WebML WG Teleconference – 22 September 2022 - 14:00-15:00 UTC

Latest version: https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-09-22-wg-agenda.md


WebML WG Teleconference – 22 September 2022 - 14:00-15:00 UTC
San Francisco (U.S.A. - California)     Thu, 22 September 2022  07:00   UTC-7 hours
Boston (U.S.A. - Massachusetts) Thu, 22 September 2022  10:00   UTC-4 hours
London (United Kingdom - England)       Thu, 22 September 2022  15:00   UTC+1 hours
Berlin (Germany)        Thu, 22 September 2022  16:00   UTC+2 hours
Helsinki (Finland)      Thu, 22 September 2022  17:00   UTC+3 hours
Shanghai (China)        Thu, 22 September 2022  22:00   UTC+8 hours
Tokyo (Japan)   Thu, 22 September 2022  23:00   UTC+9 hours
Corresponding UTC (GMT) Thu, 22 September 2022  14:00 UTC

Other locations: https://www.timeanddate.com/worldclock/fixedtime.html?iso=20220922T14


<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-09-22-wg-agenda.md#logistics>Logistics

  *   Chair: Anssi
  *   Scribe: ? (see howto<https://github.com/webmachinelearning/meetings/blob/main/scribe-howto.md>, volunteers welcome!)
  *   IRC: irc://irc.w3.org:6667/#webmachinelearning

  *   IRC web client: https://irc.w3.org/?channels=#webmachinelearning

  *   Joining instructions: https://lists.w3.org/Archives/Member/internal-webmachinelearning/2020Apr/0000.html

  *   Minutes: https://www.w3.org/2022/09/22-webmachinelearning-minutes.html


<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-09-22-wg-agenda.md#%E2%84%B9%EF%B8%8F-webnn-api-candidate-recommendation-open-issues>ℹ️ WebNN API Candidate Recommendation open issues
Review and discuss the current CR issues, work out a plan to address the issues prior to the expected CR publication.

  *   Current CR issues https://github.com/webmachinelearning/webnn/issues?q=is%3Aissue+is%3Aopen+label%3Acr


  *   Support asynchronous context creation (two PRs for two design alternatives)

     *    TAG recommendation requested w3ctag/design-reviews#771<https://github.com/w3ctag/design-reviews/issues/771>
     *    issue: webmachinelearning/webnn#272<https://github.com/webmachinelearning/webnn/issues/272>
     *   Status: Awaits TAG recommendation on the design, no WG action required.
  *   Web platform tests

     *    test plan: webmachinelearning/webnn#265 (comment)<https://github.com/webmachinelearning/webnn/issues/265#issuecomment-1246622380>
     *   Status: Test plan published, review ahead the meeting.
  *   Add method steps and normative algorithms to operations

     *    issue: webmachinelearning/webnn#210<https://github.com/webmachinelearning/webnn/issues/210>
     *    issue: webmachinelearning/webnn#211<https://github.com/webmachinelearning/webnn/issues/211>
     *   Status: Discuss the required algorithm updates, work out a plan with contributors.
  *   Support for int8 quantized models

     *    issue: webmachinelearning/webnn#128<https://github.com/webmachinelearning/webnn/issues/128>
     *   Status: Discuss the two design alternatives: quantized ops as a new device type vs. support for all device types. Can we commit this to CR?

<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-09-22-wg-agenda.md#%E2%84%B9%EF%B8%8F-webgpu-working-group-review-request-and-webnn-webgpu-interop>ℹ️ WebGPU Working Group review request and WebNN-WebGPU interop
Discuss WG's response to the WebGPU review request, focus on WebNN-WebGPU interop requirements and issues.

  *   Review request https://lists.w3.org/Archives/Public/public-webmachinelearning-wg/2022Jul/0000.html


  *   11 August 2022 discussion https://www.w3.org/2022/08/11-webmachinelearning-minutes.html#t08


  *    related issue: webmachinelearning/webnn#264<https://github.com/webmachinelearning/webnn/issues/264>

<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-09-22-wg-agenda.md#%E2%84%B9%EF%B8%8F-prs-in-review>ℹ️ PRs in review

  *   Define the data type of the padding, strides and dilations

     *    issue: webmachinelearning/webnn#269<https://github.com/webmachinelearning/webnn/issues/269>
     *    PR: webmachinelearning/webnn#294<https://github.com/webmachinelearning/webnn/pull/294>
  *   Reshape doesn't support full range of operand dimension size

     *    issue: webmachinelearning/webnn#289<https://github.com/webmachinelearning/webnn/issues/289>
     *    PR: webmachinelearning/webnn#291<https://github.com/webmachinelearning/webnn/pull/291>

<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-09-22-wg-agenda.md#%E2%84%B9%EF%B8%8F-proposed-new-features>ℹ️ Proposed new features

  *   Need for type casting?

     *    issue: webmachinelearning/webnn#284<https://github.com/webmachinelearning/webnn/issues/284>
  *   Softmax should only support input of floating-point types

     *    issue: webmachinelearning/webnn#283<https://github.com/webmachinelearning/webnn/issues/283>

Revisit proposed new features discussed earlier:

  *   Should MLBufferView + MLOperandDescriptor be strongly typed

     *    proposed CR issue: webmachinelearning/webnn#275<https://github.com/webmachinelearning/webnn/issues/275>
  *   Support coordinate transformation modes for Resample2d

     *    proposed CR issue: webmachinelearning/webnn#270<https://github.com/webmachinelearning/webnn/issues/270>
  *   l2Pool2d algorithm clarifications

     *    issue: webmachinelearning/webnn#278<https://github.com/webmachinelearning/webnn/issues/278>

<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-09-22-wg-agenda.md#%E2%84%B9%EF%B8%8F-webml-wg-charter-2023-2025-early-heads-up>ℹ️ WebML WG Charter 2023-2025 early heads-up
WebML WG Charter 2023-2025 brainstorming discussion. Start solicit use cases and model requirements for WebNN "V2". WG rechartering process to formally kick off early 2023. New technical proposals to be incubated in the CG prior to the WG adoption.

  *   WG Charter: https://www.w3.org/2021/04/web-machine-learning-charter.html

  *   CG Charter: https://webmachinelearning.github.io/charter/