
from __future__ import annotations

import os
from collections.abc import Mapping

lowerCamelCase_						     =					tuple[int, int]




class      __A:

  """simple docstring"""







  def __init__(self	,      SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						):
       UpperCamelCase__				=    vertices
       UpperCamelCase__				=    {
           (min(SCREAMING_SNAKE_CASE_						), max(SCREAMING_SNAKE_CASE_						)): weight for edge, weight in edges.items()
       }







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						):
       self.vertices.add(edge[0]						)
       self.vertices.add(edge[1]						)
       UpperCamelCase__				=    weight







  def 	UpperCAmelCase_ (self						):
       UpperCamelCase__				=    Graph({min(self.vertices						)}	,      {}						)
       UpperCamelCase__				=    42
       UpperCamelCase__				=    42
       UpperCamelCase__				=    42
       UpperCamelCase__				=    42

       while len(subgraph.vertices						) < len(self.vertices						):
            UpperCamelCase__				=    max(self.edges.values()						) + 1
            for edge, weight in self.edges.items():
                 if (edge[0] in subgraph.vertices) ^ (edge[1] in subgraph.vertices):
                      if weight < min_weight:
                           UpperCamelCase__				=    edge
                           UpperCamelCase__				=    weight

            subgraph.add_edge(SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						)

       return subgraph






def 						__magic_name__			(   __a      :	str = "p107_network.txt"						):



     '''simple docstring'''




     UpperCamelCase__				=    os.path.abspath(os.path.dirname(__a						)						)
     UpperCamelCase__				=    os.path.join(__a	,		__a						)
     UpperCamelCase__				=    {}
     UpperCamelCase__				=    42
     UpperCamelCase__				=    42
     UpperCamelCase__				=    42

     with open(__a						) as f:
          UpperCamelCase__				=    f.read().strip().split("""\n"""						)

     UpperCamelCase__				=    [line.split(""","""						) for line in data]

     for edgea in range(1	,		len(__a						)						):
          for edgea in range(__a						):
               if adjaceny_matrix[edgea][edgea] != "-":
                    UpperCamelCase__				=    int(adjaceny_matrix[edgea][edgea]						)

     UpperCamelCase__				=    Graph(set(range(len(__a						)						)						)	,		__a						)

     UpperCamelCase__				=    graph.prims_algorithm()

     UpperCamelCase__				=    sum(graph.edges.values()						)
     UpperCamelCase__				=    sum(subgraph.edges.values()						)

     return initial_total - optimal_total


if __name__ == "__main__":
    print(f'{solution() = }')







import warnings

from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor


lowerCamelCase_						     =					logging.get_logger(__name__)




class      __A(    __lowerCamelCase			):

  """simple docstring"""







  def __init__(self	,      *SCREAMING_SNAKE_CASE_	,      **SCREAMING_SNAKE_CASE_						):
       warnings.warn(
           """The class SegformerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
           """ Please use SegformerImageProcessor instead."""	,      SCREAMING_SNAKE_CASE_	,      )
       super().__init__(*SCREAMING_SNAKE_CASE_	,      **SCREAMING_SNAKE_CASE_						)





