Hi,
For this to work you need to pass the create_graph=True option to the first .backward() to let it know that you need to be able to call .backward() on the grad itself.
Also if you need the gradient wrt a specific variable, you can use the autograd.grad(outputs, inputs) function to get the derivative of the output(s) wrt the input(s). For example out.backward() is equivalent to autograd.grad(out, model.parameters()).