import cvxopt.amd
import cvxopt.base
import cvxopt.blas
import cvxopt.cholmod
import cvxopt.lapack
import cvxopt.misc_solvers
import cvxopt.umfpack
from cio_bt.mkl_link import test_modules
test_modules([
cvxopt.base,
cvxopt.blas,
cvxopt.cholmod,
cvxopt.lapack,
cvxopt.misc_solvers,
cvxopt.umfpack,
])
import sklearn.metrics.pairwise_fast
import sklearn.neighbors.ball_tree
import sklearn.neighbors.dist_metrics
import sklearn.neighbors.kd_tree
import sklearn.neighbors.quad_tree
import sklearn.neighbors.typedefs
import sklearn.svm.liblinear
import sklearn.svm.libsvm
import sklearn.svm.libsvm_sparse
import sklearn.tree._criterion
import sklearn.tree._splitter
import sklearn.tree._tree
import sklearn.tree._utils
import sklearn.utils._logistic_sigmoid
import sklearn.utils._random
import sklearn.utils.arrayfuncs
import sklearn.utils.fast_dict
import sklearn.utils.graph_shortest_path
import sklearn.utils.lgamma
import sklearn.utils.murmurhash
import sklearn.utils.seq_dataset
import sklearn.utils.sparsefuncs_fast
import sklearn.utils.weight_vector
from cio_bt.mkl_link import test_modules
test_modules([
sklearn.linear_model.cd_fast,
sklearn.svm.liblinear,
sklearn.utils.arrayfuncs,
])
import scipy.spatial._hausdorff
import scipy.spatial._voronoi
import scipy.spatial.ckdtree
import scipy.spatial.qhull
import scipy.special._comb
import scipy.special._ellip_harm_2
import scipy.special._test_round
import scipy.special._ufuncs
import scipy.special._ufuncs_cxx
import scipy.special.cython_special
import scipy.special.specfun
import scipy.stats._stats
import scipy.stats.mvn
import scipy.stats.statlib
from cio_bt.mkl_link import test_modules
test_modules([
scipy.integrate.vode,
scipy.linalg._fblas,
scipy.linalg._flapack,
scipy.sparse.linalg.eigen.arpack._arpack,
scipy.sparse.linalg.isolve._iterative,
])
import scipy.stats
import scipy.special
import sys
if sys.platform.startswith('linux'):
scipy.test('full')
print('HAS MKL: %r' % has_mkl)
mkl_version = getattr(numpy, '__mkl_version__', None)
print('MKL VERSION: %s' % mkl_version)
assert has_mkl == bool(mkl_version)
import numpy.core.multiarray
import numpy.core.multiarray_tests
import numpy.core.numeric
import numpy.core.operand_flag_tests
import numpy.core.struct_ufunc_test
import numpy.core.test_rational
import numpy.core.umath
import numpy.core.umath_tests
import numpy.fft.fftpack_lite
import numpy.linalg._umath_linalg
import numpy.linalg.lapack_lite
import numpy.random.mtrand
from cio_bt.mkl_link import test_modules
test_modules([numpy.linalg.lapack_lite])
from numpy.fft import using_mklfft
if sys.platform == 'win32' and sys.version_info[0] == 3:
print('Not running numpy tests Windows on Py3k')
else:
numpy.test()
print('USING MKLFFT: %s' % using_mklfft)
import sklearn.neighbors.ball_tree
import sklearn.neighbors.dist_metrics
import sklearn.neighbors.kd_tree
import sklearn.neighbors.typedefs
import sklearn.svm.liblinear
import sklearn.svm.libsvm
import sklearn.svm.libsvm_sparse
import sklearn.tree._criterion
import sklearn.tree._splitter
import sklearn.tree._tree
import sklearn.tree._utils
import sklearn.utils._logistic_sigmoid
import sklearn.utils._random
import sklearn.utils.arrayfuncs
import sklearn.utils.fast_dict
import sklearn.utils.graph_shortest_path
import sklearn.utils.lgamma
import sklearn.utils.murmurhash
import sklearn.utils.seq_dataset
import sklearn.utils.sparsefuncs_fast
import sklearn.utils.sparsetools._graph_tools
import sklearn.utils.sparsetools._traversal
import sklearn.utils.weight_vector
from cio_bt.mkl_link import test_modules
test_modules([
sklearn.linear_model.cd_fast,
sklearn.svm.liblinear,
sklearn.utils.arrayfuncs,
])
import os
import numpy
import numexpr
import numexpr.interpreter
from multiprocessing import freeze_support
from cio_bt.mkl_link import test_modules
test_modules([numexpr.interpreter])
has_mkl = not int(os.getenv('NOMKL', 0))
print('MKL: %r' % has_mkl)
use_vml = getattr(numexpr, 'use_vml', None)
print('numexpr.use_vml: %r' % use_vml)
assert use_vml == has_mkl == bool(getattr(numpy, '__mkl_version__', None))
if has_mkl:
vml_version = numexpr.get_vml_version()
print("VML: %r" % vml_version)
vmls = 'Intel(R) Math Kernel Library Version '
assert vml_version.startswith(vmls)
def run_tests():
numexpr.test()
if __name__ == "__main__":
freeze_support()
run_tests()
has_mkl = not int(os.getenv('NOMKL', 0))
print('HAS MKL: %r' % has_mkl)
mkl_version = getattr(numpy, '__mkl_version__', None)
print('MKL VERSION: %s' % mkl_version)
assert has_mkl == bool(mkl_version)
import numpy.core.multiarray
import numpy.core.multiarray_tests
import numpy.core.numeric
import numpy.core.operand_flag_tests
import numpy.core.struct_ufunc_test
import numpy.core.test_rational
import numpy.core.umath
import numpy.core.umath_tests
import numpy.fft.fftpack_lite
import numpy.linalg._umath_linalg
import numpy.linalg.lapack_lite
import numpy.random.mtrand
from cio_bt.mkl_link import test_modules
test_modules([numpy.linalg.lapack_lite])
from numpy.fft import using_mklfft
if sys.platform == 'win32' and sys.version_info[0] == 3:
print('Not running numpy tests Windows on Py3k')
else:
numpy.test()
print('USING MKLFFT: %s' % using_mklfft)
import scipy.linalg.cython_lapack
import scipy.sparse.linalg.eigen.arpack._arpack
import scipy.linalg._interpolative
import scipy.interpolate.interpnd
import scipy.sparse.csgraph._reordering
import scipy.sparse.linalg.dsolve._superlu
import scipy.special.specfun
import scipy.linalg._decomp_update
import scipy.linalg._flapack
import scipy.sparse._csparsetools
import scipy.spatial.qhull
import scipy.special._ufuncs
import scipy.spatial.ckdtree
import scipy.sparse._sparsetools
from cio_bt.mkl_link import test_modules
test_modules([
scipy.integrate.vode,
scipy.linalg._fblas,
scipy.linalg._flapack,
scipy.sparse.linalg.eigen.arpack._arpack,
scipy.sparse.linalg.isolve._iterative,
])
import scipy.stats
import scipy.special
import sys
if sys.platform.startswith('linux'):
scipy.test('full')
