






import copy

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


SCREAMING_SNAKE_CASE__											=     logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__											=     {
    '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_		(    lowerCamelCase       ):
  lowercase  	=   """dpt"""

  def __init__(   self    ,	_SCREAMING_SNAKE_CASE=768    ,	_SCREAMING_SNAKE_CASE=12    ,	_SCREAMING_SNAKE_CASE=12    ,	_SCREAMING_SNAKE_CASE=3072    ,	_SCREAMING_SNAKE_CASE="gelu"    ,	_SCREAMING_SNAKE_CASE=0.0    ,	_SCREAMING_SNAKE_CASE=0.0    ,	_SCREAMING_SNAKE_CASE=0.0_2    ,	_SCREAMING_SNAKE_CASE=1e-12    ,	_SCREAMING_SNAKE_CASE=384    ,	_SCREAMING_SNAKE_CASE=16    ,	_SCREAMING_SNAKE_CASE=3    ,	_SCREAMING_SNAKE_CASE=False    ,	_SCREAMING_SNAKE_CASE=True    ,	_SCREAMING_SNAKE_CASE=[2, 5, 8, 11]    ,	_SCREAMING_SNAKE_CASE="project"    ,	_SCREAMING_SNAKE_CASE=[4, 2, 1, 0.5]    ,	_SCREAMING_SNAKE_CASE=[96, 192, 384, 768]    ,	_SCREAMING_SNAKE_CASE=256    ,	_SCREAMING_SNAKE_CASE=-1    ,	_SCREAMING_SNAKE_CASE=False    ,	_SCREAMING_SNAKE_CASE=True    ,	_SCREAMING_SNAKE_CASE=0.4    ,	_SCREAMING_SNAKE_CASE=255    ,	_SCREAMING_SNAKE_CASE=0.1    ,	_SCREAMING_SNAKE_CASE=[1, 1024, 24, 24]    ,	_SCREAMING_SNAKE_CASE=[0, 1]    ,	_SCREAMING_SNAKE_CASE=None    ,	**_SCREAMING_SNAKE_CASE    ,	)						->   str:



        """simple docstring"""






        super().__init__(**_SCREAMING_SNAKE_CASE   )

        UpperCamelCase       						=      hidden_size
        UpperCamelCase       						=      is_hybrid

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

              UpperCamelCase       						=      backbone_featmap_shape
              UpperCamelCase       						=      neck_ignore_stages

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

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


  def 						A__		(   self   )						->   Dict:



        """simple docstring"""






        UpperCamelCase       						=      copy.deepcopy(self.__dict__   )

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

        UpperCamelCase       						=      self.__class__.model_type
        return output








'''simple docstring'''

from __future__ import annotations







def 					lowercase__				(   __UpperCamelCase	,		__UpperCamelCase	,		__UpperCamelCase					)->				tuple[float, list[float]]:
      UpperCamelCase       						=      list(range(len(__UpperCamelCase					)					)					)
      UpperCamelCase       						=      [v / w for v, w in zip(__UpperCamelCase	,		__UpperCamelCase					)]
      index.sort(key=lambda __UpperCamelCase					: ratio[i]	,		reverse=__UpperCamelCase					)

      UpperCamelCase       						=      0
      UpperCamelCase       						=      [0] * len(__UpperCamelCase					)
      for i in index:
            if weight[i] <= capacity:
                  UpperCamelCase       						=      1
                  max_value += value[i]
                  capacity -= weight[i]
            else:
                  UpperCamelCase       						=      capacity / weight[i]
                  max_value += value[i] * capacity / weight[i]
                  break

      return max_value, fractions


if __name__ == "__main__":
     import doctest

     doctest.testmod()
