code: def test_regression_scoring_functions(self):
      scoring_functions = list(
          autosklearn.metrics.REGRESSION_METRICS.values()
      )
      scoring_functions.remove(
          autosklearn.metrics.root_mean_squared_error
      )
  
      metrics = list(autosklearn.metrics.REGRESSION_METRICS.keys())
      metrics.remove("mean_squared_log_error")
  
      y_true = np.array([1, 2, 3, -4])
      y_pred = y_true.copy()
  
      score_dict = calculate_scores(
          y_true,
          y_pred,
          REGRESSION,
          [autosklearn.metrics.root_mean_squared_error],
          scoring_functions=scoring_functions,
      )
  
      self.assertIsInstance(score_dict, dict)
      self.assertTrue(len(metrics), len(score_dict))
      for metric in metrics:
          self.assertIn(metric, score_dict.keys())
          self.assertAlmostEqual(
              autosklearn.metrics.REGRESSION_METRICS[metric]._optimum,
              score_dict[metric],
          )
  
imports: import warnings
  import numpy
  import sklearn.metrics
  import autosklearn.metrics
  from autosklearn.constants import BINARY_CLASSIFICATION, REGRESSION
  from autosklearn.metrics import calculate_losses, calculate_scores, compute_single_metric
  import pytest
  import unittest
label_desc: Use image node_id 3 for calling the TestCalculateScore obj's underlying member method code with example usage: obj.test_regression_scoring_functions() without return types