




'''simple docstring'''



from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


lowerCamelCase_			=						logging.get_logger(__name__)







class 		lowercase_   (			A_					,  A_       ):


   """simple docstring"""

   lowerCamelCase_      =						'''maskformer-swin'''

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



   def __init__(   self :     Optional[Any]  ,				__lowerCamelCase :     Union[str, Any]=2_2_4  ,				__lowerCamelCase :     Optional[int]=4  ,				__lowerCamelCase :     Optional[int]=3  ,				__lowerCamelCase :     int=9_6  ,				__lowerCamelCase :     str=[2, 2, 6, 2]  ,				__lowerCamelCase :     Union[str, Any]=[3, 6, 1_2, 2_4]  ,				__lowerCamelCase :     List[str]=7  ,				__lowerCamelCase :     Dict=4.0  ,				__lowerCamelCase :     Tuple=True  ,				__lowerCamelCase :     Any=0.0  ,				__lowerCamelCase :     Dict=0.0  ,				__lowerCamelCase :     Dict=0.1  ,				__lowerCamelCase :     Optional[int]="gelu"  ,				__lowerCamelCase :     Tuple=False  ,				__lowerCamelCase :     Union[str, Any]=0.0_2  ,				__lowerCamelCase :     int=1e-5  ,				__lowerCamelCase :     List[str]=None  ,				__lowerCamelCase :     Any=None  ,				**__lowerCamelCase :     str  ,				) ->    Optional[int]:

      """simple docstring"""
      super().__init__(**_lowerCamelCase   )

      _SCREAMING_SNAKE_CASE	=				image_size
      _SCREAMING_SNAKE_CASE	=				patch_size
      _SCREAMING_SNAKE_CASE	=				num_channels
      _SCREAMING_SNAKE_CASE	=				embed_dim
      _SCREAMING_SNAKE_CASE	=				depths
      _SCREAMING_SNAKE_CASE	=				len(_lowerCamelCase   )
      _SCREAMING_SNAKE_CASE	=				num_heads
      _SCREAMING_SNAKE_CASE	=				window_size
      _SCREAMING_SNAKE_CASE	=				mlp_ratio
      _SCREAMING_SNAKE_CASE	=				qkv_bias
      _SCREAMING_SNAKE_CASE	=				hidden_dropout_prob
      _SCREAMING_SNAKE_CASE	=				attention_probs_dropout_prob
      _SCREAMING_SNAKE_CASE	=				drop_path_rate
      _SCREAMING_SNAKE_CASE	=				hidden_act
      _SCREAMING_SNAKE_CASE	=				use_absolute_embeddings
      _SCREAMING_SNAKE_CASE	=				layer_norm_eps
      _SCREAMING_SNAKE_CASE	=				initializer_range
      # 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
      _SCREAMING_SNAKE_CASE	=				int(embed_dim * 2 ** (len(_lowerCamelCase   ) - 1)   )
      _SCREAMING_SNAKE_CASE	=				["stem"] + [F"""stage{idx}""" for idx in range(1  ,				len(_lowerCamelCase   ) + 1   )]
      _SCREAMING_SNAKE_CASE,	_SCREAMING_SNAKE_CASE	=				get_aligned_output_features_output_indices(
          out_features=_lowerCamelCase  ,				out_indices=_lowerCamelCase  ,				stage_names=self.stage_names   )







'''simple docstring'''



from ...configuration_utils import PretrainedConfig







class 		lowercase_   (			A       ):


   """simple docstring"""

   lowerCamelCase_      =						'''bert-generation'''



   def __init__(   self :     int  ,				__lowerCamelCase :     int=5_0_3_5_8  ,				__lowerCamelCase :     Union[str, Any]=1_0_2_4  ,				__lowerCamelCase :     str=2_4  ,				__lowerCamelCase :     int=1_6  ,				__lowerCamelCase :     Union[str, Any]=4_0_9_6  ,				__lowerCamelCase :     Optional[Any]="gelu"  ,				__lowerCamelCase :     Tuple=0.1  ,				__lowerCamelCase :     str=0.1  ,				__lowerCamelCase :     Optional[Any]=5_1_2  ,				__lowerCamelCase :     List[Any]=0.0_2  ,				__lowerCamelCase :     Union[str, Any]=1e-12  ,				__lowerCamelCase :     List[Any]=0  ,				__lowerCamelCase :     List[Any]=2  ,				__lowerCamelCase :     Dict=1  ,				__lowerCamelCase :     Tuple="absolute"  ,				__lowerCamelCase :     Union[str, Any]=True  ,				**__lowerCamelCase :     Optional[Any]  ,				):

      """simple docstring"""
      super().__init__(pad_token_id=__lowerCamelCase  ,				bos_token_id=__lowerCamelCase  ,				eos_token_id=__lowerCamelCase  ,				**__lowerCamelCase   )

      _SCREAMING_SNAKE_CASE	=				vocab_size
      _SCREAMING_SNAKE_CASE	=				hidden_size
      _SCREAMING_SNAKE_CASE	=				num_hidden_layers
      _SCREAMING_SNAKE_CASE	=				num_attention_heads
      _SCREAMING_SNAKE_CASE	=				hidden_act
      _SCREAMING_SNAKE_CASE	=				intermediate_size
      _SCREAMING_SNAKE_CASE	=				hidden_dropout_prob
      _SCREAMING_SNAKE_CASE	=				attention_probs_dropout_prob
      _SCREAMING_SNAKE_CASE	=				max_position_embeddings
      _SCREAMING_SNAKE_CASE	=				initializer_range
      _SCREAMING_SNAKE_CASE	=				layer_norm_eps
      _SCREAMING_SNAKE_CASE	=				position_embedding_type
      _SCREAMING_SNAKE_CASE	=				use_cache

