[scikit-image] Numba on pypi
Ralf Gommers
ralf.gommers at gmail.com
Thu Jul 13 03:50:39 EDT 2017
On Thu, Jul 13, 2017 at 6:16 PM, Stefan van der Walt <stefanv at berkeley.edu>
wrote:
> Hi everyone,
>
> As many of you know, speed has been a point of contention in
> scikit-image for a long time. We've made a very deliberate decision to
> focus on writing high-level, understandable code (via Python and
> Cython): both to lower the barrier to entry for newcomers, and to lessen
> the burden on maintainers. But execution time comparisons, vs OpenCV
> e.g., left much to be desired.
>
> I think we have hit a turning point in the road. Binary wheels for
> Numba (actually, llvmlite) were recently uploaded to PyPi, making this
> technology available to users on both pip and conda installations. The
> importance of this release on pypi should not be dismissed, and I am
> grateful to the numba team and Continuum for making that decision.
>
Agreed. Note that there are no Windows wheels up on PyPI (yet, or not
coming?). Given that there are no SciPy wheels for Windows either I don't
think that that changes your argument much - people should just use a
binary distribution on Windows - but I thought I'd point it out anway.
>
> So, how does that impact scikit-image? Well, imagine we choose to
> optimize various procedures via numba (see Juan's blog post for exactly
> how impactful this can be:
> https://ilovesymposia.com/2017/03/15/prettier-
> lowlevelcallables-with-numba-jit-and-decorators/).
>
That's a great post. @Juan: get yourself on Planet Python!
> The only question we have to answer (from a survival point of view)
> needs to be: if, somehow, something happens to numba, will an
> alternative will be available at that time? Looking at the Python JIT
> landscape (which is very active), and the current state of numba
> development, I think this is likely. And, if we choose to use numba, of
> course we'll help to keep it healthy, as far as we can.
>
> I'd love to hear your thoughts.
I'm only an occasional user at the moment, so won't express an opinion
either way. But will be following this thread with interest.
Cheers,
Ralf
> I, for one, am excited about the
> prospect of writing kernels as simply as:
>
> >>> @jit_filter_function
> ... def fmin(values):
> ... result = np.inf
> ... for v in values:
> ... if v < result:
> ... result = v
> ... return result
>
> >>> ndi.generic_filter(image, fmin, footprint=fp)
>
> Best regards
> Stéfan
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