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Model Server for Apache MXNet is a tool for serving neural net models for inference

Project description

Apache MXNet Model Server (MMS) is a flexible and easy to use tool for serving deep learning models exported from MXNet or the Open Neural Network Exchange (ONNX).

Use the MMS Server CLI, or the pre-configured Docker images, to start a service that sets up HTTP endpoints to handle model inference requests.

Detailed documentation and examples are provided in the docs folder.

Prerequisites

  • java 8: Required. MMS use java to serve HTTP requests. You must install java 8 (or later) and make sure java is on available in $PATH environment variable before installing MMS. If you have multiple java installed, you can use $JAVA_HOME environment vairable to control which java to use.
  • mxnet: mxnet will not be installed by default with MMS 1.0 any more. You have to install it manually if you use MxNet.

For ubuntu:

sudo apt-get install openjdk-8-jre-headless

For centos

sudo yum install java-1.8.0-openjdk

For Mac:

brew tap caskroom/versions
brew update
brew cask install java8

Install MxNet:

pip install mxnet

MXNet offers MKL pip packages that will be much faster when running on Intel hardware. To install mkl package for CPU:

pip install mxnet-mkl

or for GPU instance:

pip install mxnet-cu92mkl

Installation

pip install mxnet-model-server

Development

We welcome new contributors of all experience levels. For information on how to install MMS for development, refer to the MMS docs.

Source code

You can check the latest source code as follows:

git clone https://github.com/awslabs/mxnet-model-server.git

Testing

After installation, try out the MMS Quickstart for

Help and Support

Citation

If you use MMS in a publication or project, please cite MMS: https://github.com/awslabs/mxnet-model-server

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