code: def test_build_inputs_with_special_tokens(self):
      if not self.test_slow_tokenizer:
          # as we don't have a slow version, we can't compare the outputs between slow and fast versions
          return
  
      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
          with self.subTest(
              f"{tokenizer.__class__.__name__} ({pretrained_name})"
          ):
              tokenizer_r = self.rust_tokenizer_class.from_pretrained(
                  pretrained_name, **kwargs
              )
              tokenizer_p = self.tokenizer_class.from_pretrained(
                  pretrained_name, **kwargs
              )
  
              # Input tokens id
              nodes, xpaths = self.get_nodes_and_xpaths()
              input_simple = tokenizer_p.encode(
                  nodes, xpaths=xpaths, add_special_tokens=False
              )
              input_pair = tokenizer_p.encode(
                  nodes, xpaths=xpaths, add_special_tokens=False
              )
  
              # Generate output
              output_r = tokenizer_r.build_inputs_with_special_tokens(
                  input_simple
              )
              output_p = tokenizer_p.build_inputs_with_special_tokens(
                  input_simple
              )
              self.assertEqual(output_p, output_r)
  
              # Generate pair output
              output_r = tokenizer_r.build_inputs_with_special_tokens(
                  input_simple, input_pair
              )
              output_p = tokenizer_p.build_inputs_with_special_tokens(
                  input_simple, input_pair
              )
              self.assertEqual(output_p, output_r)
  
imports: import inspect
  import json
  import os
  import re
  import shutil
  import tempfile
  import unittest
  from typing import List
  from transformers import AddedToken, MarkupLMTokenizerFast, SpecialTokensMixin, is_tf_available, is_torch_available, logging
  from transformers.models.markuplm.tokenization_markuplm import VOCAB_FILES_NAMES, MarkupLMTokenizer
  from transformers.testing_utils import is_pt_tf_cross_test, require_tokenizers, require_torch, slow
  from ...test_tokenization_common import SMALL_TRAINING_CORPUS, TokenizerTesterMixin, merge_model_tokenizer_mappings
label_desc: Use image node_id 23 for calling the MarkupLMTokenizationTest obj's underlying member method code with example usage: obj.test_build_inputs_with_special_tokens() without return types