def test_simple_creation() -> None:
tensor = torch.tensor(np.random.rand(3, 2, 3))
box_tensor = MinDeltaBoxTensor(tensor)
assert (tensor.data.numpy() == box_tensor.data.numpy()).all() # type: ignore
assert isinstance(box_tensor, BoxTensor)
tensor = torch.tensor(np.random.rand(2, 10))
box_tensor = MinDeltaBoxTensor(tensor)
assert (tensor.data.numpy() == box_tensor.data.numpy()).all() # type: ignore
assert isinstance(box_tensor, BoxTensor)
def test_shape_validation_during_creation():
tensor = torch.tensor(np.random.rand(3))
with pytest.raises(ValueError):
box_tensor = MinDeltaBoxTensor(tensor)
tensor = torch.tensor(np.random.rand(3, 11))
with pytest.raises(ValueError):
box_tensor = MinDeltaBoxTensor(tensor)
tensor = torch.tensor(np.random.rand(3, 3, 3))
with pytest.raises(ValueError):
box_tensor = MinDeltaBoxTensor(tensor)
def test_round_trip():
shape = (3, 1, 5)
minimum_delta = 1.0
z = torch.tensor(np.random.rand(*shape))
Z = z + torch.tensor(np.random.rand(*shape)) + minimum_delta
W = MinDeltaBoxTensor.W(z, Z, minimum_delta=minimum_delta)
box = MinDeltaBoxTensor(W, minimum_delta=minimum_delta)
assert box.z.shape == (3, 1, 5)
assert torch.allclose(box.z, z)
assert torch.allclose(box.Z, Z)
assert ((box.Z - box.z) > minimum_delta).all()
def test_creation_from_center(beta, threshold, delta):
shape = (3, 5)
c = torch.tensor(np.random.rand(*shape))
box = MinDeltaBoxTensor.from_center_vector(c,
delta=delta,
beta=beta,
threshold=threshold)
assert torch.allclose(box.Z, c + delta / 2.0)
assert torch.allclose(box.z, c - delta / 2.0)
def test_creation_from_zZ():
shape = (3, 1, 5)
minimum_delta = 1.0
z = torch.tensor(np.random.rand(*shape))
Z = z + torch.tensor(np.random.rand(*shape)) + minimum_delta
box = MinDeltaBoxTensor.from_zZ(z, Z, minimum_delta=minimum_delta)
assert box.z.shape == (3, 1, 5)
assert torch.allclose(box.z, z)
assert torch.allclose(box.Z, Z)
assert ((box.Z - box.z) > minimum_delta).all()
def test_creation_from_vector(beta, threshold):
shape = (3, 1, 5)
z = torch.tensor(np.random.rand(*shape))
w_delta = torch.tensor(np.random.rand(*shape))
v = torch.cat((z, w_delta), dim=-1)
box = MinDeltaBoxTensor.from_vector(v, beta=beta, threshold=threshold)
assert box.Z.shape == (3, 1, 5)
assert torch.allclose(box.z, z)
assert torch.allclose(
box.Z,
z
+ torch.nn.functional.softplus(
w_delta, beta=beta, threshold=threshold
),
)
def test_creation_from_zZ():
shape = (3, 1, 5)
z = torch.tensor(np.random.rand(*shape))
Z = z + torch.tensor(np.random.rand(*shape))
box = MinDeltaBoxTensor.from_zZ(z, Z)
assert box.z.shape == (3, 1, 5)