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Two major modifications of this PR: 1. Refactor OrtTensorRTProviderOptions initialization and make it easy to add new field. 2. Make Python API capable of using TensorRT plugins by adding new Python binding api `register_tensorrt_plugins_as_custom_ops`. (It needs to register ep's custom op domain before model load. For C++ API, it's slightly different, when calling SessionOptionsAppendExecutionProvider_TensorRT_XX, it appends cutom op domain to session option. Later ORT can register custom op domain from session option before model loading) |
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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 v12.x+ or Electron v5.x+.
Following platforms are supported with pre-built binaries:
- Windows x64 CPU NAPI_v3
- Linux x64 CPU NAPI_v3
- MacOS x64 CPU NAPI_v3
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.
License
License information can be found here.