def test_iforest():
    X_train = np.array([[0, 1], [1, 2]])
    X_test = np.array([[2, 1], [1, 1]])

    grid = ParameterGrid({"n_estimators": [3],
                          "max_samples": [0.5, 1.0, 3],
                          "bootstrap": [True, False]})

    with ignore_warnings():
        for params in grid:
            IsolationForest(random_state=rng,
                            **params).fit(X_train).predict(X_test)
Composes multiple objects into a one.
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/ensemble/tests/test_iforest.py/test_iforest--crossover with--dataset/ETHPy150Open GoogleCloudPlatform/Data-Pipeline/app/src/clients/gcs.py/Gcs.ComposeObjects