
=== 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 0x7fc7da43f250>

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: 1.0398 top1= 62.0312
[E 1B20 |  13440/60000 ( 22%) ] Loss: 0.3909 top1= 88.4375

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.6491 top1= 81.0998


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=7.4146 top1= 49.3690


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.7197 top1= 44.2508

Train epoch 2
[E 2B0  |    640/60000 (  1%) ] Loss: 0.2813 top1= 90.9375
[E 2B10 |   7040/60000 ( 12%) ] Loss: 0.1925 top1= 94.0625
[E 2B20 |  13440/60000 ( 22%) ] Loss: 0.1983 top1= 94.5312

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5205 top1= 86.8590


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=3.7234 top1= 50.0100


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=3.6070 top1= 45.8934

Train epoch 3
[E 3B0  |    640/60000 (  1%) ] Loss: 0.1511 top1= 95.1562
[E 3B10 |   7040/60000 ( 12%) ] Loss: 0.1147 top1= 97.3438
[E 3B20 |  13440/60000 ( 22%) ] Loss: 0.1510 top1= 95.4688

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4139 top1= 87.9808


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.9675 top1= 50.0501


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.7316 top1= 46.7548

Train epoch 4
[E 4B0  |    640/60000 (  1%) ] Loss: 0.1323 top1= 95.6250
[E 4B10 |   7040/60000 ( 12%) ] Loss: 0.0877 top1= 97.5000
[E 4B20 |  13440/60000 ( 22%) ] Loss: 0.1173 top1= 96.5625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3512 top1= 88.9423


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.6939 top1= 52.7043


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.3918 top1= 49.5292

Train epoch 5
[E 5B0  |    640/60000 (  1%) ] Loss: 0.1114 top1= 97.0312
[E 5B10 |   7040/60000 ( 12%) ] Loss: 0.0687 top1= 98.2812
[E 5B20 |  13440/60000 ( 22%) ] Loss: 0.0920 top1= 97.0312

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3142 top1= 89.6735


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.6458 top1= 54.2167


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.2549 top1= 51.9832

Train epoch 6
[E 6B0  |    640/60000 (  1%) ] Loss: 0.0858 top1= 97.9688
[E 6B10 |   7040/60000 ( 12%) ] Loss: 0.0491 top1= 98.9062
[E 6B20 |  13440/60000 ( 22%) ] Loss: 0.0720 top1= 97.8125

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2954 top1= 90.2544


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.6476 top1= 55.4487


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.1576 top1= 54.8878

Train epoch 7
[E 7B0  |    640/60000 (  1%) ] Loss: 0.0635 top1= 98.4375
[E 7B10 |   7040/60000 ( 12%) ] Loss: 0.0369 top1= 99.0625
[E 7B20 |  13440/60000 ( 22%) ] Loss: 0.0557 top1= 97.9688

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2903 top1= 90.3646


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.6593 top1= 56.7909


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.0517 top1= 57.1114

Train epoch 8
[E 8B0  |    640/60000 (  1%) ] Loss: 0.0479 top1= 98.9062
[E 8B10 |   7040/60000 ( 12%) ] Loss: 0.0281 top1= 99.6875
[E 8B20 |  13440/60000 ( 22%) ] Loss: 0.0464 top1= 98.4375

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2897 top1= 90.3045


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.5248 top1= 58.2232


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.1430 top1= 56.9311

Train epoch 9
[E 9B0  |    640/60000 (  1%) ] Loss: 0.0434 top1= 98.4375
[E 9B10 |   7040/60000 ( 12%) ] Loss: 0.0263 top1= 99.2188
[E 9B20 |  13440/60000 ( 22%) ] Loss: 0.0395 top1= 98.7500

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2688 top1= 91.1358


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.3142 top1= 60.0361


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.4259 top1= 55.0982

Train epoch 10
[E10B0  |    640/60000 (  1%) ] Loss: 0.0383 top1= 98.9062
[E10B10 |   7040/60000 ( 12%) ] Loss: 0.0334 top1= 98.4375
[E10B20 |  13440/60000 ( 22%) ] Loss: 0.0535 top1= 98.1250

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2690 top1= 90.7652


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.2193 top1= 60.1562


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.3849 top1= 57.6422

Train epoch 11
[E11B0  |    640/60000 (  1%) ] Loss: 0.0556 top1= 97.9688
[E11B10 |   7040/60000 ( 12%) ] Loss: 0.0297 top1= 99.5312
[E11B20 |  13440/60000 ( 22%) ] Loss: 0.0486 top1= 98.2812

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2511 top1= 91.5565


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.1549 top1= 59.8558


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.9958 top1= 58.8341

Train epoch 12
[E12B0  |    640/60000 (  1%) ] Loss: 0.0203 top1= 99.6875
[E12B10 |   7040/60000 ( 12%) ] Loss: 0.0159 top1= 99.8438
[E12B20 |  13440/60000 ( 22%) ] Loss: 0.0196 top1= 99.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2502 top1= 91.9071


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=2.1451 top1= 60.9075


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=2.0732 top1= 56.5104

Train epoch 13
[E13B0  |    640/60000 (  1%) ] Loss: 0.0427 top1= 98.5938
[E13B10 |   7040/60000 ( 12%) ] Loss: 0.0183 top1= 99.3750
[E13B20 |  13440/60000 ( 22%) ] Loss: 0.0118 top1= 99.8438

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2376 top1= 92.2075


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.8790 top1= 64.5933


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.9359 top1= 59.2248

Train epoch 14
[E14B0  |    640/60000 (  1%) ] Loss: 0.0195 top1= 99.3750
[E14B10 |   7040/60000 ( 12%) ] Loss: 0.0114 top1= 99.8438
[E14B20 |  13440/60000 ( 22%) ] Loss: 0.0115 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2261 top1= 92.7684


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.9961 top1= 63.3313


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.9656 top1= 59.4852

Train epoch 15
[E15B0  |    640/60000 (  1%) ] Loss: 0.0074 top1=100.0000
[E15B10 |   7040/60000 ( 12%) ] Loss: 0.0115 top1= 99.6875
[E15B20 |  13440/60000 ( 22%) ] Loss: 0.0143 top1= 99.3750

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2242 top1= 92.8586


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.7081 top1= 65.7953


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.6326 top1= 64.8037

Train epoch 16
[E16B0  |    640/60000 (  1%) ] Loss: 0.0090 top1=100.0000
[E16B10 |   7040/60000 ( 12%) ] Loss: 0.0070 top1=100.0000
[E16B20 |  13440/60000 ( 22%) ] Loss: 0.0120 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2301 top1= 92.8385


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.5763 top1= 67.5280


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.4227 top1= 68.2392

Train epoch 17
[E17B0  |    640/60000 (  1%) ] Loss: 0.0060 top1= 99.8438
[E17B10 |   7040/60000 ( 12%) ] Loss: 0.0038 top1=100.0000
[E17B20 |  13440/60000 ( 22%) ] Loss: 0.0057 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2325 top1= 92.8085


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.4683 top1= 68.9403


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.6537 top1= 66.0757

Train epoch 18
[E18B0  |    640/60000 (  1%) ] Loss: 0.0057 top1=100.0000
[E18B10 |   7040/60000 ( 12%) ] Loss: 0.0042 top1=100.0000
[E18B20 |  13440/60000 ( 22%) ] Loss: 0.0040 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2306 top1= 92.7784


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.4101 top1= 69.8317


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.5965 top1= 68.1691

Train epoch 19
[E19B0  |    640/60000 (  1%) ] Loss: 0.0069 top1= 99.8438
[E19B10 |   7040/60000 ( 12%) ] Loss: 0.0028 top1=100.0000
[E19B20 |  13440/60000 ( 22%) ] Loss: 0.0045 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2192 top1= 93.3894


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.4189 top1= 70.1022


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.3779 top1= 70.7933

Train epoch 20
[E20B0  |    640/60000 (  1%) ] Loss: 0.0025 top1=100.0000
[E20B10 |   7040/60000 ( 12%) ] Loss: 0.0030 top1=100.0000
[E20B20 |  13440/60000 ( 22%) ] Loss: 0.0043 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2222 top1= 93.3594


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.3592 top1= 71.4243


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.3562 top1= 71.4744

Train epoch 21
[E21B0  |    640/60000 (  1%) ] Loss: 0.0019 top1=100.0000
[E21B10 |   7040/60000 ( 12%) ] Loss: 0.0023 top1=100.0000
[E21B20 |  13440/60000 ( 22%) ] Loss: 0.0035 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2197 top1= 93.5296


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.3417 top1= 71.9050


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.2336 top1= 73.4075

Train epoch 22
[E22B0  |    640/60000 (  1%) ] Loss: 0.0017 top1=100.0000
[E22B10 |   7040/60000 ( 12%) ] Loss: 0.0021 top1=100.0000
[E22B20 |  13440/60000 ( 22%) ] Loss: 0.0021 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2215 top1= 93.5397


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.3062 top1= 72.5561


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.2165 top1= 74.2889

Train epoch 23
[E23B0  |    640/60000 (  1%) ] Loss: 0.0015 top1=100.0000
[E23B10 |   7040/60000 ( 12%) ] Loss: 0.0016 top1=100.0000
[E23B20 |  13440/60000 ( 22%) ] Loss: 0.0020 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2228 top1= 93.5697


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.2727 top1= 73.2071


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.2223 top1= 74.4091

Train epoch 24
[E24B0  |    640/60000 (  1%) ] Loss: 0.0015 top1=100.0000
[E24B10 |   7040/60000 ( 12%) ] Loss: 0.0016 top1=100.0000
[E24B20 |  13440/60000 ( 22%) ] Loss: 0.0018 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2235 top1= 93.6098


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.2415 top1= 73.8482


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.1731 top1= 75.4307

Train epoch 25
[E25B0  |    640/60000 (  1%) ] Loss: 0.0013 top1=100.0000
[E25B10 |   7040/60000 ( 12%) ] Loss: 0.0015 top1=100.0000
[E25B20 |  13440/60000 ( 22%) ] Loss: 0.0016 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2246 top1= 93.6098


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.2083 top1= 74.4591


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.1652 top1= 75.8113

Train epoch 26
[E26B0  |    640/60000 (  1%) ] Loss: 0.0012 top1=100.0000
[E26B10 |   7040/60000 ( 12%) ] Loss: 0.0013 top1=100.0000
[E26B20 |  13440/60000 ( 22%) ] Loss: 0.0015 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2252 top1= 93.6899


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1802 top1= 74.8698


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.1441 top1= 76.3321

Train epoch 27
[E27B0  |    640/60000 (  1%) ] Loss: 0.0012 top1=100.0000
[E27B10 |   7040/60000 ( 12%) ] Loss: 0.0012 top1=100.0000
[E27B20 |  13440/60000 ( 22%) ] Loss: 0.0014 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2259 top1= 93.7200


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1549 top1= 75.2304


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.1311 top1= 76.7027

Train epoch 28
[E28B0  |    640/60000 (  1%) ] Loss: 0.0011 top1=100.0000
[E28B10 |   7040/60000 ( 12%) ] Loss: 0.0012 top1=100.0000
[E28B20 |  13440/60000 ( 22%) ] Loss: 0.0013 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2266 top1= 93.7400


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1292 top1= 75.8313


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.1219 top1= 76.9131

Train epoch 29
[E29B0  |    640/60000 (  1%) ] Loss: 0.0011 top1=100.0000
[E29B10 |   7040/60000 ( 12%) ] Loss: 0.0011 top1=100.0000
[E29B20 |  13440/60000 ( 22%) ] Loss: 0.0012 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2271 top1= 93.7400


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.1070 top1= 76.1518


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.1111 top1= 77.2837

Train epoch 30
[E30B0  |    640/60000 (  1%) ] Loss: 0.0010 top1=100.0000
[E30B10 |   7040/60000 ( 12%) ] Loss: 0.0010 top1=100.0000
[E30B20 |  13440/60000 ( 22%) ] Loss: 0.0011 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2275 top1= 93.7800


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=1.0879 top1= 76.5625


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=1.1002 top1= 77.5841

