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Benchopt benchmark for exact Optimal Transport

Build Status Python 3.6+

Benchopt is a package to simplify and make more transparent and reproducible the comparisons of optimization algorithms. This benchmark is dedicated to solvers of discrete exact optimal transport:

$$\min_{x \in \mathbb{R}^{n_1 \times n_2}} \langle C, x \rangle \quad \mathrm{subject , to} \quad a^\top x = 1_{n_2}, \, x b = 1_{n_1} $$

where $$C \in \mathbb{R}^{n_1 \times n_2}, a \in \mathbb{R}_+^{n_1} \ , b \in \mathbb{R}_+^{n_2}$$

Install

This benchmark can be run using the following commands:

$ pip install -U benchopt
$ git clone https://github.com/tomMoral/benchmark_ot
$ benchopt run benchmark_ot

Apart from the problem, options can be passed to benchopt run, to restrict the benchmarks to some solvers or datasets, e.g.:

$ benchopt run benchmark_ot -s solver1 -d dataset2 --max-runs 10 --n-repetitions 10

Use benchopt run -h for more details about these options, or visit https://benchopt.github.io/api.html.

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Benchmark for Optimal transport libraries

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