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XLA (Accelerated Linear Algebra) is an open-source machine learning (ML)compiler for GPUs, CPUs, and ML accelerators.

The XLA compiler takes models from popular ML frameworks such as PyTorch,TensorFlow, and JAX, and optimizes them for high-performance execution acrossdifferent hardware platforms including GPUs, CPUs, and ML accelerators.

openxla.org is the project's website.

If you want to use XLA to compile your ML project, refer to the correspondingdocumentation for your ML framework:

• PyTorch
• TensorFlow
• JAX

If you're not contributing code to the XLA compiler, you don't need to clone andbuild this repo. Everything here is intended for XLA contributors who want todevelop the compiler and XLA integrators who want to debug or add support for MLfrontends and hardware backends.

If you'd like to contribute to XLA, reviewHow to Contribute and then see thedeveloper guide.

• For questions, contact the maintainers - maintainers at openxla.org

• Community Resources

While under TensorFlow governance, all community spaces for SIG OpenXLA aresubject to theTensorFlow Code of Conduct.