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()