Awesome new set of features! They can be found in https://docs.nvidia.com/deeplearning/sdk/cudnn-developer-guide/index.html#features-of-rnn-functions. Since the changes will likely require API changes in RNN op, I took the liberty to repurpose @sbodenstein 's issue for the API discussion.
Desirable new features would be: - Allow packed sequence data or padding handling for variable length sequences. - Support LSTM-projection for large-scale RNNs. - RNN state clipping. Desirable performance improvements would be: - Allow down conversion to enable HMMA when possible. - Allow algorithm search for performance tuning through `findIntensity`. - Reuse the space for random states when dropout is enabled. Unclear: - What's the recommendation for `_ALGO_PERSIST_*`? @DickJC123 @ptrendx [ Full content available at: https://github.com/apache/incubator-mxnet/issues/9543 ] This message was relayed via gitbox.apache.org for [email protected]
