import tensorflow as tf

    """
    gh_x, gh_w = hermgauss(num_gauss_hermite_points)
    gh_x = gh_x.reshape(1, -1)
    gh_w = gh_w.reshape(-1, 1) / np.sqrt(np.pi)
    shape = tf.shape(Fmu)
    Fmu, Fvar = [tf.reshape(e, (-1, 1)) for e in (Fmu, Fvar)]
    X = gh_x * tf.sqrt(2.0 * Fvar) + Fmu
    logp = phi(X)
