parameters: (self, word, freq=None)
docstring: Add a user defined word to JiebaTokenizer's dictionary.
  
          Args:
              word (str): The word to be added to the JiebaTokenizer instance.
                  The added word will not be written into the built-in dictionary on disk.
              freq (int, optional): The frequency of the word to be added. The higher the frequency,
                  the better chance the word will be tokenized (default=None, use default frequency).
  
          Examples:
              >>> from mindspore.dataset.text import JiebaMode
              >>> jieba_hmm_file = "/path/to/jieba/hmm/file"
              >>> jieba_mp_file = "/path/to/jieba/mp/file"
              >>> jieba_op = text.JiebaTokenizer(jieba_hmm_file, jieba_mp_file, mode=JiebaMode.MP)
              >>> sentence_piece_vocab_file = "/path/to/sentence/piece/vocab/file"
              >>> with open(sentence_piece_vocab_file, 'r') as f:
              ...     for line in f:
              ...         word = line.split(',')[0]
              ...         jieba_op.add_word(word)
              >>> text_file_dataset = text_file_dataset.map(operations=jieba_op, input_columns=["text"])
docstring_summary: Add a user defined word to JiebaTokenizer's dictionary.
docstring_tokens: Add a user defined word to JiebaTokenizer s dictionary .
function: def add_word(self, word, freq=None):
          """
          Add a user defined word to JiebaTokenizer's dictionary.
  
          Args:
              word (str): The word to be added to the JiebaTokenizer instance.
                  The added word will not be written into the built-in dictionary on disk.
              freq (int, optional): The frequency of the word to be added. The higher the frequency,
                  the better chance the word will be tokenized (default=None, use default frequency).
  
          Examples:
              >>> from mindspore.dataset.text import JiebaMode
              >>> jieba_hmm_file = "/path/to/jieba/hmm/file"
              >>> jieba_mp_file = "/path/to/jieba/mp/file"
              >>> jieba_op = text.JiebaTokenizer(jieba_hmm_file, jieba_mp_file, mode=JiebaMode.MP)
              >>> sentence_piece_vocab_file = "/path/to/sentence/piece/vocab/file"
              >>> with open(sentence_piece_vocab_file, 'r') as f:
              ...     for line in f:
              ...         word = line.split(',')[0]
              ...         jieba_op.add_word(word)
              >>> text_file_dataset = text_file_dataset.map(operations=jieba_op, input_columns=["text"])
          """
  
          if freq is None:
              self.words.append((word, 0))
          else:
              self.words.append((word, freq))
function_tokens: def add_word ( self , word , freq = None ) : if freq is None : self . words . append ( ( word , 0 ) ) else : self . words . append ( ( word , freq ) )