Question about creating a custom regression layer in matlab NN toolbox

The information required to create a custom regression layer is given in the link https://www.mathworks.com/help/deeplearning/ug/define-custom-regression-output-layer.html. I have a question about the information given in this link, specifically in step 5 : create a backward loss function. The sample code given is

        function dLdY = backwardLoss(layer, Y, T)
            % Returns the derivatives of the MAE loss with respect to the predictions Y

            R = size(Y,3);
            N = size(Y,4);
            dLdY = sign(Y-T)/(N*R);
        end

Shoudn't there be a summation over the mini-batch size when computing dLdY? Or does the toolbox take care of it internally?