
=== 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 0x7f59f00fc6d0>

Train epoch 1
[E 1B0  |    640/60000 (  1%) ] Loss: 2.3080 top1=  8.4375

=== Peeking data label distribution E1B0 ===
Worker 0 has targets: tensor([4, 0, 4, 4, 4], device='cuda:0')
Worker 1 has targets: tensor([2, 6, 1, 4, 8], device='cuda:0')
Worker 2 has targets: tensor([3, 0, 3, 2, 7], device='cuda:0')
Worker 3 has targets: tensor([1, 4, 8, 2, 8], device='cuda:0')
Worker 4 has targets: tensor([9, 5, 0, 1, 3], device='cuda:0')
Worker 5 has targets: tensor([5, 6, 2, 4, 3], device='cuda:0')
Worker 6 has targets: tensor([2, 5, 0, 9, 9], device='cuda:0')
Worker 7 has targets: tensor([2, 2, 1, 9, 5], device='cuda:0')
Worker 8 has targets: tensor([3, 8, 7, 0, 3], device='cuda:0')
Worker 9 has targets: tensor([1, 7, 1, 7, 2], device='cuda:0')
Worker 10 has targets: tensor([8, 4, 4, 3, 9], device='cuda:0')
Worker 11 has targets: tensor([3, 4, 7, 7, 9], device='cuda:0')
Worker 12 has targets: tensor([7, 4, 3, 9, 4], device='cuda:0')
Worker 13 has targets: tensor([4, 5, 0, 7, 1], device='cuda:0')
Worker 14 has targets: tensor([4, 2, 3, 5, 5], device='cuda:0')
Worker 15 has targets: tensor([4, 7, 5, 4, 7], device='cuda:0')
Worker 16 has targets: tensor([1, 1, 5, 7, 9], device='cuda:0')
Worker 17 has targets: tensor([8, 7, 2, 2, 0], device='cuda:0')
Worker 18 has targets: tensor([7, 8, 0, 0, 6], device='cuda:0')
Worker 19 has targets: tensor([9, 9, 5, 2, 8], device='cuda:0')


[E 1B10 |   7040/60000 ( 12%) ] Loss: 1.8917 top1= 50.0000
[E 1B20 |  13440/60000 ( 22%) ] Loss: 0.8795 top1= 71.7188

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4451 top1= 86.9391


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.4718 top1= 86.3482


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.4621 top1= 85.9776

Train epoch 2
[E 2B0  |    640/60000 (  1%) ] Loss: 0.7474 top1= 75.7812
[E 2B10 |   7040/60000 ( 12%) ] Loss: 0.5952 top1= 81.0938
[E 2B20 |  13440/60000 ( 22%) ] Loss: 0.4463 top1= 87.6562

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3096 top1= 90.9255


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.3142 top1= 90.5950


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.3102 top1= 91.1058

Train epoch 3
[E 3B0  |    640/60000 (  1%) ] Loss: 0.2636 top1= 91.0938
[E 3B10 |   7040/60000 ( 12%) ] Loss: 0.2583 top1= 91.7188
[E 3B20 |  13440/60000 ( 22%) ] Loss: 0.2610 top1= 91.0938

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2407 top1= 92.9487


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2504 top1= 92.4880


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.2424 top1= 92.7484

Train epoch 4
[E 4B0  |    640/60000 (  1%) ] Loss: 0.1914 top1= 94.2188
[E 4B10 |   7040/60000 ( 12%) ] Loss: 0.1585 top1= 95.7812
[E 4B20 |  13440/60000 ( 22%) ] Loss: 0.1505 top1= 95.6250

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2045 top1= 93.9603


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2142 top1= 93.4595


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.2072 top1= 93.6699

Train epoch 5
[E 5B0  |    640/60000 (  1%) ] Loss: 0.1161 top1= 96.5625
[E 5B10 |   7040/60000 ( 12%) ] Loss: 0.0995 top1= 97.5000
[E 5B20 |  13440/60000 ( 22%) ] Loss: 0.0970 top1= 97.1875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1825 top1= 94.5413


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.1924 top1= 94.1707


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1821 top1= 94.4712

Train epoch 6
[E 6B0  |    640/60000 (  1%) ] Loss: 0.0751 top1= 98.4375
[E 6B10 |   7040/60000 ( 12%) ] Loss: 0.0585 top1= 98.9062
[E 6B20 |  13440/60000 ( 22%) ] Loss: 0.0633 top1= 98.5938

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1717 top1= 94.8818


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.1860 top1= 94.4712


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1661 top1= 94.9720

Train epoch 7
[E 7B0  |    640/60000 (  1%) ] Loss: 0.0527 top1= 98.9062
[E 7B10 |   7040/60000 ( 12%) ] Loss: 0.0338 top1= 99.5312
[E 7B20 |  13440/60000 ( 22%) ] Loss: 0.0423 top1= 99.2188

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1703 top1= 94.9920


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.1865 top1= 94.6815


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1614 top1= 95.1322

Train epoch 8
[E 8B0  |    640/60000 (  1%) ] Loss: 0.0341 top1= 99.6875
[E 8B10 |   7040/60000 ( 12%) ] Loss: 0.0219 top1=100.0000
[E 8B20 |  13440/60000 ( 22%) ] Loss: 0.0284 top1= 99.5312

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1727 top1= 95.0621


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.1870 top1= 94.7416


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1679 top1= 95.0821

Train epoch 9
[E 9B0  |    640/60000 (  1%) ] Loss: 0.0222 top1= 99.8438
[E 9B10 |   7040/60000 ( 12%) ] Loss: 0.0147 top1=100.0000
[E 9B20 |  13440/60000 ( 22%) ] Loss: 0.0189 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1790 top1= 95.0921


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.1883 top1= 94.9319


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1824 top1= 94.8818

Train epoch 10
[E10B0  |    640/60000 (  1%) ] Loss: 0.0149 top1= 99.8438
[E10B10 |   7040/60000 ( 12%) ] Loss: 0.0106 top1=100.0000
[E10B20 |  13440/60000 ( 22%) ] Loss: 0.0150 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1794 top1= 95.2324


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.1932 top1= 95.0220


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1749 top1= 95.2224

Train epoch 11
[E11B0  |    640/60000 (  1%) ] Loss: 0.0086 top1=100.0000
[E11B10 |   7040/60000 ( 12%) ] Loss: 0.0085 top1=100.0000
[E11B20 |  13440/60000 ( 22%) ] Loss: 0.0088 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1798 top1= 95.3826


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.1960 top1= 95.0921


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1707 top1= 95.4127

Train epoch 12
[E12B0  |    640/60000 (  1%) ] Loss: 0.0070 top1=100.0000
[E12B10 |   7040/60000 ( 12%) ] Loss: 0.0072 top1=100.0000
[E12B20 |  13440/60000 ( 22%) ] Loss: 0.0070 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1839 top1= 95.3926


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2022 top1= 95.1222


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1782 top1= 95.2724

Train epoch 13
[E13B0  |    640/60000 (  1%) ] Loss: 0.0058 top1=100.0000
[E13B10 |   7040/60000 ( 12%) ] Loss: 0.0052 top1=100.0000
[E13B20 |  13440/60000 ( 22%) ] Loss: 0.0055 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1868 top1= 95.5729


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2032 top1= 95.2123


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1801 top1= 95.4127

Train epoch 14
[E14B0  |    640/60000 (  1%) ] Loss: 0.0048 top1=100.0000
[E14B10 |   7040/60000 ( 12%) ] Loss: 0.0036 top1=100.0000
[E14B20 |  13440/60000 ( 22%) ] Loss: 0.0047 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1907 top1= 95.4828


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2058 top1= 95.1923


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1857 top1= 95.4828

Train epoch 15
[E15B0  |    640/60000 (  1%) ] Loss: 0.0037 top1=100.0000
[E15B10 |   7040/60000 ( 12%) ] Loss: 0.0029 top1=100.0000
[E15B20 |  13440/60000 ( 22%) ] Loss: 0.0037 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1943 top1= 95.3125


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2083 top1= 95.3425


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1887 top1= 95.4728

Train epoch 16
[E16B0  |    640/60000 (  1%) ] Loss: 0.0027 top1=100.0000
[E16B10 |   7040/60000 ( 12%) ] Loss: 0.0023 top1=100.0000
[E16B20 |  13440/60000 ( 22%) ] Loss: 0.0027 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.1969 top1= 95.3726


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2082 top1= 95.2324


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1900 top1= 95.4527

Train epoch 17
[E17B0  |    640/60000 (  1%) ] Loss: 0.0024 top1=100.0000
[E17B10 |   7040/60000 ( 12%) ] Loss: 0.0019 top1=100.0000
[E17B20 |  13440/60000 ( 22%) ] Loss: 0.0022 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2000 top1= 95.4026


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2114 top1= 95.2925


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1915 top1= 95.4728

Train epoch 18
[E18B0  |    640/60000 (  1%) ] Loss: 0.0023 top1=100.0000
[E18B10 |   7040/60000 ( 12%) ] Loss: 0.0017 top1=100.0000
[E18B20 |  13440/60000 ( 22%) ] Loss: 0.0021 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2019 top1= 95.4327


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2134 top1= 95.3325


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1938 top1= 95.5929

Train epoch 19
[E19B0  |    640/60000 (  1%) ] Loss: 0.0020 top1=100.0000
[E19B10 |   7040/60000 ( 12%) ] Loss: 0.0016 top1=100.0000
[E19B20 |  13440/60000 ( 22%) ] Loss: 0.0018 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2023 top1= 95.4627


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2149 top1= 95.3425


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1929 top1= 95.5829

Train epoch 20
[E20B0  |    640/60000 (  1%) ] Loss: 0.0015 top1=100.0000
[E20B10 |   7040/60000 ( 12%) ] Loss: 0.0016 top1=100.0000
[E20B20 |  13440/60000 ( 22%) ] Loss: 0.0015 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2036 top1= 95.4127


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2164 top1= 95.3526


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1947 top1= 95.5929

Train epoch 21
[E21B0  |    640/60000 (  1%) ] Loss: 0.0013 top1=100.0000
[E21B10 |   7040/60000 ( 12%) ] Loss: 0.0013 top1=100.0000
[E21B20 |  13440/60000 ( 22%) ] Loss: 0.0014 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2047 top1= 95.4127


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2177 top1= 95.3526


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1947 top1= 95.6430

Train epoch 22
[E22B0  |    640/60000 (  1%) ] Loss: 0.0011 top1=100.0000
[E22B10 |   7040/60000 ( 12%) ] Loss: 0.0011 top1=100.0000
[E22B20 |  13440/60000 ( 22%) ] Loss: 0.0013 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2057 top1= 95.4327


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2189 top1= 95.3626


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1951 top1= 95.6530

Train epoch 23
[E23B0  |    640/60000 (  1%) ] Loss: 0.0011 top1=100.0000
[E23B10 |   7040/60000 ( 12%) ] Loss: 0.0011 top1=100.0000
[E23B20 |  13440/60000 ( 22%) ] Loss: 0.0012 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2068 top1= 95.4427


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2199 top1= 95.3726


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1963 top1= 95.6530

Train epoch 24
[E24B0  |    640/60000 (  1%) ] Loss: 0.0010 top1=100.0000
[E24B10 |   7040/60000 ( 12%) ] Loss: 0.0010 top1=100.0000
[E24B20 |  13440/60000 ( 22%) ] Loss: 0.0011 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2078 top1= 95.4327


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2208 top1= 95.3626


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1974 top1= 95.6430

Train epoch 25
[E25B0  |    640/60000 (  1%) ] Loss: 0.0010 top1=100.0000
[E25B10 |   7040/60000 ( 12%) ] Loss: 0.0009 top1=100.0000
[E25B20 |  13440/60000 ( 22%) ] Loss: 0.0011 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2086 top1= 95.4327


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2216 top1= 95.3726


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1982 top1= 95.6330

Train epoch 26
[E26B0  |    640/60000 (  1%) ] Loss: 0.0009 top1=100.0000
[E26B10 |   7040/60000 ( 12%) ] Loss: 0.0009 top1=100.0000
[E26B20 |  13440/60000 ( 22%) ] Loss: 0.0010 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2094 top1= 95.4327


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2225 top1= 95.3726


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1990 top1= 95.6330

Train epoch 27
[E27B0  |    640/60000 (  1%) ] Loss: 0.0009 top1=100.0000
[E27B10 |   7040/60000 ( 12%) ] Loss: 0.0009 top1=100.0000
[E27B20 |  13440/60000 ( 22%) ] Loss: 0.0010 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2100 top1= 95.4427


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2231 top1= 95.3626


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.1997 top1= 95.6430

Train epoch 28
[E28B0  |    640/60000 (  1%) ] Loss: 0.0009 top1=100.0000
[E28B10 |   7040/60000 ( 12%) ] Loss: 0.0008 top1=100.0000
[E28B20 |  13440/60000 ( 22%) ] Loss: 0.0010 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2106 top1= 95.4427


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2236 top1= 95.3626


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.2004 top1= 95.6430

Train epoch 29
[E29B0  |    640/60000 (  1%) ] Loss: 0.0009 top1=100.0000
[E29B10 |   7040/60000 ( 12%) ] Loss: 0.0008 top1=100.0000
[E29B20 |  13440/60000 ( 22%) ] Loss: 0.0009 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2112 top1= 95.4427


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2243 top1= 95.3626


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.2010 top1= 95.6530

Train epoch 30
[E30B0  |    640/60000 (  1%) ] Loss: 0.0008 top1=100.0000
[E30B10 |   7040/60000 ( 12%) ] Loss: 0.0008 top1=100.0000
[E30B20 |  13440/60000 ( 22%) ] Loss: 0.0009 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2117 top1= 95.4627


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=0.2248 top1= 95.4127


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=0.2016 top1= 95.6430

