├── README.md ├── code ├── caffe-super-convergence │ ├── L2TermComputation3.py │ ├── L2TermComputation4.py │ ├── README.md │ ├── Results │ │ ├── clr3SS5kCifar100Fig8 │ │ ├── clr3SS5kFig1a │ │ ├── clr3SS5kMom85Fig11 │ │ ├── clr3SS5kMom8Fig11 │ │ ├── clr3SS5kMom95Fig11 │ │ ├── clr3SS5kNestFig9 │ │ ├── clr3SS5kRes110Tab1 │ │ ├── clr3SS5kRes20Tab1 │ │ ├── clr3SS5kTr10kTab1 │ │ ├── clr3SS5kTr20kTab1 │ │ ├── clr3SS5kTr30kTab1 │ │ ├── clr3SS5kTr40kTab1 │ │ ├── clr3SS5kWD-3Fig11 │ │ ├── clr3SS5kWD-5Fig11 │ │ ├── clr3SS5kWD-6Fig11 │ │ ├── lr35AdaDeltaFig9 │ │ ├── lr35AdaGradFig9 │ │ ├── lr35AdamFig9 │ │ ├── lr35Cifar100Fig8 │ │ ├── lr35Fig1a │ │ ├── lr35NestFig9 │ │ ├── lr35Res110Fig6b │ │ ├── lr35Res20Fig6b │ │ ├── lr35Tr10kTab1 │ │ ├── lr35Tr20kTab1 │ │ ├── lr35Tr30kTab1 │ │ ├── lr35Tr40kTab1 │ │ ├── lrRange3SS520kClip10Fig12a │ │ ├── lrRange3SS520kClip10Fig12b │ │ ├── lrRange3SS520kClip2Fig12a │ │ ├── lrRange3SS520kClip2Fig12b │ │ ├── lrRange3SS520kClip5Fig12a │ │ ├── lrRange3SS520kClip5Fig12b │ │ ├── lrRange3SS520kDropuoutFig10a │ │ ├── range2Res110Fig4b │ │ ├── range2Res20Fig4b │ │ ├── range2SS80kRes56LR │ │ ├── range2SS80kRes56wd0 │ │ ├── range2SS80kRes56wd1 │ │ ├── range3Cifar100kFig8 │ │ ├── range3Iter100kFig2b │ │ ├── range3Iter20kFig2b │ │ └── range3Iter5kFig2b │ ├── architectures │ │ ├── ResNeXt56.prototxt │ │ ├── Resnet110Cifar.prototxt │ │ ├── Resnet20Cifar.prototxt │ │ ├── Resnet56Cifar-mod.prototxt │ │ ├── Resnet56Cifar.prototxt │ │ ├── Resnet56DM1.prototxt │ │ ├── Resnet56Dropout.prototxt │ │ ├── arch.prototxt │ │ ├── bottleneckResnet56.prototxt │ │ └── resnet56.prototxt │ ├── clrsolver.prototxt │ ├── lrRangeSolver.prototxt │ ├── solver.prototxt │ ├── train.sh │ └── x.sh ├── fastai_superconvergence │ └── Cyclical LR and momentums.ipynb ├── fastai_swa │ ├── experimental-tests-swa.ipynb │ └── functional-tests-swa.ipynb ├── img_classification_pk_pytorch │ ├── README.md │ ├── args.py │ ├── config.py │ ├── dataloader.py │ ├── getbest.py │ ├── main.py │ ├── models │ │ ├── __init__.py │ │ ├── densenet.py │ │ └── resnet.py │ ├── requirements.txt │ ├── scripts │ │ ├── cifar10.sh │ │ └── cifar100.sh │ ├── train.py │ └── utils.py ├── keras_stochastic_depth │ ├── LICENSE │ ├── README.md │ ├── cifar10.py │ └── stochastic-depth.ipynb ├── lasagne_SGDR │ ├── README.md │ └── SGDR_WRNs.py ├── pytorch_cutout │ ├── README.md │ ├── images │ │ └── cutout_on_cifar10.jpg │ ├── model │ │ ├── __init__.py │ │ ├── resnet.py │ │ └── wide_resnet.py │ ├── shake-shake │ │ ├── README.md │ │ ├── cifar10.lua │ │ ├── cifar100.lua │ │ └── transforms.lua │ ├── train.py │ └── util │ │ ├── __init__.py │ │ ├── cutout.py │ │ └── misc.py ├── pytorch_efficient_densenet │ ├── README.md │ ├── demo.py │ ├── images │ │ ├── forward.png │ │ └── memvslayers.png │ ├── models │ │ ├── __init__.py │ │ ├── densenet.py │ │ └── densenet_efficient.py │ ├── pytest.ini │ ├── setup.cfg │ └── test │ │ └── densenet_efficient_test.py ├── pytorch_mixup │ ├── README.md │ ├── easy_mixup.py │ ├── images │ │ ├── cifar10_wd1em4.png │ │ └── cifar10_wd5em4.png │ ├── models │ │ ├── __init__.py │ │ ├── densenet.py │ │ ├── dpn.py │ │ ├── googlenet.py │ │ ├── lenet.py │ │ ├── mobilenet.py │ │ ├── pnasnet.py │ │ ├── preact_resnet.py │ │ ├── resnet.py │ │ ├── resnext.py │ │ ├── senet.py │ │ ├── shufflenet.py │ │ └── vgg.py │ └── utils.py ├── pytorch_pyramidNet │ ├── PyramidNet.py │ ├── README.md │ ├── preresnet.py │ ├── resnet.py │ └── train.py ├── pytorch_random_erasing │ ├── README.md │ ├── cifar.py │ ├── fashionmnist.py │ ├── models │ │ ├── __init__.py │ │ ├── cifar │ │ │ ├── __init__.py │ │ │ ├── __init__.py~ │ │ │ ├── alexnet.py~ │ │ │ ├── preresnet.py~ │ │ │ ├── preresnetimagenet.py~ │ │ │ ├── resnet.py │ │ │ ├── wideresnet.py~ │ │ │ └── wrn.py │ │ └── fashion │ │ │ ├── __init__.py │ │ │ ├── __init__.py~ │ │ │ ├── alexnet.py~ │ │ │ ├── preresnet.py~ │ │ │ ├── preresnetimagenet.py~ │ │ │ ├── resnet.py │ │ │ ├── resnet.py~ │ │ │ ├── resnext.py~ │ │ │ ├── wideresnet.py~ │ │ │ ├── wrn.py │ │ │ └── wrn.py~ │ ├── transforms.py │ └── utils │ │ ├── __init__.py │ │ ├── eval.py │ │ ├── logger.py │ │ ├── misc.py │ │ ├── progress │ │ ├── LICENSE │ │ ├── MANIFEST.in │ │ ├── README.rst │ │ ├── demo.gif │ │ ├── progress │ │ │ ├── __init__.py │ │ │ ├── bar.py │ │ │ ├── counter.py │ │ │ ├── helpers.py │ │ │ └── spinner.py │ │ ├── setup.py │ │ └── test_progress.py │ │ ├── transforms.py │ │ └── visualize.py ├── pytorch_shake_shake │ ├── LICENSE │ ├── README.md │ ├── dataloader.py │ ├── figures │ │ ├── shake-shake-26_2x32d.png │ │ ├── shake-shake-26_2x64d.png │ │ └── shake-shake-26_2x96d.png │ ├── functions │ │ └── shake_shake_function.py │ ├── main.py │ └── shake_shake.py ├── pytorch_swa │ ├── LICENSE │ ├── README.md │ ├── logs1K.txt │ ├── models │ │ ├── __init__.py │ │ ├── preresnet.py │ │ ├── vgg.py │ │ └── wide_resnet.py │ ├── train.py │ ├── train1.py │ ├── train_swa_erasing.py │ ├── train_swa_mixup.py │ ├── train_swa_mixup_re.py │ ├── train_swa_re_mixup.py │ ├── transforms.py │ ├── utils.py │ ├── utils1.py │ └── utils_swa_mixup.py ├── pytorch_wide_residual_networks │ ├── README.md │ ├── main.py │ ├── requirements.txt │ ├── resnet.py │ └── utils.py ├── torch_PyramidNet │ ├── README.md │ ├── addpyramidnet.lua │ └── mulpyramidnet.lua ├── torch_densenet │ ├── LICENSE │ ├── README.md │ ├── checkpoints.lua │ ├── dataloader.lua │ ├── datasets │ │ ├── README.md │ │ ├── cifar10-gen.lua │ │ ├── cifar10.lua │ │ ├── cifar100-gen.lua │ │ ├── cifar100.lua │ │ ├── imagenet-gen.lua │ │ ├── imagenet.lua │ │ ├── init.lua │ │ └── transforms.lua │ ├── main.lua │ ├── models │ │ ├── DenseConnectLayer.lua │ │ ├── README.md │ │ ├── densenet.lua │ │ └── init.lua │ ├── opts.lua │ └── train.lua ├── torch_fb.resnet.torch │ ├── CONTRIBUTING.md │ ├── INSTALL.md │ ├── LICENSE │ ├── PATENTS │ ├── README.md │ ├── TRAINING.md │ ├── checkpoints.lua │ ├── dataloader.lua │ ├── datasets │ │ ├── README.md │ │ ├── cifar10-gen.lua │ │ ├── cifar10.lua │ │ ├── cifar100-gen.lua │ │ ├── cifar100.lua │ │ ├── imagenet-gen.lua │ │ ├── imagenet.lua │ │ ├── init.lua │ │ └── transforms.lua │ ├── main.lua │ ├── models │ │ ├── init.lua │ │ ├── preresnet.lua │ │ └── resnet.lua │ ├── opts.lua │ ├── pretrained │ │ ├── CONVERGENCE.md │ │ ├── README.md │ │ ├── classify.lua │ │ ├── extract-features.lua │ │ └── imagenet.lua │ └── train.lua ├── torch_resnext │ ├── CONTRIBUTING.md │ ├── LICENSE │ ├── PATENTS │ ├── README.md │ ├── checkpoints.lua │ ├── dataloader.lua │ ├── datasets │ │ ├── README.md │ │ ├── cifar10-gen.lua │ │ ├── cifar10.lua │ │ ├── cifar100-gen.lua │ │ ├── cifar100.lua │ │ ├── imagenet-gen.lua │ │ ├── imagenet.lua │ │ ├── init.lua │ │ └── transforms.lua │ ├── main.lua │ ├── models │ │ ├── init.lua │ │ └── resnext.lua │ ├── opts.lua │ └── train.lua ├── torch_shakedrop │ ├── README.md │ ├── ShakeDrop.lua │ ├── init.lua │ └── pyramidnet.lua ├── torch_shakeshake │ ├── LICENSE │ ├── README.md │ ├── checkpoints.lua │ ├── main.lua │ ├── models │ │ ├── init.lua │ │ ├── mulconstantslices.lua │ │ ├── shakeshake.lua │ │ ├── shakeshakeblock.lua │ │ └── shakeshaketable.lua │ ├── opts.lua │ └── train.lua ├── torch_stochastic_depth │ ├── README.md │ ├── ResidualDrop.lua │ ├── cifar-dataset.lua │ ├── main.lua │ └── svhn-dataset.lua └── torch_wide_residual_networks │ ├── README.md │ ├── logs │ ├── nin_1875527964 │ │ └── log.txt │ ├── resnet-pre-act_17934627 │ │ └── log.txt │ ├── vgg_24208029 │ │ └── log.txt │ └── wide-resnet_1121914561 │ │ └── log.txt │ ├── models │ ├── nin.lua │ ├── resnet-pre-act.lua │ ├── utils.lua │ ├── vgg.lua │ └── wide-resnet.lua │ ├── notebooks │ ├── sweeper.py │ └── visualize.ipynb │ ├── pretrained │ ├── README.md │ └── wide-resnet.lua │ ├── scripts │ ├── train_cifar.sh │ └── train_svhn.sh │ └── train.lua └── images ├── ban_cifar10.png ├── born_again.png ├── clr.png ├── cutout.png ├── densenet.png ├── erase_relu.png ├── mixup_cifar.png ├── preact_resnet.png ├── pyramid.png ├── pyramid_drop.png ├── 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