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Staged here: https://natke.github.io/onnxruntime/docs/genai/howto/build-from-source.html#option-3-build-from-source
146 lines
3.4 KiB
Markdown
146 lines
3.4 KiB
Markdown
---
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title: Build from source
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description: How to build the ONNX Runtime generate() API from source
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has_children: false
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parent: How to
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grand_parent: Generative AI (Preview)
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nav_order: 2
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---
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# Build onnxruntime-genai from source
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{: .no_toc }
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* TOC placeholder
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{:toc}
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## Pre-requisites
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`cmake`
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## Clone the onnxruntime-genai repo
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```bash
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git clone https://github.com/microsoft/onnxruntime-genai
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cd onnxruntime-genai
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```
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## Install ONNX Runtime
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By default, the onnxruntime-genai build expects to find the ONNX Runtime include and binaries in a folder called `ort` in the root directory of onnxruntime-genai. You can put the ONNX Runtime files in a different location and specify this location to the onnxruntime-genai build. These instructions use `ORT_HOME` as the location.
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### Option 1: Install from release
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These instructions are for the Linux GPU build of ONNX Runtime. Replace `linux-gpu` with your target of choice.
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```bash
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cd <ORT_HOME>
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curl -L https://github.com/microsoft/onnxruntime/releases/download/v1.17.1/onnxruntime-linux-x64-gpu-1.17.1.tgz
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tar xvzf onnxruntime-linux-x64-gpu-1.17.1.tgz
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mv onnxruntime-linux-x64-gpu-1.17.1/include .
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mv onnxruntime-linux-x64-gpu-1.17.1/lib .
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```
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### Option 2: Install from nightly
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Download the nightly nuget package `Microsoft.ML.OnnxRuntime` from: https://aiinfra.visualstudio.com/PublicPackages/_artifacts/feed/ORT-Nightly.
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Extract the nuget package.
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```bash
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tar xvf Microsoft.ML.OnnxRuntime.1.18.0-dev-20240322-0323-ca825cb6e6.nupkg
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```
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Copy the include and lib files into `ORT_HOME`.
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On Windows
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Example is given for `win-x64`. Change this to your architecture if different.
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```cmd
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copy build\native\include\onnxruntime_c_api.h <ORT_HOME>\include
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copy runtimes\win-x64\native\*.dll <ORT_HOME>\lib
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```
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On Linux
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```cmd
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cp build/native/include/onnxruntime_c_api.h <ORT_HOME>/include
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cp build/linux-x64/native/libonnxruntime*.so* <ORT_HOME>/lib
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```
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### Option 3: Build from source
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```
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git clone https://github.com/microsoft/onnxruntime.git
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cd onnxruntime
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```
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Create include and lib folders in the `ORT_HOME` directory
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```bash
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mkdir <ORT HOME>/include
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mkdir <ORT_HOME>/lib
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```
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Build from source and copy the include and libraries into `ORT_HOME`
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On Windows
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```cmd
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build.bat --build_shared_lib --skip_tests --parallel [--use_cuda] --config Release
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copy include\onnxruntime\core\session\onnxruntime_c_api.h <ORT_HOME>\include
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copy build\Windows\Release\Release\*.dll <ORT_HOME>\lib
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copy build\Windows\Release\Release\onnxruntime.lib <ORTHOME>\lib
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```
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On Linux
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```bash
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./build.sh --build_shared_lib --skip_tests --parallel [--use_cuda] --config Release
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cp include/onnxruntime/core/session/onnxruntime_c_api.h <ORT_HOME>/include
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cp build/Linux/Release/libonnxruntime*.so* <ORT_HOME>/lib
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```
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On Mac
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```bash
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./build.sh --build_shared_lib --skip_tests --parallel --config Release
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cp include/onnxruntime/core/session/onnxruntime_c_api.h <ORT_HOME>/include
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cp build/MacOS/Release/libonnxruntime*.dylib* <ORT_HOME>/lib
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```
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## Build onnxruntime-genai
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### Build for CPU
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```bash
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cd ..
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python build.py [--ort_home <ORT_HOME>]
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```
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### Build for CUDA
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These instructions assume you already have CUDA installed.
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```bash
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cd ..
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python build.py --cuda_home <path to cuda home> [--ort_home <ORT_HOME>]
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```
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## Install the library into your application
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### Install Python wheel
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```bash
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cd build/wheel
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pip install *.whl
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```
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### Install Nuget package
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_Coming soon_
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### Install C/C++ header file and library
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_Coming soon_
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