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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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  • TOC placeholder {:toc}

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-8 locale. On Linux, install language-pack-en package by running locale-gen en_US.UTF-8 and update-locale LANG=en_US.UTF-8

  • Windows builds require Visual C++ 2019 runtime.

  • 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