def test_set_subtensor():
x = TensorWrapper([1, 2, 3])
x[:] = [1, 1, 1]
np.testing.assert_almost_equal(x.numpy(), [1, 1, 1], decimal=6)
x[[0, 2]] = [3, 2]
np.testing.assert_almost_equal(x.numpy(), [3, 1, 2], decimal=6)
x[1:3] = [4, 5]
np.testing.assert_almost_equal(x.numpy(), [3, 4, 5], decimal=6)
def test_release():
def check(f):
n = 0
d = None
for i in range(3):
f()
m = len(gc.get_objects())
d = m - n
n = m
assert d == 0
x = TensorWrapper([0.0])
dy = TensorWrapper(np.ones_like(x.numpy()))
@check
def _():
g = Grad().wrt(x)
y = x * x
g(y, dy)
@check
def _():
with Grad().wrt(x) as g:
pass
@check
def _():
with Grad().wrt(x) as g:
y = x * x
def test_matmul():
A = TensorWrapper(np.random.rand(5, 7).astype("float32"))
B = TensorWrapper(np.random.rand(7, 10).astype("float32"))
C = A @ B
np.testing.assert_almost_equal(C.numpy(), A.numpy() @ B.numpy(), decimal=6)