code: def check_labels_out_of_vocab(self, config, input_features, *args):
      model = MCTCTForCTC(config)
      model.to(torch_device)
      model.train()
  
      input_features = input_features[:3]
  
      input_lengths = [input_features.shape[-1] // i for i in [4, 2, 1]]
      max_length_labels = model._get_feat_extract_output_lengths(
          torch.tensor(input_lengths)
      )
      labels = ids_tensor(
          (input_features.shape[0], max(max_length_labels) - 2),
          model.config.vocab_size + 100,
      )
  
      with self.parent.assertRaises(ValueError):
          model(input_features, labels=labels)
  
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 9 for calling the MCTCTModelTester obj's underlying member method code with example usage: obj.check_labels_out_of_vocab(config, input_features) without return types