"""simple docstring"""







import os
import unittest

from transformers import MPNetTokenizerFast
from transformers.models.mpnet.tokenization_mpnet import VOCAB_FILES_NAMES, MPNetTokenizer
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class 							__snake_case(					a__				,	unittest.TestCase	):


    '''simple docstring'''





    _UpperCAmelCase       =			MPNetTokenizer
    _UpperCAmelCase       =			MPNetTokenizerFast
    _UpperCAmelCase       =			True
    _UpperCAmelCase       =			True
    def 						_a							(  self	):




         '''simple docstring'''



         super().setUp()

         __A					:					List[Any]								=		[
             '''[UNK]''',
             '''[CLS]''',
             '''[SEP]''',
             '''[PAD]''',
             '''[MASK]''',
             '''want''',
             '''##want''',
             '''##ed''',
             '''wa''',
             '''un''',
             '''runn''',
             '''##ing''',
             ''',''',
             '''low''',
             '''lowest''',
         ]
         __A					:					Optional[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 						_a							(  self					,       __lowerCamelCase	):




         '''simple docstring'''



         __A					:					Optional[int]								=		'''UNwant\u00E9d,running'''
         __A					:					Dict								=		'''unwanted, running'''
         return input_text, output_text
    def 						_a							(  self	):




         '''simple docstring'''



         __A					:					Dict								=		self.tokenizer_class(self.vocab_file	)

         __A					:					List[str]								=		tokenizer.tokenize('UNwant\u00E9d,running'	)
         self.assertListEqual(lowercase__					,       ['un', '##want', '##ed', ',', 'runn', '##ing']	)
         self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase__	)					,       [9, 6, 7, 12, 10, 11]	)

    @slow
    def 						_a							(  self	):




         '''simple docstring'''



         __A					:					Tuple								=		self.tokenizer_class.from_pretrained('microsoft/mpnet-base'	)

         __A					:					Any								=		tokenizer.encode('sequence builders'					,       add_special_tokens=lowercase__	)
         __A					:					int								=		tokenizer.encode('multi-sequence build'					,       add_special_tokens=lowercase__	)

         __A					:					Any								=		tokenizer.build_inputs_with_special_tokens(lowercase__	)
         __A					:					Dict								=		tokenizer.build_inputs_with_special_tokens(lowercase__					,       lowercase__	)

         assert encoded_sentence == [0] + text + [2]
         assert encoded_pair == [0] + text + [2] + [2] + text_a + [2]










'''simple docstring'''

from __future__ import annotations

import random

# Adjacency list representation of this graph:
# https://en.wikipedia.org/wiki/File:Single_run_of_Karger%E2%80%99s_Mincut_algorithm.svg
UpperCAmelCase       :		List[Any]		=				{
    '1': ['2', '3', '4', '5'],
    '2': ['1', '3', '4', '5'],
    '3': ['1', '2', '4', '5', '10'],
    '4': ['1', '2', '3', '5', '6'],
    '5': ['1', '2', '3', '4', '7'],
    '6': ['7', '8', '9', '10', '4'],
    '7': ['6', '8', '9', '10', '5'],
    '8': ['6', '7', '9', '10'],
    '9': ['6', '7', '8', '10'],
    '10': ['6', '7', '8', '9', '3'],
}




def  _a     (				lowerCAmelCase_						):





      """simple docstring"""



      _snake_case		:						Dict         =  {node: {node} for node in graph}

      _snake_case		:						str         =  {node: graph[node][:] for node in graph}

      while len(lowerCAmelCase_						) > 2:
            # Choose a random edge.
            _snake_case		:						Optional[Any]         =  random.choice(list(graph_copy.keys()						)						)
            _snake_case		:						Union[str, Any]         =  random.choice(graph_copy[u]						)

            # Contract edge (u, v) to new node uv
            _snake_case		:						List[str]         =  u + v
            _snake_case		:						List[str]         =  list(set(graph_copy[u] + graph_copy[v]						)						)
            uv_neighbors.remove(lowerCAmelCase_						)
            uv_neighbors.remove(lowerCAmelCase_						)
            _snake_case		:						Tuple         =  uv_neighbors
            for neighbor in uv_neighbors:
                  graph_copy[neighbor].append(lowerCAmelCase_						)

            _snake_case		:						Tuple         =  set(contracted_nodes[u].union(contracted_nodes[v]						)						)

            # Remove nodes u and v.
            del graph_copy[u]
            del graph_copy[v]
            for neighbor in uv_neighbors:
                  if u in graph_copy[neighbor]:
                        graph_copy[neighbor].remove(lowerCAmelCase_						)
                  if v in graph_copy[neighbor]:
                        graph_copy[neighbor].remove(lowerCAmelCase_						)

    # Find cutset.
      _snake_case		:						Any         =  [contracted_nodes[node] for node in graph_copy]
      return {
          (node, neighbor)
          for node in groups[0]
          for neighbor in graph[node]
          if neighbor in groups[1]
      }


if __name__ == "__main__":
   print(partition_graph(TEST_GRAPH))


