Not the same, although there are similarities. However asv provides
tools to compare benchmarks across commits, and to publish them in html
format to follow their evolution through time such as
https://pv.github.io/numpy-bench/
Here's the link of the benchmark suite :
https://github.com/jeremiedbb/scikit-learn_benchmarks
On 26/02/2019 11:48, Andreas Mueller wrote:
Was that the same that Vlad used?
https://github.com/scikit-learn/scikit-learn-speed
We might want to just replace that, given that it hasn't been touched
in 7 years?
On 2/26/19 5:22 AM, Jeremie du Boisberranger wrote:
I totally forgot to mention it before the sprint started but i'd like
to have a discussion about the integration of a new benchmark suite
into the scikit-learn organization.
Essentially, I've been working on a benchmark suite for sklearn using
the airspeed velocity (asv) framework. The purpose of asv is to
benchmark a repo across commits. It can be used for instance to
detect regressions, performance wise and memory wise.
If you want to discuss it, let me know. I'm here the whole week.
Jérémie
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