On Mon, 08 Sep 2014, Olivier Grisel wrote: > 2014-09-08 7:46 GMT-07:00 Yaroslav Halchenko <[email protected]>:
> > It is a bit early to say about Debian servers conclusively -- I have just > > uploaded to Debian proper, so they have been rebuilt across > > architectures: > > https://buildd.debian.org/status/package.php?p=scikit-learn&suite=unstable > > and armel seems to whine a bit: > > ====================================================================== > > FAIL: sklearn.feature_extraction.tests.test_text.test_tfidf_no_smoothing > > ---------------------------------------------------------------------- > > Traceback (most recent call last): > > File "/usr/lib/python2.7/dist-packages/nose/case.py", line 197, in runTest > > self.test(*self.arg) > > File > > "/«PKGBUILDDIR»/debian/python-sklearn/usr/lib/python2.7/dist-packages/sklearn/feature_extraction/tests/test_text.py", > > line 361, in test_tfidf_no_smoothing > > tr.fit_transform, X).toarray() > > File > > "/«PKGBUILDDIR»/debian/python-sklearn/usr/lib/python2.7/dist-packages/sklearn/utils/testing.py", > > line 211, in assert_warns_message > > % func.__name__) > > AssertionError: No warning raised when calling fit_transform > > ====================================================================== > > FAIL: sklearn.metrics.tests.test_metrics.test_precision_recall_curve_toydata > > ---------------------------------------------------------------------- > > Traceback (most recent call last): > > File "/usr/lib/python2.7/dist-packages/nose/case.py", line 197, in runTest > > self.test(*self.arg) > > File > > "/«PKGBUILDDIR»/debian/python-sklearn/usr/lib/python2.7/dist-packages/sklearn/metrics/tests/test_metrics.py", > > line 1224, in test_precision_recall_curve_toydata > > assert_raises(Exception, precision_recall_curve, y_true, y_score) > > AssertionError: Exception not raised > > ---------------------------------------------------------------------- > > Ran 2753 tests in 1756.468s > Interesting. It's great to have people test scikit-learn on the ARM > platform. What is the armel architecture? how it compares to arm64 and > armhf? I would better refer to e.g. https://wiki.debian.org/ArmEabiPort https://wiki.debian.org/Arm64Port for the description besides stating that armel is conformant to older 32bit ABI so it could run on all kinds of old ARM hardware (e.g. I have some midnight gbox sitting under the TV running Debian within a chroot) > Why the does arm64 build does not work for scikit-learn? Is > there a missing dependency on that platform? hm... actually not clear since it claims that it is because of missing bdepends scikit-learn build-depends on missing: - libsvm-dev (>= 2.84.0) while that one is available :-/ I will check > Apparently those two errors on armel are caused by the fact that numpy > does not raise an error when dividing by zero on this platform. > I created an issue here: > https://github.com/scikit-learn/scikit-learn/issues/3649 > It might be a bug in numpy or a fundamental limitation on armel. In > the latter case we should update our code to take that into account. > Do you know how to detect that we are running on armel from Python? > e.g. what are the values of: > from platform import processor, machine, architecture > print(processor()) > print(machine()) > print(architecture()) I believe we did similar in pandas: + import platform + if platform.uname()[4].startswith('armv'): + raise nose.SkipTest("Fails on Debian arm boxes due to locales or whatelse") so I guess I would need to do smth like that here as well, unless you would do it upstream right away (after it gets cleared out, thanks for the investigation above -- I forgot the detail if I knew it before) -- Yaroslav O. Halchenko, Ph.D. http://neuro.debian.net http://www.pymvpa.org http://www.fail2ban.org Research Scientist, Psychological and Brain Sciences Dept. Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755 Phone: +1 (603) 646-9834 Fax: +1 (603) 646-1419 WWW: http://www.linkedin.com/in/yarik ------------------------------------------------------------------------------ Want excitement? Manually upgrade your production database. When you want reliability, choose Perforce Perforce version control. Predictably reliable. http://pubads.g.doubleclick.net/gampad/clk?id=157508191&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
