
=== 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 ByzantineWorker(index=20)
=> Add worker ByzantineWorker(index=21)

=== Start adding graph ===
<codes.graph_utils.DumbbellVariant object at 0x7fd4396982e0>

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: 1.0368 top1= 61.7188
[E 1B20 |  14784/60000 ( 25%) ] Loss: 0.4003 top1= 88.4375

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.7378 top1= 78.1851


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=9.1187 top1= 49.2889


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.7745 top1= 44.2107

Train epoch 2
[E 2B0  |    704/60000 (  1%) ] Loss: 0.2863 top1= 90.6250
[E 2B10 |   7744/60000 ( 13%) ] Loss: 0.1929 top1= 93.7500
[E 2B20 |  14784/60000 ( 25%) ] Loss: 0.1980 top1= 94.0625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.6909 top1= 83.9343


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.6127 top1= 49.8197


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.4790 top1= 45.7632

Train epoch 3
[E 3B0  |    704/60000 (  1%) ] Loss: 0.1626 top1= 94.3750
[E 3B10 |   7744/60000 ( 13%) ] Loss: 0.1094 top1= 96.8750
[E 3B20 |  14784/60000 ( 25%) ] Loss: 0.1243 top1= 96.2500

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.6266 top1= 85.2764


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.5481 top1= 50.1502


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.6626 top1= 46.1639

Train epoch 4
[E 4B0  |    704/60000 (  1%) ] Loss: 0.1168 top1= 96.7188
[E 4B10 |   7744/60000 ( 13%) ] Loss: 0.0803 top1= 97.9688
[E 4B20 |  14784/60000 ( 25%) ] Loss: 0.0811 top1= 97.1875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5775 top1= 85.5669


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.7443 top1= 50.3606


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.6416 top1= 46.4744

Train epoch 5
[E 5B0  |    704/60000 (  1%) ] Loss: 0.0812 top1= 98.1250
[E 5B10 |   7744/60000 ( 13%) ] Loss: 0.0629 top1= 98.2812
[E 5B20 |  14784/60000 ( 25%) ] Loss: 0.0579 top1= 98.2812

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5396 top1= 85.9575


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.8470 top1= 50.4407


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.7722 top1= 46.7147

Train epoch 6
[E 6B0  |    704/60000 (  1%) ] Loss: 0.0582 top1= 98.7500
[E 6B10 |   7744/60000 ( 13%) ] Loss: 0.0431 top1= 98.7500
[E 6B20 |  14784/60000 ( 25%) ] Loss: 0.0492 top1= 98.4375

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5049 top1= 86.7288


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.0000 top1= 50.5008


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.8328 top1= 46.7548

Train epoch 7
[E 7B0  |    704/60000 (  1%) ] Loss: 0.0463 top1= 99.2188
[E 7B10 |   7744/60000 ( 13%) ] Loss: 0.0304 top1= 99.2188
[E 7B20 |  14784/60000 ( 25%) ] Loss: 0.0342 top1= 98.9062

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4799 top1= 86.4283


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.1076 top1= 50.4607


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.0864 top1= 46.9351

Train epoch 8
[E 8B0  |    704/60000 (  1%) ] Loss: 0.0345 top1= 99.3750
[E 8B10 |   7744/60000 ( 13%) ] Loss: 0.0226 top1= 99.3750
[E 8B20 |  14784/60000 ( 25%) ] Loss: 0.0247 top1= 99.2188

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4672 top1= 85.8474


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.1724 top1= 50.5809


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.5924 top1= 46.7748

Train epoch 9
[E 9B0  |    704/60000 (  1%) ] Loss: 0.0287 top1= 99.0625
[E 9B10 |   7744/60000 ( 13%) ] Loss: 0.0146 top1= 99.8438
[E 9B20 |  14784/60000 ( 25%) ] Loss: 0.0225 top1= 99.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4809 top1= 84.7155


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.2241 top1= 50.6611


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.8532 top1= 46.8349

Train epoch 10
[E10B0  |    704/60000 (  1%) ] Loss: 0.0202 top1= 99.5312
[E10B10 |   7744/60000 ( 13%) ] Loss: 0.0141 top1= 99.8438
[E10B20 |  14784/60000 ( 25%) ] Loss: 0.0120 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4664 top1= 84.9559


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.4077 top1= 50.6210


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.1905 top1= 46.7648

Train epoch 11
[E11B0  |    704/60000 (  1%) ] Loss: 0.0122 top1= 99.8438
[E11B10 |   7744/60000 ( 13%) ] Loss: 0.0106 top1= 99.8438
[E11B20 |  14784/60000 ( 25%) ] Loss: 0.0111 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4558 top1= 85.3365


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.5628 top1= 50.6410


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.3166 top1= 46.9551

Train epoch 12
[E12B0  |    704/60000 (  1%) ] Loss: 0.0076 top1= 99.8438
[E12B10 |   7744/60000 ( 13%) ] Loss: 0.0083 top1=100.0000
[E12B20 |  14784/60000 ( 25%) ] Loss: 0.0152 top1= 99.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4301 top1= 86.3782


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.8175 top1= 50.6711


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.1485 top1= 47.0353

Train epoch 13
[E13B0  |    704/60000 (  1%) ] Loss: 0.0070 top1= 99.8438
[E13B10 |   7744/60000 ( 13%) ] Loss: 0.0053 top1=100.0000
[E13B20 |  14784/60000 ( 25%) ] Loss: 0.0204 top1= 99.0625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4160 top1= 86.8690


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.1394 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.8319 top1= 47.1755

Train epoch 14
[E14B0  |    704/60000 (  1%) ] Loss: 0.0043 top1=100.0000
[E14B10 |   7744/60000 ( 13%) ] Loss: 0.0034 top1=100.0000
[E14B20 |  14784/60000 ( 25%) ] Loss: 0.0074 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3902 top1= 88.1711


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.3961 top1= 50.7212


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.9207 top1= 46.6246

Train epoch 15
[E15B0  |    704/60000 (  1%) ] Loss: 0.0222 top1= 99.3750
[E15B10 |   7744/60000 ( 13%) ] Loss: 0.0045 top1=100.0000
[E15B20 |  14784/60000 ( 25%) ] Loss: 0.0057 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4056 top1= 86.8590


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.5694 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.6801 top1= 47.1855

Train epoch 16
[E16B0  |    704/60000 (  1%) ] Loss: 0.0028 top1=100.0000
[E16B10 |   7744/60000 ( 13%) ] Loss: 0.0027 top1=100.0000
[E16B20 |  14784/60000 ( 25%) ] Loss: 0.0030 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4077 top1= 86.4683


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.7387 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.0267 top1= 47.2155

Train epoch 17
[E17B0  |    704/60000 (  1%) ] Loss: 0.0022 top1=100.0000
[E17B10 |   7744/60000 ( 13%) ] Loss: 0.0023 top1=100.0000
[E17B20 |  14784/60000 ( 25%) ] Loss: 0.0027 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4240 top1= 85.6671


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.8805 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.2780 top1= 47.2155

Train epoch 18
[E18B0  |    704/60000 (  1%) ] Loss: 0.0021 top1=100.0000
[E18B10 |   7744/60000 ( 13%) ] Loss: 0.0018 top1=100.0000
[E18B20 |  14784/60000 ( 25%) ] Loss: 0.0022 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4123 top1= 86.1378


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.0142 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.4725 top1= 47.2857

Train epoch 19
[E19B0  |    704/60000 (  1%) ] Loss: 0.0013 top1=100.0000
[E19B10 |   7744/60000 ( 13%) ] Loss: 0.0013 top1=100.0000
[E19B20 |  14784/60000 ( 25%) ] Loss: 0.0014 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3932 top1= 86.8490


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.1422 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.6659 top1= 47.2857

Train epoch 20
[E20B0  |    704/60000 (  1%) ] Loss: 0.0010 top1=100.0000
[E20B10 |   7744/60000 ( 13%) ] Loss: 0.0011 top1=100.0000
[E20B20 |  14784/60000 ( 25%) ] Loss: 0.0012 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3936 top1= 86.7788


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.2614 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.8080 top1= 47.2756

Train epoch 21
[E21B0  |    704/60000 (  1%) ] Loss: 0.0009 top1=100.0000
[E21B10 |   7744/60000 ( 13%) ] Loss: 0.0010 top1=100.0000
[E21B20 |  14784/60000 ( 25%) ] Loss: 0.0010 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3945 top1= 86.7087


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.3704 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.9584 top1= 47.2556

Train epoch 22
[E22B0  |    704/60000 (  1%) ] Loss: 0.0008 top1=100.0000
[E22B10 |   7744/60000 ( 13%) ] Loss: 0.0009 top1=100.0000
[E22B20 |  14784/60000 ( 25%) ] Loss: 0.0009 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3939 top1= 86.6987


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.4725 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.0779 top1= 47.2656

Train epoch 23
[E23B0  |    704/60000 (  1%) ] Loss: 0.0007 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=0.3934 top1= 86.7188


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.5697 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.1840 top1= 47.2756

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=0.3933 top1= 86.7087


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.6596 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.2816 top1= 47.2656

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: 0.0007 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3932 top1= 86.6687


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.7432 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.3716 top1= 47.2656

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=0.3930 top1= 86.7087


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.8202 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.4538 top1= 47.2656

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=0.3930 top1= 86.6687


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.9009 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.5342 top1= 47.2656

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

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3930 top1= 86.6787


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.9685 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.6085 top1= 47.2656

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=0.3932 top1= 86.6987


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=9.0374 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.6801 top1= 47.2656

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=0.3932 top1= 86.7087


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=9.1021 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.7476 top1= 47.2656

