WebML WG Teleconference – 22 August 2024 - 14:00-15:00 UTC

Latest version: https://github.com/webmachinelearning/meetings/blob/main/telcons/2024-08-22-wg-agenda.md


WebML WG Teleconference – 22 August 2024 - 14:00-15:00 UTC
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2024-08-22-wg-agenda.md#webml-wg-teleconference--22-august-2024---1400-1500-utc>
See the timezone table ...

Logistics
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2024-08-22-wg-agenda.md#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/2023Jun/0000.html

  *   Minutes: https://www.w3.org/2024/08/22-webmachinelearning-minutes.html


Agenda
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2024-08-22-wg-agenda.md#agenda>
📢 Last Call: TPAC 2024 registration and WebML WG F2F agenda
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2024-08-22-wg-agenda.md#-last-call-tpac-2024-registration-and-webml-wg-f2f-agenda>


W3C TPAC 2024 takes place in Anaheim, CA, USA at the Hilton Anaheim on 23–27 September 2024. The WebML WG will meet F2F on Monday, 23 September 2024, 09:00–18:00 PDT.


Important

  *   Please complete the registration form: https://www.w3.org/2024/09/TPAC/#registration

     *   For remote participation, please choose the "I will attend remotely" option.
     *   Note on fee waivers: https://www.w3.org/2024/09/TPAC/registration.html#waiver

  *   Review the in development F2F agenda and provide your suggestions: #25<https://github.com/webmachinelearning/meetings/issues/25>

ℹ️ Device selection abstractions
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2024-08-22-wg-agenda.md#%E2%84%B9%EF%B8%8F-device-selection-abstractions>


📌 We agreed to evolve MLContextOptions and other API controls for device selection informed by further implementation experience and new use cases from the wider web community.

  *   Discuss WebKit feedback for MLContextOptions.deviceType

     *   ⨀ webmachinelearning/webnn#749<https://github.com/webmachinelearning/webnn/issues/749>
  *   References:

     *   Current device selection mechanism: device selection<https://www.w3.org/TR/webnn/#programming-model-device-selection>, MLContextOptions<https://www.w3.org/TR/webnn/#dictdef-mlcontextoptions>
     *   🏷️ All device selection<https://github.com/webmachinelearning/webnn/labels/device%20selection> issues

ℹ️ MLBuffer
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2024-08-22-wg-agenda.md#%E2%84%B9%EF%B8%8F-mlbuffer>


📌 A placeholder for discussion on active MLBuffer topics as appropriate.

  *   ⨀ webmachinelearning/webnn#542<https://github.com/webmachinelearning/webnn/issues/542>
  *   ⨀ webmachinelearning/webnn#697<https://github.com/webmachinelearning/webnn/issues/697>
  *   🏷️ All webgpu interop<https://github.com/webmachinelearning/webnn/labels/webgpu%20interop> issues

ℹ️ Open issues and PRs
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2024-08-22-wg-agenda.md#%E2%84%B9%EF%B8%8F-open-issues-and-prs>


We'll discuss new issues, debrief the group on merged PRs and review open PRs since our last meeting:

  *   ⨀ All open issues<https://github.com/webmachinelearning/webnn/issues>
  *   ⛙ All open pull requests<https://github.com/webmachinelearning/webnn/pulls>
  *   ⛙ Recently merged PRs<https://github.com/webmachinelearning/webnn/pulls?q=is%3Apr+is%3Amerged>


Priority is given to issues and PRs proposed for discussion in the following issue:

  *   🆕 #27<https://github.com/webmachinelearning/meetings/issues/27>


Time permitting, we'll pick from the following list of issues that have received your attention recently:

🏷️ operator specific<https://github.com/webmachinelearning/webnn/labels/operator%20specific>
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2024-08-22-wg-agenda.md#%EF%B8%8F-operator-specific>

  *   How to define the algorithm of L2_Pool2d?

     *   ⨀ webmachinelearning/webnn#278<https://github.com/webmachinelearning/webnn/issues/278>
     *   ☰ Discuss any changes required to standard L2 pooling and L2 norm formulas, address TFLite backend issue with decomp?
  *   Need clarify the usage of axes=[0,1] for resample2d

     *   ⨀ webmachinelearning/webnn#624<https://github.com/webmachinelearning/webnn/issues/624>
     *   ☰ No use cases for axes [0,1], revert and start with the intersection? Discuss implicit vs. explicit passing.
  *   Consider removing lstm and gru operators

     *   ⨀ webmachinelearning/webnn#689<https://github.com/webmachinelearning/webnn/issues/689>
     *   ☰ Tests landed: check backend consistency & re-evaluate.
  *   Consider adding int64/uint64 data type support for some reduce operators

     *   ⨀ webmachinelearning/webnn#694<https://github.com/webmachinelearning/webnn/issues/694>
     *   ⛙ webmachinelearning/webnn#695<https://github.com/webmachinelearning/webnn/pull/695>
     *   ☰ Review PR & discuss any blockers.

🏷️ feature request<https://github.com/webmachinelearning/webnn/labels/feature%20request>
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2024-08-22-wg-agenda.md#%EF%B8%8F-feature-request>

  *   Support for LocalResponseNormalization (LRN) operation

     *   ⨀ webmachinelearning/webnn#228<https://github.com/webmachinelearning/webnn/issues/228>
     *   ☰ Discuss prototyping findings.
  *   WebNN should support int8 quantized models

     *   ⨀ webmachinelearning/webnn#128<https://github.com/webmachinelearning/webnn/issues/128>
     *   ☰ Discuss backend differences for proposed new quant ops.

🏷️ interop<https://github.com/webmachinelearning/webnn/labels/interop>
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2024-08-22-wg-agenda.md#%EF%B8%8F-inteop>

  *   Open Do we need an MLConstantOperand

     *   ⨀ webmachinelearning/webnn#668<https://github.com/webmachinelearning/webnn/issues/668>
     *   ⛙ webmachinelearning/webnn#747<https://github.com/webmachinelearning/webnn/pull/747>
     *   ☰ Review PR.
  *   Limited support for pad on Core ML backend

     *   ⨀ webmachinelearning/webnn#739<https://github.com/webmachinelearning/webnn/issues/739>
     *   ☰ Discuss Core ML backend constraints & address questions.