| import math | |
| def adjust_learning_rate(optimizer, epoch, args): | |
| """Decay the learning rate with half-cycle cosine after warmup""" | |
| if epoch < args.warmup_epochs: | |
| lr = args.lr * epoch / args.warmup_epochs | |
| else: | |
| if args.lr_schedule == "constant": | |
| lr = args.lr | |
| elif args.lr_schedule == "cosine": | |
| lr = args.min_lr + (args.lr - args.min_lr) * 0.5 * \ | |
| (1. + math.cos(math.pi * (epoch - args.warmup_epochs) / (args.epochs - args.warmup_epochs))) | |
| else: | |
| raise NotImplementedError | |
| for param_group in optimizer.param_groups: | |
| if "lr_scale" in param_group: | |
| param_group["lr"] = lr * param_group["lr_scale"] | |
| else: | |
| param_group["lr"] = lr | |
| return lr | |