* If all existing RNN integration tests pass with MKL-DNN build, this should give enough confidence? * Also, I remember one of the community member saying "mxnet-mkl" pypi package is not compiled with MKLDNN. Not sure about this, but, can we please confirm?
Best, Sandeep On Tue, Jul 3, 2018 at 7:37 PM Zhao, Patric <[email protected]> wrote: > Hi Alex, > > Regarding RNN, the first version of MKL-DNN RNN API is available in the > MKL-DNN master branch. > We have integrated it in our local branch and you can try our code (still > in developments). > > > https://github.com/lihaofd/incubator-mxnet/blob/mkldnn-rnn/src/operator/nn/mkldnn/mkldnn_rnn_impl.h > > We plan to PR our integration into MXNET master when both functionality > and performance are qualified. > > Thanks, > > --Patric > > > -----Original Message----- > > From: Alex Zai [mailto:[email protected]] > > Sent: Wednesday, July 4, 2018 1:17 AM > > To: [email protected] > > Subject: MKLDNN Integration Stable Release > > > > We are preparing a stable release of MKL-DNN integration in 1.3.0 > > (experimental since 1.2.0), which supports acceleration of operations > such as > > Convolution, Deconvolution, FullyConnected, Pooling, Batch Normalization, > > Activation, LRN, Softmax. Currently the RNN operator is not supported as > the > > MKL-DNN API is still experimental; however, they hope to release a more > > stable version RNN API this or next week in MKL-DNN 0.15. > > > > We will have CPP unit test support on these operators and I am planning > to > > write python unit tests to compare a RNN network's results from the > MKLDNN > > backend with that of the GPU to test accuracy. Is there any additional > coverage > > that you think we should cover in the next two weeks? > > > > Alex > -- Sandeep Krishnamurthy
