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How to Build GPU Deployment Environment

FastDeploy supports Paddle Inference, ONNX Runtime and TensorRT in the GPU environment. It should be noted that users also can use CPU in a GPU environment in Linux & Windows, so users can integrate the OpenVINO backend at the same time.

Backend Platform Supported model format Description
Paddle Inference Windows(x64)
Linux(x64)		 Paddle Support both CPU/GPU, and compilation switch is ENABLE_PADDLE_BACKEND. The default is OFF
ONNX Runtime Windows(x64)
Linux(x64/aarch64)
Mac(x86/arm64)		 Paddle/ONNX Support both CPU/GPU, and compilation switch is ENABLE_ORT_BACKEND. The default is OFF
TensorRT Windows(x64)
Linux(x64)		 Paddle/ONNX Support GPU only, and compilation switch is ENABLE_TRT_BACKEND. The default is OFF
OpenVINO Windows(x64)
Linux(x64)		 Paddle/ONNX Support CPU only, and compilation switch is ENABLE_OPENVINO_BACKEND. The default is OFF

Note:

When the environment is GPU, please set WITH_GPU as ON and specify CUDA_DIRECTORY. If TensorRT integration is needed, please specify TRT_DIRECTORY as well.

How to Build and Install C++ SDK

Linux

Prerequisite for Compiling on Linux:

  • gcc/g++ >= 5.4 (8.2 is recommended)
  • cmake >= 3.18.0
  • cuda >= 11.2
  • cudnn >= 8.2
git clone https://github.com/PaddlePaddle/FastDeploy.git
cd FastDeploy
mkdir build && cd build
cmake .. -DENABLE_ORT_BACKEND=ON \
         -DENABLE_PADDLE_BACKEND=ON \
         -DENABLE_OPENVINO_BACKEND=ON \
         -DENABLE_TRT_BACKEND=ON \
         -DWITH_GPU=ON \
         -DTRT_DIRECTORY=/Paddle/TensorRT-8.4.1.5 \
         -DCUDA_DIRECTORY=/usr/local/cuda \
         -DCMAKE_INSTALL_PREFIX=${PWD}/compiled_fastdeploy_sdk \
         -DENABLE_VISION=ON
make -j12
make install

Windows

Prerequisite for Compiling on Windows:

  • Windows 10/11 x64
  • Visual Studio 2019
  • cuda >= 11.2
  • cudnn >= 8.2

Notice: Make sure Visual Studio Integration is installed during CUDA installation, or manually copy the 4 files under C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\extras\visual_studio_integration\MSBuildExtensions\ into C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\MSBuild\Microsoft\VC\v160\BuildCustomizations\. Otherwise, you may run into No CUDA toolset found error during cmake.

Launch the x64 Native Tools Command Prompt for VS 2019 from the Windows Start Menu and run the following commands:

git clone https://github.com/PaddlePaddle/FastDeploy.git
cd FastDeploy
mkdir build && cd build
cmake .. -G "Visual Studio 16 2019" -A x64 \
         -DENABLE_ORT_BACKEND=ON \
         -DENABLE_PADDLE_BACKEND=ON \
         -DENABLE_OPENVINO_BACKEND=ON \
         -DENABLE_TRT_BACKEND=ON
         -DENABLE_VISION=ON \
         -DWITH_GPU=ON \
         -DTRT_DIRECTORY="D:\Paddle\TensorRT-8.4.1.5" \
         -DCUDA_DIRECTORY="C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2" \
         -DCMAKE_INSTALL_PREFIX="D:\Paddle\compiled_fastdeploy"
msbuild fastdeploy.sln /m /p:Configuration=Release /p:Platform=x64
msbuild INSTALL.vcxproj /m /p:Configuration=Release /p:Platform=x64

Once compiled, the C++ inference library is generated in the directory specified by CMAKE_INSTALL_PREFIX

If you use CMake GUI, please refer to How to Compile with CMakeGUI + Visual Studio 2019 IDE on Windows

How to Build and Install Python SDK

Linux

Prerequisite for Compiling on Linux:

  • gcc/g++ >= 5.4 (8.2 is recommended)

  • cmake >= 3.18.0

  • python >= 3.6

  • cuda >= 11.2

  • cudnn >= 8.2

All compilation options are imported via environment variables

git clone https://github.com/PaddlePaddle/FastDeploy.git
cd FastDeploy/python
export ENABLE_ORT_BACKEND=ON
export ENABLE_PADDLE_BACKEND=ON
export ENABLE_OPENVINO_BACKEND=ON
export ENABLE_VISION=ON
export ENABLE_TRT_BACKEND=ON
export WITH_GPU=ON
export TRT_DIRECTORY=/Paddle/TensorRT-8.4.1.5
export CUDA_DIRECTORY=/usr/local/cuda

python setup.py build
python setup.py bdist_wheel

Windows

Prerequisite for Compiling on Windows:

  • Windows 10/11 x64
  • Visual Studio 2019
  • python >= 3.6
  • cuda >= 11.2
  • cudnn >= 8.2

Launch the x64 Native Tools Command Prompt for VS 2019 from the Windows Start Menu and run the following commands:

git clone https://github.com/PaddlePaddle/FastDeploy.git
cd FastDeploy/python
set ENABLE_ORT_BACKEND=ON
set ENABLE_PADDLE_BACKEND=ON
set ENABLE_OPENVINO_BACKEND=ON
set ENABLE_VISION=ON
set ENABLE_TRT_BACKEND=ON
set WITH_GPU=ON
set TRT_DIRECTORY=D:\Paddle\TensorRT-8.4.1.5
set CUDA_DIRECTORY=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2

python setup.py build
python setup.py bdist_wheel

The compiled wheel package will be generated in the FastDeploy/python/dist directory once finished. Users can pip-install it directly.

During the compilation, if developers want to change the compilation parameters, it is advisable to delete the build and .setuptools-cmake-build subdirectories in the FastDeploy/python to avoid the possible impact from cache, and then recompile.