Skip to content

hyper-ml/jupyter-extensions

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

13 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Run Jupyter notebooks in background

This extension supports running and monitoring notebooks in the background from the comfort of Jupyter Labs.

The use cases are -

  • you want to continue working on an approach and try several other approaches at the same time in background
  • you are sharing expensive resources like GPU with others in your team or univ

Requirements

  • Jupyter Labs (>2.0.0)
  • hyperML (>0.9.0)

Install

jupyter labextension install hyperml-submit-notebooks

Get Started

Setup the following OS environment variables:

  • hyperML:
    • HYPERML_SERVER_ENDPOINT
    • HYPERML_API_KEY
  • AWS S3: The source Notebook and the processed notebook will be stored on S3 or Minio
    • HYPERML_S3_ACCESS_KEY
    • HYPERML_S3_SECRET_KEY
    • HYPERML_S3_BUCKET (defaults to hyperML)
    • HYPERML_S3_URL (e.g. s3-us-west-2.amazonaws.com)
    • HYPERML_S3_SECURE (default true)

Scheduling notebooks

  1. Locate Run in Background button in notebook toolbar

check screens/run-in-background.png

  1. Enter Resource Plan (must be setup on hyperML) and Container Image

check screens/choose-params.png

  1. Click OK
  2. Continue working on the current notebook or monitor the background request on background-notebooks tab.

check screens/background-notebooks.png

  1. Download and Open the processed notebook

Note: You can also open background notebooks from command search 'background-notebooks:open'.

Limitations

Only Dark mode styling as of now

Issue Reporting

Welcome any issues. We are a small team to expect a reponse time of 2-3 days

About hyperML

hyperML is a radically simplifies on-cloud machine learning for teams/developers. Scale your training jobs right from jupyter labs session or launch a notebook with click of button. Read more details at https://www.hyperml.com

About

Run notebooks in background from comfort of Jupyter Labs

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published