This release is a pre-release and may not be stable for production use.
Project Description
Multi 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 multi-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.
Important links
Source code
You can check the latest source code as follows:
git clone https://github.com/awslabs/multi-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/multi-model-server
1 maintainer
Metadata
1 maintainer
Release files for multi-model-server 1.1.0b20191126
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Release files / multi_model_server-1.1.0b20191126-py2.py3-none-any.whl
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