def test_numpy_compare(self):
rng = np.random.RandomState(utt.fetch_seed())
M = matrix("A", dtype=config.floatX)
V = vector("V", dtype=config.floatX)
a = rng.rand(4, 4).astype(config.floatX)
b = rng.rand(4).astype(config.floatX)
A = (
[None, "fro", "inf", "-inf", 1, -1, None, "inf", "-inf", 0, 1, -1, 2, -2],
[M, M, M, M, M, M, V, V, V, V, V, V, V, V],
[a, a, a, a, a, a, b, b, b, b, b, b, b, b],
[None, "fro", inf, -inf, 1, -1, None, inf, -inf, 0, 1, -1, 2, -2],
)
for i in range(0, 14):
f = function([A[1][i]], norm(A[1][i], A[0][i]))
t_n = f(A[2][i])
n_n = np.linalg.norm(A[2][i], A[3][i])
assert _allclose(n_n, t_n)
def test_tensor_input(self):
with pytest.raises(NotImplementedError):
norm(np.random.rand(3, 4, 5), None)
def test_non_tensorial_input(self):
with pytest.raises(ValueError):
norm(3, None)
def test_wrong_type_of_ord_for_matrix(self):
with pytest.raises(ValueError):
norm([[2, 1], [3, 4]], 0)
def test_wrong_type_of_ord_for_vector(self):
with pytest.raises(ValueError):
norm([2, 1], "fro")
