'''simple docstring'''
from __future__ import annotations

from typing import Any







class lowerCamelCase							:




  '''simple docstring'''



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






  def  lowerCAmelCase__ (      self			:       Optional[Any]  ,							UpperCAmelCase__			:       int  ,							UpperCAmelCase__			:       int  ,							UpperCAmelCase__			:       int  )				->None:
        self.m_edges.append([u_node, v_node, weight]  )






  def  lowerCAmelCase__ (      self			:       Tuple  ,							UpperCAmelCase__			:       int  )				->int:

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






  def  lowerCAmelCase__ (      self			:       int  ,							UpperCAmelCase__			:       int  )				->None:

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






  def  lowerCAmelCase__ (      self			:       Tuple  ,							UpperCAmelCase__			:       list[int]  ,							UpperCAmelCase__			:       int  ,							UpperCAmelCase__			:       int  )				->None:

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

        elif component_size[u_node] >= component_size[v_node]:
              UpperCAmelCase_            =  self.find_component(UpperCAmelCase__  )
              component_size[u_node] += component_size[v_node]
              self.set_component(UpperCAmelCase__  )






  def  lowerCAmelCase__ (      self			:       int  )				->None:
        UpperCAmelCase_            =  []
        UpperCAmelCase_            =  0

        UpperCAmelCase_            =  [-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_            =  self.m_num_of_nodes

        while num_of_components > 1:
              for edge in self.m_edges:
                    UpperCAmelCase_      ,		UpperCAmelCase_      ,		UpperCAmelCase_            =  edge

                    UpperCAmelCase_            =  self.m_component[u]
                    UpperCAmelCase_            =  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_            =  [u, v, w]

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

                          UpperCAmelCase_            =  self.m_component[u]
                          UpperCAmelCase_            =  self.m_component[v]

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

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






def  __lowerCamelCase       (      ):


      '''simple docstring'''




if __name__ == "__main__":
      import doctest

      doctest.testmod()






'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


lowercase__  :      Union[str, Any]        =					{
    "configuration_mobilevit": ["MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MobileViTConfig", "MobileViTOnnxConfig"],
}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase__  :      Union[str, Any]        =					["MobileViTFeatureExtractor"]
      lowercase__  :      List[Any]        =					["MobileViTImageProcessor"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase__  :      Dict        =					[
          "MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST",
          "MobileViTForImageClassification",
          "MobileViTForSemanticSegmentation",
          "MobileViTModel",
          "MobileViTPreTrainedModel",
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase__  :      Optional[int]        =					[
          "TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST",
          "TFMobileViTForImageClassification",
          "TFMobileViTForSemanticSegmentation",
          "TFMobileViTModel",
          "TFMobileViTPreTrainedModel",
      ]

if TYPE_CHECKING:
      from .configuration_mobilevit import MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, MobileViTConfig, MobileViTOnnxConfig

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_mobilevit import MobileViTFeatureExtractor
            from .image_processing_mobilevit import MobileViTImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_mobilevit import (
                MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                MobileViTForImageClassification,
                MobileViTForSemanticSegmentation,
                MobileViTModel,
                MobileViTPreTrainedModel,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_mobilevit import (
                TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFMobileViTForImageClassification,
                TFMobileViTForSemanticSegmentation,
                TFMobileViTModel,
                TFMobileViTPreTrainedModel,
            )


else:
      import sys

      lowercase__  :      int        =					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





