
=== Start adding workers ===
=> Add worker SGDMWorker(index=0, momentum=0.9)
=> Add worker SGDMWorker(index=1, momentum=0.9)
=> Add worker SGDMWorker(index=2, momentum=0.9)
=> Add worker SGDMWorker(index=3, momentum=0.9)
=> Add worker SGDMWorker(index=4, momentum=0.9)
=> Add worker SGDMWorker(index=5, momentum=0.9)
=> Add worker SGDMWorker(index=6, momentum=0.9)
=> Add worker SGDMWorker(index=7, momentum=0.9)
=> Add worker SGDMWorker(index=8, momentum=0.9)
=> Add worker SGDMWorker(index=9, momentum=0.9)
=> Add worker SGDMWorker(index=10, momentum=0.9)
=> Add worker SGDMWorker(index=11, momentum=0.9)
=> Add worker SGDMWorker(index=12, momentum=0.9)
=> Add worker SGDMWorker(index=13, momentum=0.9)
=> Add worker SGDMWorker(index=14, momentum=0.9)
=> Add worker SGDMWorker(index=15, momentum=0.9)
=> Add worker SGDMWorker(index=16, momentum=0.9)
=> Add worker SGDMWorker(index=17, momentum=0.9)
=> Add worker SGDMWorker(index=18, momentum=0.9)
=> Add worker SGDMWorker(index=19, momentum=0.9)
=> Add worker BitFlippingWorker
=> Add worker BitFlippingWorker

=== Start adding graph ===
<codes.graph_utils.DumbbellVariant object at 0x7f07ed35f2b0>

Train epoch 1
[E 1B0  |    704/60000 (  1%) ] Loss: 2.3066 top1=  9.2188

=== Peeking data label distribution E1B0 ===
Worker 0 has targets: tensor([3, 2, 2, 4, 3], device='cuda:0')
Worker 1 has targets: tensor([1, 0, 0, 4, 0], device='cuda:0')
Worker 2 has targets: tensor([4, 1, 0, 1, 0], device='cuda:0')
Worker 3 has targets: tensor([0, 1, 4, 1, 3], device='cuda:0')
Worker 4 has targets: tensor([0, 4, 1, 2, 4], device='cuda:0')
Worker 5 has targets: tensor([2, 2, 4, 4, 4], device='cuda:0')
Worker 6 has targets: tensor([1, 1, 4, 4, 3], device='cuda:0')
Worker 7 has targets: tensor([4, 4, 1, 3, 0], device='cuda:0')
Worker 8 has targets: tensor([1, 3, 1, 0, 4], device='cuda:0')
Worker 9 has targets: tensor([1, 3, 3, 3, 1], device='cuda:0')
Worker 10 has targets: tensor([8, 9, 7, 7, 9], device='cuda:0')
Worker 11 has targets: tensor([8, 9, 6, 6, 7], device='cuda:0')
Worker 12 has targets: tensor([8, 6, 5, 7, 8], device='cuda:0')
Worker 13 has targets: tensor([7, 6, 9, 6, 5], device='cuda:0')
Worker 14 has targets: tensor([8, 5, 8, 6, 7], device='cuda:0')
Worker 15 has targets: tensor([9, 5, 6, 8, 6], device='cuda:0')
Worker 16 has targets: tensor([7, 7, 8, 5, 8], device='cuda:0')
Worker 17 has targets: tensor([9, 7, 5, 6, 6], device='cuda:0')
Worker 18 has targets: tensor([7, 7, 7, 6, 6], device='cuda:0')
Worker 19 has targets: tensor([5, 7, 9, 9, 7], device='cuda:0')
Worker 20 has targets: tensor([3, 2, 2, 4, 3], device='cuda:0')
Worker 21 has targets: tensor([8, 9, 7, 7, 9], device='cuda:0')


[E 1B10 |   7744/60000 ( 13%) ] Loss: 1.0367 top1= 61.7188
[E 1B20 |  14784/60000 ( 25%) ] Loss: 0.3983 top1= 88.4375

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.7412 top1= 78.0849


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=9.0303 top1= 49.2388


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.7305 top1= 44.1907

Train epoch 2
[E 2B0  |    704/60000 (  1%) ] Loss: 0.2870 top1= 90.7812
[E 2B10 |   7744/60000 ( 13%) ] Loss: 0.1911 top1= 93.7500
[E 2B20 |  14784/60000 ( 25%) ] Loss: 0.1970 top1= 94.2188

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.6917 top1= 84.2047


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.5540 top1= 49.7997


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.4792 top1= 45.7232

Train epoch 3
[E 3B0  |    704/60000 (  1%) ] Loss: 0.1645 top1= 94.0625
[E 3B10 |   7744/60000 ( 13%) ] Loss: 0.1100 top1= 96.8750
[E 3B20 |  14784/60000 ( 25%) ] Loss: 0.1269 top1= 96.4062

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.6286 top1= 85.3766


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.4723 top1= 50.1402


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.6291 top1= 46.1338

Train epoch 4
[E 4B0  |    704/60000 (  1%) ] Loss: 0.1209 top1= 96.7188
[E 4B10 |   7744/60000 ( 13%) ] Loss: 0.0801 top1= 97.9688
[E 4B20 |  14784/60000 ( 25%) ] Loss: 0.0837 top1= 97.1875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5789 top1= 86.0577


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.6222 top1= 50.3405


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.6013 top1= 46.4243

Train epoch 5
[E 5B0  |    704/60000 (  1%) ] Loss: 0.0857 top1= 97.8125
[E 5B10 |   7744/60000 ( 13%) ] Loss: 0.0635 top1= 98.1250
[E 5B20 |  14784/60000 ( 25%) ] Loss: 0.0598 top1= 98.2812

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5381 top1= 86.5785


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.7457 top1= 50.4107


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.6868 top1= 46.7047

Train epoch 6
[E 6B0  |    704/60000 (  1%) ] Loss: 0.0611 top1= 98.5938
[E 6B10 |   7744/60000 ( 13%) ] Loss: 0.0465 top1= 98.7500
[E 6B20 |  14784/60000 ( 25%) ] Loss: 0.0502 top1= 98.2812

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5031 top1= 87.0994


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.8445 top1= 50.4908


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.7778 top1= 46.7748

Train epoch 7
[E 7B0  |    704/60000 (  1%) ] Loss: 0.0464 top1= 99.0625
[E 7B10 |   7744/60000 ( 13%) ] Loss: 0.0307 top1= 99.2188
[E 7B20 |  14784/60000 ( 25%) ] Loss: 0.0378 top1= 98.9062

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4767 top1= 87.3197


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.9521 top1= 50.4607


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.8566 top1= 46.9852

Train epoch 8
[E 8B0  |    704/60000 (  1%) ] Loss: 0.0372 top1= 99.0625
[E 8B10 |   7744/60000 ( 13%) ] Loss: 0.0231 top1= 99.5312
[E 8B20 |  14784/60000 ( 25%) ] Loss: 0.0267 top1= 99.0625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4575 top1= 87.1294


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.9280 top1= 50.5409


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.2540 top1= 46.8049

Train epoch 9
[E 9B0  |    704/60000 (  1%) ] Loss: 0.0329 top1= 98.9062
[E 9B10 |   7744/60000 ( 13%) ] Loss: 0.0171 top1= 99.8438
[E 9B20 |  14784/60000 ( 25%) ] Loss: 0.0228 top1= 99.0625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4510 top1= 86.8790


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.9489 top1= 50.6611


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.5078 top1= 46.8750

Train epoch 10
[E10B0  |    704/60000 (  1%) ] Loss: 0.0178 top1= 99.6875
[E10B10 |   7744/60000 ( 13%) ] Loss: 0.0118 top1=100.0000
[E10B20 |  14784/60000 ( 25%) ] Loss: 0.0158 top1= 99.5312

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4653 top1= 85.6070


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.9190 top1= 50.6711


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.8888 top1= 46.8249

Train epoch 11
[E11B0  |    704/60000 (  1%) ] Loss: 0.0169 top1= 99.6875
[E11B10 |   7744/60000 ( 13%) ] Loss: 0.0122 top1= 99.6875
[E11B20 |  14784/60000 ( 25%) ] Loss: 0.0107 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4451 top1= 86.3482


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.0709 top1= 50.6410


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.0825 top1= 46.9151

Train epoch 12
[E12B0  |    704/60000 (  1%) ] Loss: 0.0080 top1= 99.8438
[E12B10 |   7744/60000 ( 13%) ] Loss: 0.0089 top1=100.0000
[E12B20 |  14784/60000 ( 25%) ] Loss: 0.0095 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4360 top1= 86.3982


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.2683 top1= 50.6510


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.1330 top1= 46.9952

Train epoch 13
[E13B0  |    704/60000 (  1%) ] Loss: 0.0061 top1=100.0000
[E13B10 |   7744/60000 ( 13%) ] Loss: 0.0068 top1=100.0000
[E13B20 |  14784/60000 ( 25%) ] Loss: 0.0167 top1= 99.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4321 top1= 86.3482


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.5443 top1= 50.6811


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.8745 top1= 46.9852

Train epoch 14
[E14B0  |    704/60000 (  1%) ] Loss: 0.0048 top1=100.0000
[E14B10 |   7744/60000 ( 13%) ] Loss: 0.0086 top1= 99.8438
[E14B20 |  14784/60000 ( 25%) ] Loss: 0.0132 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3891 top1= 88.4816


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.8393 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.8065 top1= 47.0853

Train epoch 15
[E15B0  |    704/60000 (  1%) ] Loss: 0.0069 top1= 99.8438
[E15B10 |   7744/60000 ( 13%) ] Loss: 0.0036 top1=100.0000
[E15B20 |  14784/60000 ( 25%) ] Loss: 0.0212 top1= 99.2188

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3855 top1= 88.7019


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.0048 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.2558 top1= 46.9251

Train epoch 16
[E16B0  |    704/60000 (  1%) ] Loss: 0.0066 top1=100.0000
[E16B10 |   7744/60000 ( 13%) ] Loss: 0.0062 top1= 99.8438
[E16B20 |  14784/60000 ( 25%) ] Loss: 0.0058 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3929 top1= 88.0308


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.1724 top1= 50.7212


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.3796 top1= 47.1955

Train epoch 17
[E17B0  |    704/60000 (  1%) ] Loss: 0.0024 top1=100.0000
[E17B10 |   7744/60000 ( 13%) ] Loss: 0.0026 top1=100.0000
[E17B20 |  14784/60000 ( 25%) ] Loss: 0.0022 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3943 top1= 87.2997


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.3092 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.6477 top1= 47.2756

Train epoch 18
[E18B0  |    704/60000 (  1%) ] Loss: 0.0023 top1=100.0000
[E18B10 |   7744/60000 ( 13%) ] Loss: 0.0022 top1=100.0000
[E18B20 |  14784/60000 ( 25%) ] Loss: 0.0023 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4012 top1= 86.8189


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.4318 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.9168 top1= 47.2857

Train epoch 19
[E19B0  |    704/60000 (  1%) ] Loss: 0.0019 top1=100.0000
[E19B10 |   7744/60000 ( 13%) ] Loss: 0.0015 top1=100.0000
[E19B20 |  14784/60000 ( 25%) ] Loss: 0.0021 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3900 top1= 87.3097


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.5536 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.1438 top1= 47.3157

Train epoch 20
[E20B0  |    704/60000 (  1%) ] Loss: 0.0011 top1=100.0000
[E20B10 |   7744/60000 ( 13%) ] Loss: 0.0012 top1=100.0000
[E20B20 |  14784/60000 ( 25%) ] Loss: 0.0014 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3764 top1= 87.9507


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.6687 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.3033 top1= 47.2957

Train epoch 21
[E21B0  |    704/60000 (  1%) ] Loss: 0.0009 top1=100.0000
[E21B10 |   7744/60000 ( 13%) ] Loss: 0.0011 top1=100.0000
[E21B20 |  14784/60000 ( 25%) ] Loss: 0.0011 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3753 top1= 87.9307


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.7698 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.4159 top1= 47.3057

Train epoch 22
[E22B0  |    704/60000 (  1%) ] Loss: 0.0009 top1=100.0000
[E22B10 |   7744/60000 ( 13%) ] Loss: 0.0009 top1=100.0000
[E22B20 |  14784/60000 ( 25%) ] Loss: 0.0010 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3756 top1= 87.8806


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.8622 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.5571 top1= 47.2656

Train epoch 23
[E23B0  |    704/60000 (  1%) ] Loss: 0.0008 top1=100.0000
[E23B10 |   7744/60000 ( 13%) ] Loss: 0.0008 top1=100.0000
[E23B20 |  14784/60000 ( 25%) ] Loss: 0.0009 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3745 top1= 87.9006


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.9581 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.6759 top1= 47.2857

Train epoch 24
[E24B0  |    704/60000 (  1%) ] Loss: 0.0007 top1=100.0000
[E24B10 |   7744/60000 ( 13%) ] Loss: 0.0007 top1=100.0000
[E24B20 |  14784/60000 ( 25%) ] Loss: 0.0008 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3742 top1= 87.9307


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.0398 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.7804 top1= 47.2756

Train epoch 25
[E25B0  |    704/60000 (  1%) ] Loss: 0.0006 top1=100.0000
[E25B10 |   7744/60000 ( 13%) ] Loss: 0.0007 top1=100.0000
[E25B20 |  14784/60000 ( 25%) ] Loss: 0.0008 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3736 top1= 87.8906


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.1174 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.8750 top1= 47.2756

Train epoch 26
[E26B0  |    704/60000 (  1%) ] Loss: 0.0006 top1=100.0000
[E26B10 |   7744/60000 ( 13%) ] Loss: 0.0006 top1=100.0000
[E26B20 |  14784/60000 ( 25%) ] Loss: 0.0007 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3733 top1= 87.8806


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.1927 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.9617 top1= 47.2756

Train epoch 27
[E27B0  |    704/60000 (  1%) ] Loss: 0.0005 top1=100.0000
[E27B10 |   7744/60000 ( 13%) ] Loss: 0.0006 top1=100.0000
[E27B20 |  14784/60000 ( 25%) ] Loss: 0.0006 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3728 top1= 87.8906


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.2633 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.0415 top1= 47.2756

Train epoch 28
[E28B0  |    704/60000 (  1%) ] Loss: 0.0005 top1=100.0000
[E28B10 |   7744/60000 ( 13%) ] Loss: 0.0006 top1=100.0000
[E28B20 |  14784/60000 ( 25%) ] Loss: 0.0006 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3728 top1= 87.8706


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.3291 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.1170 top1= 47.2756

Train epoch 29
[E29B0  |    704/60000 (  1%) ] Loss: 0.0005 top1=100.0000
[E29B10 |   7744/60000 ( 13%) ] Loss: 0.0005 top1=100.0000
[E29B20 |  14784/60000 ( 25%) ] Loss: 0.0006 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3726 top1= 87.8405


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.3923 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.1885 top1= 47.2756

Train epoch 30
[E30B0  |    704/60000 (  1%) ] Loss: 0.0004 top1=100.0000
[E30B10 |   7744/60000 ( 13%) ] Loss: 0.0005 top1=100.0000
[E30B20 |  14784/60000 ( 25%) ] Loss: 0.0005 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3725 top1= 87.8205


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.4499 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.2556 top1= 47.2756

