code: def test_inference_masked_lm(self):
      model = TFRobertaPreLayerNormForMaskedLM.from_pretrained(
          "andreasmadsen/efficient_mlm_m0.40"
      )
  
      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(
          [
              [
                  [40.4880, 18.0199, -5.2367],
                  [-1.8877, -4.0885, 10.7085],
                  [-2.2613, -5.6110, 7.2665],
              ]
          ]
      )
      self.assertTrue(
          numpy.allclose(
              output[:, :3, :3].numpy(),
              EXPECTED_SLICE.numpy(),
              atol=1e-4,
          )
      )
  
imports: from __future__ import annotations
  import unittest
  from transformers import RobertaPreLayerNormConfig, 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
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 1 for calling the TFRobertaPreLayerNormModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_masked_lm() without return types