
=== 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.Dumbbell object at 0x7fa6abe8d490>

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: 1.0334 top1= 62.1875
[E 1B20 |  14784/60000 ( 25%) ] Loss: 0.3980 top1= 88.2812

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.7232 top1= 78.8962


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=8.9532 top1= 49.3089


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=7.7106 top1= 44.2508

Train epoch 2
[E 2B0  |    704/60000 (  1%) ] Loss: 0.2803 top1= 90.7812
[E 2B10 |   7744/60000 ( 13%) ] Loss: 0.1890 top1= 93.7500
[E 2B20 |  14784/60000 ( 25%) ] Loss: 0.1960 top1= 94.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.6689 top1= 84.6855


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.5022 top1= 49.8598


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.4957 top1= 45.7933

Train epoch 3
[E 3B0  |    704/60000 (  1%) ] Loss: 0.1612 top1= 95.0000
[E 3B10 |   7744/60000 ( 13%) ] Loss: 0.1099 top1= 96.7188
[E 3B20 |  14784/60000 ( 25%) ] Loss: 0.1228 top1= 96.5625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.6019 top1= 86.3281


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.4615 top1= 50.1302


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.6090 top1= 46.1538

Train epoch 4
[E 4B0  |    704/60000 (  1%) ] Loss: 0.1172 top1= 96.4062
[E 4B10 |   7744/60000 ( 13%) ] Loss: 0.0803 top1= 97.9688
[E 4B20 |  14784/60000 ( 25%) ] Loss: 0.0783 top1= 97.5000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.5429 top1= 86.8389


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.5737 top1= 50.3405


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.6490 top1= 46.4643

Train epoch 5
[E 5B0  |    704/60000 (  1%) ] Loss: 0.0795 top1= 98.1250
[E 5B10 |   7744/60000 ( 13%) ] Loss: 0.0583 top1= 98.2812
[E 5B20 |  14784/60000 ( 25%) ] Loss: 0.0546 top1= 98.2812

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4938 top1= 86.9692


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.7275 top1= 50.4708


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.7308 top1= 46.6747

Train epoch 6
[E 6B0  |    704/60000 (  1%) ] Loss: 0.0590 top1= 98.7500
[E 6B10 |   7744/60000 ( 13%) ] Loss: 0.0415 top1= 98.9062
[E 6B20 |  14784/60000 ( 25%) ] Loss: 0.0400 top1= 98.5938

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4540 top1= 87.5901


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.8827 top1= 50.5308


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.7488 top1= 46.8450

Train epoch 7
[E 7B0  |    704/60000 (  1%) ] Loss: 0.0414 top1= 99.0625
[E 7B10 |   7744/60000 ( 13%) ] Loss: 0.0265 top1= 99.5312
[E 7B20 |  14784/60000 ( 25%) ] Loss: 0.0341 top1= 99.0625

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.4214 top1= 88.6218


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.0804 top1= 50.5208


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.7032 top1= 46.7648

Train epoch 8
[E 8B0  |    704/60000 (  1%) ] Loss: 0.0327 top1= 99.2188
[E 8B10 |   7744/60000 ( 13%) ] Loss: 0.0242 top1= 99.3750
[E 8B20 |  14784/60000 ( 25%) ] Loss: 0.0276 top1= 99.2188

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3968 top1= 88.6819


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.2088 top1= 50.5108


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.7676 top1= 47.0853

Train epoch 9
[E 9B0  |    704/60000 (  1%) ] Loss: 0.0220 top1= 99.5312
[E 9B10 |   7744/60000 ( 13%) ] Loss: 0.0166 top1= 99.8438
[E 9B20 |  14784/60000 ( 25%) ] Loss: 0.0194 top1= 99.5312

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3860 top1= 88.3614


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.1500 top1= 50.5509


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.0983 top1= 46.8049

Train epoch 10
[E10B0  |    704/60000 (  1%) ] Loss: 0.0231 top1= 99.3750
[E10B10 |   7744/60000 ( 13%) ] Loss: 0.0120 top1= 99.8438
[E10B20 |  14784/60000 ( 25%) ] Loss: 0.0151 top1= 99.6875

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3730 top1= 88.7119


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=6.0151 top1= 50.6510


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.2152 top1= 46.9551

Train epoch 11
[E11B0  |    704/60000 (  1%) ] Loss: 0.0090 top1= 99.8438
[E11B10 |   7744/60000 ( 13%) ] Loss: 0.0106 top1=100.0000
[E11B20 |  14784/60000 ( 25%) ] Loss: 0.0214 top1= 99.2188

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3784 top1= 87.9107


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.7616 top1= 50.6811


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.2618 top1= 47.0052

Train epoch 12
[E12B0  |    704/60000 (  1%) ] Loss: 0.0115 top1= 99.6875
[E12B10 |   7744/60000 ( 13%) ] Loss: 0.0093 top1= 99.8438
[E12B20 |  14784/60000 ( 25%) ] Loss: 0.0101 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3669 top1= 88.4816


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.7621 top1= 50.6210


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.2877 top1= 47.0753

Train epoch 13
[E13B0  |    704/60000 (  1%) ] Loss: 0.0086 top1=100.0000
[E13B10 |   7744/60000 ( 13%) ] Loss: 0.0102 top1=100.0000
[E13B20 |  14784/60000 ( 25%) ] Loss: 0.0108 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3373 top1= 89.6534


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.4925 top1= 50.6611


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.1881 top1= 47.1454

Train epoch 14
[E14B0  |    704/60000 (  1%) ] Loss: 0.0056 top1=100.0000
[E14B10 |   7744/60000 ( 13%) ] Loss: 0.0036 top1=100.0000
[E14B20 |  14784/60000 ( 25%) ] Loss: 0.0056 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3355 top1= 89.6635


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.4169 top1= 50.6911


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.0103 top1= 46.8850

Train epoch 15
[E15B0  |    704/60000 (  1%) ] Loss: 0.0076 top1=100.0000
[E15B10 |   7744/60000 ( 13%) ] Loss: 0.0035 top1=100.0000
[E15B20 |  14784/60000 ( 25%) ] Loss: 0.0062 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3254 top1= 89.9038


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.4535 top1= 50.6711


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.0572 top1= 47.1755

Train epoch 16
[E16B0  |    704/60000 (  1%) ] Loss: 0.0029 top1=100.0000
[E16B10 |   7744/60000 ( 13%) ] Loss: 0.0029 top1=100.0000
[E16B20 |  14784/60000 ( 25%) ] Loss: 0.0046 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3253 top1= 89.6935


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.5090 top1= 50.7212


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.0811 top1= 47.0753

Train epoch 17
[E17B0  |    704/60000 (  1%) ] Loss: 0.0036 top1=100.0000
[E17B10 |   7744/60000 ( 13%) ] Loss: 0.0027 top1=100.0000
[E17B20 |  14784/60000 ( 25%) ] Loss: 0.0035 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3133 top1= 90.0441


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.4928 top1= 50.7412


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=6.0042 top1= 47.1454

Train epoch 18
[E18B0  |    704/60000 (  1%) ] Loss: 0.0024 top1=100.0000
[E18B10 |   7744/60000 ( 13%) ] Loss: 0.0021 top1=100.0000
[E18B20 |  14784/60000 ( 25%) ] Loss: 0.0030 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3156 top1= 89.9239


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.4215 top1= 50.7512


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.9338 top1= 47.1955

Train epoch 19
[E19B0  |    704/60000 (  1%) ] Loss: 0.0023 top1=100.0000
[E19B10 |   7744/60000 ( 13%) ] Loss: 0.0023 top1=100.0000
[E19B20 |  14784/60000 ( 25%) ] Loss: 0.0029 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3142 top1= 89.8838


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.3370 top1= 50.7312


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.8025 top1= 47.2155

Train epoch 20
[E20B0  |    704/60000 (  1%) ] Loss: 0.0022 top1=100.0000
[E20B10 |   7744/60000 ( 13%) ] Loss: 0.0023 top1=100.0000
[E20B20 |  14784/60000 ( 25%) ] Loss: 0.0028 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3124 top1= 89.9639


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.2332 top1= 50.7212


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.6706 top1= 47.2055

Train epoch 21
[E21B0  |    704/60000 (  1%) ] Loss: 0.0021 top1=100.0000
[E21B10 |   7744/60000 ( 13%) ] Loss: 0.0022 top1=100.0000
[E21B20 |  14784/60000 ( 25%) ] Loss: 0.0028 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3109 top1= 89.9539


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.1255 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.5337 top1= 47.1855

Train epoch 22
[E22B0  |    704/60000 (  1%) ] Loss: 0.0021 top1=100.0000
[E22B10 |   7744/60000 ( 13%) ] Loss: 0.0022 top1=100.0000
[E22B20 |  14784/60000 ( 25%) ] Loss: 0.0028 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3082 top1= 90.0441


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=5.0104 top1= 50.7011


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.4025 top1= 47.1755

Train epoch 23
[E23B0  |    704/60000 (  1%) ] Loss: 0.0021 top1=100.0000
[E23B10 |   7744/60000 ( 13%) ] Loss: 0.0022 top1=100.0000
[E23B20 |  14784/60000 ( 25%) ] Loss: 0.0028 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3055 top1= 90.1142


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.8960 top1= 50.7011


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.2698 top1= 47.1655

Train epoch 24
[E24B0  |    704/60000 (  1%) ] Loss: 0.0021 top1=100.0000
[E24B10 |   7744/60000 ( 13%) ] Loss: 0.0021 top1=100.0000
[E24B20 |  14784/60000 ( 25%) ] Loss: 0.0028 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.3023 top1= 90.1843


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.7868 top1= 50.6911


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.1416 top1= 47.1655

Train epoch 25
[E25B0  |    704/60000 (  1%) ] Loss: 0.0022 top1=100.0000
[E25B10 |   7744/60000 ( 13%) ] Loss: 0.0021 top1=100.0000
[E25B20 |  14784/60000 ( 25%) ] Loss: 0.0029 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2993 top1= 90.3045


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.6770 top1= 50.6811


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=5.0083 top1= 47.1554

Train epoch 26
[E26B0  |    704/60000 (  1%) ] Loss: 0.0022 top1=100.0000
[E26B10 |   7744/60000 ( 13%) ] Loss: 0.0022 top1=100.0000
[E26B20 |  14784/60000 ( 25%) ] Loss: 0.0029 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2958 top1= 90.4247


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.5635 top1= 50.6811


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.8746 top1= 47.1554

Train epoch 27
[E27B0  |    704/60000 (  1%) ] Loss: 0.0022 top1=100.0000
[E27B10 |   7744/60000 ( 13%) ] Loss: 0.0022 top1=100.0000
[E27B20 |  14784/60000 ( 25%) ] Loss: 0.0029 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2927 top1= 90.5148


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.4594 top1= 50.7111


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.7505 top1= 47.1354

Train epoch 28
[E28B0  |    704/60000 (  1%) ] Loss: 0.0022 top1=100.0000
[E28B10 |   7744/60000 ( 13%) ] Loss: 0.0022 top1=100.0000
[E28B20 |  14784/60000 ( 25%) ] Loss: 0.0029 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2896 top1= 90.4848


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.3569 top1= 50.7712


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.6192 top1= 47.1154

Train epoch 29
[E29B0  |    704/60000 (  1%) ] Loss: 0.0022 top1=100.0000
[E29B10 |   7744/60000 ( 13%) ] Loss: 0.0022 top1=100.0000
[E29B20 |  14784/60000 ( 25%) ] Loss: 0.0029 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2870 top1= 90.5749


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.2597 top1= 50.8514


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.4952 top1= 47.1354

Train epoch 30
[E30B0  |    704/60000 (  1%) ] Loss: 0.0023 top1=100.0000
[E30B10 |   7744/60000 ( 13%) ] Loss: 0.0022 top1=100.0000
[E30B20 |  14784/60000 ( 25%) ] Loss: 0.0029 top1=100.0000

=> Averaged model (Global Average Validation Accuracy) | Eval Loss=0.2840 top1= 90.7151


=> Averaged model (Clique1 Average Validation Accuracy) | Eval Loss=4.1650 top1= 50.9716


=> Averaged model (Clique2 Average Validation Accuracy) | Eval Loss=4.3836 top1= 47.1454

