Guys, I am stucking on getting the gradients of a network’s parameters. So basically, what I wanna do is creating a long one-dimensional tensor which stores all the gradients of the parameters(weights, bias) of a network without updating the parameters with Optimizer_Network.step(), the reason why I have to use this one-dimensional tensor is that I have to do some other operations later with it. How can I get it?