Thanks for your reply. I asked that because of the following (I hope you could shed some light): I have a model that forward-propagates using features a that were calculated as a function of another vector c without pytorch  – I used numpy and then converted a to tensor (that’s why they are not part of the graph, I guess). The output of the model I am working on, a scalar, can be differentiated with respect to c. However, because c is nowhere registered in the computational graph, it will not be possible to compute the derivative of the output with respect to it. Is this correct? And there is no way to compute that gradient with autograd unless c is used somewhere and registered.