Note: I have been to and read
which are the two tutorials about model parallelism.
They link to this git repo:
which has some files allowing run to train on cifar10 and mnist datasets using a lot of nifty arguments.
However, this code is written in a very esoteric way (from the perspective of someone new to MXNet).
So my question is or topic is basically a tutorial for using multiple gpus.
Something simple like initializing a simple network with gluon and then training it on multiple gpus.
Also explaining what is and how to use
module = mx.module.Module(context=[mx.gpu(0), mx.gpu(2)], ...)
would be nice as the current isolated documentation does not make it very clear (again, from the point of a newcomer, perhaps it makes more sense for those who are more experienced with MXNet).
I appreciate your assistance and clarification in advance.