code: def test_multilabel_with_incorrect_model_classes(
      text_multilabel_classification_dataset_mock,
  ):
      # Arrange
      check = SingleDatasetPerformance()
  
      # Assert
      assert_that(
          calling(check.run).with_args(
              text_multilabel_classification_dataset_mock,
              model_classes=["meh", "wise"],
          ),
          raises(
              DeepchecksValueError,
              "Received model_classes of length 2, but data indicates labels of length 3",
          ),
      )
  
imports: import numpy
  from hamcrest import assert_that, calling, close_to, equal_to, has_items, raises
  from deepchecks.core.errors import DeepchecksValueError, ValidationError
  from deepchecks.nlp.checks.model_evaluation.single_dataset_performance import SingleDatasetPerformance
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 7 for calling a global function with example usage: test_multilabel_with_incorrect_model_classes(text_multilabel_classification_dataset_mock) without return types