




def 						__A						(      __lowerCamelCase       ) ->			list:
	a									=				len(__lowerCamelCase       )
	for i in range(1				,     __lowerCamelCase       ):
		a									=				collection[i]
		a									=				0
		a									=				i - 1

		while low <= high:
			a									=				(low + high) // 2
			if val < collection[mid]:
				a									=				mid - 1
			else:
				a									=				mid + 1
		for j in range(__lowerCamelCase				,     __lowerCamelCase				,     -1       ):
			a									=				collection[j - 1]
		a									=				val
	return collection


if __name__ == "__main__":
		__UpperCamelCase   :			str          = input("Enter numbers separated by a comma:\n").strip()
		__UpperCamelCase   :			str          = [int(item) for item in user_input.split(",")]
		print(binary_insertion_sort(unsorted))







import copy

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


__UpperCamelCase   :			Any          = logging.get_logger(__name__)

__UpperCamelCase   :			Tuple          = {
    "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 						__lowerCAmelCase      (      __magic_name__					):
							UpperCamelCase__   	=    '''deformable_detr'''
							UpperCamelCase__   	=    {
							    '''hidden_size''': '''d_model''',
							    '''num_attention_heads''': '''encoder_attention_heads''',
							}
							def __init__(		self		:List[str]						, __magic_name__		:Tuple=True						, __magic_name__		:str=None						, __magic_name__		:Tuple=3						, __magic_name__		:List[str]=300						, __magic_name__		:Dict=1024						, __magic_name__		:Tuple=6						, __magic_name__		:Tuple=1024						, __magic_name__		:int=8						, __magic_name__		:List[Any]=6						, __magic_name__		:Tuple=1024						, __magic_name__		:List[Any]=8						, __magic_name__		:Union[str, Any]=0.0						, __magic_name__		:Union[str, Any]=True						, __magic_name__		:str="relu"						, __magic_name__		:Optional[Any]=256						, __magic_name__		:int=0.1						, __magic_name__		:List[str]=0.0						, __magic_name__		:str=0.0						, __magic_name__		:str=0.02						, __magic_name__		:int=1.0						, __magic_name__		:List[str]=True						, __magic_name__		:Union[str, Any]=False						, __magic_name__		:List[Any]="sine"						, __magic_name__		:Union[str, Any]="resnet50"						, __magic_name__		:int=True						, __magic_name__		:Any=False						, __magic_name__		:List[str]=4						, __magic_name__		:Tuple=4						, __magic_name__		:Union[str, Any]=4						, __magic_name__		:Optional[int]=False						, __magic_name__		:Tuple=300						, __magic_name__		:Tuple=False						, __magic_name__		:List[Any]=1						, __magic_name__		:List[str]=5						, __magic_name__		:List[Any]=2						, __magic_name__		:Optional[int]=1						, __magic_name__		:Union[str, Any]=1						, __magic_name__		:List[Any]=5						, __magic_name__		:Optional[Any]=2						, __magic_name__		:Optional[int]=0.1						, __magic_name__		:List[str]=0.25						, __magic_name__		:str=False						, **__magic_name__		:List[str]						, ):







								'''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									=				CONFIG_MAPPING["""resnet"""](out_features=["""stage4"""]							)
									elif isinstance(__magic_name__						, __magic_name__							):
										a									=				backbone_config.get("""model_type"""							)
										a									=				CONFIG_MAPPING[backbone_model_type]
										a									=				config_class.from_dict(__magic_name__							)
								a									=				use_timm_backbone
								a									=				backbone_config
								a									=				num_channels
								a									=				num_queries
								a									=				max_position_embeddings
								a									=				d_model
								a									=				encoder_ffn_dim
								a									=				encoder_layers
								a									=				encoder_attention_heads
								a									=				decoder_ffn_dim
								a									=				decoder_layers
								a									=				decoder_attention_heads
								a									=				dropout
								a									=				attention_dropout
								a									=				activation_dropout
								a									=				activation_function
								a									=				init_std
								a									=				init_xavier_std
								a									=				encoder_layerdrop
								a									=				auxiliary_loss
								a									=				position_embedding_type
								a									=				backbone
								a									=				use_pretrained_backbone
								a									=				dilation
								# deformable attributes
								a									=				num_feature_levels
								a									=				encoder_n_points
								a									=				decoder_n_points
								a									=				two_stage
								a									=				two_stage_num_proposals
								a									=				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
								a									=				class_cost
								a									=				bbox_cost
								a									=				giou_cost
								# Loss coefficients
								a									=				mask_loss_coefficient
								a									=				dice_loss_coefficient
								a									=				bbox_loss_coefficient
								a									=				giou_loss_coefficient
								a									=				eos_coefficient
								a									=				focal_alpha
								a									=				disable_custom_kernels
								super().__init__(is_encoder_decoder=__magic_name__						, **__magic_name__							)
							@property
							def  lowerCamelCase__				(		self		:List[Any]							):







								'''simple docstring'''







								return self.encoder_attention_heads
							@property
							def  lowerCamelCase__				(		self		:int							):







								'''simple docstring'''







								return self.d_model





							def  lowerCamelCase__				(		self		:Optional[int]							):







								'''simple docstring'''







								a									=				copy.deepcopy(self.__dict__							)
								if self.backbone_config is not None:
									a									=				self.backbone_config.to_dict()
								a									=				self.__class__.model_type
								return output

