


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


snake_case				:    Optional[int]       				=     logging.get_logger(__name__)

snake_case				:    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  (      _snake_case						,    _snake_case							):
 SCREAMING_SNAKE_CASE__      =       'swin'

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




 def __init__(		self					,  _lowerCamelCase=224					,  _lowerCamelCase=4					,  _lowerCamelCase=3					,  _lowerCamelCase=96					,  _lowerCamelCase=[2, 2, 6, 2]					,  _lowerCamelCase=[3, 6, 12, 24]					,  _lowerCamelCase=7					,  _lowerCamelCase=4.0					,  _lowerCamelCase=True					,  _lowerCamelCase=0.0					,  _lowerCamelCase=0.0					,  _lowerCamelCase=0.1					,  _lowerCamelCase="gelu"					,  _lowerCamelCase=False					,  _lowerCamelCase=0.02					,  _lowerCamelCase=1e-5					,  _lowerCamelCase=32					,  _lowerCamelCase=None					,  _lowerCamelCase=None					,  **_lowerCamelCase					,  ):
       super().__init__(**_lowerCamelCase    )

       a						:Optional[Any] 							=       image_size
       a						:List[Any] 							=       patch_size
       a						:Any 							=       num_channels
       a						:str 							=       embed_dim
       a						:str 							=       depths
       a						:Optional[Any] 							=       len(_lowerCamelCase    )
       a						:int 							=       num_heads
       a						:str 							=       window_size
       a						:List[Any] 							=       mlp_ratio
       a						:Union[str, Any] 							=       qkv_bias
       a						:Optional[Any] 							=       hidden_dropout_prob
       a						:List[Any] 							=       attention_probs_dropout_prob
       a						:Any 							=       drop_path_rate
       a						:Dict 							=       hidden_act
       a						:Union[str, Any] 							=       use_absolute_embeddings
       a						:Tuple 							=       layer_norm_eps
       a						:Optional[Any] 							=       initializer_range
       a						:List[str] 							=       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						:List[str] 							=       int(embed_dim * 2 ** (len(_lowerCamelCase    ) - 1)    )
       a						:List[Any] 							=       ['''stem'''] + [F'''stage{idx}''' for idx in range(1					,  len(_lowerCamelCase    ) + 1    )]
       a							,				a						:Dict 							=       get_aligned_output_features_output_indices(
           out_features=_lowerCamelCase					,  out_indices=_lowerCamelCase					,  stage_names=self.stage_names    )







class 		_snake_case  (      _snake_case							):
 SCREAMING_SNAKE_CASE__      =       version.parse('1.11'							)




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




 @property
 def        SCREAMING_SNAKE_CASE__				(		self    ):
       return 1e-4









"""simple docstring"""




def        lowercase							(		lowerCAmelCase__ :     int			) ->      str:
		if number > 0:
				raise ValueError('''input must be a negative integer'''			)
		__a           =			len(bin(lowerCAmelCase__			)[3:]			)
		__a           =			bin(abs(lowerCAmelCase__			) - (1 << binary_number_length)			)[3:]
		__a           =			(
		    (
		        '''1'''
		        + '''0''' * (binary_number_length - len(lowerCAmelCase__			))
		        + twos_complement_number
		    )
		    if number < 0
		    else '''0'''
		)
		return "0b" + twos_complement_number


if __name__ == "__main__":
				import doctest

				doctest.testmod()






