

'''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 							A__    (       unittest.TestCase  ):





  def 						A  (		self      :	Tuple )	->    Union[str, Any]:





       '''simple docstring'''






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





  @require_multi_gpu
  def 						A  (		self      :	Optional[int] )	->    str:





       '''simple docstring'''






       print(f"Found {torch.cuda.device_count()} devices." )
       _SCREAMING_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(a_							,					env=os.environ.copy() )





  @require_multi_gpu
  def 						A  (		self      :	Dict )	->    List[str]:





       '''simple docstring'''






       print(f"Found {torch.cuda.device_count()} devices." )
       _SCREAMING_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(a_							,					env=os.environ.copy() )





  @require_multi_gpu
  def 						A  (		self      :	str )	->    Any:





       '''simple docstring'''






       _SCREAMING_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(a_							,					env=os.environ.copy() )





  @require_multi_gpu
  def 						A  (		self      :	List[str] )	->    int:





       '''simple docstring'''






       print(f"Found {torch.cuda.device_count()} devices, using 2 devices only" )
       _SCREAMING_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(a_							,					env=os.environ.copy() )


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

     lowerCamelCase :      Tuple					 =     ""

     lowerCamelCase :      List[str]					 =     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 :      Tuple					 =     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 :      Tuple					 =     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"""


from __future__ import annotations


def 					UpperCAmelCase__       (snake_case__							:					list[float]    ):
  """simple docstring"""

  _snake_case							:		int								=  0.00
  _snake_case							:		int								=  0
  for resistor in resistors:
    if resistor <= 0:
      _snake_case							:		Dict								=  F"Resistor at index {index} has a negative or zero value!"
      raise ValueError(snake_case__    )
    first_sum += 1 / float(snake_case__    )
    index += 1
  return 1 / first_sum


def 					UpperCAmelCase__       (snake_case__							:					list[float]    ):
  """simple docstring"""

  _snake_case							:		Union[str, Any]								=  0.00
  _snake_case							:		Any								=  0
  for resistor in resistors:
    sum_r += resistor
    if resistor < 0:
      _snake_case							:		Any								=  F"Resistor at index {index} has a negative value!"
      raise ValueError(snake_case__    )
    index += 1
  return sum_r


if __name__ == "__main__":
     import doctest

     doctest.testmod()


