test_torch.py 文件源码

def test_symeig(self):
        xval = torch.rand(100, 3)
        cov = torch.mm(xval.t(), xval)
        rese = torch.zeros(3)
        resv = torch.zeros(3, 3)

        # First call to symeig
        self.assertTrue(resv.is_contiguous(), 'resv is not contiguous')
        torch.symeig(cov.clone(), True, out=(rese, resv))
        ahat = torch.mm(torch.mm(resv, torch.diag(rese)), resv.t())
        self.assertEqual(cov, ahat, 1e-8, 'VeV\' wrong')

        # Second call to symeig
        self.assertFalse(resv.is_contiguous(), 'resv is contiguous')
        torch.symeig(cov.clone(), True, out=(rese, resv))
        ahat = torch.mm(torch.mm(resv, torch.diag(rese)), resv.t())
        self.assertEqual(cov, ahat, 1e-8, 'VeV\' wrong')

        # test non-contiguous
        X = torch.rand(5, 5)
        X = X.t() * X
        e = torch.zeros(4, 2).select(1, 1)
        v = torch.zeros(4, 2, 4)[:, 1]
        self.assertFalse(v.is_contiguous(), 'V is contiguous')
        self.assertFalse(e.is_contiguous(), 'E is contiguous')
        torch.symeig(X, True, out=(e, v))
        Xhat = torch.mm(torch.mm(v, torch.diag(e)), v.t())
        self.assertEqual(X, Xhat, 1e-8, 'VeV\' wrong')