adfa6de1d87baced85215985da9ed2ce671c2a93,GPy/kern/rbf.py,rbf,dK_dtheta,#rbf#Any#Any#Any#Any#,85

Before Change

        target[0] += np.sum(self._K_dvar*dL_dK)
        if self.ARD == True:
            dl = self._K_dvar[:,:,None]*self.variance*self._K_dist2/self.lengthscale
            target[1:] += (dl*dL_dK[:,:,None]).sum(0).sum(0)
        else:
            target[1] += np.sum(self._K_dvar*self.variance*(self._K_dist2.sum(-1))/self.lengthscale*dL_dK)
        //np.sum(self._K_dvar*self.variance*self._K_dist2/self.lengthscale*dL_dK)

After Change

        self._K_computations(X,X2)
        target[0] += np.sum(self._K_dvar*dL_dK)
        if self.ARD:
            [np.add(target[1+q:2+q],self.variance/self.lengthscale[q]**3*np.sum(self._K_dvar*dL_dK*np.square(X[:,q][:,None]-X2[:,q][None,:])),target[1+q:2+q]) for q in range(self.D)]
        else:
            target[1] += np.sum(self._K_dvar*self.variance*self._K_dist2/self.lengthscale*dL_dK)

Instances