
=== 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.Dumbbell object at 0x7f94aaca66d0>

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: 1.0427 top1= 61.7188
[E 1B20 |  14784/60000 ( 25%) ] Loss: 0.4034 top1= 88.5938

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.7314 top1= 77.8846


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.9094 top1= 49.2588


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.5966 top1= 44.3009

Train epoch 2
[E 2B0  |    704/60000 (  1%) ] Loss: 0.2864 top1= 90.6250
[E 2B10 |   7744/60000 ( 13%) ] Loss: 0.1949 top1= 93.9062
[E 2B20 |  14784/60000 ( 25%) ] Loss: 0.1934 top1= 94.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.6722 top1= 84.4551


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.5053 top1= 49.7796


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.4348 top1= 45.8033

Train epoch 3
[E 3B0  |    704/60000 (  1%) ] Loss: 0.1616 top1= 95.0000
[E 3B10 |   7744/60000 ( 13%) ] Loss: 0.1096 top1= 96.5625
[E 3B20 |  14784/60000 ( 25%) ] Loss: 0.1191 top1= 96.8750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.6032 top1= 85.6270


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.5369 top1= 50.1002


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.5998 top1= 46.2440

Train epoch 4
[E 4B0  |    704/60000 (  1%) ] Loss: 0.1162 top1= 96.2500
[E 4B10 |   7744/60000 ( 13%) ] Loss: 0.0783 top1= 97.8125
[E 4B20 |  14784/60000 ( 25%) ] Loss: 0.0776 top1= 97.1875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5554 top1= 85.9375


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.9249 top1= 50.4107


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.6657 top1= 46.4944

Train epoch 5
[E 5B0  |    704/60000 (  1%) ] Loss: 0.0765 top1= 98.2812
[E 5B10 |   7744/60000 ( 13%) ] Loss: 0.0585 top1= 98.2812
[E 5B20 |  14784/60000 ( 25%) ] Loss: 0.0538 top1= 98.4375

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5121 top1= 86.5986


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.1929 top1= 50.4507


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.9166 top1= 46.6847

Train epoch 6
[E 6B0  |    704/60000 (  1%) ] Loss: 0.0541 top1= 99.0625
[E 6B10 |   7744/60000 ( 13%) ] Loss: 0.0368 top1= 99.0625
[E 6B20 |  14784/60000 ( 25%) ] Loss: 0.0399 top1= 98.9062

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4774 top1= 87.0493


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.4670 top1= 50.5208


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.0817 top1= 46.8349

Train epoch 7
[E 7B0  |    704/60000 (  1%) ] Loss: 0.0406 top1= 99.2188
[E 7B10 |   7744/60000 ( 13%) ] Loss: 0.0268 top1= 99.5312
[E 7B20 |  14784/60000 ( 25%) ] Loss: 0.0301 top1= 99.2188

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4480 top1= 87.1895


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.7232 top1= 50.5108


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.5516 top1= 46.8850

Train epoch 8
[E 8B0  |    704/60000 (  1%) ] Loss: 0.0298 top1= 99.3750
[E 8B10 |   7744/60000 ( 13%) ] Loss: 0.0187 top1= 99.6875
[E 8B20 |  14784/60000 ( 25%) ] Loss: 0.0201 top1= 99.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4373 top1= 86.5485


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.8622 top1= 50.5409


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.0623 top1= 46.8049

Train epoch 9
[E 9B0  |    704/60000 (  1%) ] Loss: 0.0278 top1= 99.2188
[E 9B10 |   7744/60000 ( 13%) ] Loss: 0.0133 top1= 99.8438
[E 9B20 |  14784/60000 ( 25%) ] Loss: 0.0202 top1= 99.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4380 top1= 86.0777


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.7425 top1= 50.7011


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.4438 top1= 46.9551

Train epoch 10
[E10B0  |    704/60000 (  1%) ] Loss: 0.0138 top1= 99.6875
[E10B10 |   7744/60000 ( 13%) ] Loss: 0.0093 top1=100.0000
[E10B20 |  14784/60000 ( 25%) ] Loss: 0.0115 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4462 top1= 85.4667


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.8761 top1= 50.6510


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.7495 top1= 46.8149

Train epoch 11
[E11B0  |    704/60000 (  1%) ] Loss: 0.0145 top1= 99.5312
[E11B10 |   7744/60000 ( 13%) ] Loss: 0.0087 top1= 99.8438
[E11B20 |  14784/60000 ( 25%) ] Loss: 0.0101 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4245 top1= 86.4083


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.1295 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.0220 top1= 46.8349

Train epoch 12
[E12B0  |    704/60000 (  1%) ] Loss: 0.0110 top1= 99.6875
[E12B10 |   7744/60000 ( 13%) ] Loss: 0.0068 top1=100.0000
[E12B20 |  14784/60000 ( 25%) ] Loss: 0.0092 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4154 top1= 86.7188


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.3910 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.1421 top1= 46.9752

Train epoch 13
[E13B0  |    704/60000 (  1%) ] Loss: 0.0051 top1=100.0000
[E13B10 |   7744/60000 ( 13%) ] Loss: 0.0095 top1= 99.6875
[E13B20 |  14784/60000 ( 25%) ] Loss: 0.0046 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3891 top1= 87.3698


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.8053 top1= 50.7011


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.1218 top1= 47.1154

Train epoch 14
[E14B0  |    704/60000 (  1%) ] Loss: 0.0056 top1= 99.8438
[E14B10 |   7744/60000 ( 13%) ] Loss: 0.0028 top1=100.0000
[E14B20 |  14784/60000 ( 25%) ] Loss: 0.0054 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3754 top1= 87.8506


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.0560 top1= 50.6911


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.0124 top1= 47.0753

Train epoch 15
[E15B0  |    704/60000 (  1%) ] Loss: 0.0053 top1= 99.8438
[E15B10 |   7744/60000 ( 13%) ] Loss: 0.0024 top1=100.0000
[E15B20 |  14784/60000 ( 25%) ] Loss: 0.0087 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3726 top1= 88.2312


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.2600 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.0571 top1= 47.0553

Train epoch 16
[E16B0  |    704/60000 (  1%) ] Loss: 0.0025 top1=100.0000
[E16B10 |   7744/60000 ( 13%) ] Loss: 0.0025 top1=100.0000
[E16B20 |  14784/60000 ( 25%) ] Loss: 0.0037 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3872 top1= 86.9892


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.4314 top1= 50.7212


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.2543 top1= 47.1755

Train epoch 17
[E17B0  |    704/60000 (  1%) ] Loss: 0.0023 top1=100.0000
[E17B10 |   7744/60000 ( 13%) ] Loss: 0.0023 top1=100.0000
[E17B20 |  14784/60000 ( 25%) ] Loss: 0.0025 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3897 top1= 86.8990


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.5989 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.4989 top1= 47.2256

Train epoch 18
[E18B0  |    704/60000 (  1%) ] Loss: 0.0012 top1=100.0000
[E18B10 |   7744/60000 ( 13%) ] Loss: 0.0016 top1=100.0000
[E18B20 |  14784/60000 ( 25%) ] Loss: 0.0014 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3976 top1= 86.4383


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.7463 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.5946 top1= 47.2356

Train epoch 19
[E19B0  |    704/60000 (  1%) ] Loss: 0.0016 top1=100.0000
[E19B10 |   7744/60000 ( 13%) ] Loss: 0.0011 top1=100.0000
[E19B20 |  14784/60000 ( 25%) ] Loss: 0.0011 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3905 top1= 86.6887


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.8792 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.7917 top1= 47.2055

Train epoch 20
[E20B0  |    704/60000 (  1%) ] Loss: 0.0010 top1=100.0000
[E20B10 |   7744/60000 ( 13%) ] Loss: 0.0008 top1=100.0000
[E20B20 |  14784/60000 ( 25%) ] Loss: 0.0010 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3793 top1= 87.1194

