WebML CG Teleconference – 9 March 2022 - 05:00-06:00 UTC+0

Latest version: https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-03-09-cg-agenda.md


WebML CG Teleconference – 9 March 2022 - 05:00-06:00 UTC+0
See the timezone table ...
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-03-09-cg-agenda.md#logistics>Logistics

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

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

  *   Call-in details: https://lists.w3.org/Archives/Member/internal-webmachinelearning/2020Apr/0000.html

  *   Minutes: https://www.w3.org/2022/03/09-webmachinelearning-minutes.html


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<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-03-09-cg-agenda.md#agenda>Agenda
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-03-09-cg-agenda.md#-model-loader-api>🔄 Model Loader API
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-03-09-cg-agenda.md#%E2%84%B9%EF%B8%8F-versioning>ℹ️ Versioning

  *   How to version the API? (supported ops and formats)

<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-03-09-cg-agenda.md#%E2%84%B9%EF%B8%8F-streaming-inputs>ℹ️ Streaming inputs

  *   Dedicated interface for streaming inputs (e.g. buffered inputs for video, audio)?

<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-03-09-cg-agenda.md#%E2%84%B9%EF%B8%8F-model-format>ℹ️ Model format

  *   Prototype vs standard format requirements
  *   "The Model Loader API needs a standard format supported across browsers and devices for broad interoperability." condition for standards adoption into WebML WG

<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-03-09-cg-agenda.md#%E2%84%B9%EF%B8%8F-support-for-non-ietf-754-float-point-types>ℹ️ Support for non-IETF 754 float point types

  *    issue: Open question: support for non-IETF 754 float point types #23 https://github.com/webmachinelearning/model-loader/issues/23


Some accelerators use non-standard float point types (e.g. bfloat16 and TF32) for performance, memory usage optimization. Discuss Model Loader experimentation with these types, open questions:

  *   Could WebNN and Model Loader API use a common approach for these types?
  *   How to represent, manipulate these types in JavaScript? Or auto-convert at runtime with some heuristic?
  *   How to have the two specs complement each other?
  *   WebNN provides general purpose feature that runs everywhere (write once, run everywhere), Model Loader optionally makes use of accelerator specific features, and could run extremely efficiently based on the model?
  *   How much information would this give away, privacy risk?

<https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-03-09-cg-agenda.md#%E2%84%B9%EF%B8%8F-references>ℹ️ References

  *   WebML CG Teleconference – 9 Feb 2022 minutes<https://www.w3.org/2022/02/09-webmachinelearning-minutes.html>
  *   WebML CG Teleconference – 12 Jan 2022 minutes<https://www.w3.org/2022/01/12-webmachinelearning-minutes.html>
  *   Model Loader API explainer<https://github.com/webmachinelearning/model-loader/blob/main/explainer.md> and early spec draft<https://webmachinelearning.github.io/model-loader/>
  *   Model Loader API Chromium prototype<https://chromium-review.googlesource.com/c/chromium/src/+/3341136>