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import datasets |
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import zipfile |
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import urllib.request |
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import os |
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logger = datasets.logging.get_logger(__name__) |
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_DESCRIPTION = """\ |
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A colossal, cleaned version of Common Crawl's web crawl corpus. |
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Based on Common Crawl dataset: "https://commoncrawl.org". |
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This is the processed version of Google's mC4 dataset by AllenAI. |
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""" |
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_CITATION = """ |
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@article{2019t5, |
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author = {Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu}, |
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title = {Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer}, |
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journal = {arXiv e-prints}, |
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year = {2019}, |
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archivePrefix = {arXiv}, |
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eprint = {1910.10683}, |
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} |
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""" |
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_URL = "https://linghub.ru/static/Taiga/news.zip" |
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_DATA_URL = "https://linghub.ru/static/Taiga/news.zip" |
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class TaigaConfig(datasets.BuilderConfig): |
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"""BuilderConfig for mC4.""" |
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def __init__(self, *args, **kwargs): |
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"""BuilderConfig for mC4. |
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Args: |
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languages (:obj:`List[str]`): list of languages to load |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super().__init__( |
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*args, |
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name="taiga", |
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**kwargs, |
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) |
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class Taiga(datasets.GeneratorBasedBuilder): |
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"""mC4, a colossal, cleaned version of Common Crawl's web crawl corpus.""" |
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BUILDER_CONFIGS = [TaigaConfig()] |
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BUILDER_CONFIG_CLASS = TaigaConfig |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"text": datasets.Value("string"), |
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} |
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), |
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) |
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def _split_generators(self, dl_manager): |
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downloaded_file = dl_manager.download(['proza_ru2.zip', 'stihi_ru.zip', 'proza_ru1.zip']) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_file}), |
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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_ = 0 |
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for filepath in filepaths: |
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logger.info("generating examples from = %s", filepath) |
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with zipfile.ZipFile(filepath) as z: |
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for filename in z.namelist(): |
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if not os.path.isdir(filename) and '.txt' in filename.split('/') and len(filename.split('/')) > 2: |
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with z.open(filename) as f: |
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txt = f.read().decode('utf-8') |
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yield id_, {'text': txt} |
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id_ += 1 |
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