| | |
| | |
| | import json |
| | import pathlib |
| |
|
| | import datasets |
| | import fsspec |
| | from datasets import DatasetInfo, Value, Features |
| |
|
| | logger = datasets.logging.get_logger(__name__) |
| |
|
| | _INFO = DatasetInfo( |
| | description='Automatically generated for wikitext (wikitext-103-raw-v1), split into 8 shards, detokenized.\n\nOriginal Description:\n The WikiText language modeling dataset is a collection of over 100 million tokens extracted from the set of verified\n Good and Featured articles on Wikipedia. The dataset is available under the Creative Commons Attribution-ShareAlike\n License.\n', |
| | citation='@misc{merity2016pointer,\n title={Pointer Sentinel Mixture Models},\n author={Stephen Merity and Caiming Xiong and James Bradbury and Richard Socher},\n year={2016},\n eprint={1609.07843},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}\n', |
| | homepage='https://blog.einstein.ai/the-wikitext-long-term-dependency-language-modeling-dataset/', |
| | license='Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)', |
| | version="1.0.0", |
| | features=Features.from_dict({'text': {'dtype': 'string', 'id': None, '_type': 'Value'}}), |
| | supervised_keys=None) |
| |
|
| |
|
| | class AutoDataset(datasets.GeneratorBasedBuilder): |
| | BUILDER_CONFIGS = [datasets.BuilderConfig()] |
| |
|
| | def __init__(self, **kwargs): |
| | super().__init__(**kwargs) |
| |
|
| | def _info(self): |
| | return _INFO |
| |
|
| | @property |
| | def dataset_dir(self): |
| | return pathlib.Path(__file__).parent |
| |
|
| | def _split_generators(self, dl_manager): |
| | metadata = json.load(open(dl_manager.download("metadata.json"), 'rt')) |
| | return [ |
| | datasets.SplitGenerator( |
| | name=split, |
| | gen_kwargs={"filepaths": dl_manager.download(split_metadata["files"])}, |
| | ) |
| | for split, split_metadata in metadata["splits"].items() |
| | ] |
| |
|
| | def _generate_examples(self, filepaths): |
| | """This function returns the examples in the raw (text) form by iterating on all the files.""" |
| | id_: int = 0 |
| | for filepath in filepaths: |
| | logger.info(f"Generating examples from {filepath}") |
| | with fsspec.open(filepath, mode="rt", compression="infer", encoding="utf-8") as f: |
| | for line in f: |
| | if line: |
| | example = json.loads(line) |
| | yield id_, example |
| | id_ += 1 |
| |
|
| |
|
| | if __name__ == "__main__": |
| | AutoDataset().download_and_prepare() |
