






'''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


__lowerCamelCase   :					Any   							=					logging.get_logger(__name__)

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







class    A_	(a_							):
							"""simple docstring"""




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

							def __init__(		self			:List[Any]       ,							lowerCAmelCase__			:List[str]=True       ,							lowerCAmelCase__			:Union[str, Any]=None       ,							lowerCAmelCase__			:Any=3       ,							lowerCAmelCase__			:Dict=300       ,							lowerCAmelCase__			:List[Any]=6       ,							lowerCAmelCase__			:Any=2_048       ,							lowerCAmelCase__			:Any=8       ,							lowerCAmelCase__			:Union[str, Any]=6       ,							lowerCAmelCase__			:Tuple=2_048       ,							lowerCAmelCase__			:Optional[int]=8       ,							lowerCAmelCase__			:Dict=0.0       ,							lowerCAmelCase__			:Any=0.0       ,							lowerCAmelCase__			:Optional[int]=True       ,							lowerCAmelCase__			:List[Any]="relu"       ,							lowerCAmelCase__			:Tuple=256       ,							lowerCAmelCase__			:str=0.1       ,							lowerCAmelCase__			:int=0.0       ,							lowerCAmelCase__			:Optional[Any]=0.0       ,							lowerCAmelCase__			:Optional[int]=0.0_2       ,							lowerCAmelCase__			:Dict=1.0       ,							lowerCAmelCase__			:List[str]=False       ,							lowerCAmelCase__			:List[Any]="sine"       ,							lowerCAmelCase__			:Any="resnet50"       ,							lowerCAmelCase__			:Tuple=True       ,							lowerCAmelCase__			:List[str]=False       ,							lowerCAmelCase__			:Tuple=2       ,							lowerCAmelCase__			:List[Any]=5       ,							lowerCAmelCase__			:Optional[int]=2       ,							lowerCAmelCase__			:Optional[Any]=1       ,							lowerCAmelCase__			:List[str]=1       ,							lowerCAmelCase__			:Union[str, Any]=2       ,							lowerCAmelCase__			:Tuple=5       ,							lowerCAmelCase__			:Dict=2       ,							lowerCAmelCase__			:List[str]=0.2_5       ,							**lowerCAmelCase__			:Tuple       ,							)				->  Any:


										'''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."				)
																snake_case_				:					Any   =       CONFIG_MAPPING["resnet"](out_features=["stage4"]				)
													elif isinstance(lowerCAmelCase__       ,							lowerCAmelCase__				):
																snake_case_				:					Optional[Any]   =       backbone_config.get("model_type"				)
																snake_case_				:					Tuple   =       CONFIG_MAPPING[backbone_model_type]
																snake_case_				:					List[str]   =       config_class.from_dict(lowerCAmelCase__				)

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

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


										'''simple docstring'''




										return self.encoder_attention_heads

							@property
							def 							_A	(		self			:Optional[int]				)				->  int:


										'''simple docstring'''




										return self.d_model






							def 							_A	(		self			:Optional[int]				)				->  Optional[Any]:


										'''simple docstring'''




										snake_case_				:					Optional[Any]   =       copy.deepcopy(self.__dict__				)
										if self.backbone_config is not None:
													snake_case_				:					Union[str, Any]   =       self.backbone_config.to_dict()
										snake_case_				:					str   =       self.__class__.model_type
										return output







class    A_	(a_							):
							"""simple docstring"""




							a__   		=	version.parse('''1.11'''							)

							@property
							def 							_A	(		self			:Any				)				->  Mapping[str, Mapping[int, str]]:


										'''simple docstring'''




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

							@property
							def 							_A	(		self			:Dict				)				->  float:


										'''simple docstring'''




										return 1E-5






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


										'''simple docstring'''




										return 12












'''simple docstring'''




def 	__UpperCAmelCase       ( __magic_name__						)->    list[int]:



			"""simple docstring"""



			if length <= 0 or not isinstance(__magic_name__     ,__magic_name__						):
						raise ValueError("Length must be a positive integer."						)
			return [n * (2 * n - 1) for n in range(__magic_name__						)]


if __name__ == "__main__":
		print(hexagonal_numbers(length=5))
		print(hexagonal_numbers(length=10))




