Backpropogation through Maxpool and relu Why is backpropagation through maxpool and relu needed?

Purpose of backpropagation is to update weights while on the other hand maxpool and relu only perform a simple operation on the input. They don't really have any weights or any filters. So why is there a need to backpropagate through them?
Why is backpropagation through maxpool and relu needed?


Any differentiable function (max pool and relu) through which inputs pass will have a gradient.. The nonlinear functions are still functions, so the chain rule still applies here...and hence we have the Gradients flowing through them..This gradient will have to be backpropagated...