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Dnnc config arg #585
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FROM deeppavlov/base-gpu:0.17.5 | ||
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RUN pip install git+https://github.com/deeppavlov/DeepPavlov.git@1.3.0 | ||
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WORKDIR /base/DeepPavlov | ||
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WORKDIR /src | ||
RUN mkdir common | ||
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COPY annotators/dnnc_intents/requirements.txt ./requirements.txt | ||
RUN pip install -r requirements.txt | ||
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RUN python -m spacy download en_core_web_sm | ||
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ARG SERVICE_PORT | ||
ENV SERVICE_PORT=$SERVICE_PORT | ||
ARG CONFIG | ||
ENV CONFIG=$CONFIG | ||
ARG CLASSES | ||
ENV CLASSES=$CLASSES | ||
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COPY annotators/dnnc_intents/ ./ | ||
COPY common/ common/ | ||
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CMD gunicorn --workers=1 server:app -b 0.0.0.0:${SERVICE_PORT} --timeout=1200 --preload |
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# DNNC intent classifier | ||
## Description | ||
Classifier that classifies DNNC intent in the few-shot mode. Default version is the logistic regression. Howeve, with config classifier_roberta.json entailment-trained roberta is also supported | ||
## Input/Output | ||
**Input** | ||
Batch of last utterances | ||
**Output** | ||
For each utterance - dictionary {probable class: probability} | ||
## Dependencies | ||
As stated in requirements.txt. And if you use entailment-trained roberta, file utils_roberta.py also is useful |
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{ | ||
"chainer": { | ||
"in": ["x"], | ||
"pipe": [ | ||
{ | ||
"class_name": "stream_spacy_tokenizer", | ||
"in": [ | ||
"x" | ||
], | ||
"id": "my_tokenizer", | ||
"lemmas": false, | ||
"out": "token_lemmas", | ||
"spacy_model": "en_core_web_sm", | ||
"support_load_path": "{DOWNLOADS_PATH}/logreg_files/support_dataset.json" | ||
}, | ||
{ | ||
"ref": "my_tokenizer", | ||
"in": [ | ||
"token_lemmas" | ||
], | ||
"out": [ | ||
"text_lem" | ||
] | ||
}, | ||
{ | ||
"class_name": "fasttext", | ||
"in": [ | ||
"token_lemmas" | ||
], | ||
"load_path": "{DOWNLOADS_PATH}/embeddings/fasttext/{LANGUAGE}.bin", | ||
"mean": true, | ||
"out": [ | ||
"text_vector" | ||
] | ||
}, | ||
{ | ||
"in": [ | ||
"text_vector" | ||
], | ||
"out": [ | ||
"y_pred_probas" | ||
], | ||
"class_name": "sklearn_component", | ||
"main": true, | ||
"save_path": "{DOWNLOADS_PATH}/logreg_files/model.pkl", | ||
"load_path": "{DOWNLOADS_PATH}/logreg_files/model.pkl", | ||
"model_class": "sklearn.linear_model:LogisticRegression", | ||
"infer_method": "predict_proba", | ||
"C": 10, | ||
"penalty": "l2" | ||
} | ||
], | ||
"out": ["y_pred_probas"] | ||
}, | ||
"metadata": { | ||
"variables": { | ||
"ROOT_PATH": "~/.deeppavlov", | ||
"DOWNLOADS_PATH":"{ROOT_PATH}/downloads", | ||
"LOGREG_PATH": "{DOWNLOADS_PATH}/logreg_files", | ||
"LANGUAGE":"en" | ||
}, | ||
"imports":["utils"], | ||
"download": [ | ||
{ | ||
"url": "http://files.deeppavlov.ai/embeddings/fasttext/{LANGUAGE}.bin", | ||
"subdir": "{DOWNLOADS_PATH}/embeddings/fasttext" | ||
}, | ||
{ | ||
"url": "https://files.deeppavlov.ai/dream_data/dnnc_intents/logreg_files.tar.gz", | ||
"subdir": "{LOGREG_PATH}" | ||
} | ||
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] | ||
} | ||
} |
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{ | ||
"chainer": { | ||
"in": ["text"], | ||
"pipe": [ | ||
{ | ||
"class_name": "dnnc_preparer", | ||
"in": ["text"], | ||
"out": ["texts","dataset"] | ||
}, | ||
{ | ||
"class_name": "dnnc_pairgenerator", | ||
"in": ["texts", "dataset"], | ||
"out": ["x", "x_support", "x_populated", "y_support"], | ||
"bidirectional": false | ||
}, | ||
{ | ||
"class_name": "torch_transformers_preprocessor", | ||
"in": ["x_populated", "x_support"], | ||
"out": ["bert_features"], | ||
"vocab_file": "{BASE_MODEL}", | ||
"do_lower_case": true, | ||
"max_seq_length": 128 | ||
}, | ||
{ | ||
"class_name": "torch_transformers_classifier_batch1", | ||
"main": true, | ||
"in": ["bert_features"], | ||
"out": ["simmilarity_scores"], | ||
"n_classes": 2, | ||
"return_probas": true, | ||
"pretrained_bert": "{BASE_MODEL}", | ||
"save_path": "{MODEL_PATH}/model", | ||
"load_path": "{MODEL_PATH}/model", | ||
"is_binary": "{BINARY_CLASSIFICATION}" | ||
}, | ||
{ | ||
"class_name": "dnnc_proba2labels", | ||
"is_binary": "{BINARY_CLASSIFICATION}", | ||
"in": ["simmilarity_scores", "x", "x_populated", "x_support", "y_support"], | ||
"out": ["y_pred"], | ||
"confidence_threshold": 0.0 | ||
} | ||
], | ||
"out": ["y_pred"] | ||
}, | ||
"metadata": { | ||
"variables": { | ||
"ROOT_PATH": "~/.deeppavlov", | ||
"MODEL_PATH": "{ROOT_PATH}/models/fewshot/roberta_nli_mrpc_1_10", | ||
"BINARY_CLASSIFICATION": true, | ||
"BASE_MODEL": "roberta-base" | ||
}, | ||
"imports":["utils_roberta"], | ||
"download": [ | ||
{ | ||
"url": "http://files.deeppavlov.ai/v1/classifiers/fewshot/roberta_nli_mrpc_1_10.tar.gz", | ||
"subdir": "{MODEL_PATH}" | ||
} | ||
] | ||
} | ||
} |
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а базового докер образа поновее сразу нет? чтобы не переставлять, а сразу взять новый? если нет, напиши Феде запрос на такой, пожалуйста, в паблик канале слака.