
"""simple docstring"""




from __future__ import annotations

from typing import Any







class   _lowercase						:



     def __init__(      self ,			__UpperCamelCase  )->					None:
          UpperCAmelCase__							: Union[str, Any] 							=						num_of_nodes
          UpperCAmelCase__							: Optional[int] 							=						[]
          UpperCAmelCase__							: Optional[Any] 							=						{}



     def  lowerCAmelCase__       (      self ,			__UpperCamelCase ,			__UpperCamelCase ,			__UpperCamelCase  )->					None:
          self.m_edges.append([u_node, v_node, weight]  )



     def  lowerCAmelCase__       (      self ,			__UpperCamelCase  )->					int:

          if self.m_component[u_node] == u_node:
               return u_node
          return self.find_component(self.m_component[u_node]  )



     def  lowerCAmelCase__       (      self ,			__UpperCamelCase  )->					None:

          if self.m_component[u_node] != u_node:
               for k in self.m_component:
                    UpperCAmelCase__							: Any 							=						self.find_component(snake_case_  )



     def  lowerCAmelCase__       (      self ,			__UpperCamelCase ,			__UpperCamelCase ,			__UpperCamelCase  )->					None:

          if component_size[u_node] <= component_size[v_node]:
               UpperCAmelCase__							: Tuple 							=						v_node
               component_size[v_node] += component_size[u_node]
               self.set_component(snake_case_  )

          elif component_size[u_node] >= component_size[v_node]:
               UpperCAmelCase__							: Union[str, Any] 							=						self.find_component(snake_case_  )
               component_size[u_node] += component_size[v_node]
               self.set_component(snake_case_  )



     def  lowerCAmelCase__       (      self  )->					None:
          UpperCAmelCase__							: Tuple 							=						[]
          UpperCAmelCase__							: Any 							=						0

          UpperCAmelCase__							: Optional[int] 							=						[-1] * self.m_num_of_nodes

          # A list of components (initialized to all of the nodes)
          for node in range(self.m_num_of_nodes  ):
               self.m_component.update({node: node}  )
               component_size.append(1  )

          UpperCAmelCase__							: Optional[int] 							=						self.m_num_of_nodes

          while num_of_components > 1:
               for edge in self.m_edges:
                    UpperCAmelCase__							,	UpperCAmelCase__							,	UpperCAmelCase__							: Union[str, Any] 							=						edge

                    UpperCAmelCase__							: Dict 							=						self.m_component[u]
                    UpperCAmelCase__							: int 							=						self.m_component[v]

                    if u_component != v_component:

                         for component in (u_component, v_component):
                              if (
                                  minimum_weight_edge[component] == -1
                                  or minimum_weight_edge[component][2] > w
                              ):
                                   UpperCAmelCase__							: Optional[int] 							=						[u, v, w]

               for edge in minimum_weight_edge:
                    if isinstance(snake_case_ ,			snake_case_  ):
                         UpperCAmelCase__							,	UpperCAmelCase__							,	UpperCAmelCase__							: int 							=						edge

                         UpperCAmelCase__							: Optional[Any] 							=						self.m_component[u]
                         UpperCAmelCase__							: int 							=						self.m_component[v]

                         if u_component != v_component:
                              mst_weight += w
                              self.union(snake_case_ ,			snake_case_ ,			snake_case_  )
                              print(F"Added edge [{u} - {v}]\nAdded weight: {w}\n"  )
                              num_of_components -= 1

               UpperCAmelCase__							: Dict 							=						[-1] * self.m_num_of_nodes
          print(F"The total weight of the minimal spanning tree is: {mst_weight}"  )





def 							a__ (				):






     '''simple docstring'''



if __name__ == "__main__":
    import doctest

    doctest.testmod()





"""simple docstring"""




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__      :	Union[str, Any]          =    logging.get_logger(__name__)

A__      :	Optional[int]          =    {
    """microsoft/table-transformer-detection""": (
        """https://huggingface.co/microsoft/table-transformer-detection/resolve/main/config.json"""
    ),
}







class   _lowercase						(       lowerCAmelCase_				):


     '''simple docstring'''





     _A								=							'table-transformer'
     _A								=							['past_key_values']
     _A								=							{
         'hidden_size': 'd_model',
         'num_attention_heads': 'encoder_attention_heads',
     }



     def __init__(      self ,			__UpperCamelCase=True ,			__UpperCamelCase=None ,			__UpperCamelCase=3 ,			__UpperCamelCase=1_00 ,			__UpperCamelCase=6 ,			__UpperCamelCase=20_48 ,			__UpperCamelCase=8 ,			__UpperCamelCase=6 ,			__UpperCamelCase=20_48 ,			__UpperCamelCase=8 ,			__UpperCamelCase=0.0 ,			__UpperCamelCase=0.0 ,			__UpperCamelCase=True ,			__UpperCamelCase="relu" ,			__UpperCamelCase=2_56 ,			__UpperCamelCase=0.1 ,			__UpperCamelCase=0.0 ,			__UpperCamelCase=0.0 ,			__UpperCamelCase=0.02 ,			__UpperCamelCase=1.0 ,			__UpperCamelCase=False ,			__UpperCamelCase="sine" ,			__UpperCamelCase="resnet50" ,			__UpperCamelCase=True ,			__UpperCamelCase=False ,			__UpperCamelCase=1 ,			__UpperCamelCase=5 ,			__UpperCamelCase=2 ,			__UpperCamelCase=1 ,			__UpperCamelCase=1 ,			__UpperCamelCase=5 ,			__UpperCamelCase=2 ,			__UpperCamelCase=0.1 ,			**__UpperCamelCase ,			)->					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."  )
                    UpperCAmelCase__							: Any 							=						CONFIG_MAPPING["resnet"](out_features=["stage4"]  )
               elif isinstance(__UpperCamelCase ,			__UpperCamelCase  ):
                    UpperCAmelCase__							: int 							=						backbone_config.get("model_type"  )
                    UpperCAmelCase__							: Optional[Any] 							=						CONFIG_MAPPING[backbone_model_type]
                    UpperCAmelCase__							: int 							=						config_class.from_dict(__UpperCamelCase  )
               # set timm attributes to None
               UpperCAmelCase__							,	UpperCAmelCase__							,	UpperCAmelCase__							: List[str] 							=						None, None, None

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



     @property
     def  lowerCAmelCase__       (      self  )->					int:
          return self.encoder_attention_heads



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







class   _lowercase						(       lowerCAmelCase_				):


     '''simple docstring'''





     _A								=							version.parse('1.11'				)



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



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



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



