rocAL documentation#

The ROCm Augmentation Library (rocAL) lets you improve the throughput and performance of your deep learning applications. It’s designed to efficiently decode and process image and video pipelines from a variety of storage formats on AMD GPUs and CPUs. Its C++ and Python APIs let you program customizable pipelines for different datasets and models. rocAL is optimized for loading and pre-processing data for deep learning applications, with support for multiple data formats and augmentations.

The rocAL public repository is located at ROCm/rocAL.

To contribute to the documentation refer to Contributing to ROCm Docs.

You can find licensing information on the Licensing page.