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2020-02-04 00:39:19 Iteration 100 Training Loss: 2.414e-01 Loss in Target Net: 1.148e-01 |
2020-02-04 00:42:39 Iteration 150 Training Loss: 2.291e-01 Loss in Target Net: 1.455e-01 |
2020-02-04 00:45:59 Iteration 200 Training Loss: 2.182e-01 Loss in Target Net: 1.198e-01 |
2020-02-04 00:49:21 Iteration 250 Training Loss: 2.120e-01 Loss in Target Net: 1.528e-01 |
2020-02-04 00:52:37 Iteration 300 Training Loss: 2.077e-01 Loss in Target Net: 1.358e-01 |
2020-02-04 00:55:59 Iteration 350 Training Loss: 2.054e-01 Loss in Target Net: 1.342e-01 |
2020-02-04 00:59:22 Iteration 400 Training Loss: 2.038e-01 Loss in Target Net: 1.121e-01 |
2020-02-04 01:02:45 Iteration 450 Training Loss: 2.032e-01 Loss in Target Net: 1.093e-01 |
2020-02-04 01:06:06 Iteration 500 Training Loss: 2.025e-01 Loss in Target Net: 1.293e-01 |
2020-02-04 01:09:30 Iteration 550 Training Loss: 1.976e-01 Loss in Target Net: 1.002e-01 |
2020-02-04 01:12:51 Iteration 600 Training Loss: 1.988e-01 Loss in Target Net: 1.296e-01 |
2020-02-04 01:16:13 Iteration 650 Training Loss: 1.985e-01 Loss in Target Net: 1.243e-01 |
2020-02-04 01:19:35 Iteration 700 Training Loss: 1.935e-01 Loss in Target Net: 9.215e-02 |
2020-02-04 01:22:57 Iteration 750 Training Loss: 1.994e-01 Loss in Target Net: 1.008e-01 |
2020-02-04 01:26:18 Iteration 800 Training Loss: 1.887e-01 Loss in Target Net: 1.044e-01 |
2020-02-04 01:29:42 Iteration 850 Training Loss: 1.951e-01 Loss in Target Net: 9.580e-02 |
2020-02-04 01:33:05 Iteration 900 Training Loss: 1.886e-01 Loss in Target Net: 9.595e-02 |
2020-02-04 01:36:27 Iteration 950 Training Loss: 1.875e-01 Loss in Target Net: 7.346e-02 |
2020-02-04 01:39:48 Iteration 1000 Training Loss: 1.982e-01 Loss in Target Net: 9.997e-02 |
2020-02-04 01:43:10 Iteration 1050 Training Loss: 1.904e-01 Loss in Target Net: 1.064e-01 |
2020-02-04 01:46:32 Iteration 1100 Training Loss: 1.875e-01 Loss in Target Net: 1.096e-01 |
2020-02-04 01:49:53 Iteration 1150 Training Loss: 1.895e-01 Loss in Target Net: 9.593e-02 |
2020-02-04 01:53:15 Iteration 1200 Training Loss: 1.909e-01 Loss in Target Net: 6.983e-02 |
2020-02-04 01:56:36 Iteration 1250 Training Loss: 1.873e-01 Loss in Target Net: 8.101e-02 |
2020-02-04 01:59:58 Iteration 1300 Training Loss: 1.891e-01 Loss in Target Net: 8.129e-02 |
2020-02-04 02:03:19 Iteration 1350 Training Loss: 1.875e-01 Loss in Target Net: 8.225e-02 |
2020-02-04 02:06:40 Iteration 1400 Training Loss: 1.842e-01 Loss in Target Net: 7.693e-02 |
2020-02-04 02:09:52 Iteration 1450 Training Loss: 1.889e-01 Loss in Target Net: 8.289e-02 |
2020-02-04 02:13:31 Iteration 1499 Training Loss: 1.854e-01 Loss in Target Net: 8.716e-02 |
Evaluating against victims networks |
DPN92 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 02:14:24, Epoch 0, Iteration 7, loss 0.266 (0.469), acc 92.308 (90.200) |
2020-02-04 02:19:49, Epoch 30, Iteration 7, loss 0.000 (0.000), acc 100.000 (100.000) |
Target Label: 6, Poison label: 8, Prediction:3, Target's Score:[-2.6449792, -2.5857873, -0.073259346, 7.2257442, -2.2324111, -1.2879597, 4.8474555, -2.9354293, 3.293991, -3.0309472], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-02-04 02:25:24 Epoch 59, Val iteration 0, acc 93.000 (93.000) |
2020-02-04 02:26:17 Epoch 59, Val iteration 19, acc 93.200 (93.000) |
* Prec: 93.00000190734863 |
-------- |
------SUMMARY------ |
TIME ELAPSED (mins): 101 |
TARGET INDEX: 7 |
DPN92 0 |
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=8, 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/1500/8 |
Selected base image indices: [213, 225, 227, 247, 249] |
2020-02-04 00:32:46 Iteration 0 Training Loss: 9.456e-01 Loss in Target Net: 1.119e+00 |
2020-02-04 00:36:06 Iteration 50 Training Loss: 2.417e-01 Loss in Target Net: 1.646e-01 |
2020-02-04 00:39:32 Iteration 100 Training Loss: 2.096e-01 Loss in Target Net: 1.352e-01 |
2020-02-04 00:42:57 Iteration 150 Training Loss: 2.007e-01 Loss in Target Net: 9.136e-02 |
2020-02-04 00:46:21 Iteration 200 Training Loss: 1.950e-01 Loss in Target Net: 9.621e-02 |
2020-02-04 00:49:45 Iteration 250 Training Loss: 1.869e-01 Loss in Target Net: 8.086e-02 |
2020-02-04 00:53:05 Iteration 300 Training Loss: 1.840e-01 Loss in Target Net: 7.603e-02 |
2020-02-04 00:56:30 Iteration 350 Training Loss: 1.811e-01 Loss in Target Net: 8.426e-02 |
2020-02-04 00:59:55 Iteration 400 Training Loss: 1.836e-01 Loss in Target Net: 8.698e-02 |
2020-02-04 01:03:20 Iteration 450 Training Loss: 1.788e-01 Loss in Target Net: 9.068e-02 |
2020-02-04 01:06:44 Iteration 500 Training Loss: 1.786e-01 Loss in Target Net: 7.983e-02 |
2020-02-04 01:10:09 Iteration 550 Training Loss: 1.739e-01 Loss in Target Net: 8.527e-02 |
2020-02-04 01:13:33 Iteration 600 Training Loss: 1.738e-01 Loss in Target Net: 8.538e-02 |
2020-02-04 01:16:57 Iteration 650 Training Loss: 1.731e-01 Loss in Target Net: 9.008e-02 |
2020-02-04 01:20:21 Iteration 700 Training Loss: 1.699e-01 Loss in Target Net: 7.564e-02 |
2020-02-04 01:23:45 Iteration 750 Training Loss: 1.715e-01 Loss in Target Net: 8.135e-02 |
2020-02-04 01:27:09 Iteration 800 Training Loss: 1.744e-01 Loss in Target Net: 7.857e-02 |
2020-02-04 01:30:33 Iteration 850 Training Loss: 1.715e-01 Loss in Target Net: 7.675e-02 |
2020-02-04 01:33:58 Iteration 900 Training Loss: 1.771e-01 Loss in Target Net: 8.173e-02 |
2020-02-04 01:37:22 Iteration 950 Training Loss: 1.710e-01 Loss in Target Net: 7.983e-02 |
2020-02-04 01:40:47 Iteration 1000 Training Loss: 1.727e-01 Loss in Target Net: 7.742e-02 |
2020-02-04 01:44:12 Iteration 1050 Training Loss: 1.699e-01 Loss in Target Net: 8.091e-02 |
2020-02-04 01:47:38 Iteration 1100 Training Loss: 1.696e-01 Loss in Target Net: 7.498e-02 |
2020-02-04 01:51:02 Iteration 1150 Training Loss: 1.723e-01 Loss in Target Net: 7.843e-02 |
2020-02-04 01:54:27 Iteration 1200 Training Loss: 1.704e-01 Loss in Target Net: 7.062e-02 |
2020-02-04 01:57:51 Iteration 1250 Training Loss: 1.695e-01 Loss in Target Net: 7.365e-02 |
2020-02-04 02:01:15 Iteration 1300 Training Loss: 1.698e-01 Loss in Target Net: 6.959e-02 |
2020-02-04 02:04:40 Iteration 1350 Training Loss: 1.741e-01 Loss in Target Net: 7.087e-02 |
2020-02-04 02:08:02 Iteration 1400 Training Loss: 1.699e-01 Loss in Target Net: 7.375e-02 |
2020-02-04 02:11:29 Iteration 1450 Training Loss: 1.732e-01 Loss in Target Net: 7.458e-02 |
2020-02-04 02:15:09 Iteration 1499 Training Loss: 1.676e-01 Loss in Target Net: 7.081e-02 |
Evaluating against victims networks |
DPN92 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-04 02:16:11, Epoch 0, Iteration 7, loss 0.466 (0.458), acc 90.385 (89.800) |
2020-02-04 02:21:28, 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:[0.61989427, -0.6240385, -2.748663, -1.4359447, -3.207033, -2.2536025, 3.0481393, -2.1341903, 9.109847, 0.13551125], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-02-04 02:27:16 Epoch 59, Val iteration 0, acc 95.400 (95.400) |
2020-02-04 02:28:07 Epoch 59, Val iteration 19, acc 93.400 (93.190) |
* Prec: 93.19000244140625 |
-------- |
------SUMMARY------ |
TIME ELAPSED (mins): 103 |
TARGET INDEX: 8 |
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=9, 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/1500/9 |
Selected base image indices: [213, 225, 227, 247, 249] |
2020-02-04 00:32:57 Iteration 0 Training Loss: 1.022e+00 Loss in Target Net: 1.346e+00 |
2020-02-04 00:36:16 Iteration 50 Training Loss: 2.361e-01 Loss in Target Net: 7.037e-02 |
2020-02-04 00:39:39 Iteration 100 Training Loss: 1.982e-01 Loss in Target Net: 4.214e-02 |
2020-02-04 00:43:02 Iteration 150 Training Loss: 1.837e-01 Loss in Target Net: 2.425e-02 |
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