





'''simple docstring'''




import os
import unittest

from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer

from ...test_tokenization_common import TokenizerTesterMixin


class 			SCREAMING_SNAKE_CASE   (a__ ,		unittest.TestCase							):
     lowerCAmelCase		      =	PhobertTokenizer
     lowerCAmelCase		      =	False


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          super().setUp()

          # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
          __A						:			str								=	['T@@', 'i', 'I', 'R@@', 'r', 'e@@']
          __A						:			Tuple								=	dict(zip(_UpperCAmelCase						,     range(len(_UpperCAmelCase))))
          __A						:			List[Any]								=	['#version: 0.2', 'l à</w>']
          __A						:			Dict								=	{'unk_token': '<unk>'}

          __A						:			int								=	os.path.join(self.tmpdirname						,     VOCAB_FILES_NAMES['vocab_file'])
          __A						:			int								=	os.path.join(self.tmpdirname						,     VOCAB_FILES_NAMES['merges_file'])

          with open(self.vocab_file						,     'w'						,     encoding='utf-8') as fp:
               for token in vocab_tokens:
                    fp.write(F'{token} {vocab_tokens[token]}\n')
          with open(self.merges_file						,     'w'						,     encoding='utf-8') as fp:
               fp.write('\n'.join(_UpperCAmelCase))


     def 							SCREAMING_SNAKE_CASE  (						self						,     **_UpperCAmelCase):

          '''simple docstring'''






          kwargs.update(self.special_tokens_map)
          return PhobertTokenizer.from_pretrained(self.tmpdirname						,     **_UpperCAmelCase)


     def 							SCREAMING_SNAKE_CASE  (						self						,     _UpperCAmelCase):

          '''simple docstring'''






          __A						:			List[str]								=	'Tôi là VinAI Research'
          __A						:			Union[str, Any]								=	'T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>'
          return input_text, output_text


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						:			str								=	PhobertTokenizer(self.vocab_file						,     self.merges_file						,     **self.special_tokens_map)
          __A						:			Optional[Any]								=	'Tôi là VinAI Research'
          __A						:			Union[str, Any]								=	'T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'.split()
          __A						:			List[str]								=	tokenizer.tokenize(_UpperCAmelCase)
          print(_UpperCAmelCase)
          self.assertListEqual(_UpperCAmelCase						,     _UpperCAmelCase)

          __A						:			Optional[int]								=	tokens + [tokenizer.unk_token]

          __A						:			Tuple								=	[4, 3, 5, 3, 3, 3, 3, 3, 3, 6, 7, 9, 3, 9, 3, 3, 3, 3, 3]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCAmelCase)						,     _UpperCAmelCase)






'''simple docstring'''




def 	_lowerCAmelCase      (  __snake_case  :			str      )					->					str:
     __A						:			Optional[Any]								=	[0] * len(__snake_case      )
     __A						:			Dict								=	[]
     __A						:			Optional[int]								=	[1] * len(__snake_case      )

     for values in graph.values():
          for i in values:
               indegree[i] += 1

     for i in range(len(__snake_case      )      ):
          if indegree[i] == 0:
               queue.append(__snake_case      )

     while queue:
          __A						:			int								=	queue.pop(0      )
          for x in graph[vertex]:
               indegree[x] -= 1

               if long_dist[vertex] + 1 > long_dist[x]:
                    __A						:			str								=	long_dist[vertex] + 1

               if indegree[x] == 0:
                    queue.append(__snake_case      )

     print(max(__snake_case      )      )


# Adjacency list of Graph
lowercase__   :				Dict      =   {0: [2, 3, 4], 1: [2, 7], 2: [5], 3: [5, 7], 4: [7], 5: [6], 6: [7], 7: []}







longest_distance(graph)