JarreNael·4년 전·discussIn PyTorch: a = torch.tensor([2., 3.], requires_grad=True) b = torch.tensor([6., 4.], requires_grad=True) Q = 3*a**3 - b**2 external_grad = torch.tensor([1., 1.]) Q.backward(gradient=external_grad) print(a.grad, b.grad) # the computed gradients. All this is done on the GPU. Automatic Differentiation is the workhorse of modern NN.
All this is done on the GPU. Automatic Differentiation is the workhorse of modern NN.