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From sandeep krishnamurthy <>
Subject [Launch Announcement] Keras 2 with Apache MXNet (incubating) backend
Date Tue, 22 May 2018 16:15:06 GMT
Hello MXNet community,

Keras users can now use the high-performance MXNet deep learning engine for
the distributed training of convolutional neural networks (CNNs) and
recurrent neural networks (RNNs). With an update of a few lines of code,
Keras developers can increase training speed by using MXNet's multi-GPU
distributed training capabilities. Saving an MXNet model is another
valuable feature of the release. You can design in Keras, train with
Keras-MXNet, and run inference in production, at-scale with MXNet.

>From our initial benchmarks, CNNs with Keras-MXNet is up to 3X faster on
GPUs compared to the default backend. See the benchmark module
<> for
more details.

RNN support in this release is experimental with few known
issues/unsupported functionalities. See using RNN with Keras-MXNet
limitations and workarounds doc
for more details.

See Release Notes
<> for
more details on unsupported operators and known issues. We will continue
our efforts in the future releases to close the gaps.

Thank you for all the contributors - Lai Wei <>, Karan
Jariwala <>, Jiajie Chen
<>, Kalyanee Chendke <>,
Junyuan Xie <>

We welcome your contributions - Here is the issue with the
list of operators to be implemented. Do check it out and create a PR -


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