
# 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__		:     int     			=      '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__							(					)      ->   Tuple:
   _A:  Optional[int]					=       _ask_options(
       '''In which compute environment are you running?'''		,		['''This machine''', '''AWS (Amazon SageMaker)''']		,		_convert_compute_environment		,		)
   if compute_environment == ComputeEnvironment.AMAZON_SAGEMAKER:
      _A:  Optional[int]					=       get_sagemaker_input()
   else:
      _A:  List[str]					=       get_cluster_input()
   return config






def   lowerCamelCase__							(					a=None      )      ->   Union[str, Any]:
   if subparsers is not None:
      _A:  List[str]					=       subparsers.add_parser('''config'''		,		description=a      )
   else:
      _A:  Union[str, Any]					=       argparse.ArgumentParser('''Accelerate config command'''		,		description=a      )

   parser.add_argument(
       '''--config_file'''		,		default=a		,		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=a      )
   return parser






def   lowerCamelCase__							(					a      )      ->   Optional[int]:
   _A:  Optional[Any]					=       get_user_input()
   if args.config_file is not None:
      _A:  Any					=       args.config_file
   else:
      if not os.path.isdir(a      ):
         os.makedirs(a      )
      _A:  Dict					=       default_yaml_config_file

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






def   lowerCamelCase__							(					)      ->   Union[str, Any]:
   _A:  Optional[int]					=       config_command_parser()
   _A:  str					=       parser.parse_args()
   config_command(a      )


if __name__ == "__main__":
   main()





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


UpperCAmelCase__		:     Any     			=      {'configuration_swin': ['SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SwinConfig', 'SwinOnnxConfig']}


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase__		:     Union[str, Any]     			=      [
       'SWIN_PRETRAINED_MODEL_ARCHIVE_LIST',
       'SwinForImageClassification',
       'SwinForMaskedImageModeling',
       'SwinModel',
       'SwinPreTrainedModel',
       'SwinBackbone',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase__		:     str     			=      [
       'TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST',
       'TFSwinForImageClassification',
       'TFSwinForMaskedImageModeling',
       'TFSwinModel',
       'TFSwinPreTrainedModel',
   ]

if TYPE_CHECKING:
   from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_swin import (
          SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
          SwinBackbone,
          SwinForImageClassification,
          SwinForMaskedImageModeling,
          SwinModel,
          SwinPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_swin import (
          TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFSwinForImageClassification,
          TFSwinForMaskedImageModeling,
          TFSwinModel,
          TFSwinPreTrainedModel,
      )

else:
   import sys

   UpperCAmelCase__		:     Tuple     			=      _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



