| import datasets | |
| import os | |
| from datasets import load_dataset | |
| from .m2d2_split_names import M2D2_SPLIT_NAMES | |
| CITATION = """ | |
| @inproceedings{reid2022m2d2, | |
| title={ {M2D2}: A Massively Multi-Domain Language Modeling Dataset }, | |
| author={ Machel Reid and Victor Zhong and Suchin Gururangan and Luke Zettlemoyer }, | |
| booktitle={ EMNLP }, | |
| year={ 2022 } | |
| } | |
| """ | |
| DESCRIPTION = """ | |
| M2D2 dataset from 'M2D2: A Massively Multi-Domain Language Modeling Dataset' | |
| """ | |
| FEATURES = datasets.Features({"text": datasets.Value("string")}) | |
| def _URLS(split): | |
| return f"https://huggingface.co/datasets/machelreid/m2d2/resolve/main/data/{split}.tar.gz" | |
| class M2D2Config(datasets.BuilderConfig): | |
| def __init__(self, features, citation, **kwargs): | |
| super().__init__(**kwargs) | |
| self.features = features | |
| self.citation = citation | |
| class M2D2(datasets.GeneratorBasedBuilder): | |
| BUILDER_CONFIGS = [ | |
| M2D2Config(name=name, features=FEATURES, citation=CITATION) | |
| for name in M2D2_SPLIT_NAMES | |
| ] | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=DESCRIPTION, citation=CITATION, features=FEATURES | |
| ) | |
| def _split_generators(self, dl_manager): | |
| urls = _URLS(self.config.name) | |
| data_dir = dl_manager.download_and_extract(urls) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "filepath": os.path.join(data_dir, self.config.name, "train.txt"), | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.VALIDATION, | |
| gen_kwargs={ | |
| "filepath": os.path.join(data_dir, self.config.name, "valid.txt"), | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| gen_kwargs={ | |
| "filepath": os.path.join(data_dir, self.config.name, "test.txt"), | |
| }, | |
| ), | |
| ] | |
| def _generate_examples(self, filepath): | |
| with open(filepath, encoding="utf-8") as f: | |
| for key, row in enumerate(f): | |
| data = row.strip() | |
| yield key, {"text": data} | |