gnnrl 1.0.6

gnnrl pipeline

GNN-RL-Model-Compression

GNN-RL Compression: Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning

Dependencies

Current code base is tested under following environment:

1. Python 3.8
2. PyTorch 1.8.0 (cuda 11.1)
3. torchvision 0.7.0
4. torch-geometric 1.6.1

Results on ImageNet

Models	FLOPs ratio	Top1 Acc. (%)	Acc.	Dataset
MobileNet-v1	40% FLOPs	69.50	-1.40	ImageNet
MobileNet-v1	70% FLOPs	70.70	-0.20	ImageNet
MobileNet-v2	58% FLOPs	70.04	-1.83	ImageNet
VGG-16	20% FLOPs	70.992	+0.49	ImageNet
ResNet-50	47% FLOPs	74.28	-1.82	ImageNet
ResNet-18	50% FLOPs	68.66	-1.10	ImageNet