onnxruntime/js/react_native
Sumit Agarwal f4f49535a4
[ORT 1.18.2] Cherry Pick Pad Optimizations + Update DML to 1.15.1 (#21670)
### Description
This change cherry-picks 2 Pad fusion optimization:
https://github.com/microsoft/onnxruntime/pull/21640 and
https://github.com/microsoft/onnxruntime/pull/21556.

It also has to cherry-pick 2 extra changes to unblock pipeline and
dependency failure: https://github.com/microsoft/onnxruntime/pull/21300
and https://github.com/microsoft/onnxruntime/pull/21662 (didn't include
test which are part of 1.18.1 payload).

Also uploaded new version of
[onnxruntime_build_dependencies:10.177](https://dev.azure.com/onnxruntime/onnxruntime/_artifacts/feed/onnxruntime/UPack/onnxruntime_build_dependencies/overview/1.0.177)
and updated the same in `download-deps.yml`.

Additionally it also updates DML binary to 1.15.1.



### 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. -->

---------

Co-authored-by: Changming Sun <chasun@microsoft.com>
Co-authored-by: Tianlei Wu <tlwu@microsoft.com>
2024-08-12 07:02:00 -07:00
..
android [js/rn] Support load external data (#20090) 2024-04-05 05:55:03 -07:00
e2e Bump ip from 1.1.8 to 1.1.9 in /js/react_native/e2e (#19583) 2024-02-22 13:58:17 -08:00
ios [js/rn] Add test for validating "executionProvider" options (#16651) 2023-07-12 14:55:47 -07:00
lib [ORT 1.18.2] Cherry Pick Pad Optimizations + Update DML to 1.15.1 (#21670) 2024-08-12 07:02:00 -07:00
scripts [js] update prepack script to use exact version (#17484) 2023-09-13 00:07:16 -07:00
.gitignore
app.plugin.js [REACT NATIVE] Bugfix -> casing Podfile (#18861) 2023-12-19 10:20:46 +10:00
babel.config.js [js] enable formatter for more file types (#16888) 2023-07-28 15:46:58 -07:00
onnxruntime-react-native.podspec
package.json [ORT 1.18.2] Cherry Pick Pad Optimizations + Update DML to 1.15.1 (#21670) 2024-08-12 07:02:00 -07:00
README.md [js] enable formatter for more file types (#16888) 2023-07-28 15:46:58 -07:00
test_types_models.readme.md
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 [ORT 1.18.2] Cherry Pick Pad Optimizations + Update DML to 1.15.1 (#21670) 2024-08-12 07:02:00 -07:00

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.