""" python -c "from datasets import load_dataset;load_dataset('.')" """ import json from itertools import chain import datasets logger = datasets.logging.get_logger(__name__) _DESCRIPTION = """[SQuAD Shifts](https://modestyachts.github.io/squadshifts-website/index.html) dataset for question generation (QG) task.""" _URL = 'https://huggingface.co/datasets/asahi417/qg_squadshift/raw/main/data/processed' _FILES = { str(datasets.Split.TEST): { 'new_wiki': [f'{_URL}/new_wiki.test{i:02d}.jsonl' for i in range(3)], 'nyt': [f'{_URL}/nyt.test{i:02d}.jsonl' for i in range(4)], 'reddit': [f'{_URL}/reddit.test{i:02d}.jsonl' for i in range(4)], 'amazon': [f'{_URL}/amazon.test{i:02d}.jsonl' for i in range(4)] }, str(datasets.Split.TRAIN): { 'new_wiki': [f'{_URL}/new_wiki.train{i:02d}.jsonl' for i in range(2)], 'nyt': [f'{_URL}/nyt.train{i:02d}.jsonl' for i in range(3)], 'reddit': [f'{_URL}/reddit.train{i:02d}.jsonl' for i in range(3)], 'amazon': [f'{_URL}/amazon.train{i:02d}.jsonl' for i in range(3)] }, str(datasets.Split.VALIDATION): { 'new_wiki': [f'{_URL}/new_wiki.validation{i:02d}.jsonl' for i in range(2)], 'nyt': [f'{_URL}/nyt.validation{i:02d}.jsonl' for i in range(3)], 'reddit': [f'{_URL}/reddit.validation{i:02d}.jsonl' for i in range(3)], 'amazon': [f'{_URL}/amazon.validation{i:02d}.jsonl' for i in range(3)] }, } # _FILES = { # str(datasets.Split.TEST): { # 'new_wiki': [f'{_URL}/new_wiki.test.jsonl'], # 'nyt': [f'{_URL}/nyt.test.jsonl'], # 'reddit': [f'{_URL}/reddit.test.jsonl'], # 'amazon': [f'{_URL}/amazon.test.jsonl'] # }, # str(datasets.Split.TRAIN): { # 'new_wiki': [f'{_URL}/new_wiki.train.jsonl'], # 'nyt': [f'{_URL}/nyt.train.jsonl'], # 'reddit': [f'{_URL}/reddit.train.jsonl'], # 'amazon': [f'{_URL}/amazon.train.jsonl'] # }, # str(datasets.Split.VALIDATION): { # 'new_wiki': [f'{_URL}/new_wiki.validation.jsonl'], # 'nyt': [f'{_URL}/nyt.validation.jsonl'], # 'reddit': [f'{_URL}/reddit.validation.jsonl'], # 'amazon': [f'{_URL}/amazon.validation.jsonl'] # }, # } _DOMAIN = list(_FILES[list(_FILES.keys())[0]].keys()) class QGSQuADShiftsConfig(datasets.BuilderConfig): """BuilderConfig for SquadQG""" def __init__(self, **kwargs): """BuilderConfig for SquadQG. Args: **kwargs: keyword arguments forwarded to super. """ super(QGSQuADShiftsConfig, self).__init__(**kwargs) class QGSQuADShifts(datasets.GeneratorBasedBuilder): BUILDER_CONFIGS = [QGSQuADShiftsConfig(name="default", description="All domain.")] BUILDER_CONFIGS += [QGSQuADShiftsConfig(name=i, description=f"Domain {i}") for i in sorted(_DOMAIN)] def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "answer": 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): if self.config.name == 'default': downloaded_file = dl_manager.download_and_extract({k: list(chain(*list(v.values()))) for k, v in _FILES.items()}) else: downloaded_file = dl_manager.download_and_extract({k: v[self.config.name] for k, v in _FILES.items()}) return [datasets.SplitGenerator(name=k, gen_kwargs={"filepaths": downloaded_file[k]}) for k in _FILES.keys()] 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