

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    ):


 def _UpperCamelCase	(						self		: int    )    ->      int:
   UpperCAmelCase					      =  inspect.getfile(accelerate.test_utils    )
   UpperCAmelCase					      =  os.path.sep.join(mod_file.split(os.path.sep    )[:-1] + ["scripts", "test_script.py"]    )
   UpperCAmelCase					      =  os.path.sep.join(
       mod_file.split(os.path.sep    )[:-1] + ["scripts", "test_distributed_data_loop.py"]    )
   UpperCAmelCase					      =  os.path.sep.join(mod_file.split(os.path.sep    )[:-1] + ["scripts", "test_ops.py"]    )


 @require_multi_gpu
 def _UpperCamelCase	(						self		: str    )    ->      List[Any]:
   print(f"Found {torch.cuda.device_count()} devices."    )
   UpperCAmelCase					      =  ['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		: Tuple    )    ->      List[Any]:
   print(f"Found {torch.cuda.device_count()} devices."    )
   UpperCAmelCase					      =  ['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		: Dict    )    ->      str:
   UpperCAmelCase					      =  ['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		: Optional[Any]    )    ->      Tuple:
   print(f"Found {torch.cuda.device_count()} devices, using 2 devices only"    )
   UpperCAmelCase					      =  ['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)






def      _lowerCAmelCase(	__A			):
  assert column_title.isupper()
  UpperCAmelCase					      =  0
  UpperCAmelCase					      =  len(__A			) - 1
  UpperCAmelCase					      =  0

  while index >= 0:
    UpperCAmelCase					      =  (ord(column_title[index]			) - 64) * pow(26   ,       __A			)
    answer += value
    power += 1
    index -= 1

  return answer


if __name__ == "__main__":
      from doctest import testmod

      testmod()



