def testBinExecution(self):
from mars.tensor.expressions.arithmetic import BIN_UFUNC, mod, fmod, \
bitand, bitor, bitxor, lshift, rshift, ldexp
_sp_bin_ufunc = [mod, fmod, bitand, bitor, bitxor, lshift, rshift]
_new_bin_ufunc = list(BIN_UFUNC - set(_sp_bin_ufunc) - set([ldexp]))
executor_numexpr = Executor()
for i, j in itertools.permutations(range(len(_new_bin_ufunc)), 2):
raw = np.random.random((9, 9, 9))
arr1 = tensor(raw, chunk_size=5)
func1 = _new_bin_ufunc[i]
func2 = _new_bin_ufunc[j]
arr2 = func1(1, func2(2, 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]))
for i, j in itertools.permutations(range(len(_sp_bin_ufunc)), 2):
raw = np.random.randint(1, 100, size=(10, 10, 10))
arr1 = tensor(raw, chunk_size=3)
func1 = _sp_bin_ufunc[i]
func2 = _sp_bin_ufunc[j]
arr2 = func1(10, func2(arr1, 5))
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.expressions.arithmetic import UNARY_UFUNC, arccosh, invert, sin, conj
_sp_unary_ufunc = set([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 testBaseExecution(self):
executor_numpy = Executor('numpy')
raw1 = np.random.randint(10, size=(10, 10, 10))
raw2 = np.random.randint(10, size=(10, 10, 10))
arr1 = tensor(raw1, chunk_size=3)
arr2 = tensor(raw2, chunk_size=3)
arr3 = arr1 + arr2 + 10
arr4 = 10 + arr1 + arr2
res3 = executor_numpy.execute_tensor(arr3, concat=True)
res3_cmp = self.executor.execute_tensor(arr4, concat=True)
self.assertTrue(np.array_equal(res3[0], res3_cmp[0]))
res5 = executor_numpy.execute_tensor((arr1 + arr1), concat=True)
res5_cmp = self.executor.execute_tensor((arr1 + arr1), concat=True)
self.assertTrue(np.array_equal(res5[0], res5_cmp[0]))
def setUp(self):
self.executor = Executor('numpy')
def setUp(self):
self.executor = Executor('numpy')
local_session = LocalSession()
local_session._executor = self.executor
self.session = Session()
self.session._sess = local_session
def setUp(self):
self.executor = Executor()
def setUp(self):
self.executor = Executor('cupy')
def setUp(self):
super(Test, self).setUp()
self.executor = Executor()
def setUp(self):
self.executor = Executor('numpy')
self.old_chunk = options.tensor.chunk_size
options.tensor.chunk_size = 10
def setUp(self):
self.executor = Executor('numpy', storage=MockStorage(), prefetch=True)