Model Server for Apache MXNet is a tool for serving neural net models for inference. With Prometheus metrics.
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.
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.
sudo apt-get install openjdk-8-jre-headless
sudo yum install java-1.8.0-openjdk
brew tap caskroom/versions brew update brew cask install java8
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
pip install mxnet-model-server
We welcome new contributors of all experience levels. For information on how to install MMS for development, refer to the MMS docs.
You can check the latest source code as follows:
git clone https://github.com/awslabs/mxnet-model-server.git
After installation, try out the MMS Quickstart for
Help and Support
If you use MMS in a publication or project, please cite MMS: https://github.com/awslabs/mxnet-model-server
Release history Release notifications | RSS feed
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Hashes for mxnet-model-server-prometheus-1.0.8b20190923.tar.gz
Hashes for mxnet_model_server_prometheus-1.0.8b20190923-py3.7.egg
Hashes for mxnet_model_server_prometheus-1.0.8b20190923-py3-none-any.whl