code: def load_data():
      house_dataset = sklearn.datasets.fetch_california_housing()
      (
          x_train,
          x_test,
          y_train,
          y_test,
      ) = sklearn.model_selection.train_test_split(
          house_dataset.data,
          np.array(house_dataset.target),
          test_size=0.2,
          random_state=42,
      )
      return (x_train, y_train), (x_test, y_test)
  
imports: import numpy
  import pandas
  import sklearn
  import tensorflow
  import autokeras
  from benchmark.experiments import experiment
label_desc: Use image node_id 1 for calling the CaliforniaHousing obj's underlying member method code with example usage: obj.load_data() and returns: x_train,  y_train,  x_test,  y_test