





'''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


__UpperCamelCase					    =	4
__UpperCamelCase					    =	3




class  _A (					__lowercase		):
		pass







def 					_a						(       _lowerCamelCase ) ->				List[Any]:



			"""simple docstring"""


			for shard in shards:
						for i in range(_lowerCamelCase ):
									yield {"i": i, "shard": shard}







def 					_a						(       ) ->				str:



			"""simple docstring"""


			__snake_case					:      List[str]							      =     int(os.environ["""RANK"""] )
			__snake_case					:      str							      =     int(os.environ["""WORLD_SIZE"""] )

			__snake_case					:      Optional[int]							      =     ArgumentParser()
			parser.add_argument("""--streaming"""    ,	type=_lowerCamelCase )
			parser.add_argument("""--local_rank"""    ,	type=_lowerCamelCase )
			parser.add_argument("""--num_workers"""    ,	type=_lowerCamelCase    ,	default=0 )
			__snake_case					:      Any							      =     parser.parse_args()
			__snake_case					:      Any							      =     args.streaming
			__snake_case					:      Dict							      =     args.num_workers

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

			__snake_case					:      str							      =     split_dataset_by_node(_lowerCamelCase    ,	rank=_lowerCamelCase    ,	world_size=_lowerCamelCase )
			__snake_case					:      Union[str, Any]							      =     torch.utils.data.DataLoader(_lowerCamelCase    ,	num_workers=_lowerCamelCase )

			__snake_case					:      List[Any]							      =     NUM_SHARDS * NUM_ITEMS_PER_SHARD
			__snake_case					:      Any							      =     full_size // world_size
			expected_local_size += int(rank < (full_size % world_size) )

			__snake_case					:      Tuple							      =     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 __future__ import annotations

import math







def 					_a						(       _lowerCamelCase    ,	_lowerCamelCase    ,	_lowerCamelCase    ,	_lowerCamelCase    ,	_lowerCamelCase ) ->				int:



			"""simple docstring"""


			if depth < 0:
						raise ValueError("""Depth cannot be less than 0""" )

			if not scores:
						raise ValueError("""Scores cannot be empty""" )

			if depth == height:
						return scores[node_index]

			return (
			    max(
			        minimax(depth + 1    ,	node_index * 2    ,	_lowerCamelCase    ,	_lowerCamelCase    ,	_lowerCamelCase )    ,	minimax(depth + 1    ,	node_index * 2 + 1    ,	_lowerCamelCase    ,	_lowerCamelCase    ,	_lowerCamelCase )    ,	)
			    if is_max
			    else min(
			        minimax(depth + 1    ,	node_index * 2    ,	_lowerCamelCase    ,	_lowerCamelCase    ,	_lowerCamelCase )    ,	minimax(depth + 1    ,	node_index * 2 + 1    ,	_lowerCamelCase    ,	_lowerCamelCase    ,	_lowerCamelCase )    ,	)
			)







def 					_a						(       ) ->				None:



			"""simple docstring"""


			__snake_case					:      Union[str, Any]							      =     [90, 23, 6, 33, 21, 65, 123, 3_4423]
			__snake_case					:      Optional[int]							      =     math.log(len(_lowerCamelCase )    ,	2 )
			print(F'''Optimal value : {minimax(0    ,	0    ,	_lowerCamelCase    ,	_lowerCamelCase    ,	_lowerCamelCase )}''' )


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	main()


