'''simple docstring'''

from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase__     :	int				=			logging.get_logger(__name__)

UpperCamelCase__     :	str				=			{
    'microsoft/swinv2-tiny-patch4-window8-256': (
        'https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json'
    ),
}


class 				_lowercase	(      __lowercase   ):
      '''simple docstring'''


      UpperCAmelCase_      :      int      							=   'swinv2'

      UpperCAmelCase_      :      List[str]      							=   {
          '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_					,)			->			Optional[Any]:



         '''simple docstring'''



         super().__init__(**__A							)

         UpperCAmelCase__							:				Optional[Any]   				=  image_size
         UpperCAmelCase__							:				List[Any]   				=  patch_size
         UpperCAmelCase__							:				Tuple   				=  num_channels
         UpperCAmelCase__							:				Dict   				=  embed_dim
         UpperCAmelCase__							:				List[Any]   				=  depths
         UpperCAmelCase__							:				Optional[int]   				=  len(__A							)
         UpperCAmelCase__							:				List[str]   				=  num_heads
         UpperCAmelCase__							:				Any   				=  window_size
         UpperCAmelCase__							:				Dict   				=  mlp_ratio
         UpperCAmelCase__							:				List[Any]   				=  qkv_bias
         UpperCAmelCase__							:				List[Any]   				=  hidden_dropout_prob
         UpperCAmelCase__							:				List[str]   				=  attention_probs_dropout_prob
         UpperCAmelCase__							:				Optional[Any]   				=  drop_path_rate
         UpperCAmelCase__							:				Optional[int]   				=  hidden_act
         UpperCAmelCase__							:				List[str]   				=  use_absolute_embeddings
         UpperCAmelCase__							:				Union[str, Any]   				=  layer_norm_eps
         UpperCAmelCase__							:				Optional[Any]   				=  initializer_range
         UpperCAmelCase__							:				str   				=  encoder_stride
         # we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
         # this indicates the channel dimension after the last stage of the model
         UpperCAmelCase__							:				str   				=  int(embed_dim * 2 ** (len(__A							) - 1)							)
         UpperCAmelCase__							:				Dict   				=  (0, 0, 0, 0)




'''simple docstring'''

import re







def __UpperCamelCase(   _A					:				str    ):
   '''simple docstring'''

   if len(re.findall('''[ATCG]'''  ,			_A    )    ) != len(_A    ):
      raise ValueError('''Invalid Strand'''    )

   return dna.translate(dna.maketrans('''ATCG'''  ,			'''TAGC'''    )    )


if __name__ == "__main__":
  import doctest

  doctest.testmod()




