

'''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


__snake_case					:      Union[str, Any] 		=     logging.get_logger(__name__)

__snake_case					:      List[Any] 		=     {
    "microsoft/conditional-detr-resnet-50": (
        "https://huggingface.co/microsoft/conditional-detr-resnet-50/resolve/main/config.json"
    ),
}



class lowerCamelCase					(    lowercase_		):



			'''simple docstring'''






			__snake_case             =			'conditional_detr'
			__snake_case             =			['past_key_values']
			__snake_case             =			{
			    'hidden_size': 'd_model',
			    'num_attention_heads': 'encoder_attention_heads',
			}


			def __init__( self			:		Optional[Any]						,     lowerCAmelCase_			:		Tuple=True						,     lowerCAmelCase_			:		List[str]=None						,     lowerCAmelCase_			:		Any=3						,     lowerCAmelCase_			:		Any=3_00						,     lowerCAmelCase_			:		Any=6						,     lowerCAmelCase_			:		Optional[Any]=20_48						,     lowerCAmelCase_			:		Tuple=8						,     lowerCAmelCase_			:		Optional[Any]=6						,     lowerCAmelCase_			:		str=20_48						,     lowerCAmelCase_			:		Any=8						,     lowerCAmelCase_			:		int=0.0						,     lowerCAmelCase_			:		Union[str, Any]=0.0						,     lowerCAmelCase_			:		Optional[Any]=True						,     lowerCAmelCase_			:		Optional[int]="relu"						,     lowerCAmelCase_			:		Optional[int]=2_56						,     lowerCAmelCase_			:		Optional[Any]=0.1						,     lowerCAmelCase_			:		int=0.0						,     lowerCAmelCase_			:		str=0.0						,     lowerCAmelCase_			:		Tuple=0.02						,     lowerCAmelCase_			:		str=1.0						,     lowerCAmelCase_			:		List[Any]=False						,     lowerCAmelCase_			:		Any="sine"						,     lowerCAmelCase_			:		Optional[Any]="resnet50"						,     lowerCAmelCase_			:		Optional[Any]=True						,     lowerCAmelCase_			:		List[str]=False						,     lowerCAmelCase_			:		Optional[int]=2						,     lowerCAmelCase_			:		int=5						,     lowerCAmelCase_			:		int=2						,     lowerCAmelCase_			:		Tuple=1						,     lowerCAmelCase_			:		int=1						,     lowerCAmelCase_			:		Any=2						,     lowerCAmelCase_			:		Tuple=5						,     lowerCAmelCase_			:		Union[str, Any]=2						,     lowerCAmelCase_			:		Union[str, Any]=0.25						,     **lowerCAmelCase_			:		Dict						,     )     ->						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."""					)
																					A__	:  Optional[int]           =CONFIG_MAPPING["""resnet"""](out_features=["""stage4"""]					)
															elif isinstance(a_						,     a_					):
																					A__	:  Tuple           =backbone_config.get("""model_type"""					)
																					A__	:  Union[str, Any]           =CONFIG_MAPPING[backbone_model_type]
																					A__	:  int           =config_class.from_dict(a_					)

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


			@property
			def lowercase__		( self			:		List[Any]					)     ->						Dict:





									'''simple docstring'''
									return self.encoder_attention_heads


			@property
			def lowercase__		( self			:		Dict					)     ->						int:





									'''simple docstring'''
									return self.d_model



			def lowercase__		( self			:		Optional[int]					)     ->						int:





									'''simple docstring'''
									A__	:  str           =copy.deepcopy(self.__dict__					)
									if self.backbone_config is not None:
															A__	:  Any           =self.backbone_config.to_dict()
									A__	:  int           =self.__class__.model_type
									return output



class lowerCamelCase					(    lowercase_		):



			'''simple docstring'''






			__snake_case             =			version.parse('1.11'		)


			@property
			def lowercase__		( self			:		Tuple					)     ->						List[str]:





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


			@property
			def lowercase__		( self			:		Any					)     ->						Union[str, Any]:





									'''simple docstring'''
									return 1e-5



			@property
			def lowercase__		( self			:		Any					)     ->						Optional[Any]:





									'''simple docstring'''
									return 12






from bisect import bisect
from itertools import accumulate







def     UpperCAmelCase_		(					snake_case__    ,			snake_case__    ,			snake_case__    ,			snake_case__					)	->     Optional[int]:



				"""simple docstring"""





				lowerCAmelCase__		  =  sorted(zip(snake_case__    ,			snake_case__					)    ,			key=lambda snake_case__					: x[0] / x[1]    ,			reverse=snake_case__					)
				lowerCAmelCase__  ,   lowerCAmelCase__		  =  [i[0] for i in r], [i[1] for i in r]
				lowerCAmelCase__		  =  list(accumulate(snake_case__					)					)
				lowerCAmelCase__		  =  bisect(snake_case__    ,			snake_case__					)
				return (
				    0
				    if k == 0
				    else sum(vl[:k]					) + (w - acc[k - 1]) * (vl[k]) / (wt[k])
				    if k != n
				    else sum(vl[:k]					)
				)


if __name__ == "__main__":
	import doctest

	doctest.testmod()
