Windows
This page describes how to build sherpa-onnx on Windows.
Hint
MinGW is known not to work with sherpa-onnx.
Please install Visual Studio 2022 before you continue.
Note
You can download pre-compiled binaries for both 32-bit and 64-bit Windows from the following URL https://huggingface.co/csukuangfj/sherpa-onnx-libs/tree/main.
Please always download the latest version.
URLs to download the version 1.12.10 is given below.
64-bit Windows (static lib) |
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64-bit Windows (shared lib) |
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32-bit Windows (static lib) |
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32-bit Windows (shared lib) |
If you cannot access huggingface.co, then please replace huggingface.co with
hf-mirror.com.
64-bit Windows (x64)
CPU
git clone https://github.com/k2-fsa/sherpa-onnx
cd sherpa-onnx
mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE=Release ..
cmake --build . --config Release
GPU (CUDA 11.8)
git clone https://github.com/k2-fsa/sherpa-onnx
cd sherpa-onnx
mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE=Release -DBUILD_SHARED_LIBS=ON -DSHERPA_ONNX_ENABLE_GPU=ON ..
cmake --build . --config Release
Hint
You need to install CUDA toolkit 11.8. Otherwise, you would get errors at runtime.
Caution: Please install cuda toolkit 11.8. Other versions do NOT work!
Caution: Please install cuda toolkit 11.8. Other versions do NOT work!
Caution: Please install cuda toolkit 11.8. Other versions do NOT work!
If it crashes without any errors, please see
You need to also install cudnn.
GPU (CUDA 12.x)
# We assume you use git bash commandline to run the following commands for curl, unzip, and export
git clone https://github.com/k2-fsa/sherpa-onnx
cd sherpa-onnx
curl -SL -O https://github.com/microsoft/onnxruntime/releases/download/v1.22.0/onnxruntime-win-x64-gpu-1.22.0.zip
unzip onnxruntime-win-x64-gpu-1.22.0.zip
export SHERPA_ONNXRUNTIME_LIB_DIR=$PWD/onnxruntime-win-x64-gpu-1.22.0/lib
export SHERPA_ONNXRUNTIME_INCLUDE_DIR=$PWD/onnxruntime-win-x64-gpu-1.22.0/include
mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE=Release -DBUILD_SHARED_LIBS=ON -DSHERPA_ONNX_ENABLE_GPU=ON ..
cmake --build . --config Release
Note
You can download pre-build libraries and executables of sherpa-onnx for CUDA 12.x with CUDNN 9
at https://github.com/k2-fsa/sherpa-onnx/releases. Please always use the latest version.
For instance, for the version 1.12.13, you can use:
wget https://github.com/k2-fsa/sherpa-onnx/releases/download/v1.12.13/sherpa-onnx-v1.12.13-cuda-12.x-cudnn-9.x-win-x64-cuda.tar.bz2
After building, you will find an executable sherpa-onnx.exe inside the bin/Release directory.
That’s it!
Please refer to Pre-trained models for a list of pre-trained models.
32-bit Windows (x86)
Hint
It does not support NVIDIA GPU for Win32/x86.
All you need is to run:
git clone https://github.com/k2-fsa/sherpa-onnx
cd sherpa-onnx
mkdir build
cd build
# Please select one toolset among VS 2015, 2017, 2019, and 2022 below
# We use VS 2022 as an example.
# For Visual Studio 2015
# cmake -T v140,host=x64 -A Win32 -D CMAKE_BUILD_TYPE=Release ..
# For Visual Studio 2017
# cmake -T v141,host=x64 -A Win32 -D CMAKE_BUILD_TYPE=Release ..
# For Visual Studio 2019
# cmake -T v142,host=x64 -A Win32 -D CMAKE_BUILD_TYPE=Release ..
# For Visual Studio 2022
cmake -T v143,host=x64 -A Win32 -D CMAKE_BUILD_TYPE=Release ..
cmake --build . --config Release
After building, you will find an executable sherpa-onnx.exe inside the bin/Release directory.
That’s it!
Please refer to Pre-trained models for a list of pre-trained models.
Hint
By default, it builds static libraries of sherpa-onnx. To get dynamic/shared
libraries, please pass -DBUILD_SHARED_LIBS=ON to cmake. That is, use
cmake -DCMAKE_BUILD_TYPE=Release -DBUILD_SHARED_LIBS=ON ..