






import os
import unittest

from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir

from ...test_tokenization_common import TokenizerTesterMixin


UpperCAmelCase__				   =		get_tests_dir("fixtures/test_sentencepiece_bpe.model")






class 		lowercase_					(	lowercase ,  unittest.TestCase   ):






      '''simple docstring'''




      __snake_case       =  BartphoTokenizer
      __snake_case       =  False
      __snake_case       =  True







      def       __lowerCAmelCase					(      self      :						Optional[int]  )    ->Union[str, Any]:




       """simple docstring"""


       super().setUp()

       a		  =      ['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']
       a		  =      dict(zip(__UpperCAmelCase ,					range(len(__UpperCAmelCase  )  )  )  )
       a		  =      {'''unk_token''': '''<unk>'''}

       a		  =      os.path.join(self.tmpdirname ,					VOCAB_FILES_NAMES['''monolingual_vocab_file''']  )
       with open(self.monolingual_vocab_file ,					'''w''' ,					encoding='''utf-8'''  ) as fp:
        for token in vocab_tokens:
         fp.write(F"""{token} {vocab_tokens[token]}\n"""  )

       a		  =      BartphoTokenizer(__UpperCAmelCase ,					self.monolingual_vocab_file ,					**self.special_tokens_map  )
       tokenizer.save_pretrained(self.tmpdirname  )







      def       __lowerCAmelCase					(      self      :						str ,					**__UpperCAmelCase      :						Any  )    ->List[str]:




       """simple docstring"""


       kwargs.update(self.special_tokens_map  )
       return BartphoTokenizer.from_pretrained(self.tmpdirname ,					**__UpperCAmelCase  )







      def       __lowerCAmelCase					(      self      :						str ,					__UpperCAmelCase      :						Union[str, Any]  )    ->List[Any]:




       """simple docstring"""


       a		  =      '''This is a là test'''
       a		  =      '''This is a<unk><unk> test'''
       return input_text, output_text







      def       __lowerCAmelCase					(      self      :						List[str]  )    ->Optional[Any]:




       """simple docstring"""


       a		  =      BartphoTokenizer(__UpperCAmelCase ,					self.monolingual_vocab_file ,					**self.special_tokens_map  )
       a		  =      '''This is a là test'''
       a		  =      '''▁This ▁is ▁a ▁l à ▁t est'''.split()
       a		  =      tokenizer.tokenize(__UpperCAmelCase  )
       self.assertListEqual(__UpperCAmelCase ,					__UpperCAmelCase  )

       a		  =      tokens + [tokenizer.unk_token]
       a		  =      [4, 5, 6, 3, 3, 7, 8, 3]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCAmelCase  ) ,					__UpperCAmelCase  )







"""simple docstring"""
from __future__ import annotations

import os
from collections.abc import Mapping

_lowerCAmelCase    :Tuple     =					tuple[int, int]
class 							_UpperCAmelCase							:





     '''simple docstring'''



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





     def  __lowerCAmelCase	(					self       ,	A       ,	A		)							->					None:
         self.vertices.add(edge[0]		)
         self.vertices.add(edge[1]		)
         _UpperCAmelCase							:  List[Any]											=    weight





     def  __lowerCAmelCase	(					self		)							->					Graph:
         _UpperCAmelCase							:  Graph											=    Graph({min(self.vertices		)}       ,	{}		)
         _UpperCAmelCase							:  EdgeT
         _UpperCAmelCase							:  int
         _UpperCAmelCase							:  EdgeT
         _UpperCAmelCase							:  int

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

             subgraph.add_edge(A       ,	A		)

         return subgraph





def  lowerCamelCase_						(UpperCamelCase__		:		str = "p107_network.txt"							):
    _UpperCAmelCase							:  str											=    os.path.abspath(os.path.dirname(UpperCamelCase__							)							)
    _UpperCAmelCase							:  str											=    os.path.join(UpperCamelCase__     ,       UpperCamelCase__							)
    _UpperCAmelCase							:  dict[EdgeT, int]											=    {}
    _UpperCAmelCase							:  list[str]
    _UpperCAmelCase							:  int
    _UpperCAmelCase							:  int

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

    _UpperCAmelCase							:  List[Any]											=    [line.split(''','''							) for line in data]

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

    _UpperCAmelCase							:  Graph											=    Graph(set(range(len(UpperCamelCase__							)							)							)     ,       UpperCamelCase__							)

    _UpperCAmelCase							:  Graph											=    graph.prims_algorithm()

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

    return initial_total - optimal_total


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


