#     a, mu, P = x
#     a_mu = a-mu
#     a_mu = tf.expand_dims(a_mu,1)
#     return -0.5*tf.matmul( tf.matmul( a_mu, P ), tf.transpose(a_mu,[0,2,1]) )

    u, mu, p = x
    u_mu = tf.expand_dims(u - mu, -1)
    advan = -tf.matmul(tf.transpose(u_mu, [0, 2, 1]), tf.matmul(p, u_mu))*0.5
    advan = tf.reshape(advan, [-1, 1])
    return advan