forked from enviPath/enviPy
The caching is now finished. The cache is created in `settings.py` giving us the most flexibility for using it in the future. The cache is currently updated/accessed by `tasks.py/get_ml_model` which can be called from whatever task needs to access ml models in this way (currently, `predict` and `predict_simple`). This implementation currently caches all ml models including the relative reasoning. If we don't want this and only want to cache enviFormer, i can change it to that. However, I don't think there is a harm in having the other models be cached as well. Co-authored-by: Liam Brydon <62733830+MyCreativityOutlet@users.noreply.github.com> Reviewed-on: enviPath/enviPy#156 Co-authored-by: liambrydon <lbry121@aucklanduni.ac.nz> Co-committed-by: liambrydon <lbry121@aucklanduni.ac.nz>