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| title | parent | nav_order |
|---|---|---|
| Install ORT | How to | 1 |
Install ONNX Runtime
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See the installation matrix for recommended instructions for desired combinations of target operating system, hardware, accelerator, and language.
Details on OS versions, compilers, language versions, dependent libraries, etc can be found under Compatibility.
Contents
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Inference
The table below lists the build variants available as officially supported packages. Others can be built from source from each release branch.
Requirements
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All builds require the English language package with
en_US.UTF-8locale. On Linux, install language-pack-en package by runninglocale-gen en_US.UTF-8andupdate-locale LANG=en_US.UTF-8 -
Windows builds require Visual C++ 2019 runtime.
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Please note additional requirements and dependencies in the table below:
| Official build | Nightly build | Reqs | |
|---|---|---|---|
| Python | If using pip, run pip install --upgrade pip prior to downloading. |
||
| CPU: onnxruntime | ort-nightly (dev) | ||
| GPU - CUDA: onnxruntime-gpu | ort-nightly-gpu (dev) | View | |
| OpenVINO: intel/onnxruntime - Intel managed | View | ||
| TensorRT (Jetson): Jetson Zoo - NVIDIA managed | |||
| C#/C/C++ | CPU: Microsoft.ML.OnnxRuntime | ort-nightly (dev) | |
| GPU - CUDA: Microsoft.ML.OnnxRuntime.Gpu | ort-nightly (dev) | View | |
| GPU - DirectML: Microsoft.ML.OnnxRuntime.DirectML | ort-nightly (dev) | View | |
| WinML | Microsoft.AI.MachineLearning | View | |
| Java | CPU: com.microsoft.onnxruntime:onnxruntime | View | |
| GPU - CUDA: com.microsoft.onnxruntime:onnxruntime_gpu | View | ||
| Android | com.microsoft.onnxruntime:onnxruntime-mobile | View | |
| iOS (C/C++) | CocoaPods: onnxruntime-mobile-c | View | |
| Objective-C | CocoaPods: onnxruntime-mobile-objc | View | |
| React Native | onnxruntime-react-native | View | |
| Node.js | onnxruntime-node | View | |
| Web | onnxruntime-web | View |
Note: Dev builds created from the master branch are available for testing newer changes between official releases. Please use these at your own risk. We strongly advise against deploying these to production workloads as support is limited for dev builds.
Training
ONNX Runtime Training packages are available for different versions of PyTorch, CUDA and ROCm versions.
The install command is:
pip3 install torch-ort [-f location]
python 3 -m torch_ort.configure
The location needs to be specified for any specific version other than the default combination. The location for the different configurations are below:
| Official build (location) | Nightly build (location) | |
|---|---|---|
| PyTorch 1.8.1 (CUDA 10.2) | onnxruntime_stable_torch181.cu102 | onnxruntime_nightly_torch181.cu102 |
| PyTorch 1.8.1 (CUDA 11.1) | onnxruntime_stable_torch181.cu111 | onnxruntime_nightly_torch181.cu111 |
| PyTorch 1.9 (CUDA 10.2) Default | onnxruntime-training | onnxruntime_nightly_torch190.cu102 |
| PyTorch 1.9 (CUDA 11.1) | onnxruntime_stable_torch190.cu111 | onnxruntime_nightly_torch190.cu111 |
| [Preview] PyTorch 1.8.1 (ROCm 4.2) | onnxruntime_stable_torch181.rocm42 | onnxruntime_nightly_torch181.rocm42 |
| [Preview] PyTorch 1.9 (ROCm 4.2) | onnxruntime_stable_torch190.rocm42 | onnxruntime_nightly_torch190.rocm42 |