def METHOD_NAME() -> None:
    """
    In Maximum Likelihood Estimation (MLE), i.e. when there are no priors on
    the parameters, the objective should not depend on any transforms on the
    parameters.
    We use GPR as a simple model that has an objective.
    """
    data = (Datum.X, Datum.Y)
    l_value = Datum.lengthscale
    l_variable = tf.Variable(l_value, dtype=gpflow.default_float(), trainable=True)
    m1 = gpflow.models.GPR(data, kernel=gpflow.kernels.SquaredExponential(lengthscales=l_value))
    m2 = gpflow.models.GPR(data, kernel=gpflow.kernels.SquaredExponential())
    m2.kernel.lengthscales = gpflow.Parameter(l_variable, transform=None)
    assert np.allclose(
        m1.kernel.lengthscales.numpy(), m2.kernel.lengthscales.numpy()
    )  # consistency check
    assert np.allclose(
        m1.log_marginal_likelihood().numpy(), m2.log_marginal_likelihood().numpy()
    ), "MLE objective should not depend on Parameter transform"