Suggestion: do not reoptimize already converged points

[samuelstjean]

Similar to the idea from https://github.com/tensorflow/probability/pull/928, it seems like internally the (l)bgfs optimisers will go through points that already have reached convergence if any other points in the problem have not. The linked PR allows one to re-enter the optimiser with an initial state, allowing one to remove those already converged points manually.

I was wondering if doing that internally would be an option, that is skipping computations for batches that are already converged, or if that would be too complicated/slow for the general use case to do that internally and automatically.