lr = 0.005 if 30 <= epoch < 60 # lr = 0.0005 if 60 <= epoch < 90 # ... scheduler = StepLR(optimizer, step_size=30, gamma=0.1) for epoch in range(100): scheduler.step() train(...)

styles_Y_gram, trainer = get_inits(X, device, lr, styles_Y) scheduler = torch.optim.lr_scheduler.StepLR(trainer, lr_decay_epoch, 0.8) animator = d2l.Animator(xlabel='epoch', ylabel='loss' SGD(net.parameters(), lr=lr, momentum=0.9, weight_decay=wd) scheduler = torch.optim.lr_scheduler.StepLR(trainer, lr_period, lr_decay) num_batches, timer = len(train_iter), d2l.Timer() legend = momentum=0.9, weight_decay=wd) scheduler = torch.optim.lr_scheduler.StepLR(trainer, lr_period, lr_decay) (continues on next page) 13.14. 实战Kaggle比赛：狗的品种识别（ImageNet Dogs）