





"""simple docstring"""





from __future__ import annotations

from itertools import permutations
from random import randint
from timeit import repeat



def 					lowerCAmelCase_      (   ):


							'''simple docstring'''







							__lowerCamelCase   :   str       =[randint(-1000     ,    1000 ) for i in range(10 )]
							__lowerCamelCase   :   List[str]       =randint(-5000     ,    5000 )
							return (arr, r)


_UpperCamelCase					      =   make_dataset()



def 					lowerCAmelCase_      (   SCREAMING_SNAKE_CASE							:				list[int]     ,    SCREAMING_SNAKE_CASE							:				int ):


							'''simple docstring'''







							for triplet in permutations(SCREAMING_SNAKE_CASE     ,    3 ):
														if sum(SCREAMING_SNAKE_CASE ) == target:
																					return tuple(sorted(SCREAMING_SNAKE_CASE ) )
							return (0, 0, 0)



def 					lowerCAmelCase_      (   SCREAMING_SNAKE_CASE							:				list[int]     ,    SCREAMING_SNAKE_CASE							:				int ):


							'''simple docstring'''







							arr.sort()
							__lowerCamelCase   :   str       =len(SCREAMING_SNAKE_CASE )
							for i in range(n - 1 ):
														__lowerCamelCase     ,    __lowerCamelCase   :   Optional[Any]       =i + 1, n - 1
														while left < right:
																					if arr[i] + arr[left] + arr[right] == target:
																												return (arr[i], arr[left], arr[right])
																					elif arr[i] + arr[left] + arr[right] < target:
																												left += 1
																					elif arr[i] + arr[left] + arr[right] > target:
																												right -= 1
							return (0, 0, 0)



def 					lowerCAmelCase_      (   ):


							'''simple docstring'''







							__lowerCamelCase   :   Optional[int]       ='''
from __main__ import dataset, triplet_sum1, triplet_sum2
'''
							__lowerCamelCase   :   Dict       ='''
triplet_sum1(*dataset)
'''
							__lowerCamelCase   :   Optional[Any]       ='''
triplet_sum2(*dataset)
'''
							__lowerCamelCase   :   Optional[Any]       =repeat(setup=SCREAMING_SNAKE_CASE     ,    stmt=SCREAMING_SNAKE_CASE     ,    repeat=5     ,    number=10000 )
							__lowerCamelCase   :   str       =repeat(setup=SCREAMING_SNAKE_CASE     ,    stmt=SCREAMING_SNAKE_CASE     ,    repeat=5     ,    number=10000 )
							return (min(SCREAMING_SNAKE_CASE ), min(SCREAMING_SNAKE_CASE ))


if __name__ == "__main__":
							from doctest import testmod

							testmod()
							_UpperCamelCase					      =   solution_times()
							print(f'''The time for naive implementation is {times[0]}.''')
							print(f'''The time for optimized implementation is {times[1]}.''')











"""simple docstring"""





import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_huggingface_suite,
    require_multi_gpu,
    require_single_gpu,
)
from accelerate.utils import patch_environment
@require_huggingface_suite
class 		SCREAMING_SNAKE_CASE_				(     unittest.TestCase ):
				"""simple docstring"""




				def        __lowercase	(  self	:Dict      ):
											__lowerCamelCase   :   Union[str, Any]       =inspect.getfile(accelerate.test_utils      )
											__lowerCamelCase   :   Union[str, Any]       =os.path.sep.join(
											    mod_file.split(os.path.sep      )[:-1] + ['''scripts''', '''external_deps''', '''test_metrics.py''']      )

											from accelerate.test_utils.scripts.external_deps import test_metrics  # noqa: F401

											__lowerCamelCase   :   List[str]       =test_metrics




				@require_cpu
				def        __lowercase	(  self	:Optional[Any]      ):
											debug_launcher(self.test_metrics.main    ,     num_processes=1      )




				@require_cpu
				def        __lowercase	(  self	:int      ):
											debug_launcher(self.test_metrics.main      )




				@require_single_gpu
				def        __lowercase	(  self	:int      ):
											self.test_metrics.main()




				@require_multi_gpu
				def        __lowercase	(  self	:Dict      ):
											print(f'Found {torch.cuda.device_count()} devices.'      )
											__lowerCamelCase   :   Union[str, Any]       =['''torchrun''', f'--nproc_per_node={torch.cuda.device_count()}', self.test_file_path]
											with patch_environment(omp_num_threads=1      ):
																		execute_subprocess_async(__lowercase    ,     env=os.environ.copy()      )




