


'''simple docstring'''






import copy

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


lowercase							=logging.get_logger(__name__)

lowercase							={
    '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  __magic_name__							(		lowerCAmelCase    ):
       UpperCAmelCase										="dpt"






       def __init__(      self  ,							snake_case=7_6_8  ,							snake_case=1_2  ,							snake_case=1_2  ,							snake_case=3_0_7_2  ,							snake_case="gelu"  ,							snake_case=0.0  ,							snake_case=0.0  ,							snake_case=0.02  ,							snake_case=1E-1_2  ,							snake_case=3_8_4  ,							snake_case=1_6  ,							snake_case=3  ,							snake_case=False  ,							snake_case=True  ,							snake_case=[2, 5, 8, 1_1]  ,							snake_case="project"  ,							snake_case=[4, 2, 1, 0.5]  ,							snake_case=[9_6, 1_9_2, 3_8_4, 7_6_8]  ,							snake_case=2_5_6  ,							snake_case=-1  ,							snake_case=False  ,							snake_case=True  ,							snake_case=0.4  ,							snake_case=2_5_5  ,							snake_case=0.1  ,							snake_case=[1, 1_0_2_4, 2_4, 2_4]  ,							snake_case=[0, 1]  ,							snake_case=None  ,							**snake_case  ,							)						->  List[Any]:




          '''simple docstring'''
          super().__init__(**snake_case)

          _UpperCAmelCase       :       Any							   =hidden_size
          _UpperCAmelCase       :       Union[str, Any]							   =is_hybrid

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

             _UpperCAmelCase       :       Optional[Any]							   =backbone_featmap_shape
             _UpperCAmelCase       :       str							   =neck_ignore_stages

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

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






       def       lowerCAmelCase		(      self)						->  List[Any]:




          '''simple docstring'''
          _UpperCAmelCase       :       Optional[Any]							   =copy.deepcopy(self.__dict__)

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

          _UpperCAmelCase       :       str							   =self.__class__.model_type
          return output





'''simple docstring'''






from typing import Any





def lowerCamelCase__      (						__lowerCamelCase	:							list	,   __lowerCamelCase	:							list	,   __lowerCamelCase	:							dict	,   __lowerCamelCase	:							dict	,   __lowerCamelCase	:							dict	,   ):







   '''simple docstring'''




   _validation(
       __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   )
   # Creates data structures and fill initial step
   _UpperCAmelCase       :       dict							   ={}
   _UpperCAmelCase       :       dict							   ={}
   for state in states_space:
      _UpperCAmelCase       :       int							   =observations_space[0]
      _UpperCAmelCase       :       int							   =(
          initial_probabilities[state] * emission_probabilities[state][observation]
      )
      _UpperCAmelCase       :       int							   =None

   # Fills the data structure with the probabilities of
   # different transitions and pointers to previous states
   for o in range(1	,   len(__lowerCamelCase							)							):
      _UpperCAmelCase       :       List[Any]							   =observations_space[o]
      _UpperCAmelCase       :       Optional[int]							   =observations_space[o - 1]
      for state in states_space:
         # Calculates the argmax for probability function
         _UpperCAmelCase       :       List[str]							   =''
         _UpperCAmelCase       :       Dict							   =-1
         for k_state in states_space:
            _UpperCAmelCase       :       List[str]							   =(
                probabilities[(k_state, prior_observation)]
                * transition_probabilities[k_state][state]
                * emission_probabilities[state][observation]
            )
            if probability > max_probability:
               _UpperCAmelCase       :       int							   =probability
               _UpperCAmelCase       :       List[Any]							   =k_state

            # Update probabilities and pointers dicts
         _UpperCAmelCase       :       str							   =(
             probabilities[(arg_max, prior_observation)]
             * transition_probabilities[arg_max][state]
             * emission_probabilities[state][observation]
         )

         _UpperCAmelCase       :       List[Any]							   =arg_max

    # The final observation
   _UpperCAmelCase       :       int							   =observations_space[len(__lowerCamelCase							) - 1]

   # argmax for given final observation
   _UpperCAmelCase       :       Any							   =''
   _UpperCAmelCase       :       Union[str, Any]							   =-1
   for k_state in states_space:
      _UpperCAmelCase       :       Optional[int]							   =probabilities[(k_state, final_observation)]
      if probability > max_probability:
         _UpperCAmelCase       :       Union[str, Any]							   =probability
         _UpperCAmelCase       :       int							   =k_state
   _UpperCAmelCase       :       int							   =arg_max

   # Process pointers backwards
   _UpperCAmelCase       :       List[str]							   =last_state
   _UpperCAmelCase       :       Optional[int]							   =[]
   for o in range(len(__lowerCamelCase							) - 1	,   -1	,   -1							):
      result.append(__lowerCamelCase							)
      _UpperCAmelCase       :       Optional[Any]							   =pointers[previous, observations_space[o]]
   result.reverse()

   return result





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   ):







   '''simple docstring'''




   _validate_not_empty(
       __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   )
   _validate_lists(__lowerCamelCase	,   __lowerCamelCase							)
   _validate_dicts(
       __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   ):







   '''simple docstring'''




   if not all(
       [
           observations_space,
           states_space,
           initial_probabilities,
           transition_probabilities,
           emission_probabilities,
       ]							):
      raise ValueError('There\'s an empty parameter'							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any							):







   '''simple docstring'''




   _validate_list(__lowerCamelCase	,   'observations_space'							)
   _validate_list(__lowerCamelCase	,   'states_space'							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							str							):







   '''simple docstring'''




   if not isinstance(_object	,   __lowerCamelCase							):
      _UpperCAmelCase       :       Any							   =f"{var_name} must be a list"
      raise ValueError(__lowerCamelCase							)
   else:
      for x in _object:
         if not isinstance(__lowerCamelCase	,   __lowerCamelCase							):
            _UpperCAmelCase       :       Optional[int]							   =f"{var_name} must be a list of strings"
            raise ValueError(__lowerCamelCase							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   ):







   '''simple docstring'''




   _validate_dict(__lowerCamelCase	,   'initial_probabilities'	,   __lowerCamelCase							)
   _validate_nested_dict(__lowerCamelCase	,   'transition_probabilities'							)
   _validate_nested_dict(__lowerCamelCase	,   'emission_probabilities'							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							str							):







   '''simple docstring'''




   _validate_dict(_object	,   __lowerCamelCase	,   __lowerCamelCase							)
   for x in _object.values():
      _validate_dict(__lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							str	,   __lowerCamelCase	:							type	,   __lowerCamelCase	:							bool = False							):







   '''simple docstring'''




   if not isinstance(_object	,   __lowerCamelCase							):
      _UpperCAmelCase       :       List[str]							   =f"{var_name} must be a dict"
      raise ValueError(__lowerCamelCase							)
   if not all(isinstance(__lowerCamelCase	,   __lowerCamelCase							) for x in _object							):
      _UpperCAmelCase       :       str							   =f"{var_name} all keys must be strings"
      raise ValueError(__lowerCamelCase							)
   if not all(isinstance(__lowerCamelCase	,   __lowerCamelCase							) for x in _object.values()							):
      _UpperCAmelCase       :       int							   ='nested dictionary ' if nested else ''
      _UpperCAmelCase       :       Optional[int]							   =f"{var_name} {nested_text}all values must be {value_type.__name__}"
      raise ValueError(__lowerCamelCase							)


if __name__ == "__main__":
 from doctest import testmod

 testmod()

