652b3ce2c6870a2357d537c4b87bfe3d300cbc66,GPy/kern/prod.py,prod,dK_dtheta,#prod#Any#Any#Any#Any#,61

Before Change

        self.k2.dK_dtheta(dL_dK*K1, X, X2, k2_target)

        target[:self.k1.Nparam] += k1_target
        target[self.k1.Nparam:] += k2_target

    def dK_dX(self,dL_dK,X,X2,target):
        derivative of the covariance matrix with respect to X.

After Change

            self.k2.dK_dtheta(dL_dK*self._K1, X[:,self.slice2], None, target[self.k1.Nparam:])
        else:
            self.k1.dK_dtheta(dL_dK*self._K2, X[:,self.slice1], X2[:,self.slice1], target[:self.k1.Nparam])
            self.k2.dK_dtheta(dL_dK*self._K1, X[:,self.slice2], X2[:,self.slice2], target[self.k1.Nparam:])

    def Kdiag(self,X,target):
        Compute the diagonal of the covariance matrix associated to X.
        target1 = np.zeros(X.shape[0])

Instances