




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


UpperCAmelCase_		:					Any          =  4
UpperCAmelCase_		:					List[str]          =  3




class 		__A   (      UpperCamelCase__      ):
						pass




def 		lowerCAmelCase_ (						lowerCamelCase ):
				for shard in shards:
								for i in range(lowerCamelCase ):
												yield {"i": i, "shard": shard}




def 		lowerCAmelCase_ (						):
				__magic_name__						:						Tuple										=int(os.environ["""RANK"""] )
				__magic_name__						:						List[Any]										=int(os.environ["""WORLD_SIZE"""] )

				__magic_name__						:						Optional[Any]										=ArgumentParser()
				parser.add_argument("""--streaming"""						,  type=lowerCamelCase )
				parser.add_argument("""--local_rank"""						,  type=lowerCamelCase )
				parser.add_argument("""--num_workers"""						,  type=lowerCamelCase						,  default=0 )
				__magic_name__						:						List[str]										=parser.parse_args()
				__magic_name__						:						int										=args.streaming
				__magic_name__						:						Optional[int]										=args.num_workers

				__magic_name__						:						str										={"""shards""": [F"shard_{shard_idx}" for shard_idx in range(lowerCamelCase )]}
				__magic_name__						:						Optional[Any]										=IterableDataset.from_generator(lowerCamelCase						,  gen_kwargs=lowerCamelCase )
				if not streaming:
								__magic_name__						:						Dict										=Dataset.from_list(list(lowerCamelCase ) )

				__magic_name__						:						Tuple										=split_dataset_by_node(lowerCamelCase						,  rank=lowerCamelCase						,  world_size=lowerCamelCase )
				__magic_name__						:						List[Any]										=torch.utils.data.DataLoader(lowerCamelCase						,  num_workers=lowerCamelCase )

				__magic_name__						:						Dict										=NUM_SHARDS * NUM_ITEMS_PER_SHARD
				__magic_name__						:						Tuple										=full_size // world_size
				expected_local_size += int(rank < (full_size % world_size) )

				__magic_name__						:						Union[str, Any]										=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()










UpperCAmelCase_		:					Tuple          =  0  # The first color of the flag.
UpperCAmelCase_		:					Any          =  1  # The second color of the flag.
UpperCAmelCase_		:					str          =  2  # The third color of the flag.
UpperCAmelCase_		:					Tuple          =  (red, white, blue)




def 		lowerCAmelCase_ (						lowerCamelCase ):
				if not sequence:
								return []
				if len(lowerCamelCase ) == 1:
								return list(lowerCamelCase )
				__magic_name__						:						int										=0
				__magic_name__						:						str										=len(lowerCamelCase ) - 1
				__magic_name__						:						Optional[Any]										=0
				while mid <= high:
								if sequence[mid] == colors[0]:
												__magic_name__					,			__magic_name__						:						Tuple										=sequence[mid], sequence[low]
												low += 1
												mid += 1
								elif sequence[mid] == colors[1]:
												mid += 1
								elif sequence[mid] == colors[2]:
												__magic_name__					,			__magic_name__						:						Optional[Any]										=sequence[high], sequence[mid]
												high -= 1
								else:
												__magic_name__						:						Optional[int]										=F"The elements inside the sequence must contains only {colors} values"
												raise ValueError(lowerCamelCase )
				return sequence


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							UpperCAmelCase_		:					List[Any]          =  input("Enter numbers separated by commas:\n").strip()
							UpperCAmelCase_		:					Optional[int]          =  [int(item.strip()) for item in user_input.split(",")]
							print(F"""{dutch_national_flag_sort(unsorted)}""")




