What’s the Base Docker Image?

Caliban’s modes build docker images using a dynamically generated Dockerfile. You’ll see this Dockerfile stream to stdout when you run any of Caliban’s commands.

In addition to the isolation Docker provides, the images set up a Python virtual environment inside of each container. This guarantees you a truly blank slate; the dependencies you declare in your code directory are the only Python libraries that will be present. No more version clashes or surprises.

Caliban uses a set of base images covering a set of common combinations of python and cuda versions. You can find our base images here. The format of our base image names is gcr.io/blueshift-playground/blueshift:TAG, where TAG describes the configuration of the base image.

For example, gcr.io/blueshift-playground/blueshift:gpu-cuda100-py37 is a base image that has CUDA 10.0 and python 3.7, while gcr.io/blueshift-playground/blueshift:cpu-py38 is a base image that has no CUDA support and uses python 3.8.

Our current matrix of supported combinations:

python 3.7

python 3.8

no cuda



cuda 10.0



cuda 10.1



These images are automatically updated, and if you have an image combination that we don’t support, please file an issue and we’ll consider adding it to our set of supported images. We are planning to add support for custom base images so you can build and use your own specialized image.

The dockerfiles we use to generate our supported images can be found here. We create base gpu images from the Dockerfile.gpu file, and then use these as base images for creating full GPU images with support for specific python versions using this Dockerfile.

We base our gpu base images on the nvidia/cuda images, which contain the relevant CUDA drivers required for GPU use. The virtual environment inside of the Caliban container isolates you from these low-level details, so you can install any tensorflow version you like, or use Jax or Pytorch or any other system.

Details for Maintainers

We utilize Google’s Cloud Build service to build Caliban’s base images. Our Cloud Build configuration file that controls our image generation can be found in the source repository here.

This file can quickly get lengthy and difficult to maintain, so we generate this file using a script and a configuration file. In the configuration file, we specify our supported CUDA versions, our supported python versions, and a list of the combinations we use in our supported images. For our CUDA and python versions, we specify a list of build-args that we then pass to the docker build process for the Dockerfiles described above.

To generate a new cloudbuild.json file, invoke the cloudbuild.py utility with your configuration file:

python ./scripts/cloudbuild.py --config scripts/cloudbuild_config.json  --output cloudbuild.json

This will generate a new cloudbuild.json file which is used by the Cloud Build service to generate our base docker images. For testing, you can set a different base image url for the docker images by using the --base_url keyword argument.

To manually start a Cloud Build for these docker images, navigate to the top-level of the caliban source repository, and use the gcloud builds command:

gcloud builds submit --project=<destination project> --config=cloudbuild.json .

By default this uses your default project and the cloudbuild.json file in your current directory. If you are pushing the images to a different project than your gcloud default, then you may need to set the --project flag to the target project where you are pushing your images. The logs from the build process will be streamed to your console, but they are also available from the Cloud Build tab in the GCP dashboard for your project.

To automate the generation of these images, we utilize build triggers to start a new cloud build whenever the Caliban Dockerfiles are modified in the repository.