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DPN92 0 |
Namespace(chk_path='chk-black-end2end', chk_subdir='poisons', device='cuda', dset_path='datasets', end2end=True, eval_poison_path='', gpu='0', lr_decay_epoch=[30, 45], mode='mean', model_resume_path='model-chks', nearest=False, net_repeat=1, num_per_class=50, original_grad=True, poison_decay_ites=[], poison_decay_ratio... |
Path: chk-black-end2end/mean/1500/48 |
Selected base image indices: [213, 225, 227, 247, 249] |
2020-02-02 13:06:21 Iteration 0 Training Loss: 9.982e-01 Loss in Target Net: 1.393e+00 |
2020-02-02 13:06:37 Iteration 50 Training Loss: 2.972e-01 Loss in Target Net: 3.272e-01 |
2020-02-02 13:06:53 Iteration 100 Training Loss: 2.712e-01 Loss in Target Net: 2.612e-01 |
2020-02-02 13:07:10 Iteration 150 Training Loss: 2.570e-01 Loss in Target Net: 2.761e-01 |
2020-02-02 13:07:28 Iteration 200 Training Loss: 2.498e-01 Loss in Target Net: 2.598e-01 |
2020-02-02 13:07:45 Iteration 250 Training Loss: 2.430e-01 Loss in Target Net: 2.764e-01 |
2020-02-02 13:08:02 Iteration 300 Training Loss: 2.423e-01 Loss in Target Net: 3.001e-01 |
2020-02-02 13:08:18 Iteration 350 Training Loss: 2.375e-01 Loss in Target Net: 2.558e-01 |
2020-02-02 13:08:33 Iteration 400 Training Loss: 2.339e-01 Loss in Target Net: 3.228e-01 |
2020-02-02 13:08:49 Iteration 450 Training Loss: 2.369e-01 Loss in Target Net: 2.769e-01 |
2020-02-02 13:09:04 Iteration 500 Training Loss: 2.382e-01 Loss in Target Net: 2.914e-01 |
2020-02-02 13:09:20 Iteration 550 Training Loss: 2.307e-01 Loss in Target Net: 3.020e-01 |
2020-02-02 13:09:37 Iteration 600 Training Loss: 2.309e-01 Loss in Target Net: 3.353e-01 |
2020-02-02 13:09:53 Iteration 650 Training Loss: 2.270e-01 Loss in Target Net: 3.159e-01 |
2020-02-02 13:10:08 Iteration 700 Training Loss: 2.347e-01 Loss in Target Net: 3.106e-01 |
2020-02-02 13:10:24 Iteration 750 Training Loss: 2.363e-01 Loss in Target Net: 2.970e-01 |
2020-02-02 13:10:40 Iteration 800 Training Loss: 2.322e-01 Loss in Target Net: 3.336e-01 |
2020-02-02 13:10:55 Iteration 850 Training Loss: 2.240e-01 Loss in Target Net: 2.887e-01 |
2020-02-02 13:11:11 Iteration 900 Training Loss: 2.251e-01 Loss in Target Net: 2.923e-01 |
2020-02-02 13:11:27 Iteration 950 Training Loss: 2.356e-01 Loss in Target Net: 3.149e-01 |
2020-02-02 13:11:43 Iteration 1000 Training Loss: 2.249e-01 Loss in Target Net: 2.817e-01 |
2020-02-02 13:11:59 Iteration 1050 Training Loss: 2.325e-01 Loss in Target Net: 3.168e-01 |
2020-02-02 13:12:15 Iteration 1100 Training Loss: 2.307e-01 Loss in Target Net: 3.129e-01 |
2020-02-02 13:12:31 Iteration 1150 Training Loss: 2.301e-01 Loss in Target Net: 3.592e-01 |
2020-02-02 13:12:47 Iteration 1200 Training Loss: 2.262e-01 Loss in Target Net: 3.748e-01 |
2020-02-02 13:13:03 Iteration 1250 Training Loss: 2.279e-01 Loss in Target Net: 3.432e-01 |
2020-02-02 13:13:19 Iteration 1300 Training Loss: 2.334e-01 Loss in Target Net: 3.468e-01 |
2020-02-02 13:13:35 Iteration 1350 Training Loss: 2.260e-01 Loss in Target Net: 3.067e-01 |
2020-02-02 13:13:51 Iteration 1400 Training Loss: 2.216e-01 Loss in Target Net: 3.077e-01 |
2020-02-02 13:14:06 Iteration 1450 Training Loss: 2.271e-01 Loss in Target Net: 3.036e-01 |
2020-02-02 13:14:22 Iteration 1499 Training Loss: 2.211e-01 Loss in Target Net: 3.193e-01 |
Evaluating against victims networks |
DPN92 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-02 13:14:31, Epoch 0, Iteration 7, loss 0.236 (0.329), acc 92.308 (91.200) |
2020-02-02 13:15:29, 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:[0.9360886, -0.316368, -2.5909395, -2.1841722, -2.5372443, -1.9682672, 0.47649133, -2.3556173, 10.697428, 0.4530875], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-02-02 13:16:28 Epoch 59, Val iteration 0, acc 92.400 (92.400) |
2020-02-02 13:16:36 Epoch 59, Val iteration 19, acc 92.000 (92.240) |
* Prec: 92.24000129699706 |
-------- |
------SUMMARY------ |
TIME ELAPSED (mins): 8 |
TARGET INDEX: 48 |
DPN92 1 |
Namespace(chk_path='chk-black-end2end', chk_subdir='poisons', device='cuda', dset_path='datasets', end2end=True, eval_poison_path='', gpu='1', lr_decay_epoch=[30, 45], mode='mean', model_resume_path='model-chks', nearest=False, net_repeat=1, num_per_class=50, original_grad=True, poison_decay_ites=[], poison_decay_ratio... |
Path: chk-black-end2end/mean/1500/49 |
Selected base image indices: [213, 225, 227, 247, 249] |
2020-02-02 13:07:48 Iteration 0 Training Loss: 9.836e-01 Loss in Target Net: 1.252e+00 |
2020-02-02 13:08:05 Iteration 50 Training Loss: 2.633e-01 Loss in Target Net: 1.841e-01 |
2020-02-02 13:08:22 Iteration 100 Training Loss: 2.387e-01 Loss in Target Net: 1.410e-01 |
2020-02-02 13:08:38 Iteration 150 Training Loss: 2.241e-01 Loss in Target Net: 1.320e-01 |
2020-02-02 13:08:54 Iteration 200 Training Loss: 2.230e-01 Loss in Target Net: 1.320e-01 |
2020-02-02 13:09:11 Iteration 250 Training Loss: 2.174e-01 Loss in Target Net: 1.173e-01 |
2020-02-02 13:09:27 Iteration 300 Training Loss: 2.107e-01 Loss in Target Net: 9.651e-02 |
2020-02-02 13:09:44 Iteration 350 Training Loss: 2.179e-01 Loss in Target Net: 1.102e-01 |
2020-02-02 13:10:00 Iteration 400 Training Loss: 2.115e-01 Loss in Target Net: 1.105e-01 |
2020-02-02 13:10:16 Iteration 450 Training Loss: 2.092e-01 Loss in Target Net: 1.174e-01 |
2020-02-02 13:10:32 Iteration 500 Training Loss: 2.054e-01 Loss in Target Net: 1.118e-01 |
2020-02-02 13:10:48 Iteration 550 Training Loss: 2.103e-01 Loss in Target Net: 1.112e-01 |
2020-02-02 13:11:05 Iteration 600 Training Loss: 2.145e-01 Loss in Target Net: 1.255e-01 |
2020-02-02 13:11:21 Iteration 650 Training Loss: 2.056e-01 Loss in Target Net: 1.238e-01 |
2020-02-02 13:11:37 Iteration 700 Training Loss: 2.050e-01 Loss in Target Net: 1.161e-01 |
2020-02-02 13:11:54 Iteration 750 Training Loss: 2.040e-01 Loss in Target Net: 1.084e-01 |
2020-02-02 13:12:10 Iteration 800 Training Loss: 2.119e-01 Loss in Target Net: 1.052e-01 |
2020-02-02 13:12:27 Iteration 850 Training Loss: 2.069e-01 Loss in Target Net: 1.084e-01 |
2020-02-02 13:12:43 Iteration 900 Training Loss: 2.024e-01 Loss in Target Net: 1.091e-01 |
2020-02-02 13:13:00 Iteration 950 Training Loss: 2.052e-01 Loss in Target Net: 1.159e-01 |
2020-02-02 13:13:16 Iteration 1000 Training Loss: 2.064e-01 Loss in Target Net: 1.230e-01 |
2020-02-02 13:13:32 Iteration 1050 Training Loss: 2.038e-01 Loss in Target Net: 1.227e-01 |
2020-02-02 13:13:49 Iteration 1100 Training Loss: 2.045e-01 Loss in Target Net: 1.193e-01 |
2020-02-02 13:14:06 Iteration 1150 Training Loss: 2.054e-01 Loss in Target Net: 1.016e-01 |
2020-02-02 13:14:22 Iteration 1200 Training Loss: 2.047e-01 Loss in Target Net: 1.054e-01 |
2020-02-02 13:14:39 Iteration 1250 Training Loss: 1.997e-01 Loss in Target Net: 1.113e-01 |
2020-02-02 13:14:56 Iteration 1300 Training Loss: 2.029e-01 Loss in Target Net: 1.112e-01 |
2020-02-02 13:15:12 Iteration 1350 Training Loss: 1.997e-01 Loss in Target Net: 1.118e-01 |
2020-02-02 13:15:29 Iteration 1400 Training Loss: 2.010e-01 Loss in Target Net: 1.140e-01 |
2020-02-02 13:15:45 Iteration 1450 Training Loss: 2.037e-01 Loss in Target Net: 1.213e-01 |
2020-02-02 13:16:01 Iteration 1499 Training Loss: 2.019e-01 Loss in Target Net: 1.244e-01 |
Evaluating against victims networks |
DPN92 |
Using Adam for retraining |
Files already downloaded and verified |
2020-02-02 13:16:11, Epoch 0, Iteration 7, loss 0.596 (0.379), acc 84.615 (91.200) |
2020-02-02 13:17:08, 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:[-2.9051585, -0.889524, 1.2907454, -0.5365509, -2.0070844, 0.89917004, 0.07782448, -3.2540936, 10.374059, -2.722627], Poisons' Predictions:[8, 8, 8, 8, 8] |
2020-02-02 13:18:08 Epoch 59, Val iteration 0, acc 92.600 (92.600) |
2020-02-02 13:18:15 Epoch 59, Val iteration 19, acc 92.600 (92.990) |
* Prec: 92.9900016784668 |
-------- |
------SUMMARY------ |
TIME ELAPSED (mins): 8 |
TARGET INDEX: 49 |
DPN92 1 |
Namespace(chk_path='chk-black-end2end', chk_subdir='poisons', device='cuda', dset_path='datasets', end2end=True, eval_poison_path='', gpu='1', lr_decay_epoch=[30, 45], mode='mean', model_resume_path='model-chks', nearest=False, net_repeat=1, num_per_class=50, original_grad=True, poison_decay_ites=[], poison_decay_ratio... |
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