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Dnnc config arg #585

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Fix requirements.txt (#84)
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25 changes: 25 additions & 0 deletions annotators/dnnc_intents/Dockerfile
Original file line number Diff line number Diff line change
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FROM deeppavlov/base-gpu:0.17.5

RUN pip install git+https://github.com/deeppavlov/[email protected]
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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.


WORKDIR /base/DeepPavlov

WORKDIR /src
RUN mkdir common

COPY annotators/dnnc_intents/requirements.txt ./requirements.txt
RUN pip install -r requirements.txt

RUN python -m spacy download en_core_web_sm

ARG SERVICE_PORT
ENV SERVICE_PORT=$SERVICE_PORT
ARG CONFIG
ENV CONFIG=$CONFIG
ARG CLASSES
ENV CLASSES=$CLASSES

COPY annotators/dnnc_intents/ ./
COPY common/ common/

CMD gunicorn --workers=1 server:app -b 0.0.0.0:${SERVICE_PORT} --timeout=1200 --preload
10 changes: 10 additions & 0 deletions annotators/dnnc_intents/Readme.md
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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
75 changes: 75 additions & 0 deletions annotators/dnnc_intents/classifier.json
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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}"
}

]
}
}
61 changes: 61 additions & 0 deletions annotators/dnnc_intents/classifier_roberta.json
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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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