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.