mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-10 02:50:19 +08:00
c38b7d4377
* Fix links in readme * Fix links in readme * Update PPOCRv2/v3 examples * Update auto compression configs * Add neww quantization support for paddleclas model * Update quantized Yolov6s model download link * Improve PPOCR comments * Add English doc for quantization * Fix PPOCR rec model bug * Add new paddleseg quantization support * Add new paddleseg quantization support * Add new paddleseg quantization support * Add new paddleseg quantization support * Add Ascend model list * Add ascend model list * Add ascend model list * Add ascend model list * Add ascend model list * Add ascend model list * Add ascend model list * Support DirectML in onnxruntime * Support onnxruntime DirectML * Support onnxruntime DirectML * Support onnxruntime DirectML * Support OnnxRuntime DirectML * Support OnnxRuntime DirectML * Support OnnxRuntime DirectML * Support OnnxRuntime DirectML * Support OnnxRuntime DirectML * Support OnnxRuntime DirectML * Support OnnxRuntime DirectML * Support OnnxRuntime DirectML * Remove DirectML vision model example * Imporve OnnxRuntime DirectML * Imporve OnnxRuntime DirectML * fix opencv cmake in Windows * recheck codestyle
58 lines
3.1 KiB
Markdown
58 lines
3.1 KiB
Markdown
English | [中文](../../cn/build_and_install/directml.md)
|
|
|
|
# How to Build DirectML Deployment Environment
|
|
Direct Machine Learning (DirectML) is a high-performance, hardware-accelerated DirectX 12 library for machine learning on Windows systems.
|
|
Currently, Fastdeploy's ONNX Runtime backend has DirectML integrated, allowing users to deploy models on AMD/Intel/Nvidia/Qualcomm GPUs with DirectX 12 support.
|
|
|
|
More details:
|
|
- [ONNX Runtime DirectML Execution Provider](https://onnxruntime.ai/docs/execution-providers/DirectML-ExecutionProvider.html)
|
|
|
|
# DirectML requirements
|
|
- Compilation requirements: Visual Studio 2017 toolchain and above.
|
|
- Operating system: Windows 10, version 1903, and newer. (DirectML is part of the operating system and does not need to be installed separately)
|
|
- Hardware requirements: DirectX 12 supported graphics cards, e.g., AMD GCN 1st generation and above/ Intel Haswell HD integrated graphics and above/ Nvidia Kepler architecture and above/ Qualcomm Adreno 600 and above.
|
|
|
|
# How to Build and Install DirectML C++ SDK
|
|
The DirectML is integrated with the ONNX Runtime backend, so to use DirectML, users need to turn on the option to compile ONNX Runtime. Also, FastDeploy's DirectML supports building programs for x64/x86 (Win32) architectures.
|
|
|
|
For the x64 example, in the Windows menu, find `x64 Native Tools Command Prompt for VS 2019` and open it by executing the following command
|
|
```bat
|
|
git clone https://github.com/PaddlePaddle/FastDeploy.git
|
|
cd FastDeploy
|
|
mkdir build && cd build
|
|
|
|
cmake .. -G "Visual Studio 16 2019" -A x64 ^
|
|
-DWITH_DIRECTML=ON ^
|
|
-DENABLE_ORT_BACKEND=ON ^
|
|
-DENABLE_VISION=ON ^
|
|
-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](../faq/build_on_win_with_gui.md)
|
|
|
|
|
|
For the x86(Win32) example, in the Windows menu, find `x86 Native Tools Command Prompt for VS 2019` and open it by executing the following command
|
|
```bat
|
|
git clone https://github.com/PaddlePaddle/FastDeploy.git
|
|
cd FastDeploy
|
|
mkdir build && cd build
|
|
|
|
cmake .. -G "Visual Studio 16 2019" -A Win32 ^
|
|
-DWITH_DIRECTML=ON ^
|
|
-DENABLE_ORT_BACKEND=ON ^
|
|
-DENABLE_VISION=ON ^
|
|
-DCMAKE_INSTALL_PREFIX="D:\Paddle\compiled_fastdeploy" ^
|
|
|
|
msbuild fastdeploy.sln /m /p:Configuration=Release /p:Platform=Win32
|
|
msbuild INSTALL.vcxproj /m /p:Configuration=Release /p:Platform=Win32
|
|
```
|
|
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](../faq/build_on_win_with_gui.md)
|
|
|
|
# How to use compiled DirectML SDK.
|
|
The DirectML compiled library can be used in the same way as any other hardware on Windows, see the following link.
|
|
- [Using the FastDeploy C++ SDK on Windows Platform](../faq/use_sdk_on_windows.md)
|