Sure, no problem.
It’s an auto-encoder, so the target is the same the input. The network reduces the input to a smaller-dimensional feature vector (embedding) and then tries to re-construct it.
For example, if input is 272 element vector, the network reduces this vector down to something that is say a 100 element vector. It then tries to reconstruct the original vector based on this reduced version.
so x in and x out.