



'''simple docstring'''





import copy

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


lowercase_									=    logging.get_logger(__name__)

lowercase_									=    {
    "ut/deta": "https://huggingface.co/ut/deta/resolve/main/config.json",
}






class __A     (    A		):



 '''simple docstring'''







 __lowerCamelCase       :			Any		=			'deta'
 __lowerCamelCase       :			Tuple		=			{
     'hidden_size': 'd_model',
     'num_attention_heads': 'encoder_attention_heads',
 }



 def __init__(self					,  A=None					,  A=900					,  A=2_048					,  A=6					,  A=2_048					,  A=8					,  A=6					,  A=1_024					,  A=8					,  A=0.0					,  A=True					,  A="relu"					,  A=256					,  A=0.1					,  A=0.0					,  A=0.0					,  A=0.02					,  A=1.0					,  A=True					,  A=False					,  A="sine"					,  A=5					,  A=4					,  A=4					,  A=True					,  A=300					,  A=True					,  A=True					,  A=1					,  A=5					,  A=2					,  A=1					,  A=1					,  A=5					,  A=2					,  A=0.1					,  A=0.25					,  **A					,  )       ->	Optional[int]:


      """simple docstring"""



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

      _a           =    backbone_config
      _a           =    num_queries
      _a           =    max_position_embeddings
      _a           =    d_model
      _a           =    encoder_ffn_dim
      _a           =    encoder_layers
      _a           =    encoder_attention_heads
      _a           =    decoder_ffn_dim
      _a           =    decoder_layers
      _a           =    decoder_attention_heads
      _a           =    dropout
      _a           =    attention_dropout
      _a           =    activation_dropout
      _a           =    activation_function
      _a           =    init_std
      _a           =    init_xavier_std
      _a           =    encoder_layerdrop
      _a           =    auxiliary_loss
      _a           =    position_embedding_type
      # deformable attributes
      _a           =    num_feature_levels
      _a           =    encoder_n_points
      _a           =    decoder_n_points
      _a           =    two_stage
      _a           =    two_stage_num_proposals
      _a           =    with_box_refine
      _a           =    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
      _a           =    class_cost
      _a           =    bbox_cost
      _a           =    giou_cost
      # Loss coefficients
      _a           =    mask_loss_coefficient
      _a           =    dice_loss_coefficient
      _a           =    bbox_loss_coefficient
      _a           =    giou_loss_coefficient
      _a           =    eos_coefficient
      _a           =    focal_alpha
      super().__init__(is_encoder_decoder=A					,  **A			)



 @property
 def    a__    (self			)       ->	int:


      """simple docstring"""



      return self.encoder_attention_heads



 @property
 def    a__    (self			)       ->	int:


      """simple docstring"""



      return self.d_model



 def    a__    (self			)       ->	Union[str, Any]:


      """simple docstring"""



      _a           =    copy.deepcopy(self.__dict__			)
      _a           =    self.backbone_config.to_dict()
      _a           =    self.__class__.model_type
      return output








'''simple docstring'''





def lowerCAmelCase    (__A    ,      __A):



     """simple docstring"""



     if digit_amount > 0:
          return round(number - int(__A)    ,      __A)
     return number - int(__A)


if __name__ == "__main__":
  print(decimal_isolate(1.53, 0))
  print(decimal_isolate(35.345, 1))
  print(decimal_isolate(35.345, 2))
  print(decimal_isolate(35.345, 3))
  print(decimal_isolate(-14.789, 3))
  print(decimal_isolate(0, 2))
  print(decimal_isolate(-14.123, 1))
  print(decimal_isolate(-14.123, 2))
  print(decimal_isolate(-14.123, 3))



