CD) in machine learning projectsImplementing continuous integration & delivery (CI/CD) in machine learning projects

Last update: Oct 03, 2022

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Overview

CML with cloud compute

This repository contains a sample project using CML with Terraform (via the cml-runner function) to launch an AWS EC2 instance and then run a neural style transfer on that instance. On a pull request, the following actions will occur:

GitHub will deploy a runner with a custom CML Docker image
cml-runner will provision an EC2 instance and pass the neural style transfer workflow to it. DVC is used to version the workflow and dependencies.
Neural style transfer will be executed on the EC2 instance
CML will report results of the style transfer as a comment in the pull request.

The key file enabling these actions is .github/workflows/cml.yaml.

Variables

You must create a personal access token with repository and workflow privileges to supply as a secret, in addition to your AWS credentials (AWS_ACCESS_KEY_ID,AWS_SECRET_ACCESS_KEY, and optinoally AWS_SESSION_TOKEN).

Owner

Iterative

Developer Tools for Machine Learning

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