be included in the various overviews. This option
+# has no effect if EXTRACT_ALL is enabled.
+# The default value is: NO.
+
+HIDE_UNDOC_CLASSES     = NO
+
+# If the HIDE_FRIEND_COMPOUNDS tag is set to YES, doxygen will hide all friend
+# declarations. If set to NO, these declarations will be included in the
+# documentation.
+# The default value is: NO.
+
+HIDE_FRIEND_COMPOUNDS  = NO
+
+# If the HIDE_IN_BODY_DOCS tag is set to YES, doxygen will hide any
+# documentation blocks found inside the body of a function. If set to NO, these
+# blocks will be appended to the function's detailed documentation block.
+# The default value is: NO.
+
+HIDE_IN_BODY_DOCS      = NO
+
+# The INTERNAL_DOCS tag determines if documentation that is typed after a
+# \internal command is included. If the tag is set to NO then the documentation
+# will be excluded. Set it to YES to include the internal documentation.
+# The default value is: NO.
+
+INTERNAL_DOCS          = NO
+
+# If the CASE_SENSE_NAMES tag is set to NO then doxygen will only generate file
+# names in lower-case letters. If set to YES, upper-case letters are also
+# allowed. This is useful if you have classes or files whose names only differ
+# in case and if your file system supports case sensitive file names. Windows
+# (including Cygwin) ands Mac users are advised to set this option to NO.
+# The default value is: system dependent.
+
+CASE_SENSE_NAMES       = YES
+
+# If the HIDE_SCOPE_NAMES tag is set to NO then doxygen will show members with
+# their full class and namespace scopes in the documentation. If set to YES, the
+# scope will be hidden.
+# The default value is: NO.
+
+HIDE_SCOPE_NAMES       = NO
+
+# If the HIDE_COMPOUND_REFERENCE tag is set to NO (default) then doxygen will
+# append additional text to a page's title, such as Class Reference. If set to
+# YES the compound reference will be hidden.
+# The default value is: NO.
+
+HIDE_COMPOUND_REFERENCE= NO
+
+# If the SHOW_INCLUDE_FILES tag is set to YES then doxygen will put a list of
+# the files that are included by a file in the documentation of that file.
+# The default value is: YES.
+
+SHOW_INCLUDE_FILES     = YES
+
+# If the SHOW_GROUPED_MEMB_INC tag is set to YES then Doxygen will add for each
+# grouped member an include statement to the documentation, telling the reader
+# which file to include in order to use the member.
+# The default value is: NO.
+
+SHOW_GROUPED_MEMB_INC  = NO
+
+# If the FORCE_LOCAL_INCLUDES tag is set to YES then doxygen will list include
+# files with double quotes in the documentation rather than with sharp brackets.
+# The default value is: NO.
+
+FORCE_LOCAL_INCLUDES   = NO
+
+# If the INLINE_INFO tag is set to YES then a tag [inline] is inserted in the
+# documentation for inline members.
+# The default value is: YES.
+
+INLINE_INFO            = YES
+
+# If the SORT_MEMBER_DOCS tag is set to YES then doxygen will sort the
+# (detailed) documentation of file and class members alphabetically by member
+# name. If set to NO, the members will appear in declaration order.
+# The default value is: YES.
+
+SORT_MEMBER_DOCS       = YES
+
+# If the SORT_BRIEF_DOCS tag is set to YES then doxygen will sort the brief
+# descriptions of file, namespace and class members alphabetically by member
+# name. If set to NO, the members will appear in declaration order. Note that
+# this will also influence the order of the classes in the class list.
+# The default value is: NO.
+
+SORT_BRIEF_DOCS        = NO
+
+# If the SORT_MEMBERS_CTORS_1ST tag is set to YES then doxygen will sort the
+# (brief and detailed) documentation of class members so that constructors and
+# destructors are listed first. If set to NO the constructors will appear in the
+# respective orders defined by SORT_BRIEF_DOCS and SORT_MEMBER_DOCS.
+# Note: If SORT_BRIEF_DOCS is set to NO this option is ignored for sorting brief
+# member documentation.
+# Note: If SORT_MEMBER_DOCS is set to NO this option is ignored for sorting
+# detailed member documentation.
+# The default value is: NO.
+
+SORT_MEMBERS_CTORS_1ST = NO
+
+# If the SORT_GROUP_NAMES tag is set to YES then doxygen will sort the hierarchy
+# of group names into alphabetical order. If set to NO the group names will
+# appear in their defined order.
+# The default value is: NO.
+
+SORT_GROUP_NAMES       = NO
+
+# If the SORT_BY_SCOPE_NAME tag is set to YES, the class list will be sorted by
+# fully-qualified names, including namespaces. If set to NO, the class list will
+# be sorted only by class name, not including the namespace part.
+# Note: This option is not very useful if HIDE_SCOPE_NAMES is set to YES.
+# Note: This option applies only to the class list, not to the alphabetical
+# list.
+# The default value is: NO.
+
+SORT_BY_SCOPE_NAME     = NO
+
+# If the STRICT_PROTO_MATCHING option is enabled and doxygen fails to do proper
+# type resolution of all parameters of a function it will reject a match between
+# the prototype and the implementation of a member function even if there is
+# only one candidate or it is obvious which candidate to choose by doing a
+# simple string match. By disabling STRICT_PROTO_MATCHING doxygen will still
+# accept a match between prototype and implementation in such cases.
+# The default value is: NO.
+
+STRICT_PROTO_MATCHING  = NO
+
+# The GENERATE_TODOLIST tag can be used to enable (YES) or disable (NO) the todo
+# list. This list is created by putting \todo commands in the documentation.
+# The default value is: YES.
+
+GENERATE_TODOLIST      = YES
+
+# The GENERATE_TESTLIST tag can be used to enable (YES) or disable (NO) the test
+# list. This list is created by putting \test commands in the documentation.
+# The default value is: YES.
+
+GENERATE_TESTLIST      = YES
+
+# The GENERATE_BUGLIST tag can be used to enable (YES) or disable (NO) the bug
+# list. This list is created by putting \bug commands in the documentation.
+# The default value is: YES.
+
+GENERATE_BUGLIST       = YES
+
+# The GENERATE_DEPRECATEDLIST tag can be used to enable (YES) or disable (NO)
+# the deprecated list. This list is created by putting \deprecated commands in
+# the documentation.
+# The default value is: YES.
+
+GENERATE_DEPRECATEDLIST= YES
+
+# The ENABLED_SECTIONS tag can be used to enable conditional documentation
+# sections, marked by \if  ... \endif and \cond 
+# ... \endcond blocks.
+
+ENABLED_SECTIONS       =
+
+# The MAX_INITIALIZER_LINES tag determines the maximum number of lines that the
+# initial value of a variable or macro / define can have for it to appear in the
+# documentation. If the initializer consists of more lines than specified here
+# it will be hidden. Use a value of 0 to hide initializers completely. The
+# appearance of the value of individual variables and macros / defines can be
+# controlled using \showinitializer or \hideinitializer command in the
+# documentation regardless of this setting.
+# Minimum value: 0, maximum value: 10000, default value: 30.
+
+MAX_INITIALIZER_LINES  = 30
+
+# Set the SHOW_USED_FILES tag to NO to disable the list of files generated at
+# the bottom of the documentation of classes and structs. If set to YES, the
+# list will mention the files that were used to generate the documentation.
+# The default value is: YES.
+
+SHOW_USED_FILES        = YES
+
+# Set the SHOW_FILES tag to NO to disable the generation of the Files page. This
+# will remove the Files entry from the Quick Index and from the Folder Tree View
+# (if specified).
+# The default value is: YES.
+
+SHOW_FILES             = YES
+
+# Set the SHOW_NAMESPACES tag to NO to disable the generation of the Namespaces
+# page. This will remove the Namespaces entry from the Quick Index and from the
+# Folder Tree View (if specified).
+# The default value is: YES.
+
+SHOW_NAMESPACES        = YES
+
+# The FILE_VERSION_FILTER tag can be used to specify a program or script that
+# doxygen should invoke to get the current version for each file (typically from
+# the version control system). Doxygen will invoke the program by executing (via
+# popen()) the command command input-file, where command is the value of the
+# FILE_VERSION_FILTER tag, and input-file is the name of an input file provided
+# by doxygen. Whatever the program writes to standard output is used as the file
+# version. For an example see the documentation.
+
+FILE_VERSION_FILTER    =
+
+# The LAYOUT_FILE tag can be used to specify a layout file which will be parsed
+# by doxygen. The layout file controls the global structure of the generated
+# output files in an output format independent way. To create the layout file
+# that represents doxygen's defaults, run doxygen with the -l option. You can
+# optionally specify a file name after the option, if omitted DoxygenLayout.xml
+# will be used as the name of the layout file.
+#
+# Note that if you run doxygen from a directory containing a file called
+# DoxygenLayout.xml, doxygen will parse it automatically even if the LAYOUT_FILE
+# tag is left empty.
+
+LAYOUT_FILE            =
+
+# The CITE_BIB_FILES tag can be used to specify one or more bib files containing
+# the reference definitions. This must be a list of .bib files. The .bib
+# extension is automatically appended if omitted. This requires the bibtex tool
+# to be installed. See also https://en.wikipedia.org/wiki/BibTeX for more info.
+# For LaTeX the style of the bibliography can be controlled using
+# LATEX_BIB_STYLE. To use this feature you need bibtex and perl available in the
+# search path. See also \cite for info how to create references.
+
+CITE_BIB_FILES         =
+
+#---------------------------------------------------------------------------
+# Configuration options related to warning and progress messages
+#---------------------------------------------------------------------------
+
+# The QUIET tag can be used to turn on/off the messages that are generated to
+# standard output by doxygen. If QUIET is set to YES this implies that the
+# messages are off.
+# The default value is: NO.
+
+QUIET                  = NO
+
+# The WARNINGS tag can be used to turn on/off the warning messages that are
+# generated to standard error (stderr) by doxygen. If WARNINGS is set to YES
+# this implies that the warnings are on.
+#
+# Tip: Turn warnings on while writing the documentation.
+# The default value is: YES.
+
+WARNINGS               = YES
+
+# If the WARN_IF_UNDOCUMENTED tag is set to YES then doxygen will generate
+# warnings for undocumented members. If EXTRACT_ALL is set to YES then this flag
+# will automatically be disabled.
+# The default value is: YES.
+
+WARN_IF_UNDOCUMENTED   = YES
+
+# If the WARN_IF_DOC_ERROR tag is set to YES, doxygen will generate warnings for
+# potential errors in the documentation, such as not documenting some parameters
+# in a documented function, or documenting parameters that don't exist or using
+# markup commands wrongly.
+# The default value is: YES.
+
+WARN_IF_DOC_ERROR      = YES
+
+# This WARN_NO_PARAMDOC option can be enabled to get warnings for functions that
+# are documented, but have no documentation for their parameters or return
+# value. If set to NO, doxygen will only warn about wrong or incomplete
+# parameter documentation, but not about the absence of documentation. If
+# EXTRACT_ALL is set to YES then this flag will automatically be disabled.
+# The default value is: NO.
+
+WARN_NO_PARAMDOC       = NO
+
+# If the WARN_AS_ERROR tag is set to YES then doxygen will immediately stop when
+# a warning is encountered.
+# The default value is: NO.
+
+WARN_AS_ERROR          = NO
+
+# The WARN_FORMAT tag determines the format of the warning messages that doxygen
+# can produce. The string should contain the $file, $line, and $text tags, which
+# will be replaced by the file and line number from which the warning originated
+# and the warning text. Optionally the format may contain $version, which will
+# be replaced by the version of the file (if it could be obtained via
+# FILE_VERSION_FILTER)
+# The default value is: $file:$line: $text.
+
+WARN_FORMAT            = "$file:$line: $text"
+
+# The WARN_LOGFILE tag can be used to specify a file to which warning and error
+# messages should be written. If left blank the output is written to standard
+# error (stderr).
+
+WARN_LOGFILE           =
+
+#---------------------------------------------------------------------------
+# Configuration options related to the input files
+#---------------------------------------------------------------------------
+
+# The INPUT tag is used to specify the files and/or directories that contain
+# documented source files. You may enter file names like myfile.cpp or
+# directories like /usr/src/myproject. Separate the files or directories with
+# spaces. See also FILE_PATTERNS and EXTENSION_MAPPING
+# Note: If this tag is empty the current directory is searched.
+
+INPUT                  =
+
+# This tag can be used to specify the character encoding of the source files
+# that doxygen parses. Internally doxygen uses the UTF-8 encoding. Doxygen uses
+# libiconv (or the iconv built into libc) for the transcoding. See the libiconv
+# documentation (see: https://www.gnu.org/software/libiconv/) for the list of
+# possible encodings.
+# The default value is: UTF-8.
+
+INPUT_ENCODING         = UTF-8
+
+# If the value of the INPUT tag contains directories, you can use the
+# FILE_PATTERNS tag to specify one or more wildcard patterns (like *.cpp and
+# *.h) to filter out the source-files in the directories.
+#
+# Note that for custom extensions or not directly supported extensions you also
+# need to set EXTENSION_MAPPING for the extension otherwise the files are not
+# read by doxygen.
+#
+# If left blank the following patterns are tested:*.c, *.cc, *.cxx, *.cpp,
+# *.c++, *.java, *.ii, *.ixx, *.ipp, *.i++, *.inl, *.idl, *.ddl, *.odl, *.h,
+# *.hh, *.hxx, *.hpp, *.h++, *.cs, *.d, *.php, *.php4, *.php5, *.phtml, *.inc,
+# *.m, *.markdown, *.md, *.mm, *.dox (to be provided as doxygen C comment),
+# *.doc (to be provided as doxygen C comment), *.txt (to be provided as doxygen
+# C comment), *.py, *.pyw, *.f90, *.f95, *.f03, *.f08, *.f, *.for, *.tcl, *.vhd,
+# *.vhdl, *.ucf, *.qsf and *.ice.
+
+FILE_PATTERNS          = *.c \
+                         *.cc \
+                         *.cxx \
+                         *.cpp \
+                         *.c++ \
+                         *.java \
+                         *.ii \
+                         *.ixx \
+                         *.ipp \
+                         *.i++ \
+                         *.inl \
+                         *.idl \
+                         *.ddl \
+                         *.odl \
+                         *.h \
+                         *.hh \
+                         *.hxx \
+                         *.hpp \
+                         *.h++ \
+                         *.cs \
+                         *.d \
+                         *.php \
+                         *.php4 \
+                         *.php5 \
+                         *.phtml \
+                         *.inc \
+                         *.m \
+                         *.markdown \
+                         *.md \
+                         *.mm \
+                         *.dox \
+                         *.doc \
+                         *.txt \
+                         *.py \
+                         *.pyw \
+                         *.f90 \
+                         *.f95 \
+                         *.f03 \
+                         *.f08 \
+                         *.f \
+                         *.for \
+                         *.tcl \
+                         *.vhd \
+                         *.vhdl \
+                         *.ucf \
+                         *.qsf \
+                         *.ice
+
+# The RECURSIVE tag can be used to specify whether or not subdirectories should
+# be searched for input files as well.
+# The default value is: NO.
+
+RECURSIVE              = YES
+
+# The EXCLUDE tag can be used to specify files and/or directories that should be
+# excluded from the INPUT source files. This way you can easily exclude a
+# subdirectory from a directory tree whose root is specified with the INPUT tag.
+#
+# Note that relative paths are relative to the directory from which doxygen is
+# run.
+
+EXCLUDE                =
+
+# The EXCLUDE_SYMLINKS tag can be used to select whether or not files or
+# directories that are symbolic links (a Unix file system feature) are excluded
+# from the input.
+# The default value is: NO.
+
+EXCLUDE_SYMLINKS       = NO
+
+# If the value of the INPUT tag contains directories, you can use the
+# EXCLUDE_PATTERNS tag to specify one or more wildcard patterns to exclude
+# certain files from those directories.
+#
+# Note that the wildcards are matched against the file with absolute path, so to
+# exclude all test directories for example use the pattern */test/*
+
+EXCLUDE_PATTERNS       =
+
+# The EXCLUDE_SYMBOLS tag can be used to specify one or more symbol names
+# (namespaces, classes, functions, etc.) that should be excluded from the
+# output. The symbol name can be a fully qualified name, a word, or if the
+# wildcard * is used, a substring. Examples: ANamespace, AClass,
+# AClass::ANamespace, ANamespace::*Test
+#
+# Note that the wildcards are matched against the file with absolute path, so to
+# exclude all test directories use the pattern */test/*
+
+EXCLUDE_SYMBOLS        =
+
+# The EXAMPLE_PATH tag can be used to specify one or more files or directories
+# that contain example code fragments that are included (see the \include
+# command).
+
+EXAMPLE_PATH           =
+
+# If the value of the EXAMPLE_PATH tag contains directories, you can use the
+# EXAMPLE_PATTERNS tag to specify one or more wildcard pattern (like *.cpp and
+# *.h) to filter out the source-files in the directories. If left blank all
+# files are included.
+
+EXAMPLE_PATTERNS       = *
+
+# If the EXAMPLE_RECURSIVE tag is set to YES then subdirectories will be
+# searched for input files to be used with the \include or \dontinclude commands
+# irrespective of the value of the RECURSIVE tag.
+# The default value is: NO.
+
+EXAMPLE_RECURSIVE      = NO
+
+# The IMAGE_PATH tag can be used to specify one or more files or directories
+# that contain images that are to be included in the documentation (see the
+# \image command).
+
+IMAGE_PATH             =
+
+# The INPUT_FILTER tag can be used to specify a program that doxygen should
+# invoke to filter for each input file. Doxygen will invoke the filter program
+# by executing (via popen()) the command:
+#
+#  
+#
+# where  is the value of the INPUT_FILTER tag, and  is the
+# name of an input file. Doxygen will then use the output that the filter
+# program writes to standard output. If FILTER_PATTERNS is specified, this tag
+# will be ignored.
+#
+# Note that the filter must not add or remove lines; it is applied before the
+# code is scanned, but not when the output code is generated. If lines are added
+# or removed, the anchors will not be placed correctly.
+#
+# Note that for custom extensions or not directly supported extensions you also
+# need to set EXTENSION_MAPPING for the extension otherwise the files are not
+# properly processed by doxygen.
+
+INPUT_FILTER           =
+
+# The FILTER_PATTERNS tag can be used to specify filters on a per file pattern
+# basis. Doxygen will compare the file name with each pattern and apply the
+# filter if there is a match. The filters are a list of the form: pattern=filter
+# (like *.cpp=my_cpp_filter). See INPUT_FILTER for further information on how
+# filters are used. If the FILTER_PATTERNS tag is empty or if none of the
+# patterns match the file name, INPUT_FILTER is applied.
+#
+# Note that for custom extensions or not directly supported extensions you also
+# need to set EXTENSION_MAPPING for the extension otherwise the files are not
+# properly processed by doxygen.
+
+FILTER_PATTERNS        =
+
+# If the FILTER_SOURCE_FILES tag is set to YES, the input filter (if set using
+# INPUT_FILTER) will also be used to filter the input files that are used for
+# producing the source files to browse (i.e. when SOURCE_BROWSER is set to YES).
+# The default value is: NO.
+
+FILTER_SOURCE_FILES    = NO
+
+# The FILTER_SOURCE_PATTERNS tag can be used to specify source filters per file
+# pattern. A pattern will override the setting for FILTER_PATTERN (if any) and
+# it is also possible to disable source filtering for a specific pattern using
+# *.ext= (so without naming a filter).
+# This tag requires that the tag FILTER_SOURCE_FILES is set to YES.
+
+FILTER_SOURCE_PATTERNS =
+
+# If the USE_MDFILE_AS_MAINPAGE tag refers to the name of a markdown file that
+# is part of the input, its contents will be placed on the main page
+# (index.html). This can be useful if you have a project on for instance GitHub
+# and want to reuse the introduction page also for the doxygen output.
+
+USE_MDFILE_AS_MAINPAGE =
+
+#---------------------------------------------------------------------------
+# Configuration options related to source browsing
+#---------------------------------------------------------------------------
+
+# If the SOURCE_BROWSER tag is set to YES then a list of source files will be
+# generated. Documented entities will be cross-referenced with these sources.
+#
+# Note: To get rid of all source code in the generated output, make sure that
+# also VERBATIM_HEADERS is set to NO.
+# The default value is: NO.
+
+SOURCE_BROWSER         = NO
+
+# Setting the INLINE_SOURCES tag to YES will include the body of functions,
+# classes and enums directly into the documentation.
+# The default value is: NO.
+
+INLINE_SOURCES         = NO
+
+# Setting the STRIP_CODE_COMMENTS tag to YES will instruct doxygen to hide any
+# special comment blocks from generated source code fragments. Normal C, C++ and
+# Fortran comments will always remain visible.
+# The default value is: YES.
+
+STRIP_CODE_COMMENTS    = YES
+
+# If the REFERENCED_BY_RELATION tag is set to YES then for each documented
+# entity all documented functions referencing it will be listed.
+# The default value is: NO.
+
+REFERENCED_BY_RELATION = NO
+
+# If the REFERENCES_RELATION tag is set to YES then for each documented function
+# all documented entities called/used by that function will be listed.
+# The default value is: NO.
+
+REFERENCES_RELATION    = NO
+
+# If the REFERENCES_LINK_SOURCE tag is set to YES and SOURCE_BROWSER tag is set
+# to YES then the hyperlinks from functions in REFERENCES_RELATION and
+# REFERENCED_BY_RELATION lists will link to the source code. Otherwise they will
+# link to the documentation.
+# The default value is: YES.
+
+REFERENCES_LINK_SOURCE = YES
+
+# If SOURCE_TOOLTIPS is enabled (the default) then hovering a hyperlink in the
+# source code will show a tooltip with additional information such as prototype,
+# brief description and links to the definition and documentation. Since this
+# will make the HTML file larger and loading of large files a bit slower, you
+# can opt to disable this feature.
+# The default value is: YES.
+# This tag requires that the tag SOURCE_BROWSER is set to YES.
+
+SOURCE_TOOLTIPS        = YES
+
+# If the USE_HTAGS tag is set to YES then the references to source code will
+# point to the HTML generated by the htags(1) tool instead of doxygen built-in
+# source browser. The htags tool is part of GNU's global source tagging system
+# (see https://www.gnu.org/software/global/global.html). You will need version
+# 4.8.6 or higher.
+#
+# To use it do the following:
+# - Install the latest version of global
+# - Enable SOURCE_BROWSER and USE_HTAGS in the configuration file
+# - Make sure the INPUT points to the root of the source tree
+# - Run doxygen as normal
+#
+# Doxygen will invoke htags (and that will in turn invoke gtags), so these
+# tools must be available from the command line (i.e. in the search path).
+#
+# The result: instead of the source browser generated by doxygen, the links to
+# source code will now point to the output of htags.
+# The default value is: NO.
+# This tag requires that the tag SOURCE_BROWSER is set to YES.
+
+USE_HTAGS              = NO
+
+# If the VERBATIM_HEADERS tag is set the YES then doxygen will generate a
+# verbatim copy of the header file for each class for which an include is
+# specified. Set to NO to disable this.
+# See also: Section \class.
+# The default value is: YES.
+
+VERBATIM_HEADERS       = YES
+
+# If the CLANG_ASSISTED_PARSING tag is set to YES then doxygen will use the
+# clang parser (see: http://clang.llvm.org/) for more accurate parsing at the
+# cost of reduced performance. This can be particularly helpful with template
+# rich C++ code for which doxygen's built-in parser lacks the necessary type
+# information.
+# Note: The availability of this option depends on whether or not doxygen was
+# generated with the -Duse_libclang=ON option for CMake.
+# The default value is: NO.
+
+CLANG_ASSISTED_PARSING = NO
+
+# If clang assisted parsing is enabled you can provide the compiler with command
+# line options that you would normally use when invoking the compiler. Note that
+# the include paths will already be set by doxygen for the files and directories
+# specified with INPUT and INCLUDE_PATH.
+# This tag requires that the tag CLANG_ASSISTED_PARSING is set to YES.
+
+CLANG_OPTIONS          =
+
+# If clang assisted parsing is enabled you can provide the clang parser with the
+# path to the compilation database (see:
+# http://clang.llvm.org/docs/HowToSetupToolingForLLVM.html) used when the files
+# were built. This is equivalent to specifying the "-p" option to a clang tool,
+# such as clang-check. These options will then be passed to the parser.
+# Note: The availability of this option depends on whether or not doxygen was
+# generated with the -Duse_libclang=ON option for CMake.
+
+CLANG_DATABASE_PATH    =
+
+#---------------------------------------------------------------------------
+# Configuration options related to the alphabetical class index
+#---------------------------------------------------------------------------
+
+# If the ALPHABETICAL_INDEX tag is set to YES, an alphabetical index of all
+# compounds will be generated. Enable this if the project contains a lot of
+# classes, structs, unions or interfaces.
+# The default value is: YES.
+
+ALPHABETICAL_INDEX     = YES
+
+# The COLS_IN_ALPHA_INDEX tag can be used to specify the number of columns in
+# which the alphabetical index list will be split.
+# Minimum value: 1, maximum value: 20, default value: 5.
+# This tag requires that the tag ALPHABETICAL_INDEX is set to YES.
+
+COLS_IN_ALPHA_INDEX    = 5
+
+# In case all classes in a project start with a common prefix, all classes will
+# be put under the same header in the alphabetical index. The IGNORE_PREFIX tag
+# can be used to specify a prefix (or a list of prefixes) that should be ignored
+# while generating the index headers.
+# This tag requires that the tag ALPHABETICAL_INDEX is set to YES.
+
+IGNORE_PREFIX          =
+
+#---------------------------------------------------------------------------
+# Configuration options related to the HTML output
+#---------------------------------------------------------------------------
+
+# If the GENERATE_HTML tag is set to YES, doxygen will generate HTML output
+# The default value is: YES.
+
+GENERATE_HTML          = YES
+
+# The HTML_OUTPUT tag is used to specify where the HTML docs will be put. If a
+# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of
+# it.
+# The default directory is: html.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_OUTPUT            = html
+
+# The HTML_FILE_EXTENSION tag can be used to specify the file extension for each
+# generated HTML page (for example: .htm, .php, .asp).
+# The default value is: .html.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_FILE_EXTENSION    = .html
+
+# The HTML_HEADER tag can be used to specify a user-defined HTML header file for
+# each generated HTML page. If the tag is left blank doxygen will generate a
+# standard header.
+#
+# To get valid HTML the header file that includes any scripts and style sheets
+# that doxygen needs, which is dependent on the configuration options used (e.g.
+# the setting GENERATE_TREEVIEW). It is highly recommended to start with a
+# default header using
+# doxygen -w html new_header.html new_footer.html new_stylesheet.css
+# YourConfigFile
+# and then modify the file new_header.html. See also section "Doxygen usage"
+# for information on how to generate the default header that doxygen normally
+# uses.
+# Note: The header is subject to change so you typically have to regenerate the
+# default header when upgrading to a newer version of doxygen. For a description
+# of the possible markers and block names see the documentation.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_HEADER            =
+
+# The HTML_FOOTER tag can be used to specify a user-defined HTML footer for each
+# generated HTML page. If the tag is left blank doxygen will generate a standard
+# footer. See HTML_HEADER for more information on how to generate a default
+# footer and what special commands can be used inside the footer. See also
+# section "Doxygen usage" for information on how to generate the default footer
+# that doxygen normally uses.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_FOOTER            =
+
+# The HTML_STYLESHEET tag can be used to specify a user-defined cascading style
+# sheet that is used by each HTML page. It can be used to fine-tune the look of
+# the HTML output. If left blank doxygen will generate a default style sheet.
+# See also section "Doxygen usage" for information on how to generate the style
+# sheet that doxygen normally uses.
+# Note: It is recommended to use HTML_EXTRA_STYLESHEET instead of this tag, as
+# it is more robust and this tag (HTML_STYLESHEET) will in the future become
+# obsolete.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_STYLESHEET        =
+
+# The HTML_EXTRA_STYLESHEET tag can be used to specify additional user-defined
+# cascading style sheets that are included after the standard style sheets
+# created by doxygen. Using this option one can overrule certain style aspects.
+# This is preferred over using HTML_STYLESHEET since it does not replace the
+# standard style sheet and is therefore more robust against future updates.
+# Doxygen will copy the style sheet files to the output directory.
+# Note: The order of the extra style sheet files is of importance (e.g. the last
+# style sheet in the list overrules the setting of the previous ones in the
+# list). For an example see the documentation.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_EXTRA_STYLESHEET  =
+
+# The HTML_EXTRA_FILES tag can be used to specify one or more extra images or
+# other source files which should be copied to the HTML output directory. Note
+# that these files will be copied to the base HTML output directory. Use the
+# $relpath^ marker in the HTML_HEADER and/or HTML_FOOTER files to load these
+# files. In the HTML_STYLESHEET file, use the file name only. Also note that the
+# files will be copied as-is; there are no commands or markers available.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_EXTRA_FILES       =
+
+# The HTML_COLORSTYLE_HUE tag controls the color of the HTML output. Doxygen
+# will adjust the colors in the style sheet and background images according to
+# this color. Hue is specified as an angle on a colorwheel, see
+# https://en.wikipedia.org/wiki/Hue for more information. For instance the value
+# 0 represents red, 60 is yellow, 120 is green, 180 is cyan, 240 is blue, 300
+# purple, and 360 is red again.
+# Minimum value: 0, maximum value: 359, default value: 220.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_COLORSTYLE_HUE    = 220
+
+# The HTML_COLORSTYLE_SAT tag controls the purity (or saturation) of the colors
+# in the HTML output. For a value of 0 the output will use grayscales only. A
+# value of 255 will produce the most vivid colors.
+# Minimum value: 0, maximum value: 255, default value: 100.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_COLORSTYLE_SAT    = 100
+
+# The HTML_COLORSTYLE_GAMMA tag controls the gamma correction applied to the
+# luminance component of the colors in the HTML output. Values below 100
+# gradually make the output lighter, whereas values above 100 make the output
+# darker. The value divided by 100 is the actual gamma applied, so 80 represents
+# a gamma of 0.8, The value 220 represents a gamma of 2.2, and 100 does not
+# change the gamma.
+# Minimum value: 40, maximum value: 240, default value: 80.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_COLORSTYLE_GAMMA  = 80
+
+# If the HTML_TIMESTAMP tag is set to YES then the footer of each generated HTML
+# page will contain the date and time when the page was generated. Setting this
+# to YES can help to show when doxygen was last run and thus if the
+# documentation is up to date.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_TIMESTAMP         = NO
+
+# If the HTML_DYNAMIC_MENUS tag is set to YES then the generated HTML
+# documentation will contain a main index with vertical navigation menus that
+# are dynamically created via JavaScript. If disabled, the navigation index will
+# consists of multiple levels of tabs that are statically embedded in every HTML
+# page. Disable this option to support browsers that do not have JavaScript,
+# like the Qt help browser.
+# The default value is: YES.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_DYNAMIC_MENUS     = YES
+
+# If the HTML_DYNAMIC_SECTIONS tag is set to YES then the generated HTML
+# documentation will contain sections that can be hidden and shown after the
+# page has loaded.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_DYNAMIC_SECTIONS  = NO
+
+# With HTML_INDEX_NUM_ENTRIES one can control the preferred number of entries
+# shown in the various tree structured indices initially; the user can expand
+# and collapse entries dynamically later on. Doxygen will expand the tree to
+# such a level that at most the specified number of entries are visible (unless
+# a fully collapsed tree already exceeds this amount). So setting the number of
+# entries 1 will produce a full collapsed tree by default. 0 is a special value
+# representing an infinite number of entries and will result in a full expanded
+# tree by default.
+# Minimum value: 0, maximum value: 9999, default value: 100.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_INDEX_NUM_ENTRIES = 100
+
+# If the GENERATE_DOCSET tag is set to YES, additional index files will be
+# generated that can be used as input for Apple's Xcode 3 integrated development
+# environment (see: https://developer.apple.com/xcode/), introduced with OSX
+# 10.5 (Leopard). To create a documentation set, doxygen will generate a
+# Makefile in the HTML output directory. Running make will produce the docset in
+# that directory and running make install will install the docset in
+# ~/Library/Developer/Shared/Documentation/DocSets so that Xcode will find it at
+# startup. See https://developer.apple.com/library/archive/featuredarticles/Doxy
+# genXcode/_index.html for more information.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+GENERATE_DOCSET        = NO
+
+# This tag determines the name of the docset feed. A documentation feed provides
+# an umbrella under which multiple documentation sets from a single provider
+# (such as a company or product suite) can be grouped.
+# The default value is: Doxygen generated docs.
+# This tag requires that the tag GENERATE_DOCSET is set to YES.
+
+DOCSET_FEEDNAME        = "Doxygen generated docs"
+
+# This tag specifies a string that should uniquely identify the documentation
+# set bundle. This should be a reverse domain-name style string, e.g.
+# com.mycompany.MyDocSet. Doxygen will append .docset to the name.
+# The default value is: org.doxygen.Project.
+# This tag requires that the tag GENERATE_DOCSET is set to YES.
+
+DOCSET_BUNDLE_ID       = org.doxygen.Project
+
+# The DOCSET_PUBLISHER_ID tag specifies a string that should uniquely identify
+# the documentation publisher. This should be a reverse domain-name style
+# string, e.g. com.mycompany.MyDocSet.documentation.
+# The default value is: org.doxygen.Publisher.
+# This tag requires that the tag GENERATE_DOCSET is set to YES.
+
+DOCSET_PUBLISHER_ID    = org.doxygen.Publisher
+
+# The DOCSET_PUBLISHER_NAME tag identifies the documentation publisher.
+# The default value is: Publisher.
+# This tag requires that the tag GENERATE_DOCSET is set to YES.
+
+DOCSET_PUBLISHER_NAME  = Publisher
+
+# If the GENERATE_HTMLHELP tag is set to YES then doxygen generates three
+# additional HTML index files: index.hhp, index.hhc, and index.hhk. The
+# index.hhp is a project file that can be read by Microsoft's HTML Help Workshop
+# (see: https://www.microsoft.com/en-us/download/details.aspx?id=21138) on
+# Windows.
+#
+# The HTML Help Workshop contains a compiler that can convert all HTML output
+# generated by doxygen into a single compiled HTML file (.chm). Compiled HTML
+# files are now used as the Windows 98 help format, and will replace the old
+# Windows help format (.hlp) on all Windows platforms in the future. Compressed
+# HTML files also contain an index, a table of contents, and you can search for
+# words in the documentation. The HTML workshop also contains a viewer for
+# compressed HTML files.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+GENERATE_HTMLHELP      = NO
+
+# The CHM_FILE tag can be used to specify the file name of the resulting .chm
+# file. You can add a path in front of the file if the result should not be
+# written to the html output directory.
+# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
+
+CHM_FILE               =
+
+# The HHC_LOCATION tag can be used to specify the location (absolute path
+# including file name) of the HTML help compiler (hhc.exe). If non-empty,
+# doxygen will try to run the HTML help compiler on the generated index.hhp.
+# The file has to be specified with full path.
+# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
+
+HHC_LOCATION           =
+
+# The GENERATE_CHI flag controls if a separate .chi index file is generated
+# (YES) or that it should be included in the master .chm file (NO).
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
+
+GENERATE_CHI           = NO
+
+# The CHM_INDEX_ENCODING is used to encode HtmlHelp index (hhk), content (hhc)
+# and project file content.
+# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
+
+CHM_INDEX_ENCODING     =
+
+# The BINARY_TOC flag controls whether a binary table of contents is generated
+# (YES) or a normal table of contents (NO) in the .chm file. Furthermore it
+# enables the Previous and Next buttons.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
+
+BINARY_TOC             = NO
+
+# The TOC_EXPAND flag can be set to YES to add extra items for group members to
+# the table of contents of the HTML help documentation and to the tree view.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
+
+TOC_EXPAND             = NO
+
+# If the GENERATE_QHP tag is set to YES and both QHP_NAMESPACE and
+# QHP_VIRTUAL_FOLDER are set, an additional index file will be generated that
+# can be used as input for Qt's qhelpgenerator to generate a Qt Compressed Help
+# (.qch) of the generated HTML documentation.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+GENERATE_QHP           = NO
+
+# If the QHG_LOCATION tag is specified, the QCH_FILE tag can be used to specify
+# the file name of the resulting .qch file. The path specified is relative to
+# the HTML output folder.
+# This tag requires that the tag GENERATE_QHP is set to YES.
+
+QCH_FILE               =
+
+# The QHP_NAMESPACE tag specifies the namespace to use when generating Qt Help
+# Project output. For more information please see Qt Help Project / Namespace
+# (see: https://doc.qt.io/archives/qt-4.8/qthelpproject.html#namespace).
+# The default value is: org.doxygen.Project.
+# This tag requires that the tag GENERATE_QHP is set to YES.
+
+QHP_NAMESPACE          = org.doxygen.Project
+
+# The QHP_VIRTUAL_FOLDER tag specifies the namespace to use when generating Qt
+# Help Project output. For more information please see Qt Help Project / Virtual
+# Folders (see: https://doc.qt.io/archives/qt-4.8/qthelpproject.html#virtual-
+# folders).
+# The default value is: doc.
+# This tag requires that the tag GENERATE_QHP is set to YES.
+
+QHP_VIRTUAL_FOLDER     = doc
+
+# If the QHP_CUST_FILTER_NAME tag is set, it specifies the name of a custom
+# filter to add. For more information please see Qt Help Project / Custom
+# Filters (see: https://doc.qt.io/archives/qt-4.8/qthelpproject.html#custom-
+# filters).
+# This tag requires that the tag GENERATE_QHP is set to YES.
+
+QHP_CUST_FILTER_NAME   =
+
+# The QHP_CUST_FILTER_ATTRS tag specifies the list of the attributes of the
+# custom filter to add. For more information please see Qt Help Project / Custom
+# Filters (see: https://doc.qt.io/archives/qt-4.8/qthelpproject.html#custom-
+# filters).
+# This tag requires that the tag GENERATE_QHP is set to YES.
+
+QHP_CUST_FILTER_ATTRS  =
+
+# The QHP_SECT_FILTER_ATTRS tag specifies the list of the attributes this
+# project's filter section matches. Qt Help Project / Filter Attributes (see:
+# https://doc.qt.io/archives/qt-4.8/qthelpproject.html#filter-attributes).
+# This tag requires that the tag GENERATE_QHP is set to YES.
+
+QHP_SECT_FILTER_ATTRS  =
+
+# The QHG_LOCATION tag can be used to specify the location of Qt's
+# qhelpgenerator. If non-empty doxygen will try to run qhelpgenerator on the
+# generated .qhp file.
+# This tag requires that the tag GENERATE_QHP is set to YES.
+
+QHG_LOCATION           =
+
+# If the GENERATE_ECLIPSEHELP tag is set to YES, additional index files will be
+# generated, together with the HTML files, they form an Eclipse help plugin. To
+# install this plugin and make it available under the help contents menu in
+# Eclipse, the contents of the directory containing the HTML and XML files needs
+# to be copied into the plugins directory of eclipse. The name of the directory
+# within the plugins directory should be the same as the ECLIPSE_DOC_ID value.
+# After copying Eclipse needs to be restarted before the help appears.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+GENERATE_ECLIPSEHELP   = NO
+
+# A unique identifier for the Eclipse help plugin. When installing the plugin
+# the directory name containing the HTML and XML files should also have this
+# name. Each documentation set should have its own identifier.
+# The default value is: org.doxygen.Project.
+# This tag requires that the tag GENERATE_ECLIPSEHELP is set to YES.
+
+ECLIPSE_DOC_ID         = org.doxygen.Project
+
+# If you want full control over the layout of the generated HTML pages it might
+# be necessary to disable the index and replace it with your own. The
+# DISABLE_INDEX tag can be used to turn on/off the condensed index (tabs) at top
+# of each HTML page. A value of NO enables the index and the value YES disables
+# it. Since the tabs in the index contain the same information as the navigation
+# tree, you can set this option to YES if you also set GENERATE_TREEVIEW to YES.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+DISABLE_INDEX          = NO
+
+# The GENERATE_TREEVIEW tag is used to specify whether a tree-like index
+# structure should be generated to display hierarchical information. If the tag
+# value is set to YES, a side panel will be generated containing a tree-like
+# index structure (just like the one that is generated for HTML Help). For this
+# to work a browser that supports JavaScript, DHTML, CSS and frames is required
+# (i.e. any modern browser). Windows users are probably better off using the
+# HTML help feature. Via custom style sheets (see HTML_EXTRA_STYLESHEET) one can
+# further fine-tune the look of the index. As an example, the default style
+# sheet generated by doxygen has an example that shows how to put an image at
+# the root of the tree instead of the PROJECT_NAME. Since the tree basically has
+# the same information as the tab index, you could consider setting
+# DISABLE_INDEX to YES when enabling this option.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+GENERATE_TREEVIEW      = NO
+
+# The ENUM_VALUES_PER_LINE tag can be used to set the number of enum values that
+# doxygen will group on one line in the generated HTML documentation.
+#
+# Note that a value of 0 will completely suppress the enum values from appearing
+# in the overview section.
+# Minimum value: 0, maximum value: 20, default value: 4.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+ENUM_VALUES_PER_LINE   = 4
+
+# If the treeview is enabled (see GENERATE_TREEVIEW) then this tag can be used
+# to set the initial width (in pixels) of the frame in which the tree is shown.
+# Minimum value: 0, maximum value: 1500, default value: 250.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+TREEVIEW_WIDTH         = 250
+
+# If the EXT_LINKS_IN_WINDOW option is set to YES, doxygen will open links to
+# external symbols imported via tag files in a separate window.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+EXT_LINKS_IN_WINDOW    = NO
+
+# Use this tag to change the font size of LaTeX formulas included as images in
+# the HTML documentation. When you change the font size after a successful
+# doxygen run you need to manually remove any form_*.png images from the HTML
+# output directory to force them to be regenerated.
+# Minimum value: 8, maximum value: 50, default value: 10.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+FORMULA_FONTSIZE       = 10
+
+# Use the FORMULA_TRANSPARENT tag to determine whether or not the images
+# generated for formulas are transparent PNGs. Transparent PNGs are not
+# supported properly for IE 6.0, but are supported on all modern browsers.
+#
+# Note that when changing this option you need to delete any form_*.png files in
+# the HTML output directory before the changes have effect.
+# The default value is: YES.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+FORMULA_TRANSPARENT    = YES
+
+# The FORMULA_MACROFILE can contain LaTeX \newcommand and \renewcommand commands
+# to create new LaTeX commands to be used in formulas as building blocks. See
+# the section "Including formulas" for details.
+
+FORMULA_MACROFILE      =
+
+# Enable the USE_MATHJAX option to render LaTeX formulas using MathJax (see
+# https://www.mathjax.org) which uses client side JavaScript for the rendering
+# instead of using pre-rendered bitmaps. Use this if you do not have LaTeX
+# installed or if you want to formulas look prettier in the HTML output. When
+# enabled you may also need to install MathJax separately and configure the path
+# to it using the MATHJAX_RELPATH option.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+USE_MATHJAX            = YES
+
+# When MathJax is enabled you can set the default output format to be used for
+# the MathJax output. See the MathJax site (see:
+# http://docs.mathjax.org/en/latest/output.html) for more details.
+# Possible values are: HTML-CSS (which is slower, but has the best
+# compatibility), NativeMML (i.e. MathML) and SVG.
+# The default value is: HTML-CSS.
+# This tag requires that the tag USE_MATHJAX is set to YES.
+
+MATHJAX_FORMAT         = HTML-CSS
+
+# When MathJax is enabled you need to specify the location relative to the HTML
+# output directory using the MATHJAX_RELPATH option. The destination directory
+# should contain the MathJax.js script. For instance, if the mathjax directory
+# is located at the same level as the HTML output directory, then
+# MATHJAX_RELPATH should be ../mathjax. The default value points to the MathJax
+# Content Delivery Network so you can quickly see the result without installing
+# MathJax. However, it is strongly recommended to install a local copy of
+# MathJax from https://www.mathjax.org before deployment.
+# The default value is: https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/.
+# This tag requires that the tag USE_MATHJAX is set to YES.
+
+MATHJAX_RELPATH        = https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/
+
+# The MATHJAX_EXTENSIONS tag can be used to specify one or more MathJax
+# extension names that should be enabled during MathJax rendering. For example
+# MATHJAX_EXTENSIONS = TeX/AMSmath TeX/AMSsymbols
+# This tag requires that the tag USE_MATHJAX is set to YES.
+
+MATHJAX_EXTENSIONS     =
+
+# The MATHJAX_CODEFILE tag can be used to specify a file with javascript pieces
+# of code that will be used on startup of the MathJax code. See the MathJax site
+# (see: http://docs.mathjax.org/en/latest/output.html) for more details. For an
+# example see the documentation.
+# This tag requires that the tag USE_MATHJAX is set to YES.
+
+MATHJAX_CODEFILE       =
+
+# When the SEARCHENGINE tag is enabled doxygen will generate a search box for
+# the HTML output. The underlying search engine uses javascript and DHTML and
+# should work on any modern browser. Note that when using HTML help
+# (GENERATE_HTMLHELP), Qt help (GENERATE_QHP), or docsets (GENERATE_DOCSET)
+# there is already a search function so this one should typically be disabled.
+# For large projects the javascript based search engine can be slow, then
+# enabling SERVER_BASED_SEARCH may provide a better solution. It is possible to
+# search using the keyboard; to jump to the search box use  + S
+# (what the  is depends on the OS and browser, but it is typically
+# , /