
=== 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)

=== Start adding graph ===
<codes.graph_utils.Dumbbell object at 0x7ffbb4196250>

Train epoch 1
[E 1B0  |    640/60000 (  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')


[E 1B10 |   7040/60000 ( 12%) ] Loss: 1.0369 top1= 61.7188
[E 1B20 |  13440/60000 ( 22%) ] Loss: 0.4004 top1= 88.4375

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.7370 top1= 78.2352


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=9.1292 top1= 49.2788


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.7707 top1= 44.2208

Train epoch 2
[E 2B0  |    640/60000 (  1%) ] Loss: 0.2859 top1= 90.7812
[E 2B10 |   7040/60000 ( 12%) ] Loss: 0.1924 top1= 93.7500
[E 2B20 |  13440/60000 ( 22%) ] Loss: 0.1985 top1= 94.0625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.6901 top1= 84.0946


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.6220 top1= 49.7897


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.4843 top1= 45.7632

Train epoch 3
[E 3B0  |    640/60000 (  1%) ] Loss: 0.1628 top1= 94.6875
[E 3B10 |   7040/60000 ( 12%) ] Loss: 0.1095 top1= 96.8750
[E 3B20 |  13440/60000 ( 22%) ] Loss: 0.1245 top1= 96.2500

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.6248 top1= 85.3666


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.5646 top1= 50.1402


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.6446 top1= 46.1538

Train epoch 4
[E 4B0  |    640/60000 (  1%) ] Loss: 0.1176 top1= 96.7188
[E 4B10 |   7040/60000 ( 12%) ] Loss: 0.0802 top1= 97.9688
[E 4B20 |  13440/60000 ( 22%) ] Loss: 0.0798 top1= 97.1875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5757 top1= 85.6470


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.7567 top1= 50.3706


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.6272 top1= 46.4543

Train epoch 5
[E 5B0  |    640/60000 (  1%) ] Loss: 0.0818 top1= 98.1250
[E 5B10 |   7040/60000 ( 12%) ] Loss: 0.0631 top1= 98.2812
[E 5B20 |  13440/60000 ( 22%) ] Loss: 0.0578 top1= 98.2812

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5368 top1= 86.2280


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.8793 top1= 50.4507


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.7555 top1= 46.7348

Train epoch 6
[E 6B0  |    640/60000 (  1%) ] Loss: 0.0579 top1= 98.7500
[E 6B10 |   7040/60000 ( 12%) ] Loss: 0.0429 top1= 98.5938
[E 6B20 |  13440/60000 ( 22%) ] Loss: 0.0487 top1= 98.4375

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5000 top1= 86.9892


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.0058 top1= 50.5208


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.8159 top1= 46.7648

Train epoch 7
[E 7B0  |    640/60000 (  1%) ] Loss: 0.0457 top1= 99.2188
[E 7B10 |   7040/60000 ( 12%) ] Loss: 0.0303 top1= 99.3750
[E 7B20 |  13440/60000 ( 22%) ] Loss: 0.0334 top1= 98.9062

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4788 top1= 86.4984


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.1163 top1= 50.5008


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.0751 top1= 46.9451

Train epoch 8
[E 8B0  |    640/60000 (  1%) ] Loss: 0.0347 top1= 99.3750
[E 8B10 |   7040/60000 ( 12%) ] Loss: 0.0227 top1= 99.3750
[E 8B20 |  13440/60000 ( 22%) ] Loss: 0.0259 top1= 99.2188

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4658 top1= 85.9976


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.1806 top1= 50.6010


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.5741 top1= 46.7849

Train epoch 9
[E 9B0  |    640/60000 (  1%) ] Loss: 0.0314 top1= 99.2188
[E 9B10 |   7040/60000 ( 12%) ] Loss: 0.0145 top1= 99.8438
[E 9B20 |  13440/60000 ( 22%) ] Loss: 0.0229 top1= 99.2188

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4753 top1= 85.1362


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.2046 top1= 50.6611


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.8220 top1= 46.8550

Train epoch 10
[E10B0  |    640/60000 (  1%) ] Loss: 0.0207 top1= 99.5312
[E10B10 |   7040/60000 ( 12%) ] Loss: 0.0142 top1= 99.6875
[E10B20 |  13440/60000 ( 22%) ] Loss: 0.0123 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4630 top1= 85.0962


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.3981 top1= 50.6310


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.1672 top1= 46.7849

Train epoch 11
[E11B0  |    640/60000 (  1%) ] Loss: 0.0126 top1= 99.8438
[E11B10 |   7040/60000 ( 12%) ] Loss: 0.0105 top1= 99.8438
[E11B20 |  13440/60000 ( 22%) ] Loss: 0.0106 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4511 top1= 85.5669


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.5585 top1= 50.6310


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.2744 top1= 47.0252

Train epoch 12
[E12B0  |    640/60000 (  1%) ] Loss: 0.0073 top1= 99.8438
[E12B10 |   7040/60000 ( 12%) ] Loss: 0.0080 top1=100.0000
[E12B20 |  13440/60000 ( 22%) ] Loss: 0.0165 top1= 99.0625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4329 top1= 86.2881


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.8018 top1= 50.6611


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.1310 top1= 47.0353

Train epoch 13
[E13B0  |    640/60000 (  1%) ] Loss: 0.0067 top1=100.0000
[E13B10 |   7040/60000 ( 12%) ] Loss: 0.0051 top1=100.0000
[E13B20 |  13440/60000 ( 22%) ] Loss: 0.0192 top1= 99.0625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4068 top1= 87.3698


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.1092 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.9244 top1= 47.1755

Train epoch 14
[E14B0  |    640/60000 (  1%) ] Loss: 0.0043 top1=100.0000
[E14B10 |   7040/60000 ( 12%) ] Loss: 0.0032 top1=100.0000
[E14B20 |  13440/60000 ( 22%) ] Loss: 0.0090 top1= 99.5312

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3907 top1= 88.2512


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.3666 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.8791 top1= 46.5545

Train epoch 15
[E15B0  |    640/60000 (  1%) ] Loss: 0.0221 top1= 99.3750
[E15B10 |   7040/60000 ( 12%) ] Loss: 0.0046 top1=100.0000
[E15B20 |  13440/60000 ( 22%) ] Loss: 0.0045 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3939 top1= 87.6002


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.5374 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.5508 top1= 47.2055

Train epoch 16
[E16B0  |    640/60000 (  1%) ] Loss: 0.0024 top1=100.0000
[E16B10 |   7040/60000 ( 12%) ] Loss: 0.0024 top1=100.0000
[E16B20 |  13440/60000 ( 22%) ] Loss: 0.0033 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4016 top1= 86.8890


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.7164 top1= 50.7212


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.8606 top1= 47.2556

Train epoch 17
[E17B0  |    640/60000 (  1%) ] Loss: 0.0023 top1=100.0000
[E17B10 |   7040/60000 ( 12%) ] Loss: 0.0025 top1=100.0000
[E17B20 |  13440/60000 ( 22%) ] Loss: 0.0028 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4214 top1= 85.8674


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.8474 top1= 50.7212


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.2154 top1= 47.1755

Train epoch 18
[E18B0  |    640/60000 (  1%) ] Loss: 0.0023 top1=100.0000
[E18B10 |   7040/60000 ( 12%) ] Loss: 0.0020 top1=100.0000
[E18B20 |  13440/60000 ( 22%) ] Loss: 0.0029 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4174 top1= 85.9575


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.9773 top1= 50.7212


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.4294 top1= 47.1955

Train epoch 19
[E19B0  |    640/60000 (  1%) ] Loss: 0.0016 top1=100.0000
[E19B10 |   7040/60000 ( 12%) ] Loss: 0.0014 top1=100.0000
[E19B20 |  13440/60000 ( 22%) ] Loss: 0.0017 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3951 top1= 86.7788


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.1091 top1= 50.7212


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.6066 top1= 47.2556

Train epoch 20
[E20B0  |    640/60000 (  1%) ] Loss: 0.0010 top1=100.0000
[E20B10 |   7040/60000 ( 12%) ] Loss: 0.0011 top1=100.0000
[E20B20 |  13440/60000 ( 22%) ] Loss: 0.0012 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3884 top1= 87.1494


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.2332 top1= 50.7212


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.7359 top1= 47.2857

Train epoch 21
[E21B0  |    640/60000 (  1%) ] Loss: 0.0009 top1=100.0000
[E21B10 |   7040/60000 ( 12%) ] Loss: 0.0010 top1=100.0000
[E21B20 |  13440/60000 ( 22%) ] Loss: 0.0010 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3910 top1= 86.8890


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.3426 top1= 50.7212


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.8781 top1= 47.2756

Train epoch 22
[E22B0  |    640/60000 (  1%) ] Loss: 0.0008 top1=100.0000
[E22B10 |   7040/60000 ( 12%) ] Loss: 0.0009 top1=100.0000
[E22B20 |  13440/60000 ( 22%) ] Loss: 0.0009 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3902 top1= 86.9391


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.4504 top1= 50.7212


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.0088 top1= 47.2857

Train epoch 23
[E23B0  |    640/60000 (  1%) ] Loss: 0.0007 top1=100.0000
[E23B10 |   7040/60000 ( 12%) ] Loss: 0.0008 top1=100.0000
[E23B20 |  13440/60000 ( 22%) ] Loss: 0.0008 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3903 top1= 86.9291


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.5416 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.1197 top1= 47.2857

Train epoch 24
[E24B0  |    640/60000 (  1%) ] Loss: 0.0006 top1=100.0000
[E24B10 |   7040/60000 ( 12%) ] Loss: 0.0007 top1=100.0000
[E24B20 |  13440/60000 ( 22%) ] Loss: 0.0008 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3901 top1= 86.8990


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.6339 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.2177 top1= 47.2756

Train epoch 25
[E25B0  |    640/60000 (  1%) ] Loss: 0.0006 top1=100.0000
[E25B10 |   7040/60000 ( 12%) ] Loss: 0.0007 top1=100.0000
[E25B20 |  13440/60000 ( 22%) ] Loss: 0.0007 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3902 top1= 86.8990


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.7198 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.3113 top1= 47.2756

Train epoch 26
[E26B0  |    640/60000 (  1%) ] Loss: 0.0006 top1=100.0000
[E26B10 |   7040/60000 ( 12%) ] Loss: 0.0006 top1=100.0000
[E26B20 |  13440/60000 ( 22%) ] Loss: 0.0007 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3903 top1= 86.8890


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.7973 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.3969 top1= 47.2756

Train epoch 27
[E27B0  |    640/60000 (  1%) ] Loss: 0.0005 top1=100.0000
[E27B10 |   7040/60000 ( 12%) ] Loss: 0.0006 top1=100.0000
[E27B20 |  13440/60000 ( 22%) ] Loss: 0.0006 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3901 top1= 86.9291


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.8757 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.4761 top1= 47.2756

Train epoch 28
[E28B0  |    640/60000 (  1%) ] Loss: 0.0005 top1=100.0000
[E28B10 |   7040/60000 ( 12%) ] Loss: 0.0005 top1=100.0000
[E28B20 |  13440/60000 ( 22%) ] Loss: 0.0006 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3904 top1= 86.9091


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.9467 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.5531 top1= 47.2756

Train epoch 29
[E29B0  |    640/60000 (  1%) ] Loss: 0.0005 top1=100.0000
[E29B10 |   7040/60000 ( 12%) ] Loss: 0.0005 top1=100.0000
[E29B20 |  13440/60000 ( 22%) ] Loss: 0.0005 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3904 top1= 86.8990


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=9.0129 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.6228 top1= 47.2756

Train epoch 30
[E30B0  |    640/60000 (  1%) ] Loss: 0.0004 top1=100.0000
[E30B10 |   7040/60000 ( 12%) ] Loss: 0.0005 top1=100.0000
[E30B20 |  13440/60000 ( 22%) ] Loss: 0.0005 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3906 top1= 86.8890


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=9.0800 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=8.6906 top1= 47.2756

