def rq(self, tensor: Tensor, pivot_axis: int = -1, non_negative_diagonal: bool = False) -> Tuple[Tensor, Tensor]: if non_negative_diagonal: errstr = "Can't specify non_negative_diagonal with BlockSparse." raise NotImplementedError(errstr) return decompositions.rq(self.bs, tensor, pivot_axis)
def test_rq(dtype, R, R1, num_charges): np.random.seed(10) D = 30 charges = [ BaseCharge(np.random.randint(-5, 6, (D, num_charges)), charge_types=[U1Charge] * num_charges) for n in range(R) ] flows = [True] * R A = BlockSparseTensor.random( [Index(charges[n], flows[n]) for n in range(R)], dtype=dtype) r, q = decompositions.rq(bs, A, R1) res = bs.tensordot(r, q, 1) r_dense, q_dense = np_decompositions.rq(np, A.todense(), R1, False) res2 = np.tensordot(r_dense, q_dense, 1) np.testing.assert_almost_equal(res.todense(), res2)