Official implementation of our paper, FlowerFormer: Empowering Neural Architecture Encoding using a Flow-aware Graph Transformer (CVPR 2024)
- Python 3.10
- Pytorch 1.13.1
- Pytorch Geometric 2.2.0
Our model implemented on with GraphGPS framework as the backbone.
Please, install GraphGPS from link
In our paper, we used 5 datasets: NAS-Bench-101, NAS-Bench-201, NAS-Bench-301, NAS-Bench-Graph, NAS-Bench-ASR.
We provided preprocessed datasets (PyG format) here.
Please place the data in ./data folder.
Run python experiments.py [config_path] with corresponding config path.