fix the compile and the dockerfile document

doc/COMPILE.md

@@ -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=${CUDNN_LIBRARY} \
+    -DCUDA_CUDART_LIBRARY=${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 ..

doc/COMPILE_CN.md

@@ -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 ..

doc/DOCKER_IMAGES.md

@@ -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                          |
 | :----------------------------------------------------------: | :-----: | :--------------------------: | :----------------------------------------------------------: |

doc/DOCKER_IMAGES_CN.md

@@ -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                                                   |
 | -------------------------------------------------- | -------- | ---------------------------- | ------------------------------------------------------------ |