See the timezone table ...
San Francisco (U.S.A. - California) | Thu, 11 May 2022 | 07:00 | UTC-7 hours |
Boston (U.S.A. - Massachusetts) | Thu, 11 May 2022 | 10:00 | UTC-4 hours |
London (United Kingdom - England) | Thu, 11 May 2022 | 15:00 | UTC+1 hours |
Berlin (Germany) | Thu, 11 May 2022 | 16:00 | UTC+2 hours |
Helsinki (Finland) | Thu, 11 May 2022 | 17:00 | UTC+3 hours |
Shanghai (China) | Thu, 11 May 2022 | 22:00 | UTC+8 hours |
Tokyo (Japan) | Thu, 11 May 2022 | 23:00 | UTC+9 hours |
Corresponding UTC (GMT) | Thu, 11 May 2022 | 14:00 UTC |
Other locations: https://www.timeanddate.com/worldclock/fixedtime.html?iso=20230511T14
- Chair: Anssi
- Scribe: ? (see howto, 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/2023/05/11-webmachinelearning-minutes.html
-
The constant() method steps
- meta issue: webmachinelearning/webnn#210 (comment)
- PR: webmachinelearning/webnn#365
-
Sync async algorithms
-
The builder.input() method steps
- meta issue: webmachinelearning/webnn#210 (comment)
- PR: webmachinelearning/webnn#364
-
Review the rest of the standard conventions PRs (all ready for review):
- meta issue: webmachinelearning/webnn#210 (comment)
- open PRs: https://github.com/webmachinelearning/webnn/pulls
-
float16 support (discuss prototype findings to inform v2 feature work)
- issue: webmachinelearning/webnn#373
- prototype PR: Honry/onnxruntime#1
- TC39 proposal: http://tc39.es/proposal-float16array/
-
Subclass MLGraph based on the context that creates it
- issue: webmachinelearning/webnn#344
-
Error handling of MLNamedArrayBufferViews transfer algorithm
- issue: webmachinelearning/webnn#351
-
Support depth_multiplier > 1 for a depthwise conv2d op
- issue: webmachinelearning/webnn#353
-
Clarify interpolation algorithm for resample2d
- issue: webmachinelearning/webnn#358
- related issue: webmachinelearning/webnn#270
Continue discuss transformers and related requirements and gaps. Test our improved contribution guidelines with these new ops: explore key use cases, sample models, cross-framework support, cross-platform implementability.
Status: The WG decided to start explore support for transformers in WebNN.
Next step: Identify use cases. Contributions welcome via issue 375.
- issue: webmachinelearning/webnn#375
- Guidelines for adding new ops: https://github.com/webmachinelearning/webnn/blob/main/CONTRIBUTING.md#proposing-and-adding-a-new-operation
- Minutes from the kick off: https://www.w3.org/2023/04/27-webmachinelearning-minutes.html#t11