WebML WG Teleconference – 25 August 2022 - 14:00-15:00 UTC

Latest version: https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-08-25-wg-agenda.md


WebML WG Teleconference – 25 August 2022 - 14:00-15:00 UTC
San Francisco (U.S.A. - California)     Thu, 25 August 2022     07:00   UTC-7 hours
Boston (U.S.A. - Massachusetts) Thu, 25 August 2022     10:00   UTC-4 hours
London (United Kingdom - England)       Thu, 25 August 2022     15:00   UTC+1 hours
Berlin (Germany)        Thu, 25 August 2022     16:00   UTC+2 hours
Helsinki (Finland)      Thu, 25 August 2022     17:00   UTC+3 hours
Shanghai (China)        Thu, 25 August 2022     22:00   UTC+8 hours
Tokyo (Japan)   Thu, 25 August 2022     23:00   UTC+9 hours
Corresponding UTC (GMT) Thu, 25 August 2022     14:00 UTC

Other locations: https://www.timeanddate.com/worldclock/fixedtime.html?iso=20220825T14


<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-08-25-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/2022/08/25-webmachinelearning-minutes.html


<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-08-25-wg-agenda.md#%E2%84%B9%EF%B8%8F-meeting-logistics-update>ℹ️ Meeting logistics update
Teleconferences: Given good overlap of participants across WG+CG, we plan to repurpose monthly Sydney afternoon CG slots (Wed 04:00-05:00 UTC) for WG+CG topics when there's demand. This slot will be in addition to the normal WG bi-weekly (Thu 14:00-15:00 UTC) and caters specifically to our participants from APAC time zones.
TPAC: The Web Machine Learning Working Group's hybrid TPAC meeting is canceled due to key participants' inability to attend the in-person meeting.
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-08-25-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


  *   Remove the support of negative dimension values

     *    issue: webmachinelearning/webnn#279<https://github.com/webmachinelearning/webnn/issues/279>
     *    PR: webmachinelearning/webnn#281<https://github.com/webmachinelearning/webnn/pull/281>
  *   Support asynchronous context creation

     *    issue: webmachinelearning/webnn#272<https://github.com/webmachinelearning/webnn/issues/272>
     *    PR: webmachinelearning/webnn#274<https://github.com/webmachinelearning/webnn/pull/274>
  *   Define ULP (unit of least precision) tolerances for testing

     *    issue: webmachinelearning/webnn#265<https://github.com/webmachinelearning/webnn/issues/265>
     *    PR: web-platform-tests/wpt#34287<https://github.com/web-platform-tests/wpt/pull/34287>
  *   Support for int8 quantized models

     *    issue: webmachinelearning/webnn#128<https://github.com/webmachinelearning/webnn/issues/128>
  *   Add method steps to operations

     *    issue: webmachinelearning/webnn#210<https://github.com/webmachinelearning/webnn/issues/210>
     *    related: webmachinelearning/webnn#211<https://github.com/webmachinelearning/webnn/issues/211>
  *   Wide review

     *    tracker: webmachinelearning/webnn#239<https://github.com/webmachinelearning/webnn/issues/239>
     *    WG's privacy response: webmachinelearning/webnn#280 (comment)<https://github.com/webmachinelearning/webnn/issues/280#issuecomment-1212860627>

<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-08-25-wg-agenda.md#%E2%84%B9%EF%B8%8F-proposed-new-features>ℹ️ Proposed new features

  *    issue: l2Pool2d algorithm clarifications webmachinelearning/webnn#278<https://github.com/webmachinelearning/webnn/issues/278>

Revisit proposed new features discussed earlier:

  *    issue: Should MLBufferView + MLOperandDescriptor be strongly typed webmachinelearning/webnn#275<https://github.com/webmachinelearning/webnn/issues/275>

  *    issue: Support coordinate transformation modes for Resample2d webmachinelearning/webnn#270<https://github.com/webmachinelearning/webnn/issues/270>

  *    issue: Define the data type of the padding, strides and dilations webmachinelearning/webnn#269<https://github.com/webmachinelearning/webnn/issues/269>