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