code: def create_and_check_model(
      self,
      config,
      input_ids,
      bbox,
      pixel_values,
      token_type_ids,
      input_mask,
  ):
      model = TFLayoutLMv3Model(config=config)
  
      # text + image
      result = model(
          input_ids, pixel_values=pixel_values, training=False
      )
      result = model(
          input_ids,
          bbox=bbox,
          pixel_values=pixel_values,
          attention_mask=input_mask,
          token_type_ids=token_type_ids,
          training=False,
      )
      result = model(
          input_ids,
          bbox=bbox,
          pixel_values=pixel_values,
          training=False,
      )
  
      self.parent.assertEqual(
          result.last_hidden_state.shape,
          (self.batch_size, self.seq_length, self.hidden_size),
      )
  
      # text only
      result = model(input_ids, training=False)
      self.parent.assertEqual(
          result.last_hidden_state.shape,
          (self.batch_size, self.text_seq_length, self.hidden_size),
      )
  
      # image only
      result = model({"pixel_values": pixel_values}, training=False)
      self.parent.assertEqual(
          result.last_hidden_state.shape,
          (self.batch_size, self.image_seq_length, self.hidden_size),
      )
  
imports: import copy
  import inspect
  import unittest
  import numpy
  from transformers import is_tf_available, is_vision_available
  from transformers.models.auto import get_values
  from transformers.testing_utils import require_tf, slow
  from transformers.utils import cached_property
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
label_desc: Use image node_id 3 for calling the TFLayoutLMv3ModelTester obj's underlying member method code with example usage: obj.create_and_check_model(config, input_ids, bbox, pixel_values, token_type_ids, input_mask) without return types