This code can be used to replicate results from "selective sampling for accelerating training of deep neural networks"
To clone:
git clone --recursive https://github.com/paper-submissions/mms-select
- Training the resnet44 in Cifar10:
python main.py --dataset cifar10 --model resnet --model-config "{'depth': 44, 'regime':'normal_selective'}" -b 64 --epochs 2000 --save resnet44_cifar10_select_mms --device-ids 0 -sb 640
- Training the WRN-28-10 on Cifar100:
python main.py --dataset cifar100 --model resnet --model-config "{'depth': 28, 'width': [160, 320, 640], 'regime':'resnet-wide_selective'}" -b 64 --epochs 2000 --save resnet28_wide_cifar100_select_mms --device-ids 1 --cutout --autoaugment -sb 640
- pytorch
- torchvision to load the datasets, perform image transforms
- pandas for logging to csv
- bokeh for training visualization
- Configure your dataset path with
datasets-dirargument - To get the ILSVRC data, you should register on their site for access: http://www.image-net.org/