
"""simple docstring"""


from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


_lowercase				 =					logging.get_logger(__name__)

_lowercase				 =					{
    '''google/bit-50''': '''https://huggingface.co/google/bit-50/resolve/main/config.json''',
}







class 					lowerCAmelCase_					(   _lowercase		,       _lowercase     ):



						'''simple docstring'''


						_lowerCamelCase:     Any   =     '''bit'''
						_lowerCamelCase:     List[Any]   =     ['''preactivation''', '''bottleneck''']
						_lowerCamelCase:     Tuple   =     ['''SAME''', '''VALID''']


						def __init__(			self  :   Union[str, Any]	,A_  :   Tuple=3	,A_  :   List[Any]=64	,A_  :   Optional[int]=[256, 512, 1024, 2048]	,A_  :   List[Any]=[3, 4, 6, 3]	,A_  :   Optional[Any]="preactivation"	,A_  :   Optional[int]="relu"	,A_  :   Optional[Any]=None	,A_  :   Any=32	,A_  :   Union[str, Any]=0.0	,A_  :   Optional[int]=False	,A_  :   Tuple=32	,A_  :   Dict=1	,A_  :   str=None	,A_  :   List[str]=None	,**A_  :   Dict	,)  -> Any:
							super().__init__(**A_   )
							if layer_type not in self.layer_types:
								raise ValueError(F'layer_type={layer_type} is not one of {",".join(self.layer_types   )}'   )
							if global_padding is not None:
								if global_padding.upper() in self.supported_padding:
									A     = global_padding.upper()
								else:
									raise ValueError(F'Padding strategy {global_padding} not supported'   )
							A     = num_channels
							A     = embedding_size
							A     = hidden_sizes
							A     = depths
							A     = layer_type
							A     = hidden_act
							A     = global_padding
							A     = num_groups
							A     = drop_path_rate
							A     = embedding_dynamic_padding
							A     = output_stride
							A     = width_factor

							A     = ['stem'] + [F'stage{idx}' for idx in range(1	,len(A_   ) + 1   )]
							A ,   A     = get_aligned_output_features_output_indices(
							    out_features=A_	,out_indices=A_	,stage_names=self.stage_names   )

"""simple docstring"""


# 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


_lowercase				 =					'''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    _snake_case					(		):
	A     = _ask_options(
	    'In which compute environment are you running?'						,   ['This machine', 'AWS (Amazon SageMaker)']						,   _convert_compute_environment						,   )
	if compute_environment == ComputeEnvironment.AMAZON_SAGEMAKER:
		A     = get_sagemaker_input()
	else:
		A     = get_cluster_input()
	return config






def    _snake_case					(		snake_case__ :  Any=None  ):
	if subparsers is not None:
		A     = subparsers.add_parser('config'						,   description=snake_case__  )
	else:
		A     = 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    _snake_case					(		snake_case__ :  Tuple  ):
	A     = get_user_input()
	if args.config_file is not None:
		A     = args.config_file
	else:
		if not os.path.isdir(snake_case__  ):
			os.makedirs(snake_case__  )
		A     = 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    _snake_case					(		):
	A     = config_command_parser()
	A     = parser.parse_args()
	config_command(snake_case__  )


if __name__ == "__main__":
		main()