class_docstr: Apply the jieba tokenizer to tokenize Chinese sentences.
  
  For more details, you may refer to [jieba](https://github.com/fxsjy/jieba)
class_docstr_tok: ["Apply","the","jieba","tokenizer","to","tokenize","Chinese","sentences",".","For","more","details",",","you","may","refer","to","[","jieba","]","(","https",":","\/\/github.com\/fxsjy\/jieba",")"]
code: def decode(self, tokens):
      is_multiple_sentences = is_tokens_from_multiple_sentences(tokens)
      if not is_multiple_sentences:
          tokens = [tokens]
      token_type = get_token_type(tokens)
      if token_type is str:
          ret = ["".join(ele_tokens) for ele_tokens in tokens]
      elif token_type is int:
          if self._vocab is None:
              raise TokenizerDecodeWithoutVocabError
          ret = [
              "".join(self._vocab.to_tokens(ele_tokens))
              for ele_tokens in tokens
          ]
      else:
          raise TokenTypeNotSupportedError(token_type)
      if is_multiple_sentences:
          return ret
      else:
          return ret[0]
  
file_path: gluon-nlp/src/gluonnlp/data/tokenizers/jieba.py
imports: from typing import Optional
  from .base import *
  from ..vocab import Vocab
  from ...utils.lazy_imports import try_import_jieba
label_desc: Use image node_id 4 for calling the JiebaTokenizer obj's underlying member method code with example usage: obj.decode(tokens) and returns: ret, ret