

import copy

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


SCREAMING_SNAKE_CASE		:Optional[int]						=     logging.get_logger(__name__)

SCREAMING_SNAKE_CASE		:str						=     {
    """SenseTime/deformable-detr""": """https://huggingface.co/sensetime/deformable-detr/resolve/main/config.json""",
    # See all Deformable DETR models at https://huggingface.co/models?filter=deformable-detr
}






class 						__magic_name__					(							snake_case				):
     UpperCamelCase_	:Optional[int]										=      """deformable_detr"""
     UpperCamelCase_	:List[Any]										=      {
         """hidden_size""": """d_model""",
         """num_attention_heads""": """encoder_attention_heads""",
     }






     def __init__(				self		,						_lowercase=True		,						_lowercase=None		,						_lowercase=3		,						_lowercase=300		,						_lowercase=1_024		,						_lowercase=6		,						_lowercase=1_024		,						_lowercase=8		,						_lowercase=6		,						_lowercase=1_024		,						_lowercase=8		,						_lowercase=0.0		,						_lowercase=True		,						_lowercase="relu"		,						_lowercase=256		,						_lowercase=0.1		,						_lowercase=0.0		,						_lowercase=0.0		,						_lowercase=0.02		,						_lowercase=1.0		,						_lowercase=True		,						_lowercase=False		,						_lowercase="sine"		,						_lowercase="resnet50"		,						_lowercase=True		,						_lowercase=False		,						_lowercase=4		,						_lowercase=4		,						_lowercase=4		,						_lowercase=False		,						_lowercase=300		,						_lowercase=False		,						_lowercase=1		,						_lowercase=5		,						_lowercase=2		,						_lowercase=1		,						_lowercase=1		,						_lowercase=5		,						_lowercase=2		,						_lowercase=0.1		,						_lowercase=0.25		,						_lowercase=False		,						**_lowercase		,						)->     Optional[int]:
         if backbone_config is not None and use_timm_backbone:
             raise ValueError("You can't specify both `backbone_config` and `use_timm_backbone`."	)

         if not use_timm_backbone:
             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=["stage4"]	)
             elif isinstance(_lowercase		,						_lowercase	):
                 UpperCamelCase_			  =						backbone_config.get("model_type"	)
                 UpperCamelCase_			  =						CONFIG_MAPPING[backbone_model_type]
                 UpperCamelCase_			  =						config_class.from_dict(_lowercase	)
         UpperCamelCase_			  =						use_timm_backbone
         UpperCamelCase_			  =						backbone_config
         UpperCamelCase_			  =						num_channels
         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
         UpperCamelCase_			  =						backbone
         UpperCamelCase_			  =						use_pretrained_backbone
         UpperCamelCase_			  =						dilation
         # 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
         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
         UpperCamelCase_			  =						disable_custom_kernels
         super().__init__(is_encoder_decoder=_lowercase		,						**_lowercase	)






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






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






     def 	UpperCAmelCase_				(				self	)->     Optional[Any]:
         UpperCamelCase_			  =						copy.deepcopy(self.__dict__	)
         if self.backbone_config is not None:
             UpperCamelCase_			  =						self.backbone_config.to_dict()
         UpperCamelCase_			  =						self.__class__.model_type
         return output



def 			lowerCAmelCase(      SCREAMING_SNAKE_CASE_			)->						str:



    """simple docstring"""






    if isinstance(SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			):
        raise TypeError("'float' object cannot be interpreted as an integer"			)
    if isinstance(SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			):
        raise TypeError("'str' object cannot be interpreted as an integer"			)

    if num == 0:
        return "0b0"

    UpperCamelCase_			  =						False

    if num < 0:
        UpperCamelCase_			  =						True
        UpperCamelCase_			  =						-num

    UpperCamelCase_			  =						[]
    while num > 0:
        binary.insert(0			,						num % 2			)
        num >>= 1

    if negative:
        return "-0b" + "".join(str(SCREAMING_SNAKE_CASE_			) for e in binary			)

    return "0b" + "".join(str(SCREAMING_SNAKE_CASE_			) for e in binary			)


if __name__ == "__main__":
 import doctest

 doctest.testmod()
