Unofficial PyTorch implementation of Guided Dropout

This is a simple implementation of Guided Dropout for research. We try to reproduce the algorithm according to the paper published in AAA-19, but we can't guarantee the performance reported in the paper. We will list some experiment results soon.

TODO

• Release the reproduced code
• list experiment results
• ...

Setup

pip install -r requirements.txt

Run

1. Run Guided Dropout on CIFAR10 Dataset (mlp 3 hidden layers with 1024 nodes)

python mainpro.py --dataset CIFAR10 --arc mlp --mlp-depth 3 --hidden-dim 1024 -e 200 --lr 0.01 --exp-name mlp-1024-3-guided-dropout-cifar10

2. Run Original Dropout on Fashionmnist Dataset (mlp 3 hidden layers with 8192 nodes)

python mainpro.py --dataset Fashionmnist --arc mlp --mlp-depth 3 --hidden-dim 8192 -e 200 --lr 0.01 --exp-name mlp-8192-3-original-dropout-cifar10 --drop-type Dropout --drop-rate 0.2

3. Run Guided Dropout on CIFAR100 Dataset (ResNet-18)

python mainpro.py --dataset CIFAR100 --arc ResNet18 -e 200 --lr 0.01 --exp-name resnet18-guided-dropout-cifar100 --drop-type GuidedDropout --drop-rate 0.2

Result

CIFAR10

* means the result listed in the paper

CIFAR100