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import json |
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import pathlib |
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import datasets |
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import fsspec |
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from datasets import DatasetInfo, Value, Features |
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logger = datasets.logging.get_logger(__name__) |
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_INFO = DatasetInfo( |
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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', |
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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', |
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homepage='https://blog.einstein.ai/the-wikitext-long-term-dependency-language-modeling-dataset/', |
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license='Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)', |
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version="1.0.0", |
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features=Features.from_dict({'text': {'dtype': 'string', 'id': None, '_type': 'Value'}}), |
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supervised_keys=None) |
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class AutoDataset(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = [datasets.BuilderConfig()] |
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def __init__(self, **kwargs): |
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super().__init__(**kwargs) |
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def _info(self): |
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return _INFO |
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@property |
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def dataset_dir(self): |
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return pathlib.Path(__file__).parent |
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def _split_generators(self, dl_manager): |
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metadata = json.load(open(dl_manager.download("metadata.json"), 'rt')) |
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return [ |
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datasets.SplitGenerator( |
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name=split, |
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gen_kwargs={"filepaths": dl_manager.download(split_metadata["files"])}, |
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) |
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for split, split_metadata in metadata["splits"].items() |
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] |
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def _generate_examples(self, filepaths): |
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"""This function returns the examples in the raw (text) form by iterating on all the files.""" |
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id_: int = 0 |
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for filepath in filepaths: |
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logger.info(f"Generating examples from {filepath}") |
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with fsspec.open(filepath, mode="rt", compression="infer", encoding="utf-8") as f: |
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for line in f: |
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if line: |
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example = json.loads(line) |
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yield id_, example |
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id_ += 1 |
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if __name__ == "__main__": |
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AutoDataset().download_and_prepare() |
