code: def test_jieba_tokenizer():
      tokenizer = JiebaTokenizer()
      gt_zh_tokenized = [
          [
              "苟活",
              "者",
              "在",
              "淡红",
              "的",
              "血色",
              "中",
              "，",
              "会",
              "依稀",
              "看见",
              "微茫",
              "的",
              "希望",
              "；",
              "真的",
              "猛士",
              "，",
              "将",
              "更奋",
              "然而",
              "前行",
              "。",
          ],
          [
              "参加",
              "工作",
              "，",
              "哈尔滨工业大学",
              "无线电",
              "工程系",
              "电子仪器",
              "及",
              "测量",
              "技术",
              "专业",
              "毕业",
              "。",
          ],
      ]
      verify_encode_token(tokenizer, ZH_SAMPLES, gt_zh_tokenized)
      verify_decode(tokenizer, ZH_SAMPLES, str)
      vocab = Vocab(collections.Counter(sum(gt_zh_tokenized, [])))
      verify_decode_no_vocab_raise(tokenizer)
      tokenizer.set_vocab(vocab)
      verify_decode(tokenizer, ZH_SAMPLES, int)
      verify_pickleble(tokenizer, JiebaTokenizer)
  
imports: import pytest
  import random
  import collections
  import pickle
  from uuid import uuid4
  import os
  import unicodedata
  import tempfile
  from pkg_resources import parse_version
  import gluonnlp
  from gluonnlp.data.tokenizers import WhitespaceTokenizer, MosesTokenizer, JiebaTokenizer, SpacyTokenizer, SubwordNMTTokenizer, YTTMTokenizer, SentencepieceTokenizer, HuggingFaceBPETokenizer, HuggingFaceByteBPETokenizer, HuggingFaceWordPieceTokenizer, HuggingFaceTokenizer
  from gluonnlp.base import get_repo_url
  from gluonnlp.data import Vocab, load_vocab
  from gluonnlp.utils.misc import download
  from gluonnlp.models.t5 import T5Tokenizer
label_desc: Use image node_id 14 for calling a global function with example usage: test_jieba_tokenizer() without return types