import json import datasets logger = datasets.logging.get_logger(__name__) _VERSION = "0.0.0" _NAME = "qag_koquad" _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 = """Question & answer generation dataset based on SQuAD.""" _URL = f"https://huggingface.co/datasets/lmqg/{_NAME}/resolve/main/data/processed" _URLS = { 'train': f'{_URL}/train.jsonl', 'test': f'{_URL}/test.jsonl', 'validation': f'{_URL}/validation.jsonl' } class QAGKOQuADConfig(datasets.BuilderConfig): """BuilderConfig""" def __init__(self, **kwargs): """BuilderConfig. Args: **kwargs: keyword arguments forwarded to super. """ super(QAGKOQuADConfig, self).__init__(**kwargs) class QAGKOQuAD(datasets.GeneratorBasedBuilder): BUILDER_CONFIGS = [ QAGKOQuADConfig(name=_NAME, version=datasets.Version(_VERSION), description=_DESCRIPTION), ] def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "answers": datasets.Sequence(datasets.Value("string")), "questions": datasets.Sequence(datasets.Value("string")), "paragraph": datasets.Value("string"), "questions_answers": 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=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_file["train"]}), datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_file["validation"]}), datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_file["test"]}), ] def _generate_examples(self, filepath): _key = 0 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