



UpperCAmelCase_									=							"\n# Transformers 설치 방법\n! pip install transformers datasets\n# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"

UpperCAmelCase_									=							[{"type": "code", "content": INSTALL_CONTENT}]
UpperCAmelCase_									=							{
    "{processor_class}": "FakeProcessorClass",
    "{model_class}": "FakeModelClass",
    "{object_class}": "FakeObjectClass",
}




# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

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


UpperCAmelCase_									=							"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 							UpperCAmelCase__		(				)->Any:
      _lowerCAmelCase 			=  _ask_options(
          '''In which compute environment are you running?'''     ,				['''This machine''', '''AWS (Amazon SageMaker)''']     ,				_convert_compute_environment     ,				)
      if compute_environment == ComputeEnvironment.AMAZON_SAGEMAKER:
            _lowerCAmelCase 			=  get_sagemaker_input()
      else:
            _lowerCAmelCase 			=  get_cluster_input()
      return config
def 							UpperCAmelCase__		(				_SCREAMING_SNAKE_CASE   :	int=None				)->str:
      if subparsers is not None:
            _lowerCAmelCase 			=  subparsers.add_parser('''config'''     ,				description=_SCREAMING_SNAKE_CASE				)
      else:
            _lowerCAmelCase 			=  argparse.ArgumentParser('''Accelerate config command'''     ,				description=_SCREAMING_SNAKE_CASE				)

      parser.add_argument(
          '''--config_file'''     ,				default=_SCREAMING_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=_SCREAMING_SNAKE_CASE				)
      return parser
def 							UpperCAmelCase__		(				_SCREAMING_SNAKE_CASE   :	Dict				)->str:
      _lowerCAmelCase 			=  get_user_input()
      if args.config_file is not None:
            _lowerCAmelCase 			=  args.config_file
      else:
            if not os.path.isdir(_SCREAMING_SNAKE_CASE				):
                  os.makedirs(_SCREAMING_SNAKE_CASE				)
            _lowerCAmelCase 			=  default_yaml_config_file

      if config_file.endswith('''.json'''				):
            config.to_json_file(_SCREAMING_SNAKE_CASE				)
      else:
            config.to_yaml_file(_SCREAMING_SNAKE_CASE				)
      print(f'''accelerate configuration saved at {config_file}'''				)
def 							UpperCAmelCase__		(				)->List[Any]:
      _lowerCAmelCase 			=  config_command_parser()
      _lowerCAmelCase 			=  parser.parse_args()
      config_command(_SCREAMING_SNAKE_CASE				)


if __name__ == "__main__":
    main()