code: def test_indices_to_tokens(self):
      allennlp_tokenizer = PretrainedTransformerTokenizer(
          "bert-base-uncased"
      )
      indexer_max_length = PretrainedTransformerIndexer(
          model_name="bert-base-uncased", max_length=4
      )
      indexer_no_max_length = PretrainedTransformerIndexer(
          model_name="bert-base-uncased"
      )
      string_no_specials = "AllenNLP is great"
  
      allennlp_tokens = allennlp_tokenizer.tokenize(string_no_specials)
      vocab = Vocabulary()
      indexed = indexer_no_max_length.tokens_to_indices(
          allennlp_tokens, vocab
      )
      tokens_from_indices = indexer_no_max_length.indices_to_tokens(
          indexed, vocab
      )
  
      self._assert_tokens_equal(allennlp_tokens, tokens_from_indices)
  
      indexed = indexer_max_length.tokens_to_indices(
          allennlp_tokens, vocab
      )
      tokens_from_indices = indexer_max_length.indices_to_tokens(
          indexed, vocab
      )
  
      # For now we are not removing special tokens introduced from max_length
      sep_cls = [allennlp_tokens[-1], allennlp_tokens[0]]
      expected = (
          allennlp_tokens[:3]
          + sep_cls
          + allennlp_tokens[3:5]
          + sep_cls
          + allennlp_tokens[5:]
      )
  
      self._assert_tokens_equal(expected, tokens_from_indices)
  
imports: import pytest
  from allennlp.common import cached_transformers
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.data import Vocabulary
  from allennlp.data.token_indexers import PretrainedTransformerIndexer
  from allennlp.data.tokenizers import PretrainedTransformerTokenizer
label_desc: Use image node_id 12 for calling the TestPretrainedTransformerIndexer obj's underlying member method code with example usage: obj.test_indices_to_tokens() without return types