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<h1>Benchopt</h1>
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<h2> Contents </h2>
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<h1><code class="docutils literal notranslate"><span class="pre">Benchopt</span></code><a class="headerlink" href="#benchopt" title="Link to this heading">#</a></h1>
<p><em>—Making your ML and optimization benchmarks simple and open—</em></p>
<p><a class="reference external" href="https://www.python.org/downloads/release/python-360/"><img alt="Python 3.6+" src="https://img.shields.io/badge/python-3.6%2B-blue" /></a> <a class="reference external" href="https://pypi.org/project/benchopt/"><img alt="PyPI version" src="https://badge.fury.io/py/benchopt.svg" /></a> <a class="reference external" href="https://github.com/benchopt/benchopt/blob/main/LICENSE"><img alt="License" src="https://img.shields.io/badge/License-BSD_3--Clause-blue.svg" /></a></p>
<p>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.</p>
<p>Reproducing an existing benchmark should be as easy as running</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><style type="text/css">
span.prompt1:before {
content: "$ ";
}
</style><span class="prompt1">benchopt<span class="w"> </span>run<span class="w"> </span>.<span class="w"> </span>--config<span class="w"> </span>./example_config.yml</span>
</pre></div></div><figure class="align-center">
<a class="reference internal image-reference" href="https://benchopt.github.io/_images/sphx_glr_plot_run_benchmark_001.png"><img alt="https://benchopt.github.io/_images/sphx_glr_plot_run_benchmark_001.png" src="https://benchopt.github.io/_images/sphx_glr_plot_run_benchmark_001.png" style="width: 70%;" />
</a>
</figure>
<p>There are already many <a class="reference internal" href="available_benchmarks.html#available-benchmarks"><span class="std std-ref">Available benchmarks</span></a> that have been created using benchopt.
Learn how to run them and how to construct your own with the following pages!</p>
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<div class="sd-row sd-row-cols-2 sd-row-cols-xs-2 sd-row-cols-sm-2 sd-row-cols-md-2 sd-row-cols-lg-2 sd-g-1 sd-g-xs-1 sd-g-sm-1 sd-g-md-1 sd-g-lg-1 docutils">
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<p class="sd-card-text">Install benchopt and run your first benchmark</p>
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<section id="frequently-asked-questions-faq">
<span id="faq"></span><h2>Frequently asked questions (FAQ)<a class="headerlink" href="#frequently-asked-questions-faq" title="Link to this heading">#</a></h2>
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<span class="sd-summary-text">How to add my solver to an existing benchmark?</span><span class="sd-summary-state-marker sd-summary-chevron-right"><svg version="1.1" width="1.5em" height="1.5em" class="sd-octicon sd-octicon-chevron-right" viewBox="0 0 24 24" aria-hidden="true"><path d="M8.72 18.78a.75.75 0 0 1 0-1.06L14.44 12 8.72 6.28a.751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018l6.25 6.25a.75.75 0 0 1 0 1.06l-6.25 6.25a.75.75 0 0 1-1.06 0Z"></path></svg></span></summary><div class="sd-summary-content sd-card-body docutils">
<p class="sd-card-text">Visit the <a class="reference internal" href="tutorials/add_solver.html#add-solver"><span class="std std-ref">Add a solver to an existing benchmark</span></a> tutorial for a step-by-step procedure to add a solver to an existing benchmark.</p>
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</details><details class="sd-sphinx-override sd-dropdown sd-card sd-mb-3">
<summary class="sd-summary-title sd-card-header">
<span class="sd-summary-text">How can I write a benchmark?</span><span class="sd-summary-state-marker sd-summary-chevron-right"><svg version="1.1" width="1.5em" height="1.5em" class="sd-octicon sd-octicon-chevron-right" viewBox="0 0 24 24" aria-hidden="true"><path d="M8.72 18.78a.75.75 0 0 1 0-1.06L14.44 12 8.72 6.28a.751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018l6.25 6.25a.75.75 0 0 1 0 1.06l-6.25 6.25a.75.75 0 0 1-1.06 0Z"></path></svg></span></summary><div class="sd-summary-content sd-card-body docutils">
<p class="sd-card-text">Learn how to <a class="reference internal" href="benchmark_workflow/write_benchmark.html#write-benchmark"><span class="std std-ref">Write a benchmark</span></a>, including creating an objective, a solver, and a dataset.</p>
<p class="sd-card-text">Also take a look at our template repository for <a class="reference external" href="https://github.com/benchopt/template_benchmark">Optimization</a> and <a class="reference external" href="https://github.com/benchopt/template_benchmark_ml">ML</a> to easily start a new benchmark.</p>
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<span class="sd-summary-text">How are performance curves constructed and the solvers stopped?</span><span class="sd-summary-state-marker sd-summary-chevron-right"><svg version="1.1" width="1.5em" height="1.5em" class="sd-octicon sd-octicon-chevron-right" viewBox="0 0 24 24" aria-hidden="true"><path d="M8.72 18.78a.75.75 0 0 1 0-1.06L14.44 12 8.72 6.28a.751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018l6.25 6.25a.75.75 0 0 1 0 1.06l-6.25 6.25a.75.75 0 0 1-1.06 0Z"></path></svg></span></summary><div class="sd-summary-content sd-card-body docutils">
<p class="sd-card-text">One of benchopt’s goals is to evaluate the method’s performance with
respect to its computational budget.
Benchopt allows several strategies to vary the computational budget, that
can be set on a per solver basis.
It is also possible to set various stopping criterions to decide when to
stop growing the computational budget, to avoid wasting resources.
Visit the <a class="reference internal" href="user_guide/performance_curves.html#performance-curves"><span class="std std-ref">Performance curves</span></a> page for more details.</p>
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<span class="sd-summary-text">How can I reuse code in a benchmark?</span><span class="sd-summary-state-marker sd-summary-chevron-right"><svg version="1.1" width="1.5em" height="1.5em" class="sd-octicon sd-octicon-chevron-right" viewBox="0 0 24 24" aria-hidden="true"><path d="M8.72 18.78a.75.75 0 0 1 0-1.06L14.44 12 8.72 6.28a.751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018l6.25 6.25a.75.75 0 0 1 0 1.06l-6.25 6.25a.75.75 0 0 1-1.06 0Z"></path></svg></span></summary><div class="sd-summary-content sd-card-body docutils">
<p class="sd-card-text">For some solvers and datasets, it is handy to share some operations or pre-processing steps.
Benchopt allows to factorize this code by <a class="reference internal" href="user_guide/advanced.html#benchmark-utils-import"><span class="std std-ref">Reusing some code in a benchmark</span></a>.</p>
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<span class="sd-summary-text">Can I run a benchmark in parallel?</span><span class="sd-summary-state-marker sd-summary-chevron-right"><svg version="1.1" width="1.5em" height="1.5em" class="sd-octicon sd-octicon-chevron-right" viewBox="0 0 24 24" aria-hidden="true"><path d="M8.72 18.78a.75.75 0 0 1 0-1.06L14.44 12 8.72 6.28a.751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018l6.25 6.25a.75.75 0 0 1 0 1.06l-6.25 6.25a.75.75 0 0 1-1.06 0Z"></path></svg></span></summary><div class="sd-summary-content sd-card-body docutils">
<p class="sd-card-text">Benchopt allows to run different benchmarked methods in parallel, either with <code class="docutils literal notranslate"><span class="pre">joblib</span></code> using <code class="docutils literal notranslate"><span class="pre">-j</span> <span class="pre">4</span></code> to run on multiple CPUs of a single machine or using SLURM, as described in <a class="reference internal" href="user_guide/advanced.html#slurm-run"><span class="std std-ref">Running the benchmark on a SLURM cluster</span></a>.</p>
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</details></section>
<section id="join-the-community">
<h2>Join the community<a class="headerlink" href="#join-the-community" title="Link to this heading">#</a></h2>
<p>Join benchopt <a class="reference external" href="https://discord.gg/EA2HGQb7nv">discord server</a> and get in touch with the community!</p>
<p>Feel free to drop 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.</p>
</section>
<section id="citing-benchopt">
<h2>Citing Benchopt<a class="headerlink" href="#citing-benchopt" title="Link to this heading">#</a></h2>
<p>Benchopt is a continuous effort to make reproducible and transparent ML and optimization benchmarks.
Join this endeavor! If you use benchopt in a scientific publication, please cite</p>
<div class="highlight-bibtex notranslate"><div class="highlight"><pre><span></span><span class="nc">@inproceedings</span><span class="p">{</span><span class="nl">benchopt</span><span class="p">,</span>
<span class="w"> </span><span class="na">author</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{Moreau, Thomas and Massias, Mathurin and Gramfort, Alexandre</span>
<span class="s"> and Ablin, Pierre and Bannier, Pierre-Antoine</span>
<span class="s"> and Charlier, Benjamin and Dagréou, Mathieu and Dupré la Tour, Tom</span>
<span class="s"> and Durif, Ghislain and F. Dantas, Cassio and Klopfenstein, Quentin</span>
<span class="s"> and Larsson, Johan and Lai, En and Lefort, Tanguy</span>
<span class="s"> and Malézieux, Benoit and Moufad, Badr and T. Nguyen, Binh and Rakotomamonjy,</span>
<span class="s"> Alain and Ramzi, Zaccharie and Salmon, Joseph and Vaiter, Samuel}</span><span class="p">,</span>
<span class="w"> </span><span class="na">title</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{Benchopt: Reproducible, efficient and collaborative optimization benchmarks}</span><span class="p">,</span>
<span class="w"> </span><span class="na">year</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{2022}</span><span class="p">,</span>
<span class="w"> </span><span class="na">booktitle</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{NeurIPS}</span><span class="p">,</span>
<span class="w"> </span><span class="na">url</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{https://arxiv.org/abs/2206.13424}</span>
<span class="p">}</span>
</pre></div>
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