



'''simple docstring'''




import argparse
import os

from accelerate.utils import ComputeEnvironment

from .cluster import get_cluster_input
from .config_args import cache_dir, default_config_file, default_yaml_config_file, load_config_from_file  # noqa: F401
from .config_utils import _ask_field, _ask_options, _convert_compute_environment  # noqa: F401
from .sagemaker import get_sagemaker_input


lowercase__   :				List[Any]      =   '''Launches a series of prompts to create and save a `default_config.yaml` configuration file for your training system. Should always be ran first on your machine'''






def 	_lowerCAmelCase      (  )					->					Dict:
     __A						:			Union[str, Any]								=	_ask_options(
         'In which compute environment are you running?'			,							['This machine', 'AWS (Amazon SageMaker)']			,							_convert_compute_environment			,							)
     if compute_environment == ComputeEnvironment.AMAZON_SAGEMAKER:
          __A						:			str								=	get_sagemaker_input()
     else:
          __A						:			Union[str, Any]								=	get_cluster_input()
     return config






def 	_lowerCAmelCase      (  __snake_case  :			List[str]=None      )					->					Dict:
     if subparsers is not None:
          __A						:			Tuple								=	subparsers.add_parser('config'			,							description=__snake_case      )
     else:
          __A						:			str								=	argparse.ArgumentParser('Accelerate config command'			,							description=__snake_case      )

     parser.add_argument(
         '--config_file'			,							default=__snake_case			,							help=(
             'The path to use to store the config file. Will default to a file named default_config.yaml in the cache '
             'location, which is the content of the environment `HF_HOME` suffixed with \'accelerate\', or if you don\'t have '
             'such an environment variable, your cache directory (\'~/.cache\' or the content of `XDG_CACHE_HOME`) suffixed '
             'with \'huggingface\'.'
         )			,							)

     if subparsers is not None:
          parser.set_defaults(func=__snake_case      )
     return parser






def 	_lowerCAmelCase      (  __snake_case  :			List[str]      )					->					List[str]:
     __A						:			Optional[int]								=	get_user_input()
     if args.config_file is not None:
          __A						:			Dict								=	args.config_file
     else:
          if not os.path.isdir(__snake_case      ):
               os.makedirs(__snake_case      )
          __A						:			Any								=	default_yaml_config_file

     if config_file.endswith('.json'      ):
          config.to_json_file(__snake_case      )
     else:
          config.to_yaml_file(__snake_case      )
     print(f'accelerate configuration saved at {config_file}'      )






def 	_lowerCAmelCase      (  )					->					int:
     __A						:			Optional[Any]								=	config_command_parser()
     __A						:			Any								=	parser.parse_args()
     config_command(__snake_case      )


if __name__ == "__main__":
  main()






'''simple docstring'''




lowercase__   :				Any      =   {'''a''': ['''c''', '''b'''], '''b''': ['''d''', '''e'''], '''c''': [], '''d''': [], '''e''': []}
lowercase__   :				List[Any]      =   ['''a''', '''b''', '''c''', '''d''', '''e''']






def 	_lowerCAmelCase      (  __snake_case  :			str			,							__snake_case  :			Tuple			,							__snake_case  :			int      )					->					Tuple:
     __A						:			List[str]								=	start
     # add current to visited
     visited.append(__snake_case      )
     __A						:			Optional[int]								=	edges[current]
     for neighbor in neighbors:
          # if neighbor not in visited, visit
          if neighbor not in visited:
               __A						:			int								=	topological_sort(__snake_case			,							__snake_case			,							__snake_case      )
    # if all neighbors visited add current to sort
     sort.append(__snake_case      )
     # if all vertices haven't been visited select a new one to visit
     if len(__snake_case      ) != len(__snake_case      ):
          for vertice in vertices:
               if vertice not in visited:
                    __A						:			Dict								=	topological_sort(__snake_case			,							__snake_case			,							__snake_case      )
    # return sort
     return sort


if __name__ == "__main__":
  lowercase__   :				Tuple      =   topological_sort('''a''', [], [])
  print(sort)