






"""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__			:							List[Any]					   =   logging.get_logger(__name__)

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







class   lowercase__     (				__SCREAMING_SNAKE_CASE  ):
			_UpperCAmelCase						:str       =					"conditional_detr"
			_UpperCAmelCase						:Dict       =					["past_key_values"]
			_UpperCAmelCase						:Any       =					{
			    "hidden_size": "d_model",
			    "num_attention_heads": "encoder_attention_heads",
			}


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

										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."   )
																								lowerCamelCase_			:				List[Any]										=CONFIG_MAPPING["resnet"](out_features=["stage4"]   )
																	elif isinstance(_SCREAMING_SNAKE_CASE  ,			_SCREAMING_SNAKE_CASE   ):
																								lowerCamelCase_			:				List[Any]										=backbone_config.get("model_type"   )
																								lowerCamelCase_			:				Any										=CONFIG_MAPPING[backbone_model_type]
																								lowerCamelCase_			:				Dict										=config_class.from_dict(_SCREAMING_SNAKE_CASE   )

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


			@property
			def       UpperCAmelCase__		( self	:    Dict   ):
										return self.encoder_attention_heads


			@property
			def       UpperCAmelCase__		( self	:    str   ):
										return self.d_model


			def       UpperCAmelCase__		( self	:    Any   ):
										lowerCamelCase_			:				int										=copy.deepcopy(self.__dict__   )
										if self.backbone_config is not None:
																	lowerCamelCase_			:				Optional[Any]										=self.backbone_config.to_dict()
										lowerCamelCase_			:				List[str]										=self.__class__.model_type
										return output







class   lowercase__     (				__SCREAMING_SNAKE_CASE  ):
			_UpperCAmelCase						:Any       =					version.parse("1.11"  )


			@property
			def       UpperCAmelCase__		( self	:    str   ):
										return OrderedDict(
										    [
										        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
										        ("pixel_mask", {0: "batch"}),
										    ]   )


			@property
			def       UpperCAmelCase__		( self	:    List[str]   ):
										return 1E-5


			@property
			def       UpperCAmelCase__		( self	:    List[Any]   ):
										return 12








"""simple docstring"""






# Function to print upper half of diamond (pyramid)


def      _lowercase							(    __snake_case      )		->  Dict:
			for i in range(0   ,__snake_case      ):
						for _ in range(0   ,n - i - 1      ):  # printing spaces
									print(" "   ,end=""      )
						for _ in range(0   ,i + 1      ):  # printing stars
									print("* "   ,end=""      )
						print()


def      _lowercase							(    __snake_case      )		->  Tuple:
			for i in range(__snake_case   ,0   ,-1      ):
						for _ in range(__snake_case   ,0   ,-1      ):  # printing stars
									print("* "   ,end=""      )
						print()
						for _ in range(n - i + 1   ,0   ,-1      ):  # printing spaces
									print(" "   ,end=""      )


def      _lowercase							(    __snake_case      )		->  Any:
			if n <= 0:
						print("       ...       ....        nothing printing :("      )
						return
			floyd(__snake_case      )  # upper half
			reverse_floyd(__snake_case      )  # lower half


if __name__ == "__main__":
	print(R'| /\ | |- |  |-  |--| |\  /| |-')
	print(R'|/  \| |- |_ |_  |__| | \/ | |_')
	__snake_case				:  Tuple =       1
	while K:
		__snake_case				:  List[str] =       int(input('enter the number and , and see the magic : '))
		print()
		pretty_print(user_number)
		__snake_case				:  Optional[Any] =       int(input('press 0 to exit... and 1 to continue...'))

	print('Good Bye...')