scanvi.cuda()
// Setup an optimizer
optim = Adam({"lr": args.learning_rate})
// Tell Pyro to enumerate out y when y is unobserved
guide = config_enumerate(scanvi.guide, "parallel", expand=True)
After Change
// Setup an optimizer (Adam) and learning rate scheduler.
// By default we start with a moderately high learning rate (0.005)
// and reduce by a factor of 5 after 20 epochs.
scheduler = MultiStepLR({"optimizer": Adam,
"optim_args": {"lr": args.learning_rate},
"milestones": [20],
"gamma": 0.2})
// Tell Pyro to enumerate out y when y is unobserved
guide = config_enumerate(scanvi.guide, "parallel", expand=True)
