






import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


lowerCamelCase     :							Tuple    =logging.get_logger(__name__)

lowerCamelCase     :							Dict    ={
    '''ut/deta''': '''https://huggingface.co/ut/deta/resolve/main/config.json''',
}





class       __a  (   __lowercase	):
 _lowerCAmelCase	:	Optional[int]				=			'''deta'''
 _lowerCAmelCase	:	Optional[Any]				=			{
     '''hidden_size''': '''d_model''',
     '''num_attention_heads''': '''encoder_attention_heads''',
 }







 def __init__(		self :       Optional[int]							,       SCREAMING_SNAKE_CASE :       List[str]=None							,       SCREAMING_SNAKE_CASE :       str=9_00							,       SCREAMING_SNAKE_CASE :       str=20_48							,       SCREAMING_SNAKE_CASE :       Optional[int]=6							,       SCREAMING_SNAKE_CASE :       Tuple=20_48							,       SCREAMING_SNAKE_CASE :       Any=8							,       SCREAMING_SNAKE_CASE :       Tuple=6							,       SCREAMING_SNAKE_CASE :       str=10_24							,       SCREAMING_SNAKE_CASE :       List[Any]=8							,       SCREAMING_SNAKE_CASE :       Optional[Any]=0.0							,       SCREAMING_SNAKE_CASE :       List[Any]=True							,       SCREAMING_SNAKE_CASE :       Optional[Any]="relu"							,       SCREAMING_SNAKE_CASE :       Any=2_56							,       SCREAMING_SNAKE_CASE :       Optional[Any]=0.1							,       SCREAMING_SNAKE_CASE :       Dict=0.0							,       SCREAMING_SNAKE_CASE :       Dict=0.0							,       SCREAMING_SNAKE_CASE :       Any=0.0_2							,       SCREAMING_SNAKE_CASE :       Union[str, Any]=1.0							,       SCREAMING_SNAKE_CASE :       Optional[int]=True							,       SCREAMING_SNAKE_CASE :       Optional[int]=False							,       SCREAMING_SNAKE_CASE :       Tuple="sine"							,       SCREAMING_SNAKE_CASE :       Any=5							,       SCREAMING_SNAKE_CASE :       Any=4							,       SCREAMING_SNAKE_CASE :       Tuple=4							,       SCREAMING_SNAKE_CASE :       List[Any]=True							,       SCREAMING_SNAKE_CASE :       int=3_00							,       SCREAMING_SNAKE_CASE :       int=True							,       SCREAMING_SNAKE_CASE :       Tuple=True							,       SCREAMING_SNAKE_CASE :       Optional[Any]=1							,       SCREAMING_SNAKE_CASE :       str=5							,       SCREAMING_SNAKE_CASE :       List[Any]=2							,       SCREAMING_SNAKE_CASE :       List[Any]=1							,       SCREAMING_SNAKE_CASE :       Union[str, Any]=1							,       SCREAMING_SNAKE_CASE :       Optional[Any]=5							,       SCREAMING_SNAKE_CASE :       Optional[Any]=2							,       SCREAMING_SNAKE_CASE :       Tuple=0.1							,       SCREAMING_SNAKE_CASE :       Dict=0.2_5							,       **SCREAMING_SNAKE_CASE :       str							,       ):


      '''simple docstring'''






      if backbone_config is None:
           logger.info("`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."						)
           UpperCamelCase__      :       List[Any]	    =  CONFIG_MAPPING["resnet"](out_features=["stage2", "stage3", "stage4"]						)
      else:
           if isinstance(_a							,       _a						):
                UpperCamelCase__      :       Any	    =  backbone_config.pop("model_type"						)
                UpperCamelCase__      :       str	    =  CONFIG_MAPPING[backbone_model_type]
                UpperCamelCase__      :       Tuple	    =  config_class.from_dict(_a						)

      UpperCamelCase__      :       Dict	    =  backbone_config
      UpperCamelCase__      :       Optional[int]	    =  num_queries
      UpperCamelCase__      :       List[Any]	    =  max_position_embeddings
      UpperCamelCase__      :       Union[str, Any]	    =  d_model
      UpperCamelCase__      :       Tuple	    =  encoder_ffn_dim
      UpperCamelCase__      :       str	    =  encoder_layers
      UpperCamelCase__      :       List[str]	    =  encoder_attention_heads
      UpperCamelCase__      :       str	    =  decoder_ffn_dim
      UpperCamelCase__      :       int	    =  decoder_layers
      UpperCamelCase__      :       Optional[int]	    =  decoder_attention_heads
      UpperCamelCase__      :       Optional[Any]	    =  dropout
      UpperCamelCase__      :       Union[str, Any]	    =  attention_dropout
      UpperCamelCase__      :       int	    =  activation_dropout
      UpperCamelCase__      :       Tuple	    =  activation_function
      UpperCamelCase__      :       int	    =  init_std
      UpperCamelCase__      :       Optional[int]	    =  init_xavier_std
      UpperCamelCase__      :       Union[str, Any]	    =  encoder_layerdrop
      UpperCamelCase__      :       Optional[Any]	    =  auxiliary_loss
      UpperCamelCase__      :       Union[str, Any]	    =  position_embedding_type
      # deformable attributes
      UpperCamelCase__      :       List[str]	    =  num_feature_levels
      UpperCamelCase__      :       Tuple	    =  encoder_n_points
      UpperCamelCase__      :       List[str]	    =  decoder_n_points
      UpperCamelCase__      :       Tuple	    =  two_stage
      UpperCamelCase__      :       Dict	    =  two_stage_num_proposals
      UpperCamelCase__      :       List[str]	    =  with_box_refine
      UpperCamelCase__      :       Optional[int]	    =  assign_first_stage
      if two_stage is True and with_box_refine is False:
           raise ValueError("If two_stage is True, with_box_refine must be True."						)
      # Hungarian matcher
      UpperCamelCase__      :       List[Any]	    =  class_cost
      UpperCamelCase__      :       Optional[int]	    =  bbox_cost
      UpperCamelCase__      :       List[str]	    =  giou_cost
      # Loss coefficients
      UpperCamelCase__      :       Tuple	    =  mask_loss_coefficient
      UpperCamelCase__      :       str	    =  dice_loss_coefficient
      UpperCamelCase__      :       Union[str, Any]	    =  bbox_loss_coefficient
      UpperCamelCase__      :       int	    =  giou_loss_coefficient
      UpperCamelCase__      :       List[Any]	    =  eos_coefficient
      UpperCamelCase__      :       Any	    =  focal_alpha
      super().__init__(is_encoder_decoder=_a							,       **_a						)







 @property
 def  __lowercase (		self :       int						):


      '''simple docstring'''






      return self.encoder_attention_heads







 @property
 def  __lowercase (		self :       Any						):


      '''simple docstring'''






      return self.d_model







 def  __lowercase (		self :       Dict						):


      '''simple docstring'''






      UpperCamelCase__      :       List[str]	    =  copy.deepcopy(self.__dict__						)
      UpperCamelCase__      :       Dict	    =  self.backbone_config.to_dict()
      UpperCamelCase__      :       str	    =  self.__class__.model_type
      return output











def 		SCREAMING_SNAKE_CASE							( __lowerCAmelCase ,   __lowerCAmelCase      )			->     Any:
     # "extended trapezoidal rule"
     # int(f) = dx/2 * (f1 + 2f2 + ... + fn)
     UpperCamelCase__      :       int	    =  (boundary[1] - boundary[0]) / steps
     UpperCamelCase__      :       Optional[Any]	    =  boundary[0]
     UpperCamelCase__      :       List[Any]	    =  boundary[1]
     UpperCamelCase__      :       List[Any]	    =  make_points(__lowerCAmelCase ,   __lowerCAmelCase ,   __lowerCAmelCase      )
     UpperCamelCase__      :       int	    =  0.0
     y += (h / 2.0) * f(__lowerCAmelCase      )
     for i in x_i:
          # print(i)
          y += h * f(__lowerCAmelCase      )
     y += (h / 2.0) * f(__lowerCAmelCase      )
     return y







def 		SCREAMING_SNAKE_CASE							( __lowerCAmelCase ,   __lowerCAmelCase ,   __lowerCAmelCase      )			->     List[str]:
     UpperCamelCase__      :       Optional[int]	    =  a + h
     while x < (b - h):
          yield x
          UpperCamelCase__      :       Union[str, Any]	    =  x + h







def 		SCREAMING_SNAKE_CASE							( __lowerCAmelCase      )			->     Any:  # enter your function here
     UpperCamelCase__      :       Dict	    =  (x - 0) * (x - 0)
     return y







def 		SCREAMING_SNAKE_CASE							( )			->     Dict:
     UpperCamelCase__      :       List[Any]	    =  0.0  # Lower bound of integration
     UpperCamelCase__      :       Tuple	    =  1.0  # Upper bound of integration
     UpperCamelCase__      :       Any	    =  1_0.0  # define number of steps or resolution
     UpperCamelCase__      :       List[str]	    =  [a, b]  # define boundary of integration
     UpperCamelCase__      :       Any	    =  method_a(__lowerCAmelCase ,   __lowerCAmelCase      )
     print(f'y = {y}'      )


if __name__ == "__main__":
 main()