def test_copy_detached(self):
x = State(k=torch.nn.Parameter(torch.rand(5, 3)))
y = x.make_copy()
y.k[:] = 0
print(x.k)
print(y.k)
def test_copy_deep(self):
x = State(k=np.asarray(["a", "b", "c"]))
y = x.make_copy(deep=False)
y.k[:] = "q"
print(x.k)
print(y.k)
def test_copy_non_detached(self):
x = State(k=torch.nn.Parameter(torch.rand(5, 3)))
y = x.make_copy(detach=False)
l = y.k.sum()
l.backward()
print(x.k.grad)