WebML WG Teleconference – 27 February 2025 - 15:00-16:00 UTC

Latest version: https://github.com/webmachinelearning/meetings/blob/main/telcons/2025-02-27-wg-agenda.md


WebML WG Teleconference – 27 February 2025 - 15:00-16:00 UTC
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2025-02-27-wg-agenda.md#webml-wg-teleconference--27-february-2025---1500-1600-utc>
See the timezone table ...

Logistics
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2025-02-27-wg-agenda.md#logistics>

  *   Chair: Anssi
  *   Scribe: Anssi
  *   IRC: irc://irc.w3.org:6667/#webmachinelearning

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

  *   Zoom joining instructions: https://lists.w3.org/Archives/Member/internal-webmachinelearning/2023Jun/0000.html

  *   Minutes: https://www.w3.org/2025/02/27-webmachinelearning-minutes.html


Agenda
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2025-02-27-wg-agenda.md#agenda>

🧪 Incubations summary
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2025-02-27-wg-agenda.md#-incubations-summary>


A summary of the most recent WebML Community Group meeting will be shared to keep the Working Group abreast of incubations.


  *   WebML CG Teleconference – 26 February 2025 - 00:00-01:00 UTC<https://github.com/webmachinelearning/meetings/blob/main/telcons/2025-02-26-cg-agenda.md>

ℹ️ Query mechanism for supported devices
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2025-02-27-wg-agenda.md#%E2%84%B9%EF%B8%8F-query-mechanism-for-supported-devices>


Discuss, refine and solicit proposals and use cases for the query mechanism for supported devices. Consider implementability, privacy, security implications.


  *   ⨀ webmachinelearning/webnn#815<https://github.com/webmachinelearning/webnn/issues/815>

ℹ️ Operator set Wave 3
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2025-02-27-wg-agenda.md#%E2%84%B9%EF%B8%8F-operator-set-wave-3>


Review draft PR and (many!) issues it closes. Discuss any opens as needed.

PR welcomes contributions to finish algorithm steps in gatherNd/scatterNd, update slice output shape.


  *   ⛙ webmachinelearning/webnn#805<https://github.com/webmachinelearning/webnn/pull/805>


Closes: ⨀ #93<https://github.com/webmachinelearning/webnn/issues/93>, ⨀ #467<https://github.com/webmachinelearning/webnn/issues/467>, ⨀ #772<https://github.com/webmachinelearning/webnn/issues/772>, ⨀ #767<https://github.com/webmachinelearning/webnn/issues/767>, ⨀ #773<https://github.com/webmachinelearning/webnn/issues/773>, ⨀ #779<https://github.com/webmachinelearning/webnn/issues/779>

🏷️ feature request<https://github.com/webmachinelearning/webnn/labels/feature%20request> issues

<https://github.com/webmachinelearning/meetings/blob/main/telcons/2025-02-27-wg-agenda.md#%EF%B8%8F-feature-request-issues>

  *   Rounding operators

     *   ⨀ webmachinelearning/webnn#817<https://github.com/webmachinelearning/webnn/issues/817>
     *   ☰ Discuss known gaps in rounding functions, review the initial proposal.
  *   Remove pool2d MLRoundingType

     *   ⨀ webmachinelearning/webnn#324<https://github.com/webmachinelearning/webnn/issues/324>
     *   ⛙ webmachinelearning/webnn#770<https://github.com/webmachinelearning/webnn/pull/770>
     *   ☰ Discuss remaining PR review comments.

🏷️ bug<https://github.com/webmachinelearning/webnn/labels/bug> issues
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2025-02-27-wg-agenda.md#%EF%B8%8F-bug-issues>

  *   Reject promises for in-progress operations on an MLTensor if it is destroyed
     *   ⨀ follow-up to webmachinelearning/webnn#477<https://github.com/webmachinelearning/webnn/issues/477>
     *   ⛙ webmachinelearning/webnn#799<https://github.com/webmachinelearning/webnn/pull/799>
     *   ☰ Review PR.

🏷️ interop<https://github.com/webmachinelearning/webnn/labels/interop> issues
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2025-02-27-wg-agenda.md#%EF%B8%8F-interop-issues>

  *   Behavior when there are NaNs in argmin/max inputs
     *   ⨀ webmachinelearning/webnn#811<https://github.com/webmachinelearning/webnn/issues/811>
     *   ☰ Discuss how backends handle NaNs in the input and agree on next steps.