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import datasets |
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import os |
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import numpy as np |
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import itertools |
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SHARD_SIZE = 2500 |
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NUM_SHARDS = 40 |
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_DATA_FILES = [ |
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f'data_{i*SHARD_SIZE}_to_{(i+1)*SHARD_SIZE}.zip' for i in range(NUM_SHARDS) |
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] + [ 'val.zip' ] |
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_DESCRIPTION = """\ |
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TODO |
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""" |
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class CommaVQ(datasets.GeneratorBasedBuilder): |
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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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{"path": datasets.Value("string")} |
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) |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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dl_manager.download_config.ignore_url_params = True |
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to_dl = list(itertools.chain(*[x[1] for x in self.config.data_files.items()])) if self.config.data_files is not None else _DATA_FILES |
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downloaded_files = dl_manager.download(to_dl) |
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local_extracted_archive = dl_manager.extract(downloaded_files) if not dl_manager.is_streaming else [None]*len(downloaded_files) |
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return [ |
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datasets.SplitGenerator( |
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name=str(i), |
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gen_kwargs={"local_extracted_archive":local_extracted_archive[i], "files": dl_manager.iter_archive(downloaded_files[i])} |
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) for i in range(len(downloaded_files))] |
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def _generate_examples(self, local_extracted_archive, files): |
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for path_in_archive, f in files: |
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path = os.path.join(local_extracted_archive, path_in_archive) if local_extracted_archive is not None else path_in_archive |
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yield path_in_archive, {'path': path} |