# Codes for "Adversarial Visual Robustness by Causal Intervention"
# Anonymous Supplementary Material

### Baseline Training
Baseline models and other AT or non-AT models all need to use another config file. Take cifar10 as an example:
```
CUDA_VISIBLE_DEVICES=0 python main.py --cfg config/_cifar10.yaml --output_dir checkpoints/cifar10_resnet_baseline  --require_eval --phase train
```
AT settings and non-AT settings can be switched on in the corresponding config file.

### CiiV Training
Using the yaml files in config folder to train the model, for example:
```
CUDA_VISIBLE_DEVICES=0 python main.py --cfg config/_cifar10_ciiv.yaml --output_dir checkpoints/cifar10_resnet_ciiv  --require_eval --phase train
```
All the hyper-parameters are already in the yaml config file.
