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add token_type_ids in lm forward signature #964

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merged 8 commits into from
Oct 31, 2024
Merged

add token_type_ids in lm forward signature #964

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958c365
add token_type_ids in lm forward signature
eaidova Oct 24, 2024
9fab315
update tests
eaidova Oct 28, 2024
7f2f404
Update tests/openvino/test_modeling.py
eaidova Oct 28, 2024
d36de5c
add message in tests
eaidova Oct 28, 2024
b5bed05
Update tests/openvino/test_modeling.py
eaidova Oct 28, 2024
43cca8f
Merge branch 'main' into ea/add_token_type_ids
eaidova Oct 29, 2024
3b0bf83
Update tests/openvino/test_modeling.py
echarlaix Oct 31, 2024
e298792
Update optimum/intel/openvino/modeling_decoder.py
echarlaix Oct 31, 2024
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2 changes: 2 additions & 0 deletions optimum/intel/openvino/modeling_decoder.py
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Original file line number Diff line number Diff line change
Expand Up @@ -522,9 +522,11 @@ def forward(
attention_mask: Optional[torch.LongTensor] = None,
past_key_values: Optional[Tuple[Tuple[torch.FloatTensor]]] = None,
position_ids: Optional[torch.LongTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
**kwargs,
) -> CausalLMOutputWithPast:
self.compile()
kwargs["token_type_ids"] = token_type_ids
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inputs = self.prepare_inputs(
input_ids=input_ids,
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9 changes: 5 additions & 4 deletions tests/openvino/test_modeling.py
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Expand Up @@ -872,7 +872,6 @@ def test_compare_to_transformers(self, model_arch):
self.assertTrue(ov_model.use_cache)
tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=model_arch in self.REMOTE_CODE_MODELS)
tokens = tokenizer("This is a sample output", return_tensors="pt")
tokens.pop("token_type_ids", None)

ov_outputs = ov_model(**tokens)
self.assertTrue("logits" in ov_outputs)
Expand Down Expand Up @@ -909,7 +908,6 @@ def test_compare_to_transformers(self, model_arch):
# Compare batched generation
tokenizer.padding_side = "left"
tokens = tokenizer(["Today is a nice day and I am longer", "This is me"], return_tensors="pt", padding=True)
tokens.pop("token_type_ids", None)
ov_model.generation_config.eos_token_id = None
transformers_model.generation_config.eos_token_id = None
ov_model.config.eos_token_id = None
Expand All @@ -933,7 +931,10 @@ def test_compare_to_transformers(self, model_arch):

additional_inputs = {"past_key_values": DynamicCache()}
transformers_outputs = transformers_model.generate(**tokens, generation_config=gen_config, **additional_inputs)
self.assertTrue(torch.allclose(ov_outputs, transformers_outputs))
self.assertTrue(
torch.allclose(ov_outputs, transformers_outputs),
"OV output {ov_outputs}\nTransofrmers output {transformers_output}",
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)

del transformers_model
del ov_model
Expand Down Expand Up @@ -1102,6 +1103,7 @@ def test_beam_search(self, model_arch):
# starting from transformers 4.45.0 gemma2 uses eager attention by default, while ov - sdpa
if model_arch == "gemma2" and is_transformers_version(">=", "4.45.0"):
model_kwargs["attn_implementation"] = "sdpa"

# Qwen tokenizer does not support padding, chatglm, glm4 testing models produce nan that incompatible with beam search
if model_arch in ["qwen", "chatglm", "glm4"]:
return
Expand Down Expand Up @@ -1177,7 +1179,6 @@ def test_beam_search(self, model_arch):
from transformers.cache_utils import DynamicCache
tokenizer.pad_token_id = tokenizer.eos_token_id
tokens = tokenizer(["Today is a nice day and I am longer", "This is me"], return_tensors="pt", padding=True)
tokens.pop("token_type_ids", None)
ov_model_stateful.generation_config.eos_token_id = None
ov_model_stateless.generation_config.eos_token_id = None
transformers_model.generation_config.eos_token_id = None
Expand Down
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