Im working on multigpu, single gpu and cpu on the same model.
I noticed that dataparallel changes the parameter names appending the names to a “module.” prefix.
eg. from “conv1.weight” to “module.conv1.weight”
This is fine for training, until one needs to load the parameters in a model that is not running DataParallel.
Short of rebuilding the OrderedDict splitting “module.” out of the names; or building a generalized trained model loader that matches partial names and tensor shapes, Is there a generalized way of handling this?
its no biggie, but i rather use a generalized handler if one is available. Im testing inference times on cpu only devices but my training setup is multigpu.
thanks