[Numpy-discussion] 64-bit windows numpy / scipy wheels for testing

Matthew Brett matthew.brett at gmail.com
Fri Apr 25 01:21:15 EDT 2014


Hi,

On Thu, Apr 24, 2014 at 5:26 PM,  <josef.pktd at gmail.com> wrote:
>
>
>
> On Thu, Apr 24, 2014 at 7:29 PM, <josef.pktd at gmail.com> wrote:
>>
>>
>>
>>
>> On Thu, Apr 24, 2014 at 7:20 PM, Charles R Harris
>> <charlesr.harris at gmail.com> wrote:
>>>
>>>
>>>
>>>
>>> On Thu, Apr 24, 2014 at 5:08 PM, <josef.pktd at gmail.com> wrote:
>>>>
>>>>
>>>>
>>>>
>>>> On Thu, Apr 24, 2014 at 7:00 PM, Charles R Harris
>>>> <charlesr.harris at gmail.com> wrote:
>>>>>
>>>>>
>>>>> Hi Matthew,
>>>>>
>>>>> On Thu, Apr 24, 2014 at 3:56 PM, Matthew Brett
>>>>> <matthew.brett at gmail.com> wrote:
>>>>>>
>>>>>> Hi,
>>>>>>
>>>>>> Thanks to Cark Kleffner's toolchain and some help from Clint Whaley
>>>>>> (main author of ATLAS), I've built 64-bit windows numpy and scipy
>>>>>> wheels for testing.
>>>>>>
>>>>>> The build uses Carl's custom mingw-w64 build with static linking.
>>>>>>
>>>>>> There are two harmless test failures on scipy (being discussed on the
>>>>>> list at the moment) - tests otherwise clean.
>>>>>>
>>>>>> Wheels are here:
>>>>>>
>>>>>>
>>>>>> https://nipy.bic.berkeley.edu/scipy_installers/numpy-1.8.1-cp27-none-win_amd64.whl
>>>>>>
>>>>>> https://nipy.bic.berkeley.edu/scipy_installers/scipy-0.13.3-cp27-none-win_amd64.whl
>>>>>>
>>>>>> You can test with:
>>>>>>
>>>>>> pip install -U pip # to upgrade pip to latest
>>>>>> pip install -f https://nipy.bic.berkeley.edu/scipy_installers numpy
>>>>>> scipy
>>>>>>
>>>>>> Please do send feedback.
>>>>>>
>>>>>> ATLAS binary here:
>>>>>>
>>>>>>
>>>>>> https://nipy.bic.berkeley.edu/scipy_installers/atlas_builds/atlas-64-full-sse2.tar.bz2
>>>>>>
>>>>>> Many thanks for Carl in particular for doing all the hard work,
>>>>>>
>>>>>
>>>>> Cool. After all these long years... Now all we need is a box running
>>>>> tests for CI.
>>>>>
>>>>> Chuck
>>>>>
>>>>> _______________________________________________
>>>>> NumPy-Discussion mailing list
>>>>> NumPy-Discussion at scipy.org
>>>>> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>>>>>
>>>>
>>>> I get two test failures with numpy
>>>>
>>>> Josef
>>>>
>>>> >>> np.test()
>>>> Running unit tests for numpy
>>>> NumPy version 1.8.1
>>>> NumPy is installed in C:\Python27\lib\site-packages\numpy
>>>> Python version 2.7.3 (default, Apr 10 2012, 23:24:47) [MSC v.1500 64 bit
>>>> (AMD64)]
>>>> nose version 1.1.2
>>>>
>>>> ======================================================================
>>>> FAIL: test_iterator.test_iter_broadcasting_errors
>>>> ----------------------------------------------------------------------
>>>> Traceback (most recent call last):
>>>>   File "C:\Python27\lib\site-packages\nose\case.py", line 197, in
>>>> runTest
>>>>     self.test(*self.arg)
>>>>   File
>>>> "C:\Python27\lib\site-packages\numpy\core\tests\test_iterator.py", line 657,
>>>> in test_iter_broadcasting_errors
>>>>     '(2)->(2,newaxis)') % msg)
>>>>   File "C:\Python27\lib\site-packages\numpy\testing\utils.py", line 44,
>>>> in assert_
>>>>     raise AssertionError(msg)
>>>> AssertionError: Message "operands could not be broadcast together with
>>>> remapped shapes [original->remapped]: (2,3)->(2,3) (2,)->(2,newaxis) and
>>>> requested shape (4,3)" doesn't contain remapped operand
>>>> shape(2)->(2,newaxis)
>>>>
>>>> ======================================================================
>>>> FAIL: test_iterator.test_iter_array_cast
>>>> ----------------------------------------------------------------------
>>>> Traceback (most recent call last):
>>>>   File "C:\Python27\lib\site-packages\nose\case.py", line 197, in
>>>> runTest
>>>>     self.test(*self.arg)
>>>>   File
>>>> "C:\Python27\lib\site-packages\numpy\core\tests\test_iterator.py", line 836,
>>>> in test_iter_array_cast
>>>>     assert_equal(i.operands[0].strides, (-96,8,-32))
>>>>   File "C:\Python27\lib\site-packages\numpy\testing\utils.py", line 255,
>>>> in assert_equal
>>>>     assert_equal(actual[k], desired[k], 'item=%r\n%s' % (k, err_msg),
>>>> verbose)
>>>>   File "C:\Python27\lib\site-packages\numpy\testing\utils.py", line 317,
>>>> in assert_equal
>>>>     raise AssertionError(msg)
>>>> AssertionError:
>>>> Items are not equal:
>>>> item=0
>>>>
>>>>  ACTUAL: 96L
>>>>  DESIRED: -96
>>>>
>>>> ----------------------------------------------------------------------
>>>> Ran 4828 tests in 46.306s
>>>>
>>>> FAILED (KNOWNFAIL=10, SKIP=8, failures=2)
>>>> <nose.result.TextTestResult run=4828 errors=0 failures=2>
>>>>
>>>
>>> Strange. That second one looks familiar, at least the "-96" part. Wonder
>>> why this doesn't show up with the MKL builds.
>>
>>
>> ok tried again, this time deleting the old numpy directories before
>> installing
>>
>> Ran 4760 tests in 42.124s
>>
>> OK (KNOWNFAIL=10, SKIP=8)
>> <nose.result.TextTestResult run=4760 errors=0 failures=0>
>>
>>
>> so pip also seems to be reusing leftover files.
>>
>> all clear.
>
>
> Running the statsmodels test suite, I get a failure in
> test_discrete.TestProbitCG where fmin_cg converges to something that differs
> in the 3rd decimal.
>
> I usually only test the 32-bit version, so I don't know if this is specific
> to this scipy version, but we haven't seen this in a long time.
> I used our nightly binaries http://statsmodels.sourceforge.net/binaries/

That's interesting, you saw also we're getting failures on the tests
for powell optimization because of small unit-at-last-place
differences in the exp function in mingw-w64.  Is there any chance you
can track down where the optimization path is diverging and why?
It's just that - if this is also the exp function maybe we can see if
the error is exceeding reasonable bounds and then feed back to
mingw-w64 and fall back to the numpy default implementation in the
meantime.

Cheers,

Matthew



More information about the NumPy-Discussion mailing list