



'''simple docstring'''

from __future__ import annotations

import os
from collections.abc import Mapping

a							   =				tuple[int, int]






class 						a_		:


							def __init__(				self   :						Tuple      ,						a_   :						set[int]      ,						a_   :						Mapping[EdgeT, int]			)			->					None:
										snake_case:    set[int]      							=vertices
										snake_case:    dict[EdgeT, int]      							={
										    (min(a_			), max(a_			)): weight for edge, weight in edges.items()
										}


							def    UpperCamelCase     (				self   :						str      ,						a_   :						EdgeT      ,						a_   :						int			)			->					None:
										self.vertices.add(edge[0]			)
										self.vertices.add(edge[1]			)
										snake_case:    Union[str, Any]      							=weight




							def    UpperCamelCase     (				self   :						Dict			)			->					Graph:
										snake_case:    Graph      							=Graph({min(self.vertices			)}      ,						{}			)
										snake_case:    EdgeT
										snake_case:    int
										snake_case:    EdgeT
										snake_case:    int

										while len(subgraph.vertices			) < len(self.vertices			):
													snake_case:    Tuple      							=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:
																						snake_case:    int      							=edge
																						snake_case:    Optional[int]      							=weight

													subgraph.add_edge(a_      ,						a_			)

										return subgraph







def a_     (    __UpperCAmelCase = "p107_network.txt"					)				->					int:





			"""simple docstring"""







			snake_case:    str      							=os.path.abspath(os.path.dirname(__UpperCAmelCase					)					)
			snake_case:    str      							=os.path.join(__UpperCAmelCase				,							__UpperCAmelCase					)
			snake_case:    dict[EdgeT, int]      							={}
			snake_case:    list[str]
			snake_case:    int
			snake_case:    int

			with open(__UpperCAmelCase					) as f:
						snake_case:    str      							=f.read().strip().split('\n'					)

			snake_case:    Tuple      							=[line.split(','					) for line in data]

			for edgea in range(1				,							len(__UpperCAmelCase					)					):
						for edgea in range(__UpperCAmelCase					):
									if adjaceny_matrix[edgea][edgea] != "-":
												snake_case:    Union[str, Any]      							=int(adjaceny_matrix[edgea][edgea]					)

			snake_case:    Graph      							=Graph(set(range(len(__UpperCAmelCase					)					)					)				,							__UpperCAmelCase					)

			snake_case:    Graph      							=graph.prims_algorithm()

			snake_case:    int      							=sum(graph.edges.values()					)
			snake_case:    int      							=sum(subgraph.edges.values()					)

			return initial_total - optimal_total


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









'''simple docstring'''

import os
import unittest

from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class 						a_		(     snake_case    ,   unittest.TestCase    ):
							UpperCAmelCase			:		int        =				FunnelTokenizer
							UpperCAmelCase			:		Tuple        =				FunnelTokenizerFast
							UpperCAmelCase			:		List[str]        =				True
							UpperCAmelCase			:		Tuple        =				True


							def    UpperCamelCase     (				self   :						Optional[Any]			)			->					Optional[Any]:
										super().setUp()

										snake_case:    Optional[Any]      							=[
										    '<unk>',
										    '<cls>',
										    '<sep>',
										    'want',
										    '##want',
										    '##ed',
										    'wa',
										    'un',
										    'runn',
										    '##ing',
										    ',',
										    'low',
										    'lowest',
										]
										snake_case:    Any      							=os.path.join(self.tmpdirname      ,						VOCAB_FILES_NAMES['vocab_file']			)
										with open(self.vocab_file      ,						'w'      ,						encoding='utf-8'			) as vocab_writer:
													vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]			)			)


							def    UpperCamelCase     (				self   :						Tuple      ,						**a_   :						str			)			->					Any:
										return FunnelTokenizer.from_pretrained(self.tmpdirname      ,						**a_			)


							def    UpperCamelCase     (				self   :						List[Any]      ,						**a_   :						int			)			->					str:
										return FunnelTokenizerFast.from_pretrained(self.tmpdirname      ,						**a_			)


							def    UpperCamelCase     (				self   :						Any      ,						a_   :						Union[str, Any]			)			->					Union[str, Any]:
										snake_case:    List[str]      							='UNwant\u00E9d,running'
										snake_case:    Dict      							='unwanted, running'
										return input_text, output_text


							def    UpperCamelCase     (				self   :						Optional[int]			)			->					List[Any]:
										snake_case:    Union[str, Any]      							=self.tokenizer_class(self.vocab_file			)

										snake_case:    Dict      							=tokenizer.tokenize('UNwant\u00E9d,running'			)
										self.assertListEqual(a_      ,						['un', '##want', '##ed', ',', 'runn', '##ing']			)
										self.assertListEqual(tokenizer.convert_tokens_to_ids(a_			)      ,						[7, 4, 5, 1_0, 8, 9]			)




							def    UpperCamelCase     (				self   :						List[str]			)			->					Dict:
										snake_case:    Optional[Any]      							=self.get_tokenizers(do_lower_case=a_			)
										for tokenizer in tokenizers:
													snake_case:    str      							=tokenizer('UNwant\u00E9d,running'			)
													snake_case:    Union[str, Any]      							=len(inputs['input_ids']			) - 1
													self.assertListEqual(inputs['token_type_ids']      ,						[2] + [0] * sentence_len			)

													snake_case:    List[str]      							=tokenizer('UNwant\u00E9d,running'      ,						'UNwant\u00E9d,running'			)
													self.assertListEqual(inputs['token_type_ids']      ,						[2] + [0] * sentence_len + [1] * sentence_len			)




