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Project Description

TorchServe (PyTorch mdoel server) is a flexible and easy to use tool for serving deep learning models exported from PyTorch.

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

Prerequisites

  • java 8: Required. TorchServe 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 torchserve. If you have multiple java installed, you can use $JAVA_HOME environment vairable to control which java to use.
  • PyTorch: Required. Latest version of PyTorch will be installed as a part of TorchServe installation.

For ubuntu:

sudo apt-get install openjdk-8-jdk

For centos

sudo yum install java-1.8.0-openjdk

For Mac:

brew tap caskroom/versions
brew update
brew cask install java8

Install PyTorch:

pip install torch torchvision torchtext

Installation

pip install torchserve

Source code

You can check the latest source code as follows:

git clone https://github.com/pytorch/serve.git

Citation

If you use torchserve in a publication or project, please cite torchserve: https://github.com/pytorch/serve