code: def test_tokenizer_serde_no_fitting():
      tokenizer = text.Tokenizer(num_words=100)
  
      tokenizer_json = tokenizer.to_json()
      recovered = text.tokenizer_from_json(tokenizer_json)
  
      assert tokenizer.get_config() == recovered.get_config()
  
      assert tokenizer.word_docs == recovered.word_docs
      assert tokenizer.word_counts == recovered.word_counts
      assert tokenizer.word_index == recovered.word_index
      assert tokenizer.index_word == recovered.index_word
      assert tokenizer.index_docs == recovered.index_docs
  
imports: from collections import OrderedDict
  import numpy
  import pytest
  from tensorflow import keras
  from keras_preprocessing import text
label_desc: Use image node_id 5 for calling a global function with example usage: test_tokenizer_serde_no_fitting() without return types