code: def test_batch_encoding_word_to_tokens(self):
      tokenizer_r = BertTokenizerFast.from_pretrained("bert-base-cased")
      encoded = tokenizer_r(
          ["Test", "\xad", "test"], is_split_into_words=True
      )
  
      self.assertEqual(
          encoded.word_to_tokens(0), TokenSpan(start=1, end=2)
      )
      self.assertEqual(encoded.word_to_tokens(1), None)
      self.assertEqual(
          encoded.word_to_tokens(2), TokenSpan(start=2, end=3)
      )
  
imports: import os
  import pickle
  import tempfile
  import unittest
  from typing import Callable, Optional
  import numpy
  from transformers import PreTrainedTokenizerFast
  from transformers import BatchEncoding, BertTokenizer, BertTokenizerFast, PreTrainedTokenizer, TensorType, TokenSpan, is_tokenizers_available
  from transformers.models.gpt2.tokenization_gpt2 import GPT2Tokenizer
  from transformers.testing_utils import CaptureStderr, require_flax, require_tf, require_tokenizers, require_torch, slow
label_desc: Use image node_id 9 for calling the TokenizerUtilsTest obj's underlying member method code with example usage: obj.test_batch_encoding_word_to_tokens() without return types