code: def test_multioutput(self):
      cache = Memory(location=tempfile.gettempdir())
      cached_func = cache.cache(sklearn.datasets.make_regression)
      X, Y = cached_func(
          n_samples=250,
          n_features=20,
          n_informative=9,
          n_targets=4,
          bias=0.5,
          effective_rank=10,
          tail_strength=0.4,
          noise=0.3,
          shuffle=True,
          coef=False,
          random_state=1,
      )
      X_train = X[:200, :]
      Y_train = Y[:200, :]
      X_test = X[200:, :]
      Y_test = Y[200:, :]
  
      data = {
          "X_train": X_train,
          "Y_train": Y_train,
          "X_test": X_test,
          "Y_test": Y_test,
      }
  
      dataset_properties = {"multioutput": True}
      pipeline = SimpleRegressionPipeline(
          dataset_properties=dataset_properties
      )
      cs = pipeline.get_hyperparameter_search_space()
  
      self._test_configurations(
          cs, data=data, dataset_properties=dataset_properties
      )
  
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 7 for calling the SimpleRegressionPipelineTest obj's underlying member method code with example usage: obj.test_multioutput() without return types