code: def test_condition_failed_for_multiclass(
      iris_split_dataset_and_model,
  ):
      train_ds, test_ds, clf = iris_split_dataset_and_model
      # Arrange
      check = SimpleModelComparison(
          strategy="most_frequent"
      ).add_condition_gain_greater_than(0.8)
      # Act X
      result = check.run(train_ds, test_ds, clf)
      # Assert
      assert_that(
          result.conditions_results,
          has_items(
              equal_condition_result(
                  is_pass=False,
                  name="Model performance gain over simple model is greater than 80%",
                  details="Found classes with failed metric's gain: {1: {'F1': '78.15%'}}",
              )
          ),
      )
  
imports: from hamcrest import assert_that, calling, close_to, equal_to, greater_than, has_entries, has_entry, has_items, has_length, is_, raises
  from sklearn.metrics import f1_score, get_scorer, make_scorer, recall_score
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.tabular.checks.model_evaluation import SimpleModelComparison
  from deepchecks.tabular.metric_utils.scorers import get_default_scorers
  from deepchecks.tabular.utils.task_type import TaskType
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 14 for calling a global function with example usage: test_condition_failed_for_multiclass(iris_split_dataset_and_model) without return types