def test_low_workcount(self):
# build parallel native code ufunc
pv = Vectorize(vector_add, target='parallel')
for ty in (int32, uint32, float32, float64):
pv.add(ty(ty, ty))
para_ufunc = pv.build_ufunc()
# build python ufunc
np_ufunc = np.vectorize(vector_add)
# test it out
def test(ty):
data = np.arange(1).astype(ty) # just one item
result = para_ufunc(data, data)
gold = np_ufunc(data, data)
np.testing.assert_allclose(gold, result)
test(np.double)
test(np.float32)
test(np.int32)
test(np.uint32)
def test_low_workcount(self):
# build parallel native code ufunc
pv = Vectorize(vector_add, target='parallel')
for ty in (int32, uint32, float32, float64):
pv.add(ty(ty, ty))
para_ufunc = pv.build_ufunc()
# build python ufunc
np_ufunc = np.vectorize(vector_add)
# test it out
def test(ty):
data = np.arange(1).astype(ty) # just one item
result = para_ufunc(data, data)
gold = np_ufunc(data, data)
np.testing.assert_allclose(gold, result)
test(np.double)
test(np.float32)
test(np.int32)
test(np.uint32)
def test_low_workcount(self):
# build parallel native code ufunc
pv = Vectorize(vector_add, target='parallel')
pv.add(restype=int32, argtypes=[int32, int32])
pv.add(restype=uint32, argtypes=[uint32, uint32])
pv.add(restype=float32, argtypes=[float32, float32])
pv.add(restype=float64, argtypes=[float64, float64])
para_ufunc = pv.build_ufunc()
# build python ufunc
np_ufunc = np.vectorize(vector_add)
# test it out
def test(ty):
data = np.arange(1).astype(ty) # just one item
result = para_ufunc(data, data)
gold = np_ufunc(data, data)
self.assertTrue(np.allclose(gold, result))
test(np.double)
test(np.float32)
test(np.int32)
test(np.uint32)