What’s new in BNNS Graph
The BNNS Graph Builder API now enables developers to write graphs of operations using the familiar Swift language to generate pre- and post-processing routines and small machine-learning models. BNNS compiles graphs ahead of execution and supports real-time and latency-sensitive use cases such as audio processing. In this session, we revisit last year’s bit-crusher example and simplify the Swift component by removing the reliance on a separate Python file and instead implement the audio effect entirely in Swift. The BNNS Graph Builder API is also suited to pre-processing image data before passing that data to a machine learning model. The session also includes a demonstration of clipping the transparent pixels from an image with an alpha channel.
No notes available yet
Be the hero who changes that. Watch the video, jot down what matters, and open a pull request – it's genuinely quick.
Learn how to contribute