Beta
We previously called these features ‘Experimental’ and we found that this created confusion amongst some of the users. In the case of a Beta level features, the value add, similar to a Stable feature, has been proven (e.g. pruning is a commonly used technique for reducing the number of parameters in NN models, independent of the implementation details of our particular choices) and the feature generally works and is documented. This feature is tagged as Beta because the API may change based on user feedback, because the performance needs to improve or because coverage across operators is not yet complete.
Level of commitment: We are committing to seeing the feature through to the Stable classification. We are however not committing to Backwards Compatibility. Users can depend on us providing a solution for problems in this area going forward, but the APIs and performance characteristics of this feature may change.
