code: def test_inference_model(self):
      model = TFRemBertModel.from_pretrained("google/rembert")
  
      input_ids = tf.constant([[312, 56498, 313, 2125, 313]])
      segment_ids = tf.constant([[0, 0, 0, 1, 1]])
      output = model(
          input_ids,
          token_type_ids=segment_ids,
          output_hidden_states=True,
      )
  
      hidden_size = 1152
  
      expected_shape = [1, 5, hidden_size]
      self.assertEqual(
          output["last_hidden_state"].shape, expected_shape
      )
  
      expected_implementation = tf.constant(
          [
              [
                  [0.0754, -0.2022, 0.1904],
                  [-0.3354, -0.3692, -0.4791],
                  [-0.2314, -0.6729, -0.0749],
                  [-0.0396, -0.3105, -0.4234],
                  [-0.1571, -0.0525, 0.5353],
              ]
          ]
      )
      tf.debugging.assert_near(
          output["last_hidden_state"][:, :, :3],
          expected_implementation,
          atol=1e-4,
      )
  
imports: import unittest
  from transformers import RemBertConfig, is_tf_available
  from transformers.testing_utils import require_tf, slow
  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 1 for calling the TFRemBertModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_model() without return types