


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      __lowerCAmelCase  (			unittest.TestCase       ):






  """simple docstring"""





  def        lowerCAmelCase__	(  self							:							Tuple	) ->			Dict:




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



  @require_multi_gpu
  def        lowerCAmelCase__	(  self							:							Optional[int]	) ->			Any:




     """simple docstring"""
     print(F'''Found {torch.cuda.device_count()} devices.'''	)
     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(lowerCAmelCase_     ,					env=os.environ.copy()	)



  @require_multi_gpu
  def        lowerCAmelCase__	(  self							:							Any	) ->			Dict:




     """simple docstring"""
     print(F'''Found {torch.cuda.device_count()} devices.'''	)
     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(lowerCAmelCase_     ,					env=os.environ.copy()	)



  @require_multi_gpu
  def        lowerCAmelCase__	(  self							:							Tuple	) ->			str:




     """simple docstring"""
     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(lowerCAmelCase_     ,					env=os.environ.copy()	)



  @require_multi_gpu
  def        lowerCAmelCase__	(  self							:							Optional[Any]	) ->			List[Any]:




     """simple docstring"""
     print(F'''Found {torch.cuda.device_count()} devices, using 2 devices only'''	)
     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(lowerCAmelCase_     ,					env=os.environ.copy()	)


if __name__ == "__main__":
   SCREAMING_SNAKE_CASE						:str			=  Accelerator()
   SCREAMING_SNAKE_CASE						:str			=  (accelerator.state.process_index + 2, 10)
   SCREAMING_SNAKE_CASE						:Optional[Any]			=  torch.randint(0, 10, shape).to(accelerator.device)

   SCREAMING_SNAKE_CASE						:Dict			=  ''

   SCREAMING_SNAKE_CASE						:Optional[int]			=  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)."

   SCREAMING_SNAKE_CASE						:str			=  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."
   SCREAMING_SNAKE_CASE						:int			=  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'''


import os
import re
import shutil
import sys
import tempfile
import unittest

import black


_snake_case : str  				=						os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))

import check_copies  # noqa: E402


# This is the reference code that will be used in the tests.
# If DDPMSchedulerOutput is changed in scheduling_ddpm.py, this code needs to be manually updated.
_snake_case : List[str]  				=						'    \"""\n    Output class for the scheduler\'s step function output.\n\n    Args:\n        prev_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):\n            Computed sample (x_{t-1}) of previous timestep. `prev_sample` should be used as next model input in the\n            denoising loop.\n        pred_original_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):\n            The predicted denoised sample (x_{0}) based on the model output from the current timestep.\n            `pred_original_sample` can be used to preview progress or for guidance.\n    \"""\n\n    prev_sample: torch.FloatTensor\n    pred_original_sample: Optional[torch.FloatTensor] = None\n'

class      A       (						unittest.TestCase       ):







							def   __lowerCAmelCase     (    self			:    int   )     ->				List[Any]:


														"""simple docstring"""


														_a      	=							tempfile.mkdtemp()
														os.makedirs(os.path.join(self.diffusers_dir				,     '''schedulers/'''   )   )
														_a      	=							self.diffusers_dir
														shutil.copy(
														    os.path.join(lowerCAmelCase_				,     '''src/diffusers/schedulers/scheduling_ddpm.py'''   )				,     os.path.join(self.diffusers_dir				,     '''schedulers/scheduling_ddpm.py'''   )				,     )







							def   __lowerCAmelCase     (    self			:    Dict   )     ->				int:


														"""simple docstring"""


														_a      	=							'''src/diffusers'''
														shutil.rmtree(self.diffusers_dir   )







							def   __lowerCAmelCase     (    self			:    int				,     lowerCAmelCase_			:    str				,     lowerCAmelCase_			:    List[Any]				,     lowerCAmelCase_			:    Union[str, Any]				,     lowerCAmelCase_			:    str=None   )     ->				Union[str, Any]:


														"""simple docstring"""


														_a      	=							comment + F'\nclass {class_name}(nn.Module):\n' + class_code
														if overwrite_result is not None:
																					_a      	=							comment + F'\nclass {class_name}(nn.Module):\n' + overwrite_result
														_a      	=							black.Mode(target_versions={black.TargetVersion.PYaa}				,     line_length=1_19   )
														_a      	=							black.format_str(lowerCAmelCase_				,     mode=lowerCAmelCase_   )
														_a      	=							os.path.join(self.diffusers_dir				,     '''new_code.py'''   )
														with open(lowerCAmelCase_				,     '''w'''				,     newline='''\n'''   ) as f:
																					f.write(lowerCAmelCase_   )
														if overwrite_result is None:
																					self.assertTrue(len(check_copies.is_copy_consistent(lowerCAmelCase_   )   ) == 0   )
														else:
																					check_copies.is_copy_consistent(f.name				,     overwrite=lowerCAmelCase_   )
																					with open(lowerCAmelCase_				,     '''r'''   ) as f:
																												self.assertTrue(f.read()				,     lowerCAmelCase_   )







							def   __lowerCAmelCase     (    self			:    Optional[Any]   )     ->				Union[str, Any]:


														"""simple docstring"""


														_a      	=							check_copies.find_code_in_diffusers('''schedulers.scheduling_ddpm.DDPMSchedulerOutput'''   )
														self.assertEqual(lowerCAmelCase_				,     lowerCAmelCase_   )







							def   __lowerCAmelCase     (    self			:    Dict   )     ->				Union[str, Any]:


														"""simple docstring"""


														self.check_copy_consistency(
														    '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput'''				,     '''DDPMSchedulerOutput'''				,     REFERENCE_CODE + '''\n'''				,     )

														# With no empty line at the end
														self.check_copy_consistency(
														    '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput'''				,     '''DDPMSchedulerOutput'''				,     lowerCAmelCase_				,     )

														# Copy consistency with rename
														self.check_copy_consistency(
														    '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test'''				,     '''TestSchedulerOutput'''				,     re.sub('''DDPM'''				,     '''Test'''				,     lowerCAmelCase_   )				,     )

														# Copy consistency with a really long name
														_a      	=							'''TestClassWithAReallyLongNameBecauseSomePeopleLikeThatForSomeReason'''
														self.check_copy_consistency(
														    F'# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->{long_class_name}'				,     F'{long_class_name}SchedulerOutput'				,     re.sub('''Bert'''				,     lowerCAmelCase_				,     lowerCAmelCase_   )				,     )

														# Copy consistency with overwrite
														self.check_copy_consistency(
														    '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test'''				,     '''TestSchedulerOutput'''				,     lowerCAmelCase_				,     overwrite_result=re.sub('''DDPM'''				,     '''Test'''				,     lowerCAmelCase_   )				,     )

