"""simple docstring"""







import copy

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


lowerCamelCase__           =	logging.get_logger(__name__)

lowerCamelCase__           =	{
    """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 				A__ (			_lowerCamelCase):
		A_		: Optional[Any]            =			'deformable_detr'
		A_		: Tuple            =			{
		    'hidden_size': 'd_model',
		    'num_attention_heads': 'encoder_attention_heads',
		}

		def __init__(   self ,	_SCREAMING_SNAKE_CASE=True ,	_SCREAMING_SNAKE_CASE=None ,	_SCREAMING_SNAKE_CASE=3 ,	_SCREAMING_SNAKE_CASE=3_00 ,	_SCREAMING_SNAKE_CASE=10_24 ,	_SCREAMING_SNAKE_CASE=6 ,	_SCREAMING_SNAKE_CASE=10_24 ,	_SCREAMING_SNAKE_CASE=8 ,	_SCREAMING_SNAKE_CASE=6 ,	_SCREAMING_SNAKE_CASE=10_24 ,	_SCREAMING_SNAKE_CASE=8 ,	_SCREAMING_SNAKE_CASE=0.0 ,	_SCREAMING_SNAKE_CASE=True ,	_SCREAMING_SNAKE_CASE="relu" ,	_SCREAMING_SNAKE_CASE=2_56 ,	_SCREAMING_SNAKE_CASE=0.1 ,	_SCREAMING_SNAKE_CASE=0.0 ,	_SCREAMING_SNAKE_CASE=0.0 ,	_SCREAMING_SNAKE_CASE=0.02 ,	_SCREAMING_SNAKE_CASE=1.0 ,	_SCREAMING_SNAKE_CASE=True ,	_SCREAMING_SNAKE_CASE=False ,	_SCREAMING_SNAKE_CASE="sine" ,	_SCREAMING_SNAKE_CASE="resnet50" ,	_SCREAMING_SNAKE_CASE=True ,	_SCREAMING_SNAKE_CASE=False ,	_SCREAMING_SNAKE_CASE=4 ,	_SCREAMING_SNAKE_CASE=4 ,	_SCREAMING_SNAKE_CASE=4 ,	_SCREAMING_SNAKE_CASE=False ,	_SCREAMING_SNAKE_CASE=3_00 ,	_SCREAMING_SNAKE_CASE=False ,	_SCREAMING_SNAKE_CASE=1 ,	_SCREAMING_SNAKE_CASE=5 ,	_SCREAMING_SNAKE_CASE=2 ,	_SCREAMING_SNAKE_CASE=1 ,	_SCREAMING_SNAKE_CASE=1 ,	_SCREAMING_SNAKE_CASE=5 ,	_SCREAMING_SNAKE_CASE=2 ,	_SCREAMING_SNAKE_CASE=0.1 ,	_SCREAMING_SNAKE_CASE=0.25 ,	_SCREAMING_SNAKE_CASE=False ,	**_SCREAMING_SNAKE_CASE ,	):
			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[str]		    =   backbone_config.get('model_type'				)
					__lowerCAmelCase    :		Optional[Any]		    =   CONFIG_MAPPING[backbone_model_type]
					__lowerCAmelCase    :		int		    =   config_class.from_dict(_SCREAMING_SNAKE_CASE				)
			__lowerCAmelCase    :		Optional[Any]		    =   use_timm_backbone
			__lowerCAmelCase    :		Any		    =   backbone_config
			__lowerCAmelCase    :		List[Any]		    =   num_channels
			__lowerCAmelCase    :		Optional[Any]		    =   num_queries
			__lowerCAmelCase    :		Optional[Any]		    =   max_position_embeddings
			__lowerCAmelCase    :		Optional[int]		    =   d_model
			__lowerCAmelCase    :		Optional[Any]		    =   encoder_ffn_dim
			__lowerCAmelCase    :		Tuple		    =   encoder_layers
			__lowerCAmelCase    :		Union[str, Any]		    =   encoder_attention_heads
			__lowerCAmelCase    :		int		    =   decoder_ffn_dim
			__lowerCAmelCase    :		List[Any]		    =   decoder_layers
			__lowerCAmelCase    :		Optional[int]		    =   decoder_attention_heads
			__lowerCAmelCase    :		List[str]		    =   dropout
			__lowerCAmelCase    :		Optional[Any]		    =   attention_dropout
			__lowerCAmelCase    :		Optional[int]		    =   activation_dropout
			__lowerCAmelCase    :		Union[str, Any]		    =   activation_function
			__lowerCAmelCase    :		Optional[Any]		    =   init_std
			__lowerCAmelCase    :		List[str]		    =   init_xavier_std
			__lowerCAmelCase    :		List[str]		    =   encoder_layerdrop
			__lowerCAmelCase    :		Any		    =   auxiliary_loss
			__lowerCAmelCase    :		Dict		    =   position_embedding_type
			__lowerCAmelCase    :		str		    =   backbone
			__lowerCAmelCase    :		int		    =   use_pretrained_backbone
			__lowerCAmelCase    :		int		    =   dilation
			# deformable attributes
			__lowerCAmelCase    :		List[Any]		    =   num_feature_levels
			__lowerCAmelCase    :		Dict		    =   encoder_n_points
			__lowerCAmelCase    :		Optional[Any]		    =   decoder_n_points
			__lowerCAmelCase    :		str		    =   two_stage
			__lowerCAmelCase    :		int		    =   two_stage_num_proposals
			__lowerCAmelCase    :		Tuple		    =   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
			__lowerCAmelCase    :		str		    =   class_cost
			__lowerCAmelCase    :		List[str]		    =   bbox_cost
			__lowerCAmelCase    :		List[str]		    =   giou_cost
			# Loss coefficients
			__lowerCAmelCase    :		Any		    =   mask_loss_coefficient
			__lowerCAmelCase    :		Any		    =   dice_loss_coefficient
			__lowerCAmelCase    :		Optional[Any]		    =   bbox_loss_coefficient
			__lowerCAmelCase    :		Tuple		    =   giou_loss_coefficient
			__lowerCAmelCase    :		List[str]		    =   eos_coefficient
			__lowerCAmelCase    :		str		    =   focal_alpha
			__lowerCAmelCase    :		Optional[Any]		    =   disable_custom_kernels
			super().__init__(is_encoder_decoder=_SCREAMING_SNAKE_CASE ,	**_SCREAMING_SNAKE_CASE				)

		@property
		def 							__lowerCamelCase							(   self				):
			return self.encoder_attention_heads

		@property
		def 							__lowerCamelCase							(   self				):
			return self.d_model







		def 							__lowerCamelCase							(   self				):
			__lowerCAmelCase    :		Tuple		    =   copy.deepcopy(self.__dict__				)
			if self.backbone_config is not None:
				__lowerCAmelCase    :		Optional[int]		    =   self.backbone_config.to_dict()
			__lowerCAmelCase    :		Tuple		    =   self.__class__.model_type
			return output

"""simple docstring"""







class 				A__ :

		def __init__(   self				):
			__lowerCAmelCase    :		Optional[int]		    =   0
			__lowerCAmelCase    :		Any		    =   0
			__lowerCAmelCase    :		List[Any]		    =   {}

		def 							__lowerCamelCase							(   self ,	_SCREAMING_SNAKE_CASE				):
			if vertex not in self.adjacency:
				__lowerCAmelCase    :		Dict		    =   {}
				self.num_vertices += 1

		def 							__lowerCamelCase							(   self ,	_SCREAMING_SNAKE_CASE ,	_SCREAMING_SNAKE_CASE ,	_SCREAMING_SNAKE_CASE				):
			self.add_vertex(_SCREAMING_SNAKE_CASE				)
			self.add_vertex(_SCREAMING_SNAKE_CASE				)

			if head == tail:
				return

			__lowerCAmelCase    :		Union[str, Any]		    =   weight
			__lowerCAmelCase    :		str		    =   weight

		def 							__lowerCamelCase							(   self				):
			__lowerCAmelCase    :		int		    =   self.get_edges()
			for edge in edges:
				__lowerCAmelCase    ,     __lowerCAmelCase    ,     __lowerCAmelCase    :		Optional[Any]		    =   edge
				edges.remove((tail, head, weight)				)
			for i in range(len(_SCREAMING_SNAKE_CASE				)				):
				__lowerCAmelCase    :		List[str]		    =   list(edges[i]				)

			edges.sort(key=lambda _SCREAMING_SNAKE_CASE				: e[2]				)
			for i in range(len(_SCREAMING_SNAKE_CASE				) - 1				):
				if edges[i][2] >= edges[i + 1][2]:
					__lowerCAmelCase    :		Dict		    =   edges[i][2] + 1
			for edge in edges:
				__lowerCAmelCase    ,     __lowerCAmelCase    ,     __lowerCAmelCase    :		str		    =   edge
				__lowerCAmelCase    :		Union[str, Any]		    =   weight
				__lowerCAmelCase    :		Optional[int]		    =   weight

		def __str__(   self				):
			__lowerCAmelCase    :		List[Any]		    =   ''
			for tail in self.adjacency:
				for head in self.adjacency[tail]:
					__lowerCAmelCase    :		str		    =   self.adjacency[head][tail]
					string += f"{head} -> {tail} == {weight}\n"
			return string.rstrip('\n'				)

		def 							__lowerCamelCase							(   self				):
			__lowerCAmelCase    :		Tuple		    =   []
			for tail in self.adjacency:
				for head in self.adjacency[tail]:
					output.append((tail, head, self.adjacency[head][tail])				)
			return output

		def 							__lowerCamelCase							(   self				):
			return self.adjacency.keys()

		@staticmethod
		def 							__lowerCamelCase							(   _SCREAMING_SNAKE_CASE=None ,	_SCREAMING_SNAKE_CASE=None				):
			__lowerCAmelCase    :		List[str]		    =   Graph()
			if vertices is None:
				__lowerCAmelCase    :		int		    =   []
			if edges is None:
				__lowerCAmelCase    :		Optional[int]		    =   []
			for vertex in vertices:
				g.add_vertex(_SCREAMING_SNAKE_CASE				)
			for edge in edges:
				g.add_edge(*_SCREAMING_SNAKE_CASE				)
			return g




		class 				A__ :

				def __init__(   self				):
					__lowerCAmelCase    :		Dict		    =   {}
					__lowerCAmelCase    :		Optional[int]		    =   {}

				def __len__(   self				):
					return len(self.parent				)

				def 							__lowerCamelCase							(   self ,	_SCREAMING_SNAKE_CASE				):
					if item in self.parent:
						return self.find(_SCREAMING_SNAKE_CASE				)

					__lowerCAmelCase    :		Dict		    =   item
					__lowerCAmelCase    :		int		    =   0
					return item

				def 							__lowerCamelCase							(   self ,	_SCREAMING_SNAKE_CASE				):
					if item not in self.parent:
						return self.make_set(_SCREAMING_SNAKE_CASE				)
					if item != self.parent[item]:
						__lowerCAmelCase    :		Dict		    =   self.find(self.parent[item]				)
					return self.parent[item]







				def 							__lowerCamelCase							(   self ,	_SCREAMING_SNAKE_CASE ,	_SCREAMING_SNAKE_CASE				):
					__lowerCAmelCase    :		Any		    =   self.find(_SCREAMING_SNAKE_CASE				)
					__lowerCAmelCase    :		List[str]		    =   self.find(_SCREAMING_SNAKE_CASE				)

					if roota == roota:
						return roota

					if self.rank[roota] > self.rank[roota]:
						__lowerCAmelCase    :		Tuple		    =   roota
						return roota

					if self.rank[roota] < self.rank[roota]:
						__lowerCAmelCase    :		str		    =   roota
						return roota

					if self.rank[roota] == self.rank[roota]:
						self.rank[roota] += 1
						__lowerCAmelCase    :		Optional[int]		    =   roota
						return roota
					return None



		@staticmethod
		def 							__lowerCamelCase							(   _SCREAMING_SNAKE_CASE				):
			__lowerCAmelCase    :		Union[str, Any]		    =   graph.num_vertices

			__lowerCAmelCase    :		List[Any]		    =   Graph.UnionFind()
			__lowerCAmelCase    :		Tuple		    =   []
			while num_components > 1:
				__lowerCAmelCase    :		str		    =   {}
				for vertex in graph.get_vertices():
					__lowerCAmelCase    :		Union[str, Any]		    =   -1

				__lowerCAmelCase    :		int		    =   graph.get_edges()
				for edge in edges:
					__lowerCAmelCase    ,     __lowerCAmelCase    ,     __lowerCAmelCase    :		Union[str, Any]		    =   edge
					edges.remove((tail, head, weight)				)
				for edge in edges:
					__lowerCAmelCase    ,     __lowerCAmelCase    ,     __lowerCAmelCase    :		Any		    =   edge
					__lowerCAmelCase    :		Optional[int]		    =   union_find.find(_SCREAMING_SNAKE_CASE				)
					__lowerCAmelCase    :		str		    =   union_find.find(_SCREAMING_SNAKE_CASE				)
					if seta != seta:
						if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
							__lowerCAmelCase    :		List[str]		    =   [head, tail, weight]

						if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
							__lowerCAmelCase    :		List[str]		    =   [head, tail, weight]
				for vertex in cheap_edge:
					if cheap_edge[vertex] != -1:
						__lowerCAmelCase    ,     __lowerCAmelCase    ,     __lowerCAmelCase    :		str		    =   cheap_edge[vertex]
						if union_find.find(_SCREAMING_SNAKE_CASE				) != union_find.find(_SCREAMING_SNAKE_CASE				):
							union_find.union(_SCREAMING_SNAKE_CASE ,	_SCREAMING_SNAKE_CASE				)
							mst_edges.append(cheap_edge[vertex]				)
							__lowerCAmelCase    :		List[str]		    =   num_components - 1
			__lowerCAmelCase    :		Union[str, Any]		    =   Graph.build(edges=_SCREAMING_SNAKE_CASE				)
			return mst