Paul
Paul
> @paul0403 just checking that this should still be open? @josh146 my plan is to have seperate issue, separate PR, separate story, separate everything, for the batching rule bug and...
Closing this as `value_and_grad` is merged in by #804
> * an enhancement on the frontend to side to split out quantum tapes into different functions, with one benefit being that multi-tape transforms are compatible with the mlir gradient...
We should reach out to the original author before deciding whether this should be an additional section to the [original demo](https://github.com/PennyLaneAI/qml/blob/master/demonstrations/tutorial_eqnn_force_field.py) or a separate new demo. Until then I won't...
@isaacdevlugt given that this change is quite small, should we make any updates to the metadata?
> You'll want to change the "Updated on:" field in the metadata. Done
@isaacdevlugt I don't think there's any leftover work here, so I think we should deploy it and mark it as done. Not sure about CI though.
> @paul0403 @isaacdevlugt I recommend not merging this demo if it is using finite-difference or a reduction in the timesteps that deviates from the current demo. > > @paul0403 you...
> @paul0403 @isaacdevlugt I recommend not merging this demo if it is using finite-difference or a reduction in the timesteps that deviates from the current demo. > > @paul0403 you...
> The actual error is probably because of this typo though: > > ``` > decomp = qml.QubitUnitary.compute_decomposition(U, wires=wires)#, id="U") > for op in decomp: > qml.apply(op) # was decomp...