centos下cmake安装caffe
2024-06-03 13:38:51
安装必要的依赖项：
sudo yum install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel
sudo yum install gflags-devel glog-devel lmdb-devel
sudo yum atlas-devel cmake glibc-devel gcc-gfortran autoconf automake gcc gcc-c++ git libtool make pkgconfig zlib-devel SDL* yasm* python-devel cmake* git ncurses* *freetype2 nasm nasm*
安装Boost
安装glog
安装protobuf
安装lmdb
安装leveldb
安装gflags
安装hdf5
***切记，上述依赖需要安装到/usr/local下面的目录，否则编译时会提示找不到相关库文件。
安装ffmpeg
安装opencv
安装cuda
查看cuda版本：cat /usr/local/cuda/version.txt
安装cudnn
如果将来要采用python调用caffe的话，必须将numpy提前装好：
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安装caffe
下载BVLC版本的caffe
[root@localhost build]# git clone https://github.com/BVLC/caffe
使用cmake安装及编译caffe
进入caffe根目录：
#cd xxx/xxx/caffe
创建build文件夹并配置
mkdir build
cd build
cmake ..如果在执行cmake ..时报了一些错误如下：
cmake cannot find -lopencv_dep_cudart
（解决方案参考：https://blog.csdn.net/qq_36130482/article/details/70171301,
https://blog.csdn.net/mystylee/article/details/79071553）
我的做法是在cmake时附加额外指定信息：
[root@localhost build]# cmake .. -DBLAS=open -DCUDA_USE_STATIC_CUDA_RUNTIME=OFF其中-DBLAS=open是由于在centos下blas无atlas库，安装的是openblas库，因此此处指定下；
-DCUDA_USE_STATIC_CUDA_RUNTIME=OFF是为了解决上面的错误的。
cmake后产生如下内容……
[root@localhost build]# cmake .. -DBLAS=open -DCUDA_USE_STATIC_CUDA_RUNTIME=OFF
CMake Warning at /usr/local/share/cmake-3.6/Modules/FindBoost.cmake:743 (message):Imported targets not available for Boost version 106600
Call Stack (most recent call first):/usr/local/share/cmake-3.6/Modules/FindBoost.cmake:842 (_Boost_COMPONENT_DEPENDENCIES)/usr/local/share/cmake-3.6/Modules/FindBoost.cmake:1395 (_Boost_MISSING_DEPENDENCIES)cmake/Dependencies.cmake:8 (find_package)CMakeLists.txt:49 (include)CMake Warning at /usr/local/share/cmake-3.6/Modules/FindBoost.cmake:743 (message):Imported targets not available for Boost version 106600
Call Stack (most recent call first):/usr/local/share/cmake-3.6/Modules/FindBoost.cmake:842 (_Boost_COMPONENT_DEPENDENCIES)/usr/local/share/cmake-3.6/Modules/FindBoost.cmake:1395 (_Boost_MISSING_DEPENDENCIES)cmake/Dependencies.cmake:8 (find_package)CMakeLists.txt:49 (include)CMake Warning at /usr/local/share/cmake-3.6/Modules/FindBoost.cmake:743 (message):Imported targets not available for Boost version 106600
Call Stack (most recent call first):/usr/local/share/cmake-3.6/Modules/FindBoost.cmake:842 (_Boost_COMPONENT_DEPENDENCIES)/usr/local/share/cmake-3.6/Modules/FindBoost.cmake:1395 (_Boost_MISSING_DEPENDENCIES)cmake/Dependencies.cmake:8 (find_package)CMakeLists.txt:49 (include)-- Boost version: 1.66.0
-- Found the following Boost libraries:
-- system
-- thread
-- filesystem
-- Found gflags (include: /usr/include, library: /usr/lib64/libgflags.so)
-- Found glog (include: /usr/include, library: /usr/lib64/libglog.so)
-- Found PROTOBUF Compiler: /usr/local/bin/protoc
-- HDF5: Using hdf5 compiler wrapper to determine C configuration
-- HDF5: Using hdf5 compiler wrapper to determine CXX configuration
-- Found lmdb (include: /usr/include, library: /usr/lib64/liblmdb.so)
-- Found LevelDB (include: /usr/include, library: /usr/lib64/libleveldb.so)
-- Found Snappy (include: /usr/include, library: /usr/lib64/libsnappy.so)
-- CUDA detected: 8.0
-- Found cuDNN: ver. 5.1.5 found (include: /usr/local/cuda/include, library: /usr/local/cuda/lib64/libcudnn.so)
-- Added CUDA NVCC flags for: sm_61
-- OpenCV found (/usr/local/opencv-2.4.13)
-- Found OpenBLAS libraries: /usr/lib64/libopenblas.so
-- Found OpenBLAS include: /usr/include
-- NumPy ver. 1.15.4 found (include: /usr/lib64/python2.7/site-packages/numpy/core/include)
CMake Warning at /usr/local/share/cmake-3.6/Modules/FindBoost.cmake:743 (message):Imported targets not available for Boost version 106600
Call Stack (most recent call first):/usr/local/share/cmake-3.6/Modules/FindBoost.cmake:842 (_Boost_COMPONENT_DEPENDENCIES)/usr/local/share/cmake-3.6/Modules/FindBoost.cmake:1395 (_Boost_MISSING_DEPENDENCIES)cmake/Dependencies.cmake:180 (find_package)CMakeLists.txt:49 (include)-- Boost version: 1.66.0
-- Found the following Boost libraries:
-- python
-- Detected Doxygen OUTPUT_DIRECTORY: ./doxygen/
--
-- ******************* Caffe Configuration Summary *******************
-- General:
-- Version : 1.0.0
-- Git : 1.0-132-g99bd997
-- System : Linux
-- C++ compiler : /bin/c++
-- Release CXX flags : -O3 -DNDEBUG -fPIC -Wall -Wno-sign-compare -Wno-uninitialized
-- Debug CXX flags : -g -fPIC -Wall -Wno-sign-compare -Wno-uninitialized
-- Build type : Release
--
-- BUILD_SHARED_LIBS : ON
-- BUILD_python : ON
-- BUILD_matlab : OFF
-- BUILD_docs : ON
-- CPU_ONLY : OFF
-- USE_OPENCV : ON
-- USE_LEVELDB : ON
-- USE_LMDB : ON
-- USE_NCCL : OFF
-- ALLOW_LMDB_NOLOCK : OFF
-- USE_HDF5 : ON
--
-- Dependencies:
-- BLAS : Yes (open)
-- Boost : Yes (ver. 1.66)
-- glog : Yes
-- gflags : Yes
-- protobuf : Yes (ver. 3.5.0)
-- lmdb : Yes (ver. 0.9.22)
-- LevelDB : Yes (ver. 1.12)
-- Snappy : Yes (ver. 1.1.0)
-- OpenCV : Yes (ver. 2.4.13)
-- CUDA : Yes (ver. 8.0)
--
-- NVIDIA CUDA:
-- Target GPU(s) : Auto
-- GPU arch(s) : sm_61
-- cuDNN : Yes (ver. 5.1.5)
--
-- Python:
-- Interpreter : /bin/python2.7 (ver. 2.7.5)
-- Libraries : //lib64/libpython2.7.so (ver 2.7.5)
-- NumPy : /usr/lib64/python2.7/site-packages/numpy/core/include (ver 1.15.4)
--
-- Documentaion:
-- Doxygen : /bin/doxygen (1.8.5)
-- config_file : /home/chensq/caffe/.Doxyfile
--
-- Install:
-- Install path : /home/chensq/caffe/build/install
--
-- Configuring done
-- Generating done
-- Build files have been written to: /home/chensq/caffe/build
然后运行以下指定进行编译：
make -j16 # -j后面为cpu核数，可小于或等于实际cpu核数[root@localhost build]# make clean
[root@localhost build]# make -j16
[ 1%] Running C++/Python protocol buffer compiler on /home/chensq/caffe/src/caffe/proto/caffe.proto
Scanning dependencies of target caffeproto
[ 1%] Building CXX object src/caffe/CMakeFiles/caffeproto.dir/__/__/include/caffe/proto/caffe.pb.cc.o
[ 2%] Linking CXX static library ../../lib/libcaffeproto.a
[ 2%] Built target caffeproto
[ 2%] Building NVCC (Device) object src/caffe/CMakeFiles/cuda_compile.dir/layers/cuda_compile_generated_accuracy_layer.cu.o
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测试caffe是否安装成功……
#进入caffe目录
sh data/mnist/get_mnist.sh
sh examples/mnist/create_mnist.sh
sh examples/mnist/train_lenet.sh参考：https://www.cnblogs.com/qjoanven/p/7813957.html
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