

"""simple docstring"""




import copy

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


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

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


class 		_A       (			__a					):
      __a								=	'deta'
      __a								=	{
          '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__=0.02    ,						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__=0.25    ,						**SCREAMING_SNAKE_CASE__    ,						)   ->					Tuple:
         if backbone_config is None:
            logger.info("`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."		)
            lowerCamelCase__						=			CONFIG_MAPPING["resnet"](out_features=["stage2", "stage3", "stage4"]		)
         else:
            if isinstance(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__		):
               lowerCamelCase__						=			backbone_config.pop("model_type"		)
               lowerCamelCase__						=			CONFIG_MAPPING[backbone_model_type]
               lowerCamelCase__						=			config_class.from_dict(SCREAMING_SNAKE_CASE__		)

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





      @property
      def 					_lowerCamelCase  (  self		)   ->					int:
         return self.encoder_attention_heads





      @property
      def 					_lowerCamelCase  (  self		)   ->					int:
         return self.d_model





      def 					_lowerCamelCase  (  self		)   ->					str:
         lowerCamelCase__						=			copy.deepcopy(self.__dict__		)
         lowerCamelCase__						=			self.backbone_config.to_dict()
         lowerCamelCase__						=			self.__class__.model_type
         return output







"""simple docstring"""




import copy

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


SCREAMING_SNAKE_CASE_     :			Dict	  =			logging.get_logger(__name__)


class 		_A       (			__a					):
      __a								=	'encoder-decoder'
      __a								=	True





      def __init__(  self    ,						**SCREAMING_SNAKE_CASE__		)   ->					Optional[int]:
         super().__init__(**SCREAMING_SNAKE_CASE__		)
         assert (
             "encoder" in kwargs and "decoder" in kwargs
         ), "Config has to be initialized with encoder and decoder config"
         lowerCamelCase__						=			kwargs.pop("encoder"		)
         lowerCamelCase__						=			encoder_config.pop("model_type"		)
         lowerCamelCase__						=			kwargs.pop("decoder"		)
         lowerCamelCase__						=			decoder_config.pop("model_type"		)

         from ..auto.configuration_auto import AutoConfig

         lowerCamelCase__						=			AutoConfig.for_model(SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__		)
         lowerCamelCase__						=			AutoConfig.for_model(SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__		)
         lowerCamelCase__						=			True





      @classmethod
      def 					_lowerCamelCase  (  cls    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__		)   ->					PretrainedConfig:
         logger.info("Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config"		)
         lowerCamelCase__						=			True
         lowerCamelCase__						=			True

         return cls(encoder=encoder_config.to_dict()    ,						decoder=decoder_config.to_dict()    ,						**SCREAMING_SNAKE_CASE__		)





      def 					_lowerCamelCase  (  self		)   ->					int:
         lowerCamelCase__						=			copy.deepcopy(self.__dict__		)
         lowerCamelCase__						=			self.encoder.to_dict()
         lowerCamelCase__						=			self.decoder.to_dict()
         lowerCamelCase__						=			self.__class__.model_type
         return output




