

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







   @require_multi_gpu
   def     __UpperCamelCase						( self			:      Optional[int]							):
     print(F'''Found {torch.cuda.device_count()} devices, using 2 devices only'''							)
     SCREAMING_SNAKE_CASE:int						      =					["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(SCREAMING_SNAKE_CASE__     ,env=os.environ.copy()							)


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

    A_       						=							""

    A_       						=							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)."

    A_       						=							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."
    A_       						=							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 ..utils import DummyObject, requires_backends





class 							_snake_case (       metaclass=_a						):
   _A       :     Any       =					['''torch''', '''torchsde''']
   def __init__( self			:      Any     ,*SCREAMING_SNAKE_CASE__			:      int     ,**SCREAMING_SNAKE_CASE__			:      Tuple							):
     requires_backends(self     ,["torch", "torchsde"]							)
   @classmethod
   def     __UpperCamelCase						( cls			:      Dict     ,*SCREAMING_SNAKE_CASE__			:      Dict     ,**SCREAMING_SNAKE_CASE__			:      Optional[Any]							):
     requires_backends(cls     ,["torch", "torchsde"]							)







   @classmethod
   def     __UpperCamelCase						( cls			:      List[str]     ,*SCREAMING_SNAKE_CASE__			:      int     ,**SCREAMING_SNAKE_CASE__			:      Optional[Any]							):
     requires_backends(cls     ,["torch", "torchsde"]							)






