
=== 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 0x7f05aefc62b0>

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: 1.0294 top1= 62.3438
[E 1B20 |  14784/60000 ( 25%) ] Loss: 0.3995 top1= 88.1250

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.7285 top1= 78.8361


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=9.0849 top1= 49.2989


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.8186 top1= 44.2408

Train epoch 2
[E 2B0  |    704/60000 (  1%) ] Loss: 0.2818 top1= 90.7812
[E 2B10 |   7744/60000 ( 13%) ] Loss: 0.1875 top1= 93.7500
[E 2B20 |  14784/60000 ( 25%) ] Loss: 0.1967 top1= 94.5312

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.6782 top1= 84.5954


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.6242 top1= 49.8197


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.6146 top1= 45.8133

Train epoch 3
[E 3B0  |    704/60000 (  1%) ] Loss: 0.1618 top1= 95.1562
[E 3B10 |   7744/60000 ( 13%) ] Loss: 0.1089 top1= 96.5625
[E 3B20 |  14784/60000 ( 25%) ] Loss: 0.1206 top1= 96.7188

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.6171 top1= 85.9275


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.6037 top1= 50.1302


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.7797 top1= 46.1939

Train epoch 4
[E 4B0  |    704/60000 (  1%) ] Loss: 0.1139 top1= 96.8750
[E 4B10 |   7744/60000 ( 13%) ] Loss: 0.0782 top1= 97.8125
[E 4B20 |  14784/60000 ( 25%) ] Loss: 0.0768 top1= 97.5000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5560 top1= 86.7188


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.8573 top1= 50.4006


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.9113 top1= 46.4944

Train epoch 5
[E 5B0  |    704/60000 (  1%) ] Loss: 0.0791 top1= 98.1250
[E 5B10 |   7744/60000 ( 13%) ] Loss: 0.0580 top1= 98.4375
[E 5B20 |  14784/60000 ( 25%) ] Loss: 0.0540 top1= 98.4375

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5126 top1= 86.8089


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.0646 top1= 50.4507


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.0051 top1= 46.6847

Train epoch 6
[E 6B0  |    704/60000 (  1%) ] Loss: 0.0554 top1= 98.7500
[E 6B10 |   7744/60000 ( 13%) ] Loss: 0.0383 top1= 99.0625
[E 6B20 |  14784/60000 ( 25%) ] Loss: 0.0407 top1= 98.9062

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4739 top1= 87.5901


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.3198 top1= 50.5409


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.0638 top1= 46.8750

Train epoch 7
[E 7B0  |    704/60000 (  1%) ] Loss: 0.0412 top1= 99.2188
[E 7B10 |   7744/60000 ( 13%) ] Loss: 0.0276 top1= 99.2188
[E 7B20 |  14784/60000 ( 25%) ] Loss: 0.0310 top1= 99.2188

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4439 top1= 87.6102


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.5947 top1= 50.5308


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.2936 top1= 46.9651

Train epoch 8
[E 8B0  |    704/60000 (  1%) ] Loss: 0.0273 top1= 99.3750
[E 8B10 |   7744/60000 ( 13%) ] Loss: 0.0204 top1= 99.6875
[E 8B20 |  14784/60000 ( 25%) ] Loss: 0.0204 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4270 top1= 86.9892


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.7649 top1= 50.5509


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.8024 top1= 46.8650

Train epoch 9
[E 9B0  |    704/60000 (  1%) ] Loss: 0.0262 top1= 99.0625
[E 9B10 |   7744/60000 ( 13%) ] Loss: 0.0135 top1= 99.8438
[E 9B20 |  14784/60000 ( 25%) ] Loss: 0.0186 top1= 99.5312

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4081 top1= 87.7304


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.7349 top1= 50.6410


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.1627 top1= 46.9050

Train epoch 10
[E10B0  |    704/60000 (  1%) ] Loss: 0.0119 top1= 99.8438
[E10B10 |   7744/60000 ( 13%) ] Loss: 0.0110 top1=100.0000
[E10B20 |  14784/60000 ( 25%) ] Loss: 0.0163 top1= 99.5312

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4226 top1= 86.4283


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.6899 top1= 50.6110


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.3643 top1= 46.8550

Train epoch 11
[E11B0  |    704/60000 (  1%) ] Loss: 0.0152 top1= 99.5312
[E11B10 |   7744/60000 ( 13%) ] Loss: 0.0108 top1= 99.8438
[E11B20 |  14784/60000 ( 25%) ] Loss: 0.0089 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4002 top1= 87.1795


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.7227 top1= 50.6510


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.5651 top1= 46.8550

Train epoch 12
[E12B0  |    704/60000 (  1%) ] Loss: 0.0085 top1= 99.8438
[E12B10 |   7744/60000 ( 13%) ] Loss: 0.0093 top1= 99.8438
[E12B20 |  14784/60000 ( 25%) ] Loss: 0.0093 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3781 top1= 88.1510


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.7603 top1= 50.6410


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.5448 top1= 47.1354

Train epoch 13
[E13B0  |    704/60000 (  1%) ] Loss: 0.0048 top1=100.0000
[E13B10 |   7744/60000 ( 13%) ] Loss: 0.0053 top1=100.0000
[E13B20 |  14784/60000 ( 25%) ] Loss: 0.0095 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3675 top1= 88.4716


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.8630 top1= 50.6811


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.3652 top1= 47.0653

Train epoch 14
[E14B0  |    704/60000 (  1%) ] Loss: 0.0045 top1=100.0000
[E14B10 |   7744/60000 ( 13%) ] Loss: 0.0032 top1=100.0000
[E14B20 |  14784/60000 ( 25%) ] Loss: 0.0050 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3506 top1= 89.0425


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.1573 top1= 50.7212


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.4195 top1= 46.9952

Train epoch 15
[E15B0  |    704/60000 (  1%) ] Loss: 0.0076 top1= 99.5312
[E15B10 |   7744/60000 ( 13%) ] Loss: 0.0030 top1=100.0000
[E15B20 |  14784/60000 ( 25%) ] Loss: 0.0051 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3549 top1= 88.5317


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.3151 top1= 50.7212


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.7241 top1= 47.1354

Train epoch 16
[E16B0  |    704/60000 (  1%) ] Loss: 0.0020 top1=100.0000
[E16B10 |   7744/60000 ( 13%) ] Loss: 0.0020 top1=100.0000
[E16B20 |  14784/60000 ( 25%) ] Loss: 0.0019 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3541 top1= 88.3914


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.3888 top1= 50.7212


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.7404 top1= 47.2556

Train epoch 17
[E17B0  |    704/60000 (  1%) ] Loss: 0.0015 top1=100.0000
[E17B10 |   7744/60000 ( 13%) ] Loss: 0.0020 top1=100.0000
[E17B20 |  14784/60000 ( 25%) ] Loss: 0.0017 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3582 top1= 88.0409


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.4513 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.8346 top1= 47.2356

Train epoch 18
[E18B0  |    704/60000 (  1%) ] Loss: 0.0016 top1=100.0000
[E18B10 |   7744/60000 ( 13%) ] Loss: 0.0017 top1=100.0000
[E18B20 |  14784/60000 ( 25%) ] Loss: 0.0014 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3568 top1= 87.9908


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.4981 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.8929 top1= 47.2356

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: 0.0013 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3535 top1= 88.0809


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.5296 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.9552 top1= 47.2256

Train epoch 20
[E20B0  |    704/60000 (  1%) ] Loss: 0.0012 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=0.3493 top1= 88.2612


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.5487 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.0140 top1= 47.2055

Train epoch 21
[E21B0  |    704/60000 (  1%) ] Loss: 0.0011 top1=100.0000
[E21B10 |   7744/60000 ( 13%) ] Loss: 0.0010 top1=100.0000
[E21B20 |  14784/60000 ( 25%) ] Loss: 0.0012 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3457 top1= 88.3814


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.5568 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.0340 top1= 47.2055

Train epoch 22
[E22B0  |    704/60000 (  1%) ] Loss: 0.0010 top1=100.0000
[E22B10 |   7744/60000 ( 13%) ] Loss: 0.0009 top1=100.0000
[E22B20 |  14784/60000 ( 25%) ] Loss: 0.0011 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3432 top1= 88.4816


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.5548 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.0161 top1= 47.2055

Train epoch 23
[E23B0  |    704/60000 (  1%) ] Loss: 0.0009 top1=100.0000
[E23B10 |   7744/60000 ( 13%) ] Loss: 0.0009 top1=100.0000
[E23B20 |  14784/60000 ( 25%) ] Loss: 0.0011 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3405 top1= 88.6318


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.5436 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.9850 top1= 47.2055

Train epoch 24
[E24B0  |    704/60000 (  1%) ] Loss: 0.0009 top1=100.0000
[E24B10 |   7744/60000 ( 13%) ] Loss: 0.0009 top1=100.0000
[E24B20 |  14784/60000 ( 25%) ] Loss: 0.0010 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3371 top1= 88.7320


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.5289 top1= 50.7212


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.9485 top1= 47.2155

Train epoch 25
[E25B0  |    704/60000 (  1%) ] Loss: 0.0008 top1=100.0000
[E25B10 |   7744/60000 ( 13%) ] Loss: 0.0008 top1=100.0000
[E25B20 |  14784/60000 ( 25%) ] Loss: 0.0010 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3345 top1= 88.8321


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.5043 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.9062 top1= 47.2356

Train epoch 26
[E26B0  |    704/60000 (  1%) ] Loss: 0.0008 top1=100.0000
[E26B10 |   7744/60000 ( 13%) ] Loss: 0.0008 top1=100.0000
[E26B20 |  14784/60000 ( 25%) ] Loss: 0.0010 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3321 top1= 88.9924


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.4771 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.8599 top1= 47.2356

Train epoch 27
[E27B0  |    704/60000 (  1%) ] Loss: 0.0008 top1=100.0000
[E27B10 |   7744/60000 ( 13%) ] Loss: 0.0008 top1=100.0000
[E27B20 |  14784/60000 ( 25%) ] Loss: 0.0009 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3303 top1= 89.0224


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.4419 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.8105 top1= 47.2456

Train epoch 28
[E28B0  |    704/60000 (  1%) ] Loss: 0.0007 top1=100.0000
[E28B10 |   7744/60000 ( 13%) ] Loss: 0.0008 top1=100.0000
[E28B20 |  14784/60000 ( 25%) ] Loss: 0.0009 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3289 top1= 89.0725


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.4052 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.7622 top1= 47.2456

Train epoch 29
[E29B0  |    704/60000 (  1%) ] Loss: 0.0007 top1=100.0000
[E29B10 |   7744/60000 ( 13%) ] Loss: 0.0008 top1=100.0000
[E29B20 |  14784/60000 ( 25%) ] Loss: 0.0009 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3277 top1= 89.1326


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.3620 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.7098 top1= 47.2456

Train epoch 30
[E30B0  |    704/60000 (  1%) ] Loss: 0.0007 top1=100.0000
[E30B10 |   7744/60000 ( 13%) ] Loss: 0.0007 top1=100.0000
[E30B20 |  14784/60000 ( 25%) ] Loss: 0.0009 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3266 top1= 89.1426


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.3162 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.6532 top1= 47.2456

