<html><head></head><body text="#000000" bgcolor="#FFFFFF" lang="en-GB" style="background-color: rgb(255, 255, 255); line-height: initial;"> <div style="width: 100%; font-size: initial; font-family: Calibri, 'Slate Pro', sans-serif, sans-serif; color: rgb(31, 73, 125); text-align: initial; background-color: rgb(255, 255, 255);">Loky is the default backend in joblib master. Once joblib will be released it will be vendor in scikit-learn. So there a good hope to get it in the next release of scikit-learn and even available in master quite soon. ogrisel should be able to confirm. <span style="font-size: initial; line-height: initial; text-align: initial; font-family: Calibri, 'Slate Pro', sans-serif, sans-serif;"></span></div><div style="width: 100%; font-size: initial; font-family: Calibri, 'Slate Pro', sans-serif, sans-serif; color: rgb(31, 73, 125); text-align: initial; background-color: rgb(255, 255, 255);"><span style="font-size: initial; line-height: initial; text-align: initial; font-family: Calibri, 'Slate Pro', sans-serif, sans-serif;"><br></span></div><div style="width: 100%; font-size: initial; font-family: Calibri, 'Slate Pro', sans-serif, sans-serif; color: rgb(31, 73, 125); text-align: initial; background-color: rgb(255, 255, 255);"><span style="font-size: initial; line-height: initial; text-align: initial; font-family: Calibri, 'Slate Pro', sans-serif, sans-serif;">FWIW, a nice blog post of Tom Augspurger regarding nested parallelism done during the last joblib sprint. </span></div><div style="width: 100%; font-size: initial; font-family: Calibri, 'Slate Pro', sans-serif, sans-serif; color: rgb(31, 73, 125); text-align: initial; background-color: rgb(255, 255, 255);"><span style="font-size: initial; line-height: initial; text-align: initial; font-family: Calibri, 'Slate Pro', sans-serif, sans-serif;"><br></span></div><div style="width: 100%; font-size: initial; font-family: Calibri, 'Slate Pro', sans-serif, sans-serif; color: rgb(31, 73, 125); text-align: initial; background-color: rgb(255, 255, 255);"><span style="font-size: initial; line-height: initial; text-align: initial; font-family: Calibri, 'Slate Pro', sans-serif, sans-serif;">http://tomaugspurger.github.io/distributed-joblib.html</span></div> <div style="width: 100%; font-size: initial; font-family: Calibri, 'Slate Pro', sans-serif, sans-serif; color: rgb(31, 73, 125); text-align: initial; background-color: rgb(255, 255, 255);"><br></div> <div style="font-size: initial; font-family: Calibri, 'Slate Pro', sans-serif, sans-serif; color: rgb(31, 73, 125); text-align: initial; background-color: rgb(255, 255, 255);">Guillaume Lemaitre <br>INRIA Saclay Ile-de-France / Equipe PARIETAL<br>guillaume.lemaitre@inria.fr - https://glemaitre.github.io/</div> <table width="100%" style="background-color:white;border-spacing:0px;"> <tbody><tr><td colspan="2" style="font-size: initial; text-align: initial; background-color: rgb(255, 255, 255);"> <div style="border-style: solid none none; border-top-color: rgb(181, 196, 223); border-top-width: 1pt; padding: 3pt 0in 0in; font-family: Tahoma, 'BB Alpha Sans', 'Slate Pro'; font-size: 10pt;"> <div><b>From: </b>Beaugnon Anael</div><div><b>Sent: </b>Tuesday, 20 March 2018 17:32</div><div><b>To: </b>scikit-learn@python.org</div><div><b>Reply To: </b>Scikit-learn mailing list</div><div><b>Subject: </b>[scikit-learn] scikit-learn with celery (joblib issue)</div></div></td></tr></tbody></table><div style="border-style: solid none none; border-top-color: rgb(186, 188, 209); border-top-width: 1pt; font-size: initial; text-align: initial; background-color: rgb(255, 255, 255);"></div><br><div id="_originalContent" style="background-color: rgb(255, 255, 255);">
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<p>Dear all,</p>
<p>When I run scikit-learn (version 0.19) into celery tasks, I
cannot use scikit-learn multi-threading. The joblib library raises
the following warning : <br>
</p>
<p><font size="+1"><tt>UserWarning: Multiprocessing-backend parallel
loops cannot be nested, setting n_jobs=1</tt></font></p>
<p>I attended a presentation about the <a href="https://github.com/tomMoral/loky">Loky project</a> at
PyParis in June 2017. It was presented as a solution to this
issue.</p>
<p>Is there any plan in the near future to solve this issue directly
in scikit-learn ?<br>
</p>
Cheers,<br>
Anaël Beaugnon
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