| name | nvflare-convert-lightning |
| description | Convert existing PyTorch Lightning training code into an NVFLARE federated job using the Lightning Client API patch, local validation, and job export; use only when the request names federated/NVFLARE conversion or asks multiple sites to train collaboratively while keeping each site's data local, and either names PyTorch Lightning or preliminary source inspection identifies one Lightning owner; do not use for non-federated Lightning work such as DDP, profiling, inference serving, or training-loop changes, nor for plain PyTorch, TensorFlow/Keras, other frameworks, deployment, POC/production lifecycle, or experiment workflows. |
| license | Apache-2.0 |
| metadata | {"version":"0.1.0","author":"NVIDIA FLARE Team <federatedlearning@nvidia.com>","min-flare-version":"2.9.0","blast-radius":"runs_simulator","category":"Conversion","tags":"nvflare, federated-learning, pytorch-lightning, conversion","languages":"python","frameworks":"pytorch-lightning, pytorch, nvflare","domain":"ml"} |
NVFLARE Convert PyTorch Lightning
Use When
Use only when the user asks to convert PyTorch Lightning code into an NVFLARE federated training job; require both federation intent and Lightning ownership. Treat requests for multiple sites or institutions to train collaboratively while each site's data remains local as federation intent, even when the request does not say "federated" or "NVFLARE."
Lightning source evidence alone is not sufficient. Relevant source may contain a LightningModule, LightningDataModule, a Trainer fit/validate/test loop,
Lightning callbacks, checkpointing, or loggers.
Supported: the PyTorch recipe family with as the model
exchange integration, Lightning-native evaluation, custom aggregation through
the same recipe hook, and local validation and export.
