1. Rayvolution Mac Os Update
2. Rayvolution Mac Os Download
3. Rayvolution Mac Os Catalina
4. Rayvolution Mac Os X

Ray currently supports MacOS and Linux.Windows wheels are now available, but Windows support is experimental and under development.

Official Releases¶

You can install the latest official version of Ray as follows. Official releases are produced according to the release process doc.

Note for Windows Users: To use Ray on Windows, Visual C++ runtime must be installed (see Windows Dependencies section). If you run into any issues, please see the Windows Support section.

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Daily Releases (Nightlies)¶

You can install the nightly Ray wheels via the following links. These daily releases are tested via automated tests but do not go through the full release process. To install these wheels, use the following pip command and wheels:

Installing from a specific commit¶

You can install the Ray wheels of any particular commit on master with the following template. You need to specify the commit hash, Ray version, Operating System, and Python version:

For example, here are the Ray 2.0.0.dev0 wheels for Python 3.7, MacOS for commit ba6cebe30fab6925e5b2d9e859ad064d53015246:

Install Ray Java with Maven¶

Before installing Ray Java with Maven, you should install Ray Python with pip install -U ray . Note that the versions of Ray Java and Ray Python must match.Note that nightly Ray python wheels are also required if you want to install Ray Java snapshot version.

The latest Ray Java release can be found in central repository. To use the latest Ray Java release in your application, add the following entries in your pom.xml:

The latest Ray Java snapshot can be found in sonatype repository. To use the latest Ray Java snapshot in your application, add the following entries in your pom.xml:

Note

When you run pipinstall to install Ray, Java jars are installed as well. The above dependencies are only used to build your Java code and to run your code in local mode.

If you want to run your Java code in a multi-node Ray cluster, it’s better to exclude Ray jars when packaging your code to avoid jar conficts if the versions (installed Ray with pipinstall and maven dependencies) don’t match.

Windows Support¶

Windows support is currently limited and “alpha” quality.Bugs, process/resource leaks, or other incompatibilities may exist under various scenarios.Unusual, unattended, or production usage is not recommended.

To use Ray on Windows, the Visual C++ runtime must be installed (see Windows Dependencies section).

If you encounter any issues, please try the following:

• Check the Windows Known Issues page on GitHub to see the latest updates on Windows support.

• In the case that your issue has been addressed, try installing the latest nightly wheels.

If your issue has not yet been addressed, comment on the Windows Known Issues page.

Windows Dependencies¶

For Windows, ensure the latest Visual C++ runtime (install link) is installed before using Ray.

Otherwise, you may receive an error similar to the following when Ray fails to findthe runtime library files (e.g. VCRUNTIME140_1.dll):

Installing Ray on Arch Linux¶

Note: Installing Ray on Arch Linux is not tested by the Project Ray developers.

Ray is available on Arch Linux via the Arch User Repository (AUR) aspython-ray.

You can manually install the package by following the instructions on theArch Wiki or use an AUR helper like yay (recommended for ease of install)as follows:

To discuss any issues related to this package refer to the comments sectionon the AUR page of python-rayhere.

Installing Ray with Anaconda¶

If you use Anaconda and want to use Ray in a defined environment, e.g, ray, use these commands:

Use piplist to confirm that ray is installed.

Building Ray from Source¶

Installing from pip should be sufficient for most Ray users.

However, should you need to build from source, follow these instructions for building Ray.

Docker Source Images¶

Most users should pull a Docker image from the Ray Docker Hub.

• The rayproject/rayimage has ray and all required dependencies. It comes with anaconda and Python 3.7.

• The rayproject/ray-mlimage has the above features as well as many additional libraries.

• The rayproject/base-deps and rayproject/ray-deps are for the linux and python dependencies respectively.

Image releases are tagged using the following format:

Each tag has variants that add or change functionality:

If you want to tweak some aspect of these images and build them locally, refer to the following script:

Beyond creating the above Docker images, this script can also produce the following two images.

• The rayproject/development image has the ray source code included and is setup for development.

• The rayproject/examples image adds additional libraries for running examples.

Rayvolution Mac Os Update

Review images by listing them:

Output should look something like the following:

Launch Ray in Docker¶

Start out by launching the deployment container.

Replace <shm-size> with a limit appropriate for your system, for example512M or 2G. A good estimate for this is to use roughly 30% of your available memory (this iswhat Ray uses internally for its Object Store). The -t and -i options here are required to supportinteractive use of the container.

Note: Ray requires a large amount of shared memory because each objectstore keeps all of its objects in shared memory, so the amount of shared memorywill limit the size of the object store.

You should now see a prompt that looks something like:

Rayvolution Mac Os Download

Test if the installation succeeded¶

To test if the installation was successful, try running some tests. This assumesthat you’ve cloned the git repository.

Troubleshooting¶

Rayvolution Mac Os Catalina

If importing Ray (python3-c'importray') in your development clone resultsin this error:

Rayvolution Mac Os X

Then you should run the following commands: