



'''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     _UpperCAmelCase			(       unittest.TestCase     ):




     def 		snake_case_		(				self):
         A__		 =					inspect.getfile(accelerate.test_utils)
         A__		 =					os.path.sep.join(mod_file.split(os.path.sep)[:-1] + ['''scripts''', '''test_script.py'''])
         A__		 =					os.path.sep.join(
             mod_file.split(os.path.sep)[:-1] + ['''scripts''', '''test_distributed_data_loop.py'''])
         A__		 =					os.path.sep.join(mod_file.split(os.path.sep)[:-1] + ['''scripts''', '''test_ops.py'''])




     @require_multi_gpu
     def 		snake_case_		(				self):
         print(F"Found {torch.cuda.device_count()} devices.")
         A__		 =					['''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 		snake_case_		(				self):
         print(F"Found {torch.cuda.device_count()} devices.")
         A__		 =					['''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 		snake_case_		(				self):
         A__		 =					['''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 		snake_case_		(				self):
         print(F"Found {torch.cuda.device_count()} devices, using 2 devices only")
         A__		 =					['''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__":
   _lowercase						  =		Accelerator()
   _lowercase						  =		(accelerator.state.process_index + 2, 10)
   _lowercase						  =		torch.randint(0, 10, shape).to(accelerator.device)

   _lowercase						  =		""

   _lowercase						  =		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)."

   _lowercase						  =		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."
   _lowercase						  =		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)





def 		lowerCAmelCase__    (					UpperCamelCase_				:       Optional[int] ,       UpperCamelCase_				:       List[str] ,       UpperCamelCase_				:       List[Any] ,       UpperCamelCase_				:       str	)->  int:
    if height >= 1:
        move_tower(height - 1 ,       UpperCamelCase_ ,       UpperCamelCase_ ,       UpperCamelCase_	)
        move_disk(UpperCamelCase_ ,       UpperCamelCase_	)
        move_tower(height - 1 ,       UpperCamelCase_ ,       UpperCamelCase_ ,       UpperCamelCase_	)



def 		lowerCAmelCase__    (					UpperCamelCase_				:       Optional[int] ,       UpperCamelCase_				:       List[Any]	)->  str:
    print('''moving disk from''' ,       UpperCamelCase_ ,       '''to''' ,       UpperCamelCase_	)



def 		lowerCAmelCase__    (					)->  Tuple:
    A__		 =					int(input('''Height of hanoi: '''	).strip()	)
    move_tower(UpperCamelCase_ ,       '''A''' ,       '''B''' ,       '''C'''	)


if __name__ == "__main__":
   main()
