automatic differentiation in deep learning figure - computational graph along with the input variables (xyand )we will see the variable awhich is an intermediate variable that stores the computed value of ( )and the variable fwhich stores the final value of ( ) -- * in the forward passwe will substitute the values and arrive at the final value as =- then( ) ( ) - thereforef - we can visualize this using the computational graph shown in figure -