import copy
import re




class 	__snake_case	:





      '''simple docstring'''






      _snake_case    		=       'hp'
      _snake_case    		=       {}
      _snake_case    		=       None



      @classmethod
      def 	_SCREAMING_SNAKE_CASE    (					cls     :				List[Any]    ,  _UpperCamelCase     :				Union[str, Any]    ,  _UpperCamelCase     :				Any)				->Tuple:


          """simple docstring"""


          _lowerCamelCase     :		Optional[int] 						=						prefix
          _lowerCamelCase     :		Union[str, Any] 						=						defaults
          cls.build_naming_info()



      @staticmethod
      def 	_SCREAMING_SNAKE_CASE    (					_UpperCamelCase     :				Any    ,  _UpperCamelCase     :				List[Any])				->int:


          """simple docstring"""


          if len(_UpperCamelCase) == 0:
              return ""
          _lowerCamelCase     :		Optional[Any] 						=						None
          if any(char.isdigit() for char in word):
              raise Exception(F"""Parameters should not contain numbers: '{word}' contains a number""")
          if word in info["short_word"]:
              return info["short_word"][word]
          for prefix_len in range(1    ,  len(_UpperCamelCase) + 1):
              _lowerCamelCase     :		List[str] 						=						word[:prefix_len]
              if prefix in info["reverse_short_word"]:
                  continue
              else:
                  _lowerCamelCase     :		int 						=						prefix
                  break

          if short_word is None:
              # Paranoid fallback
              def int_to_alphabetic(_UpperCamelCase     :				Dict):
                  _lowerCamelCase     :		Union[str, Any] 						=						""""""
                  while integer != 0:
                      _lowerCamelCase     :		Any 						=						chr(ord("""A""") + integer % 10) + s
                      integer //= 10
                  return s

              _lowerCamelCase     :		int 						=						0
              while True:
                  _lowerCamelCase     :		int 						=						word + """#""" + int_to_alphabetic(_UpperCamelCase)
                  if sword in info["reverse_short_word"]:
                      continue
                  else:
                      _lowerCamelCase     :		Optional[Any] 						=						sword
                      break

          _lowerCamelCase     :		Tuple 						=						short_word
          _lowerCamelCase     :		Union[str, Any] 						=						word
          return short_word



      @staticmethod
      def 	_SCREAMING_SNAKE_CASE    (					_UpperCamelCase     :				List[str]    ,  _UpperCamelCase     :				Optional[Any])				->Any:


          """simple docstring"""


          _lowerCamelCase     :		Optional[Any] 						=						param_name.split("""_""")

          _lowerCamelCase     :		int 						=						[TrialShortNamer.shortname_for_word(_UpperCamelCase    ,  _UpperCamelCase) for word in words]

          # We try to create a separatorless short name, but if there is a collision we have to fallback
          # to a separated short name
          _lowerCamelCase     :		str 						=						["""""", """_"""]

          for separator in separators:
              _lowerCamelCase     :		Optional[Any] 						=						separator.join(_UpperCamelCase)
              if shortname not in info["reverse_short_param"]:
                  _lowerCamelCase     :		Any 						=						shortname
                  _lowerCamelCase     :		Optional[int] 						=						param_name
                  return shortname

          return param_name



      @staticmethod
      def 	_SCREAMING_SNAKE_CASE    (					_UpperCamelCase     :				Optional[int]    ,  _UpperCamelCase     :				Union[str, Any])				->Dict:


          """simple docstring"""


          _lowerCamelCase     :		str 						=						TrialShortNamer.shortname_for_key(_UpperCamelCase    ,  _UpperCamelCase)
          _lowerCamelCase     :		int 						=						short_name
          _lowerCamelCase     :		Optional[int] 						=						param_name



      @classmethod
      def 	_SCREAMING_SNAKE_CASE    (					cls     :				Tuple)				->int:


          """simple docstring"""


          if cls.NAMING_INFO is not None:
              return

          _lowerCamelCase     :		str 						=						{
              """short_word""": {},
              """reverse_short_word""": {},
              """short_param""": {},
              """reverse_short_param""": {},
          }

          _lowerCamelCase     :		int 						=						list(cls.DEFAULTS.keys())

          for k in field_keys:
              cls.add_new_param_name(_UpperCamelCase    ,  _UpperCamelCase)

          _lowerCamelCase     :		List[Any] 						=						info



      @classmethod
      def 	_SCREAMING_SNAKE_CASE    (					cls     :				Dict    ,  _UpperCamelCase     :				List[str])				->Dict:


          """simple docstring"""


          cls.build_naming_info()
          assert cls.PREFIX is not None
          _lowerCamelCase     :		List[str] 						=						[copy.copy(cls.PREFIX)]

          for k, v in params.items():
              if k not in cls.DEFAULTS:
                  raise Exception(F"""You should provide a default value for the param name {k} with value {v}""")
              if v == cls.DEFAULTS[k]:
                  # The default value is not added to the name
                  continue

              _lowerCamelCase     :		Any 						=						cls.NAMING_INFO["""short_param"""][k]

              if isinstance(_UpperCamelCase    ,  _UpperCamelCase):
                  _lowerCamelCase     :		int 						=						1 if v else 0

              _lowerCamelCase     :		List[str] 						=						"""""" if isinstance(_UpperCamelCase    ,  (int, float)) else """-"""
              _lowerCamelCase     :		Dict 						=						F"""{key}{sep}{v}"""
              name.append(_UpperCamelCase)

          return "_".join(_UpperCamelCase)




      @classmethod
      def 	_SCREAMING_SNAKE_CASE    (					cls     :				int    ,  _UpperCamelCase     :				Tuple)				->Tuple:


          """simple docstring"""


          _lowerCamelCase     :		Tuple 						=						repr[len(cls.PREFIX) + 1 :]
          if repr == "":
              _lowerCamelCase     :		List[Any] 						=						[]
          else:
              _lowerCamelCase     :		Dict 						=						repr.split("""_""")

          _lowerCamelCase     :		Tuple 						=						{}

          for value in values:
              if "-" in value:
                  _lowerCamelCase						,							_lowerCamelCase     :		Tuple 						=						value.split("""-""")
              else:
                  _lowerCamelCase     :		int 						=						re.sub("""[0-9.]"""    ,  """"""    ,  _UpperCamelCase)
                  _lowerCamelCase     :		Tuple 						=						float(re.sub("""[^0-9.]"""    ,  """"""    ,  _UpperCamelCase))

              _lowerCamelCase     :		Dict 						=						cls.NAMING_INFO["""reverse_short_param"""][p_k]

              _lowerCamelCase     :		int 						=						p_v

          for k in cls.DEFAULTS:
              if k not in parameters:
                  _lowerCamelCase     :		List[Any] 						=						cls.DEFAULTS[k]

          return parameters





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			:							Any     =logging.get_logger(__name__)

lowerCAmelCase			:							List[Any]     ={
    "microsoft/swin-tiny-patch4-window7-224": (
        "https://huggingface.co/microsoft/swin-tiny-patch4-window7-224/resolve/main/config.json"
    ),
    # See all Swin models at https://huggingface.co/models?filter=swin
}




class 	__snake_case	( __lowerCAmelCase ,  __lowerCAmelCase		):





      '''simple docstring'''






      _snake_case    		=       'swin'

      _snake_case    		=       {
          'num_attention_heads': 'num_heads',
          'num_hidden_layers': 'num_layers',
      }



      def __init__(					self     :				Optional[int]    ,  _UpperCamelCase     :				List[str]=224    ,  _UpperCamelCase     :				List[str]=4    ,  _UpperCamelCase     :				List[Any]=3    ,  _UpperCamelCase     :				Dict=96    ,  _UpperCamelCase     :				Any=[2, 2, 6, 2]    ,  _UpperCamelCase     :				Any=[3, 6, 12, 24]    ,  _UpperCamelCase     :				Tuple=7    ,  _UpperCamelCase     :				Tuple=4.0    ,  _UpperCamelCase     :				Dict=True    ,  _UpperCamelCase     :				Tuple=0.0    ,  _UpperCamelCase     :				Any=0.0    ,  _UpperCamelCase     :				Optional[int]=0.1    ,  _UpperCamelCase     :				Any="gelu"    ,  _UpperCamelCase     :				str=False    ,  _UpperCamelCase     :				str=0.0_2    ,  _UpperCamelCase     :				Dict=1E-5    ,  _UpperCamelCase     :				List[str]=32    ,  _UpperCamelCase     :				Optional[Any]=None    ,  _UpperCamelCase     :				List[Any]=None    ,  **_UpperCamelCase     :				List[Any]    ,  )				->Tuple:


          """simple docstring"""


          super().__init__(**_UpperCamelCase)

          _lowerCamelCase     :		List[str] 						=						image_size
          _lowerCamelCase     :		Tuple 						=						patch_size
          _lowerCamelCase     :		Dict 						=						num_channels
          _lowerCamelCase     :		Union[str, Any] 						=						embed_dim
          _lowerCamelCase     :		str 						=						depths
          _lowerCamelCase     :		str 						=						len(_UpperCamelCase)
          _lowerCamelCase     :		Optional[Any] 						=						num_heads
          _lowerCamelCase     :		Tuple 						=						window_size
          _lowerCamelCase     :		int 						=						mlp_ratio
          _lowerCamelCase     :		Optional[int] 						=						qkv_bias
          _lowerCamelCase     :		List[str] 						=						hidden_dropout_prob
          _lowerCamelCase     :		str 						=						attention_probs_dropout_prob
          _lowerCamelCase     :		Tuple 						=						drop_path_rate
          _lowerCamelCase     :		List[str] 						=						hidden_act
          _lowerCamelCase     :		Dict 						=						use_absolute_embeddings
          _lowerCamelCase     :		int 						=						layer_norm_eps
          _lowerCamelCase     :		str 						=						initializer_range
          _lowerCamelCase     :		Dict 						=						encoder_stride
          # we set the hidden_size attribute in order to make Swin work with VisionEncoderDecoderModel
          # this indicates the channel dimension after the last stage of the model
          _lowerCamelCase     :		int 						=						int(embed_dim * 2 ** (len(_UpperCamelCase) - 1))
          _lowerCamelCase     :		Dict 						=						["""stem"""] + [F"""stage{idx}""" for idx in range(1    ,  len(_UpperCamelCase) + 1)]
          _lowerCamelCase						,							_lowerCamelCase     :		List[str] 						=						get_aligned_output_features_output_indices(
              out_features=_UpperCamelCase    ,  out_indices=_UpperCamelCase    ,  stage_names=self.stage_names)





class 	__snake_case	( __lowerCAmelCase		):





      '''simple docstring'''






      _snake_case    		=       version.parse('1.11'		)



      @property
      def 	_SCREAMING_SNAKE_CASE    (					self     :				Tuple)				->Mapping[str, Mapping[int, str]]:


          """simple docstring"""


          return OrderedDict(
              [
                  ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
              ])




      @property
      def 	_SCREAMING_SNAKE_CASE    (					self     :				Union[str, Any])				->float:


          """simple docstring"""


          return 1E-4




