code: def test_multi_thread(self):
      text = "The quick brown fox jumps over the lazy dog"
      n = 3
  
      w2v_model_path = os.path.join(
          os.environ["MODEL_DIR"],
          "word",
          "word_embs",
          "GoogleNews-vectors-negative300.bin",
      )
  
      flows = [
          naf.Sequential(
              [
                  naf.Sequential(
                      [
                          nac.OcrAug(),
                          naw.WordEmbsAug(
                              model_type="word2vec",
                              model_path=w2v_model_path,
                          ),
                      ]
                  ),
                  naf.Sequential(
                      [
                          nac.RandomCharAug(),
                      ]
                  ),
                  naw.ContextualWordEmbsAug(
                      model_path="distilroberta-base",
                      action="substitute",
                      device="cpu",
                  ),
              ]
          ),
          naf.Sometimes(
              [
                  naf.Sequential(
                      [
                          nac.OcrAug(),
                          nac.RandomCharAug(),
                      ]
                  ),
                  naf.Sometimes(
                      [
                          naw.WordEmbsAug(
                              model_type="word2vec",
                              model_path=w2v_model_path,
                          )
                      ],
                      aug_p=0.999,
                  ),
                  naw.ContextualWordEmbsAug(
                      model_path="bert-base-cased",
                      action="substitute",
                      device="cpu",
                  ),
              ],
              aug_p=0.9999,
          ),
      ]
  
      for num_thread in [1, 3]:
          for flow in flows:
              augmented_data = flow.augment(
                  text, n=n, num_thread=num_thread
              )
              self.assertEqual(len(augmented_data), n)
  
imports: import unittest
  import os
  import numpy
  from dotenv import load_dotenv
  import nlpaug.augmenter.char
  import nlpaug.augmenter.word
  import nlpaug.augmenter.audio
  import nlpaug.augmenter.spectrogram
  import nlpaug.flow
  from nlpaug.util.audio.loader import AudioLoader
  from nlpaug.util import Action
label_desc: Use image node_id 8 for calling the TestFlow obj's underlying member method code with example usage: obj.test_multi_thread() without return types