dad476faf6c1b03d9e940edb65cdcee9b6a36e2c,GPy/kern/_src/linear.py,Linear,psi2,#Linear#Any#Any#,129

Before Change

    def psi2(self, Z, variational_posterior):
        if isinstance(variational_posterior, variational.SpikeAndSlabPosterior):
            gamma = variational_posterior.binary_prob
            mu = variational_posterior.mean
            S = variational_posterior.variance
            mu2 = np.square(mu)
            variances2 = np.square(self.variances)
            tmp = np.einsum("nq,q,mq,nq->nm",gamma,self.variances,Z,mu)
            return np.einsum("nq,q,mq,oq,nq->nmo",gamma,variances2,Z,Z,mu2+S)+\
                np.einsum("nm,no->nmo",tmp,tmp) - np.einsum("nq,q,mq,oq,nq->nmo",np.square(gamma),variances2,Z,Z,mu2)
        else:
            ZA = Z * self.variances
            ZAinner = self._ZAinner(variational_posterior, Z)
            return np.dot(ZAinner, ZA.T)

After Change

    @Cache_this(limit=1)
    def psi2(self, Z, variational_posterior):
        if isinstance(variational_posterior, variational.SpikeAndSlabPosterior):
            return self.psicomp.psicomputations(self.variances, Z, variational_posterior.mean, variational_posterior.variance, variational_posterior.binary_prob)[2]
        else:
            ZA = Z * self.variances
            ZAinner = self._ZAinner(variational_posterior, Z)
            return np.dot(ZAinner, ZA.T)

Instances