code: def test_process_multi_label_dataset(self):
      label = ["O I-MISC I-MISC", "O B-MISC I-MISC"]
      label_filepath = tempfile.mktemp(
          suffix="label_file_for_unitest.txt"
      )
      with open(label_filepath, mode="w", encoding="utf-8") as fobj:
          for token in label:
              fobj.write(token)
              fobj.write("\n")
      label_ds = tf.data.TextLineDataset(label_filepath)
      true_res = [[0, 8, 8], [0, 7, 8]]
      label_ds = process_multi_label_dataset(label_ds, self.config)
      iterator = tf.data.make_initializable_iterator(label_ds)
      label_res = iterator.get_next()
  
      with tf.Session() as sess:
          sess.run(iterator.initializer)
          for i in range(len(label)):
              self.assertEqual(
                  list(sess.run(label_res)[:3]), true_res[i]
              )
  
imports: import os
  from pathlib import Path
  import delta.compat
  from absl import logging
  import tempfile
  import numpy
  from delta import PACKAGE_ROOT_DIR
  from delta import utils
  from delta.data.preprocess.text_ops import clean_english_str_tf
  from delta.data.preprocess.text_ops import char_cut_tf
  from delta.data.preprocess.text_ops import tokenize_label
  from delta.data.preprocess.text_ops import tokenize_sentence
  from delta.data.preprocess.text_ops import process_one_label_dataset
  from delta.data.preprocess.text_ops import process_multi_label_dataset
label_desc: Use image node_id 8 for calling the TextOpsTest obj's underlying member method code with example usage: obj.test_process_multi_label_dataset() without return types