""" python -c "from datasets import load_dataset;load_dataset('.')" """ import json from itertools import chain import datasets logger = datasets.logging.get_logger(__name__) _VERSION = "5.0.1" _NAME = "qg_ruquad" _CITATION = """ @inproceedings{ushio-etal-2022-generative, title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration", author = "Ushio, Asahi and Alva-Manchego, Fernando and Camacho-Collados, Jose", booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing", month = dec, year = "2022", address = "Abu Dhabi, U.A.E.", publisher = "Association for Computational Linguistics", } """ _DESCRIPTION = """[SberSQuAD](https://huggingface.co/datasets/sberquad) dataset for question generation (QG) task.""" _URL = 'https://huggingface.co/datasets/lmqg/qg_ruquad/resolve/main/data/processed' _URLS = { str(datasets.Split.TEST): [f'{_URL}/test{i:02d}.jsonl' for i in range(8)], str(datasets.Split.TRAIN): [f'{_URL}/train{i:02d}.jsonl' for i in range(58)], str(datasets.Split.VALIDATION): [f'{_URL}/validation{i:02d}.jsonl' for i in range(8)], # str(datasets.Split.TEST): f'{_URL}/test.jsonl', # str(datasets.Split.TRAIN): f'{_URL}/train.jsonl', # str(datasets.Split.VALIDATION): f'{_URL}/validation.jsonl' } class QGRuQuADConfig(datasets.BuilderConfig): """BuilderConfig for SquadQG""" def __init__(self, **kwargs): """BuilderConfig for SquadQG. Args: **kwargs: keyword arguments forwarded to super. """ super(QGRuQuADConfig, self).__init__(**kwargs) class QGRuQuAD(datasets.GeneratorBasedBuilder): BUILDER_CONFIGS = [ QGRuQuADConfig(name=_NAME, version=datasets.Version(_VERSION), description=_DESCRIPTION), ] def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "answer": datasets.Value("string"), "paragraph_question": datasets.Value("string"), "question": datasets.Value("string"), "sentence": datasets.Value("string"), "paragraph": datasets.Value("string"), "sentence_answer": datasets.Value("string"), "paragraph_answer": datasets.Value("string"), "paragraph_sentence": datasets.Value("string"), "paragraph_id": datasets.Value("string") } ), supervised_keys=None, homepage="https://github.com/asahi417/lm-question-generation" ) def _split_generators(self, dl_manager): downloaded_file = dl_manager.download_and_extract(_URLS) return [datasets.SplitGenerator(name=i, gen_kwargs={"filepaths": downloaded_file[str(i)]}) for i in [datasets.Split.TRAIN, datasets.Split.VALIDATION, datasets.Split.TEST]] def _generate_examples(self, filepaths): _key = 0 for filepath in filepaths: logger.info("generating examples from = %s", filepath) with open(filepath, encoding="utf-8") as f: _list = f.read().split('\n') if _list[-1] == '': _list = _list[:-1] for i in _list: data = json.loads(i) yield _key, data _key += 1