code: def test_prepare_for_model(self):
      tokenizers = self.get_tokenizers(do_lower_case=False)
      for tokenizer in tokenizers:
          # only test prepare_for_model for the slow tokenizer
          if tokenizer.__class__.__name__ == "MarkupLMTokenizerFast":
              continue
          with self.subTest(f"{tokenizer.__class__.__name__}"):
              nodes, xpaths = self.get_nodes_and_xpaths()
              prepared_input_dict = tokenizer.prepare_for_model(
                  nodes, xpaths=xpaths, add_special_tokens=True
              )
  
              input_dict = tokenizer.encode_plus(
                  nodes, xpaths=xpaths, add_special_tokens=True
              )
  
              self.assertEqual(input_dict, prepared_input_dict)
  
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 41 for calling the MarkupLMTokenizationTest obj's underlying member method code with example usage: obj.test_prepare_for_model() without return types