



'''simple docstring'''







from typing import List

from tokenizers import NormalizedString, PreTokenizedString, normalizers




class 				__lowerCAmelCase:






			def __init__(   self  :							Union[str, Any]      ,       SCREAMING_SNAKE_CASE  :							Optional[Any]	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Any										=      vocab
					SCREAMING_SNAKE_CASE_						:Optional[Any]										=      normalizers.BertNormalizer(
					    clean_text=SCREAMING_SNAKE_CASE__      ,       handle_chinese_chars=SCREAMING_SNAKE_CASE__      ,       strip_accents=SCREAMING_SNAKE_CASE__      ,       lowercase=SCREAMING_SNAKE_CASE__      ,       )
					try:
							import rjieba
					except ImportError:
							raise ImportError(
							    'You need to install rjieba to use RoFormerTokenizer. '
							    'See https://pypi.org/project/rjieba/ for installation.'	)
					SCREAMING_SNAKE_CASE_						:int										=      rjieba






			def 				_lowercase	(   self  :							int      ,       SCREAMING_SNAKE_CASE  :							Any      ,       SCREAMING_SNAKE_CASE  :							Union[str, Any]	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:List[Any]										=      []

					# this code slice normalized_string is too slow (6s) but test_alignement_methods can pass
					for token, start, end in self.jieba.tokenize(str(SCREAMING_SNAKE_CASE__	)      ,       hmm=SCREAMING_SNAKE_CASE__	):
							if token in self.vocab:
									splits.append(normalized_string[start:end]	)
							else:
									SCREAMING_SNAKE_CASE_						:Dict										=      self.normalizers.normalize_str(SCREAMING_SNAKE_CASE__	).split()
									for token in token_list:
											if token:
													SCREAMING_SNAKE_CASE_						:Any										=      start + len(SCREAMING_SNAKE_CASE__	)
													splits.append(normalized_string[start:end]	)
													SCREAMING_SNAKE_CASE_						:List[str]										=      end

        # this code test_alignement_methods can't pass but fast (300ms)
        # for token in self.jieba.cut(str(normalized_string), False):
        #     if token in self.vocab:
        #         splits.append(NormalizedString(token))
        #     else:
        #         token_list = self.normalizers.normalize_str(token).split()
        #         for token in token_list:
        #             if token:
        #                 splits.append(NormalizedString(token))

					return splits






			def 				_lowercase	(   self  :							Tuple      ,       SCREAMING_SNAKE_CASE  :							List[Any]	):




					"""simple docstring"""







					pretok.split(self.jieba_split	)



"""simple docstring"""




SCREAMING_SNAKE_CASE_  :      Optional[int]							=      {0: [1, 2], 1: [0, 3], 2: [0], 3: [1], 4: [5, 6], 5: [4, 6], 6: [4, 5]}

SCREAMING_SNAKE_CASE_  :      str							=      {0: [1, 2, 3], 1: [0, 3], 2: [0], 3: [0, 1], 4: [], 5: []}



def 						UpperCAmelCase__ (					A__						,     A__						,     A__ )   ->   list:




   """simple docstring"""
   lowerCamelCase__						       =      True
   lowerCamelCase__						       =      []

   for neighbour in graph[vert]:
      if not visited[neighbour]:
         connected_verts += dfs(A__						,     A__						,     A__ )

   return [vert, *connected_verts]



def 						UpperCAmelCase__ (					A__ )   ->   list:




   """simple docstring"""
   lowerCamelCase__						       =      len(A__ )
   lowerCamelCase__						       =      graph_size * [False]
   lowerCamelCase__						       =      []

   for i in range(A__ ):
      if not visited[i]:
         lowerCamelCase__						       =      dfs(A__						,     A__						,     A__ )
         components_list.append(A__ )

   return components_list


if __name__ == "__main__":
     import doctest

     doctest.testmod()




