[Numpy-discussion] numpy 1.9b1 bug in pad function?
In [1]: import numpy as np
In [2]: a = np.arange(4)
In [3]: np.pad(a,2)
---
ValueError Traceback (most recent call last)
in ()
> 1 np.pad(a,2)
/usr/lib64/python3.3/site-packages/numpy/lib/arraypad.py in pad(array,
pad_width, mode, **kwargs)
1331 elif mode is None:
1332 raise ValueError('Keyword "mode" must be a function or one of
%s.' %
-> 1333 (list(allowedkwargs.keys()),))
1334 else:
1335 # Drop back to old, slower np.apply_along_axis mode for
user-supplied
ValueError: Keyword "mode" must be a function or one of ['edge', 'constant',
'wrap', 'reflect', 'median', 'maximum', 'minimum', 'symmetric', 'linear_ramp',
'mean'].
In [4]: np.__version__
Out[4]: '1.9.0b1'
The documentation specify that the mode parameter is optional
I am getting the same for both python 2.7 and 3.3
OS: Gentoo linux
Nadav
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Re: [Numpy-discussion] Switch to using ATLAS for OSX binary wheels
On 13.06.2014 14:07, Matthew Brett wrote: > Hi, > > Summary : I'm planning to upload OSX wheels for numpy and scipy using > the ATLAS blas / lapack library instead of the default OSX Accelerate > framework. > hi, thanks for doing this. Have you built a generic atlas binary? atlas tunes it self to the capabilities of the machine its building on. So if the machine used to create be binary is newer than the oldest mac machine we want to support it can produce errors due to the use of illegal instructions (avx/sse4 etc.) So far I know the unknown machine type will produce a somewhat generic binary (but not for ARM). ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Switch to using ATLAS for OSX binary wheels
On 13 June 2014 18:00, Ralf Gommers wrote: > pip install numpy[mkl] >> ? >> > > I think that's possible. > MKL are fairly famous, but perhaps it would be legally safer to use [mkl-nonfree] (or something of the sort) to signal the licence. But maybe I am bikeshedding here. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Switch to using ATLAS for OSX binary wheels
Chris Barker wrote: > I'm curious, why not? Because an MKL license is required to redistribute MKL. If someone wants to include the binaries in their product they must acquire a license. An MKL-based binary wheel would be for end-users that wants to install and use NumPy. It would not be for those who redistribute NumPy as a component of a larger application. ATLAS and OpenBLAS are free, and Accelerate Framework is a part of Apple's operating systems. Those binaries can be redistributed by third parties without Intel's licensisng restrictions. But if you are an end-user installing NumPy for your own work you'd want the MKL binary wheel instead. Sturla ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Switch to using ATLAS for OSX binary wheels
Ralf Gommers wrote: > We have already asked and obtained that permission, under the condition > that we put some attribution to Intel MKL on our website (which we already > have at href="http://scipy.org/scipylib/donations.html";>http://scipy.org/scipylib/donations.html). > I would not be in favor > of distributing only MKL binaries, but distributing those in addition to > ATLAS/Accelerate ones would be fine. That is great news :) If we can distribute MKL and ATLAS binaries it will make everyone happy. I suppose this applies to Windows as well? Sturla ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Switch to using ATLAS for OSX binary wheels
On Fri, Jun 13, 2014 at 2:07 PM, Matthew Brett wrote: > Hi, > > Summary : I'm planning to upload OSX wheels for numpy and scipy using > the ATLAS blas / lapack library instead of the default OSX Accelerate > framework. > > We've run into some trouble with a segfault in recent OSX Accelerate: > > https://github.com/numpy/numpy/issues/4007 > > and Accelerate also doesn't play well with multiprocessing. > > https://github.com/numpy/numpy/issues/4776 > > Because there's nothing I love more than half-day compilation runs on > my laptop, I've built ATLAS binaries with gcc 4.8, and linked numpy > and scipy to them to make OSX wheels. These pass all tests in i386 > and x86_64 mode, including numpy, scipy, matplotlib, pandas: > > https://travis-ci.org/matthew-brett/scipy-stack-osx-testing/builds/27442987 > > The build process needs some automating, but it's recorded here: > > https://github.com/matthew-brett/numpy-atlas-binaries > > It's possible to get travis-ci to build these guys from a bare machine > and then upload them somewhere, but I haven't tried to do that. > > Meanwhile Sturla kindly worked up a patch to numpy to work round the > Accelerate segfault [1]. I haven't tested that, but given I'd already > built the wheels, I prefer the ATLAS builds because they work with > multiprocessing. > > I propose uploading these wheels as the default for numpy and scipy. > Does anyone have any objection or comments before I go ahead and do > that? > >From your README and wscript I don't see what numpy version you're using to compile scipy against. I got the impression that you used 1.8.1, but it should be numpy 1.5.1 for the 2.7 build, and 1.7.1 for 3.x. I've tried the scipy 0.14.0 python2.7 wheel, but I get import errors (see below). Your wheels should work with all common Python installs (mine is homebrew) right? Ralf $ python2.7 -c "import scipy; scipy.test()" Running unit tests for scipy NumPy version 1.9.0.dev-056ab73 NumPy is installed in /usr/local/Cellar/python/2.7.5/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy SciPy version 0.14.0 SciPy is installed in /usr/local/Cellar/python/2.7.5/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy Python version 2.7.5 (default, Jun 18 2013, 21:21:44) [GCC 4.2.1 Compatible Apple LLVM 4.2 (clang-425.0.28)] nose version 1.3.0 E...EEEE == ERROR: Failure: ImportError (dlopen(/usr/local/Cellar/python/2.7.5/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/cluster/_hierarchy_wrap.so, 2): Symbol not found: _PyModule_Create2 Referenced from: /usr/local/Cellar/python/2.7.5/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/cluster/_hierarchy_wrap.so Expected in: flat namespace in /usr/local/Cellar/python/2.7.5/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/cluster/_hierarchy_wrap.so) -- Traceback (most recent call last): File "/usr/local/Cellar/python/2.7.5/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/loader.py", line 413, in loadTestsFromName addr.filename, addr.module) File "/usr/local/Cellar/python/2.7.5/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/importer.py", line 47, in importFromPath return self.importFromDir(dir_path, fqname) File "/usr/local/Cellar/python/2.7.5/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/importer.py", line 94, in importFromDir mod = load_module(part_fqname, fh, filename, desc) File "/usr/local/Cellar/python/2.7.5/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/cluster/__init__.py", line 27, in from . import vq, hierarchy File "/usr/local/Cellar/python/2.7.5/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/cluster/hierarchy.py", line 175, in from . import _hierarchy_wrap ImportError: dlopen(/usr/local/Cellar/python/2.7.5/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/cluster/_hierarchy_wrap.so, 2): Symbol not found: _PyModule_Create2 Referenced from: /usr/local/Cellar/python/2.7.5/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/cluster/_hierarchy_wrap.so Expected in: flat namespace in /usr/local/Cellar/python/2.7.5/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/cluster/_hierarchy_wrap.so ... <42 more errors> ... > Cheers, > > Matthew > > [1] http://mail.scipy.org/pipermail/numpy-discussion/2014-June/070333.html > ___ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discu
Re: [Numpy-discussion] Switch to using ATLAS for OSX binary wheels
On Fri, Jun 13, 2014 at 5:53 PM, Chris Barker wrote: > On Fri, Jun 13, 2014 at 8:18 AM, Ralf Gommers > wrote: > >> We have already asked and obtained that permission, under the condition >> that we put some attribution to Intel MKL on our website (which we already >> have at http://scipy.org/scipylib/donations.html). I would not be in >> favor of distributing only MKL binaries, but distributing those in addition >> to ATLAS/Accelerate ones would be fine. >> > > I'm curious, why not? > Because I think that we should provide a set of binaries that people can reproduce without needing to buy/obtain licenses. Good for debugging, rotating release manager duties, etc. > But in any case, if the numpy project itself is distributing more than one > binary type, then we still need to decide what goes on PyPy. I'm confused > about the whole pip optional features thing, but could you put up both and > have folks access it with, for example: > > pip install numpy[mkl] > ? > I think that's possible. Ralf > > > -Chris > > > > -- > > Christopher Barker, Ph.D. > Oceanographer > > Emergency Response Division > NOAA/NOS/OR&R(206) 526-6959 voice > 7600 Sand Point Way NE (206) 526-6329 fax > Seattle, WA 98115 (206) 526-6317 main reception > > chris.bar...@noaa.gov > > ___ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Switch to using ATLAS for OSX binary wheels
On Fri, Jun 13, 2014 at 8:18 AM, Ralf Gommers wrote: > We have already asked and obtained that permission, under the condition > that we put some attribution to Intel MKL on our website (which we already > have at http://scipy.org/scipylib/donations.html). I would not be in > favor of distributing only MKL binaries, but distributing those in addition > to ATLAS/Accelerate ones would be fine. > I'm curious, why not? But in any case, if the numpy project itself is distributing more than one binary type, then we still need to decide what goes on PyPy. I'm confused about the whole pip optional features thing, but could you put up both and have folks access it with, for example: pip install numpy[mkl] ? -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R(206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception chris.bar...@noaa.gov ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Switch to using ATLAS for OSX binary wheels
On Fri, Jun 13, 2014 at 3:03 PM, Sturla Molden wrote: > > Perhaps we could ask Intel permission to use MKL in the binary wheels? We have already asked and obtained that permission, under the condition that we put some attribution to Intel MKL on our website (which we already have at http://scipy.org/scipylib/donations.html). I would not be in favor of distributing only MKL binaries, but distributing those in addition to ATLAS/Accelerate ones would be fine. Ralf ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Switch to using ATLAS for OSX binary wheels
Matthew Brett wrote: > Meanwhile Sturla kindly worked up a patch to numpy to work round the > Accelerate segfault [1]. I haven't tested that, but given I'd already > built the wheels, I prefer the ATLAS builds because they work with > multiprocessing. It is an ugly hack. If it is used it would be better to keep it in a separate branch rather than in NumPy master. I am not able to post a PR because my fork of NumPy is unavailable on GitHub. > I propose uploading these wheels as the default for numpy and scipy. > Does anyone have any objection or comments before I go ahead and do > that? ATLAS should be fine. Performance will not be anything like the alternatives (Accelerate and OpenBLAS), but correctness is more important. I am not sure why ATLAS is preferred over OpenBLAS, though, but I don't really care. Perhaps we could ask Intel permission to use MKL in the binary wheels? The Accelerate vs. multiptocessing issue will never be fixed for Python 2.7 and poissibly Python 3.3 (it is fixed in Python 3.4). The error is in multiprocessing, so Apple will not patch Accelerate. New features will not be added to Python 2.7 standard lib, so there is no chance of getting the required fix backported there either. Stalemate. Sturla ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Switch to using ATLAS for OSX binary wheels
Hi, Summary : I'm planning to upload OSX wheels for numpy and scipy using the ATLAS blas / lapack library instead of the default OSX Accelerate framework. We've run into some trouble with a segfault in recent OSX Accelerate: https://github.com/numpy/numpy/issues/4007 and Accelerate also doesn't play well with multiprocessing. https://github.com/numpy/numpy/issues/4776 Because there's nothing I love more than half-day compilation runs on my laptop, I've built ATLAS binaries with gcc 4.8, and linked numpy and scipy to them to make OSX wheels. These pass all tests in i386 and x86_64 mode, including numpy, scipy, matplotlib, pandas: https://travis-ci.org/matthew-brett/scipy-stack-osx-testing/builds/27442987 The build process needs some automating, but it's recorded here: https://github.com/matthew-brett/numpy-atlas-binaries It's possible to get travis-ci to build these guys from a bare machine and then upload them somewhere, but I haven't tried to do that. Meanwhile Sturla kindly worked up a patch to numpy to work round the Accelerate segfault [1]. I haven't tested that, but given I'd already built the wheels, I prefer the ATLAS builds because they work with multiprocessing. I propose uploading these wheels as the default for numpy and scipy. Does anyone have any objection or comments before I go ahead and do that? Cheers, Matthew [1] http://mail.scipy.org/pipermail/numpy-discussion/2014-June/070333.html ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
