onnxruntime/js/react_native
Ashrit Shetty 4b5b5f7101
Update win-ort-main to tip main 250123 (#23473)
### Description
This PR is to update the win-ort-main branch to the tip main branch as
of 2025-01-23.

### PR List
ddf0d377a7 [QNN EP] Add LoggingManager::HasDefaultLogger() to provider
bridge API (#23467)
05fbbdf91f [QNN EP] Make QNN EP a shared library (#23120)
1336566d7f Add custom vcpkg ports (#23456)
2e1173c411 Update the compile flags for vcpkg packages (#23455)
1f628a9858 [Mobile] Add BrowserStack Android MAUI Test (#23383)
009cae0ec8 [js/webgpu] Optimize ConvTranspose (Continue) (#23429)
04a4a694cb Use onnx_protobuf.h to suppress some GCC warnings (#23453)
2e3b62b4b0 Suppress some strict-aliasing related warnings in WebGPU EP
(#23454)
b708f9b1dc Bump ruff from 0.9.1 to 0.9.2 (#23427)
c0afc66b2a [WebNN] Remove workarounds for TFLite backend (#23406)
8a821ff7f9 Bump vite from 6.0.7 to 6.0.11 in
/js/web/test/e2e/exports/testcases/vite-default (#23446)
220c1a203e Make ORT and Dawn use the same protobuf/abseil source code
(#23447)
b7b5792147 Change MacOS-13 to ubuntu on for
android-java-api-aar-test.yml. (#23444)
19d0d2a30f WIP: Dp4MatMulNBits accuracy level 4 matmul for WebGPU EP
(#23365)
95b8effbc4 [QNN EP]: Clean up QNN logging resources if an error occurs
during initialization (#23435)
626134c5b5 Bump clang-format from 19.1.6 to 19.1.7 (#23428)
0cf975301f Fix eigen external deps (#23439)
f9440aedce Moving RN_CI Android Testing to Linux (#23422)
1aa5902ff4 [QNN EP] workaround for QNN validation bug for Tanh with
uint16 quantized output (#23432)
7f5582a0e2 Seperate RN andriod and IOS into 2 separated Stages. (#23400)
73deac2e7f Implement some missing element wise Add/Sub/Mul/Div/Neg
operations for CPU and CUDA EPs (#23090)
949fe42af4 Upgrade Java version from react-native/android to Java 17
(#23066)
0892c23463 Update Qnn SDK default version to 2.30 (#23411)
94c099bcec Fix type cast build error (#23423)
d633e571d1 [WebNN EP] Fix AddInitializersToSkip issues (#23354)
e988ef00e2 [QNN EP] Fix regression for MatMul with two quantized/dynamic
uint16 inputs (#23419)
7538795f6b Update onnxruntime binary size checks ci pipeline's docker
image (#23405)
6c5ea41cad Revert "[QNN EP] Clean up correctly from a partial setup
(#23320)" (#23420)
e866804bbe Enable comprehension simplification in ruff rules (#23414)
0a5f1f392c bugfix: string_view of invalid memory (#23417)
4cc38e0277 fix crash when first input of BatchNormalization is 1-D
(#23387)
033441487f Target py310 and modernize codebase with ruff (#23401)
87341ac010 [QNN EP] Fix segfault when unregistering HTP shared memory
handles (#23402)

### Motivation and Context
This update includes the change to make QNN-EP a shared library.

---------

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: Adrian Lizarraga <adlizarraga@microsoft.com>
Co-authored-by: Justin Chu <justinchuby@users.noreply.github.com>
Co-authored-by: Yulong Wang <7679871+fs-eire@users.noreply.github.com>
Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com>
Co-authored-by: Changming Sun <chasun@microsoft.com>
Co-authored-by: Peishen Yan <peishen.yan@intel.com>
Co-authored-by: Tianlei Wu <tlwu@microsoft.com>
Co-authored-by: Hector Li <hecli@microsoft.com>
Co-authored-by: Jian Chen <cjian@microsoft.com>
Co-authored-by: Alexis Tsogias <1114095+Zyrin@users.noreply.github.com>
Co-authored-by: junchao-zhao <68935141+junchao-loongson@users.noreply.github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: sushraja-msft <44513542+sushraja-msft@users.noreply.github.com>
Co-authored-by: Wanming Lin <wanming.lin@intel.com>
Co-authored-by: Jiajia Qin <jiajiaqin@microsoft.com>
Co-authored-by: Caroline Zhu <wolfivyaura@gmail.com>
2025-01-23 09:12:03 -08:00
..
android Update win-ort-main to tip main 250123 (#23473) 2025-01-23 09:12:03 -08:00
e2e Update win-ort-main to tip main 250116 (#23398) 2025-01-16 15:20:25 -08:00
ios Update win-ort-main to tip main 250116 (#23398) 2025-01-16 15:20:25 -08:00
lib bumps up version in main from 1.20 -> 1.21 (#22482) 2024-10-17 12:32:35 -07:00
scripts [js] change default formatter for JavaScript/TypeScript from clang-format to Prettier (#21728) 2024-08-14 16:51:22 -07:00
.gitignore
app.plugin.js [js] change default formatter for JavaScript/TypeScript from clang-format to Prettier (#21728) 2024-08-14 16:51:22 -07:00
babel.config.js [js] change default formatter for JavaScript/TypeScript from clang-format to Prettier (#21728) 2024-08-14 16:51:22 -07:00
onnxruntime-react-native.podspec Update win-ort-main to tip main 250116 (#23398) 2025-01-16 15:20:25 -08:00
package.json Update win-ort-main to tip main 250116 (#23398) 2025-01-16 15:20:25 -08:00
README.md [js] enable formatter for more file types (#16888) 2023-07-28 15:46:58 -07:00
test_types_models.readme.md Use full ORT package for onnxruntime-react-native. (#13037) 2022-09-23 07:20:03 +10:00
tsconfig.build.json
tsconfig.json [js] upgrade JS shared dev dependencies (#17831) 2023-10-10 17:44:39 -07:00
tsconfig.scripts.json
unimodule.json [js] enable formatter for more file types (#16888) 2023-07-28 15:46:58 -07:00
yarn.lock Update win-ort-main to tip main 250116 (#23398) 2025-01-16 15:20:25 -08:00

onnxruntime-react-native

ONNX Runtime React Native provides a JavaScript library for running ONNX models in a React Native app.

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 React Native

With ONNX Runtime React Native, React Native developers can score pre-trained ONNX models directly in React Native apps by leveraging ONNX Runtime, so it provides a light-weight inference solution for Android and iOS.

Installation

yarn add onnxruntime-react-native

Usage

import { InferenceSession } from "onnxruntime-react-native";

// load a model
const session: InferenceSession = await InferenceSession.create(modelPath);
// input as InferenceSession.OnnxValueMapType
const result = session.run(input, ['num_detection:0', 'detection_classes:0'])

Refer to ONNX Runtime JavaScript examples for samples and tutorials. The ONNX Runtime React Native library does not currently support the following features:

  • Tensors with unsigned data types, with the exception of uint8 on Android devices
  • Model loading using ArrayBuffer

Operator and type support

ONNX Runtime React Native version 1.13 supports both ONNX and ORT format models, and includes all operators and types.

Previous ONNX Runtime React Native packages use the ONNX Runtime Mobile package, and support operators and types used in popular mobile models. See here for the list of supported operators and types.

License

License information can be found here.