code: def test_regression_metrics(diabetes, diabetes_model):
      ds, _ = diabetes
  
      # Act & Assert
      r_2_deepchecks_scorer = DeepcheckScorer(
          "R2", model_classes=None, observed_classes=None
      )
      score_r_2 = r_2_deepchecks_scorer(diabetes_model, ds)
      assert_that(score_r_2, close_to(0.85, 0.01))
  
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 9 for calling a global function with example usage: test_regression_metrics(diabetes, diabetes_model) without return types