About

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.

Build a Custom Container with Gradient

1. Create a Dockerfile Host on GitHub or a local file. Example on GitHub Example: https://github.com/Paperspace/tf-jupyter-dockerfile/blob/master/Dockerfile

2. Run a Job to build the container from the Dockerfile and publish to a container registry Example:

paperspace jobs create \
--apiKey XXXXXXXXXXXXXXXXXXx \
--workspace /path/to/repo \
--useDockerfile true \
--buildOnly true \
--registryTarget my-registry/name:tag \
--registryTargetUsername my-username \
--registryTargetPassword XXXXXXXXXXXXX

Build a Custom Container Locally

1. To get started, you’ll need:

• An Ubuntu computer with DockerCE, NVIDIA-docker, 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 Docker Hub account docker login -u <username> -p <password>

2. Add a Docker file to a working directory on your system

You can make your own file (see Requirements below) or use one like this example: https://github.com/Paperspace/tensorflow-python​

3. In the same directory:

• 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

4. Push the image to Docker Hub with your username:

docker push <username>/test-container:latest

Requirements of Custom Notebooks

• Python

• Jupyter and all of Jupyter dependencies must be installed:

​ http://jupyter.org/install​

conda install -c conda-forge jupyterlab

If you don't specify a user, your container user will be 'root'

Bringing your Custom Container to Gradient

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!

Notebooks

Click the advanced options toggle on the notebook create a notebook page.

Follow the rest of the steps here to create your Notebook by selecting your machine type, naming your notebook, and clicking Create.