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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 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} |