wandb docker
2 minute read
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:
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 |
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