






'''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    ):






 """simple docstring"""





 def 	_UpperCAmelCase							(				self			):
       UpperCamelCase_					: int            =				inspect.getfile(accelerate.test_utils			)
       UpperCamelCase_					: Union[str, Any]            =				os.path.sep.join(mod_file.split(os.path.sep			)[:-1] + ["""scripts""", """test_script.py"""]			)
       UpperCamelCase_					: Optional[Any]            =				os.path.sep.join(
           mod_file.split(os.path.sep			)[:-1] + ["""scripts""", """test_distributed_data_loop.py"""]			)
       UpperCamelCase_					: List[Any]            =				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(__lowerCAmelCase      ,  env=os.environ.copy()			)
 @require_multi_gpu
 def 	_UpperCAmelCase							(				self			):
       print(F"Found {torch.cuda.device_count()} devices."			)
       UpperCamelCase_					: int            =				["""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(__lowerCAmelCase      ,  env=os.environ.copy()			)
 @require_multi_gpu
 def 	_UpperCAmelCase							(				self			):
       UpperCamelCase_					: Any            =				["""torchrun""", F"--nproc_per_node={torch.cuda.device_count()}", inspect.getfile(self.__class__			)]
       with patch_environment(omp_num_threads=1			):
             execute_subprocess_async(__lowerCAmelCase      ,  env=os.environ.copy()			)





 @require_multi_gpu
 def 	_UpperCAmelCase							(				self			):
       print(F"Found {torch.cuda.device_count()} devices, using 2 devices only"			)
       UpperCamelCase_					: List[Any]            =				["""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(__lowerCAmelCase      ,  env=os.environ.copy()			)


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














'''simple docstring'''

from abc import ABC, abstractmethod
from argparse import ArgumentParser




class      A     (   SCREAMING_SNAKE_CASE__    ):






 """simple docstring"""





 @staticmethod
 @abstractmethod
 def 	_UpperCAmelCase							(				__lowerCAmelCase			):
       raise NotImplementedError()





 @abstractmethod
 def 	_UpperCAmelCase							(				self			):
       raise NotImplementedError()






