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From Xingjian SHI <xsh...@connect.ust.hk>
Subject Re: Request for comments - Keras-MXNet as submodule in MXNet
Date Fri, 23 Mar 2018 18:44:47 GMT
-1. I think we should wait until it's merged into keras-team/keras. The repo is still not mature
enough.


Best,

Xingjian


________________________________
From: sandeep krishnamurthy <sandeep.krishna98@gmail.com>
Sent: Friday, March 23, 2018 1:49 PM
To: dev@mxnet.incubator.apache.org
Subject: Request for comments - Keras-MXNet as submodule in MXNet

Hello MXNet Community,

Along with Lai, Karan and other MXNet contributors, I am working on adding
MXNet backend for Keras. Currently supporting around ~70% of Keras APIs
across CNNs and RNNs.
https://github.com/deep-learning-tools/keras/tree/keras2_mxnet_backend
[https://avatars0.githubusercontent.com/u/32447491?s=400&v=4]<https://github.com/deep-learning-tools/keras/tree/keras2_mxnet_backend>

deep-learning-tools/keras<https://github.com/deep-learning-tools/keras/tree/keras2_mxnet_backend>
github.com
keras - Deep Learning library for Python. Runs on TensorFlow, Theano, or CNTK.




We wanted to gather the community feedback on the proposal for including
this keras-mxnet package as a submodule in Apache MXNet. This will enable
providing the Keras interface for MXNet users. MXNet users can choose Keras
interface for building their Neural Networks in Symbolic Mode (Ex:
mx.keras).

*Advantages:*

1. Keras is widely popular interface that many DL practitioners are
familiar. By including keras interface within MXNet natively, we enable
many users to use MXNet with 0 learning curve.

2.  Adding as submodule and exposing natively within MXNet pip package,
would greatly enhance user experience and get more users as compared to
releasing a fork repository independently.

3. Why submodule? - Helps in easily managing with patching the latest
parent keras-team/keras developments and releases. Thereby helping us
provide users the core keras experience. Operational management.

4. Other minor advantages - Operational maintenance, pip, CI and quality
control.

Please do share your comments on the proposal.

Best,
Sandeep

*Note: *We tried merging with keras-team/keras and we created a PR
<https://github.com/keras-team/keras/pull/9291> as well. However, due to
multiple design incompatibility challenges, we need significant re-work on
MXNet Module, KVStore, Optimizers to address keras-team design concerns.
Since, we are adhering to keras API interface exposed to users, we are
planning release on the forked repo for now. More details on the design
challenges and workaround tried -
https://docs.google.com/document/d/1Vn5ip5MzCKcN29KCCnwjB2d59y-VevdLrdn_eNd3nE4/edit?usp=sharing

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