Function test_sgpr_qu

tests/gpflow/models/test_sgpr.py:29–44

()

def test_sgpr_qu() -> None:
    rng = np.random.RandomState(1)
    X = to_default_float(Datum.X)
    Z = to_default_float(Datum.Z)
    Y = to_default_float(np.sin(X @ np.array([[-1.4], [0.5]])) + 0.5 * rng.randn(len(X), 1))
    model = gpflow.models.SGPR(
        (X, Y), kernel=gpflow.kernels.SquaredExponential(), inducing_variable=Z
    )

    gpflow.optimizers.Scipy().minimize(model.training_loss, variables=model.trainable_variables)

    qu_mean, qu_cov = model.compute_qu()
    f_at_Z_mean, f_at_Z_cov = model.predict_f(model.inducing_variable.Z, full_cov=True)

    np.testing.assert_allclose(qu_mean, f_at_Z_mean, rtol=1e-5, atol=1e-5)
    np.testing.assert_allclose(tf.reshape(qu_cov, (1, 20, 20)), f_at_Z_cov, rtol=1e-5, atol=1e-5)


def test_sgpr_svgp_qu_equivivalent() -> None: