This standard defines a set of operator interfaces frequently found in artificial intelligence (AI) applications, where the AI operators refer to the standard building blocks and primitives for performing basic AI operations. It defines the functionality and the specific input and output operands of an AI operator. It takes into account both generality and efficiency, and covers various types of operators, such as those related to basic mathematics, neural network, and machine learning.
- Sponsor Committee
- C/DC - Data Compression Standards Committee
- Active PAR
- PAR Approval
Working Group Details
Standard for Application Programming Interface (API) of Deep Learning Inference Engine
This standard defines a set of application programming interfaces (APIs) that can be used on different deep learning inference engines. The interfaces include parameter reading, model compilation optimization, operator registration, thread management, input/output data acquisition, inference instance creation and inference execution.
IEEE Standard for Artificial Intelligence (AI) Model Representation, Compression, Distribution, and Management
The AI development interface, AI model interoperable representation, coding format, and model encapsulated format for efficient AI model inference, storage, distribution, and management are discussed in this standard.