Tutorial: Host a PyTorch Model for Inference on an Amazon EC2 Instance

Tutorial: Host a PyTorch Model for Inference on an Amazon EC2 Instance

Tutorial: Host a PyTorch Model for Inference on an Amazon EC2 Instance. Assuming you followed the steps mentioned in the previous tutorial, you should have an EC2 instance with a mounted EFS file system.

In this tutorial, I will walk you through the steps involved in hosting a PyTorch model on Amazon Web Services’ EC2 backed by an EFS file system. This article is a part of the series on making AWS Lambda functions stateful with Amazon EFS ( Part 1,  Part 2).

Assuming you followed the steps mentioned in the previous tutorial, you should have an EC2 instance with a mounted EFS file system. We will now configure it to run a Flask server that exposes a PyTorch inference API.

Our goal is to install all the dependencies of PyTorch and test the inference on EC2 before running it in AWS Lambda.

Preparing the EC2 Instance

We will start by creating two directories that will hold the PyTorch modules and the pre-trained ResNet model respectively.

sudo mkdir - p / mnt / efs / fs1 / ml / lib

sudo mkdir - p / mnt / efs / fs1 / ml / model

Let’s start by taking ownership of the EFS file system. This will enable us to install everything that’s needed for the tutorial.

sudo chown -R ec2 - user : ec2 - user / mnt / efs / fs1

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