



'''simple docstring'''





from ...configuration_utils import PretrainedConfig
from ...utils import logging


A__    :   List[Any]           =					logging.get_logger(__name__)

A__    :   Optional[Any]           =					{
    '''vinvino02/glpn-kitti''': '''https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json''',
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}



class  snake_case__						(    SCREAMING_SNAKE_CASE_				):
 A__				= '''glpn'''
 def __init__(   self						:							Union[str, Any]      ,     __a						:							List[str]=3      ,     __a						:							Dict=4      ,     __a						:							Tuple=[2, 2, 2, 2]      ,     __a						:							int=[8, 4, 2, 1]      ,     __a						:							Tuple=[32, 64, 160, 256]      ,     __a						:							Optional[int]=[7, 3, 3, 3]      ,     __a						:							Dict=[4, 2, 2, 2]      ,     __a						:							List[str]=[1, 2, 5, 8]      ,     __a						:							int=[4, 4, 4, 4]      ,     __a						:							int="gelu"      ,     __a						:							Optional[Any]=0.0      ,     __a						:							Optional[Any]=0.0      ,     __a						:							List[Any]=0.0_2      ,     __a						:							Any=0.1      ,     __a						:							Tuple=1e-6      ,     __a						:							Union[str, Any]=64      ,     __a						:							Any=10      ,     __a						:							Optional[Any]=-1      ,     **__a						:							Union[str, Any]      ,     )      ->   List[str]:







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

       __snake_case :   Dict													=    num_channels
       __snake_case :   List[Any]													=    num_encoder_blocks
       __snake_case :   Optional[int]													=    depths
       __snake_case :   Optional[int]													=    sr_ratios
       __snake_case :   List[Any]													=    hidden_sizes
       __snake_case :   Any													=    patch_sizes
       __snake_case :   List[str]													=    strides
       __snake_case :   Dict													=    mlp_ratios
       __snake_case :   Dict													=    num_attention_heads
       __snake_case :   Optional[int]													=    hidden_act
       __snake_case :   Optional[Any]													=    hidden_dropout_prob
       __snake_case :   List[Any]													=    attention_probs_dropout_prob
       __snake_case :   Tuple													=    initializer_range
       __snake_case :   List[str]													=    drop_path_rate
       __snake_case :   List[Any]													=    layer_norm_eps
       __snake_case :   Union[str, Any]													=    decoder_hidden_size
       __snake_case :   str													=    max_depth
       __snake_case :   Union[str, Any]													=    head_in_index








'''simple docstring'''





import functools





def   a_   (		_UpperCAmelCase    :      list[int] ,_UpperCAmelCase    :      list[int]				)    ->  int:

      # Validation
      if not isinstance(_UpperCAmelCase ,_UpperCAmelCase				) or not all(isinstance(_UpperCAmelCase ,_UpperCAmelCase				) for day in days				):
            raise ValueError('The parameter days should be a list of integers'				)

      if len(_UpperCAmelCase				) != 3 or not all(isinstance(_UpperCAmelCase ,_UpperCAmelCase				) for cost in costs				):
            raise ValueError('The parameter costs should be a list of three integers'				)

      if len(_UpperCAmelCase				) == 0:
            return 0

      if min(_UpperCAmelCase				) <= 0:
            raise ValueError('All days elements should be greater than 0'				)

      if max(_UpperCAmelCase				) >= 3_66:
            raise ValueError('All days elements should be less than 366'				)

      __snake_case :   str													=    set(_UpperCAmelCase				)

      @functools.cache
      def dynamic_programming(_UpperCAmelCase    :      int				) -> int:
            if index > 3_65:
                  return 0

            if index not in days_set:
                  return dynamic_programming(index + 1				)

            return min(
                costs[0] + dynamic_programming(index + 1				) ,costs[1] + dynamic_programming(index + 7				) ,costs[2] + dynamic_programming(index + 30				) ,)

      return dynamic_programming(1				)


if __name__ == "__main__":
    import doctest

    doctest.testmod()



