INFO:root:Namespace(batch_size=128, drop_rate=0.0, logging_dir='logs', lr=0.1, lr_decay=0.1, lr_decay_epoch='100,150', lr_decay_period=0, mode='hybrid', model='cifar_resnet110_v2', momentum=0.9, num_epochs=220, num_gpus=1, num_workers=2, resume_from=None, save_dir='params', save_period=10, save_plot_dir='.', wd=0.0001)
[21:49:49] 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=0.219171 val=0.449100 loss=1.901859 time: 62.120021
INFO:root:[Epoch 1] train=0.197152 val=0.566900 loss=1.634252 time: 59.344641
INFO:root:[Epoch 2] train=0.186784 val=0.660100 loss=1.497598 time: 59.812715
INFO:root:[Epoch 3] train=0.178882 val=0.696900 loss=1.461501 time: 59.553321
INFO:root:[Epoch 4] train=0.172196 val=0.739200 loss=1.366683 time: 59.726729
INFO:root:[Epoch 5] train=0.167921 val=0.731300 loss=1.344437 time: 59.403266
INFO:root:[Epoch 6] train=0.163921 val=0.764300 loss=1.297254 time: 59.866806
INFO:root:[Epoch 7] train=0.160523 val=0.782000 loss=1.301287 time: 59.839828
INFO:root:[Epoch 8] train=0.158939 val=0.781900 loss=1.292367 time: 59.845678
INFO:root:[Epoch 9] train=0.156484 val=0.806900 loss=1.277237 time: 59.423230
INFO:root:[Epoch 10] train=0.154865 val=0.801300 loss=1.278692 time: 58.779990
INFO:root:[Epoch 11] train=0.152182 val=0.813400 loss=1.241966 time: 59.610148
INFO:root:[Epoch 12] train=0.151717 val=0.794200 loss=1.246839 time: 59.708745
INFO:root:[Epoch 13] train=0.149258 val=0.817700 loss=1.208774 time: 59.803779
INFO:root:[Epoch 14] train=0.148292 val=0.840900 loss=1.211782 time: 59.767263
INFO:root:[Epoch 15] train=0.145689 val=0.830300 loss=1.195718 time: 61.749111
INFO:root:[Epoch 16] train=0.144458 val=0.807900 loss=1.193533 time: 62.593066
INFO:root:[Epoch 17] train=0.144086 val=0.815900 loss=1.202333 time: 60.140474
INFO:root:[Epoch 18] train=0.143556 val=0.761700 loss=1.171617 time: 60.265793
INFO:root:[Epoch 19] train=0.142009 val=0.859800 loss=1.161024 time: 60.383049
INFO:root:[Epoch 20] train=0.140413 val=0.856800 loss=1.151758 time: 60.181579
INFO:root:[Epoch 21] train=0.139153 val=0.855200 loss=1.146200 time: 59.829030
INFO:root:[Epoch 22] train=0.139876 val=0.837900 loss=1.165737 time: 59.350216
INFO:root:[Epoch 23] train=0.138154 val=0.846200 loss=1.157531 time: 60.299233
INFO:root:[Epoch 24] train=0.138636 val=0.846900 loss=1.168289 time: 60.324388
INFO:root:[Epoch 25] train=0.137819 val=0.850200 loss=1.157968 time: 59.780062
INFO:root:[Epoch 26] train=0.138216 val=0.841800 loss=1.161884 time: 59.949258
INFO:root:[Epoch 27] train=0.136139 val=0.838500 loss=1.137972 time: 60.078899
INFO:root:[Epoch 28] train=0.135395 val=0.867200 loss=1.127667 time: 59.715215
INFO:root:[Epoch 29] train=0.134104 val=0.846300 loss=1.117028 time: 60.001711
INFO:root:[Epoch 30] train=0.135730 val=0.842300 loss=1.145042 time: 59.895632
INFO:root:[Epoch 31] train=0.134081 val=0.834200 loss=1.129929 time: 59.625249
INFO:root:[Epoch 32] train=0.135014 val=0.859300 loss=1.123318 time: 63.154925
INFO:root:[Epoch 33] train=0.136001 val=0.835900 loss=1.155900 time: 60.059283
INFO:root:[Epoch 34] train=0.133306 val=0.873300 loss=1.124035 time: 59.508683
INFO:root:[Epoch 35] train=0.133672 val=0.862100 loss=1.113174 time: 59.681515
INFO:root:[Epoch 36] train=0.132251 val=0.861700 loss=1.112918 time: 60.185679
INFO:root:[Epoch 37] train=0.133574 val=0.839400 loss=1.116159 time: 60.457311
INFO:root:[Epoch 38] train=0.132995 val=0.879600 loss=1.124303 time: 61.124385
INFO:root:[Epoch 39] train=0.132025 val=0.853500 loss=1.104763 time: 59.872803
INFO:root:[Epoch 40] train=0.132066 val=0.879200 loss=1.115477 time: 62.128057
INFO:root:[Epoch 41] train=0.129123 val=0.866500 loss=1.085343 time: 61.948023
INFO:root:[Epoch 42] train=0.132688 val=0.863000 loss=1.138129 time: 60.253279
INFO:root:[Epoch 43] train=0.130413 val=0.891200 loss=1.095140 time: 60.160649
INFO:root:[Epoch 44] train=0.128272 val=0.879500 loss=1.059190 time: 59.293321
INFO:root:[Epoch 45] train=0.127637 val=0.874600 loss=1.054035 time: 59.745647
INFO:root:[Epoch 46] train=0.131768 val=0.883400 loss=1.134461 time: 59.828145
INFO:root:[Epoch 47] train=0.129030 val=0.879800 loss=1.083486 time: 60.442667
INFO:root:[Epoch 48] train=0.128529 val=0.883400 loss=1.085543 time: 60.957276
INFO:root:[Epoch 49] train=0.130222 val=0.872700 loss=1.114185 time: 62.847492
INFO:root:[Epoch 50] train=0.129449 val=0.875700 loss=1.082862 time: 62.889968
INFO:root:[Epoch 51] train=0.126919 val=0.879500 loss=1.059267 time: 59.852685
INFO:root:[Epoch 52] train=0.128478 val=0.886400 loss=1.095488 time: 59.981606
INFO:root:[Epoch 53] train=0.128406 val=0.855900 loss=1.087082 time: 59.516462
INFO:root:[Epoch 54] train=0.126499 val=0.876500 loss=1.059262 time: 60.104721
INFO:root:[Epoch 55] train=0.127093 val=0.891400 loss=1.080698 time: 60.363909
INFO:root:[Epoch 56] train=0.126517 val=0.866600 loss=1.054048 time: 59.640627
INFO:root:[Epoch 57] train=0.125718 val=0.880900 loss=1.043678 time: 59.802063
INFO:root:[Epoch 58] train=0.128397 val=0.883400 loss=1.116137 time: 59.928498
INFO:root:[Epoch 59] train=0.126652 val=0.886500 loss=1.066675 time: 59.908015
INFO:root:[Epoch 60] train=0.126211 val=0.890400 loss=1.064967 time: 59.726567
INFO:root:[Epoch 61] train=0.128279 val=0.875800 loss=1.090428 time: 59.913881
INFO:root:[Epoch 62] train=0.126041 val=0.855700 loss=1.069488 time: 59.479167
INFO:root:[Epoch 63] train=0.126342 val=0.874400 loss=1.081490 time: 59.920656
INFO:root:[Epoch 64] train=0.125427 val=0.888800 loss=1.078437 time: 60.115988
INFO:root:[Epoch 65] train=0.128156 val=0.859300 loss=1.109790 time: 60.488818
INFO:root:[Epoch 66] train=0.124859 val=0.827300 loss=1.057776 time: 60.404714
INFO:root:[Epoch 67] train=0.124667 val=0.866700 loss=1.052180 time: 60.130786
INFO:root:[Epoch 68] train=0.123305 val=0.861700 loss=1.028177 time: 60.442262
INFO:root:[Epoch 69] train=0.124941 val=0.862400 loss=1.055874 time: 60.013857
INFO:root:[Epoch 70] train=0.126129 val=0.883600 loss=1.099135 time: 60.140539
INFO:root:[Epoch 71] train=0.125688 val=0.881200 loss=1.078732 time: 61.887479
INFO:root:[Epoch 72] train=0.126109 val=0.884700 loss=1.091479 time: 61.032660
INFO:root:[Epoch 73] train=0.123239 val=0.828100 loss=1.023273 time: 60.384659
INFO:root:[Epoch 74] train=0.122537 val=0.879200 loss=1.026263 time: 60.877705
INFO:root:[Epoch 75] train=0.126935 val=0.884600 loss=1.097310 time: 62.914647
INFO:root:[Epoch 76] train=0.123894 val=0.841500 loss=1.065535 time: 62.744420
INFO:root:[Epoch 77] train=0.122027 val=0.880000 loss=1.030533 time: 63.060628
INFO:root:[Epoch 78] train=0.124587 val=0.870800 loss=1.047954 time: 62.957478
INFO:root:[Epoch 79] train=0.122824 val=0.881200 loss=1.039050 time: 63.228657
INFO:root:[Epoch 80] train=0.125943 val=0.892000 loss=1.088094 time: 62.516224
INFO:root:[Epoch 81] train=0.123894 val=0.898800 loss=1.049328 time: 63.488231
INFO:root:[Epoch 82] train=0.123928 val=0.886000 loss=1.052744 time: 63.407507
INFO:root:[Epoch 83] train=0.124748 val=0.888100 loss=1.062455 time: 63.407800
INFO:root:[Epoch 84] train=0.122532 val=0.867900 loss=1.038188 time: 60.670919
INFO:root:[Epoch 85] train=0.123900 val=0.888300 loss=1.050520 time: 60.608942
INFO:root:[Epoch 86] train=0.123670 val=0.891700 loss=1.041395 time: 60.242106
INFO:root:[Epoch 87] train=0.125263 val=0.893300 loss=1.077706 time: 60.168914
INFO:root:[Epoch 88] train=0.124188 val=0.875300 loss=1.070177 time: 60.025184
INFO:root:[Epoch 89] train=0.122380 val=0.891500 loss=1.043930 time: 60.203185
INFO:root:[Epoch 90] train=0.122486 val=0.879900 loss=1.034344 time: 59.886483
INFO:root:[Epoch 91] train=0.122421 val=0.895300 loss=1.057393 time: 60.082458
INFO:root:[Epoch 92] train=0.123682 val=0.838200 loss=1.064910 time: 59.703745
INFO:root:[Epoch 93] train=0.121080 val=0.891900 loss=1.031394 time: 63.236312
INFO:root:[Epoch 94] train=0.123708 val=0.885200 loss=1.056898 time: 63.595838
INFO:root:[Epoch 95] train=0.122858 val=0.876600 loss=1.051545 time: 62.034924
INFO:root:[Epoch 96] train=0.122912 val=0.859600 loss=1.057117 time: 60.254555
INFO:root:[Epoch 97] train=0.123209 val=0.870400 loss=1.064143 time: 62.173133
INFO:root:[Epoch 98] train=0.123070 val=0.872600 loss=1.053995 time: 60.168019
INFO:root:[Epoch 99] train=0.123785 val=0.889200 loss=1.077071 time: 60.321941
INFO:root:[Epoch 100] train=0.110298 val=0.928600 loss=0.972231 time: 60.343355
INFO:root:[Epoch 101] train=0.103923 val=0.936600 loss=0.941957 time: 60.166936
INFO:root:[Epoch 102] train=0.103595 val=0.932900 loss=0.933461 time: 60.679305
INFO:root:[Epoch 103] train=0.101959 val=0.940600 loss=0.933961 time: 60.805933
INFO:root:[Epoch 104] train=0.103890 val=0.936300 loss=0.945852 time: 62.943744
INFO:root:[Epoch 105] train=0.100166 val=0.940100 loss=0.911880 time: 60.145620
INFO:root:[Epoch 106] train=0.098819 val=0.942700 loss=0.900685 time: 60.313374
INFO:root:[Epoch 107] train=0.100658 val=0.938700 loss=0.937449 time: 59.805322
INFO:root:[Epoch 108] train=0.096710 val=0.941300 loss=0.884077 time: 59.824553
INFO:root:[Epoch 109] train=0.098291 val=0.941500 loss=0.908099 time: 59.710589
INFO:root:[Epoch 110] train=0.097110 val=0.938600 loss=0.892272 time: 59.722814
INFO:root:[Epoch 111] train=0.100269 val=0.940700 loss=0.936515 time: 60.669394
INFO:root:[Epoch 112] train=0.096848 val=0.939500 loss=0.897453 time: 60.245867
INFO:root:[Epoch 113] train=0.098204 val=0.939700 loss=0.914370 time: 59.592900
INFO:root:[Epoch 114] train=0.098421 val=0.942500 loss=0.922589 time: 60.163282
INFO:root:[Epoch 115] train=0.097128 val=0.941400 loss=0.913732 time: 60.184408
INFO:root:[Epoch 116] train=0.099136 val=0.940800 loss=0.925006 time: 60.436391
INFO:root:[Epoch 117] train=0.098632 val=0.939800 loss=0.919071 time: 60.208824
INFO:root:[Epoch 118] train=0.096419 val=0.941600 loss=0.896557 time: 59.800285
INFO:root:[Epoch 119] train=0.095997 val=0.940700 loss=0.903537 time: 61.699100
INFO:root:[Epoch 120] train=0.093294 val=0.945800 loss=0.873066 time: 62.934740
INFO:root:[Epoch 121] train=0.093845 val=0.943000 loss=0.887330 time: 62.216106
INFO:root:[Epoch 122] train=0.093502 val=0.939700 loss=0.883094 time: 61.754698
INFO:root:[Epoch 123] train=0.095943 val=0.942100 loss=0.901414 time: 59.692912
INFO:root:[Epoch 124] train=0.094571 val=0.939200 loss=0.893956 time: 60.128739
INFO:root:[Epoch 125] train=0.093926 val=0.944100 loss=0.892588 time: 59.867272
INFO:root:[Epoch 126] train=0.094747 val=0.945100 loss=0.904351 time: 59.989514
INFO:root:[Epoch 127] train=0.093574 val=0.940400 loss=0.891379 time: 59.994684
INFO:root:[Epoch 128] train=0.093457 val=0.941500 loss=0.882687 time: 60.494852
INFO:root:[Epoch 129] train=0.092696 val=0.942600 loss=0.869894 time: 60.503384
INFO:root:[Epoch 130] train=0.095884 val=0.944200 loss=0.911042 time: 60.253715
INFO:root:[Epoch 131] train=0.090631 val=0.943400 loss=0.862936 time: 60.235360
INFO:root:[Epoch 132] train=0.091837 val=0.945400 loss=0.871401 time: 60.360454
INFO:root:[Epoch 133] train=0.092712 val=0.940300 loss=0.879282 time: 60.418022
INFO:root:[Epoch 134] train=0.093750 val=0.942900 loss=0.900487 time: 60.188329
INFO:root:[Epoch 135] train=0.092641 val=0.941400 loss=0.878142 time: 59.778575
INFO:root:[Epoch 136] train=0.092543 val=0.942300 loss=0.874489 time: 60.144106
INFO:root:[Epoch 137] train=0.092700 val=0.940900 loss=0.886978 time: 60.373875
INFO:root:[Epoch 138] train=0.092380 val=0.943600 loss=0.888235 time: 60.502362
INFO:root:[Epoch 139] train=0.090712 val=0.942700 loss=0.862745 time: 60.185685
INFO:root:[Epoch 140] train=0.091752 val=0.942500 loss=0.881003 time: 59.709450
INFO:root:[Epoch 141] train=0.094047 val=0.942100 loss=0.907974 time: 59.952322
INFO:root:[Epoch 142] train=0.091365 val=0.943400 loss=0.876825 time: 59.910959
INFO:root:[Epoch 143] train=0.089212 val=0.944100 loss=0.858321 time: 60.141314
INFO:root:[Epoch 144] train=0.093220 val=0.940300 loss=0.890169 time: 61.247087
INFO:root:[Epoch 145] train=0.087833 val=0.940300 loss=0.847883 time: 60.051131
INFO:root:[Epoch 146] train=0.090464 val=0.942300 loss=0.870770 time: 60.459101
INFO:root:[Epoch 147] train=0.090083 val=0.943600 loss=0.867081 time: 60.330483
INFO:root:[Epoch 148] train=0.087606 val=0.944400 loss=0.830659 time: 60.364406
INFO:root:[Epoch 149] train=0.088674 val=0.941700 loss=0.853313 time: 60.216842
INFO:root:[Epoch 150] train=0.084718 val=0.944500 loss=0.826295 time: 60.958827
INFO:root:[Epoch 151] train=0.085695 val=0.947100 loss=0.842477 time: 60.994430
INFO:root:[Epoch 152] train=0.087487 val=0.946900 loss=0.854734 time: 60.511924
INFO:root:[Epoch 153] train=0.086321 val=0.947400 loss=0.853592 time: 60.358980
INFO:root:[Epoch 154] train=0.089786 val=0.945600 loss=0.889594 time: 60.152964
INFO:root:[Epoch 155] train=0.084660 val=0.946900 loss=0.843822 time: 60.334321
INFO:root:[Epoch 156] train=0.086657 val=0.947000 loss=0.851915 time: 60.464775
INFO:root:[Epoch 157] train=0.083953 val=0.947800 loss=0.831613 time: 60.345623
INFO:root:[Epoch 158] train=0.085049 val=0.947100 loss=0.846429 time: 60.723906
INFO:root:[Epoch 159] train=0.082316 val=0.949400 loss=0.817708 time: 60.758623
INFO:root:[Epoch 160] train=0.081828 val=0.947200 loss=0.818437 time: 60.255072
INFO:root:[Epoch 161] train=0.086357 val=0.947900 loss=0.851129 time: 59.792028
INFO:root:[Epoch 162] train=0.085379 val=0.947100 loss=0.850690 time: 60.081794
INFO:root:[Epoch 163] train=0.086828 val=0.949500 loss=0.857255 time: 60.225949
INFO:root:[Epoch 164] train=0.084966 val=0.948000 loss=0.843552 time: 60.119758
INFO:root:[Epoch 165] train=0.085267 val=0.946800 loss=0.851381 time: 60.090628
INFO:root:[Epoch 166] train=0.087877 val=0.948700 loss=0.876362 time: 63.567848
INFO:root:[Epoch 167] train=0.084797 val=0.947900 loss=0.844772 time: 63.672583
INFO:root:[Epoch 168] train=0.084078 val=0.949600 loss=0.836906 time: 60.422953
INFO:root:[Epoch 169] train=0.084102 val=0.947300 loss=0.834661 time: 59.938025
INFO:root:[Epoch 170] train=0.089080 val=0.943300 loss=0.888569 time: 59.616170
INFO:root:[Epoch 171] train=0.083595 val=0.949500 loss=0.835249 time: 61.266426
INFO:root:[Epoch 172] train=0.084506 val=0.947400 loss=0.843602 time: 60.079028
INFO:root:[Epoch 173] train=0.082953 val=0.948100 loss=0.834591 time: 60.232462
INFO:root:[Epoch 174] train=0.084329 val=0.949600 loss=0.840255 time: 60.109559
INFO:root:[Epoch 175] train=0.085293 val=0.949100 loss=0.855760 time: 60.293346
INFO:root:[Epoch 176] train=0.084223 val=0.948700 loss=0.846355 time: 60.559709
INFO:root:[Epoch 177] train=0.082887 val=0.947600 loss=0.826854 time: 59.998779
INFO:root:[Epoch 178] train=0.083267 val=0.948900 loss=0.829101 time: 60.164414
INFO:root:[Epoch 179] train=0.084375 val=0.947200 loss=0.843248 time: 59.924378
INFO:root:[Epoch 180] train=0.084355 val=0.948300 loss=0.843827 time: 60.035294
INFO:root:[Epoch 181] train=0.081740 val=0.949100 loss=0.822268 time: 62.685519
INFO:root:[Epoch 182] train=0.083640 val=0.949600 loss=0.837706 time: 61.973579
INFO:root:[Epoch 183] train=0.082734 val=0.950200 loss=0.830459 time: 60.285862
INFO:root:[Epoch 184] train=0.084199 val=0.947400 loss=0.849058 time: 60.506377
INFO:root:[Epoch 185] train=0.082692 val=0.950000 loss=0.832872 time: 60.227503
INFO:root:[Epoch 186] train=0.082709 val=0.948300 loss=0.827391 time: 60.299863
INFO:root:[Epoch 187] train=0.084373 val=0.948400 loss=0.843818 time: 60.371068
INFO:root:[Epoch 188] train=0.081183 val=0.949300 loss=0.813677 time: 60.327025
INFO:root:[Epoch 189] train=0.085127 val=0.949300 loss=0.852229 time: 59.957247
INFO:root:[Epoch 190] train=0.083077 val=0.949800 loss=0.831403 time: 60.049125
INFO:root:[Epoch 191] train=0.082489 val=0.948700 loss=0.820354 time: 60.365263
INFO:root:[Epoch 192] train=0.081216 val=0.949700 loss=0.816839 time: 60.150797
INFO:root:[Epoch 193] train=0.084536 val=0.949800 loss=0.848759 time: 60.799720
INFO:root:[Epoch 194] train=0.081982 val=0.950300 loss=0.818444 time: 60.337560
INFO:root:[Epoch 195] train=0.082328 val=0.947300 loss=0.829072 time: 63.204136
INFO:root:[Epoch 196] train=0.085329 val=0.948200 loss=0.854092 time: 60.337858
INFO:root:[Epoch 197] train=0.080282 val=0.948900 loss=0.813043 time: 60.548905
INFO:root:[Epoch 198] train=0.081644 val=0.949600 loss=0.827192 time: 60.493787
INFO:root:[Epoch 199] train=0.081714 val=0.949500 loss=0.818512 time: 60.251875
INFO:root:[Epoch 200] train=0.026475 val=0.951700 loss=0.030435 time: 61.298241
INFO:root:[Epoch 201] train=0.025142 val=0.952300 loss=0.024946 time: 62.018513
INFO:root:[Epoch 202] train=0.022529 val=0.953500 loss=0.021634 time: 62.010816
INFO:root:[Epoch 203] train=0.021756 val=0.951600 loss=0.019155 time: 60.702980
INFO:root:[Epoch 204] train=0.021484 val=0.952500 loss=0.018968 time: 63.313331
INFO:root:[Epoch 205] train=0.020745 val=0.952900 loss=0.017891 time: 60.070528
INFO:root:[Epoch 206] train=0.019727 val=0.953300 loss=0.016051 time: 59.841823
INFO:root:[Epoch 207] train=0.018164 val=0.954000 loss=0.014615 time: 59.687306
INFO:root:[Epoch 208] train=0.018117 val=0.955400 loss=0.014844 time: 60.262117
INFO:root:[Epoch 209] train=0.018245 val=0.953700 loss=0.014377 time: 59.963413
INFO:root:[Epoch 210] train=0.016618 val=0.955100 loss=0.012813 time: 59.680511
INFO:root:[Epoch 211] train=0.015836 val=0.954100 loss=0.012168 time: 60.448030
INFO:root:[Epoch 212] train=0.016456 val=0.953900 loss=0.012242 time: 60.204973
INFO:root:[Epoch 213] train=0.015484 val=0.954600 loss=0.011444 time: 60.637657
INFO:root:[Epoch 214] train=0.014982 val=0.954400 loss=0.010664 time: 60.469635
INFO:root:[Epoch 215] train=0.015050 val=0.952000 loss=0.010899 time: 60.286971
INFO:root:[Epoch 216] train=0.014975 val=0.953600 loss=0.011119 time: 60.723631
INFO:root:[Epoch 217] train=0.014335 val=0.953700 loss=0.010506 time: 62.090208
INFO:root:[Epoch 218] train=0.013705 val=0.953900 loss=0.009627 time: 61.422937
INFO:root:[Epoch 219] train=0.013914 val=0.953900 loss=0.009785 time: 60.279534