code: def test_mask_output(self):
      tokenizers = self.get_tokenizers(fast=False, do_lower_case=False)
      for tokenizer in tokenizers:
          with self.subTest(f"{tokenizer.__class__.__name__}"):
              words, boxes = self.get_words_and_boxes()
  
              if (
                  tokenizer.build_inputs_with_special_tokens.__qualname__.split(
                      "."
                  )[
                      0
                  ]
                  != "PreTrainedTokenizer"
                  and "token_type_ids" in tokenizer.model_input_names
              ):
                  information = tokenizer.encode_plus(
                      words, boxes=boxes, add_special_tokens=True
                  )
                  sequences, mask = (
                      information["input_ids"],
                      information["token_type_ids"],
                  )
                  self.assertEqual(len(sequences), len(mask))
  
imports: import inspect
  import shutil
  import tempfile
  import unittest
  from typing import List
  from transformers import AddedToken, LayoutXLMTokenizerFast, SpecialTokensMixin, is_tf_available, is_torch_available, logging
  from transformers.models.layoutxlm.tokenization_layoutxlm import LayoutXLMTokenizer
  from transformers.testing_utils import get_tests_dir, is_pt_tf_cross_test, require_pandas, require_scatter, require_sentencepiece, require_tokenizers, require_torch, slow
  from ...test_tokenization_common import SMALL_TRAINING_CORPUS, TokenizerTesterMixin, filter_non_english, merge_model_tokenizer_mappings
label_desc: Use image node_id 15 for calling the LayoutXLMTokenizationTest obj's underlying member method code with example usage: obj.test_mask_output() without return types