
from __future__ import annotations

import os
from collections.abc import Mapping

lowercase        =  tuple[int, int]





class       __A:

     def __init__(	self					:     Optional[Any]   ,					__UpperCamelCase					:     set[int]   ,					__UpperCamelCase					:     Mapping[EdgeT, int]   ):
            lowerCamelCase_							  =					vertices
            lowerCamelCase_							  =					{
                (min(__UpperCamelCase   ), max(__UpperCamelCase   )): weight for edge, weight in edges.items()
            }

     def    lowercase__      (	self					:     Union[str, Any]   ,					__UpperCamelCase					:     EdgeT   ,					__UpperCamelCase					:     int   ):
            self.vertices.add(edge[0]   )
            self.vertices.add(edge[1]   )
            lowerCamelCase_							  =					weight



     def    lowercase__      (	self					:     List[Any]   ):
            lowerCamelCase_							  =					Graph({min(self.vertices   )}   ,					{}   )
            lowerCamelCase_							  =					4_2
            lowerCamelCase_							  =					4_2
            lowerCamelCase_							  =					4_2
            lowerCamelCase_							  =					4_2

            while len(subgraph.vertices   ) < len(self.vertices   ):
                   lowerCamelCase_							  =					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:
                                        lowerCamelCase_							  =					edge
                                        lowerCamelCase_							  =					weight

                   subgraph.add_edge(__UpperCamelCase   ,					__UpperCamelCase   )

            return subgraph



def      __lowerCAmelCase						(							UpperCAmelCase__				:      str = "p107_network.txt"       )  ->    int:
       lowerCamelCase_							  =					os.path.abspath(os.path.dirname(UpperCAmelCase__       )       )
       lowerCamelCase_							  =					os.path.join(UpperCAmelCase__			,				UpperCAmelCase__       )
       lowerCamelCase_							  =					{}
       lowerCamelCase_							  =					4_2
       lowerCamelCase_							  =					4_2
       lowerCamelCase_							  =					4_2

       with open(UpperCAmelCase__       ) as f:
              lowerCamelCase_							  =					f.read().strip().split("""\n"""       )

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

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

       lowerCamelCase_							  =					Graph(set(range(len(UpperCAmelCase__       )       )       )			,				UpperCAmelCase__       )

       lowerCamelCase_							  =					graph.prims_algorithm()

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

       return initial_total - optimal_total


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







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available


lowercase        =  {'''configuration_speech_encoder_decoder''': ['''SpeechEncoderDecoderConfig''']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase        =  ['''SpeechEncoderDecoderModel''']

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase        =  ['''FlaxSpeechEncoderDecoderModel''']

if TYPE_CHECKING:
		from .configuration_speech_encoder_decoder import SpeechEncoderDecoderConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_speech_encoder_decoder import SpeechEncoderDecoderModel

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_speech_encoder_decoder import FlaxSpeechEncoderDecoderModel

else:
		import sys

		lowercase        =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





