





"""simple docstring"""
import copy

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


__UpperCamelCase     :						Any						       =  logging.get_logger(__name__)

__UpperCamelCase     :						Optional[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       a							(   a__  ):
 snake_case__             =       '''dpt'''



 def __init__(     self				,       _snake_case=7_68				,       _snake_case=12				,       _snake_case=12				,       _snake_case=30_72				,       _snake_case="gelu"				,       _snake_case=0.0				,       _snake_case=0.0				,       _snake_case=0.02				,       _snake_case=1E-12				,       _snake_case=3_84				,       _snake_case=16				,       _snake_case=3				,       _snake_case=False				,       _snake_case=True				,       _snake_case=[2, 5, 8, 11]				,       _snake_case="project"				,       _snake_case=[4, 2, 1, 0.5]				,       _snake_case=[96, 1_92, 3_84, 7_68]				,       _snake_case=2_56				,       _snake_case=-1				,       _snake_case=False				,       _snake_case=True				,       _snake_case=0.4				,       _snake_case=2_55				,       _snake_case=0.1				,       _snake_case=[1, 10_24, 24, 24]				,       _snake_case=[0, 1]				,       _snake_case=None				,       **_snake_case				,       ):







  """simple docstring"""






  super().__init__(**_snake_case     )

  lowerCAmelCase    				= hidden_size
  lowerCAmelCase    				= is_hybrid

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

   lowerCAmelCase    				= backbone_featmap_shape
   lowerCAmelCase    				= neck_ignore_stages

   if readout_type != "project":
    raise ValueError('Readout type must be \'project\' when using `DPT-hybrid` mode.'     )
  else:
   lowerCAmelCase    				= None
   lowerCAmelCase    				= None
   lowerCAmelCase    				= []

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



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  lowerCAmelCase    				= copy.deepcopy(self.__dict__     )

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

  lowerCAmelCase    				= self.__class__.model_type
  return output













from __future__ import annotations


def 				__lowerCamelCase     (							__lowerCAmelCase							:					str					,							__lowerCAmelCase							:					Tuple					,							__lowerCAmelCase							:					int					,							__lowerCAmelCase							:					Tuple							)     ->  Optional[Any]:  # noqa: E741
   while r - l > 1:
      __UpperCamelCase	:			int					=					(l + r) // 2
      if v[m] >= key:
         __UpperCamelCase	:			Dict					=					m
      else:
         __UpperCamelCase	:			Optional[Any]					=					m  # noqa: E741
   return r


def 				__lowerCamelCase     (							__lowerCAmelCase							:					list[int]							)     ->  int:
   if len(__lowerCAmelCase							) == 0:
      return 0

   __UpperCamelCase	:			Optional[Any]					=					[0] * len(__lowerCAmelCase							)
   __UpperCamelCase	:			Optional[int]					=					1

   __UpperCamelCase	:			Union[str, Any]					=					v[0]

   for i in range(1					,							len(__lowerCAmelCase							)							):
      if v[i] < tail[0]:
         __UpperCamelCase	:			Dict					=					v[i]
      elif v[i] > tail[length - 1]:
         __UpperCamelCase	:			Optional[int]					=					v[i]
         length += 1
      else:
         __UpperCamelCase	:			List[Any]					=					v[i]

   return length


if __name__ == "__main__":
       import doctest

       doctest.testmod()



