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### Description Add support for using Onnx Runtime with Node ### Motivation and Context Onnx Runtime supports the QNN HTP, but does not support it for Node.js. This adds baseline support for the Onnx Runtime to be used with Node. Note it does not update the node packages that are distributed officially. This simply patches the onnxruntime.dll to allow 'qnn' to be used as an execution provider. Testing was done using the existing onnxruntime-node package. The `onnxruntime.dll` and `onnxruntime_binding.node` were swapped into `node_modules\onnxruntime-node\bin\napi-v3\win32\arm64` with the newly built version, then the various QNN dlls and .so files were placed next to the onnxruntime.dll. Testing was performed on a variety of models and applications, but the easiest test is to modify the [node quickstart example](https://github.com/microsoft/onnxruntime-inference-examples/tree/main/js/quick-start_onnxruntime-node). |
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ONNX Runtime Node.js Binding
ONNX Runtime Node.js binding enables Node.js applications to run ONNX model inference.
Usage
Install the latest stable version:
npm install onnxruntime-node
Refer to ONNX Runtime JavaScript examples for samples and tutorials.
Requirements
ONNXRuntime works on Node.js v16.x+ (recommend v18.x+) or Electron v15.x+ (recommend v28.x+).
The following table lists the supported versions of ONNX Runtime Node.js binding provided with pre-built binaries.
| EPs/Platforms | Windows x64 | Windows arm64 | Linux x64 | Linux arm64 | MacOS x64 | MacOS arm64 |
|---|---|---|---|---|---|---|
| CPU | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ |
| DirectML | ✔️ | ✔️ | ❌ | ❌ | ❌ | ❌ |
| CUDA | ❌ | ❌ | ✔️[1] | ❌ | ❌ | ❌ |
- [1]: CUDA v11.8.
To use on platforms without pre-built binaries, you can build Node.js binding from source and consume it by npm install <onnxruntime_repo_root>/js/node/. See also instructions for building ONNX Runtime Node.js binding locally.
GPU Support
Right now, the Windows version supports only the DML provider. Linux x64 can use CUDA and TensorRT.
CUDA EP Installation
To use CUDA EP, you need to install the CUDA EP binaries. By default, the CUDA EP binaries are installed automatically when you install the package. If you want to skip the installation, you can pass the --onnxruntime-node-install-cuda=skip flag to the installation command.
npm install onnxruntime-node --onnxruntime-node-install-cuda=skip
You can also use this flag to specify the version of the CUDA: (v11 or v12)
npm install onnxruntime-node --onnxruntime-node-install-cuda=v12
License
License information can be found here.