






'''simple docstring'''





from typing import List

from tokenizers import NormalizedString, PreTokenizedString, normalizers
class 					lowercase							:


    '''simple docstring'''

    def __init__(       self  :  Optional[int]					,  __lowerCamelCase  :  List[Any]  )				->				None:

     '''simple docstring'''




     lowerCamelCase__	=  vocab
     lowerCamelCase__	=  normalizers.BertNormalizer(
         clean_text=__lowerCamelCase					,  handle_chinese_chars=__lowerCamelCase					,  strip_accents=__lowerCamelCase					,  lowercase=__lowerCamelCase					,  )
     try:
      import rjieba
     except ImportError:
      raise ImportError(
          "You need to install rjieba to use RoFormerTokenizer. "
          "See https://pypi.org/project/rjieba/ for installation."  )
     lowerCamelCase__	=  rjieba

    def  a__					(       self  :  Optional[Any]					,  __lowerCamelCase  :  int					,  __lowerCamelCase  :  NormalizedString  )				->				List[NormalizedString]:

     '''simple docstring'''




     lowerCamelCase__	=  []

     # this code slice normalized_string is too slow (6s) but test_alignement_methods can pass
     for token, start, end in self.jieba.tokenize(str(__lowerCamelCase  )					,  hmm=__lowerCamelCase  ):
      if token in self.vocab:
       splits.append(normalized_string[start:end]  )
      else:
       lowerCamelCase__	=  self.normalizers.normalize_str(__lowerCamelCase  ).split()
       for token in token_list:
        if token:
         lowerCamelCase__	=  start + len(__lowerCamelCase  )
         splits.append(normalized_string[start:end]  )
         lowerCamelCase__	=  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  a__					(       self  :  Dict					,  __lowerCamelCase  :  PreTokenizedString  )				->				Optional[int]:

     '''simple docstring'''




     pretok.split(self.jieba_split  )









'''simple docstring'''





def  lowerCamelCase_  (     lowercase__					,  lowercase__):
 lowerCamelCase__	=  len(lowercase__)
 lowerCamelCase__	=  len(lowercase__)
 lowerCamelCase__	=  (
     first_input_list_length
     if first_input_list_length > second_input_list_length
     else second_input_list_length
 )
 lowerCamelCase__	=  []
 for char_count in range(lowercase__):
  if char_count < first_input_list_length:
   output_result_list.append(first_input_list[char_count])
  if char_count < second_input_list_length:
   output_result_list.append(second_input_list[char_count])

 return output_result_list


if __name__ == "__main__":
 print(alternative_list_arrange(["""A""", """B""", """C"""], [1, 2, 3, 4, 5]), end=""" """)

