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

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Machine Learningcml_cloud_case
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
Iterative
GitHub Repository
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