def test_no_blas_crash_or_freeze_with_multiprocessing():
if sys.version_info < (3, 4):
raise nose.SkipTest('multiprocessing can cause BLAS freeze on'
' old Python')
# Check that on recent Python version, the forkserver start method can make
# it possible to use multiprocessing in conjunction of any BLAS
# implementation that happens to be used by numpy with causing a freeze or
# a crash
rng = np.random.RandomState(42)
# call BLAS DGEMM to force the initialization of the internal thread-pool
# in the main process
a = rng.randn(1000, 1000)
np.dot(a, a.T)
# check that the internal BLAS thread-pool is not in an inconsistent state
# in the worker processes managed by multiprocessing
Parallel(n_jobs=2, backend='multiprocessing')(delayed(np.dot)(a, a.T)
for i in range(2))
def test_no_blas_crash_or_freeze_with_multiprocessing():
if sys.version_info < (3, 4):
raise nose.SkipTest('multiprocessing can cause BLAS freeze on'
' old Python')
# Check that on recent Python version, the forkserver start method can make
# it possible to use multiprocessing in conjunction of any BLAS
# implementation that happens to be used by numpy with causing a freeze or
# a crash
rng = np.random.RandomState(42)
# call BLAS DGEMM to force the initialization of the internal thread-pool
# in the main process
a = rng.randn(1000, 1000)
np.dot(a, a.T)
# check that the internal BLAS thread-pool is not in an inconsistent state
# in the worker processes managed by multiprocessing
Parallel(n_jobs=2, backend='multiprocessing')(
delayed(np.dot)(a, a.T) for i in range(2))
def test_no_blas_crash_or_freeze_with_subprocesses(backend):
if backend == 'multiprocessing':
if sys.version_info < (3, 4):
raise SkipTest('multiprocessing can cause BLAS freeze on old '
'Python that relies on fork.')
# Use the spawn backend that is both robust and available on all
# platforms
backend = mp.get_context('spawn')
# Check that on recent Python version, the 'spawn' start method can make
# it possible to use multiprocessing in conjunction of any BLAS
# implementation that happens to be used by numpy with causing a freeze or
# a crash
rng = np.random.RandomState(42)
# call BLAS DGEMM to force the initialization of the internal thread-pool
# in the main process
a = rng.randn(1000, 1000)
np.dot(a, a.T)
# check that the internal BLAS thread-pool is not in an inconsistent state
# in the worker processes managed by multiprocessing
Parallel(n_jobs=2,
backend=backend)(delayed(np.dot)(a, a.T) for i in range(2))
