code: def test_check_execution_with_wrong_model_classes(self):
      train = TextData(
          raw_text=["I think therefore I am" for _ in range(20)],
          label=[
              *([0, 0, 1] for _ in range(10)),
              *([0, 1, 1] for _ in range(10)),
          ],
          task_type="text_classification",
      )
      test = train.copy()
      check = TrainTestPerformance()
  
      # Act & Assert
      assert_that(
          calling(check.run).with_args(
              train_dataset=train,
              test_dataset=test,
              train_predictions=list(train.label),
              test_predictions=list(test.label),
              model_classes=["a", "b", "c", "d"],
          ),
          raises(
              DeepchecksValueError,
              "Received model_classes of length 4, but data indicates labels of length 3",
          ),
      )
  
file_path: deepchecks/tests/nlp/checks/model_evaluation/train_test_performance_test.py
imports: import typing
  import pandas
  from hamcrest import *
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.nlp.checks import TrainTestPerformance
  from deepchecks.nlp.text_data import TextData
label_desc: Use image node_id 3 for calling the TestMultilableClassification obj's underlying member method code with example usage: obj.test_check_execution_with_wrong_model_classes() without return types