6ed91ce102545bd90644906876e5e18affe82744,GPy/kern/_src/psi_comp/linear_psi_comp.py,,psicomputations,#Any#Any#Any#,10

Before Change

    mu = variational_posterior.mean
    S = variational_posterior.variance

    psi0 = np.einsum("q,nq->n",variance,np.square(mu)+S)
    psi1 = np.einsum("q,mq,nq->nm",variance,Z,mu)
    psi2 = np.einsum("q,mq,oq,nq->mo",np.square(variance),Z,Z,S) + np.einsum("nm,no->mo",psi1,psi1)

    return psi0, psi1, psi2

After Change

    psi0 = (variance*(np.square(mu)+S)).sum(axis=1)
    psi1 = np.dot(mu,(variance*Z).T)
    psi2 = np.dot(S.sum(axis=0)*np.square(variance)*Z,Z.T)+ tdot(psi1.T)

    return psi0, psi1, psi2

def psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, Z, variational_posterior):

Instances