






'''simple docstring'''

import copy

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


SCREAMING_SNAKE_CASE__      =   logging.get_logger(__name__)

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






class 				a_						(			__a				):
  lowercase     		=      '''deta'''
  lowercase     		=      {
      '''hidden_size''': '''d_model''',
      '''num_attention_heads''': '''encoder_attention_heads''',
  }

  def __init__(      self			,		_SCREAMING_SNAKE_CASE=None			,		_SCREAMING_SNAKE_CASE=900			,		_SCREAMING_SNAKE_CASE=2048			,		_SCREAMING_SNAKE_CASE=6			,		_SCREAMING_SNAKE_CASE=2048			,		_SCREAMING_SNAKE_CASE=8			,		_SCREAMING_SNAKE_CASE=6			,		_SCREAMING_SNAKE_CASE=1024			,		_SCREAMING_SNAKE_CASE=8			,		_SCREAMING_SNAKE_CASE=0.0			,		_SCREAMING_SNAKE_CASE=True			,		_SCREAMING_SNAKE_CASE="relu"			,		_SCREAMING_SNAKE_CASE=256			,		_SCREAMING_SNAKE_CASE=0.1			,		_SCREAMING_SNAKE_CASE=0.0			,		_SCREAMING_SNAKE_CASE=0.0			,		_SCREAMING_SNAKE_CASE=0.0_2			,		_SCREAMING_SNAKE_CASE=1.0			,		_SCREAMING_SNAKE_CASE=True			,		_SCREAMING_SNAKE_CASE=False			,		_SCREAMING_SNAKE_CASE="sine"			,		_SCREAMING_SNAKE_CASE=5			,		_SCREAMING_SNAKE_CASE=4			,		_SCREAMING_SNAKE_CASE=4			,		_SCREAMING_SNAKE_CASE=True			,		_SCREAMING_SNAKE_CASE=300			,		_SCREAMING_SNAKE_CASE=True			,		_SCREAMING_SNAKE_CASE=True			,		_SCREAMING_SNAKE_CASE=1			,		_SCREAMING_SNAKE_CASE=5			,		_SCREAMING_SNAKE_CASE=2			,		_SCREAMING_SNAKE_CASE=1			,		_SCREAMING_SNAKE_CASE=1			,		_SCREAMING_SNAKE_CASE=5			,		_SCREAMING_SNAKE_CASE=2			,		_SCREAMING_SNAKE_CASE=0.1			,		_SCREAMING_SNAKE_CASE=0.2_5			,		**_SCREAMING_SNAKE_CASE			,		)  ->      Optional[int]:



        """simple docstring"""






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

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

  @property
  def   A__						(      self      )  ->      Dict:



        """simple docstring"""






        return self.encoder_attention_heads

  @property
  def   A__						(      self      )  ->      Dict:



        """simple docstring"""






        return self.d_model


  def   A__						(      self      )  ->      int:



        """simple docstring"""






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


"""simple docstring"""





from ..utils import DummyObject, requires_backends
class 						SCREAMING_SNAKE_CASE_ (						metaclass=__a ):




		"""simple docstring"""





		__lowercase							:  Tuple						   =		['''keras_nlp''']




		def __init__(     self							,  *lowerCAmelCase__							,  **lowerCAmelCase__):
				requires_backends(self							,  ["""keras_nlp"""])




