Before:
shape(NoneType) -> np.shape(None) -> ()  (numpy tends to do this for things it doesn't understand)
shape(TypedLists) -> shape(np.asarray(TypedList)) -> either converts or fails. Now TypedList are considered vectors / 1d like python lists

mit-mot outputs are never memory optimized. Skipping these outputs lets us get rid of two faulty logical branches that existed to mask each:
1. an `if i <= op.info.n_mit_mot:` inside an `else` branch. This was logically wrong in that it included the first non mit-mot output (should have been <, not <=). When this was the output of a while scan it created an artificial dependency on the scan output shape, and didn't allow the rewrite to happen.
2. because of this the outer `if(i <= op.info.n_mit_mot and ...)` had been added to sidestep this artificial dependency. The comment mentioned in was supposed to specifically handle sit-sot/mit-sot of while loops, but it was again looking at all mit-mots + first non mit-mot input. It was logically wrong but canceled the first logical mistake.

If we remove both things just work.

Also avoid useless cast to XTensorType when 0d-tensor suffices