So I know I can run a loop with te.scan(). However, te.scan() seems to require allocating a Tensor with shape (m, n), where m is the number of iterations. However, if the current state only depends on the previous state, and only the last state is needed, then we only have to allocate (2, n) space.
Is this memory optimization currently achievable using tvm?