[DNM] add experiment of training torsion energies #163
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Do not merge: this is only a very partial, bare-bones experiment to see how much work it would be to use NAGL to a) train to non-atom properties (not so bad) and b) incorporate geometric information (more work...) and c) incorporate another trained parameter (quite a lot). My general conclusion is that b) and c) is likely not worth porting to the overall library, although open to anything as usual.
All the maths is very ad-hoc and absolutely needs double-checking and testing, especially the geometry functions. Everything currently is only implemented with the DGL backend.
cc @BenCree -- there's an example notebook here that runs through a very short example of what I think you and Danny were describing to me in our call, if you're interested. Happy to chat more if you want to discuss!
P.S. the Dataset code was a huge pain and very repetitive -- it probably needs refactoring.
PR Checklist