A set of application programming interfaces (APIs) that is aimed at breaking down the barriers between different deep learning (DL) inference engines and applications is defined in this standard. The APIs are comprised of functional interfaces including parameter reading, model compilation optimization, operator registration, thread management, input/output data acquisition, inference instance creation, and inference execution.

This standard defines a set of application programming interfaces (APIs) for use with different deep learning (DL) inference engines. The interfaces include parameter reading, model compilation optimization, operator registration, thread management, input/output data acquisition, inference instance creation, and inference execution.

This standard defines efficient APIs for model management, device management, input/output, and inference that break down the barriers between different DL inference engines and applications. The target DL applications include natural language processing, image classification, and object detection.