@property
    def woodbury_chol(self):
        if self._woodbury_chol is None:
            #compute woodbury chol from
            if self._woodbury_inv is not None:
                winv = np.atleast_3d(self._woodbury_inv)
                self._woodbury_chol = np.zeros(winv.shape)
                for p in range(winv.shape[-1]):
                    self._woodbury_chol[:,:,p] = pdinv(winv[:,:,p])[2]
                #Li = jitchol(self._woodbury_inv)
                #self._woodbury_chol, _ = dtrtri(Li)
                #W, _, _, _, = pdinv(self._woodbury_inv)
                #symmetrify(W)
                #self._woodbury_chol = jitchol(W)
            #try computing woodbury chol from cov
            elif self._covariance is not None:
                raise NotImplementedError("TODO: check code here")
                B = self._K - self._covariance
                tmp, _ = dpotrs(self.K_chol, B)
                self._woodbury_inv, _ = dpotrs(self.K_chol, tmp.T)
                _, _, self._woodbury_chol, _ = pdinv(self._woodbury_inv)
            else:
                raise ValueError("insufficient information to compute posterior")
        return self._woodbury_chol
Synchronization should modify asymmetric resources files
dataset/ETHPy150Open SheffieldML/GPy/GPy/inference/latent_function_inference/posterior.py/Posterior.woodbury_chol--crossover with--dataset/ETHPy150Open mozilla/pontoon/pontoon/sync/tests/test_changeset.py/ChangeSetTests.test_obsolete_entities_asymmetric_resources_sync