Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
Consumers of VW as a library can provide their own event pools, etc. Previous parsers were always able to predict when an even would be needed ahead of time, so would only allocate when necessary. This was done by relying on a single incoming event preallocation to let the external host deallocate in the case of nothing to be parsed.
This does not work for the FB parser due to how it handles re-entrancy, and we do not want to spend the time re-architecting it to avoid this. The fix, in this case, is to expand the API to include a callback to return spare events back to the host's event pool.
Consumers of VW as a library can provide their own event pools, etc. Previous parsers were always able to predict when an even would be needed ahead of time, so would only allocate when necessary. This was done by relying on a single incoming event preallocation to let the external host deallocate in the case of nothing to be parsed.
This does not work for the FB parser due to how it handles re-entrancy, and we do not want to spend the time re-architecting it to avoid this. The fix, in this case, is to expand the API to include a callback to return spare events back to the host's event pool.