


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


snake_case    :   Any	    =					4
snake_case    :   str	    =					3







class 		_snake_case  (				_snake_case							):
 pass







def     __lowerCamelCase						(			UpperCAmelCase_						:		List[str]						):




      """simple docstring"""





      for shard in shards:
            for i in range(UpperCAmelCase_						):
                  yield {"i": i, "shard": shard}
def     __lowerCamelCase						(			):




      """simple docstring"""





      a						:List[Any]										=	int(os.environ['''RANK''']						)
      a						:Optional[Any]										=	int(os.environ['''WORLD_SIZE''']						)

      a						:List[Any]										=	ArgumentParser()
      parser.add_argument('''--streaming'''			,  type=UpperCAmelCase_						)
      parser.add_argument('''--local_rank'''			,  type=UpperCAmelCase_						)
      parser.add_argument('''--num_workers'''			,  type=UpperCAmelCase_			,  default=0						)
      a						:Tuple										=	parser.parse_args()
      a						:Union[str, Any]										=	args.streaming
      a						:Optional[int]										=	args.num_workers

      a						:Dict										=	{'''shards''': [F'''shard_{shard_idx}''' for shard_idx in range(UpperCAmelCase_						)]}
      a						:Dict										=	IterableDataset.from_generator(UpperCAmelCase_			,  gen_kwargs=UpperCAmelCase_						)
      if not streaming:
            a						:Union[str, Any]										=	Dataset.from_list(list(UpperCAmelCase_						)						)

      a						:List[Any]										=	split_dataset_by_node(UpperCAmelCase_			,  rank=UpperCAmelCase_			,  world_size=UpperCAmelCase_						)
      a						:Optional[int]										=	torch.utils.data.DataLoader(UpperCAmelCase_			,  num_workers=UpperCAmelCase_						)

      a						:Tuple										=	NUM_SHARDS * NUM_ITEMS_PER_SHARD
      a						:Union[str, Any]										=	full_size // world_size
      expected_local_size += int(rank < (full_size % world_size)						)

      a						:str										=	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()









def     __lowerCamelCase						(			UpperCAmelCase_						:		int						):




      """simple docstring"""





      if not isinstance(UpperCAmelCase_			,  UpperCAmelCase_						):
            raise TypeError('''Input value must be an \'int\' type'''						)

      a						:Optional[int]										=	0
      while number:
            position += 1
            number >>= 1

      return position


if __name__ == "__main__":
     import doctest

     doctest.testmod()





