I used your code to obtain natural samples and adversarial samples in FGSM and FGSM_L2 Three sets of EPS under L2 attack, and then I want to calculate and use them to train the deep kernel.
python train_D.py --epochs 200 --lr 0.002 --id 8 --sigma0 15 --sigma 100 --epsilon 2 --feature_dim 300 --dataset cifar
I ran the above code but showed
No such file or directory: './score_diffusion_t_cifar_stand/scores_cleansingle_vector_norm20perb_image.npy'
I think a natural sample EPS with a quantity of 500 is needed as a reference, so I need to run
python eval_epsad.py --detection_datapath './score_diffusion_t_cifar_stand' \
--num_sub 500 \
--adv_batch_size 500 \
--epsilon 0.01569 \
--diffuse_t 20 \
--single_vector_norm_flag \
--perb_image \
--clean_score_flag
To obtain a natural sample EPS with dimensions (500,3,32,32) stored in a single NPY file
I am not sure if this is the correct idea, and I have run the above code on 3090 for 24 hours and still have no results
I used your code to obtain natural samples and adversarial samples in FGSM and FGSM_L2 Three sets of EPS under L2 attack, and then I want to calculate and use them to train the deep kernel. python train_D.py --epochs 200 --lr 0.002 --id 8 --sigma0 15 --sigma 100 --epsilon 2 --feature_dim 300 --dataset cifar I ran the above code but showed No such file or directory: './score_diffusion_t_cifar_stand/scores_cleansingle_vector_norm20perb_image.npy' I think a natural sample EPS with a quantity of 500 is needed as a reference, so I need to run python eval_epsad.py --detection_datapath './score_diffusion_t_cifar_stand' \ --num_sub 500 \ --adv_batch_size 500 \ --epsilon 0.01569 \ --diffuse_t 20 \ --single_vector_norm_flag \ --perb_image \ --clean_score_flag To obtain a natural sample EPS with dimensions (500,3,32,32) stored in a single NPY file I am not sure if this is the correct idea, and I have run the above code on 3090 for 24 hours and still have no results