| --- |
| license: apache-2.0 |
| language: |
| - en |
| tags: |
| - OneScience |
| - fluid-dynamics |
| library_name: pytorch |
| --- |
| |
| # LiNO |
|
|
| ## Model and experiment |
|
|
| This package reproduces the one-dimensional viscous Burgers final-state prediction experiment from the [paper](https://arxiv.org/abs/2606.03262). LiNO uses eight light-inspired propagation modules with width 128 and efficient scattering. Initial field and spatial coordinates on a 256-point grid are mapped to the final Burgers field. |
|
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| The package includes model code, `config/config.yaml`, training, inference and visualization scripts, the recorded `results/`, and the selected `weight/best_model.pth` checkpoint. |
|
|
| ## Data |
|
|
| Download only the needed file from [OneScience/fno](https://www.modelscope.cn/datasets/OneScience/fno) with `modelscope download OneScience/fno data/burgers_data_R10.mat --repo-type dataset --local_dir ./data`. The model reads `data/data/burgers_data_R10.mat`. |
|
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| Original dataset: https://www.modelscope.cn/datasets/OneScience/fno Download the dataset before running inference where an external dataset is required. The release configuration uses relative paths, not SCNet personal-directory paths. |
|
|
| ## Installation and usage |
|
|
| ```bash |
| hf download OneScience-Group/LiNO --local-dir ./LiNO |
| cd LiNO |
| pip install -r requirements.txt |
| python scripts/inference.py |
| python scripts/result.py |
| ``` |
|
|
| For a fresh training run, use an allocated GPU/DCU compute node with a compatible PyTorch build, keep a separate copy of the supplied checkpoint, then run `python scripts/train.py` from the package root. The full budget is specified in `config/config.yaml`. Cluster-specific Slurm scripts, if present, need adaptation outside the original cluster. |
|
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| ## Training and reported result |
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| The run completed 500 epochs with AdamW and a batch size of four. The best checkpoint was selected on 448 validation samples at epoch 495; no independent test split is claimed. |
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| Validation relative L2 was 0.00816638 versus the paper Table 1 value of 0.0109, about 25.1% lower. This is a validation result, not an independent test score. See `results/` for the recorded metrics and visualizations. The supplied checkpoint comes from a completed run; another run may differ. |
|
|
| ## Source and license |
|
|
| - Paper: https://arxiv.org/abs/2606.03262. |
| - Dataset source: https://www.modelscope.cn/datasets/OneScience/fno. |
| - This model package uses the license indicated in the card metadata. Dataset redistribution terms, where not separately stated, must not be inferred from the code license. |
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|
