gridfm/genco-opfdata

GENCO optimal-power-flow checkpoints on OPFData (paper): IEEE 14, 30, 57, and 118, and GOC 500 and 2000, seeds 42, 3, and 17.

Evaluate on the paper branch by following GENCO §5.2. That guide uses graphkit genco-paper-repro and is how the paper numbers were produced.

Or evaluate the same checkpoints on graphkit main. main is under development, so the same numbers are not guaranteed. They matched the paper-branch result at commit f104900 (1 October 2026).

git clone https://github.com/gridfm/gridfm-graphkit.git
cd gridfm-graphkit
pip install -e .
pip install "huggingface_hub[cli]"
TORCH_CUDA_VERSION=$(python -c "import torch; print(torch.__version__ + ('+cpu' if torch.version.cuda is None else ''))")
pip install torch-scatter -f https://data.pyg.org/whl/torch-${TORCH_CUDA_VERSION}.html
export MLFLOW_ALLOW_FILE_STORE=true

mkdir -p data/case118_ieee/raw scripts/opfdata/splits
hf download gridfm/opfdata_case118_ieee --repo-type dataset --local-dir data/case118_ieee/raw
hf download gridfm/genco-opfdata --include "splits/*" --include "case118_ieee/seed42/**" --local-dir genco-opfdata
cp genco-opfdata/splits/*.pt scripts/opfdata/splits/

gridfm_graphkit evaluate \
  --config_conversion auto_inline \
  --config genco-opfdata/case118_ieee/seed42/HGNSQ_penalty_11_OPFData_case118_default.yaml \
  --data_path data \
  --model_path genco-opfdata/case118_ieee/seed42/best_model_state_dict.pt \
  --normalizer_stats genco-opfdata/case118_ieee/seed42/normalizer_stats.pt \
  --batch_size 512