
'''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_        =							logging.get_logger(__name__)

UpperCamelCase_        =							{
    """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 	a_	(__SCREAMING_SNAKE_CASE				,      __SCREAMING_SNAKE_CASE     ):
       __lowerCAmelCase     :					str     =   """swin"""

       __lowerCAmelCase     :					str     =   {
           """num_attention_heads""": """num_heads""",
           """num_hidden_layers""": """num_layers""",
       }




       def __init__(  self , snake_case_=2_2_4 , snake_case_=4 , snake_case_=3 , snake_case_=9_6 , snake_case_=[2, 2, 6, 2] , snake_case_=[3, 6, 1_2, 2_4] , 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_=3_2 , snake_case_=None , snake_case_=None , **snake_case_ , ):
         super().__init__(**UpperCamelCase__	)

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



class 	a_	(__SCREAMING_SNAKE_CASE     ):
       __lowerCAmelCase     :					int     =   version.parse("""1.11"""     )




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







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




'''simple docstring'''
import numpy as np




def    _UpperCamelCase						(       SCREAMING_SNAKE_CASE__			)  ->							np.ndarray:


		'''simple docstring'''


		return 1 / (1 + np.exp(-vector			))




def    _UpperCamelCase						(       SCREAMING_SNAKE_CASE__			)  ->							np.ndarray:


		'''simple docstring'''


		return vector * sigmoid(SCREAMING_SNAKE_CASE__			)


if __name__ == "__main__":
						import doctest

						doctest.testmod()


