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From Yuan Tang <terrytangy...@gmail.com>
Subject Re: Request for comments - Keras-MXNet as submodule in MXNet
Date Fri, 23 Mar 2018 18:58:51 GMT
-1 I don't think this has significant difference. The adoption from
existing Keras users will only come once it's landed in Keras repo. I doubt
that many people will use it unless it's more stable and backward
compatibility is guaranteed.

On Fri, Mar 23, 2018 at 2:54 PM, Naveen Swamy <mnnaveen@gmail.com> wrote:

> The proposal is about bringing a forked version of Keras(that works only
> with MXNet) into Apache MXNet repo submodule that way MXNet gets more
> eyeballs from existing Keras users and eventually Gluon, etc., , like
> Sandeep mentioned Keras has a large user base which MXNet could tap into.
>
> On Fri, Mar 23, 2018 at 11:50 AM, Yao Wang <kevinthesunwy@gmail.com>
> wrote:
>
> > -1 Creating Keras as submodule of MXNet will provide users a feeling that
> > MXNet depends on Keras. Keras is a frontend library which can be
> supported
> > by various different backend framework. It would be better to add backend
> > framework as Keras's submodule(Keras depends on MXNet) rather than
> > opposite.
> >
> > Best,
> > Yao
> >
> > 2018-03-23 11:44 GMT-07:00 Xingjian SHI <xshiab@connect.ust.hk>:
> >
> > > -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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