

'''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


_UpperCAmelCase  :		int  =		logging.get_logger(__name__)

_UpperCAmelCase  :		Optional[int]  =		{
    '''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 						__magic_name__   (							__SCREAMING_SNAKE_CASE ,				__SCREAMING_SNAKE_CASE ):
 UpperCamelCase__     =       'swin'

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







 def __init__(       self  , snake_case_=2_24  , snake_case_=4  , snake_case_=3  , snake_case_=96  , snake_case_=[2, 2, 6, 2]  , snake_case_=[3, 6, 12, 24]  , snake_case_=7  , snake_case_=4.0  , snake_case_=True  , snake_case_=0.0  , snake_case_=0.0  , snake_case_=0.1  , snake_case_="gelu"  , snake_case_=False  , snake_case_=0.02  , snake_case_=1E-5  , snake_case_=32  , snake_case_=None  , snake_case_=None  , **snake_case_  , ):
   super().__init__(**snake_case_   )

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

class 						__magic_name__   (							__SCREAMING_SNAKE_CASE ):
 UpperCamelCase__     =       version.parse('1.11' )







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







 @property
 def 						_A(       self   ):
   return 1E-4





def A    (							__UpperCamelCase			,						__UpperCamelCase			,						__UpperCamelCase       )    ->   int:

			if exponent == 1:
						return base
			if exponent % 2 == 0:
						A__	  =     _modexpt(__UpperCamelCase			,						exponent // 2			,						__UpperCamelCase       ) % modulo_value
						return (x * x) % modulo_value
			else:
						return (base * _modexpt(__UpperCamelCase			,						exponent - 1			,						__UpperCamelCase       )) % modulo_value


def A    (							__UpperCamelCase = 1_777			,						__UpperCamelCase = 1_855			,						__UpperCamelCase = 8       )    ->   int:
			A__	  =     base
			for _ in range(1			,						__UpperCamelCase       ):
						A__	  =     _modexpt(__UpperCamelCase			,						__UpperCamelCase			,						10**digits       )

			return result


if __name__ == "__main__":
							print(f'{solution() = }')




