Keras 1.2.2 with MXNet Backend  

Highlights

1. Adding Apache MXNet backend for Keras 1.2.2.
2. Easy to use multi-gputraining with MXNet backend.
3. High-performance model training in Keras with MXNet backend.

Getting Started Resources

1. Installation - https://github.com/dmlc/keras/wiki/Installation
2. How to use Multi-GPU for training in Keras with MXNet backend - https://github.com/dmlc/keras/wiki/Using-Keras-with-MXNet-in-Multi-GPU-mode
3. For more examples explore keras/examples directory.
4. Source Repo - https://github.com/dmlc/keras

For more details on unsupported functionalities, known issues and resources refer to release notes - https://github.com/dmlc/keras/releases

Apple CoreML Converter

You can now convert your MXNet models into Apple CoreML format so that they can be run on Apple devices which means that you can build your next iPhone app using your own MXNet model!

We This tool currently support supports conversion of models that are similar to:

• Inception
• Network-In-Network
• Squeezenet
• Resnet
• Vgg
• <More coming soon>

List of layers that can be currently converted: Activation, Batchnorm, Concat, Convolution, Deconvolution, Dense, Elementwise, Flatten, Pooling, Reshape, Softmax, Transpose. <More coming soon>.

For more details on how to convert the models, refer to https://github.com/apache/incubator-mxnet/tree/master/tools/coreml