code: def test_inference_masked_lm(self):
      model = TFAlbertForPreTraining.from_pretrained("albert-base-v2")
      input_ids = tf.constant([[0, 1, 2, 3, 4, 5]])
      output = model(input_ids)[0]
  
      expected_shape = [1, 6, 30000]
      self.assertEqual(output.shape, expected_shape)
  
      expected_slice = tf.constant(
          [
              [
                  [4.595668, 0.74462754, -1.818147],
                  [4.5954347, 0.7454184, -1.8188258],
                  [4.5954905, 0.7448235, -1.8182316],
              ]
          ]
      )
      tf.debugging.assert_near(
          output[:, :3, :3], expected_slice, atol=1e-4
      )
  
imports: import unittest
  from transformers import AlbertConfig, is_tf_available
  from transformers.models.auto import get_values
  from transformers.testing_utils import require_tf, slow
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
label_desc: Use image node_id 1 for calling the TFAlbertModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_masked_lm() without return types