INFO:root:Namespace(batch_size=128, drop_rate=0.0, lr=0.1, lr_decay=0.1, lr_decay_epoch='100,150', lr_decay_period=0, mode='hybrid', model='cifar_resnet56_v1', momentum=0.9, num_epochs=200, num_gpus=1, num_workers=2, resume_from=None, save_dir='params', save_period=10, save_plot_dir='.', wd=0.0001)
[05:57:48] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:107: Running performance tests to find the best convolution algorithm, this can take a while... (setting env variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)
INFO:root:[Epoch 0] train=0.234535 val=0.353100 loss=2.055083 time: 34.300543
INFO:root:[Epoch 1] train=0.432131 val=0.498400 loss=1.541775 time: 31.162080
INFO:root:[Epoch 2] train=0.538882 val=0.522400 loss=1.270704 time: 30.720395
INFO:root:[Epoch 3] train=0.621935 val=0.598800 loss=1.056064 time: 32.234503
INFO:root:[Epoch 4] train=0.685116 val=0.710800 loss=0.892422 time: 32.212667
INFO:root:[Epoch 5] train=0.729868 val=0.732000 loss=0.774074 time: 33.035454
INFO:root:[Epoch 6] train=0.760176 val=0.742700 loss=0.691478 time: 33.327777
INFO:root:[Epoch 7] train=0.784535 val=0.763100 loss=0.622581 time: 32.677076
INFO:root:[Epoch 8] train=0.804567 val=0.769500 loss=0.568445 time: 33.191586
INFO:root:[Epoch 9] train=0.815004 val=0.810800 loss=0.534772 time: 31.716232
INFO:root:[Epoch 10] train=0.825341 val=0.812800 loss=0.502263 time: 32.393170
INFO:root:[Epoch 11] train=0.837981 val=0.827000 loss=0.469401 time: 31.291527
INFO:root:[Epoch 12] train=0.844611 val=0.787300 loss=0.449841 time: 32.488818
INFO:root:[Epoch 13] train=0.850461 val=0.827800 loss=0.425620 time: 32.858016
INFO:root:[Epoch 14] train=0.855629 val=0.828500 loss=0.416210 time: 31.615326
INFO:root:[Epoch 15] train=0.865284 val=0.834500 loss=0.392316 time: 32.318216
INFO:root:[Epoch 16] train=0.867728 val=0.827200 loss=0.379356 time: 31.658130
INFO:root:[Epoch 17] train=0.875321 val=0.835100 loss=0.359413 time: 32.066407
INFO:root:[Epoch 18] train=0.880028 val=0.840900 loss=0.347205 time: 31.572033
INFO:root:[Epoch 19] train=0.881210 val=0.835200 loss=0.343836 time: 32.062587
INFO:root:[Epoch 20] train=0.884896 val=0.856100 loss=0.331050 time: 31.975466
INFO:root:[Epoch 21] train=0.887780 val=0.825300 loss=0.320164 time: 33.188688
INFO:root:[Epoch 22] train=0.890124 val=0.850600 loss=0.311759 time: 31.970913
INFO:root:[Epoch 23] train=0.895633 val=0.835000 loss=0.302689 time: 32.890775
INFO:root:[Epoch 24] train=0.894571 val=0.850600 loss=0.298038 time: 33.781522
INFO:root:[Epoch 25] train=0.900401 val=0.848900 loss=0.285157 time: 32.604851
INFO:root:[Epoch 26] train=0.901683 val=0.853100 loss=0.282496 time: 33.803116
INFO:root:[Epoch 27] train=0.903746 val=0.854700 loss=0.276669 time: 32.922922
INFO:root:[Epoch 28] train=0.906190 val=0.855200 loss=0.271550 time: 32.242459
INFO:root:[Epoch 29] train=0.906030 val=0.845400 loss=0.268206 time: 31.146300
INFO:root:[Epoch 30] train=0.907252 val=0.854300 loss=0.263715 time: 31.821185
INFO:root:[Epoch 31] train=0.908854 val=0.834200 loss=0.259952 time: 32.326535
INFO:root:[Epoch 32] train=0.912360 val=0.863400 loss=0.251737 time: 32.413487
INFO:root:[Epoch 33] train=0.913922 val=0.872000 loss=0.246101 time: 33.060503
INFO:root:[Epoch 34] train=0.914764 val=0.853800 loss=0.244242 time: 31.947150
INFO:root:[Epoch 35] train=0.915825 val=0.857200 loss=0.240445 time: 31.431173
INFO:root:[Epoch 36] train=0.916406 val=0.865600 loss=0.236711 time: 32.374483
INFO:root:[Epoch 37] train=0.918590 val=0.870300 loss=0.232466 time: 31.986584
INFO:root:[Epoch 38] train=0.917508 val=0.871600 loss=0.232335 time: 31.862705
INFO:root:[Epoch 39] train=0.920052 val=0.872600 loss=0.229125 time: 31.656471
INFO:root:[Epoch 40] train=0.919712 val=0.847600 loss=0.225934 time: 31.219544
INFO:root:[Epoch 41] train=0.923097 val=0.870000 loss=0.221566 time: 32.539330
INFO:root:[Epoch 42] train=0.924539 val=0.862600 loss=0.215706 time: 30.943610
INFO:root:[Epoch 43] train=0.924139 val=0.868300 loss=0.216846 time: 31.947647
INFO:root:[Epoch 44] train=0.924159 val=0.860400 loss=0.216107 time: 31.609515
INFO:root:[Epoch 45] train=0.924119 val=0.867700 loss=0.214148 time: 33.142598
INFO:root:[Epoch 46] train=0.927344 val=0.849500 loss=0.206702 time: 31.999551
INFO:root:[Epoch 47] train=0.924639 val=0.872300 loss=0.216344 time: 32.879942
INFO:root:[Epoch 48] train=0.926042 val=0.883900 loss=0.209040 time: 32.888589
INFO:root:[Epoch 49] train=0.927384 val=0.886700 loss=0.205392 time: 32.749082
INFO:root:[Epoch 50] train=0.929387 val=0.862900 loss=0.201086 time: 31.627547
INFO:root:[Epoch 51] train=0.930629 val=0.862700 loss=0.196939 time: 32.253585
INFO:root:[Epoch 52] train=0.930028 val=0.877300 loss=0.198456 time: 32.908283
INFO:root:[Epoch 53] train=0.931611 val=0.833600 loss=0.195453 time: 31.527841
INFO:root:[Epoch 54] train=0.932592 val=0.871300 loss=0.193874 time: 31.847062
INFO:root:[Epoch 55] train=0.930349 val=0.869000 loss=0.197894 time: 31.896202
INFO:root:[Epoch 56] train=0.934295 val=0.870100 loss=0.189740 time: 32.653816
INFO:root:[Epoch 57] train=0.933914 val=0.873700 loss=0.187968 time: 32.219094
INFO:root:[Epoch 58] train=0.933954 val=0.884900 loss=0.186613 time: 32.350560
INFO:root:[Epoch 59] train=0.936338 val=0.876500 loss=0.184609 time: 31.990384
INFO:root:[Epoch 60] train=0.933534 val=0.875400 loss=0.188717 time: 32.855722
INFO:root:[Epoch 61] train=0.935357 val=0.878500 loss=0.188058 time: 32.698772
INFO:root:[Epoch 62] train=0.936619 val=0.878800 loss=0.179588 time: 32.205093
INFO:root:[Epoch 63] train=0.935617 val=0.880300 loss=0.182499 time: 32.681036
INFO:root:[Epoch 64] train=0.937240 val=0.858600 loss=0.181751 time: 32.268791
INFO:root:[Epoch 65] train=0.939523 val=0.881500 loss=0.172594 time: 33.003408
INFO:root:[Epoch 66] train=0.937360 val=0.844000 loss=0.179040 time: 32.708847
INFO:root:[Epoch 67] train=0.937740 val=0.869200 loss=0.176561 time: 32.274816
INFO:root:[Epoch 68] train=0.937039 val=0.889100 loss=0.181178 time: 32.678000
INFO:root:[Epoch 69] train=0.939563 val=0.881700 loss=0.173500 time: 32.345824
INFO:root:[Epoch 70] train=0.937800 val=0.866300 loss=0.174615 time: 32.664232
INFO:root:[Epoch 71] train=0.940465 val=0.883500 loss=0.170157 time: 33.061449
INFO:root:[Epoch 72] train=0.937941 val=0.880300 loss=0.173055 time: 31.566819
INFO:root:[Epoch 73] train=0.940805 val=0.866100 loss=0.167662 time: 32.568924
INFO:root:[Epoch 74] train=0.940485 val=0.877700 loss=0.171848 time: 32.015345
INFO:root:[Epoch 75] train=0.939804 val=0.886400 loss=0.170458 time: 32.179393
INFO:root:[Epoch 76] train=0.940024 val=0.875400 loss=0.169322 time: 31.441660
INFO:root:[Epoch 77] train=0.941186 val=0.876300 loss=0.169376 time: 31.988210
INFO:root:[Epoch 78] train=0.942308 val=0.880400 loss=0.165072 time: 32.690485
INFO:root:[Epoch 79] train=0.940905 val=0.883500 loss=0.165726 time: 32.369246
INFO:root:[Epoch 80] train=0.940224 val=0.862700 loss=0.169798 time: 32.412013
INFO:root:[Epoch 81] train=0.942728 val=0.887600 loss=0.162879 time: 32.590652
INFO:root:[Epoch 82] train=0.942067 val=0.866000 loss=0.164661 time: 32.284556
INFO:root:[Epoch 83] train=0.943610 val=0.882100 loss=0.161544 time: 32.910198
INFO:root:[Epoch 84] train=0.941466 val=0.873600 loss=0.166038 time: 33.174373
INFO:root:[Epoch 85] train=0.946575 val=0.876500 loss=0.155280 time: 32.125926
INFO:root:[Epoch 86] train=0.939603 val=0.860600 loss=0.168207 time: 31.208343
INFO:root:[Epoch 87] train=0.943169 val=0.888500 loss=0.160980 time: 32.065650
INFO:root:[Epoch 88] train=0.943169 val=0.889000 loss=0.163555 time: 32.955881
INFO:root:[Epoch 89] train=0.943309 val=0.866800 loss=0.160299 time: 32.682374
INFO:root:[Epoch 90] train=0.944511 val=0.880500 loss=0.158949 time: 32.653645
INFO:root:[Epoch 91] train=0.943810 val=0.876700 loss=0.158991 time: 32.553670
INFO:root:[Epoch 92] train=0.944211 val=0.879700 loss=0.158808 time: 32.361472
INFO:root:[Epoch 93] train=0.943470 val=0.880500 loss=0.160639 time: 32.778503
INFO:root:[Epoch 94] train=0.947656 val=0.892900 loss=0.154688 time: 32.999547
INFO:root:[Epoch 95] train=0.946595 val=0.876300 loss=0.154086 time: 32.777185
INFO:root:[Epoch 96] train=0.943249 val=0.890200 loss=0.159115 time: 31.198849
INFO:root:[Epoch 97] train=0.943610 val=0.877400 loss=0.159067 time: 32.182120
INFO:root:[Epoch 98] train=0.944712 val=0.890000 loss=0.156722 time: 32.125893
INFO:root:[Epoch 99] train=0.946855 val=0.892300 loss=0.151922 time: 31.822612
INFO:root:[Epoch 100] train=0.973918 val=0.922700 loss=0.077477 time: 31.421952
INFO:root:[Epoch 101] train=0.983454 val=0.927400 loss=0.053021 time: 31.391716
INFO:root:[Epoch 102] train=0.987220 val=0.929300 loss=0.042408 time: 32.415544
INFO:root:[Epoch 103] train=0.989062 val=0.927100 loss=0.037380 time: 32.606220
INFO:root:[Epoch 104] train=0.990645 val=0.928600 loss=0.032130 time: 32.235691
INFO:root:[Epoch 105] train=0.990785 val=0.929600 loss=0.030586 time: 31.326386
INFO:root:[Epoch 106] train=0.992208 val=0.928900 loss=0.026841 time: 32.602701
INFO:root:[Epoch 107] train=0.993249 val=0.929600 loss=0.023685 time: 31.737779
INFO:root:[Epoch 108] train=0.994131 val=0.930400 loss=0.021789 time: 31.910848
INFO:root:[Epoch 109] train=0.994211 val=0.931100 loss=0.021145 time: 33.015263
INFO:root:[Epoch 110] train=0.994391 val=0.931100 loss=0.018937 time: 32.212139
INFO:root:[Epoch 111] train=0.994531 val=0.932100 loss=0.018517 time: 32.375969
INFO:root:[Epoch 112] train=0.994932 val=0.934400 loss=0.017750 time: 31.963041
INFO:root:[Epoch 113] train=0.995793 val=0.931700 loss=0.015464 time: 32.447387
INFO:root:[Epoch 114] train=0.996354 val=0.932600 loss=0.014523 time: 33.494761
INFO:root:[Epoch 115] train=0.995613 val=0.933600 loss=0.015059 time: 32.574024
INFO:root:[Epoch 116] train=0.995913 val=0.931700 loss=0.013996 time: 32.948493
INFO:root:[Epoch 117] train=0.996695 val=0.932700 loss=0.012881 time: 32.171842
INFO:root:[Epoch 118] train=0.996955 val=0.930200 loss=0.012174 time: 31.868229
INFO:root:[Epoch 119] train=0.996795 val=0.931400 loss=0.012181 time: 32.897807
INFO:root:[Epoch 120] train=0.997115 val=0.931600 loss=0.011399 time: 32.710808
INFO:root:[Epoch 121] train=0.997376 val=0.929900 loss=0.010730 time: 32.152796
INFO:root:[Epoch 122] train=0.997817 val=0.932900 loss=0.009709 time: 32.050721
INFO:root:[Epoch 123] train=0.997536 val=0.933100 loss=0.009919 time: 32.286308
INFO:root:[Epoch 124] train=0.997336 val=0.930100 loss=0.010368 time: 32.992347
INFO:root:[Epoch 125] train=0.997436 val=0.931300 loss=0.009886 time: 32.058355
INFO:root:[Epoch 126] train=0.997817 val=0.932100 loss=0.009403 time: 33.074770
INFO:root:[Epoch 127] train=0.997796 val=0.931700 loss=0.009264 time: 33.226131
INFO:root:[Epoch 128] train=0.997917 val=0.932000 loss=0.008688 time: 32.357618
INFO:root:[Epoch 129] train=0.998017 val=0.931600 loss=0.007975 time: 31.979264
INFO:root:[Epoch 130] train=0.998057 val=0.930900 loss=0.008098 time: 33.194427
INFO:root:[Epoch 131] train=0.998277 val=0.933100 loss=0.007792 time: 32.855739
INFO:root:[Epoch 132] train=0.998277 val=0.932200 loss=0.007282 time: 31.565401
INFO:root:[Epoch 133] train=0.998117 val=0.930200 loss=0.007794 time: 32.132741
INFO:root:[Epoch 134] train=0.998498 val=0.933000 loss=0.007050 time: 33.907496
INFO:root:[Epoch 135] train=0.998458 val=0.933400 loss=0.006839 time: 32.553856
INFO:root:[Epoch 136] train=0.998458 val=0.932900 loss=0.006622 time: 32.623568
INFO:root:[Epoch 137] train=0.998458 val=0.931800 loss=0.006755 time: 33.293433
INFO:root:[Epoch 138] train=0.998337 val=0.931100 loss=0.006716 time: 32.805102
INFO:root:[Epoch 139] train=0.998257 val=0.931400 loss=0.007012 time: 32.518596
INFO:root:[Epoch 140] train=0.998117 val=0.931200 loss=0.006887 time: 32.515462
INFO:root:[Epoch 141] train=0.998397 val=0.933100 loss=0.006369 time: 31.850560
INFO:root:[Epoch 142] train=0.998658 val=0.934100 loss=0.006291 time: 31.665857
INFO:root:[Epoch 143] train=0.998558 val=0.933100 loss=0.006098 time: 32.569248
INFO:root:[Epoch 144] train=0.998437 val=0.933100 loss=0.006268 time: 32.700911
INFO:root:[Epoch 145] train=0.998858 val=0.934500 loss=0.005613 time: 32.037600
INFO:root:[Epoch 146] train=0.998878 val=0.934800 loss=0.005267 time: 32.983193
INFO:root:[Epoch 147] train=0.998738 val=0.934100 loss=0.005545 time: 32.538044
INFO:root:[Epoch 148] train=0.998658 val=0.931400 loss=0.005735 time: 32.361547
INFO:root:[Epoch 149] train=0.998638 val=0.932600 loss=0.005778 time: 32.080424
INFO:root:[Epoch 150] train=0.999139 val=0.932700 loss=0.004731 time: 32.660386
INFO:root:[Epoch 151] train=0.999219 val=0.933200 loss=0.004351 time: 33.664744
INFO:root:[Epoch 152] train=0.999259 val=0.933700 loss=0.004213 time: 32.534119
INFO:root:[Epoch 153] train=0.999279 val=0.933900 loss=0.004075 time: 32.265520
INFO:root:[Epoch 154] train=0.999058 val=0.933300 loss=0.004786 time: 33.464022
INFO:root:[Epoch 155] train=0.999179 val=0.934600 loss=0.004287 time: 32.984411
INFO:root:[Epoch 156] train=0.999419 val=0.934100 loss=0.003857 time: 32.029706
INFO:root:[Epoch 157] train=0.999219 val=0.935200 loss=0.003965 time: 32.474448
INFO:root:[Epoch 158] train=0.999299 val=0.935600 loss=0.003827 time: 32.527579
INFO:root:[Epoch 159] train=0.999079 val=0.935500 loss=0.004357 time: 31.790687
INFO:root:[Epoch 160] train=0.999459 val=0.934400 loss=0.003524 time: 33.253503
INFO:root:[Epoch 161] train=0.999339 val=0.934200 loss=0.003947 time: 32.495379
INFO:root:[Epoch 162] train=0.999439 val=0.933900 loss=0.003993 time: 33.102496
INFO:root:[Epoch 163] train=0.999299 val=0.933800 loss=0.004090 time: 32.558762
INFO:root:[Epoch 164] train=0.999379 val=0.933800 loss=0.003745 time: 32.327708
INFO:root:[Epoch 165] train=0.999519 val=0.933600 loss=0.003449 time: 32.728722
INFO:root:[Epoch 166] train=0.999519 val=0.933400 loss=0.003479 time: 32.880463
INFO:root:[Epoch 167] train=0.999479 val=0.934900 loss=0.003472 time: 33.070556
INFO:root:[Epoch 168] train=0.999539 val=0.934300 loss=0.003380 time: 33.186257
INFO:root:[Epoch 169] train=0.999379 val=0.933100 loss=0.003799 time: 32.075141
INFO:root:[Epoch 170] train=0.999379 val=0.933500 loss=0.003655 time: 32.748909
INFO:root:[Epoch 171] train=0.999599 val=0.934100 loss=0.003523 time: 33.330852
INFO:root:[Epoch 172] train=0.999579 val=0.934400 loss=0.003303 time: 32.629223
INFO:root:[Epoch 173] train=0.999439 val=0.933900 loss=0.003582 time: 31.982929
INFO:root:[Epoch 174] train=0.999619 val=0.933500 loss=0.003220 time: 32.036347
INFO:root:[Epoch 175] train=0.999359 val=0.933400 loss=0.003440 time: 32.641184
INFO:root:[Epoch 176] train=0.999359 val=0.933700 loss=0.003609 time: 33.593500
INFO:root:[Epoch 177] train=0.999599 val=0.933800 loss=0.003237 time: 32.911582
INFO:root:[Epoch 178] train=0.999419 val=0.934500 loss=0.003615 time: 32.661821
INFO:root:[Epoch 179] train=0.999399 val=0.933700 loss=0.003502 time: 31.049920
INFO:root:[Epoch 180] train=0.999539 val=0.934000 loss=0.003329 time: 33.730081
INFO:root:[Epoch 181] train=0.999419 val=0.933500 loss=0.003490 time: 33.007860
INFO:root:[Epoch 182] train=0.999459 val=0.934300 loss=0.003388 time: 31.687878
INFO:root:[Epoch 183] train=0.999539 val=0.933500 loss=0.003166 time: 32.511551
INFO:root:[Epoch 184] train=0.999579 val=0.933100 loss=0.003039 time: 32.775425
INFO:root:[Epoch 185] train=0.999599 val=0.933700 loss=0.003118 time: 32.909173
INFO:root:[Epoch 186] train=0.999619 val=0.933100 loss=0.003081 time: 32.561030
INFO:root:[Epoch 187] train=0.999559 val=0.934300 loss=0.003154 time: 31.289505
INFO:root:[Epoch 188] train=0.999499 val=0.932800 loss=0.003370 time: 32.637353
INFO:root:[Epoch 189] train=0.999419 val=0.933900 loss=0.003217 time: 31.782455
INFO:root:[Epoch 190] train=0.999599 val=0.934600 loss=0.003049 time: 33.147494
INFO:root:[Epoch 191] train=0.999459 val=0.933400 loss=0.003346 time: 32.120601
INFO:root:[Epoch 192] train=0.999539 val=0.934100 loss=0.003236 time: 31.991334
INFO:root:[Epoch 193] train=0.999619 val=0.932500 loss=0.003209 time: 32.849539
INFO:root:[Epoch 194] train=0.999519 val=0.934500 loss=0.003144 time: 32.333937
INFO:root:[Epoch 195] train=0.999539 val=0.934500 loss=0.003058 time: 32.707788
INFO:root:[Epoch 196] train=0.999439 val=0.932900 loss=0.003280 time: 32.956554
INFO:root:[Epoch 197] train=0.999379 val=0.933700 loss=0.003231 time: 33.364544
INFO:root:[Epoch 198] train=0.999519 val=0.934300 loss=0.003066 time: 32.198502
INFO:root:[Epoch 199] train=0.999459 val=0.933200 loss=0.003234 time: 31.653752