



'''simple docstring'''
import random



class _A	:





		def __init__(  self			,							__UpperCAmelCase			,							__UpperCAmelCase					)							->  None:

					'''simple docstring'''
					__UpperCAmelCase :   Tuple    					=  x
					__UpperCAmelCase :   Dict    					=  y





		def 				__A							(  self					)							->  bool:

					'''simple docstring'''
					return (self.x**2 + self.y**2) <= 1





		@classmethod
		def 				__A							(  cls					)							->  int:

					'''simple docstring'''
					return cls(x=random.random()			,							y=random.random()					)


def 	lowercase_						( lowerCAmelCase__						:	int			):

			"""simple docstring"""





			if number_of_simulations < 1:
						raise ValueError("""At least one simulation is necessary to estimate PI."""			)

			__UpperCAmelCase :   List[str]    					=  0
			for _ in range(lowerCAmelCase__			):
						__UpperCAmelCase :   List[Any]    					=  Point.random_unit_square()

						if random_point.is_in_unit_circle():
									number_in_unit_circle += 1

			return 4 * number_in_unit_circle / number_of_simulations


if __name__ == "__main__":
					# import doctest

					# doctest.testmod()
					from math import pi

					_UpperCamelCase									=      '''Please enter the desired number of Monte Carlo simulations: '''
					_UpperCamelCase									=      estimate_pi(int(input(prompt).strip()))
					print(F'An estimate of PI is {my_pi} with an error of {abs(my_pi - pi)}')









'''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_multi_gpu,
    require_single_gpu,
    test_sync,
)
from accelerate.utils import patch_environment



class _A	(     unittest.TestCase     ):





		def 				__A							(  self					)							->  Optional[Any]:

					'''simple docstring'''
					__UpperCAmelCase :   int    					=  inspect.getfile(accelerate.test_utils					)
					__UpperCAmelCase :   int    					=  os.path.sep.join(mod_file.split(os.path.sep					)[:-1] + ["""scripts""", """test_sync.py"""]					)





		@require_cpu
		def 				__A							(  self					)							->  Optional[Any]:

					'''simple docstring'''
					debug_launcher(test_sync.main			,							num_processes=1					)





		@require_cpu
		def 				__A							(  self					)							->  Optional[Any]:

					'''simple docstring'''
					debug_launcher(test_sync.main					)





		@require_single_gpu
		def 				__A							(  self					)							->  Tuple:

					'''simple docstring'''
					test_sync.main()





		@require_multi_gpu
		def 				__A							(  self					)							->  List[Any]:

					'''simple docstring'''
					print(f'Found {torch.cuda.device_count()} devices.'					)
					__UpperCAmelCase :   List[str]    					=  ["""torchrun""", f'--nproc_per_node={torch.cuda.device_count()}', self.test_file_path]
					with patch_environment(omp_num_threads=1					):
								execute_subprocess_async(__UpperCAmelCase			,							env=os.environ.copy()					)




