> I set n_jobs=-1 for both FeatureUnion and estimators/gridsearchers there
I am typically careful with this, e.g., if my machine has 16 cores, I’d set feature union to n_jobs=3 and the gridsearch_cv to n_jobs=4 or so. Curious to hear what the scikit devs think about nesting calls n_jobs=-1; am I too conservative? Best, Sebastian > On Jun 17, 2016, at 11:01 AM, Philip Tully <tu...@csc.kth.se> wrote: > > Hi all, > > I notice when I train a model and expose the predict function through a web > API, predict takes longer to run in a multi-threaded environment than a > single-threaded one. I'm guessing the root cause has something to do with > thread collisions but I must be doing something incorrectly within the code > (I set n_jobs=-1 for both FeatureUnion and estimators/gridsearchers there) > > has someone else ran into a similar issue? I can provide more details if this > Q is rather opaque still > > best, > Philip > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
