d278768807dff0c1920795073a219577571959d7,gpytorch/lazy/kronecker_product_added_diag_lazy_tensor.py,KroneckerProductAddedDiagLazyTensor,inv_quad,#KroneckerProductAddedDiagLazyTensor#Any#Any#,115

Before Change

        svd_list = self._kron_svd()
        noise = self._diag_tensor[0, 0]
        v_matrix = _DiagKroneckerProdLazyTensor(DiagLazyTensor(svd_list[0].S), DiagLazyTensor(svd_list[1].S))
        q_matrix = KroneckerProductLazyTensor(lazify(svd_list[0].U), lazify(svd_list[1].U))
        for sub_ind in range(2, len(svd_list)):
            v_matrix = KroneckerProductLazyTensor(v_matrix, DiagLazyTensor(svd_list[sub_ind].S))
            q_matrix = KroneckerProductLazyTensor(q_matrix, DiagLazyTensor(svd_list[sub_ind].S))

        // TODO: this could be a memory hog.
        inv_mat = DiagLazyTensor(v_matrix.diag() + noise)

        res = q_matrix.t().matmul(tensor)
        res = inv_mat.inverse().matmul(res)

After Change

    def inv_quad(self, tensor, reduce_inv_quad=True):
        // TODO: check stability of numerics here
        svd_list = self._kron_svd
        v_matrix = KroneckerProductLazyTensor(*[DiagLazyTensor(svd_decomp.S) for svd_decomp in svd_list])
        q_matrix = KroneckerProductLazyTensor(*[lazify(svd_decomp.U) for svd_decomp in svd_list])

        // TODO: this could be a memory hog.
        inv_mat = DiagLazyTensor(1.0 / (v_matrix.diag() + self._diag_tensor.diag()))

Instances