All incoming gradients to the cloned tensor will be propagated to the original tensor as seen here:
x = torch.randn(2, 2, requires_grad=True)
y = x.clone()
y.retain_grad()

z = y**2
z.mean().backward()

print(y.grad)
print(x.grad)