code: def test_mask(self):
      # We try these models, because
      #  - BERT pads tokens with 0
      #  - RoBERTa pads tokens with 1
      #  - GPT2 has no padding token, so we choose 0
      for model in ["bert-base-uncased", "roberta-base", "gpt2"]:
          allennlp_tokenizer = PretrainedTransformerTokenizer(model)
          indexer = PretrainedTransformerIndexer(model_name=model)
          string_no_specials = "AllenNLP is great"
          allennlp_tokens = allennlp_tokenizer.tokenize(
              string_no_specials
          )
          vocab = Vocabulary()
          indexed = indexer.tokens_to_indices(allennlp_tokens, vocab)
          expected_masks = [True] * len(indexed["token_ids"])
          assert indexed["mask"] == expected_masks
          max_length = 10
          padding_lengths = {key: max_length for key in indexed.keys()}
          padded_tokens = indexer.as_padded_tensor_dict(
              indexed, padding_lengths
          )
          padding_length = max_length - len(indexed["mask"])
          expected_masks = expected_masks + ([False] * padding_length)
          assert len(padded_tokens["mask"]) == max_length
          assert padded_tokens["mask"].tolist() == expected_masks
  
          assert len(padded_tokens["token_ids"]) == max_length
          pad_token_id = allennlp_tokenizer.tokenizer.pad_token_id
          if pad_token_id is None:
              pad_token_id = 0
          padding_suffix = [pad_token_id] * padding_length
          assert (
              padded_tokens["token_ids"][-padding_length:].tolist()
              == padding_suffix
          )
  
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 8 for calling the TestPretrainedTransformerIndexer obj's underlying member method code with example usage: obj.test_mask() without return types