




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_					    = logging.get_logger(__name__)

lowerCAmelCase_					    = {
    """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  _lowerCAmelCase     (  _lowercase    ,			_lowercase	):
						A__		     =		'swin'

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

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

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






class  _lowerCAmelCase     (  _lowercase	):
						A__		     =		version.parse('1.11'	)

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







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







import math



def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase      )     ->	float:
  if (
      not isinstance(UpperCamelCase	,      (int, float)      )
      or power_factor < -1
      or power_factor > 1
  ):
    raise ValueError('''power_factor must be a valid float value between -1 and 1.'''      )
  return apparent_power * power_factor



def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase      )     ->	float:
  if (
      not isinstance(UpperCamelCase	,      (int, float)      )
      or power_factor < -1
      or power_factor > 1
  ):
    raise ValueError('''power_factor must be a valid float value between -1 and 1.'''      )
  return apparent_power * math.sqrt(1 - power_factor**2      )


if __name__ == "__main__":
     import doctest

     doctest.testmod()

