wandb docker

Usage

wandb docker [OPTIONS] [DOCKER_RUN_ARGS]... [DOCKER_IMAGE]

Summary

Run your code in a docker container.

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 existence 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.

Options

Option	Description
--nvidia / --no-nvidia	Use the nvidia runtime, defaults to nvidia if nvidia-docker is present
--digest	Output the image digest and exit
--jupyter / --no-jupyter	Run jupyter lab in the container
--dir	Which directory to mount the code in the container
--no-dir	Don’t mount the current directory
--shell	The shell to start the container with
--port	The host port to bind jupyter on
--cmd	The command to run in the container
--no-tty	Run the command without a tty