
=== 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 0x7f98e26cb2e0>

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=9.0302 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= 84.1847


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


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.4804 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=0.6283 top1= 85.3466


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.4722 top1= 50.1402


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.6354 top1= 46.1338

Train epoch 4
[E 4B0  |    704/60000 (  1%) ] Loss: 0.1211 top1= 96.7188
[E 4B10 |   7744/60000 ( 13%) ] Loss: 0.0800 top1= 97.9688
[E 4B20 |  14784/60000 ( 25%) ] Loss: 0.0838 top1= 97.1875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5785 top1= 86.1178


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.6225 top1= 50.3405


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.6171 top1= 46.4243

Train epoch 5
[E 5B0  |    704/60000 (  1%) ] Loss: 0.0853 top1= 97.6562
[E 5B10 |   7744/60000 ( 13%) ] Loss: 0.0635 top1= 98.1250
[E 5B20 |  14784/60000 ( 25%) ] Loss: 0.0599 top1= 98.2812

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5366 top1= 86.6787


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.7472 top1= 50.4107


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.7256 top1= 46.6947

Train epoch 6
[E 6B0  |    704/60000 (  1%) ] Loss: 0.0610 top1= 98.5938
[E 6B10 |   7744/60000 ( 13%) ] Loss: 0.0461 top1= 98.7500
[E 6B20 |  14784/60000 ( 25%) ] Loss: 0.0505 top1= 98.4375

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5030 top1= 87.2396


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.8426 top1= 50.4908


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.7901 top1= 46.7748

Train epoch 7
[E 7B0  |    704/60000 (  1%) ] Loss: 0.0466 top1= 99.0625
[E 7B10 |   7744/60000 ( 13%) ] Loss: 0.0310 top1= 99.2188
[E 7B20 |  14784/60000 ( 25%) ] Loss: 0.0378 top1= 98.9062

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4775 top1= 87.2997


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.9528 top1= 50.4708


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.8236 top1= 46.9852

Train epoch 8
[E 8B0  |    704/60000 (  1%) ] Loss: 0.0377 top1= 99.0625
[E 8B10 |   7744/60000 ( 13%) ] Loss: 0.0232 top1= 99.5312
[E 8B20 |  14784/60000 ( 25%) ] Loss: 0.0265 top1= 99.0625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4583 top1= 87.1294


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.9317 top1= 50.5308


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.2330 top1= 46.8149

Train epoch 9
[E 9B0  |    704/60000 (  1%) ] Loss: 0.0333 top1= 99.0625
[E 9B10 |   7744/60000 ( 13%) ] Loss: 0.0177 top1= 99.8438
[E 9B20 |  14784/60000 ( 25%) ] Loss: 0.0225 top1= 99.2188

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4514 top1= 86.7788


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.9456 top1= 50.6611


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.5028 top1= 46.8850

Train epoch 10
[E10B0  |    704/60000 (  1%) ] Loss: 0.0187 top1= 99.6875
[E10B10 |   7744/60000 ( 13%) ] Loss: 0.0117 top1=100.0000
[E10B20 |  14784/60000 ( 25%) ] Loss: 0.0158 top1= 99.5312

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4662 top1= 85.6070


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.9162 top1= 50.6611


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.8562 top1= 46.8850

Train epoch 11
[E11B0  |    704/60000 (  1%) ] Loss: 0.0166 top1= 99.5312
[E11B10 |   7744/60000 ( 13%) ] Loss: 0.0127 top1= 99.6875
[E11B20 |  14784/60000 ( 25%) ] Loss: 0.0113 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4443 top1= 86.4283


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.0565 top1= 50.6410


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.0583 top1= 46.9451

Train epoch 12
[E12B0  |    704/60000 (  1%) ] Loss: 0.0084 top1= 99.8438
[E12B10 |   7744/60000 ( 13%) ] Loss: 0.0086 top1=100.0000
[E12B20 |  14784/60000 ( 25%) ] Loss: 0.0098 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4301 top1= 86.7989


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.2497 top1= 50.6410


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.0693 top1= 47.0954

Train epoch 13
[E13B0  |    704/60000 (  1%) ] Loss: 0.0055 top1=100.0000
[E13B10 |   7744/60000 ( 13%) ] Loss: 0.0069 top1=100.0000
[E13B20 |  14784/60000 ( 25%) ] Loss: 0.0168 top1= 99.2188

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4270 top1= 86.6687


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.5370 top1= 50.6811


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.8356 top1= 47.0052

Train epoch 14
[E14B0  |    704/60000 (  1%) ] Loss: 0.0049 top1=100.0000
[E14B10 |   7744/60000 ( 13%) ] Loss: 0.0067 top1=100.0000
[E14B20 |  14784/60000 ( 25%) ] Loss: 0.0114 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3864 top1= 88.5817


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.8217 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.7645 top1= 47.0252

Train epoch 15
[E15B0  |    704/60000 (  1%) ] Loss: 0.0091 top1= 99.8438
[E15B10 |   7744/60000 ( 13%) ] Loss: 0.0032 top1=100.0000
[E15B20 |  14784/60000 ( 25%) ] Loss: 0.0143 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3897 top1= 88.5216


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.9924 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.2870 top1= 46.8249

Train epoch 16
[E16B0  |    704/60000 (  1%) ] Loss: 0.0076 top1=100.0000
[E16B10 |   7744/60000 ( 13%) ] Loss: 0.0071 top1= 99.8438
[E16B20 |  14784/60000 ( 25%) ] Loss: 0.0082 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4075 top1= 87.0793


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.1581 top1= 50.7212


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.5524 top1= 47.0553

Train epoch 17
[E17B0  |    704/60000 (  1%) ] Loss: 0.0041 top1=100.0000
[E17B10 |   7744/60000 ( 13%) ] Loss: 0.0032 top1=100.0000
[E17B20 |  14784/60000 ( 25%) ] Loss: 0.0021 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4015 top1= 86.9091


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.2963 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.7191 top1= 47.2857

Train epoch 18
[E18B0  |    704/60000 (  1%) ] Loss: 0.0020 top1=100.0000
[E18B10 |   7744/60000 ( 13%) ] Loss: 0.0022 top1=100.0000
[E18B20 |  14784/60000 ( 25%) ] Loss: 0.0024 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4027 top1= 86.7588


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.4190 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.9407 top1= 47.2756

Train epoch 19
[E19B0  |    704/60000 (  1%) ] Loss: 0.0018 top1=100.0000
[E19B10 |   7744/60000 ( 13%) ] Loss: 0.0014 top1=100.0000
[E19B20 |  14784/60000 ( 25%) ] Loss: 0.0021 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3882 top1= 87.4700


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.5421 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.1814 top1= 47.2857

Train epoch 20
[E20B0  |    704/60000 (  1%) ] Loss: 0.0010 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= 88.1110


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.6523 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.3204 top1= 47.2857

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=0.3757 top1= 87.9908


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.7572 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.4313 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: 0.0009 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3754 top1= 88.0108


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.8529 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.5700 top1= 47.2957

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=0.3748 top1= 87.9808


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.9436 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.6918 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=0.3741 top1= 88.0208


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.0293 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.7911 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: 0.0007 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3738 top1= 88.0208


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.1055 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.8839 top1= 47.2857

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=0.3734 top1= 88.0409


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.1813 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.9691 top1= 47.2857

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=0.3731 top1= 88.0108


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.2513 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.0484 top1= 47.2857

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=0.3728 top1= 88.0008


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.3186 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.1209 top1= 47.2857

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= 87.9908


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.3802 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.1925 top1= 47.2857

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= 88.0008


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.4413 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.2588 top1= 47.2857

