



"""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


_lowercase				:				str   		=		logging.get_logger(__name__)

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

class  __SCREAMING_SNAKE_CASE			(   lowerCAmelCase_     ):


					'''simple docstring'''





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



					def __init__( self							:						str,						lowerCamelCase							:						str=True,						lowerCamelCase							:						List[Any]=None,						lowerCamelCase							:						Optional[int]=3,						lowerCamelCase							:						Union[str, Any]=300,						lowerCamelCase							:						Optional[Any]=6,						lowerCamelCase							:						Dict=2048,						lowerCamelCase							:						int=8,						lowerCamelCase							:						Optional[int]=6,						lowerCamelCase							:						List[str]=2048,						lowerCamelCase							:						Any=8,						lowerCamelCase							:						Tuple=0.0,						lowerCamelCase							:						str=0.0,						lowerCamelCase							:						int=True,						lowerCamelCase							:						Union[str, Any]="relu",						lowerCamelCase							:						List[Any]=256,						lowerCamelCase							:						List[Any]=0.1,						lowerCamelCase							:						Any=0.0,						lowerCamelCase							:						Optional[int]=0.0,						lowerCamelCase							:						Optional[Any]=0.02,						lowerCamelCase							:						str=1.0,						lowerCamelCase							:						List[Any]=False,						lowerCamelCase							:						List[Any]="sine",						lowerCamelCase							:						Union[str, Any]="resnet50",						lowerCamelCase							:						Optional[int]=True,						lowerCamelCase							:						Optional[int]=False,						lowerCamelCase							:						Union[str, Any]=2,						lowerCamelCase							:						Optional[Any]=5,						lowerCamelCase							:						Optional[Any]=2,						lowerCamelCase							:						Optional[Any]=1,						lowerCamelCase							:						Union[str, Any]=1,						lowerCamelCase							:						List[str]=2,						lowerCamelCase							:						Optional[Any]=5,						lowerCamelCase							:						int=2,						lowerCamelCase							:						Any=0.25,						**lowerCamelCase							:						Optional[int],						)->      Optional[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__	:	Dict				=CONFIG_MAPPING['''resnet'''](out_features=['''stage4''']  )
											elif isinstance(lowerCamelCase,						lowerCamelCase  ):
														lowerCamelCase__	:	Tuple				=backbone_config.get('''model_type'''  )
														lowerCamelCase__	:	int				=CONFIG_MAPPING[backbone_model_type]
														lowerCamelCase__	:	Tuple				=config_class.from_dict(lowerCamelCase  )

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



					@property
					def 	snake_case ( self							:						Optional[int]  )->      int:
								return self.encoder_attention_heads



					@property
					def 	snake_case ( self							:						str  )->      int:
								return self.d_model




					def 	snake_case ( self							:						List[str]  )->      Union[str, Any]:
								lowerCamelCase__	:	List[Any]				=copy.deepcopy(self.__dict__  )
								if self.backbone_config is not None:
											lowerCamelCase__	:	Any				=self.backbone_config.to_dict()
								lowerCamelCase__	:	List[Any]				=self.__class__.model_type
								return output





class  __SCREAMING_SNAKE_CASE			(   lowerCAmelCase_     ):


					'''simple docstring'''





					_a         =							version.parse('1.11'     )



					@property
					def 	snake_case ( self							:						int  )->      Mapping[str, Mapping[int, str]]:
								return OrderedDict(
								    [
								        ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
								        ('''pixel_mask''', {0: '''batch'''}),
								    ]  )



					@property
					def 	snake_case ( self							:						str  )->      float:
								return 1E-5




					@property
					def 	snake_case ( self							:						Dict  )->      int:
								return 12









"""simple docstring"""






_lowercase				:				str   		=		0  # The first color of the flag.
_lowercase				:				Dict   		=		1  # The second color of the flag.
_lowercase				:				Tuple   		=		2  # The third color of the flag.
_lowercase				:				Optional[int]   		=		(red, white, blue)






def   snake_case__     (	__lowerCamelCase       :					list			):
			"""simple docstring"""
			if not sequence:
						return []
			if len(__lowerCamelCase			) == 1:
						return list(__lowerCamelCase			)
			lowerCamelCase__	:	List[Any]				=0
			lowerCamelCase__	:	Dict				=len(__lowerCamelCase			) - 1
			lowerCamelCase__	:	Tuple				=0
			while mid <= high:
						if sequence[mid] == colors[0]:
									lowerCamelCase__			,     lowerCamelCase__	:	Optional[Any]				=sequence[mid], sequence[low]
									low += 1
									mid += 1
						elif sequence[mid] == colors[1]:
									mid += 1
						elif sequence[mid] == colors[2]:
									lowerCamelCase__			,     lowerCamelCase__	:	Union[str, Any]				=sequence[high], sequence[mid]
									high -= 1
						else:
									lowerCamelCase__	:	Dict				=f'''The elements inside the sequence must contains only {colors} values'''
									raise ValueError(__lowerCamelCase			)
			return sequence


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		_lowercase				:				Optional[Any]   		=		input("Enter numbers separated by commas:\n").strip()
		_lowercase				:				int   		=		[int(item.strip()) for item in user_input.split(",")]
		print(f'{dutch_national_flag_sort(unsorted)}')




