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2020-02-04 03:38:32 Iteration 1050 Training Loss: 1.387e-01 Loss in Target Net: 2.491e-02 |
2020-02-04 03:41:54 Iteration 1100 Training Loss: 1.346e-01 Loss in Target Net: 2.548e-02 |
2020-02-04 03:45:17 Iteration 1150 Training Loss: 1.370e-01 Loss in Target Net: 2.500e-02 |
2020-02-04 03:48:39 Iteration 1200 Training Loss: 1.387e-01 Loss in Target Net: 2.696e-02 |
2020-02-04 03:52:01 Iteration 1250 Training Loss: 1.341e-01 Loss in Target Net: 2.369e-02 |
2020-02-04 03:55:24 Iteration 1300 Training Loss: 1.348e-01 Loss in Target Net: 2.670e-02 |
2020-02-04 03:58:42 Iteration 1350 Training Loss: 1.356e-01 Loss in Target Net: 2.420e-02 |
2020-02-04 04:02:15 Iteration 1400 Training Loss: 1.361e-01 Loss in Target Net: 2.486e-02 |
2020-02-04 04:06:00 Iteration 1450 Training Loss: 1.349e-01 Loss in Target Net: 2.550e-02 |
2020-02-04 04:09:26 Iteration 1499 Training Loss: 1.370e-01 Loss in Target Net: 2.349e-02 |
Evaluating against victims networks |
DPN92 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 04:10:56, Epoch 0, Iteration 7, loss 0.314 (0.417), acc 88.462 (90.400) |
2020-02-04 04:16:03, Epoch 30, Iteration 7, loss 0.000 (0.000), acc 100.000 (100.000) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-2.0969207, 0.43806347, -0.26123884, -0.84047246, -1.4583348, -3.9328744, 2.596048, -1.3172977, 9.535742, -2.2772706], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-02-04 04:21:57 Epoch 59, Val iteration 0, acc 93.200 (93.200) |
2020-02-04 04:22:51 Epoch 59, Val iteration 19, acc 93.000 (93.010) |
* Prec: 93.0100025177002 |
-------- |
------SUMMARY------ |
TIME ELAPSED (mins): 102 |
TARGET INDEX: 23 |
DPN92 1 |
Namespace(chk_path='chk-black-end2end', chk_subdir='poisons', device='cuda', dset_path='datasets', end2end=True, eval_poison_path='', gpu='8', lr_decay_epoch=[30, 45], mode='mean', model_resume_path='model-chks', nearest=False, net_repeat=3, num_per_class=50, original_grad=True, poison_decay_ites=[], poison_decay_ratio=0.1, poison_epsilon=0.1, poison_ites=1500, poison_label=8, poison_lr=0.04, poison_momentum=0.9, poison_num=5, poison_opt='adam', resume_poison_ite=0, retrain_bsize=64, retrain_epochs=60, retrain_lr=0.0001, retrain_momentum=0.9, retrain_opt='adam', retrain_wd=0.0005, subs_chk_name=['ckpt-%s-4800-dp0.200-droplayer0.000-seed1226.t7', 'ckpt-%s-4800-dp0.250-droplayer0.000-seed1226.t7', 'ckpt-%s-4800-dp0.300-droplayer0.000.t7'], subs_dp=[0.2, 0.25, 0.3], subset_group=0, substitute_nets=['DPN92', 'SENet18', 'ResNet50', 'ResNeXt29_2x64d'], target_index=24, target_label=6, target_net=['DPN92'], test_chk_name='ckpt-%s-4800.t7', tol=1e-06, train_data_path='datasets/CIFAR10_TRAIN_Split.pth') |
Path: chk-black-end2end/mean-3Repeat/1500/24 |
Selected base image indices: [213, 225, 227, 247, 249] |
2020-02-04 02:29:03 Iteration 0 Training Loss: 1.067e+00 Loss in Target Net: 1.414e+00 |
2020-02-04 02:32:23 Iteration 50 Training Loss: 2.202e-01 Loss in Target Net: 7.666e-02 |
2020-02-04 02:35:51 Iteration 100 Training Loss: 1.851e-01 Loss in Target Net: 3.646e-02 |
2020-02-04 02:39:21 Iteration 150 Training Loss: 1.696e-01 Loss in Target Net: 2.940e-02 |
2020-02-04 02:42:49 Iteration 200 Training Loss: 1.618e-01 Loss in Target Net: 2.073e-02 |
2020-02-04 02:46:15 Iteration 250 Training Loss: 1.559e-01 Loss in Target Net: 2.036e-02 |
2020-02-04 02:49:42 Iteration 300 Training Loss: 1.563e-01 Loss in Target Net: 2.348e-02 |
2020-02-04 02:53:09 Iteration 350 Training Loss: 1.521e-01 Loss in Target Net: 2.358e-02 |
2020-02-04 02:56:40 Iteration 400 Training Loss: 1.502e-01 Loss in Target Net: 1.997e-02 |
2020-02-04 03:00:04 Iteration 450 Training Loss: 1.481e-01 Loss in Target Net: 2.241e-02 |
2020-02-04 03:03:29 Iteration 500 Training Loss: 1.504e-01 Loss in Target Net: 1.901e-02 |
2020-02-04 03:06:57 Iteration 550 Training Loss: 1.480e-01 Loss in Target Net: 1.889e-02 |
2020-02-04 03:10:23 Iteration 600 Training Loss: 1.479e-01 Loss in Target Net: 2.306e-02 |
2020-02-04 03:13:47 Iteration 650 Training Loss: 1.461e-01 Loss in Target Net: 2.030e-02 |
2020-02-04 03:17:13 Iteration 700 Training Loss: 1.483e-01 Loss in Target Net: 2.170e-02 |
2020-02-04 03:20:40 Iteration 750 Training Loss: 1.495e-01 Loss in Target Net: 2.219e-02 |
2020-02-04 03:24:06 Iteration 800 Training Loss: 1.447e-01 Loss in Target Net: 2.094e-02 |
2020-02-04 03:27:32 Iteration 850 Training Loss: 1.439e-01 Loss in Target Net: 1.898e-02 |
2020-02-04 03:30:56 Iteration 900 Training Loss: 1.446e-01 Loss in Target Net: 1.913e-02 |
2020-02-04 03:34:23 Iteration 950 Training Loss: 1.445e-01 Loss in Target Net: 1.793e-02 |
2020-02-04 03:37:52 Iteration 1000 Training Loss: 1.438e-01 Loss in Target Net: 1.797e-02 |
2020-02-04 03:41:16 Iteration 1050 Training Loss: 1.428e-01 Loss in Target Net: 2.008e-02 |
2020-02-04 03:44:42 Iteration 1100 Training Loss: 1.456e-01 Loss in Target Net: 1.823e-02 |
2020-02-04 03:48:11 Iteration 1150 Training Loss: 1.436e-01 Loss in Target Net: 1.886e-02 |
2020-02-04 03:51:38 Iteration 1200 Training Loss: 1.421e-01 Loss in Target Net: 2.031e-02 |
2020-02-04 03:55:02 Iteration 1250 Training Loss: 1.441e-01 Loss in Target Net: 2.098e-02 |
2020-02-04 03:58:25 Iteration 1300 Training Loss: 1.430e-01 Loss in Target Net: 1.914e-02 |
2020-02-04 04:02:00 Iteration 1350 Training Loss: 1.445e-01 Loss in Target Net: 2.092e-02 |
2020-02-04 04:05:48 Iteration 1400 Training Loss: 1.417e-01 Loss in Target Net: 2.111e-02 |
2020-02-04 04:09:22 Iteration 1450 Training Loss: 1.414e-01 Loss in Target Net: 1.881e-02 |
2020-02-04 04:12:26 Iteration 1499 Training Loss: 1.423e-01 Loss in Target Net: 2.000e-02 |
Evaluating against victims networks |
DPN92 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 04:13:18, Epoch 0, Iteration 7, loss 0.262 (0.437), acc 92.308 (91.200) |
2020-02-04 04:18:34, Epoch 30, Iteration 7, loss 0.000 (0.000), acc 100.000 (100.000) |
Target Label: 6, Poison label: 8, Prediction:8, Target's Score:[-3.0565276, 0.9272231, -2.603238, -1.2573361, -0.9690539, -2.8595755, 5.6147027, -2.4055736, 8.654967, -1.7730833], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-02-04 04:24:16 Epoch 59, Val iteration 0, acc 93.200 (93.200) |
2020-02-04 04:25:09 Epoch 59, Val iteration 19, acc 94.600 (92.940) |
* Prec: 92.94000091552735 |
-------- |
------SUMMARY------ |
TIME ELAPSED (mins): 104 |
TARGET INDEX: 24 |
DPN92 1 |
Namespace(chk_path='chk-black-end2end', chk_subdir='poisons', device='cuda', dset_path='datasets', end2end=True, eval_poison_path='', gpu='9', lr_decay_epoch=[30, 45], mode='mean', model_resume_path='model-chks', nearest=False, net_repeat=3, num_per_class=50, original_grad=True, poison_decay_ites=[], poison_decay_ratio=0.1, poison_epsilon=0.1, poison_ites=1500, poison_label=8, poison_lr=0.04, poison_momentum=0.9, poison_num=5, poison_opt='adam', resume_poison_ite=0, retrain_bsize=64, retrain_epochs=60, retrain_lr=0.0001, retrain_momentum=0.9, retrain_opt='adam', retrain_wd=0.0005, subs_chk_name=['ckpt-%s-4800-dp0.200-droplayer0.000-seed1226.t7', 'ckpt-%s-4800-dp0.250-droplayer0.000-seed1226.t7', 'ckpt-%s-4800-dp0.300-droplayer0.000.t7'], subs_dp=[0.2, 0.25, 0.3], subset_group=0, substitute_nets=['DPN92', 'SENet18', 'ResNet50', 'ResNeXt29_2x64d'], target_index=25, target_label=6, target_net=['DPN92'], test_chk_name='ckpt-%s-4800.t7', tol=1e-06, train_data_path='datasets/CIFAR10_TRAIN_Split.pth') |
Path: chk-black-end2end/mean-3Repeat/1500/25 |
Selected base image indices: [213, 225, 227, 247, 249] |
2020-02-04 02:28:59 Iteration 0 Training Loss: 9.864e-01 Loss in Target Net: 1.316e+00 |
2020-02-04 02:32:13 Iteration 50 Training Loss: 2.457e-01 Loss in Target Net: 5.340e-02 |
2020-02-04 02:35:37 Iteration 100 Training Loss: 2.097e-01 Loss in Target Net: 5.085e-02 |
2020-02-04 02:38:59 Iteration 150 Training Loss: 1.897e-01 Loss in Target Net: 4.523e-02 |
2020-02-04 02:42:17 Iteration 200 Training Loss: 1.823e-01 Loss in Target Net: 4.698e-02 |
2020-02-04 02:45:37 Iteration 250 Training Loss: 1.774e-01 Loss in Target Net: 4.270e-02 |
2020-02-04 02:48:58 Iteration 300 Training Loss: 1.782e-01 Loss in Target Net: 5.163e-02 |
2020-02-04 02:52:20 Iteration 350 Training Loss: 1.762e-01 Loss in Target Net: 4.096e-02 |
2020-02-04 02:55:40 Iteration 400 Training Loss: 1.700e-01 Loss in Target Net: 4.058e-02 |
2020-02-04 02:59:01 Iteration 450 Training Loss: 1.728e-01 Loss in Target Net: 4.737e-02 |
2020-02-04 03:02:22 Iteration 500 Training Loss: 1.680e-01 Loss in Target Net: 3.798e-02 |
2020-02-04 03:05:42 Iteration 550 Training Loss: 1.678e-01 Loss in Target Net: 3.965e-02 |
2020-02-04 03:09:03 Iteration 600 Training Loss: 1.680e-01 Loss in Target Net: 3.869e-02 |
2020-02-04 03:12:25 Iteration 650 Training Loss: 1.705e-01 Loss in Target Net: 3.804e-02 |
2020-02-04 03:15:45 Iteration 700 Training Loss: 1.669e-01 Loss in Target Net: 4.033e-02 |
2020-02-04 03:19:07 Iteration 750 Training Loss: 1.666e-01 Loss in Target Net: 3.838e-02 |
2020-02-04 03:22:28 Iteration 800 Training Loss: 1.641e-01 Loss in Target Net: 3.920e-02 |
2020-02-04 03:25:51 Iteration 850 Training Loss: 1.649e-01 Loss in Target Net: 4.058e-02 |
2020-02-04 03:29:13 Iteration 900 Training Loss: 1.676e-01 Loss in Target Net: 3.553e-02 |
2020-02-04 03:32:35 Iteration 950 Training Loss: 1.658e-01 Loss in Target Net: 3.825e-02 |
2020-02-04 03:35:56 Iteration 1000 Training Loss: 1.649e-01 Loss in Target Net: 4.161e-02 |
2020-02-04 03:39:19 Iteration 1050 Training Loss: 1.636e-01 Loss in Target Net: 3.880e-02 |
2020-02-04 03:42:40 Iteration 1100 Training Loss: 1.677e-01 Loss in Target Net: 4.052e-02 |
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