docker/ray-ml/README.md
This image is an extension of the rayproject/ray image. It includes all extended requirements of RLlib, Serve and Tune. It is a well-provisioned starting point for trying out the Ray ecosystem. Find the Dockerfile here.
Images are tagged with the format {Ray version}[-{Python version}][-{Platform}]. Ray version tag can be one of the following:
| Ray version tag | Description |
|---|---|
latest | The most recent Ray release. |
x.y.z | A specific Ray release, e.g. 2.9.3 |
nightly | The most recent Ray development build (a recent commit from GitHub master) |
The optional Python version tag specifies the Python version in the image. All Python versions supported by Ray are available, e.g. py39, py310 and py311. If unspecified, the tag points to an image using Python 3.9.
The optional Platform tag specifies the platform where the image is intended for:
| Platform tag | Description |
|---|---|
-cpu | These are based off of an Ubuntu image. |
-cuXX | These are based off of an NVIDIA CUDA image with the specified CUDA version xx. They require the NVIDIA Docker Runtime. |
-gpu | Aliases to a specific -cuXX tagged image. |
| no tag | Aliases to -cpu tagged images for ray, and aliases to -gpu tagged images for ray-ml. |
Examples tags:
latestlatest: equivalent to latest-py39-gpu, i.e. image for the most recent Ray releasenightly-py39-cpu806c18-py39-cu112The ray-ml images are not built for the arm64 (aarch64) architecture.
rayproject/ray - Ray and all of its dependencies.