Awesome
LMT
Public code for a paper "Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks."
update: Pre-print and code were updated to version 2 (2018/5/23).
How to train:
python3 train.py (configuration-file-name).py
what is the configuration file?
example:
python3 train.py config/parseval_svhn/default.py --gpu 0
How to evaluate with attacks:
python3 evaluate.py (result-dir-of-trained-network) (attack-configuration).py
This script calculates each value in inequality (5) in Sec.6 and create inequality-(attack_name).npy under a specified result directory.
example:
python3 evaluate.py result/config/parseval_svhn/default-00 config/attack/cw_100_1.py
Reference
Y. Tsuzuku, I. Sato, M. Sugiyama: Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks, (2018), url, bibtex