The backpropagation algorithm is used to compute the gradient of the squared error with respect to the weights and biases of a multilayer network. How would the algorithm be changed if you wanted to compute the gradient with respect to the inputs of the network (i.e., with respect to the elements of the input vector p)? Carefully explain all of your steps, and write out the final algorithm.