Source code for deeppavlov.dataset_readers.squad_dataset_reader

# Copyright 2017 Neural Networks and Deep Learning lab, MIPT
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#     http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
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import json
from pathlib import Path
from typing import Dict, Any, Optional

from deeppavlov.core.common.registry import register
from deeppavlov.core.data.dataset_reader import DatasetReader
from deeppavlov.core.data.utils import download_decompress


[docs]@register('squad_dataset_reader') class SquadDatasetReader(DatasetReader): """ Downloads dataset files and prepares train/valid split. SQuAD: Stanford Question Answering Dataset https://rajpurkar.github.io/SQuAD-explorer/ SQuAD2.0: Stanford Question Answering Dataset, version 2.0 https://rajpurkar.github.io/SQuAD-explorer/ SberSQuAD: Dataset from SDSJ Task B https://www.sdsj.ru/ru/contest.html MultiSQuAD: SQuAD dataset with additional contexts retrieved (by tfidf) from original Wikipedia article. MultiSQuADRetr: SQuAD dataset with additional contexts retrieved by tfidf document ranker from full Wikipedia. """ url_squad = 'http://files.deeppavlov.ai/datasets/squad-v1.1.tar.gz' url_sber_squad = 'http://files.deeppavlov.ai/datasets/sber_squad-v1.1.tar.gz' url_multi_squad = 'http://files.deeppavlov.ai/datasets/multiparagraph_squad.tar.gz' url_squad2 = 'http://files.deeppavlov.ai/datasets/squad-v2.0.tar.gz'
[docs] def read(self, data_path: str, dataset: Optional[str] = 'SQuAD', url: Optional[str] = None, *args, **kwargs) \ -> Dict[str, Dict[str, Any]]: """ Args: data_path: path to save data dataset: default dataset names: ``'SQuAD'``, ``'SberSQuAD'`` or ``'MultiSQuAD'`` url: link to archive with dataset, use url argument if non-default dataset is used Returns: dataset split on train/valid Raises: RuntimeError: if `dataset` is not one of these: ``'SQuAD'``, ``'SberSQuAD'``, ``'MultiSQuAD'``. """ if url is not None: self.url = url elif dataset == 'SQuAD': self.url = self.url_squad elif dataset == 'SberSQuAD': self.url = self.url_sber_squad elif dataset == 'MultiSQuAD': self.url = self.url_multi_squad elif dataset == 'SQuAD2.0': self.url = self.url_squad2 else: raise RuntimeError(f'Dataset {dataset} is unknown') data_path = Path(data_path) if dataset == "SQuAD2.0": required_files = [f'{dt}-v2.0.json' for dt in ['train', 'dev']] else: required_files = [f'{dt}-v1.1.json' for dt in ['train', 'dev']] data_path.mkdir(parents=True, exist_ok=True) if not all((data_path / f).exists() for f in required_files): download_decompress(self.url, data_path) dataset = {} for f in required_files: with data_path.joinpath(f).open('r', encoding='utf8') as fp: data = json.load(fp) if f in {'dev-v1.1.json', 'dev-v2.0.json'}: dataset['valid'] = data else: dataset['train'] = data return dataset
@register('multi_squad_dataset_reader') class MultiSquadDatasetReader(DatasetReader): """ Downloads dataset files and prepares train/valid split. MultiSQuADRetr: Multiparagraph SQuAD dataset with additional contexts retrieved by tfidf document ranker from full En Wikipedia. MultiSQuADRuRetr: Multiparagraph SberSQuAD dataset with additional contexts retrieved by tfidf document ranker from Ru Wikipedia. """ url_multi_squad_retr = 'http://files.deeppavlov.ai/datasets/multi_squad_retr_enwiki20161221.tar.gz' url_multi_squad_ru_retr = 'http://files.deeppavlov.ai/datasets/multi_squad_ru_retr.tar.gz' def read(self, data_path: str, dataset: Optional[str] = 'MultiSQuADRetr', url: Optional[str] = None, *args, **kwargs) -> Dict[str, Dict[str, Any]]: """ Args: data_path: path to save data dataset: default dataset names: ``'MultiSQuADRetr'``, ``'MultiSQuADRuRetr'`` url: link to archive with dataset, use url argument if non-default dataset is used Returns: dataset split on train/valid Raises: RuntimeError: if `dataset` is not one of these: ``'MultiSQuADRetr'``, ``'MultiSQuADRuRetr'``. """ if url is not None: self.url = url elif dataset == 'MultiSQuADRetr': self.url = self.url_multi_squad_retr elif dataset == 'MultiSQuADRuRetr': self.url = self.url_multi_squad_ru_retr else: raise RuntimeError(f'Dataset {dataset} is unknown') data_path = Path(data_path) required_files = [f'{dt}.jsonl' for dt in ['train', 'dev']] if not data_path.exists(): data_path.mkdir(parents=True) if not all((data_path / f).exists() for f in required_files): download_decompress(self.url, data_path) dataset = {} for f in required_files: if 'dev' in f: dataset['valid'] = data_path.joinpath(f) else: dataset['train'] = data_path.joinpath(f) return dataset