

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


__lowercase				      =						logging.get_logger(__name__)

__lowercase				      =						{
    """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    _lowercase				(					__lowerCamelCase,__lowerCamelCase			):
   _lowercase     :       int  					=    'swin'

   _lowercase     :       Optional[Any]  					=    {
       'num_attention_heads': 'num_heads',
       'num_hidden_layers': 'num_layers',
   }

   def __init__(				self	:    Union[str, Any]			,						lowerCamelCase__	:    List[Any]=2_2_4			,						lowerCamelCase__	:    Any=4			,						lowerCamelCase__	:    Any=3			,						lowerCamelCase__	:    Dict=9_6			,						lowerCamelCase__	:    Tuple=[2, 2, 6, 2]			,						lowerCamelCase__	:    str=[3, 6, 1_2, 2_4]			,						lowerCamelCase__	:    Union[str, Any]=7			,						lowerCamelCase__	:    Tuple=4.0			,						lowerCamelCase__	:    List[Any]=True			,						lowerCamelCase__	:    Optional[Any]=0.0			,						lowerCamelCase__	:    Tuple=0.0			,						lowerCamelCase__	:    Tuple=0.1			,						lowerCamelCase__	:    str="gelu"			,						lowerCamelCase__	:    List[Any]=False			,						lowerCamelCase__	:    Dict=0.02			,						lowerCamelCase__	:    List[str]=1e-5			,						lowerCamelCase__	:    Optional[Any]=3_2			,						lowerCamelCase__	:    List[str]=None			,						lowerCamelCase__	:    Tuple=None			,						**lowerCamelCase__	:    Any			,						) ->			List[str]:
         """simple docstring"""





         super().__init__(**lowerCamelCase__       )

         A_							       =		image_size
         A_							       =		patch_size
         A_							       =		num_channels
         A_							       =		embed_dim
         A_							       =		depths
         A_							       =		len(lowerCamelCase__       )
         A_							       =		num_heads
         A_							       =		window_size
         A_							       =		mlp_ratio
         A_							       =		qkv_bias
         A_							       =		hidden_dropout_prob
         A_							       =		attention_probs_dropout_prob
         A_							       =		drop_path_rate
         A_							       =		hidden_act
         A_							       =		use_absolute_embeddings
         A_							       =		layer_norm_eps
         A_							       =		initializer_range
         A_							       =		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
         A_							       =		int(embed_dim * 2 ** (len(lowerCamelCase__       ) - 1)       )
         A_							       =		['''stem'''] + [F"stage{idx}" for idx in range(1			,						len(lowerCamelCase__       ) + 1       )]
         A_       ,A_							       =		get_aligned_output_features_output_indices(
             out_features=lowerCamelCase__			,						out_indices=lowerCamelCase__			,						stage_names=self.stage_names       )



class    _lowercase				(					__lowerCamelCase			):
   _lowercase     :       Optional[Any]  					=    version.parse('1.11'			)

   @property
   def     UpperCamelCase					(				self	:    int       ) ->			Mapping[str, Mapping[int, str]]:
         """simple docstring"""





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





   @property
   def     UpperCamelCase					(				self	:    Union[str, Any]       ) ->			float:
         """simple docstring"""





         return 1e-4








from __future__ import annotations







def 							_lowerCamelCase   (			SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE = None		,				SCREAMING_SNAKE_CASE = None   ):
      '''simple docstring'''







      if start is None:
            A_							       =		0

      if end is None:
            A_							       =		len(SCREAMING_SNAKE_CASE   ) - 1

      if start >= end:
            return

      A_							       =		(start + end) // 2

      slowsort(SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE   )
      slowsort(SCREAMING_SNAKE_CASE		,				mid + 1		,				SCREAMING_SNAKE_CASE   )

      if sequence[end] < sequence[mid]:
            A_       ,A_							       =		sequence[mid], sequence[end]

      slowsort(SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE		,				end - 1   )


if __name__ == "__main__":
      from doctest import testmod

      testmod()





