

"""simple docstring"""






from collections import OrderedDict
from typing import Mapping

from packaging import version

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


lowerCamelCase__ :     List[Any]							  =     logging.get_logger(__name__)

lowerCamelCase__ :     str							  =     {
    """microsoft/resnet-50""": """https://huggingface.co/microsoft/resnet-50/blob/main/config.json""",
}






class 			_UpperCAmelCase	(						snake_case__			,   snake_case__):
			__a       :				Tuple     =							"resnet"
			__a       :				Union[str, Any]     =							["basic", "bottleneck"]
			def __init__(						self					,						_A=3					,						_A=64					,						_A=[2_56, 5_12, 10_24, 20_48]					,						_A=[3, 4, 6, 3]					,						_A="bottleneck"					,						_A="relu"					,						_A=False					,						_A=None					,						_A=None					,						**_A					,						)			->			List[str]:






				'''simple docstring'''







				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   )}'''   )
				_UpperCAmelCase			:							Tuple	  =    num_channels
				_UpperCAmelCase			:							int	  =    embedding_size
				_UpperCAmelCase			:							Union[str, Any]	  =    hidden_sizes
				_UpperCAmelCase			:							int	  =    depths
				_UpperCAmelCase			:							Any	  =    layer_type
				_UpperCAmelCase			:							Optional[Any]	  =    hidden_act
				_UpperCAmelCase			:							Union[str, Any]	  =    downsample_in_first_stage
				_UpperCAmelCase			:							Dict	  =    ["stem"] + [f'''stage{idx}''' for idx in range(1					,						len(_A   ) + 1   )]
				_UpperCAmelCase			:							str	  =    get_aligned_output_features_output_indices(
				    out_features=_A					,						out_indices=_A					,						stage_names=self.stage_names   )






class 			_UpperCAmelCase	(						snake_case__):
			__a       :				List[str]     =							version.parse("""1.11""")
			@property
			def 							__snake_case       (						self   )			->			Tuple:






				'''simple docstring'''







				return OrderedDict(
				    [
				        ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
				    ]   )
			@property
			def 							__snake_case       (						self   )			->			Union[str, Any]:






				'''simple docstring'''







				return 1e-3






'''simple docstring'''




def 	UpperCamelCase_							(					_UpperCAmelCase  :      str			,	_UpperCAmelCase  :      str    )    ->    float:


       """simple docstring"""







       def get_matched_characters(_UpperCAmelCase  :      str			,	_UpperCAmelCase  :      str    ) -> str:
              _UpperCAmelCase     :  Tuple							      =    []
              _UpperCAmelCase     :  Dict							      =    min(len(_stra    )			,	len(_stra    )    ) // 2
              for i, l in enumerate(_stra    ):
                     _UpperCAmelCase     :  int							      =    int(max(0			,	i - limit    )    )
                     _UpperCAmelCase     :  Any							      =    int(min(i + limit + 1			,	len(_stra    )    )    )
                     if l in _stra[left:right]:
                            matched.append(_UpperCAmelCase    )
                            _UpperCAmelCase     :  List[Any]							      =    F"""{_stra[0:_stra.index(_UpperCAmelCase    )]} {_stra[_stra.index(_UpperCAmelCase    ) + 1:]}"""

              return "".join(_UpperCAmelCase    )

       # matching characters
       _UpperCAmelCase     :  Union[str, Any]							      =    get_matched_characters(_UpperCAmelCase			,	_UpperCAmelCase    )
       _UpperCAmelCase     :  Tuple							      =    get_matched_characters(_UpperCAmelCase			,	_UpperCAmelCase    )
       _UpperCAmelCase     :  Tuple							      =    len(_UpperCAmelCase    )

       # transposition
       _UpperCAmelCase     :  Optional[Any]							      =    (
           len([(ca, ca) for ca, ca in zip(_UpperCAmelCase			,	_UpperCAmelCase    ) if ca != ca]    ) // 2
       )

       if not match_count:
              _UpperCAmelCase     :  Dict							      =    0.0
       else:
              _UpperCAmelCase     :  Optional[int]							      =    (
                  1
                  / 3
                  * (
                      match_count / len(_UpperCAmelCase    )
                      + match_count / len(_UpperCAmelCase    )
                      + (match_count - transpositions) / match_count
                  )
              )

       # common prefix up to 4 characters
       _UpperCAmelCase     :  str							      =    0
       for ca, ca in zip(stra[:4]			,	stra[:4]    ):
              if ca == ca:
                     prefix_len += 1
              else:
                     break

       return jaro + 0.1 * prefix_len * (1 - jaro)


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  print(jaro_winkler("""hello""", """world"""))

