Re: WebML WG Teleconference – 24 August 2023 - 14:00-15:00 UTC

As part of the "WebIDL and Infra standard conventions" section would it be
helpful for me to spend a couple minutes discussing some of the motivations
behind modern spec style, and the "processing model" (i.e. how JS types
pass through Web IDL to become Infra types), etc?




On Thu, Aug 17, 2023 at 4:08 AM Kostiainen, Anssi <
anssi.kostiainen@intel.com> wrote:

> Latest version:
> https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-08-24-wg-agenda.md
>
> WebML WG Teleconference – 24 August 2023 - 14:00-15:00 UTC See the
> timezone table ...
> <https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-08-24-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/2023Jun/0000.html
>    - Minutes:
>    https://www.w3.org/2023/08/24-webmachinelearning-minutes.html
>
>
> <https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-08-24-wg-agenda.md#agenda>
> Agenda
> <https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-08-24-wg-agenda.md#%E2%84%B9%EF%B8%8F-google-chrome-teams-feedback-on-webnn-api>ℹ️
> Google Chrome team's feedback on WebNN API
>
> Vivek and Joshua B have gathered feedback from various Google teams
> interested in WebNN and will share their thoughts with the WG for
> discussion.
>
> <https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-08-24-wg-agenda.md#%E2%84%B9%EF%B8%8F-webnn-v2-review-proposed-new-ops-and-data-types>ℹ️
> WebNN v2: review proposed new ops and data types
>
> Review and discuss the proposed new ops and data types informed by v2
> model targets and recent prototyping efforts.
>
> Proposed models:
>
>    - Text-to-image: Stable Diffusion unet/VAE/text encoder
>    - Image segmentation: Segment Everything decoder
>    - Speech-to-text: Whisper Tiny
>    - Text-to-text? Summarization, translation, code completion
>    demonstrated by Transformers.js?
>
> Proposed new ops:
>
>    - Logical elementwise comparison/selection operations: equal, greater,
>    lesser, logicalNot, elementwiseIf/ternary, greaterOrEqual/lesserOrEqual
>    - More elementwise unary operations: identity, sqrt, erf (Gauss err
>    func), reciprocal
>    - Reshaping operations: squeeze, unsqueeze, flattenTo2d
>    - Data rearrangement operations: expand, gather
>    - Normalization operations: meanVarianceNormalization
>    - Index seeking operations: argMin/argMax
>    - Misc: cast, fillSequence, triangularMatrix, shape
>    - Others?
>
> Proposed new data types: int64, uint64
>
> Details: webmachinelearning/webnn#375 (comment)
> <https://github.com/webmachinelearning/webnn/issues/375#issuecomment-1674224992>
>
> Background material:
>
>    - Transformers.js presentation by Joshua Lochner
>    <https://lists.w3.org/Archives/Public/www-archive/2023Jun/att-0000/Transformers_js.pdf>
>    - Transformer models presentation by Dwayne Robinson
>    <https://lists.w3.org/Archives/Public/www-archive/2023Jun/att-0005/2023-06-29_WebNN_and_Transformers_Progress_W3C.pdf>
>    - Transformer-based models and use cases discussion:
>    webmachinelearning/webnn#375
>    <https://github.com/webmachinelearning/webnn/issues/375>
>    - Proposed v2 ops
>    <https://github.com/webmachinelearning/webnn/issues?q=is%3Aopen+label%3A%22operation+set%22+label%3A%22v2%22> (open
>    new issues for v2 op proposals)
>
>
> <https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-08-24-wg-agenda.md#%E2%84%B9%EF%B8%8F-webidl-and-infra-standard-conventions>ℹ️
> WebIDL and Infra standard conventions
>
> Decide whether we're ready to merge the zk-conventions-integration integration
> branch to main.
>
> These changes align the entire specification with modern specification
> conventions and add stylistic improvements on top that make navigating this
> specification more delightful experience.
>
> The following resources are made available to the group to assist in this
> review task:
>
>    - Preview
>    <https://pr-preview.s3.amazonaws.com/zolkis/webnn/pull/446.html> of
>    zk-conventions-integration PR
>    - Diff <https://pr-preview.s3.amazonaws.com/zolkis/webnn/pull/446.html>
>     between main and zk-conventions-integration PR
>    - Issues addressed and PRs merged to
>    <https://github.com/webmachinelearning/webnn/issues/210#issuecomment-1326361748>
>     zk-conventions-integration (see "🟡 review feedback" annotations)
>    - Commits
>    <https://github.com/webmachinelearning/webnn/compare/main...zk-conventions-integration> ahead
>    of main
>
>
> <https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-08-24-wg-agenda.md#%E2%84%B9%EF%B8%8F-enhancements>ℹ️
> Enhancements
>
>    - split() into sizes not widely supported
>       -  issue: webmachinelearning/webnn#392
>       <https://github.com/webmachinelearning/webnn/issues/392>
>    - Clarify the restriction for minValue and maxValue of MLClampOptions
>       -  issue: webmachinelearning/webnn#396
>       <https://github.com/webmachinelearning/webnn/issues/396>
>
>
>