[Numpy-discussion] how to use numpy-vendor
Tue Aug 14 05:43:44 CDT 2012
On Tue, Aug 14, 2012 at 11:22 AM, Nathaniel Smith <email@example.com> wrote:
> On Tue, Aug 14, 2012 at 11:06 AM, David Cournapeau <firstname.lastname@example.org> wrote:
>> Hi Ondrej,
>> On Tue, Aug 14, 2012 at 5:34 AM, Ondřej Čertík <email@example.com> wrote:
>>> How should one use the "vendor" repository (https://github.com/numpy/vendor)
>>> in Wine? Should I put the binaries into .wine/drive_c/Python25/libs/,
>>> or somewhere else?
>>> I've search all mailinglists and I didn't find any information on it.
>>> I vaguely remember
>>> that somebody mentioned it somewhere, but I am not able to find it.
>>> Once I understand it,
>>> I'll send a PR updating the README.
>> There is no information on vendor: that's a repo I set up to avoid
>> polluting the main repo with all the binary stuff that used to be in
>> SVN. The principle is to put binaries used to *build* numpy, but we
>> don't put anything there for end-users.
>> What binaries do you need to put there ? Numpy binaries are usually
>> put on sourceforge (although I would be more than happy to have a
>> suggestion for a better way because uploading on sourceforge is the
>> very definition of pain).
> I think he's asking how to use the binaries in numpy-vendor to build a
> release version of numpy.
Hm, good point, I don't know why I read putting .wine stuff into
vendor instead of the opposite.
Anyway, the way to use the binaries is to put them in some known
location, e.g. C:\local ($WINEPREFIX/drive_c/local for wine), and copy
the nosse/sse2/sse3 directories in there. For example:
This is then referred through env by the pavement script (see
yop to atlas would be a good idea, don't know why I let that
non-descriptive name in there.
Manually, you can just do something like "ATLAS=C:\local\lib\yop\sse2
python setup.py build", but being careful about how env variables are
passed between shell and wine (don't remember the details). Note that
the nosse is not ATLAS, but straight netlib libs, which is why in that
case you need to use BLAS=... LAPACK=...
I would strongly suggest not to use openblas for this release, because
of all the issues related to CPU tuning. We could certainly update a
bit what we have in there, but building windows binaries is big enough
of a pain, that you don't want to do everything at once I think,
especially testing/building blas on windows is very time consuming.
More information about the NumPy-Discussion