HO-FNO-Pipe-Flow

This package reproduces the Pipe experiment of Higher-Order Fourier Neural Operator. An eight-layer, second-order spectral operator maps two pipe-coordinate channels to horizontal velocity on a 129 x 129 grid.

Download

hf download OneScience-Group/HO-FNO-Pipe-Flow --local-dir ./HO-FNO-Pipe-Flow
cd HO-FNO-Pipe-Flow

Install PyTorch, NumPy, PyYAML and Matplotlib in a compatible GPU/DCU environment. The original 2310-sample Pipe dataset is available from the paper's official repository and as the OneScience ModelScope dataset. Download Pipe_X.npy, Pipe_Y.npy, and Pipe_Q.npy into data/; no dataset files are included in this Hugging Face model repository.

Run

python scripts/inference.py
python scripts/result.py
# To repeat the 500-epoch training run on an accelerator:
python scripts/train.py

The included weight/best_model.pth is from epoch 494. Its 200-case test mean relative L2 is 0.004887735; the paper reports 0.0049 for the Pipe setting. The weight SHA256 is 9d71053c64b62a6fc6f867108c29d2cc0d277d667a3504dc073a6b56072981d4. See results/ for the recorded metrics and plots.

Source and license

Model code in this reproduction is distributed under Apache 2.0. The underlying Pipe data has separate source terms; consult the original project before reuse.