



import copy

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


__lowerCamelCase     :							Any  							=				logging.get_logger(__name__)

__lowerCamelCase     :							List[str]  							=				{
    "ut/deta": "https://huggingface.co/ut/deta/resolve/main/config.json",
}





class  __magic_name__   (							A__						):
		lowercase      :       Optional[Any]          ='''deta'''
		lowercase      :       List[str]          ={
		    '''hidden_size''': '''d_model''',
		    '''num_attention_heads''': '''encoder_attention_heads''',
		}






		def __init__(						self      :     Any				,		UpperCamelCase__      :     Any=None				,		UpperCamelCase__      :     List[str]=9_00				,		UpperCamelCase__      :     List[Any]=20_48				,		UpperCamelCase__      :     Optional[int]=6				,		UpperCamelCase__      :     List[str]=20_48				,		UpperCamelCase__      :     Optional[Any]=8				,		UpperCamelCase__      :     Union[str, Any]=6				,		UpperCamelCase__      :     Optional[int]=10_24				,		UpperCamelCase__      :     int=8				,		UpperCamelCase__      :     int=0.0				,		UpperCamelCase__      :     Any=True				,		UpperCamelCase__      :     List[Any]="relu"				,		UpperCamelCase__      :     str=2_56				,		UpperCamelCase__      :     str=0.1				,		UpperCamelCase__      :     Tuple=0.0				,		UpperCamelCase__      :     List[Any]=0.0				,		UpperCamelCase__      :     List[Any]=0.02				,		UpperCamelCase__      :     str=1.0				,		UpperCamelCase__      :     List[Any]=True				,		UpperCamelCase__      :     List[str]=False				,		UpperCamelCase__      :     List[Any]="sine"				,		UpperCamelCase__      :     Union[str, Any]=5				,		UpperCamelCase__      :     Optional[Any]=4				,		UpperCamelCase__      :     List[Any]=4				,		UpperCamelCase__      :     Dict=True				,		UpperCamelCase__      :     Dict=3_00				,		UpperCamelCase__      :     Any=True				,		UpperCamelCase__      :     Optional[Any]=True				,		UpperCamelCase__      :     Optional[int]=1				,		UpperCamelCase__      :     int=5				,		UpperCamelCase__      :     str=2				,		UpperCamelCase__      :     int=1				,		UpperCamelCase__      :     List[Any]=1				,		UpperCamelCase__      :     Tuple=5				,		UpperCamelCase__      :     Dict=2				,		UpperCamelCase__      :     Dict=0.1				,		UpperCamelCase__      :     List[Any]=0.25				,		**UpperCamelCase__      :     Optional[Any]				,		)				->					List[Any]:
								'''simple docstring'''







								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(UpperCamelCase__				,		UpperCamelCase__      ):
																				UpperCAmelCase         =     backbone_config.pop("model_type"      )
																				UpperCAmelCase         =     CONFIG_MAPPING[backbone_model_type]
																				UpperCAmelCase         =     config_class.from_dict(UpperCamelCase__      )

								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=UpperCamelCase__				,		**UpperCamelCase__      )






		@property
		def SCREAMING_SNAKE_CASE_			(						self      :     List[Any]      )				->					int:
								'''simple docstring'''







								return self.encoder_attention_heads






		@property
		def SCREAMING_SNAKE_CASE_			(						self      :     Any      )				->					int:
								'''simple docstring'''







								return self.d_model







		def SCREAMING_SNAKE_CASE_			(						self      :     List[str]      )				->					Tuple:
								'''simple docstring'''







								UpperCAmelCase         =     copy.deepcopy(self.__dict__      )
								UpperCAmelCase         =     self.backbone_config.to_dict()
								UpperCAmelCase         =     self.__class__.model_type
								return output








def    lowerCamelCase_(lowerCamelCase_    ) ->       list[int]:
						UpperCAmelCase         =     len(lowerCamelCase_    )
						for i in range(lowerCamelCase_    ):
												for j in range(i + 1    ,   lowerCamelCase_    ):
																		if numbers[j] < numbers[i]:
																								UpperCAmelCase       ,		UpperCAmelCase         =     numbers[j], numbers[i]
						return numbers


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



