Reparameterization through Spatial Gradient Scaling
Official implementation of "Reparameterization through Spatial Gradient Scaling".
CUDA_VISIBLE_DEVICES=0 python tools/train.py -c configs/strategies/SGS/wei_cifar.yaml --model wei_vgg11_bn --dataset cifar100 --experiment cifar100_wei_vgg11_bn_nmi5 --sgs --data-path ~/datasets/CIFAR --dist-port 29500
| Model |
Baseline |
Paper |
This Repo |
| VGG-11 |
70.8±0.1 |
73.2±0.1 |
73.4±0.1 |
| VGG-16 |
74.9±0.1 |
76.2±0.1 |
76.7±0.1 |
| ResNet-18 |
77.8±0.1 |
78.8±0.1 |
78.6±0.1 |
| Model |
Baseline (GPUs hours) |
Ours (GPUs hours) |
| VGG-11 |
0.62 |
0.65 |
| VGG-16 |
0.83 |
0.89 |
| ResNet-18 |
1.02 |
1.15 |
bash tools/dist_train.sh 8 configs/strategies/SGS/resnet.yaml resnet18 --experiment imagenet_res18_sgs --sgs --data-path ~/datasets/ImageNet --dist-port 29500
| Model |
Baseline |
Paper |
This Repo |
| ResNet-18 |
71.13±0.04 |
71.65±0.05 |
71.62 |
