code: def test_given_linear_continuous_data_when_using_auto_gluon_regressor_linear_then_provides_good_fit():
      X, y, _ = _generate_linear_data(num_samples=2000, noise_std=0.2)
  
      x_train, x_test, y_train, y_test = train_test_split(
          X, y, test_size=0.5
      )
  
      y_test = shape_into_2d(y_test)
      with tempfile.TemporaryDirectory() as temp_dir:
          model = AutoGluonRegressor(
              path=temp_dir, time_limit=60, hyperparameters={"LR": {}}
          )
          model.fit(x_train, y_train)
  
      assert np.std(model.predict(x_test) - y_test) == approx(
          0.2, abs=1
      )
  
file_path: dowhy/tests/gcm/ml/test_autogluon.py
imports: import tempfile
  import numpy
  from flaky import flaky
  from pytest import approx, importorskip, mark
  from sklearn.model_selection import train_test_split
  from dowhy.gcm.causal_mechanisms import AdditiveNoiseModel, ClassifierFCM
  from dowhy.gcm.ml.autogluon import AutoGluonClassifier, AutoGluonRegressor
  from dowhy.gcm.util.general import shape_into_2d
label_desc: Use image node_id 2 for calling a global function with example usage: test_given_linear_continuous_data_when_using_auto_gluon_regressor_linear_then_provides_good_fit() without return types