# Model Pretrain
`DANN_cifar10_cifar10c.py`: Apply DANN to cifar10 -> cifar10-c. 
See `./results/pretrain/DANN_cifar10_cifar10c`. 

`DANN_cifar10.py`: Apply DANN to CIFAR10 -> CIFAR10 (sanity check)
See `./results/pretrain/DANN_cifar10`

`main_adv_l2.py`: Apply l2 adversarial training to cifar10
See `./results/pretrain/cifar10_adv_l2_pgd7`

`main_adv_prTTT.py`: Apply linf adversarial TTT pretraining to cifar10, wrt only the classication loss instead of the classication loss + the self-supervision loss. 
See `results/pretrain/cifar10_adv_layer2_gn_expand`

`main_adv.py`: Apply the linf adversarial training to cifar10
See `./results/pretrain/cifar10_adv_pgd7` 

`main_corruption_adv_l2.py`: Apply l2 adversarial training to all cifar10-c datasets (train and test dataset are created by a 80%, 20% split among all severity levels). 
See `results/pretrain/cifar10c_fog_adv_l2_none_gn`

`main_corruption.py`: Run standard training for cifar10-c (train and test dataset are created by a 80%, 20% split among all severity levels)
See `results/pretrain/cifar10c_fog_none_gn`

`main_corruptions_adv.py`: Apply linf adversarial training to all cifar10-c datasets (train and test dataset are created by a 80%, 20% split among all severity levels)
See `results/pretrain/cifar10c_{}_adv_none_gn`

`main.py`: Apply standard training or TTT pretraining to cifar10
See `results/pretrain/cifar10_none_gn` and `results/pretrain/cifar10_layer2_gn_expand`
