




"""simple docstring"""





import copy
from collections import OrderedDict
from typing import Mapping

from packaging import version

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


A   =       logging.get_logger(__name__)

A   =       {
    """microsoft/conditional-detr-resnet-50""": (
        """https://huggingface.co/microsoft/conditional-detr-resnet-50/resolve/main/config.json"""
    ),
}



class      a__				(	__magic_name__   ):
			lowercase_    =	"conditional_detr"
			lowercase_    =	["past_key_values"]
			lowercase_    =	{
			    "hidden_size": "d_model",
			    "num_attention_heads": "encoder_attention_heads",
			}


			def __init__(      self      :    Tuple      ,  UpperCamelCase_      :    Union[str, Any]=True      ,  UpperCamelCase_      :    Dict=None      ,  UpperCamelCase_      :    str=3      ,  UpperCamelCase_      :    Optional[int]=300      ,  UpperCamelCase_      :    Optional[Any]=6      ,  UpperCamelCase_      :    Tuple=2048      ,  UpperCamelCase_      :    List[Any]=8      ,  UpperCamelCase_      :    List[str]=6      ,  UpperCamelCase_      :    Any=2048      ,  UpperCamelCase_      :    Optional[Any]=8      ,  UpperCamelCase_      :    List[str]=0.0      ,  UpperCamelCase_      :    Optional[int]=0.0      ,  UpperCamelCase_      :    Union[str, Any]=True      ,  UpperCamelCase_      :    List[str]="relu"      ,  UpperCamelCase_      :    Dict=256      ,  UpperCamelCase_      :    Any=0.1      ,  UpperCamelCase_      :    List[str]=0.0      ,  UpperCamelCase_      :    Dict=0.0      ,  UpperCamelCase_      :    Tuple=0.02      ,  UpperCamelCase_      :    Union[str, Any]=1.0      ,  UpperCamelCase_      :    Optional[int]=False      ,  UpperCamelCase_      :    Tuple="sine"      ,  UpperCamelCase_      :    str="resnet50"      ,  UpperCamelCase_      :    Optional[int]=True      ,  UpperCamelCase_      :    str=False      ,  UpperCamelCase_      :    Tuple=2      ,  UpperCamelCase_      :    Tuple=5      ,  UpperCamelCase_      :    Dict=2      ,  UpperCamelCase_      :    Union[str, Any]=1      ,  UpperCamelCase_      :    Optional[Any]=1      ,  UpperCamelCase_      :    Any=2      ,  UpperCamelCase_      :    Any=5      ,  UpperCamelCase_      :    Union[str, Any]=2      ,  UpperCamelCase_      :    Optional[Any]=0.25      ,  **UpperCamelCase_      :    Dict      ,  ):


						"""simple docstring"""




						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	: List[str]		=					CONFIG_MAPPING["resnet"](out_features=["stage4"])
									elif isinstance(UpperCamelCase_      ,  UpperCamelCase_):
												__UpperCAmelCase	: str		=					backbone_config.get("model_type")
												__UpperCAmelCase	: Tuple		=					CONFIG_MAPPING[backbone_model_type]
												__UpperCAmelCase	: List[str]		=					config_class.from_dict(UpperCamelCase_)

						__UpperCAmelCase	: Any		=					use_timm_backbone
						__UpperCAmelCase	: Optional[int]		=					backbone_config
						__UpperCAmelCase	: Optional[Any]		=					num_channels
						__UpperCAmelCase	: List[str]		=					num_queries
						__UpperCAmelCase	: Dict		=					d_model
						__UpperCAmelCase	: Tuple		=					encoder_ffn_dim
						__UpperCAmelCase	: str		=					encoder_layers
						__UpperCAmelCase	: Tuple		=					encoder_attention_heads
						__UpperCAmelCase	: Any		=					decoder_ffn_dim
						__UpperCAmelCase	: int		=					decoder_layers
						__UpperCAmelCase	: Optional[int]		=					decoder_attention_heads
						__UpperCAmelCase	: Tuple		=					dropout
						__UpperCAmelCase	: List[str]		=					attention_dropout
						__UpperCAmelCase	: Optional[Any]		=					activation_dropout
						__UpperCAmelCase	: Optional[Any]		=					activation_function
						__UpperCAmelCase	: int		=					init_std
						__UpperCAmelCase	: Dict		=					init_xavier_std
						__UpperCAmelCase	: Dict		=					encoder_layerdrop
						__UpperCAmelCase	: Dict		=					decoder_layerdrop
						__UpperCAmelCase	: Dict		=					encoder_layers
						__UpperCAmelCase	: Optional[int]		=					auxiliary_loss
						__UpperCAmelCase	: str		=					position_embedding_type
						__UpperCAmelCase	: List[str]		=					backbone
						__UpperCAmelCase	: Optional[int]		=					use_pretrained_backbone
						__UpperCAmelCase	: Tuple		=					dilation
						# Hungarian matcher
						__UpperCAmelCase	: Dict		=					class_cost
						__UpperCAmelCase	: Optional[int]		=					bbox_cost
						__UpperCAmelCase	: Dict		=					giou_cost
						# Loss coefficients
						__UpperCAmelCase	: Optional[Any]		=					mask_loss_coefficient
						__UpperCAmelCase	: Any		=					dice_loss_coefficient
						__UpperCAmelCase	: Tuple		=					cls_loss_coefficient
						__UpperCAmelCase	: Union[str, Any]		=					bbox_loss_coefficient
						__UpperCAmelCase	: Union[str, Any]		=					giou_loss_coefficient
						__UpperCAmelCase	: Tuple		=					focal_alpha
						super().__init__(is_encoder_decoder=UpperCamelCase_      ,  **UpperCamelCase_)


			@property
			def       a_     (      self      :    Tuple):


						"""simple docstring"""




						return self.encoder_attention_heads


			@property
			def       a_     (      self      :    Any):


						"""simple docstring"""




						return self.d_model


			def       a_     (      self      :    Optional[Any]):


						"""simple docstring"""




						__UpperCAmelCase	: str		=					copy.deepcopy(self.__dict__)
						if self.backbone_config is not None:
									__UpperCAmelCase	: Tuple		=					self.backbone_config.to_dict()
						__UpperCAmelCase	: List[str]		=					self.__class__.model_type
						return output






class      a__				(	__magic_name__   ):
			lowercase_    =	version.parse("1.11"   )


			@property
			def       a_     (      self      :    Dict):


						"""simple docstring"""




						return OrderedDict(
						    [
						        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
						        ("pixel_mask", {0: "batch"}),
						    ])


			@property
			def       a_     (      self      :    Union[str, Any]):


						"""simple docstring"""




						return 1e-5


			@property
			def       a_     (      self      :    Optional[Any]):


						"""simple docstring"""




						return 12








"""simple docstring"""





def 					_UpperCamelCase    (			UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase							)			->			int:


			"""simple docstring"""

			if exponent == 1:
						return base
			if exponent % 2 == 0:
						__UpperCAmelCase	: Union[str, Any]		=					_modexpt(UpperCamelCase				,       exponent // 2				,       UpperCamelCase							) % modulo_value
						return (x * x) % modulo_value
			else:
						return (base * _modexpt(UpperCamelCase				,       exponent - 1				,       UpperCamelCase							)) % modulo_value

def 					_UpperCamelCase    (			UpperCamelCase = 1777				,       UpperCamelCase = 1855				,       UpperCamelCase = 8							)			->			int:


			"""simple docstring"""
			__UpperCAmelCase	: Optional[int]		=					base
			for _ in range(1				,       UpperCamelCase							):
						__UpperCAmelCase	: str		=					_modexpt(UpperCamelCase				,       UpperCamelCase				,       10**digits							)

			return result


if __name__ == "__main__":
					print(f'''{solution() = }''')


