






'''simple docstring'''



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


SCREAMING_SNAKE_CASE							=						logging.get_logger(__name__)

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




      """simple docstring"""




      UpperCamelCase_             =      '''swinv2'''

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






      def __init__(			self      :		Tuple  ,   UpperCAmelCase      :		Optional[int]=224  ,   UpperCAmelCase      :		Optional[Any]=4  ,   UpperCAmelCase      :		Union[str, Any]=3  ,   UpperCAmelCase      :		Optional[Any]=96  ,   UpperCAmelCase      :		str=[2, 2, 6, 2]  ,   UpperCAmelCase      :		Union[str, Any]=[3, 6, 12, 24]  ,   UpperCAmelCase      :		int=7  ,   UpperCAmelCase      :		Dict=4.0  ,   UpperCAmelCase      :		Tuple=True  ,   UpperCAmelCase      :		List[Any]=0.0  ,   UpperCAmelCase      :		Dict=0.0  ,   UpperCAmelCase      :		Tuple=0.1  ,   UpperCAmelCase      :		int="gelu"  ,   UpperCAmelCase      :		Optional[int]=False  ,   UpperCAmelCase      :		Dict=0.0_2  ,   UpperCAmelCase      :		Optional[Any]=1e-5  ,   UpperCAmelCase      :		Any=32  ,   **UpperCAmelCase      :		List[Any]  ,   )	->	int:


       '''simple docstring'''

       super().__init__(**UpperCAmelCase		)

       lowercase       : int						=image_size
       lowercase       : Any						=patch_size
       lowercase       : Union[str, Any]						=num_channels
       lowercase       : Optional[Any]						=embed_dim
       lowercase       : Union[str, Any]						=depths
       lowercase       : int						=len(UpperCAmelCase		)
       lowercase       : Union[str, Any]						=num_heads
       lowercase       : str						=window_size
       lowercase       : Optional[int]						=mlp_ratio
       lowercase       : Optional[Any]						=qkv_bias
       lowercase       : Any						=hidden_dropout_prob
       lowercase       : Optional[Any]						=attention_probs_dropout_prob
       lowercase       : Optional[int]						=drop_path_rate
       lowercase       : str						=hidden_act
       lowercase       : Any						=use_absolute_embeddings
       lowercase       : Optional[int]						=layer_norm_eps
       lowercase       : Optional[Any]						=initializer_range
       lowercase       : Dict						=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
       lowercase       : List[Any]						=int(embed_dim * 2 ** (len(UpperCAmelCase		) - 1)		)
       lowercase       : Any						=(0, 0, 0, 0)




from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig


SCREAMING_SNAKE_CASE			:						int				  =		logging.get_logger(__name__)

SCREAMING_SNAKE_CASE			:						Any				  =		"""T5Config"""
class  A_			(							a_			):
  _SCREAMING_SNAKE_CASE     					=      """mt5"""
  _SCREAMING_SNAKE_CASE     					=      MTaConfig
class  A_			(							a_			):
  _SCREAMING_SNAKE_CASE     					=      """mt5"""
  _SCREAMING_SNAKE_CASE     					=      MTaConfig
class  A_			(							a_			):
  _SCREAMING_SNAKE_CASE     					=      """mt5"""
  _SCREAMING_SNAKE_CASE     					=      MTaConfig


