TaoLv commented on issue #10104: [WIP][MXNET-107] Fused RNN implementation for CPU URL: https://github.com/apache/incubator-mxnet/pull/10104#issuecomment-387425685 I feel it difficult to change the existing gluon LSTM layer from normal `Block` to `HybridBlock` without changing APIs. (1) I need concatenate the exsiting `i2h_weight`, `h2h_weight`, `i2h_bias` and `h2h_bias` together to feed them into the fused operator. I think that is time consuming. [link](https://github.com/apache/incubator-mxnet/blob/master/python/mxnet/gluon/rnn/rnn_layer.py#L62) (2) I cannot create `begin_state` if it's not presented in the `hybrid_forward` function, since I cannot get the shape and batch size here in a HybridBlock. [link](https://github.com/apache/incubator-mxnet/blob/master/python/mxnet/gluon/rnn/rnn_layer.py#L174) Maybe I missed something. Any cues about it? @szha @piiswrong
---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected] With regards, Apache Git Services
