utils.set_use_half(args.half)
utils.show_args(args)
data_loader = load_dataset(args)
model = utils.enable_cuda(resnet.resnet18())
if args.half:
model = network_to_half(model)
criterion = utils.enable_cuda(nn.CrossEntropyLoss())
optimizer = torch.optim.SGD(model.parameters(),
args.lr,
momentum=args.momentum,
weight_decay=args.weight_decay)
optimizer = OptimizerAdapter(optimizer,
half=args.half,
static_loss_scale=args.static_loss_scale,
dynamic_loss_scale=args.dynamic_loss_scale)
model.train()
trainer = Baseline(model=model,
loader=data_loader,
criterion=criterion,
optimizer=optimizer)
trainer.train()
trainer.report_gpu()
trainer.report_train()
