def test_unpack_tensor_method():
pman = ProductManifold((Sphere(), 10), (Sphere(), (3, 2)),
(Euclidean(), ()))
point = pman.random(4, pman.n_elements)
parts = point.unpack_tensor()
assert parts[0].shape == (4, 10)
assert parts[1].shape == (4, 3, 2)
assert parts[2].shape == (4, )
def test_from_point():
point = [
Sphere().random_uniform(5, 10),
Sphere().random_uniform(5, 3, 2),
Euclidean().random_normal(5),
]
pman = ProductManifold.from_point(*point, batch_dims=1)
assert pman.n_elements == (10 + 3 * 2 + 1)
def test_from_point_checks_shapes():
point = [
Sphere().random_uniform(5, 10),
Sphere().random_uniform(3, 3, 2),
Euclidean().random_normal(5),
]
pman = ProductManifold.from_point(*point)
assert pman.n_elements == (5 * 10 + 3 * 3 * 2 + 5 * 1)
with pytest.raises(ValueError) as e:
_ = ProductManifold.from_point(*point, batch_dims=1)
assert e.match("Not all parts have same batch shape")
def test_reshaping():
pman = ProductManifold((Sphere(), 10), (Sphere(), (3, 2)),
(Euclidean(), ()))
point = [
Sphere().random_uniform(5, 10),
Sphere().random_uniform(5, 3, 2),
Euclidean().random_normal(5),
]
tensor = pman.pack_point(*point)
assert tensor.shape == (5, 10 + 3 * 2 + 1)
point_new = pman.unpack_tensor(tensor)
for old, new in zip(point, point_new):
np.testing.assert_allclose(old, new)
def test_component_inner_product():
pman = ProductManifold((Sphere(), 10), (Sphere(), (3, 2)),
(Euclidean(), ()))
point = [
Sphere().random_uniform(5, 10),
Sphere().random_uniform(5, 3, 2),
Euclidean().random_normal(5),
]
tensor = pman.pack_point(*point)
tangent = torch.randn_like(tensor)
tangent = pman.proju(tensor, tangent)
inner = pman.component_inner(tensor, tangent)
assert inner.shape == (5, pman.n_elements)
def test_init():
pman = ProductManifold((Sphere(), 10), (Sphere(), (3, 2)))
assert pman.n_elements == (10 + 3 * 2)
assert pman.name == "(Sphere)x(Sphere)"