In #108, we added a new directory ml_models to store experimental nn.Modules. This was done to support swapping a physical component, not to train or validate the wofost crop model. The models in ml_models are therefore experimental, and results from the wofost crop model using them are not validated in this package. We keep ml_models in the main branch to maintain them and include them in releases, Zenodo publications, and documentation. It also serves as a reference for researchers on how to develop and integrate their own models into the diffWOFOST ecosystem.
If ml_models grows, it could make installation heavier and harder to maintain quality (e.g., testing on GitHub runners). One option is to split it into extras, for example:
pip install diffwofost (physical models only)
pip install diffwofost[ml_models] (physical + ML models)
This isn’t urgent and can be addressed later.
In #108, we added a new directory
ml_modelsto store experimentalnn.Modules. This was done to support swapping a physical component, not to train or validate the wofost crop model. The models inml_modelsare therefore experimental, and results from the wofost crop model using them are not validated in this package. We keepml_modelsin themainbranch to maintain them and include them in releases, Zenodo publications, and documentation. It also serves as a reference for researchers on how to develop and integrate their own models into the diffWOFOST ecosystem.If
ml_modelsgrows, it could make installation heavier and harder to maintain quality (e.g., testing on GitHub runners). One option is to split it into extras, for example:This isn’t urgent and can be addressed later.