
=== 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 0x7fa4ceb542b0>

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: 1.0405 top1= 61.8750
[E 1B20 |  14784/60000 ( 25%) ] Loss: 0.3939 top1= 87.8125

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.6329 top1= 81.5705


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.4669 top1= 49.3389


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.9748 top1= 44.2508

Train epoch 2
[E 2B0  |    704/60000 (  1%) ] Loss: 0.2802 top1= 90.3125
[E 2B10 |   7744/60000 ( 13%) ] Loss: 0.1963 top1= 94.0625
[E 2B20 |  14784/60000 ( 25%) ] Loss: 0.2005 top1= 94.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4759 top1= 87.0493


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=3.0317 top1= 50.0300


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=3.0170 top1= 45.8834

Train epoch 3
[E 3B0  |    704/60000 (  1%) ] Loss: 0.1574 top1= 95.0000
[E 3B10 |   7744/60000 ( 13%) ] Loss: 0.1170 top1= 97.1875
[E 3B20 |  14784/60000 ( 25%) ] Loss: 0.1564 top1= 95.4688

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3803 top1= 88.5317


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.7833 top1= 51.6226


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.6632 top1= 47.7163

Train epoch 4
[E 4B0  |    704/60000 (  1%) ] Loss: 0.1355 top1= 95.9375
[E 4B10 |   7744/60000 ( 13%) ] Loss: 0.0856 top1= 97.1875
[E 4B20 |  14784/60000 ( 25%) ] Loss: 0.1141 top1= 96.5625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3371 top1= 89.1827


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.6678 top1= 53.5156


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.4279 top1= 50.0601

Train epoch 5
[E 5B0  |    704/60000 (  1%) ] Loss: 0.1044 top1= 97.5000
[E 5B10 |   7744/60000 ( 13%) ] Loss: 0.0610 top1= 98.1250
[E 5B20 |  14784/60000 ( 25%) ] Loss: 0.0895 top1= 97.0312

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3092 top1= 89.8438


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.6208 top1= 54.8778


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.3060 top1= 52.5741

Train epoch 6
[E 6B0  |    704/60000 (  1%) ] Loss: 0.0814 top1= 97.9688
[E 6B10 |   7744/60000 ( 13%) ] Loss: 0.0459 top1= 99.2188
[E 6B20 |  14784/60000 ( 25%) ] Loss: 0.0686 top1= 97.9688

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2965 top1= 90.1643


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.6533 top1= 55.7893


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.1598 top1= 55.6290

Train epoch 7
[E 7B0  |    704/60000 (  1%) ] Loss: 0.0631 top1= 98.9062
[E 7B10 |   7744/60000 ( 13%) ] Loss: 0.0348 top1= 99.2188
[E 7B20 |  14784/60000 ( 25%) ] Loss: 0.0560 top1= 97.8125

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2956 top1= 90.3245


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.6778 top1= 56.6707


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.1027 top1= 57.1615

Train epoch 8
[E 8B0  |    704/60000 (  1%) ] Loss: 0.0505 top1= 98.7500
[E 8B10 |   7744/60000 ( 13%) ] Loss: 0.0308 top1= 99.5312
[E 8B20 |  14784/60000 ( 25%) ] Loss: 0.0493 top1= 98.2812

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2815 top1= 90.4547


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.4401 top1= 58.5236


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.2342 top1= 55.4587

Train epoch 9
[E 9B0  |    704/60000 (  1%) ] Loss: 0.0443 top1= 98.9062
[E 9B10 |   7744/60000 ( 13%) ] Loss: 0.0292 top1= 99.0625
[E 9B20 |  14784/60000 ( 25%) ] Loss: 0.0577 top1= 98.1250

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2707 top1= 90.9455


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.2126 top1= 59.9760


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.3923 top1= 55.1082

Train epoch 10
[E10B0  |    704/60000 (  1%) ] Loss: 0.0458 top1= 97.9688
[E10B10 |   7744/60000 ( 13%) ] Loss: 0.0395 top1= 98.7500
[E10B20 |  14784/60000 ( 25%) ] Loss: 0.0504 top1= 98.2812

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2602 top1= 91.1659


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.2766 top1= 59.1046


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.1546 top1= 58.2833

Train epoch 11
[E11B0  |    704/60000 (  1%) ] Loss: 0.0248 top1= 99.2188
[E11B10 |   7744/60000 ( 13%) ] Loss: 0.0176 top1= 99.8438
[E11B20 |  14784/60000 ( 25%) ] Loss: 0.0179 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2492 top1= 91.9271


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.1706 top1= 60.5569


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.1072 top1= 56.1799

Train epoch 12
[E12B0  |    704/60000 (  1%) ] Loss: 0.0332 top1= 99.3750
[E12B10 |   7744/60000 ( 13%) ] Loss: 0.0146 top1= 99.8438
[E12B20 |  14784/60000 ( 25%) ] Loss: 0.0130 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2346 top1= 92.2576


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.2746 top1= 61.5084


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.9946 top1= 59.5853

Train epoch 13
[E13B0  |    704/60000 (  1%) ] Loss: 0.0211 top1= 99.5312
[E13B10 |   7744/60000 ( 13%) ] Loss: 0.0140 top1= 99.6875
[E13B20 |  14784/60000 ( 25%) ] Loss: 0.0137 top1= 99.5312

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2357 top1= 92.4379


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.8854 top1= 63.5617


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.1075 top1= 58.4235

Train epoch 14
[E14B0  |    704/60000 (  1%) ] Loss: 0.0138 top1= 99.8438
[E14B10 |   7744/60000 ( 13%) ] Loss: 0.0069 top1=100.0000
[E14B20 |  14784/60000 ( 25%) ] Loss: 0.0115 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2302 top1= 92.8085


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.9077 top1= 63.9924


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.6889 top1= 64.1827

Train epoch 15
[E15B0  |    704/60000 (  1%) ] Loss: 0.0077 top1= 99.8438
[E15B10 |   7744/60000 ( 13%) ] Loss: 0.0117 top1= 99.8438
[E15B20 |  14784/60000 ( 25%) ] Loss: 0.0123 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2367 top1= 92.6382


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.7392 top1= 65.6250


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.7189 top1= 64.7135

Train epoch 16
[E16B0  |    704/60000 (  1%) ] Loss: 0.0069 top1= 99.8438
[E16B10 |   7744/60000 ( 13%) ] Loss: 0.0059 top1=100.0000
[E16B20 |  14784/60000 ( 25%) ] Loss: 0.0074 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2398 top1= 92.6583


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.6555 top1= 66.7869


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.6446 top1= 65.7452

Train epoch 17
[E17B0  |    704/60000 (  1%) ] Loss: 0.0079 top1= 99.8438
[E17B10 |   7744/60000 ( 13%) ] Loss: 0.0070 top1= 99.6875
[E17B20 |  14784/60000 ( 25%) ] Loss: 0.0101 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2544 top1= 92.1875


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.5843 top1= 67.8686


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.7977 top1= 65.4046

Train epoch 18
[E18B0  |    704/60000 (  1%) ] Loss: 0.0184 top1= 99.3750
[E18B10 |   7744/60000 ( 13%) ] Loss: 0.0107 top1= 99.6875
[E18B20 |  14784/60000 ( 25%) ] Loss: 0.0055 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2442 top1= 92.6583


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.5517 top1= 68.6298


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.6130 top1= 67.1374

Train epoch 19
[E19B0  |    704/60000 (  1%) ] Loss: 0.0057 top1=100.0000
[E19B10 |   7744/60000 ( 13%) ] Loss: 0.0026 top1=100.0000
[E19B20 |  14784/60000 ( 25%) ] Loss: 0.0071 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2308 top1= 93.0789


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.4782 top1= 69.8518


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.6157 top1= 67.4279

Train epoch 20
[E20B0  |    704/60000 (  1%) ] Loss: 0.0044 top1=100.0000
[E20B10 |   7744/60000 ( 13%) ] Loss: 0.0035 top1=100.0000
[E20B20 |  14784/60000 ( 25%) ] Loss: 0.0034 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2305 top1= 93.1691


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.4523 top1= 70.2825


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5963 top1= 68.2492

Train epoch 21
[E21B0  |    704/60000 (  1%) ] Loss: 0.0021 top1=100.0000
[E21B10 |   7744/60000 ( 13%) ] Loss: 0.0021 top1=100.0000
[E21B20 |  14784/60000 ( 25%) ] Loss: 0.0025 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2285 top1= 93.2792


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.4478 top1= 70.7432


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.3751 top1= 71.4844

Train epoch 22
[E22B0  |    704/60000 (  1%) ] Loss: 0.0015 top1=100.0000
[E22B10 |   7744/60000 ( 13%) ] Loss: 0.0018 top1=100.0000
[E22B20 |  14784/60000 ( 25%) ] Loss: 0.0024 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2308 top1= 93.3594


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.4178 top1= 71.3341


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.3042 top1= 73.2272

Train epoch 23
[E23B0  |    704/60000 (  1%) ] Loss: 0.0015 top1=100.0000
[E23B10 |   7744/60000 ( 13%) ] Loss: 0.0017 top1=100.0000
[E23B20 |  14784/60000 ( 25%) ] Loss: 0.0020 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2324 top1= 93.4395


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.3707 top1= 72.2356


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.2678 top1= 74.1687

Train epoch 24
[E24B0  |    704/60000 (  1%) ] Loss: 0.0014 top1=100.0000
[E24B10 |   7744/60000 ( 13%) ] Loss: 0.0016 top1=100.0000
[E24B20 |  14784/60000 ( 25%) ] Loss: 0.0018 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2332 top1= 93.4295


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.3412 top1= 72.7464


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.2461 top1= 74.7897

Train epoch 25
[E25B0  |    704/60000 (  1%) ] Loss: 0.0013 top1=100.0000
[E25B10 |   7744/60000 ( 13%) ] Loss: 0.0014 top1=100.0000
[E25B20 |  14784/60000 ( 25%) ] Loss: 0.0016 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2338 top1= 93.4495


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.3113 top1= 73.3273


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.2192 top1= 75.2905

Train epoch 26
[E26B0  |    704/60000 (  1%) ] Loss: 0.0013 top1=100.0000
[E26B10 |   7744/60000 ( 13%) ] Loss: 0.0013 top1=100.0000
[E26B20 |  14784/60000 ( 25%) ] Loss: 0.0015 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2345 top1= 93.4395


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.2793 top1= 73.7780


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.2096 top1= 75.6410

Train epoch 27
[E27B0  |    704/60000 (  1%) ] Loss: 0.0012 top1=100.0000
[E27B10 |   7744/60000 ( 13%) ] Loss: 0.0012 top1=100.0000
[E27B20 |  14784/60000 ( 25%) ] Loss: 0.0014 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2349 top1= 93.4595


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.2484 top1= 74.2989


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.1948 top1= 75.9916

Train epoch 28
[E28B0  |    704/60000 (  1%) ] Loss: 0.0011 top1=100.0000
[E28B10 |   7744/60000 ( 13%) ] Loss: 0.0011 top1=100.0000
[E28B20 |  14784/60000 ( 25%) ] Loss: 0.0013 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2353 top1= 93.4696


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.2218 top1= 74.7897


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.1844 top1= 76.2420

Train epoch 29
[E29B0  |    704/60000 (  1%) ] Loss: 0.0011 top1=100.0000
[E29B10 |   7744/60000 ( 13%) ] Loss: 0.0011 top1=100.0000
[E29B20 |  14784/60000 ( 25%) ] Loss: 0.0012 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2357 top1= 93.4996


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1974 top1= 75.2204


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.1734 top1= 76.4623

Train epoch 30
[E30B0  |    704/60000 (  1%) ] Loss: 0.0010 top1=100.0000
[E30B10 |   7744/60000 ( 13%) ] Loss: 0.0010 top1=100.0000
[E30B20 |  14784/60000 ( 25%) ] Loss: 0.0011 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2360 top1= 93.5497


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1736 top1= 75.5409


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.1652 top1= 76.7228

