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NLO

Requirements

The code is implemented in Python using PyTorch and PyTorch Geometric.

  1. Clone the repository:

    git clone https://github.com/SMACY2017/NLO.git
    cd NLO
  2. Install dependencies:

    pip install -r requirements.txt

Usage

1. Data Preparation

Raw data must be obtained from the NOEMD database due to licensing restrictions. Please refer to data/README.md for instructions.

Once the raw CSV is placed in data/, run the processing script to generate graph data and split indices:

python scripts/01_process_data.py

2. Training

The model is trained in two stages.

Stage 1:

python scripts/02_train_stage1.py

Stage 2:

python scripts/03_train_stage2.py

3. Inference

To generate prediction results using the trained models:

python scripts/04_inference.py

The results will be saved in data/inference_results/.

License

MIT License

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