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
