A Lightweight Hyperparameter Optimization Tool
The mle-hyperopt package provides a simple and intuitive API for hyperparameter optimization of your Machine Learning Experiment (MLE) pipeline. It supports real, integer & categorical search variables and single- or multi-objective optimization.
Core features include the following:
- API Simplicity:
strategy.ask(),strategy.tell()interface & space definition. - Strategy Diversity: Grid, random, coordinate search, SMBO & wrapping around FAIR’s
nevergrad. - Search Space Refinement based on the top performing configs via
strategy.refine(top_k=10). - Export of configurations to execute via e.g.
python train.py --config_fname config.yaml. - Storage & reload search logs via
strategy.save(,) strategy.load(.)
For a quickstart check out the notebook blog 📖.