提交 b4f078aa 编写于 作者: T Thomas Young

fix the compile and the dockerfile document

上级 6fa2ae8b
......@@ -100,14 +100,21 @@ make -j10
you can execute `make install` to put targets under directory `./output`, you need to add`-DCMAKE_INSTALL_PREFIX=./output`to specify output path to cmake command shown above.
### Integrated GPU version paddle inference library
### CUDA_PATH is the cuda install path,use the command(whereis cuda) to check,it should be /usr/local/cuda.
### CUDNN_LIBRARY && CUDA_CUDART_LIBRARY is the lib path, it should be /usr/local/cuda/lib64/
``` shell
export CUDA_PATH='/usr/local'
export CUDNN_LIBRARY='/usr/local/cuda/lib64/'
export CUDA_CUDART_LIBRARY="/usr/local/cuda/lib64/"
mkdir server-build-gpu && cd server-build-gpu
cmake -DPYTHON_INCLUDE_DIR=$PYTHONROOT/include/python2.7/ \
-DPYTHON_LIBRARIES=$PYTHONROOT/lib/libpython2.7.so \
-DPYTHON_EXECUTABLE=$PYTHONROOT/bin/python \
-DCUDA_TOOLKIT_ROOT_DIR=${CUDA_PATH} \
-DCUDNN_LIBRARY=${CUDNN_LIBRARY} \
-DCUDNN_LIBRARY=${CUDNN_LIBRARY} \
-DCUDA_CUDART_LIBRARY=${CUDA_CUDART_LIBRARY} \
-DSERVER=ON \
-DWITH_GPU=ON ..
make -j10
......@@ -116,6 +123,10 @@ make -j10
### Integrated TRT version paddle inference library
```
export CUDA_PATH='/usr/local'
export CUDNN_LIBRARY='/usr/local/cuda/lib64/'
export CUDA_CUDART_LIBRARY="/usr/local/cuda/lib64/"
mkdir server-build-trt && cd server-build-trt
cmake -DPYTHON_INCLUDE_DIR=$PYTHONROOT/include/python2.7/ \
-DPYTHON_LIBRARIES=$PYTHONROOT/lib/libpython2.7.so \
......@@ -123,6 +134,7 @@ cmake -DPYTHON_INCLUDE_DIR=$PYTHONROOT/include/python2.7/ \
-DTENSORRT_ROOT=${TENSORRT_LIBRARY_PATH} \
-DCUDA_TOOLKIT_ROOT_DIR=${CUDA_PATH} \
-DCUDNN_LIBRARY=${CUDNN_LIBRARY} \
-DCUDA_CUDART_LIBRARY=${CUDA_CUDART_LIBRARY} \
-DSERVER=ON \
-DWITH_GPU=ON \
-DWITH_TRT=ON ..
......
......@@ -97,14 +97,20 @@ make -j10
可以执行`make install`把目标产出放在`./output`目录下,cmake阶段需添加`-DCMAKE_INSTALL_PREFIX=./output`选项来指定存放路径。
### 集成GPU版本Paddle Inference Library
### CUDA_PATH是cuda的安装路径,可以使用命令行whereis cuda命令确认你的cuda安装路径,通常应该是/usr/local/cuda
### CUDNN_LIBRARY CUDA_CUDART_LIBRARY 是cuda库文件的路径,通常应该是/usr/local/cuda/lib64/
``` shell
export CUDA_PATH='/usr/local'
export CUDNN_LIBRARY='/usr/local/cuda/lib64/'
export CUDA_CUDART_LIBRARY="/usr/local/cuda/lib64/"
mkdir server-build-gpu && cd server-build-gpu
cmake -DPYTHON_INCLUDE_DIR=$PYTHONROOT/include/python2.7/ \
-DPYTHON_LIBRARIES=$PYTHONROOT/lib/libpython2.7.so \
-DPYTHON_EXECUTABLE=$PYTHONROOT/bin/python \
-DCUDA_TOOLKIT_ROOT_DIR=${CUDA_PATH} \
-DCUDNN_LIBRARY=${CUDNN_LIBRARY} \
-DCUDA_CUDART_LIBRARY=${CUDA_CUDART_LIBRARY} \
-DSERVER=ON \
-DWITH_GPU=ON ..
make -j10
......@@ -113,6 +119,10 @@ make -j10
### 集成TensorRT版本Paddle Inference Library
```
export CUDA_PATH='/usr/local'
export CUDNN_LIBRARY='/usr/local/cuda/lib64/'
export CUDA_CUDART_LIBRARY="/usr/local/cuda/lib64/"
mkdir server-build-trt && cd server-build-trt
cmake -DPYTHON_INCLUDE_DIR=$PYTHONROOT/include/python2.7/ \
-DPYTHON_LIBRARIES=$PYTHONROOT/lib/libpython2.7.so \
......@@ -120,6 +130,7 @@ cmake -DPYTHON_INCLUDE_DIR=$PYTHONROOT/include/python2.7/ \
-DTENSORRT_ROOT=${TENSORRT_LIBRARY_PATH} \
-DCUDA_TOOLKIT_ROOT_DIR=${CUDA_PATH} \
-DCUDNN_LIBRARY=${CUDNN_LIBRARY} \
-DCUDA_CUDART_LIBRARY=${CUDA_CUDART_LIBRARY} \
-DSERVER=ON \
-DWITH_GPU=ON \
-DWITH_TRT=ON ..
......
......@@ -28,6 +28,7 @@ You can get images in two ways:
## Image description
Runtime images cannot be used for compilation.
If you need secondary development based on source code, use the version with the suffix - devel.
| Description | OS | TAG | Dockerfile |
| :----------------------------------------------------------: | :-----: | :--------------------------: | :----------------------------------------------------------: |
......
......@@ -28,6 +28,7 @@
## 镜像说明
运行时镜像不能用于开发编译。
若需要基于源代码二次开发编译,请使用后缀为-devel的版本。
| 镜像说明 | 操作系统 | TAG | Dockerfile |
| -------------------------------------------------- | -------- | ---------------------------- | ------------------------------------------------------------ |
......
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