+1 On Thu, Mar 22, 2018 at 10:49 PM sandeep krishnamurthy < sandeep.krishn...@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 >