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Jump ReLU
For reproducing the results in the paper, I tried to run the white box attack on AlexNet:
python attack_WhiteBox.py --eps 0.01 --test-batch-size 500 --arch AlexLike --resume cifar10_result/AlexLike_baseline.pkl --dataset cifar10 --iter 7 --iter_df 7 --runs 1 --jump 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
which is specified in the trian_protocol.md
However, when jump=0.4, I got results like (I have set iter_tr to 1000)
+--------------+------------+---------+--------------+----------+---------+
| | Clean Data | IFGSM | DeepFool_inf | DeepFool | TR |
+--------------+------------+---------+--------------+----------+---------+
| Accuracy: | 0.8832 | 0.1293 | 0.0 | 0.0 | 0.0005 |
| Rel. Noise: | 0.0 | 0.01453 | 0.06617 | 0.07672 | 0.01547 |
| Abs. Noise: | 0.0 | 0.03598 | 0.1619 | 4.76095 | 0.99368 |
+--------------+------------+---------+--------------+----------+---------+
which is quite different from the result in the paper. From table 2(B) in the paper, the result should be something like:
Clean Data | IFGSM | DeepFool_inf | DeepFool | TR |
JumpReLU (Base) 87.52% | 18.56% | (9.80%) | (10.6%) | (1.7%) |
The accuracy of DeepFool_inf in the paper is 9.80%, however I got 0%.
Did I do anything wrong? How to correctly reproduce the result in the paper?
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