Make TensorRT dir settable (#658)

deploy/README.md

@@ -5,7 +5,7 @@
 ## 模型导出
 训练得到一个满足要求的模型后，如果想要将该模型接入到C++预测库，需要通过`tools/export_model.py`导出该模型。
 
-- [导出教程](../docs/advanced_tutorials/inference/EXPORT_MODEL.md)
+- [导出教程](../docs/advanced_tutorials/deploy/EXPORT_MODEL.md)
 
 模型导出后, 目录结构如下(以`yolov3_darknet`为例):
 ```

deploy/cpp/CMakeLists.txt

@@ -9,6 +9,7 @@ option(WITH_TENSORRT "Compile demo with TensorRT."   OFF)
 SET(PADDLE_DIR "" CACHE PATH "Location of libraries")
 SET(OPENCV_DIR "" CACHE PATH "Location of libraries")
 SET(CUDA_LIB "" CACHE PATH "Location of libraries")
+SET(TENSORRT_DIR "" CACHE PATH "Compile demo with TensorRT")
 
 include(cmake/yaml-cpp.cmake)
 
@@ -112,8 +113,8 @@ endif()
 
 if (NOT WIN32)
   if (WITH_TENSORRT AND WITH_GPU)
-      include_directories("${PADDLE_DIR}/third_party/install/tensorrt/include")
-      link_directories("${PADDLE_DIR}/third_party/install/tensorrt/lib")
+     include_directories("${TENSORRT_DIR}/include")
+     link_directories("${TENSORRT_DIR}/lib")
   endif()
 endif(NOT WIN32)
 
@@ -195,15 +196,15 @@ endif(NOT WIN32)
 if(WITH_GPU)
   if(NOT WIN32)
     if (WITH_TENSORRT)
-      set(DEPS ${DEPS} ${PADDLE_DIR}/third_party/install/tensorrt/lib/libnvinfer${CMAKE_STATIC_LIBRARY_SUFFIX})
-      set(DEPS ${DEPS} ${PADDLE_DIR}/third_party/install/tensorrt/lib/libnvinfer_plugin${CMAKE_STATIC_LIBRARY_SUFFIX})
+      set(DEPS ${DEPS} ${TENSORRT_DIR}/lib/libnvinfer${CMAKE_SHARED_LIBRARY_SUFFIX})
+      set(DEPS ${DEPS} ${TENSORRT_DIR}/lib/libnvinfer_plugin${CMAKE_SHARED_LIBRARY_SUFFIX})
     endif()
     set(DEPS ${DEPS} ${CUDA_LIB}/libcudart${CMAKE_SHARED_LIBRARY_SUFFIX})
     set(DEPS ${DEPS} ${CUDNN_LIB}/libcudnn${CMAKE_SHARED_LIBRARY_SUFFIX})
   else()
     set(DEPS ${DEPS} ${CUDA_LIB}/cudart${CMAKE_STATIC_LIBRARY_SUFFIX} )
     set(DEPS ${DEPS} ${CUDA_LIB}/cublas${CMAKE_STATIC_LIBRARY_SUFFIX} )
-    set(DEPS ${DEPS} ${CUDA_LIB}/cudnn${CMAKE_STATIC_LIBRARY_SUFFIX})
+    set(DEPS ${DEPS} ${CUDNN_LIB}/cudnn${CMAKE_STATIC_LIBRARY_SUFFIX})
   endif()
 endif()
 

deploy/cpp/cmake/yaml-cpp.cmake

@@ -26,4 +26,5 @@ ExternalProject_Add(
         # Disable install step
         INSTALL_COMMAND ""
 	    LOG_DOWNLOAD ON
+        LOG_BUILD 1
 )

deploy/cpp/docs/linux_build.md

@@ -38,30 +38,40 @@ fluid_inference
 ### Step4: 编译
 
 编译`cmake`的命令在`scripts/build.sh`中，请根据实际情况修改主要参数，其主要内容说明如下：
-```
+
 # 是否使用GPU(即是否使用 CUDA)
-WITH_GPU=ON
+WITH_GPU=OFF
+# 使用MKL or openblas
+WITH_MKL=ON
 # 是否集成 TensorRT(仅WITH_GPU=ON 有效)
 WITH_TENSORRT=OFF
-# 上一步下载的 Paddle 预测库路径
-PADDLE_DIR=/root/projects/deps/fluid_inference/
-# OPENCV 路径, 如果使用自带预编译版本可不设置
-OPENCV_DIR=$(pwd)/deps/opencv346/
+# TensorRT 的lib路径
+TENSORRT_DIR=/path/to/TensorRT/
+# Paddle 预测库路径
+PADDLE_DIR=/path/to/fluid_inference/
+# Paddle 的预测库是否使用静态库来编译
+# 使用TensorRT时，Paddle的预测库通常为动态库
+WITH_STATIC_LIB=OFF
 # CUDA 的 lib 路径
-CUDA_LIB=/usr/local/cuda/lib64/
+CUDA_LIB=/path/to/cuda/lib/
 # CUDNN 的 lib 路径
-CUDNN_LIB=/usr/local/cuda/lib64/
+CUDNN_LIB=/path/to/cudnn/lib/
 
-# 以下无需改动
+# OPENCV 路径, 如果使用自带预编译版本可不修改
+sh $(pwd)/scripts/bootstrap.sh  # 下载预编译版本的opencv
+OPENCV_DIR=$(pwd)/deps/opencv3gcc4.8/
 
-sh $(pwd)/scripts/bootstrap.sh
+# 以下无需改动
 rm -rf build
 mkdir -p build
 cd build
 cmake .. \
     -DWITH_GPU=${WITH_GPU} \
+    -DWITH_MKL=${WITH_MKL} \
     -DWITH_TENSORRT=${WITH_TENSORRT} \
+    -DTENSORRT_DIR=${TENSORRT_DIR} \
     -DPADDLE_DIR=${PADDLE_DIR} \
+    -DWITH_STATIC_LIB=${WITH_STATIC_LIB} \
     -DCUDA_LIB=${CUDA_LIB} \
     -DCUDNN_LIB=${CUDNN_LIB} \
     -DOPENCV_DIR=${OPENCV_DIR}

deploy/cpp/scripts/bootstrap.sh

 # download pre-compiled opencv lib
-OPENCV_URL=https://paddleseg.bj.bcebos.com/deploy/deps/opencv346.tar.bz2
-if [ ! -d "./deps/opencv346" ]; then
+OPENCV_URL=https://paddleseg.bj.bcebos.com/deploy/docker/opencv3gcc4.8.tar.bz2
+if [ ! -d "./deps/opencv3gcc4.8" ]; then
     mkdir -p deps
     cd deps
     wget -c ${OPENCV_URL}
-    tar xvfj opencv346.tar.bz2
-    rm -rf opencv346.tar.bz2
+    tar xvfj opencv3gcc4.8.tar.bz2
+    rm -rf opencv3gcc4.8.tar.bz2
     cd ..
 fi
-

deploy/cpp/scripts/build.sh

-# compile with cuda
-WITH_GPU=ON
-# compile with tensorrt
+# 是否使用GPU(即是否使用 CUDA)
+WITH_GPU=OFF
+# 使用MKL or openblas
+WITH_MKL=ON
+# 是否集成 TensorRT(仅WITH_GPU=ON 有效)
 WITH_TENSORRT=OFF
-# path to paddle inference lib
-PADDLE_DIR=/root/projects/deps/fluid_inference/
-# path to opencv lib
-OPENCV_DIR=$(pwd)/deps/opencv346/
-# path to cuda lib
-CUDA_LIB=/usr/local/cuda/lib64/
+# TensorRT 的lib路径
+TENSORRT_DIR=/path/to/TensorRT/
+# Paddle 预测库路径
+PADDLE_DIR=/path/to/fluid_inference/
+# Paddle 的预测库是否使用静态库来编译
+# 使用TensorRT时，Paddle的预测库通常为动态库
+WITH_STATIC_LIB=OFF
+# CUDA 的 lib 路径
+CUDA_LIB=/path/to/cuda/lib/
+# CUDNN 的 lib 路径
+CUDNN_LIB=/path/to/cudnn/lib/
 
-sh $(pwd)/scripts/bootstrap.sh
+# OPENCV 路径, 如果使用自带预编译版本可不修改
+sh $(pwd)/scripts/bootstrap.sh  # 下载预编译版本的opencv
+OPENCV_DIR=$(pwd)/deps/opencv3gcc4.8/
 
+# 以下无需改动
 rm -rf build
 mkdir -p build
 cd build
 cmake .. \
-    -DWITH_GPU=OFF \
-    -DWITH_TENSORRT=OFF \
+    -DWITH_GPU=${WITH_GPU} \
+    -DWITH_MKL=${WITH_MKL} \
+    -DWITH_TENSORRT=${WITH_TENSORRT} \
+    -DTENSORRT_DIR=${TENSORRT_DIR} \
     -DPADDLE_DIR=${PADDLE_DIR} \
+    -DWITH_STATIC_LIB=${WITH_STATIC_LIB} \
     -DCUDA_LIB=${CUDA_LIB} \
-    -DOPENCV_DIR=${OPENCV_DIR} \
-    -DWITH_STATIC_LIB=OFF 
+    -DCUDNN_LIB=${CUDNN_LIB} \
+    -DOPENCV_DIR=${OPENCV_DIR}
 make