code: def test_auc_on_regression_task_raises_error(
      diabetes, diabetes_model
  ):
      ds, _ = diabetes
  
      # Act & Assert
      auc_deepchecks_scorer = DeepcheckScorer(
          "roc_auc", model_classes=None, observed_classes=None
      )
  
      assert_that(
          calling(auc_deepchecks_scorer).with_args(diabetes_model, ds),
          raises(
              DeepchecksValueError,
              "Can't compute scorer "
              r"make_scorer\(roc_auc_score, needs_threshold=True\) when predicted "
              "probabilities are not provided. Please use a model with predict_proba method or manually "
              r"provide predicted probabilities to the check\.",
          ),
      )
  
      auc_deepchecks_scorer = DeepcheckScorer(
          "roc_auc_ovo", model_classes=None, observed_classes=None
      )
  
      assert_that(
          calling(auc_deepchecks_scorer).with_args(diabetes_model, ds),
          raises(
              DeepchecksValueError,
              "Can't compute scorer "
              r"make_scorer\(roc_auc_score, needs_proba=True, multi_class=ovo\) when predicted "
              "probabilities are not provided. Please use a model with predict_proba method or manually "
              r"provide predicted probabilities to the check\.",
          ),
      )
  
imports: import pandas
  from hamcrest import assert_that, calling, close_to, has_entries, is_, raises
  from sklearn.metrics import log_loss, make_scorer, mean_squared_error
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.tabular import Dataset
  from deepchecks.tabular.metric_utils import DeepcheckScorer
  from deepchecks.tabular.metric_utils.additional_classification_metrics import false_negative_rate_metric, false_positive_rate_metric, true_negative_rate_metric
  from deepchecks.tabular.utils.task_inference import get_all_labels, infer_classes_from_model
  from deepchecks.utils.single_sample_metrics import calculate_neg_cross_entropy_per_sample, calculate_neg_mse_per_sample
  from tests.common import is_nan
label_desc: Use image node_id 10 for calling a global function with example usage: test_auc_on_regression_task_raises_error(diabetes, diabetes_model) without return types