

"""simple docstring"""




from __future__ import annotations

from typing import Any







class   __lowercase      :

  def __init__(	self		:      int       ,A		:      int     ):






   '''simple docstring'''
   UpperCAmelCase__       :	List[str]        =       num_of_nodes
   UpperCAmelCase__       :	list[list[int]]        =       []
   UpperCAmelCase__       :	dict[int, int]        =       {}

  def  __lowercase							(	self		:      Any       ,A		:      int       ,A		:      int       ,A		:      int     ):






   '''simple docstring'''
   self.m_edges.append([u_node, v_node, weight]     )

  def  __lowercase							(	self		:      Tuple       ,A		:      int     ):






   '''simple docstring'''

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

  def  __lowercase							(	self		:      List[Any]       ,A		:      int     ):






   '''simple docstring'''

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

  def  __lowercase							(	self		:      List[str]       ,A		:      list[int]       ,A		:      int       ,A		:      int     ):






   '''simple docstring'''

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

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




  def  __lowercase							(	self		:      int     ):






   '''simple docstring'''
   UpperCAmelCase__       :	Dict        =       []
   UpperCAmelCase__       :	str        =       0

   UpperCAmelCase__       :	list[Any]        =       [-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__       :	Tuple        =       self.m_num_of_nodes

   while num_of_components > 1:
    for edge in self.m_edges:
     UpperCAmelCase__ ,   UpperCAmelCase__ ,   UpperCAmelCase__       :	Optional[int]        =       edge

     UpperCAmelCase__       :	Tuple        =       self.m_component[u]
     UpperCAmelCase__       :	Optional[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(A       ,A     ):
      UpperCAmelCase__ ,   UpperCAmelCase__ ,   UpperCAmelCase__       :	Tuple        =       edge

      UpperCAmelCase__       :	str        =       self.m_component[u]
      UpperCAmelCase__       :	List[str]        =       self.m_component[v]

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

    UpperCAmelCase__       :	Union[str, Any]        =       [-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()










from typing import TYPE_CHECKING

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


_lowercase    	=		{
    "configuration_layoutlmv2": ["LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMv2Config"],
    "processing_layoutlmv2": ["LayoutLMv2Processor"],
    "tokenization_layoutlmv2": ["LayoutLMv2Tokenizer"],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _lowercase    	=		["LayoutLMv2TokenizerFast"]

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _lowercase    	=		["LayoutLMv2FeatureExtractor"]
   _lowercase    	=		["LayoutLMv2ImageProcessor"]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _lowercase    	=		[
       "LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST",
       "LayoutLMv2ForQuestionAnswering",
       "LayoutLMv2ForSequenceClassification",
       "LayoutLMv2ForTokenClassification",
       "LayoutLMv2Layer",
       "LayoutLMv2Model",
       "LayoutLMv2PreTrainedModel",
   ]

if TYPE_CHECKING:
   from .configuration_layoutlmva import LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMvaConfig
   from .processing_layoutlmva import LayoutLMvaProcessor
   from .tokenization_layoutlmva import LayoutLMvaTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor, LayoutLMvaImageProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_layoutlmva import (
          LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST,
          LayoutLMvaForQuestionAnswering,
          LayoutLMvaForSequenceClassification,
          LayoutLMvaForTokenClassification,
          LayoutLMvaLayer,
          LayoutLMvaModel,
          LayoutLMvaPreTrainedModel,
      )
else:
   import sys

   _lowercase    	=		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
