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From Naveen Swamy <mnnav...@gmail.com>
Subject Re: Request for comments - Keras-MXNet as submodule in MXNet
Date Fri, 23 Mar 2018 14:14:35 GMT
+1

> On Mar 22, 2018, at 11:11 PM, Chris Olivier <cjolivier01@gmail.com> wrote:
> 
> +1
> 
> On Thu, Mar 22, 2018 at 10:49 PM sandeep krishnamurthy <
> sandeep.krishna98@gmail.com> wrote:
> 
>> 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
>> 
>> 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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