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From "Zheng, Da" <dzz...@amazon.com>
Subject Proposal for optimizing Gluon dynamic models for seamless deployment
Date Fri, 11 May 2018 05:20:55 GMT
Hello,

Scientists like to develop models with Gluon or Pytorch and hand the models over to engineer
for deployment. It takes a lot of effort to deploy these models because engineers usually
need to reimplement the models (this is especially for NLP and speech models). Recently, Pytorch
announced their next release v1.0 in a near future, which will integrate Pytorch and Caffe2
for easy deployment of any models in Pytorch. Although Gluon is heading towards this direction,
it currently doesn’t hybridize and export any models for deployment, especially the ones
with control flows.

Previously, I proposed to add symbolic control flow operators to MXNet. I would like to extend
the previous proposal and advance Gluon to hybridize dynamic models with control flows and
deploy them seamlessly. The details of the proposal can be found here: https://cwiki.apache.org/confluence/display/MXNET/Optimize+dynamic+neural+network+models+with+control+flow+operators

Please let me know if you have any comments and suggestions.

Thanks,
Da
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