This is the code for DiffTSP. The denoising model architecture in graph_dit/models
All dependencies are specified in the requirements.txt file.
This code was developed and tested with Python 3.9, PyTorch 2.0.0, and PyG 2.3.0, Pytorch-lightning 2.0.1.
We could train the model on one 4090 GPU. Here is an example to running the code:
CUDA_VISIBLE_DEVICES=0 python main.py --config-name=config.yaml general.gpus=1 model.diffusion_steps=20
All default configurations can be found in configs/config.yaml.
If you find this repository useful, please cite our paper