test.py 文件源码

def test_conv2d_depthwise(self):
        n = 6
        x = Variable(torch.randn(1,n,5,5).double().cuda(), requires_grad=True)
        w = Variable(torch.randn(n,1,3,3).double().cuda(), requires_grad=True)
        y_fast = P.conv2d_depthwise(x, w, padding=1)
        y_ref = F.conv2d(x, w, padding=1, groups=n)
        go = torch.randn(y_fast.size()).double().cuda()

        self.assertLess((y_fast - y_ref).data.abs().max(), 1e-9)

        x.requires_grad = True
        w.requires_grad = True
        y_fast.backward(go)
        gx_fast = x.grad.data.clone()
        gw_fast = w.grad.data.clone()

        x.grad.data.zero_()
        w.grad.data.zero_()
        y_ref.backward(go)
        gx_ref = x.grad.data.clone()
        gw_ref = w.grad.data.clone()

        self.assertTrue(gradcheck(partial(P.conv2d_depthwise, padding=1), (x, w,)))