code: def test_inference_masked_lm(self):
      model = TFRobertaForMaskedLM.from_pretrained("roberta-base")
  
      input_ids = tf.constant(
          [[0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]]
      )
      output = model(input_ids)[0]
      expected_shape = [1, 11, 50265]
      self.assertEqual(list(output.numpy().shape), expected_shape)
      # compare the actual values for a slice.
      expected_slice = tf.constant(
          [
              [
                  [33.8802, -4.3103, 22.7761],
                  [4.6539, -2.8098, 13.6253],
                  [1.8228, -3.6898, 8.8600],
              ]
          ]
      )
      self.assertTrue(
          numpy.allclose(
              output[:, :3, :3].numpy(),
              expected_slice.numpy(),
              atol=1e-4,
          )
      )
  
imports: import unittest
  from transformers import RobertaConfig, is_tf_available
  from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, 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 TFRobertaModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_masked_lm() without return types