




import copy

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


_lowerCamelCase      			=						logging.get_logger(__name__)

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



class       a					(       _A      ):

     '''simple docstring'''





     lowerCAmelCase    :	Union[str, Any]       		=  'deta'
     lowerCAmelCase    :	Optional[int]       		=  {
         'hidden_size': 'd_model',
         'num_attention_heads': 'encoder_attention_heads',
     }
     def __init__(     self       :      Union[str, Any] ,   __snake_case       :      int=None ,   __snake_case       :      Dict=9_00 ,   __snake_case       :      str=20_48 ,   __snake_case       :      Any=6 ,   __snake_case       :      int=20_48 ,   __snake_case       :      Dict=8 ,   __snake_case       :      List[Any]=6 ,   __snake_case       :      str=10_24 ,   __snake_case       :      Any=8 ,   __snake_case       :      Union[str, Any]=0.0 ,   __snake_case       :      Optional[int]=True ,   __snake_case       :      str="relu" ,   __snake_case       :      Optional[Any]=2_56 ,   __snake_case       :      str=0.1 ,   __snake_case       :      List[str]=0.0 ,   __snake_case       :      Any=0.0 ,   __snake_case       :      Dict=0.02 ,   __snake_case       :      Optional[int]=1.0 ,   __snake_case       :      Any=True ,   __snake_case       :      int=False ,   __snake_case       :      Any="sine" ,   __snake_case       :      int=5 ,   __snake_case       :      int=4 ,   __snake_case       :      Optional[int]=4 ,   __snake_case       :      str=True ,   __snake_case       :      Optional[int]=3_00 ,   __snake_case       :      Union[str, Any]=True ,   __snake_case       :      Optional[int]=True ,   __snake_case       :      Any=1 ,   __snake_case       :      Tuple=5 ,   __snake_case       :      Dict=2 ,   __snake_case       :      Optional[int]=1 ,   __snake_case       :      Optional[int]=1 ,   __snake_case       :      List[Any]=5 ,   __snake_case       :      Dict=2 ,   __snake_case       :      Any=0.1 ,   __snake_case       :      Optional[int]=0.25 ,   **__snake_case       :      Tuple ,   ):
         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(__snake_case ,   __snake_case    ):
                 UpperCAmelCase_										=					backbone_config.pop('''model_type'''    )
                 UpperCAmelCase_										=					CONFIG_MAPPING[backbone_model_type]
                 UpperCAmelCase_										=					config_class.from_dict(__snake_case    )

         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=__snake_case ,   **__snake_case    )
     @property
     def   lowerCamelCase_       (     self       :      Tuple    ):
         return self.encoder_attention_heads
     @property
     def   lowerCamelCase_       (     self       :      List[str]    ):
         return self.d_model




     def   lowerCamelCase_       (     self       :      Optional[Any]    ):
         UpperCAmelCase_										=					copy.deepcopy(self.__dict__    )
         UpperCAmelCase_										=					self.backbone_config.to_dict()
         UpperCAmelCase_										=					self.__class__.model_type
         return output











from __future__ import annotations

from fractions import Fraction




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						int	,					__UpperCamelCase      :						int				)  ->							bool:
    return (
        num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
    )




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						int				)  ->							list[str]:
    UpperCAmelCase_										=					[]
    UpperCAmelCase_										=					11
    UpperCAmelCase_										=					int('''1''' + '''0''' * digit_len				)
    for num in range(__UpperCamelCase	,					__UpperCamelCase				):
        while den <= 99:
            if (num != den) and (num % 10 == den // 10) and (den % 10 != 0):
                if is_digit_cancelling(__UpperCamelCase	,					__UpperCamelCase				):
                    solutions.append(f'{num}/{den}'				)
            den += 1
        num += 1
        UpperCAmelCase_										=					10
    return solutions




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						int = 2				)  ->							int:
    UpperCAmelCase_										=					1.0
    for fraction in fraction_list(__UpperCamelCase				):
        UpperCAmelCase_										=					Fraction(__UpperCamelCase				)
        result *= frac.denominator / frac.numerator
    return int(__UpperCamelCase				)


if __name__ == "__main__":
 print(solution())





