33e3deed4f0d2df250b4231748d4c5a392b84815,test/test_mkldnn.py,TestMkldnn,test_relu,#TestMkldnn#,291

Before Change

    def test_relu(self):
        x = torch.randn((4, 5), dtype=torch.float32) * 10
        self.assertEqual(torch.relu(x), torch.relu(x.to_mkldnn()).to_dense())

    def test_relu_(self):
        x1 = torch.randn((4, 5), dtype=torch.float32) * 10
        x2 = x1.clone().to_mkldnn()

After Change

        x = torch.randn((4, 5), dtype=torch.float32) * 10
        x1 = x.clone().requires_grad_()
        x2 = x.clone().to_mkldnn().requires_grad_()
        y1 = torch.relu(x1)
        y2 = torch.relu(x2).to_dense()
        loss1 = y1.sum()
        loss2 = y2.sum()
        loss1.backward()
        loss2.backward()
        self.assertEqual(y1, y2)

Instances