

"""simple docstring"""






import copy

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


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

_lowercase				:				List[str]   		=		{
    "ut/deta": "https://huggingface.co/ut/deta/resolve/main/config.json",
}

class  __SCREAMING_SNAKE_CASE			(   lowerCAmelCase_     ):


					'''simple docstring'''





					_a         =							'deta'
					_a         =							{
					    'hidden_size': 'd_model',
					    'num_attention_heads': 'encoder_attention_heads',
					}



					def __init__( self							:						Dict,						lowerCamelCase							:						Optional[Any]=None,						lowerCamelCase							:						int=900,						lowerCamelCase							:						Dict=2048,						lowerCamelCase							:						Optional[Any]=6,						lowerCamelCase							:						Any=2048,						lowerCamelCase							:						Tuple=8,						lowerCamelCase							:						Optional[int]=6,						lowerCamelCase							:						Union[str, Any]=1024,						lowerCamelCase							:						str=8,						lowerCamelCase							:						int=0.0,						lowerCamelCase							:						Union[str, Any]=True,						lowerCamelCase							:						Tuple="relu",						lowerCamelCase							:						Optional[Any]=256,						lowerCamelCase							:						Union[str, Any]=0.1,						lowerCamelCase							:						Union[str, Any]=0.0,						lowerCamelCase							:						Optional[Any]=0.0,						lowerCamelCase							:						Union[str, Any]=0.02,						lowerCamelCase							:						List[str]=1.0,						lowerCamelCase							:						Dict=True,						lowerCamelCase							:						str=False,						lowerCamelCase							:						Any="sine",						lowerCamelCase							:						str=5,						lowerCamelCase							:						str=4,						lowerCamelCase							:						Dict=4,						lowerCamelCase							:						Dict=True,						lowerCamelCase							:						Dict=300,						lowerCamelCase							:						List[str]=True,						lowerCamelCase							:						Optional[Any]=True,						lowerCamelCase							:						Optional[Any]=1,						lowerCamelCase							:						Optional[int]=5,						lowerCamelCase							:						Optional[int]=2,						lowerCamelCase							:						Any=1,						lowerCamelCase							:						Tuple=1,						lowerCamelCase							:						Tuple=5,						lowerCamelCase							:						Union[str, Any]=2,						lowerCamelCase							:						Optional[int]=0.1,						lowerCamelCase							:						List[Any]=0.25,						**lowerCamelCase							:						int,						)->      int:
								if backbone_config is None:
											logger.info('''`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone.'''  )
											lowerCamelCase__	:	Optional[int]				=CONFIG_MAPPING['''resnet'''](out_features=['''stage2''', '''stage3''', '''stage4''']  )
								else:
											if isinstance(lowerCamelCase,						lowerCamelCase  ):
														lowerCamelCase__	:	int				=backbone_config.pop('''model_type'''  )
														lowerCamelCase__	:	List[Any]				=CONFIG_MAPPING[backbone_model_type]
														lowerCamelCase__	:	Optional[Any]				=config_class.from_dict(lowerCamelCase  )

								lowerCamelCase__	:	Tuple				=backbone_config
								lowerCamelCase__	:	List[Any]				=num_queries
								lowerCamelCase__	:	Optional[Any]				=max_position_embeddings
								lowerCamelCase__	:	Union[str, Any]				=d_model
								lowerCamelCase__	:	Tuple				=encoder_ffn_dim
								lowerCamelCase__	:	List[Any]				=encoder_layers
								lowerCamelCase__	:	Union[str, Any]				=encoder_attention_heads
								lowerCamelCase__	:	List[str]				=decoder_ffn_dim
								lowerCamelCase__	:	Tuple				=decoder_layers
								lowerCamelCase__	:	str				=decoder_attention_heads
								lowerCamelCase__	:	Any				=dropout
								lowerCamelCase__	:	str				=attention_dropout
								lowerCamelCase__	:	List[Any]				=activation_dropout
								lowerCamelCase__	:	Any				=activation_function
								lowerCamelCase__	:	Any				=init_std
								lowerCamelCase__	:	int				=init_xavier_std
								lowerCamelCase__	:	Optional[int]				=encoder_layerdrop
								lowerCamelCase__	:	Dict				=auxiliary_loss
								lowerCamelCase__	:	Any				=position_embedding_type
								# deformable attributes
								lowerCamelCase__	:	Dict				=num_feature_levels
								lowerCamelCase__	:	Dict				=encoder_n_points
								lowerCamelCase__	:	List[str]				=decoder_n_points
								lowerCamelCase__	:	Optional[int]				=two_stage
								lowerCamelCase__	:	Optional[Any]				=two_stage_num_proposals
								lowerCamelCase__	:	str				=with_box_refine
								lowerCamelCase__	:	Tuple				=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__	:	Any				=class_cost
								lowerCamelCase__	:	Union[str, Any]				=bbox_cost
								lowerCamelCase__	:	Union[str, Any]				=giou_cost
								# Loss coefficients
								lowerCamelCase__	:	Tuple				=mask_loss_coefficient
								lowerCamelCase__	:	Optional[Any]				=dice_loss_coefficient
								lowerCamelCase__	:	Union[str, Any]				=bbox_loss_coefficient
								lowerCamelCase__	:	Tuple				=giou_loss_coefficient
								lowerCamelCase__	:	Optional[Any]				=eos_coefficient
								lowerCamelCase__	:	Dict				=focal_alpha
								super().__init__(is_encoder_decoder=lowerCamelCase,						**lowerCamelCase  )



					@property
					def 	snake_case ( self							:						Optional[int]  )->      int:
								return self.encoder_attention_heads



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




					def 	snake_case ( self							:						Tuple  )->      Dict:
								lowerCamelCase__	:	Union[str, Any]				=copy.deepcopy(self.__dict__  )
								lowerCamelCase__	:	Dict				=self.backbone_config.to_dict()
								lowerCamelCase__	:	Optional[int]				=self.__class__.model_type
								return output









"""simple docstring"""






def   snake_case__     (	__lowerCamelCase       :					int = 10							,	__lowerCamelCase       :					int = 22			):
			"""simple docstring"""
			lowerCamelCase__	:	Optional[Any]				=range(1							,	__lowerCamelCase			)
			lowerCamelCase__	:	str				=range(1							,	__lowerCamelCase			)
			return sum(
			    1 for power in powers for base in bases if len(str(base**power			)			) == power			)


if __name__ == "__main__":
		print(f'{solution(1_0, 2_2) = }')




