code: def create_and_check_for_masked_lm(
      self,
      config,
      input_ids,
      token_type_ids,
      input_mask,
      sequence_labels,
      token_labels,
      choice_labels,
  ):
      model = TFRobertaPreLayerNormForMaskedLM(config=config)
      result = model([input_ids, input_mask, token_type_ids])
      self.parent.assertEqual(
          result.logits.shape,
          (self.batch_size, self.seq_length, self.vocab_size),
      )
  
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 13 for calling the TFRobertaPreLayerNormModelTester obj's underlying member method code with example usage: obj.create_and_check_for_masked_lm(config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels) without return types