This is an internal image, the rayproject/ray or rayproject/ray-ml should be used!
This has the python-level dependencies for Ray and the Ray Autoscaler. The ray image is built on top of this. This image is built periodically or when dependencies are added. 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. 1.12.1 |
nightly |
The most recent Ray development build (a recent commit from Github master) |
6 character Git SHA prefix |
A specific development build (uses a SHA from the Github master, e.g. 8960af). |
The optional Python version tag specifies the Python version in the image. All Python versions supported by Ray are available, e.g. py37, py38, py39 and py310. If unspecified, the tag points to an image using Python 3.7.
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. |
rayproject/ray- Ray and all of its dependencies.rayproject/ray-ml- This image with common ML libraries to make development & deployment more smooth!rayproject/base-deps- Internal image with system-level dependencies.