cd ../conv
#This is VAR(h)
python bayes_convnet.py -gpu 0,1,2 -n_particles_per_dev 2 -mm_npt 1 -variational f_VAR -mm_jitter 1e-3 -mm_nc 2 -mm_n_inp 4 -max_epoch 200 -stein_method map
#This is VAR-svgd(h)
#python bayes_convnet.py -gpu 0,1,2 -n_particles_per_dev 2 -mm_npt 1 -variational f_VAR -mm_jitter 1e-3 -mm_nc 2 -mm_n_inp 4 -max_epoch 200 -stein_method svgd
#This is f-svgd
#python bayes_convnet.py -gpu 0,1,2 -n_particles_per_dev 2 -mm_npt 1 -variational f_svgd -mm_jitter 1e-3 -mm_nc 2 -mm_n_inp 4 -max_epoch 200 -stein_method svgd
#This is PAC2E
#python bayes_convnet.py -gpu 0,1,2 -n_particles_per_dev 2 -mm_npt 1 -variational f_PAC2E -mm_jitter 1e-3 -mm_nc 2 -mm_n_inp 4 -max_epoch 200 -stein_method svgd


# after training, following is the code for the adversarial attack experiment. please specify the dirctory that contains the training log
#python attack.py ${train_log_dir} (default is /tmp/train_log/cifar_10_f_svgd/somedate)
