With the ROCm support for PyTorch move from “Beta” to “Stable,” all the functions and features commits are now verified through a full Continuous Integration (CI) process. The CI process helps ensure the proper build and test process ahead of an expected Docker and PIP wheel release with stable commits forthcoming.
Support for Kineto Profiler
The addition of Kineto profiler support to ROCm now helps developers and users understand performance bottlenecks through effective diagnosis and profiling tools. The tool also provides recommendations to improve known issues and visualization through TensorBoard UI.
Key PyTorch Libraries support added