33e3deed4f0d2df250b4231748d4c5a392b84815,test/test_mkldnn.py,TestMkldnn,test_relu_,#TestMkldnn#,295

Before Change

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

    @unittest.skipIf(IS_WINDOWS, "Limit support for bf16 path")
    def _test_relu_bf16_base(self, name):
        x = torch.randn((4, 5), dtype=torch.float32) * 10

After Change

    def test_relu_(self):
        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.clone())
        y2 = torch.relu_(x2.clone()).to_dense()
        loss1 = y1.sum()
        loss2 = y2.sum()
        loss1.backward()
        loss2.backward()
        self.assertEqual(y1, y2)
        self.assertEqual(x1.grad, x2.grad.to_dense())

    @unittest.skipIf(IS_WINDOWS, "Limit support for bf16 path")

Instances