automatic differentiation in deep learning figure - computational graph with computed values nowwith automatic differentiationwe would want to find the gradients of with regard to the input variables (xyand zrepresented as and in the feed-forward networkessentiallywe find the gradients of the loss function with respect to the weights to solve thiswe can use the chain rule let' find the partial derivatives for the above equation we know that ( ) and thus az thereforef az ( ( - and az if we go one step furtherwe can find the partial derivatives of with regard to and and