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  __magic_name__  (		unittest.TestCase    ):





   """simple docstring"""




   def   lowerCAmelCase						(	self					:  Tuple							):



    """simple docstring"""



    _UpperCamelCase:     str							= inspect.getfile(accelerate.test_utils							)
    _UpperCamelCase:     Any							= os.path.sep.join(mod_file.split(os.path.sep							)[:-1] + ['''scripts''', '''test_script.py''']							)
    _UpperCamelCase:     int							= os.path.sep.join(
        mod_file.split(os.path.sep							)[:-1] + ['''scripts''', '''test_distributed_data_loop.py''']							)
    _UpperCamelCase:     Tuple							= os.path.sep.join(mod_file.split(os.path.sep							)[:-1] + ['''scripts''', '''test_ops.py''']							)



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



    """simple docstring"""



    print(f"""Found {torch.cuda.device_count()} devices."""							)
    _UpperCamelCase:     List[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()							)



   @require_multi_gpu
   def   lowerCAmelCase						(	self					:  Optional[Any]							):



    """simple docstring"""



    print(f"""Found {torch.cuda.device_count()} devices."""							)
    _UpperCamelCase:     Dict							= ['''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(_lowercase		,  env=os.environ.copy()							)



   @require_multi_gpu
   def   lowerCAmelCase						(	self					:  Optional[int]							):



    """simple docstring"""



    _UpperCamelCase:     Union[str, Any]							= ['''torchrun''', f"""--nproc_per_node={torch.cuda.device_count()}""", inspect.getfile(self.__class__							)]
    with patch_environment(omp_num_threads=1							):
     execute_subprocess_async(_lowercase		,  env=os.environ.copy()							)



   @require_multi_gpu
   def   lowerCAmelCase						(	self					:  Optional[Any]							):



    """simple docstring"""



    print(f"""Found {torch.cuda.device_count()} devices, using 2 devices only"""							)
    _UpperCamelCase:     List[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(_lowercase		,  env=os.environ.copy()							)


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

  UpperCAmelCase_			    =							''''''

  UpperCAmelCase_			    =							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)."

  UpperCAmelCase_			    =							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."
  UpperCAmelCase_			    =							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_     (		lowercase:							int = 600_851_475_143		)    ->				int:







 '''simple docstring'''

 try:
  _UpperCamelCase:     Optional[int]							= int(lowercase		)
 except (TypeError, ValueError):
  raise TypeError('''Parameter n must be int or castable to int.'''		)
 if n <= 0:
  raise ValueError('''Parameter n must be greater than or equal to one.'''		)
 _UpperCamelCase:     Dict							= 1
 _UpperCamelCase:     Tuple							= 2
 while i * i <= n:
  while n % i == 0:
   _UpperCamelCase:     List[Any]							= i
   n //= i
  i += 1
 if n > 1:
  _UpperCamelCase:     Any							= n
 return int(lowercase		)


if __name__ == "__main__":
  print(f"""{solution() = }""")