Implementions of "Edge Enhancement Improves Adversarial Robustness in Image Classification" and other advserarial training method, including Standard Training(ST), Advserarial Training(AT), ALP, TRADES and Avmixup
For MNIST and Tiny ImageNet, we use DataParallel(DP). For ImageNet, we use DistributedDataParallel (DDP).
python experiments_mnist.py --data "MNIST Data" --config "Path of a config in configs_mnist"python experiments_tinyimagenet.py --data "Tiny ImageNet Data" --config "Path of a config in configs_tinyimagenet"python -m torch.distributed.launch --nproc_per_node=int(the numbers of GPUs) --master_port=12345 experiments_imagenet.py --data "ImageNet Data" --config "Path of a config in configs_imagenet"