wandb docker




W&B docker lets you run your code in a docker image ensuring wandb is configured. It adds the WANDB_DOCKER and WANDB_API_KEY environment variables to your container and mounts the current directory in /app by default. You can pass additional args which will be added to docker run before the image name is declared, we'll choose a default image for you if one isn't passed:

wandb docker -v /mnt/dataset:/app/data wandb docker gcr.io/kubeflow- images-public/tensorflow-1.12.0-notebook-cpu:v0.4.0 --jupyter wandb docker wandb/deepo:keras-gpu --no-tty --cmd "python train.py --epochs=5"

By default we override the entrypoint to check for the existance of wandb and install it if not present. If you pass the --jupyter flag we will ensure jupyter is installed and start jupyter lab on port 8888. If we detect nvidia-docker on your system we will use the nvidia runtime. If you just want wandb to set environment variable to an existing docker run command, see the wandb docker-run command.




--nvidia / --no-nvidia

Use the nvidia runtime, defaults to nvidia if nvidia-docker is present


Output the image digest and exit

--jupyter / --no-jupyter

Run jupyter lab in the container


Which directory to mount the code in the container


Don't mount the current directory


The shell to start the container with


The host port to bind jupyter on


The command to run in the container


Run the command without a tty


Show this message and exit.