


import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig


snake_case    :   Any	    =					logging.get_logger(__name__)

snake_case    :   List[Any]	    =					{
    '''Intel/dpt-large''': '''https://huggingface.co/Intel/dpt-large/resolve/main/config.json''',
    # See all DPT models at https://huggingface.co/models?filter=dpt
}







class 		_snake_case  (				lowerCamelCase_							):
 SCREAMING_SNAKE_CASE__				=	"""dpt"""




 def __init__(		self ,  _lowerCamelCase=768 ,  _lowerCamelCase=12 ,  _lowerCamelCase=12 ,  _lowerCamelCase=3072 ,  _lowerCamelCase="gelu" ,  _lowerCamelCase=0.0 ,  _lowerCamelCase=0.0 ,  _lowerCamelCase=0.02 ,  _lowerCamelCase=1e-12 ,  _lowerCamelCase=384 ,  _lowerCamelCase=16 ,  _lowerCamelCase=3 ,  _lowerCamelCase=False ,  _lowerCamelCase=True ,  _lowerCamelCase=[2, 5, 8, 11] ,  _lowerCamelCase="project" ,  _lowerCamelCase=[4, 2, 1, 0.5] ,  _lowerCamelCase=[96, 192, 384, 768] ,  _lowerCamelCase=256 ,  _lowerCamelCase=-1 ,  _lowerCamelCase=False ,  _lowerCamelCase=True ,  _lowerCamelCase=0.4 ,  _lowerCamelCase=255 ,  _lowerCamelCase=0.1 ,  _lowerCamelCase=[1, 1024, 24, 24] ,  _lowerCamelCase=[0, 1] ,  _lowerCamelCase=None ,  **_lowerCamelCase ,  ):
       super().__init__(**_UpperCAmelCase   )

       a						:str										=	hidden_size
       a						:Optional[Any]										=	is_hybrid

       if self.is_hybrid:
             if backbone_config is None:
                   logger.info('''Initializing the config with a `BiT` backbone.'''   )
                   a						:Union[str, Any]										=	{
                       '''global_padding''': '''same''',
                       '''layer_type''': '''bottleneck''',
                       '''depths''': [3, 4, 9],
                       '''out_features''': ['''stage1''', '''stage2''', '''stage3'''],
                       '''embedding_dynamic_padding''': True,
                   }
                   a						:Tuple										=	BitConfig(**_UpperCAmelCase   )
             elif isinstance(_UpperCAmelCase ,  _UpperCAmelCase   ):
                   logger.info('''Initializing the config with a `BiT` backbone.'''   )
                   a						:Any										=	BitConfig(**_UpperCAmelCase   )
             elif isinstance(_UpperCAmelCase ,  _UpperCAmelCase   ):
                   a						:int										=	backbone_config
             else:
                   raise ValueError(
                       F'''backbone_config must be a dictionary or a `PretrainedConfig`, got {backbone_config.__class__}.'''   )

             a						:int										=	backbone_featmap_shape
             a						:Optional[Any]										=	neck_ignore_stages

             if readout_type != "project":
                   raise ValueError('''Readout type must be \'project\' when using `DPT-hybrid` mode.'''   )
       else:
             a						:Union[str, Any]										=	None
             a						:List[str]										=	None
             a						:Tuple										=	[]

       a						:Optional[int]										=	num_hidden_layers
       a						:List[Any]										=	num_attention_heads
       a						:List[str]										=	intermediate_size
       a						:Optional[Any]										=	hidden_act
       a						:int										=	hidden_dropout_prob
       a						:int										=	attention_probs_dropout_prob
       a						:Any										=	initializer_range
       a						:Union[str, Any]										=	layer_norm_eps
       a						:List[Any]										=	image_size
       a						:Any										=	patch_size
       a						:str										=	num_channels
       a						:Tuple										=	qkv_bias
       a						:int										=	backbone_out_indices
       if readout_type not in ["ignore", "add", "project"]:
             raise ValueError('''Readout_type must be one of [\'ignore\', \'add\', \'project\']'''   )
       a						:Tuple										=	readout_type
       a						:List[str]										=	reassemble_factors
       a						:int										=	neck_hidden_sizes
       a						:Union[str, Any]										=	fusion_hidden_size
       a						:Optional[Any]										=	head_in_index
       a						:Optional[int]										=	use_batch_norm_in_fusion_residual
       # auxiliary head attributes (semantic segmentation)
       a						:Optional[int]										=	use_auxiliary_head
       a						:Union[str, Any]										=	auxiliary_loss_weight
       a						:Tuple										=	semantic_loss_ignore_index
       a						:Any										=	semantic_classifier_dropout




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       a						:int										=	copy.deepcopy(self.__dict__   )

       if output["backbone_config"] is not None:
             a						:List[Any]										=	self.backbone_config.to_dict()

       a						:Dict										=	self.__class__.model_type
       return output









def     __lowerCamelCase						(			UpperCAmelCase_						:		int						):




      """simple docstring"""





      if not isinstance(UpperCAmelCase_			,  UpperCAmelCase_						):
            raise TypeError('''Input value must be an \'int\' type'''						)

      a						:Optional[int]										=	0
      while number:
            position += 1
            number >>= 1

      return position


if __name__ == "__main__":
     import doctest

     doctest.testmod()





