






import inspect
import os
import unittest

import torch

import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment


class    _lowerCAmelCase			(		unittest.TestCase      ):



				"""simple docstring"""



				def 					__magic_name__							(      self    :    Dict):






											'''simple docstring'''







											snake_case__	  =       inspect.getfile(accelerate.test_utils)
											snake_case__	  =       os.path.sep.join(mod_file.split(os.path.sep)[:-1] + ["""scripts""", """test_script.py"""])
											snake_case__	  =       os.path.sep.join(
											    mod_file.split(os.path.sep)[:-1] + ["""scripts""", """test_distributed_data_loop.py"""])
											snake_case__	  =       os.path.sep.join(mod_file.split(os.path.sep)[:-1] + ["""scripts""", """test_ops.py"""])



				@require_multi_gpu
				def 					__magic_name__							(      self    :    List[str]):






											'''simple docstring'''







											print(F'''Found {torch.cuda.device_count()} devices.''')
											snake_case__	  =       ["""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())



				@require_multi_gpu
				def 					__magic_name__							(      self    :    int):






											'''simple docstring'''







											print(F'''Found {torch.cuda.device_count()} devices.''')
											snake_case__	  =       ["""torchrun""", F'''--nproc_per_node={torch.cuda.device_count()}''', self.operation_file_path]
											print(F'''Command: {cmd}''')
											with patch_environment(omp_num_threads=1):
																		execute_subprocess_async(UpperCamelCase__			,		env=os.environ.copy())



				@require_multi_gpu
				def 					__magic_name__							(      self    :    List[Any]):






											'''simple docstring'''







											snake_case__	  =       ["""torchrun""", F'''--nproc_per_node={torch.cuda.device_count()}''', inspect.getfile(self.__class__)]
											with patch_environment(omp_num_threads=1):
																		execute_subprocess_async(UpperCamelCase__			,		env=os.environ.copy())



				@require_multi_gpu
				def 					__magic_name__							(      self    :    Dict):






											'''simple docstring'''







											print(F'''Found {torch.cuda.device_count()} devices, using 2 devices only''')
											snake_case__	  =       ["""torchrun""", F'''--nproc_per_node={torch.cuda.device_count()}''', self.data_loop_file_path]
											with patch_environment(omp_num_threads=1			,		cuda_visible_devices="""0,1"""):
																		execute_subprocess_async(UpperCamelCase__			,		env=os.environ.copy())


if __name__ == "__main__":
	a__       =     Accelerator()
	a__       =     (accelerator.state.process_index + 2, 1_0)
	a__       =     torch.randint(0, 1_0, shape).to(accelerator.device)

	a__       =     """"""

	a__       =     accelerator.pad_across_processes(tensor)
	if tensora.shape[0] != accelerator.state.num_processes + 1:
		error_msg += F"Found shape {tensora.shape} but should have {accelerator.state.num_processes + 1} at dim 0."
	if not torch.equal(tensora[: accelerator.state.process_index + 2], tensor):
		error_msg += "Tensors have different values."
	if not torch.all(tensora[accelerator.state.process_index + 2 :] == 0):
		error_msg += "Padding was not done with the right value (0)."

	a__       =     accelerator.pad_across_processes(tensor, pad_first=True)
	if tensora.shape[0] != accelerator.state.num_processes + 1:
		error_msg += F"Found shape {tensora.shape} but should have {accelerator.state.num_processes + 1} at dim 0."
	a__       =     accelerator.state.num_processes - accelerator.state.process_index - 1
	if not torch.equal(tensora[index:], tensor):
		error_msg += "Tensors have different values."
	if not torch.all(tensora[:index] == 0):
		error_msg += "Padding was not done with the right value (0)."

	# Raise error at the end to make sure we don't stop at the first failure.
	if len(error_msg) > 0:
		raise ValueError(error_msg)








import random
from typing import Any

def _UpperCAmelCase   (	a						:	list ):
							for _ in range(len(a ) ):
														snake_case__	  =       random.randint(0  ,					len(a ) - 1 )
														snake_case__	  =       random.randint(0  ,					len(a ) - 1 )
														snake_case__  , snake_case__	  =       data[b], data[a]
							return data


if __name__ == "__main__":
	a__       =     [0, 1, 2, 3, 4, 5, 6, 7]
	a__       =     ["""python""", """says""", """hello""", """!"""]
	print("""Fisher-Yates Shuffle:""")
	print("""List""", integers, strings)
	print("""FY Shuffle""", fisher_yates_shuffle(integers), fisher_yates_shuffle(strings))
