code: def test_inference_masked_lm(self):
      model = TFBertForPreTraining.from_pretrained(
          "lysandre/tiny-bert-random"
      )
      input_ids = tf.constant([[0, 1, 2, 3, 4, 5]])
      output = model(input_ids)[0]
  
      expected_shape = [1, 6, 32000]
      self.assertEqual(output.shape, expected_shape)
  
      print(output[:, :3, :3])
  
      expected_slice = tf.constant(
          [
              [
                  [-0.05243197, -0.04498899, 0.05512108],
                  [-0.07444685, -0.01064632, 0.04352357],
                  [-0.05020351, 0.05530146, 0.00700043],
              ]
          ]
      )
      tf.debugging.assert_near(
          output[:, :3, :3], expected_slice, atol=1e-4
      )
  
imports: import unittest
  from transformers import BertConfig, 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, floats_tensor, ids_tensor, random_attention_mask
  from ...utils.test_modeling_tf_core import TFCoreModelTesterMixin
label_desc: Use image node_id 1 for calling the TFBertModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_masked_lm() without return types