Is considerably slower than on other operating systems. Windows does not have a copy-on-write forking model, so spinning up new You can manually install the package by following the instructions on theĪrch Wiki or use an AUR helper like yay (recommended for ease of install) Ray is available on Arch Linux via the Arch User Repository ( AUR) as Note: Installing Ray on Arch Linux is not tested by the Project Ray developers. Using a conda environment, it is recommended to install Ray from PyPi using Ray conda packages are maintained by the community, not the Ray team. Pip install ray in the newly created environment. Installing from pip should be sufficient for most Ray users. However, should you need to build from source, follow these instructions for building Ray. Most users should pull a Docker image from the Ray Docker Hub. The rayproject/ray images include Ray and all required dependencies. It comes with anaconda and various versions of Python. The rayproject/ray-ml images include the above as well as many additional ML libraries. Ray version tag can be one of the following: The rayproject/base-deps and rayproject/ray-deps images are for the Linux and Python dependencies respectively. The most recent Ray development build (a recent commit from Github master)Ī specific development build (uses a SHA from the Github master, e.g. The optional Python version tag specifies the Python version in the image. The optional Platform tag specifies the platform where the image is intended for: If unspecified, the tag points to an image using Python 3.7.Īll Python versions supported by Ray are available, e.g. These are based off of an NVIDIA CUDA image with the specified CUDA version.
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