code: def test_inference_no_head(self):
      model = TFLayoutLMv3Model.from_pretrained(
          "microsoft/layoutlmv3-base"
      )
  
      feature_extractor = self.default_feature_extractor
      image = prepare_img()
      pixel_values = feature_extractor(
          images=image, return_tensors="tf"
      ).pixel_values
  
      input_ids = tf.constant([[1, 2]])
      bbox = tf.expand_dims(
          tf.constant([[1, 2, 3, 4], [5, 6, 7, 8]]), axis=0
      )
  
      # forward pass
      outputs = model(
          input_ids=input_ids,
          bbox=bbox,
          pixel_values=pixel_values,
          training=False,
      )
  
      # verify the logits
      expected_shape = (1, 199, 768)
      self.assertEqual(outputs.last_hidden_state.shape, expected_shape)
  
      expected_slice = tf.constant(
          [
              [-0.0529, 0.3618, 0.1632],
              [-0.1587, -0.1667, -0.0400],
              [-0.1557, -0.1671, -0.0505],
          ]
      )
  
      self.assertTrue(
          np.allclose(
              outputs.last_hidden_state[0, :3, :3],
              expected_slice,
              atol=1e-4,
          )
      )
  
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 2 for calling the TFLayoutLMv3ModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_no_head() without return types