Hey, @amensch I was wondering if I could ask a question about the grad_output (V) in the doublebackward?
From my understanding, grad_output is the gradient of the loss with respect to the output of the function. So, M is d(loss)/df where f = x^3 and the loss is the output of the function. So in effect, d(loss)/df = 1.
I understand that there’s 2 returned gradients where backward1 = M * 3 * x^2 is differentiated with respect to X, and M and then multiplied by V is order to get the correct 2nd order gradient for each variable. Where V would be the derivative of some loss with respect to backward1. But what is this 2nd order loss?
Hopefully, this makes sense!
Thank you!