PyTorch Upgrades to Cloud TPUs, Links to R

A version of the PyTorch machine learning framework that incorporates a deep learning compiler to connect the Python package to cloud Tensor processors (TPUs) is now available on Google Cloud, the public cloud vendor and PyTorch co-developer Facebook announced. The general availability on PyTorch/XLA means users can access cloud TPU accelerators via a stable integration, the companies said Tuesday (Sept. Separately, promoters of the programming language R released a package that allows developers to use "PyTorch functionality natively from R." The new tool, dubbed "Torch for R," requires no Python installation. Meanwhile, Facebook and Google said PyTorch/XLA combines the machine learning library's APIs with XLA's linear algebra compiler that targets CPUs, GPUS and, now, cloud TPUs. While running on most standard Python programs, PyTorch/XLA defaults to CPUs for operations not yet supported on Tensor processors. That framework helps PyTorch users "find bottlenecks and adapt their programs to run more efficiently on cloud TPUs," said Craig Wiley, director of product development for Google's Cloud AI platform.