Initial release of mkl-service package.
Rerelease of mkl-service package with version bumped to 2.0.0 to avoid version clash with mkl-service package from Anaconda.
Improved argument checking, which raises an informative error.
Loading the package with import mkl initializes Intel(R) MKL library to use LP64 interface (i.e. use of environment variable MKL_INTERFACE will not have effect).
The choice of threading layer can be controlled with environment variable MKL_THREADING_LAYER. However the unset variable is interpreted differently that in Intel(R) MKL itself. If mkl-service detects that Gnu OpenMP has been loaded in Python space, the threading layer of Intle(R) MKL will be set to Gnu OpenMP, instead of Intel(R) OpenMP.
Work-around for VS 9.0 not having inline keyword, allowing the package to build on Windows for Python 2.7
Re-release, with some changes necessary for public CI builds to work.
Correction to setup.py to not require Cython at the installation time.
Change in setup script to not use numpy.distutils thus removing numpy as build-time dependency.
Change in conda-recipe to allow conda build to build the recipe, but ignoring run export on mkl-service coming from mkl-devel metadata.
Closed issues #8, #7 and #5.
Extended mkl.cbwr_set to recognize 'avx512_e1', 'avx512_mic_e1', as as strict conditional numerical reproducibility, supported via 'avx2,strict', 'avx512,strict' (see [issue/8](http://github.com/IntelPython/mkl-service/issues/8)).
Extended mkl.cbwrt_get() to mean mkl.cbwr('all').
Fixed CI to actually execute tests. Populated CBWR constants to match MKL headers. Added tests checking that cbwr_set and cbwr_get round-trip.