def test_add_update_params():
b = np.random.random((2, 3)).astype(np.float32)
y = Buffer(b)
@jit.trace
def f(x):
return F.add_update(y, x)
f(np.zeros((2, 3)).astype(np.float32))
z = Buffer(np.zeros((2, 3)).astype(np.float32))
F.add_update(y, z, beta=0.1)
res = f(np.ones((2, 3)).astype(np.float32))
assertTensorClose(res, b + 1)
def test_add_update():
shape = (2, 3)
v = np.random.random(shape).astype(np.float32)
b = Buffer(v)
u = F.add_update(b, 1)
assertTensorClose(u.numpy(), v + 1)
u = F.add_update(b, 1)
assertTensorClose(u.numpy(), v + 2)
x = np.ones((2, 2), dtype=np.float32)
y = x * 0.5
dest = tensor(x)
delta = tensor(y)
r = F.add_update(dest, delta, alpha=tensor(0.9), beta=0.1, bias=0.1)
assertTensorClose(r.numpy(), x * 0.9 + y * 0.1 + 0.1)