Add support for operations needed for well-known transformers e.g. Segment Anything, Stable Diffusion, etc.

[wchao1115]

Issue #375.

1. Add the following ops: equal, lesser, greater, greaterOrEqual, lesserOrEqual, not, where, copy, sqrt, erf, expand, gather, layerNormalization, reduceArgMin, reduceArgMax, cast, triangular
2. Remove squeeze
3. Add a constant overload that accepts start, end, step.
4. Add shape method in MLOperand for runtime tensor shape query.
5. Add new data type int64 and uint64 for reduceArgMin and reduceArgMax.

Notes:

• The proposed identity op is named copy to denote explicit action.
• The proposed elementwiseIf is named where to be consistent with PyTorch and ONNX.
• The proposed triangularMatrix is named triangular for brevity.
• squeeze is removed. Framework seeking squeeze, unsqueeze, flatten should just use reshape. See canonical implementations of these ops as reshape in the reshape section.
• Instead of the proposed unification of all normalizations under one new normalization operation, a new layerNormalization op is added. There are enough subtleties in the way affine parameters (e.g. scale, bias) are expected across batchNorm, instanceNorm, and layerNorm that could become ambiguous under the unified op. Additionally, downstream implementations of these normalizations have already been done in various platforms. The unification at the WebNN level could potentially confuse framework developers and affects currently defined platform-specific optimizations.
• The proposed fillSequence op is added as a constant overload due to its nature of resource allocation activity.
• The new sidebar loosens up the crowded MLGraphBuilder interface section for better op discoverability.

Big thanks to @fdwr for the thoughtful and thorough proposal.

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Preview | Diff

[huningxin]

Thanks for the great work!

[BruceDai]

Thanks @wchao1115 !
Here's a nit, PTAL.

[inexorabletash]

Looks like the build isn't clean any more, these issues should be fixed:

https://github.com/webmachinelearning/webnn/actions/runs/6836134208/job/18590708364?pr=478#step:3:885

[BruceDai]

Here's current status for baseline implementation and WPT tests of new adding ops, PTAL, thanks.

Ops	Baseline	WPT tests
equal, lesser, greater, greaterOrEqual, lesserOrEqual, not	√	pr
where	pr	WIP
copy	√	pr
reciprocal	√	pr
sqrt	√	pr
erf
expand	pr	WIP
gather
layerNormalization
reduceArgMin, reduceArgMax
cast
triangular

[wchao1115]

The new MLOperand methods type() and shape() don't have corresponding definitions.

@inexorabletash Fixed.

[wchao1115]

Looks like the build isn't clean any more, these issues should be fixed:

@inexorabletash Fixed.

[huningxin]

Big thanks to @fdwr for the thoughtful and thorough proposal.

+1. I think we should acknowledge Dwayne for his outstanding contribution. @wchao1115 @anssiko

[wchao1115]

+1. I think we should acknowledge Dwayne for his outstanding contribution. @wchao1115 @anssiko

Fixed. 😊

[fdwr]

One functional comment added, plus some typos and wording proposals. Otherwise, given all other matters are deferrable as separate issues, tis looking good to me. Thanks Chai.

Thanks to Dwayne Robinson for his work...

Arigatou 😊.

[fdwr]

Minor things, else LGTM. 😎

[anssiko]

All the discussions in this PR have been resolved, some comments spun into separate non-blocking issues as agreed with the reviewers, and the build is clean. Great work everyone involved!

@wchao1115 @huningxin please take a final look. Given this is a big PR with many micro-commits, I'd like to hear if you'd prefer to squash this. Below is my reasoning and recommendation.

For the earlier big PRs #446 we decided to keep the commit history in the main branch. For this PR here it looks like a squash merge might be preferred instead since there are many micro-commit that fix small issues and typos. GitHub will retain the commit history of this PR if we keep this PR around after the squash merge so references to these commits will continue to work. The only tradeoff I'm aware of is that the local git clones of this repo won't have access to the history of this PR by default. If you agree we want to squash this PR @wchao1115 please update your extensive PR summary in #478 (comment) to reflect the latest so we can reuse it as the squash commit message. This will help future contributors who will look at the history.

Looking forward to merging this soon 🚀

[huningxin]

LGTM, thanks much!