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Yulong Wang 45ff957973
1.17.3 cherry-picks for ORT Web changes (#19926) 
### Description
This PR is a preview of cherry-picks for ort-web to `rel-1.17.3` based
on `rel-1.17.2`.

<details>

<summary>Changes of ort-web to cherry-pick</summary>

The following commits are from main branch.

`o` stands for pick, and `x` stands for skip.
```
o   2e0a388c36 [js/webgpu] Add HardSigmoid support (#19215)
o   d226e40856 [js/webgpu] set query type in onRunStart (#19202)
o   61610ff986 [js/webgpu] Add FusedConv clip test case (#18900)
o   a33b5bd1fa [JS/WebGPU] Added Uniforms to SkipLayerNorm. (#18788)
o   591f90c0b9 [js/webgpu] Fix issue of timestamp query (#19258)
o   7252c6e747 [WebNN EP] Support WebNN async API with Asyncify (#19145)
o   5b06505073 [js/webgpu] Fix Tanh explosion (#19201)
o   656ca66186 [js/webgpu] Support uniforms for conv, conv transpose, conv grouped (#18753)
o   a3f0e2422b [js/webgpu] Support f16 uniform (#19098)
o   9e69606360 fix f16 for attention, enable slice and flatten for more types (#19262)
o   624b4e2063 [js/webgpu] Remove enableShapesUniforms (#19279)
o   90883a366a [js/webgpu] Add hardSigmoid activation for fusedConv (#19233)
o   85cef0af8c [js/webgpu] Support capture and replay for jsep (#18989)
o   d73131cf0f [js/webgpu] Use DataType as uniform cpu type (#19281)
o   dd1f6ccc45 [js/webgpu] resolve codescan alert (#19343)
o   3a2ab1963a [js/webgpu] Refactor createTensorShapeVariables (#18883)
o   efc17e79de [js/webgpu] Fix the undefined push error (#19366)
 x  50806a7dd5 [js/web] support external data in npm test (#19377)
o   ccbe264a39 [js/webgpu] Add LeakyRelu activation for fusedConv (#19369)
o   5ff27ef02a [js/webgpu] support customop FastGelu (#19392)
 x  03be65e064 [js/web] fix types exports in package.json (#19458)
o   06269a3952 [js/webgpu] allow uint8 tensors for webgpu (#19545)
o   dfeda9019c [JS/WebGPU] Add MatMulNBits (#19446)
o   1b48054e1b [js/webgpu] Create Split indices helpers by rank, not by shape (#19554)
o   3fe2c137ee [js] small fix to workaround formatter (#19400)
 x  70567a4b3a [js/web] use ApiTensor insteadof onnxjs Tensor in TensorResultValidator (#19358)
o   6e04e36e3f [js/common] upgrade tsc in common from 4.9.5 to 5.2.2 (#19317)
o   58f4921686 [js] changes to allow Float16Array if any polyfill is available (#19305)
o   57d6819212 [js/web] Fix fused-conv is not included in npm test (#19581)
o   ebd220b073 Misspelling in README.md (#19433)
o   38c3432393 Bump ip from 1.1.8 to 1.1.9 in /js/react_native (#19582)
o   fe82fccf1a [js/webgpu] Fix Conv2DTransposeMatMul f16 compilation failure (#19596)
o   76a2a487a1 Bump ip from 1.1.8 to 1.1.9 in /js/react_native/e2e (#19583)
o   29b1106033 [node] Switch to setImmediate to avoid starving the Node.js event loop (#19610)
o   ae3d73c981 [JS/WebGPU] Fix Split and Where to handle corner cases. (#19613)
o   aec2389ad0 [js/webgpu] allows a ProgramInfo's RunData to use zero sized output (#19614)
o   bb43a0f133 [js/webgpu] minor fixes to make tinyllama work (#19564)
o   0edb035808 [js/web] fix suite test list for zero sized tensor (#19638)
o   3cb81cdde2 [js/common] move 'env.wasm.trace' to 'env.trace' (#19617)
o   e30618d055 [js/webgpu] use Headless for webgpu test by default (#19702)
o   f06164ef8b [js/web] transfer input buffer back to caller thread (#19677)
 x  a788514027 [js/web] dump debug logs for karma for diagnose purpose (#19785)
o   24b72d2613 [JS/WebGPU] Preserve zero size input tensor dims. (#19737)
o   4538d31a8b [js/webgpu] expose a few properties in WebGPU API (#19857)
o   53de2d8cb0 [js/webgpu] Enable GroupedConvVectorize path (#19791)
o   ed250b88c3 [JS/WebGPU] Optimize MatMulNBits (#19852)
 x  e771a763c3 [js/test] align web test runner flags with ort.env (#19790)
o   79e50aeef3 [js/web] rewrite backend resolve to allow multiple EPs (#19735)
o   acb0df2280 Fix #19931 broken Get Started link of "ONNX Runtime JavaScript API" page (#19932)
o   b29849a287 [js/common] fix typedoc warnings (#19933)
o   afdab62f53 Bump follow-redirects from 1.15.4 to 1.15.6 in /js/web (#19949)
o   28ad6c3955 Bump follow-redirects from 1.15.4 to 1.15.6 in /js/node (#19951)
o   7e0d424934 accumulate in fp32 for Reduce* (#19868)
o   4c6a6a37f7 [js/webgpu] Fix NAN caused by un-initialized buffer in instance-norm (#19387)
o   01c7aaf6aa [js/webgpu] allow setting env.webgpu.adapter (#19940)
o   c45cff60cf [js/webgpu] fix maxpool / fp16 (#19981)
```

</details>

<details>
<summary>Cherry-pick commandlines</summary>

```sh
git cherry-pick 2e0a388c36
git cherry-pick d226e40856
git cherry-pick 61610ff986
git cherry-pick a33b5bd1fa
git cherry-pick 591f90c0b9
git cherry-pick 7252c6e747
git cherry-pick 5b06505073
git cherry-pick 656ca66186
git cherry-pick a3f0e2422b
git cherry-pick 9e69606360
git cherry-pick 624b4e2063
git cherry-pick 90883a366a
git cherry-pick 85cef0af8c  #<<<<< Note: conflicts
git cherry-pick d73131cf0f
git cherry-pick dd1f6ccc45
git cherry-pick 3a2ab1963a
git cherry-pick efc17e79de
git cherry-pick ccbe264a39
git cherry-pick 5ff27ef02a
git cherry-pick 06269a3952
git cherry-pick dfeda9019c
git cherry-pick 1b48054e1b
git cherry-pick 3fe2c137ee
git cherry-pick 6e04e36e3f
git cherry-pick 58f4921686
git cherry-pick 57d6819212
git cherry-pick ebd220b073
git cherry-pick 38c3432393
git cherry-pick fe82fccf1a
git cherry-pick 76a2a487a1
git cherry-pick 29b1106033
git cherry-pick ae3d73c981
git cherry-pick aec2389ad0
git cherry-pick bb43a0f133
git cherry-pick 0edb035808
git cherry-pick 3cb81cdde2
git cherry-pick e30618d055
git cherry-pick f06164ef8b
git cherry-pick 24b72d2613
git cherry-pick 4538d31a8b
git cherry-pick 53de2d8cb0
git cherry-pick ed250b88c3
git cherry-pick 79e50aeef3
git cherry-pick acb0df2280
git cherry-pick b29849a287
git cherry-pick afdab62f53
git cherry-pick 28ad6c3955
git cherry-pick 7e0d424934
git cherry-pick 4c6a6a37f7
git cherry-pick 01c7aaf6aa
git cherry-pick c45cff60cf
```
</details>

<details>
<summary>Cherry-pick conflicts</summary>

- 85cef0af8c #18989
this change is for enabling graph capture feature for JSEP, and it is
done after ROCM EP enabled graph capture feature. However, the ROCM EP
graph capture feature is not cherry-picked in rel-1.17.2.
</details>

---------

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: Jiajia Qin <jiajia.qin@intel.com>
Co-authored-by: Xu Xing <xing.xu@intel.com>
Co-authored-by: satyajandhyala <satya.k.jandhyala@gmail.com>
Co-authored-by: Yang Gu <yang.gu@intel.com>
Co-authored-by: Wanming Lin <wanming.lin@intel.com>
Co-authored-by: Jiajie Hu <jiajie.hu@intel.com>
Co-authored-by: Guenther Schmuelling <guschmue@microsoft.com>
Co-authored-by: Matttttt <18152455+martholomew@users.noreply.github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Segev Finer <segev208@gmail.com>
Co-authored-by: Belem Zhang <belem.zhang@intel.com>
2024-03-29 13:13:39 -07:00
..
docs 1.17.3 cherry-picks for ORT Web changes (#19926) 2024-03-29 13:13:39 -07:00
lib 1.17.3 cherry-picks for ORT Web changes (#19926) 2024-03-29 13:13:39 -07:00
script 1.17.3 cherry-picks for ORT Web changes (#19926) 2024-03-29 13:13:39 -07:00
test 1.17.3 cherry-picks for ORT Web changes (#19926) 2024-03-29 13:13:39 -07:00
.gitignore
.npmignore [js/web] fix a few package consuming problems (#18109) 2023-10-30 08:11:43 -07:00
karma.conf.js 1.17.3 cherry-picks for ORT Web changes (#19926) 2024-03-29 13:13:39 -07:00
package-lock.json 1.17.3 cherry-picks for ORT Web changes (#19926) 2024-03-29 13:13:39 -07:00
package.json Update version number to 1.17.2 (#19701) 2024-03-01 13:51:00 -08:00
README.md 1.17.3 cherry-picks for ORT Web changes (#19926) 2024-03-29 13:13:39 -07:00
tsconfig.json [js/web] fix ESLint by excluding generated .js from tsconfig.json (#18634) 2023-11-30 09:50:47 -08:00
types.d.ts Add "glue" between training WASM artifacts and training web (#17474) 2023-10-12 11:16:56 -07:00

README.md

ONNX Runtime Web

ONNX Runtime Web is a Javascript library for running ONNX models on browsers and on Node.js.

ONNX Runtime Web has adopted WebAssembly and WebGL technologies for providing an optimized ONNX model inference runtime for both CPUs and GPUs.

Why ONNX models

The Open Neural Network Exchange (ONNX) is an open standard for representing machine learning models. The biggest advantage of ONNX is that it allows interoperability across different open source AI frameworks, which itself offers more flexibility for AI frameworks adoption.

Why ONNX Runtime Web

With ONNX Runtime Web, web developers can score models directly on browsers with various benefits including reducing server-client communication and protecting user privacy, as well as offering install-free and cross-platform in-browser ML experience.

ONNX Runtime Web can run on both CPU and GPU. On CPU side, WebAssembly is adopted to execute the model at near-native speed. ONNX Runtime Web compiles the native ONNX Runtime CPU engine into WebAssembly backend by using Emscripten, so it supports most functionalities native ONNX Runtime offers, including full ONNX operator coverage, multi-threading, ONNX Runtime Quantization as well as ONNX Runtime Mobile. For performance acceleration with GPUs, ONNX Runtime Web leverages WebGL, a popular standard for accessing GPU capabilities. We are keeping improving op coverage and optimizing performance in WebGL backend.

See Compatibility and Operators Supported for a list of platforms and operators ONNX Runtime Web currently supports.

Usage

Refer to ONNX Runtime JavaScript examples for samples and tutorials.

Documents

Development

Refer to the following links for development information:

Compatibility

OS/Browser Chrome Edge Safari Electron Node.js
Windows 10 wasm, webgl wasm, webgl - wasm, webgl wasm
macOS wasm, webgl wasm, webgl wasm, webgl wasm, webgl wasm
Ubuntu LTS 18.04 wasm, webgl wasm, webgl - wasm, webgl wasm
iOS wasm, webgl wasm, webgl wasm, webgl - -
Android wasm, webgl wasm, webgl - - -

Operators

WebAssembly backend

ONNX Runtime Web currently support all operators in ai.onnx and ai.onnx.ml.

WebGL backend

ONNX Runtime Web currently supports a subset of operators in ai.onnx operator set. See webgl-operators.md for a complete, detailed list of which ONNX operators are supported by WebGL backend.

WebGPU backend

WebGPU backend is still an experimental feature. See webgpu-operators.md for a detailed list of which ONNX operators are supported by WebGPU backend.

License

License information can be found here.