def test_unary_execution(setup):
from mars.tensor.arithmetic import UNARY_UFUNC, arccosh, invert, sin, conj
_sp_unary_ufunc = {arccosh, invert, conj}
_new_unary_ufunc = list(UNARY_UFUNC - _sp_unary_ufunc)[:3]
def _normalize_by_sin(func1, func2, arr):
return func1(abs(sin((func2(arr)))))
tested = set()
rs = np.random.RandomState(0)
for func1, func2 in _gen_pairs(_new_unary_ufunc):
raw = rs.random((8, 8, 8))
arr1 = tensor(raw, chunk_size=4)
arr2 = _normalize_by_sin(func1, func2, arr1)
res = arr2.execute()
res_cmp = arr2.execute(fuse_enabled=False)
np.testing.assert_allclose(res[0], res_cmp[0])
tested.update([func1, func2])
# make sure all functions tested
assert tested == set(_new_unary_ufunc)
raw = rs.randint(100, size=(8, 8, 8))
arr1 = tensor(raw, chunk_size=4)
arr2 = arccosh(1 + abs(invert(arr1)))
res = arr2.execute(fuse_enabled=False).fetch()
res_cmp = arccosh(1 + abs(~raw))
np.testing.assert_array_almost_equal(res[0], res_cmp[0])
def testUnaryExecution(self):
from mars.tensor.arithmetic import UNARY_UFUNC, arccosh, invert, sin, conj
_sp_unary_ufunc = {arccosh, invert, conj}
_new_unary_ufunc = list(UNARY_UFUNC - _sp_unary_ufunc)
executor_numexpr = Executor()
def _normalize_by_sin(func1, func2, arr):
return func1(abs(sin((func2(arr)))))
for i, j in itertools.permutations(range(len(_new_unary_ufunc)), 2):
raw = np.random.random((8, 8, 8))
arr1 = tensor(raw, chunk_size=4)
func1 = _new_unary_ufunc[i]
func2 = _new_unary_ufunc[j]
arr2 = _normalize_by_sin(func1, func2, arr1)
res = executor_numexpr.execute_tensor(arr2, concat=True)
res_cmp = self.executor.execute_tensor(arr2, concat=True)
np.testing.assert_allclose(res[0], res_cmp[0])
raw = np.random.randint(100, size=(8, 8, 8))
arr1 = tensor(raw, chunk_size=4)
arr2 = arccosh(1 + abs(invert(arr1)))
res = executor_numexpr.execute_tensor(arr2, concat=True)
res_cmp = self.executor.execute_tensor(arr2, concat=True)
self.assertTrue(np.allclose(res[0], res_cmp[0]))
def testUnaryExecution(self):
from mars.tensor.arithmetic import UNARY_UFUNC, arccosh, invert, sin, conj
_sp_unary_ufunc = {arccosh, invert, conj}
_new_unary_ufunc = list(UNARY_UFUNC - _sp_unary_ufunc)
executor_numexpr = Executor()
def _normalize_by_sin(func1, func2, arr):
return func1(abs(sin((func2(arr)))))
tested = set()
for func1, func2 in self._gen_pairs(_new_unary_ufunc):
raw = np.random.random((8, 8, 8))
arr1 = tensor(raw, chunk_size=4)
arr2 = _normalize_by_sin(func1, func2, arr1)
res = executor_numexpr.execute_tensor(arr2, concat=True)
res_cmp = self.executor.execute_tensor(arr2, concat=True)
np.testing.assert_allclose(res[0], res_cmp[0])
tested.update([func1, func2])
# make sure all functions tested
self.assertEqual(tested, set(_new_unary_ufunc))
raw = np.random.randint(100, size=(8, 8, 8))
arr1 = tensor(raw, chunk_size=4)
arr2 = arccosh(1 + abs(invert(arr1)))
res = executor_numexpr.execute_tensor(arr2, concat=True)
res_cmp = self.executor.execute_tensor(arr2, concat=True)
self.assertTrue(np.allclose(res[0], res_cmp[0]))