Hi !
I am working on quantizing a CNN during training.
Each batch iteration, a floating point version of the network should be saved, and a quantized version should be used for forward propagation etc … then the floating point version should be loaded again and the weights should be updated using optimizer.step()
I don’t know what the proper way to copy, modify and load the network is. would you please suggest the best way for this scenario ?
Also, is it optimizer.step() what really updates the weights after back propagation? or does something else do it?
Thank you very much !