Skip to content

A Software Framework for HyperParameter Optimization

License

Notifications You must be signed in to change notification settings

ThomasFirmin/zellij

Repository files navigation

alt text PyPI version shields.io PyPI license Documentation Status GitHub latest commit Maintainer

Zellij is an open source Python framework for HyperParameter Optimization (HPO) which was orginally dedicated to Fractal Decomposition based algorithms [1] [2]. It includes tools to define mixed search space, manage objective functions, and a few algorithms. To implements metaheuristics and other optimization methods, Zellij uses DEAP[3] for the Evolutionary Algorithms part and BoTorch [4] for Bayesian Optimization. Zellij is defined as an easy to use and modular framework, based on Python object oriented paradigm.

See documentation.

Install Zellij

Original version

$ pip install zellij

Distributed Zellij

This version requires a MPI library, such as MPICH or Open MPI. It is based on mpi4py

$ pip install zellij[mpi]

User will then be able to use the MPI option of the Loss decorator.

@Loss(MPI=True)

Then the python script must be executed using mpiexec:

$ mpiexec -machinefile <path/to/hostfile> -n <number of processes> python3 <path/to/python/script>

Dependencies

Original version

MPI version

Contributors

Design

References

[1] Nakib, A., Ouchraa, S., Shvai, N., Souquet, L. & Talbi, E.-G. Deterministic metaheuristic based on fractal decomposition for large-scale optimization. Applied Soft Computing 61, 468–485 (2017).

[2] Demirhan, M., Özdamar, L., Helvacıoğlu, L. & Birbil, Ş. I. FRACTOP: A Geometric Partitioning Metaheuristic for Global Optimization. Journal of Global Optimization 14, 415–436 (1999).

[3] Félix-Antoine Fortin, François-Michel De Rainville, Marc-André Gardner, Marc Parizeau and Christian Gagné, "DEAP: Evolutionary Algorithms Made Easy", Journal of Machine Learning Research, vol. 13, pp. 2171-2175, jul 2012.

[4] M. Balandat, B. Karrer, D. R. Jiang, S. Daulton, B. Letham, A. G. Wilson, and E. Bakshy. BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization. Advances in Neural Information Processing Systems 33, 2020.

About

A Software Framework for HyperParameter Optimization

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages