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https://github.com/benchopt/benchopt

Making your benchmark of optimization algorithms simple and open
https://github.com/benchopt/benchopt

benchmark julia-language machine-learning optimization optimization-methods python rlang

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Making your benchmark of optimization algorithms simple and open

Host: GitHub
URL: https://github.com/benchopt/benchopt
Owner: benchopt
License: bsd-3-clause
Created: 2019-12-13T00:15:23.000Z (almost 5 years ago)
Default Branch: main
Last Pushed: 2024-05-29T11:55:19.000Z (6 months ago)
Last Synced: 2024-05-29T12:39:45.376Z (6 months ago)
Topics: benchmark, julia-language, machine-learning, optimization, optimization-methods, python, rlang
Language: Python
Homepage: https://benchopt.github.io
Size: 1.83 MB
Stars: 222
Watchers: 6
Forks: 52
Open Issues: 125
Metadata Files:
- Readme: README.rst
- License: LICENSE
- Roadmap: roadmap.md

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README

.. image:: https://raw.githubusercontent.com/benchopt/communication_materials/main/posters/images/logo_benchopt.png
:width: 350
:align: center

*—Making your ML and optimization benchmarks simple and open—*

----

``Benchopt`` is a benchmarking suite tailored for machine learning workflows.
It is built for simplicity, transparency, and reproducibility.
It is implemented in Python but can run algorithms written in **many programming languages**.

So far, ``benchopt`` has been tested with `Python `_,
`R `_, `Julia `_
and `C/C++ `_ (compiled binaries with a command line interface).
Programs available via `conda `_ should be compatible as well.
See for instance an `example of usage `_ with ``R``.

Install
-------

It is recommended to use ``benchopt`` within a ``conda`` environment to fully-benefit
from ``benchopt`` Command Line Interface (CLI).

To install ``benchopt``, start by creating a new ``conda`` environment and then activate it

.. code-block:: bash

conda create -n benchopt python
conda activate benchopt

Then run the following command to install the **latest release** of ``benchopt``

.. code-block:: bash

pip install -U benchopt

It is also possible to use the **latest development version**. To do so, run instead

.. code-block:: bash

pip install git+https://github.com/benchopt/benchopt.git

Getting started
---------------

After installing ``benchopt``, you can

- replicate/modify an existing benchmark
- create your own benchmark

Using an existing benchmark
^^^^^^^^^^^^^^^^^^^^^^^^^^^

Replicating an existing benchmark is simple.
Here is how to do so for the `L2-logistic Regression benchmark `_.

1. Clone the benchmark repository and ``cd`` to it

.. code-block:: bash

git clone https://github.com/benchopt/benchmark_logreg_l2
cd benchmark_logreg_l2

2. Install the desired solvers automatically with ``benchopt``

.. code-block:: bash

benchopt install . -s lightning -s sklearn

3. Run the benchmark to get the figure below

.. code-block:: bash

benchopt run . --config ./example_config.yml

.. figure:: https://benchopt.github.io/_images/sphx_glr_plot_run_benchmark_001.png
:target: how.html
:align: center
:width: 60%

These steps illustrate how to reproduce the `L2-logistic Regression benchmark `_.
Find the complete list of the `Available benchmarks`_.
Also, refer to the `documentation `_ to learn more about ``benchopt`` CLI and its features.
You can also easily extend this benchmark by adding a dataset, solver or metric.
Learn that and more in the `Benchmark workflow `_.

Creating a benchmark
^^^^^^^^^^^^^^^^^^^^

The section `Write a benchmark `_ of the documentation provides a tutorial
for creating a benchmark. The ``benchopt`` community also maintains
a `template benchmark `_ to quickly and easily start a new benchmark.

Finding help
------------

Join ``benchopt`` `discord server `_ and get in touch with the community!
Feel free to drop us a message to get help with running/constructing benchmarks
or (why not) discuss new features to be added and future development directions that ``benchopt`` should take.

Citing Benchopt
---------------

``Benchopt`` is a continuous effort to make reproducible and transparent ML and optimization benchmarks.
Join us in this endeavor! If you use ``benchopt`` in a scientific publication, please cite

.. code-block:: bibtex

@inproceedings{benchopt,
author = {Moreau, Thomas and Massias, Mathurin and Gramfort, Alexandre
and Ablin, Pierre and Bannier, Pierre-Antoine
and Charlier, Benjamin and Dagréou, Mathieu and Dupré la Tour, Tom
and Durif, Ghislain and F. Dantas, Cassio and Klopfenstein, Quentin
and Larsson, Johan and Lai, En and Lefort, Tanguy
and Malézieux, Benoit and Moufad, Badr and T. Nguyen, Binh and Rakotomamonjy,
Alain and Ramzi, Zaccharie and Salmon, Joseph and Vaiter, Samuel},
title = {Benchopt: Reproducible, efficient and collaborative optimization benchmarks},
year = {2022},
booktitle = {NeurIPS},
url = {https://arxiv.org/abs/2206.13424}
}

Available benchmarks
--------------------

.. list-table::
:widths: 70 15 15
:header-rows: 1

.. |Test Status| image:: https://github.com/benchopt/benchopt/actions/workflows/test.yml/badge.svg
:target: https://github.com/benchopt/benchopt/actions/workflows/test.yml
.. |Python 3.6+| image:: https://img.shields.io/badge/python-3.6%2B-blue
:target: https://www.python.org/downloads/release/python-360/
.. |Documentation| image:: https://img.shields.io/badge/documentation-latest-blue
:target: https://benchopt.github.io
.. |codecov| image:: https://codecov.io/gh/benchopt/benchopt/branch/main/graph/badge.svg
:target: https://codecov.io/gh/benchopt/benchopt
.. |SWH| image:: https://archive.softwareheritage.org/badge/origin/https://github.com/benchopt/benchopt/
:target: https://archive.softwareheritage.org/browse/origin/?origin_url=https://github.com/benchopt/benchopt
.. |discord| image:: https://dcbadge.vercel.app/api/server/EA2HGQb7nv?style=flat
:target: https://discord.gg/EA2HGQb7nv
.. |install-per-months| image:: https://static.pepy.tech/badge/benchopt/month
:target: https://pepy.tech/project/benchopt

.. |Build Status OLS| image:: https://github.com/benchopt/benchmark_ols/actions/workflows/main.yml/badge.svg
:target: https://github.com/benchopt/benchmark_ols/actions
.. |Build Status NNLS| image:: https://github.com/benchopt/benchmark_nnls/actions/workflows/main.yml/badge.svg
:target: https://github.com/benchopt/benchmark_nnls/actions
.. |Build Status Lasso| image:: https://github.com/benchopt/benchmark_lasso/actions/workflows/main.yml/badge.svg
:target: https://github.com/benchopt/benchmark_lasso/actions
.. |Build Status Lasso Path| image:: https://github.com/jolars/benchmark_lasso_path/actions/workflows/main.yml/badge.svg
:target: https://github.com/benchopt/benchmark_lasso_path/actions
.. |Build Status ElasticNet| image:: https://github.com/benchopt/benchmark_elastic_net/actions/workflows/main.yml/badge.svg
:target: https://github.com/benchopt/benchmark_elastic_net/actions
.. |Build Status MCP| image:: https://github.com/benchopt/benchmark_mcp/actions/workflows/main.yml/badge.svg
:target: https://github.com/benchopt/benchmark_mcp/actions
.. |Build Status LogRegL2| image:: https://github.com/benchopt/benchmark_logreg_l2/actions/workflows/main.yml/badge.svg
:target: https://github.com/benchopt/benchmark_logreg_l2/actions
.. |Build Status LogRegL1| image:: https://github.com/benchopt/benchmark_logreg_l1/actions/workflows/main.yml/badge.svg
:target: https://github.com/benchopt/benchmark_logreg_l1/actions
.. |Build Status HuberL2| image:: https://github.com/benchopt/benchmark_huber_l2/actions/workflows/main.yml/badge.svg
:target: https://github.com/benchopt/benchmark_huber_l2/actions
.. |Build Status QuantileRegL1| image:: https://github.com/benchopt/benchmark_quantile_regression/actions/workflows/main.yml/badge.svg
:target: https://github.com/benchopt/benchmark_quantile_regression/actions
.. |Build Status LinearSVM| image:: https://github.com/benchopt/benchmark_linear_svm_binary_classif_no_intercept/actions/workflows/main.yml/badge.svg
:target: https://github.com/benchopt/benchmark_linear_svm_binary_classif_no_intercept/actions
.. |Build Status LinearICA| image:: https://github.com/benchopt/benchmark_linear_ica/actions/workflows/main.yml/badge.svg
:target: https://github.com/benchopt/benchmark_linear_ica/actions
.. |Build Status JointDiag| image:: https://github.com/benchopt/benchmark_jointdiag/actions/workflows/main.yml/badge.svg
:target: https://github.com/benchopt/benchmark_jointdiag/actions
.. |Build Status TV1D| image:: https://github.com/benchopt/benchmark_tv_1d/actions/workflows/main.yml/badge.svg
:target: https://github.com/benchopt/benchmark_tv_1d/actions
.. |Build Status TV2D| image:: https://github.com/benchopt/benchmark_tv_2d/actions/workflows/main.yml/badge.svg
:target: https://github.com/benchopt/benchmark_tv_2d/actions
.. |Build Status ResNetClassif| image:: https://github.com/benchopt/benchmark_resnet_classif/actions/workflows/main.yml/badge.svg
:target: https://github.com/benchopt/benchmark_resnet_classif/actions
.. |Build Status Bilevel| image:: https://github.com/benchopt/benchmark_bilevel/actions/workflows/main.yml/badge.svg
:target: https://github.com/benchopt/benchmark_bilevel/actions