import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin







class __snake_case    (						lowerCamelCase_       ,		unittest.TestCase		):
   lowerCAmelCase_														=							PhobertTokenizer
   lowerCAmelCase_														=							False




   def      __a						(   self      :    List[Any]				):



     """simple docstring"""






     super().setUp()

     # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
     SCREAMING_SNAKE_CASE__      							=				["""T@@""", """i""", """I""", """R@@""", """r""", """e@@"""]
     SCREAMING_SNAKE_CASE__      							=				dict(zip(_lowercase	,     range(len(_lowercase				)				)				)				)
     SCREAMING_SNAKE_CASE__      							=				["""#version: 0.2""", """l à</w>"""]
     SCREAMING_SNAKE_CASE__      							=				{"""unk_token""": """<unk>"""}

     SCREAMING_SNAKE_CASE__      							=				os.path.join(self.tmpdirname	,     VOCAB_FILES_NAMES["""vocab_file"""]				)
     SCREAMING_SNAKE_CASE__      							=				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(_lowercase				)				)




   def      __a						(   self      :    List[Any]	,     **_lowercase      :    Union[str, Any]				):



     """simple docstring"""






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




   def      __a						(   self      :    Dict	,     _lowercase      :    List[str]				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				"""Tôi là VinAI Research"""
     SCREAMING_SNAKE_CASE__      							=				"""T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"""
     return input_text, output_text




   def      __a						(   self      :    List[Any]				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				PhobertTokenizer(self.vocab_file	,     self.merges_file	,     **self.special_tokens_map				)
     SCREAMING_SNAKE_CASE__      							=				"""Tôi là VinAI Research"""
     SCREAMING_SNAKE_CASE__      							=				"""T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h""".split()
     SCREAMING_SNAKE_CASE__      							=				tokenizer.tokenize(_lowercase				)
     print(_lowercase				)
     self.assertListEqual(_lowercase	,     _lowercase				)

     SCREAMING_SNAKE_CASE__      							=				tokens + [tokenizer.unk_token]

     SCREAMING_SNAKE_CASE__      							=				[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(_lowercase				)	,     _lowercase				)

def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	List[Any]     )							-> Any:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__      							=				[0] * len(__UpperCamelCase     )
  SCREAMING_SNAKE_CASE__      							=				[]
  SCREAMING_SNAKE_CASE__      							=				[1] * len(__UpperCamelCase     )

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

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

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

      if long_dist[vertex] + 1 > long_dist[x]:
        SCREAMING_SNAKE_CASE__      							=				long_dist[vertex] + 1

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

  print(max(__UpperCamelCase     )     )


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






longest_distance(graph)
