




"""simple docstring"""




import os
from argparse import ArgumentParser
from typing import List

import torch.utils.data

from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node


lowerCAmelCase							:			Union[str, Any]     							=							4
lowerCAmelCase							:			List[Any]     							=							3






class     __magic_name__							(       _A				):






				'''simple docstring'''
				pass




def     a__ (				snake_case__				)						->					Union[str, Any]:
			for shard in shards:
						for i in range(__snake_case				):
									yield {"i": i, "shard": shard}



def     a__ (				)						->					List[Any]:
			lowerCamelCase			      =					int(os.environ["""RANK"""]				)
			lowerCamelCase			      =					int(os.environ["""WORLD_SIZE"""]				)

			lowerCamelCase			      =					ArgumentParser()
			parser.add_argument("""--streaming"""       , type=__snake_case				)
			parser.add_argument("""--local_rank"""       , type=__snake_case				)
			parser.add_argument("""--num_workers"""       , type=__snake_case       , default=0				)
			lowerCamelCase			      =					parser.parse_args()
			lowerCamelCase			      =					args.streaming
			lowerCamelCase			      =					args.num_workers

			lowerCamelCase			      =					{'''shards''': [F'shard_{shard_idx}' for shard_idx in range(__snake_case				)]}
			lowerCamelCase			      =					IterableDataset.from_generator(__snake_case       , gen_kwargs=__snake_case				)
			if not streaming:
						lowerCamelCase			      =					Dataset.from_list(list(__snake_case				)				)

			lowerCamelCase			      =					split_dataset_by_node(__snake_case       , rank=__snake_case       , world_size=__snake_case				)
			lowerCamelCase			      =					torch.utils.data.DataLoader(__snake_case       , num_workers=__snake_case				)

			lowerCamelCase			      =					NUM_SHARDS * NUM_ITEMS_PER_SHARD
			lowerCamelCase			      =					full_size // world_size
			expected_local_size += int(rank < (full_size % world_size)				)

			lowerCamelCase			      =					sum(1 for _ in dataloader				)
			if local_size != expected_local_size:
						raise FailedTestError(F'local_size {local_size} != expected_local_size {expected_local_size}'				)


if __name__ == "__main__":
					main()











"""simple docstring"""



from typing import Optional
from urllib.parse import quote

import huggingface_hub as hfh
from packaging import version



def 						lowercase    (				__snake_case				: str		,					__snake_case				: str		,					__snake_case				: Optional[str] = None	):
		if version.parse(hfh.__version__	).release < version.parse('''0.11.0'''	).release:
				# old versions of hfh don't url-encode the file path
				lowercase_ : Union[str, Any]							       =   quote(__snake_case	)
		return hfh.hf_hub_url(__snake_case		,					__snake_case		,					repo_type='''dataset'''		,					revision=__snake_case	)



