

'''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			:					str	)						->     Tuple:
      UpperCAmelCase	:     Any						 =			inspect.getfile(accelerate.test_utils	)
      UpperCAmelCase	:     Dict						 =			os.path.sep.join(mod_file.split(os.path.sep	)[:-1] + ['scripts', 'test_script.py']	)
      UpperCAmelCase	:     Dict						 =			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			:					Optional[Any]	)						->     Optional[int]:
      print(f"""Found {torch.cuda.device_count()} devices."""	)
      UpperCAmelCase	:     Dict						 =			['torchrun', f"""--nproc_per_node={torch.cuda.device_count()}""", self.test_file_path]
      with patch_environment(omp_num_threads=1	):
       execute_subprocess_async(lowercase_					,      env=os.environ.copy()	)


     @require_multi_gpu
     def        UpperCAmelCase_	(		self			:					Union[str, Any]	)						->     List[Any]:
      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(lowercase_					,      env=os.environ.copy()	)


     @require_multi_gpu
     def        UpperCAmelCase_	(		self			:					str	)						->     List[Any]:
      UpperCAmelCase	:     Optional[int]						 =			['torchrun', f"""--nproc_per_node={torch.cuda.device_count()}""", inspect.getfile(self.__class__	)]
      with patch_environment(omp_num_threads=1	):
       execute_subprocess_async(lowercase_					,      env=os.environ.copy()	)




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


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

 lowercase__         =      ""

 lowercase__         =      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)."

 lowercase__         =      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."
 lowercase__         =      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'''

# Lint as: python3
import itertools
import os
import re


lowercase__         =      re.compile(r"([A-Z]+)([A-Z][a-z])")
lowercase__         =      re.compile(r"([a-z\d])([A-Z])")

lowercase__         =      re.compile(r"(?<!_)_(?!_)")
lowercase__         =      re.compile(r"(_{2,})")

lowercase__         =      r"^\w+(\.\w+)*$"

lowercase__         =      r"<>:/\|?*"




def 				UpperCamelCase(					UpperCAmelCase_     ):
 UpperCAmelCase	:     List[str]						 =			_uppercase_uppercase_re.sub(R'\1_\2'  ,	UpperCAmelCase_     )
 UpperCAmelCase	:     str						 =			_lowercase_uppercase_re.sub(R'\1_\2'  ,	UpperCAmelCase_     )
 return name.lower()




def 				UpperCamelCase(					UpperCAmelCase_     ):
 UpperCAmelCase	:     List[str]						 =			_single_underscore_re.split(UpperCAmelCase_     )
 UpperCAmelCase	:     Optional[Any]						 =			[_multiple_underscores_re.split(UpperCAmelCase_     ) for n in name]
 return "".join(n.capitalize() for n in itertools.chain.from_iterable(UpperCAmelCase_     ) if n != ''     )




def 				UpperCamelCase(					UpperCAmelCase_     ):
 if os.path.basename(UpperCAmelCase_     ) != name:
  raise ValueError(F"""Should be a dataset name, not a path: {name}"""     )
 return camelcase_to_snakecase(UpperCAmelCase_     )




def 				UpperCamelCase(					UpperCAmelCase_  ,	UpperCAmelCase_     ):
 if os.path.basename(UpperCAmelCase_     ) != name:
  raise ValueError(F"""Should be a dataset name, not a path: {name}"""     )
 if not re.match(_split_re  ,	UpperCAmelCase_     ):
  raise ValueError(F"""Split name should match '{_split_re}'' but got '{split}'."""     )
 return F"""{filename_prefix_for_name(UpperCAmelCase_     )}-{split}"""




def 				UpperCamelCase(					UpperCAmelCase_  ,	UpperCAmelCase_  ,	UpperCAmelCase_  ,	UpperCAmelCase_=None     ):
 UpperCAmelCase	:     Dict						 =			filename_prefix_for_split(UpperCAmelCase_  ,	UpperCAmelCase_     )
 if filetype_suffix:
  prefix += F""".{filetype_suffix}"""
 UpperCAmelCase	:     Optional[int]						 =			os.path.join(UpperCAmelCase_  ,	UpperCAmelCase_     )
 return F"""{filepath}*"""




def 				UpperCamelCase(					UpperCAmelCase_  ,	UpperCAmelCase_  ,	UpperCAmelCase_  ,	UpperCAmelCase_=None  ,	UpperCAmelCase_=None     ):
 UpperCAmelCase	:     Optional[int]						 =			filename_prefix_for_split(UpperCAmelCase_  ,	UpperCAmelCase_     )
 UpperCAmelCase	:     str						 =			os.path.join(UpperCAmelCase_  ,	UpperCAmelCase_     )

 if shard_lengths:
  UpperCAmelCase	:     List[str]						 =			len(UpperCAmelCase_     )
  UpperCAmelCase	:     List[str]						 =			[F"""{prefix}-{shard_id:05d}-of-{num_shards:05d}""" for shard_id in range(UpperCAmelCase_     )]
  if filetype_suffix:
   UpperCAmelCase	:     Dict						 =			[filename + F""".{filetype_suffix}""" for filename in filenames]
  return filenames
 else:
  UpperCAmelCase	:     Optional[Any]						 =			prefix
  if filetype_suffix:
   filename += F""".{filetype_suffix}"""
  return [filename]




