def METHOD_NAME() -> None:
    """
    Tests that the SVGP bound on the likelihood is the same when using
    with and without diagonals when whitening.
    """
    num_latent_gps = default_datum_svgp.Y.shape[1]
    model_1 = SVGP(
        kernel=gpflow.kernels.SquaredExponential(),
        likelihood=default_datum_svgp.lik,
        q_diag=True,
        num_latent_gps=num_latent_gps,
        inducing_variable=default_datum_svgp.Z,
        whiten=True,
    )
    model_2 = SVGP(
        kernel=gpflow.kernels.SquaredExponential(),
        likelihood=default_datum_svgp.lik,
        q_diag=False,
        num_latent_gps=num_latent_gps,
        inducing_variable=default_datum_svgp.Z,
        whiten=True,
    )
    model_1.q_sqrt.assign(default_datum_svgp.qsqrt)
    model_1.q_mu.assign(default_datum_svgp.qmean)
    model_2.q_sqrt.assign(
        np.array(
            [
                np.diag(default_datum_svgp.qsqrt[:, 0]),
                np.diag(default_datum_svgp.qsqrt[:, 1]),
            ]
        )
    )
    model_2.q_mu.assign(default_datum_svgp.qmean)
    assert_allclose(model_1.elbo(default_datum_svgp.data), model_2.elbo(default_datum_svgp.data))