




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()










def 						__A						(      ) ->			list[list[int]]:
	return [list(range(1000 - i				,     -1000 - i				,     -1       )       ) for i in range(1000       )]


__UpperCamelCase   :			str          = generate_large_matrix()
__UpperCamelCase   :			Tuple          = (
    [[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
    [[3, 2], [1, 0]],
    [[7, 7, 6]],
    [[7, 7, 6], [-1, -2, -3]],
    grid,
)





def 						__A						(      __lowerCamelCase       ) ->			None:
	assert all(row == sorted(__lowerCamelCase				,     reverse=__lowerCamelCase       ) for row in grid       )
	assert all(list(__lowerCamelCase       ) == sorted(__lowerCamelCase				,     reverse=__lowerCamelCase       ) for col in zip(*__lowerCamelCase       )       )





def 						__A						(      __lowerCamelCase       ) ->			int:
	a									=				0
	a									=				len(__lowerCamelCase       ) - 1

	# Edge cases such as no values or all numbers are negative.
	if not array or array[0] < 0:
		return 0

	while right + 1 > left:
		a									=				(left + right) // 2
		a									=				array[mid]

		# Num must be negative and the index must be greater than or equal to 0.
		if num < 0 and array[mid - 1] >= 0:
			return mid

		if num >= 0:
			a									=				mid + 1
		else:
			a									=				mid - 1
    # No negative numbers so return the last index of the array + 1 which is the length.
	return len(__lowerCamelCase       )





def 						__A						(      __lowerCamelCase       ) ->			int:
	a									=				0
	a									=				len(grid[0]       )

	for i in range(len(__lowerCamelCase       )       ):
		a									=				find_negative_index(grid[i][:bound]       )
		total += bound
	return (len(__lowerCamelCase       ) * len(grid[0]       )) - total





def 						__A						(      __lowerCamelCase       ) ->			int:
	return len([number for row in grid for number in row if number < 0]       )





def 						__A						(      __lowerCamelCase       ) ->			int:
	a									=				0
	for row in grid:
		for i, number in enumerate(__lowerCamelCase       ):
			if number < 0:
				total += len(__lowerCamelCase       ) - i
				break
	return total





def 						__A						(      ) ->			None:
	from timeit import timeit

	print("""Running benchmarks"""       )
	a									=				(
	    """from __main__ import count_negatives_binary_search, """
	    """count_negatives_brute_force, count_negatives_brute_force_with_break, grid"""
	)
	for func in (
	    "count_negatives_binary_search",  # took 0.7727 seconds
	    "count_negatives_brute_force_with_break",  # took 4.6505 seconds
	    "count_negatives_brute_force",  # took 12.8160 seconds
	):
		a									=				timeit(f'{func}(grid=grid)'				,     setup=__lowerCamelCase				,     number=500       )
		print(f'{func}() took {time:0.4f} seconds'       )


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		benchmark()

