code: def test_inference_masked_lm(self):
      model = RoCBertForMaskedLM.from_pretrained(
          "weiweishi/roc-bert-base-zh"
      )
  
      # input_text: ['[CLS]', 'b', 'a', '里', '系', '[MASK]', '国', '的', '首', '都', '[SEP]'] is the adversarial text
      # of ['[CLS]', '巴', '黎', '是', '[MASK]', '国', '的', '首', '都', '[SEP]'], means
      # "Paris is the [MASK] of France" in English
      input_ids = torch.tensor(
          [
              [
                  101,
                  144,
                  143,
                  7027,
                  5143,
                  103,
                  1744,
                  4638,
                  7674,
                  6963,
                  102,
              ]
          ]
      )
      input_shape_ids = torch.tensor(
          [
              [
                  2,
                  20324,
                  23690,
                  8740,
                  706,
                  1,
                  10900,
                  23343,
                  20205,
                  5850,
                  2,
              ]
          ]
      )
      input_pronunciation_ids = torch.tensor(
          [[2, 718, 397, 52, 61, 1, 168, 273, 180, 243, 2]]
      )
  
      output = model(
          input_ids, input_shape_ids, input_pronunciation_ids
      )
      output_ids = torch.argmax(output.logits, dim=2)
  
      # convert to tokens is: ['[CLS]', '巴', '*', '黎', '是', '法', '国', '的', '首', '都', '[SEP]']
      expected_output = torch.tensor(
          [
              [
                  101,
                  2349,
                  115,
                  7944,
                  3221,
                  3791,
                  1744,
                  4638,
                  7674,
                  6963,
                  102,
              ]
          ]
      )
  
      assert torch.allclose(output_ids, expected_output)
  
imports: import unittest
  from transformers import RoCBertConfig, is_torch_available
  from transformers.models.auto import get_values
  from transformers.testing_utils import require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 1 for calling the RoCBertModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_masked_lm() without return types