If you want an absolutely bullet proof way of doing it. Build and serialize your model during docker build stage. It limits your hosting alternatives, but it is guaranteed to work.
On Tue, Aug 25, 2015, 00:19 Stefan van der Walt <stef...@berkeley.edu> wrote: > > On 2015-08-24 15:08:57, Andreas Mueller <t3k...@gmail.com> wrote: > > > Agreed—this is exactly the type of use case I want to support. > > > Pickling won't work here, but using HDF5 like MNE does would > > > probably be close to ideal (thanks to Chris Holdgraf for the > > > heads-up): > > > > I'm not sure how this solves the issue, can you elaborate? You > > still need to map the old data structure to the new code, right? > > Yes, I would need to map the old data structure to the new code. > This may be trivial for some versions (code didn't change), > slightly harder for other versions (added keywords, etc.) or > impossible (new API / implementation). But, given that the team > works hard to keep the API stable, maintaining this matrix of > conversions shouldn't be too hard. > > Stéfan > > > ------------------------------------------------------------------------------ > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >
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