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| frameworks: PyTorch | |
| language: | |
| - en | |
| license: apache-2.0 | |
| tags: | |
| - OneScience | |
| - Earth Science | |
| - Ocean Forecasting | |
| - Global Ocean Forecasting | |
| - GLORYS12 | |
| - FNO | |
| tasks: [] | |
| datasets: | |
| - GLORYS12 | |
| <p align="center"> | |
| <strong> | |
| <span style="font-size: 30px;">GLONET</span> | |
| </strong> | |
| </p> | |
| # Model Introduction | |
| GLONET (Global Ocean Neural Network) is a global ocean neural-network forecasting system developed by Mercator Ocean International, a leading European ocean forecasting center. | |
| # Model Description | |
| GLONET forecasts global ocean states. It takes two consecutive daily states as input and outputs the 34-channel ocean state for the next day. | |
| # Use Cases | |
| | Scenario | Description | | |
| | :---: | :--- | | |
| | Global ocean forecast research | Train a dual-branch FNO/CNN ocean forecast model with GLORYS12-compatible data. | | |
| | Local quick validation | Use synthetic ocean fields to check data loading, pretraining, fine-tuning, inference, and visualization. | | |
| | ModelScope / OneCode execution | Download the standalone model package, install dependencies, and run the scripts directly. | | |
| | Multi-GPU training | Run multi-GPU training with `torchrun`. | | |
| # Usage Guide | |
| ## 1. OneCode Usage | |
| Experience intelligent one-click AI4S programming through the OneCode online environment: | |
| [Click to Experience Intelligent One-Click AI4S Programming](https://web-2069360198568017922-iaaj.ksai.scnet.cn:58043/home) | |
| ## 2. Manual Installation and Usage | |
| **Hardware Requirements** | |
| - A GPU or DCU is recommended. | |
| - CPU can be used for import and small-scale connectivity verification; full training and inference will be slow. | |
| - DCU users must install DTK in advance. DTK 25.04.2 or above, or the OneScience recommended version matching your cluster, is recommended. | |
| ### Download the Model Package | |
| ```bash | |
| hf download OneScience-Group/GLONET --local-dir ./GLONET | |
| cd GLONET | |
| ``` | |
| ### Install the Runtime Environment | |
| **DCU Environment** | |
| ```bash | |
| # Please activate DTK and CONDA first | |
| conda create -n onescience311 python=3.11 -y | |
| conda activate onescience311 | |
| # uv installation is supported | |
| pip install onescience[earth-dcu] -i http://mirrors.onescience.ai:3141/pypi/simple/ --trusted-host mirrors.onescience.ai | |
| ``` | |
| **GPU Environment** | |
| ```bash | |
| # Please activate CONDA first | |
| conda create -n onescience311 python=3.11 -y libstdcxx-ng=12 libgcc-ng=12 gcc_linux-64=12 gxx_linux-64=12 | |
| conda activate onescience311 | |
| # uv installation is supported | |
| pip install onescience[earth-gpu] -i http://mirrors.onescience.ai:3141/pypi/simple/ --trusted-host mirrors.onescience.ai | |
| ``` | |
| ### Training Data Introduction | |
| The original work uses GLORYS12 reanalysis data. Real data must first be converted to the channel order and grid specified in `conf/config.yaml`; the raw GLORYS12 data is not included in this package. The default synthetic data is only for interface checks: | |
| ```bash | |
| python scripts/fake_data.py | |
| ``` | |
| ### Training | |
| Single GPU: | |
| ```bash | |
| python scripts/train.py | |
| ``` | |
| Multi-GPU: | |
| ```bash | |
| torchrun --nproc_per_node=8 scripts/train.py | |
| ``` | |
| Checkpoints are saved to `data/checkpoints/` by default. | |
| ### Training Weights | |
| This repository provides weights trained on GLORYS12 data in the `weight/` folder. The weight files will be uploaded soon and are expected to be available in the near future. | |
| ### Inference | |
| ```bash | |
| python scripts/inference.py | |
| ``` | |
| The prediction tensor is written to `result/glonet/data/prediction.pt` by default. | |
| ### Evaluation and Visualization | |
| ```bash | |
| python scripts/result.py | |
| ``` | |
| The default output is `result/glonet/prediction.png`. Meaningful errors are computed only when a real reference field is provided. | |
| # Official OneScience Resources | |
| | Platform | OneScience Main Repository | Skills Repository | | |
| | --- | --- | --- | | |
| | Gitee | https://gitee.com/onescience-ai/onescience | https://gitee.com/onescience-ai/oneskills | | |
| | GitHub | https://github.com/onescience-ai/OneScience | https://github.com/onescience-ai/oneskills | | |
| # Citation and License | |
| - This repository is a reproduction of the original GLONET paper. | |