code: def create_and_check_model_for_ctc(
      self, config, input_features, attention_mask
  ):
      config.add_adapter = True
      config.output_hidden_size = 2 * config.hidden_size
      model = MCTCTForCTC(config=config)
      model.to(torch_device)
      model.eval()
      result = model(input_features, attention_mask=attention_mask)
      self.parent.assertEqual(
          result.logits.shape,
          (
              self.batch_size,
              self.adapter_output_seq_length,
              self.vocab_size,
          ),
      )
  
imports: import inspect
  import math
  import unittest
  from datasets import load_dataset
  from transformers import MCTCTConfig, is_torch_available
  from transformers.testing_utils import require_soundfile, require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor, ids_tensor
label_desc: Use image node_id 5 for calling the MCTCTModelTester obj's underlying member method code with example usage: obj.create_and_check_model_for_ctc(config, input_features, attention_mask) without return types