Building a Custom Container
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Last updated
The Custom Containers feature lets you pull your own image from a container registry eg Docker Hub. This article will help you prepare a custom Docker container and show you how to bring that Container into Gradient by creating either a Notebook or an Experiment with your custom container. We recommend using Docker to get the container image from your system to Gradient.
Create a Dockerfile Host on GitHub or a local file. Example on GitHub Example:
Run a Job to build the container from the Dockerfile and publish to a container registry Example:
Run: docker build -t <name of image>
For the example file above, you would enter: docker build -t test-container
Tag the image so that it can be added to a repo with the image id, your Docker Hub username, and a name for the image :
docker tag <image id> <dockerhub username>/test-container:latest
docker push <username>/test-container:latest
Python
Jupyter and all of Jupyter dependencies must be installed:
conda install -c conda-forge jupyterlab
If you don't specify a user, your container user will be 'root'
After you've pushed your custom container to Docker or you found a public container that is already there, it's time to pull it into Gradient!
Click the advanced options toggle on the notebook create a notebook page.
An Ubuntu computer with , , and NVIDIA Drivers installed (if you don’t have a Linux machine, use a Paperspace Linux VM!).
From that machine, you'll need to be logged into your account
docker login -u <username> -p <password>
You can make your own file (see Requirements below) or use one like this example:
Follow the rest of the steps to create your Notebook by selecting your machine type, naming your notebook, and clicking Create.