Carl Kleffner
2015-10-09 22:29:33 UTC
I made numpy master (numpy-1.11.0.dev0 ,
https://github.com/numpy/numpy/commit/0243bce23383ff5e894b99e40df2f8fd806ad79f)
windows binary wheels available for testing.
the mingwpy compiler toolchain.
OpenBLAS is deployed within the numpy wheels. To be performant on all usual
CPU architectures OpenBLAS is configured with it's 'dynamic architecture'
and automatic CPU detection.
This version of numpy fakes long double as double just like the MSVC builds.
Some test statistics:
win32 (32 bit)
numpy-1.11.0.dev0, python-2.6: errors=8, failures=1
numpy-1.11.0.dev0, python-2.7: errors=8, failures=1
numpy-1.11.0.dev0, python-3.3: errors=9
numpy-1.11.0.dev0, python-3.4: errors=9
amd64 (64bit)
numpy-1.11.0.dev0, python-2.6: errors=9, failures=6
numpy-1.11.0.dev0, python-2.7: errors=9, failures=6
numpy-1.11.0.dev0, python-3.3: errors=10, failures=6
numpy-1.11.0.dev0, python-3.4: errors=10, failures=6
Carl
https://github.com/numpy/numpy/commit/0243bce23383ff5e894b99e40df2f8fd806ad79f)
windows binary wheels available for testing.
pip install -i https://pypi.anaconda.org/carlkl/simple numpy
These builds are compiled with OPENBLAS trunk for BLAS/LAPACK support andthe mingwpy compiler toolchain.
OpenBLAS is deployed within the numpy wheels. To be performant on all usual
CPU architectures OpenBLAS is configured with it's 'dynamic architecture'
and automatic CPU detection.
This version of numpy fakes long double as double just like the MSVC builds.
Some test statistics:
win32 (32 bit)
numpy-1.11.0.dev0, python-2.6: errors=8, failures=1
numpy-1.11.0.dev0, python-2.7: errors=8, failures=1
numpy-1.11.0.dev0, python-3.3: errors=9
numpy-1.11.0.dev0, python-3.4: errors=9
amd64 (64bit)
numpy-1.11.0.dev0, python-2.6: errors=9, failures=6
numpy-1.11.0.dev0, python-2.7: errors=9, failures=6
numpy-1.11.0.dev0, python-3.3: errors=10, failures=6
numpy-1.11.0.dev0, python-3.4: errors=10, failures=6
Carl