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104 lines
3.7 KiB
Markdown
104 lines
3.7 KiB
Markdown
---
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title: JavaScript
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parent: Get Started
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toc: true
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nav_order: 4
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---
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# Get started with ORT for JavaScript
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{: .no_toc }
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ONNX Runtime JavaScript API is the unified interface used by [ONNX Runtime Node.js binding](https://github.com/microsoft/onnxruntime/tree/master/js/node), [ONNX Runtime Web](https://github.com/microsoft/onnxruntime/tree/master/js/web) and [ONNX Runtime for React Native](https://github.com/microsoft/onnxruntime/tree/master/js/react_native).
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## Contents
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{: .no_toc }
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* TOC placeholder
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{:toc}
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## JavaScript Examples (Install and import)
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### Web ORT (client)
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```bash
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npm install onnxruntime-web
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```
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```javascript
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const ort = require('onnxruntime-web');
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```
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### Node ORT (server)
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```bash
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npm install onnxruntime-node
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```
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```javascript
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const ort = require('onnxruntime-node');
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```
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### React Native ORT
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```bash
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npm install onnxruntime-react-native
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```
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```javascript
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const ort = require('onnxruntime-react-native');
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```
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### JavaScript Usage Example
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```javascript
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// use an async context to call onnxruntime functions.
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async function main() {
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try {
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// create a new session and load the specific model.
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//
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// the model in this example contains a single MatMul node
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// it has 2 inputs: 'a'(float32, 3x4) and 'b'(float32, 4x3)
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// it has 1 output: 'c'(float32, 3x3)
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const session = await ort.InferenceSession.create('./model.onnx');
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// prepare inputs. a tensor need its corresponding TypedArray as data
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const dataA = Float32Array.from([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]);
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const dataB = Float32Array.from([10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120]);
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const tensorA = new ort.Tensor('float32', dataA, [3, 4]);
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const tensorB = new ort.Tensor('float32', dataB, [4, 3]);
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// prepare feeds. use model input names as keys.
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const feeds = { a: tensorA, b: tensorB };
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// feed inputs and run
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const results = await session.run(feeds);
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// read from results
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const dataC = results.c.data;
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document.write(`data of result tensor 'c': ${dataC}`);
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} catch (e) {
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document.write(`failed to inference ONNX model: ${e}.`);
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}
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}
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```
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## Supported Versions
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- ONNX Runtime Node.js binding: Node.js v12.x+ or Electron v5.x+
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- ONNX Runtime Web: mainstream modern browsers on Windows, macOS, Android and iOS.
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- ONNX Runtime for React Native: same as [ORT Mobile](./with-mobile) (Android/iOS)
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## Builds
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Builds are published to **npm** and can be installed using `npm install`
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| Package | Artifact | Description | Supported Platforms |
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|---------|-----------|-------------|---------------------|
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|Node.js binding|[onnxruntime-node](https://www.npmjs.com/package/onnxruntime-node)|CPU (Release)| Windows x64 CPU NAPI_v3, Linux x64 CPU NAPI_v3, MacOS x64 CPU NAPI_v3|
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|Web|[onnxruntime-web](https://www.npmjs.com/package/onnxruntime-web)|CPU and GPU|Browsers (wasm, webgl), Node.js (wasm)|
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|React Native|[onnxruntime-react-native](https://www.npmjs.com/package/onnxruntime-react-native)|CPU|Android, iOS|
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For Node.js binding, to use on platforms without pre-built binaries, you can [build Node.js binding from source](../build/inferencing.md#apis-and-language-bindings) and consume using `npm install <onnxruntime_repo_root>/js/node/`.
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## API Reference
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See Typescript declarations for [Inference Session](https://github.com/microsoft/onnxruntime/blob/master/js/common/lib/inference-session.ts), [Tensor](https://github.com/microsoft/onnxruntime/blob/master/js/common/lib/tensor.ts) and [Environment Flags](https://github.com/microsoft/onnxruntime/blob/master/js/common/lib/env.ts) for reference.
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See also [ONNX Runtime JavaScript examples](https://github.com/microsoft/onnxruntime-inference-examples/tree/main/js).
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