def test_pickle(self):
x = dmatrix("x")
y = dmatrix("y")
m = mul(x, y)
s = pickle.dumps(m)
m2 = pickle.loads(s)
assert m2.owner.op == m.owner.op
def test_1arg(self):
x = dmatrix("x")
@as_op(dmatrix, dvector)
def cumprod(x):
return np.cumprod(x)
fn = function([x], cumprod(x))
r = fn([[1.5, 5], [2, 2]])
r0 = np.array([1.5, 7.5, 15.0, 30.0])
assert np.allclose(r, r0), (r, r0)
def test_2arg(self):
x = dmatrix("x")
x.tag.test_value = np.zeros((2, 2))
y = dvector("y")
y.tag.test_value = [0, 0, 0, 0]
@as_op([dmatrix, dvector], dvector)
def cumprod_plus(x, y):
return np.cumprod(x) + y
fn = function([x, y], cumprod_plus(x, y))
r = fn([[1.5, 5], [2, 2]], [1, 100, 2, 200])
r0 = np.array([2.5, 107.5, 17.0, 230.0])
assert np.allclose(r, r0), (r, r0)
def test_infer_shape(self):
x = dmatrix("x")
x.tag.test_value = np.zeros((2, 2))
y = dvector("y")
y.tag.test_value = [0, 0, 0, 0]
def infer_shape(fgraph, node, shapes):
x, y = shapes
return [y]
@as_op([dmatrix, dvector], dvector, infer_shape)
def cumprod_plus(x, y):
return np.cumprod(x) + y
self._compile_and_check(
[x, y],
[cumprod_plus(x, y)],
[[[1.5, 5], [2, 2]], [1, 100, 2, 200]],
cumprod_plus.__class__,
warn=False,
)
