wandb docker

Usage

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

Summary

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.

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
--help	Show this message and exit.