With the PyTorch 1.12 release, developers and researchers can now take advantage of Apple silicon GPUs for significantly faster model training. This unlocks the ability to perform machine learning workflows like prototyping and fine-tuning locally, right on Mac. Accelerated GPU training is enabled using Apple’s Metal Performance Shaders (MPS) as a backend. The benefits include performance speedup from accelerated GPU training and the ability to train larger networks or batch sizes locally. Learn more here. 




 Accelerated GPU training and evaluation speedups over CPU-only (times faster)

Alongside the new MPS device support, the M1 binaries for Core and Domain libraries that have been available for the last few releases are now an official prototype feature. These binaries can be used to run PyTorch natively on Apple Silicon.