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 | |
downloaded_files = dl_manager.download(_DATA_FILES) | |
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} |