onnxruntime/js/web
Rui Ren 6ccaeddefa
ORT 1.14.0 release -- cherry pick round3 (#14617)
### Description
<!-- Describe your changes. -->

**This is the Final cherry-pick, no more PR will be accepted**

Third round cherry pick, total 10 PRs, as below. Please check here for
[Here](https://github.com/microsoft/onnxruntime/issues?q=label%3Arelease%3A1.14+sort%3Aupdated-asc+is%3Aclosed+label%3Atriage%3Aapproved)
for the total list.

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Date | PR | # | Commit # | Short #
-- | -- | -- | -- | --
1 | remove 'module' field from package.json | 14532 |
cfb6e528c8 | cfb6e52
2 | Fix CI failure: temporarily disable real model tests from onnx repo
| 14606 | cf8bad7f19 | cf8bad7
3 | Stable Diffusion CUDA optimizations Part 2 | 14597 |
742658d171 | 742658d
4 | reduce cuda library binary size | 14555 |
8de885fdb1 | 8de885f
5 | Remove Identical Children Consolidation from default transformer
uitil. | 14602 | 585f43e31d | 585f43e
6 | Revert mimalloc from v2.0.9 to v2.0.3 | 14603 |
b6bec54341 | b6bec54
7 | Adding RunOptions synchronization behaviour to C/C++ API | 14088 |
e9ab56fa64 | e9ab56f
8 | Move TRT include_directories to outside scope | 14622 |
0a6b22018f | 0a6b220
9 | Remove torch package from requirements.txt of stable diffusion
models | 14630 | cfda876a3f | cfda876
10 | Test and fix optimizers LayerNormFusion, BiasSoftmaxFusion,
Transpose for opset 18 | 14542 |
30ec8b038f | 30ec8b0



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### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
**Last** round cherry-pick for ORT 1.14.0 release.

---------

Signed-off-by: Kevin Chen <kevinch@nvidia.com>
Signed-off-by: xadupre <xadupre@microsoft.com>
Co-authored-by: Yulong Wang <7679871+fs-eire@users.noreply.github.com>
Co-authored-by: Chun-Wei Chen <jacky82226@gmail.com>
Co-authored-by: Tianlei Wu <tlwu@microsoft.com>
Co-authored-by: Yufeng Li <liyufeng1987@gmail.com>
Co-authored-by: Jian Chen <cjian@microsoft.com>
Co-authored-by: Scott McKay <skottmckay@gmail.com>
Co-authored-by: RandySheriffH <48490400+RandySheriffH@users.noreply.github.com>
Co-authored-by: Randy Shuai <rashuai@microsoft.com>
Co-authored-by: Maximilian Müller <44298237+gedoensmax@users.noreply.github.com>
Co-authored-by: Chi Lo <chi.lo@microsoft.com>
Co-authored-by: Kevin Chen <45886021+kevinch-nv@users.noreply.github.com>
Co-authored-by: Xavier Dupré <xadupre@users.noreply.github.com>
2023-02-09 10:08:02 -08:00
..
docs to work with onnx 1.13 rc, implement ver 18 reduce and optioanl ops, … (#13765) 2023-01-09 10:26:16 -08:00
lib [web] utility functions for tensor<->image conversion in ORT web (#13603) 2023-01-12 09:05:18 -08:00
script [js/web] add 'xnnpack' to EP list (#12723) 2022-10-03 10:38:45 -07:00
test [js/web] add 'xnnpack' to EP list (#12723) 2022-10-03 10:38:45 -07:00
.gitignore prepare test folder from GitHub (#12220) 2022-07-20 22:01:08 -07:00
.npmignore [js/web] optimize bundle file size (#9817) 2021-11-22 13:56:55 -08:00
karma.conf.js [js/web] use windowed Chrome for perf mode (#12157) 2022-07-18 14:04:27 -07:00
package-lock.json Bump electron from 15.5.5 to 18.3.7 in /js/web (#13617) 2023-01-18 14:58:09 -08:00
package.json ORT 1.14.0 release -- cherry pick round3 (#14617) 2023-02-09 10:08:02 -08:00
README.md replace 'master' branch ref to 'main' for onnx repo (#12678) 2022-08-30 13:41:42 -07:00
tsconfig.json [web] utility functions for tensor<->image conversion in ORT web (#13603) 2023-01-12 09:05:18 -08:00
webpack.config.js [js/web] do not use nodejs type 'Buffer' in web (#9839) 2021-11-24 14:14:42 -08:00

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 complies 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

Developement

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 operators.md for a complete, detailed list of which ONNX operators are supported by WebGL backend.

License

License information can be found here.