

'''simple docstring'''
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 					_snake_case		(unittest.TestCase):






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      str						=  inspect.getfile(accelerate.test_utils     )
				UpperCAmelCase_     :      str						=  os.path.sep.join(mod_file.split(os.path.sep     )[:-1] + ["scripts", "test_script.py"]     )
				UpperCAmelCase_     :      Union[str, Any]						=  os.path.sep.join(
				    mod_file.split(os.path.sep     )[:-1] + ["scripts", "test_distributed_data_loop.py"]     )
				UpperCAmelCase_     :      str						=  os.path.sep.join(mod_file.split(os.path.sep     )[:-1] + ["scripts", "test_ops.py"]     )






			@require_multi_gpu
			def 		UpperCamelCase__							(  self     ):
				print(f'''Found {torch.cuda.device_count()} devices.'''     )
				UpperCAmelCase_     :      Optional[int]						=  ["torchrun", f'''--nproc_per_node={torch.cuda.device_count()}''', self.test_file_path]
				with patch_environment(omp_num_threads=1     ):
					execute_subprocess_async(__a			,env=os.environ.copy()     )






			@require_multi_gpu
			def 		UpperCamelCase__							(  self     ):
				print(f'''Found {torch.cuda.device_count()} devices.'''     )
				UpperCAmelCase_     :      Union[str, Any]						=  ["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(__a			,env=os.environ.copy()     )






			@require_multi_gpu
			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      Tuple						=  ["torchrun", f'''--nproc_per_node={torch.cuda.device_count()}''', inspect.getfile(self.__class__     )]
				with patch_environment(omp_num_threads=1     ):
					execute_subprocess_async(__a			,env=os.environ.copy()     )






			@require_multi_gpu
			def 		UpperCamelCase__							(  self     ):
				print(f'''Found {torch.cuda.device_count()} devices, using 2 devices only'''     )
				UpperCAmelCase_     :      str						=  ["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(__a			,env=os.environ.copy()     )


if __name__ == "__main__":
					_lowerCamelCase      					=     Accelerator()
					_lowerCamelCase      					=     (accelerator.state.process_index + 2, 10)
					_lowerCamelCase      					=     torch.randint(0, 10, shape).to(accelerator.device)

					_lowerCamelCase      					=     ""

					_lowerCamelCase      					=     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)."

					_lowerCamelCase      					=     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."
					_lowerCamelCase      					=     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)





'''simple docstring'''


def    lowerCAmelCase       (		UpperCamelCase__					: list							):


	"""simple docstring"""
	__UpperCAmelCase      					=      False
	while is_sorted is False:  # Until all the indices are traversed keep looping
		__UpperCAmelCase      					=      True
		for i in range(0     ,       len(UpperCamelCase__							) - 1     ,       2							):  # iterating over all even indices
			if input_list[i] > input_list[i + 1]:
				__UpperCAmelCase					,      __UpperCAmelCase      					=      input_list[i + 1], input_list[i]
				# swapping if elements not in order
				__UpperCAmelCase      					=      False

		for i in range(1     ,       len(UpperCamelCase__							) - 1     ,       2							):  # iterating over all odd indices
			if input_list[i] > input_list[i + 1]:
				__UpperCAmelCase					,      __UpperCAmelCase      					=      input_list[i + 1], input_list[i]
				# swapping if elements not in order
				__UpperCAmelCase      					=      False
	return input_list


if __name__ == "__main__":
					print("Enter list to be sorted")
					__lowerCAmelCase						:							List[str]    							=						[int(x) for x in input().split()]
					# inputing elements of the list in one line
					__lowerCAmelCase						:							Dict    							=						odd_even_sort(input_list)
					print("The sorted list is")
					print(sorted_list)
