Candidate Recommendation Snapshot: Web Neural Network API (Call for Wide Review)

Web Neural Network API

https://www.w3.org/TR/2024/CR-webnn-20240411/

feedback due by: October 1, 2024

Published by
 Web Machine Learning Working Group

Abstract

This document describes a dedicated low-level API for neural network inference hardware acceleration.

Status of the Document

This section describes the status of this document at the time of its publication. A list of current W3C publications and the latest revision of this technical report can be found in the W3C technical reports index at https://www.w3.org/TR/. 

This document was published by the Web Machine Learning Working Group as a Candidate Recommendation Snapshot using the Recommendation track. 

Publication as a Candidate Recommendation does not imply endorsement by W3C and its Members. A Candidate Recommendation Snapshot has received wide review, is intended to gather implementation experience, and has commitments from Working Group members to royalty-free licensing for implementations. 

This document is intended to become a W3C Recommendation; it will remain a Candidate Recommendation at least until 1 October 2024 to gather additional feedback. 

The Web Machine Learning Working Group maintains a list of all bug reports that the group has not yet addressed. Pull requests with proposed specification text for outstanding issues are strongly encouraged. 

This document was produced by a group operating under the W3C Patent Policy. W3C maintains a public list of any patent disclosures made in connection with the deliverables of the group; that page also includes instructions for disclosing a patent. An individual who has actual knowledge of a patent which the individual believes contains Essential Claim(s) must disclose the information in accordance with section 6 of the W3C Patent Policy. 

This document is governed by the 03 November 2023 W3C Process Document. 

 

Since the initial Candidate Recommendation Snapshot the Working Group has gathered further implementation experience and added new operations and data types needed for well-known transformers to support generative AI use cases. In addition, informed by this implementation experience, the group removed MLCommandEncoder, support for synchronous execution, and higher-level operations that can be expressed in terms of lower-level primitives in a performant manner. The group has also updated the specification to use modern authoring conventions to improve interoperability and precision of normative definitions. The group is developing a new feature, a backend-agnostic storage type, to improve performance and interoperability between the WebNN, WebGPU APIs and purpose-built hardware for ML and expects to republish this document as a Candidate Recommendation Snapshot when ready for implementation. This document is maintained and updated at any time. Some parts of this document are work in progress and further improvements are expected to be reflected in revised Candidate Recommendation Drafts and Snaphots. 

Before requesting transition to Proposed Recommendation, the Working Group will seek to demonstrate that: 
 
  * the API is implementable on top of existing APIs of major platforms, such as Android, Windows and macOS/iOS;
  * it has at least two independent, interoperable implementations of every feature defined in the specification, where interoperability can be verified by passing open test suites, and two or more implementations interoperating with each other;
  * it has an open test suite of every feature defined in the specification.

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This report was automatically generated using https://github.com/w3c/transition-notifier

Received on Thursday, 11 April 2024 07:28:08 UTC