2e948d888ab0e40ce43f18914626f956e120c152,GPy/kern/linear.py,linear,psi2,#linear#Any#Any#Any#Any#,118

Before Change

        returns N,M,M matrix
        
        mu2_S = np.square(mu)+S// N,Q,
        ZZ = Z[:,None,:]*Z[None,:,:] // M,M,Q
        psi2 = ZZ*np.square(self.variances)*mu2_S[:, None, None, :]
        target += psi2.sum(-1)

After Change

        
        returns N,M,M matrix
        
        self._psi_computations(Z,mu,S)
        psi2 = self.ZZ*np.square(self.variances)*self.mu2_S[:, None, None, :]
        target += psi2.sum(-1)

    def dpsi2_dtheta(self,partial,Z,mu,S,target):

Instances