code: def test_get_hyperparameter_search_space_dataset_properties(self):
      # TODO: We do not have any dataset properties for regression, so this
      # test is somewhat stupid
      pass
      """
          full_cs = SimpleRegressionPipeline.get_hyperparameter_search_space()
          cs_mc = SimpleRegressionPipeline.get_hyperparameter_search_space()
          self.assertEqual(full_cs, cs_mc)
  
          cs_ml = SimpleRegressionPipeline.get_hyperparameter_search_space()
          self.assertNotIn('k_nearest_neighbors', str(cs_ml))
          self.assertNotIn('liblinear', str(cs_ml))
          self.assertNotIn('libsvm_svc', str(cs_ml))
          self.assertNotIn('sgd', str(cs_ml))
  
          cs_sp = SimpleRegressionPipeline.get_hyperparameter_search_space(
              sparse=True)
          self.assertNotIn('extra_trees', str(cs_sp))
          self.assertNotIn('gradient_boosting', str(cs_sp))
          self.assertNotIn('random_forest', str(cs_sp))
  
          cs_mc_ml = SimpleRegressionPipeline.get_hyperparameter_search_space()
          self.assertEqual(cs_ml, cs_mc_ml)
  
          self.assertRaisesRegex(ValueError,
                                  "No regressor to build a configuration space "
                                  "for...", SimpleRegressionPipeline.
                                  get_hyperparameter_search_space,
                                  multiclass=True, multilabel=True, sparse=True)
      """
  
imports: import copy
  import itertools
  import resource
  import tempfile
  import numpy
  import sklearn.datasets
  import sklearn.decomposition
  import sklearn.ensemble
  import sklearn.svm
  from ConfigSpace.configuration_space import ConfigurationSpace
  from ConfigSpace.hyperparameters import CategoricalHyperparameter
  from joblib import Memory
  from sklearn.base import clone
  from sklearn.utils.validation import check_is_fitted
  import autosklearn.pipeline.components.feature_preprocessing
  import autosklearn.pipeline.components.regression
  from autosklearn.pipeline.components.base import AutoSklearnChoice, AutoSklearnComponent, AutoSklearnPreprocessingAlgorithm, AutoSklearnRegressionAlgorithm
  from autosklearn.pipeline.constants import DENSE, PREDICTIONS, SIGNED_DATA, SPARSE, UNSIGNED_DATA
  from autosklearn.pipeline.regression import SimpleRegressionPipeline
  from autosklearn.pipeline.util import get_dataset
  import unittest
  import unittest.mock
  from test.test_pipeline.ignored_warnings import ignore_warnings, regressor_warnings
label_desc: Use image node_id 16 for calling the SimpleRegressionPipelineTest obj's underlying member method code with example usage: obj.test_get_hyperparameter_search_space_dataset_properties() without return types