安裝caffe2
預先准備、安裝gflags及autoconf及GLOG
https://github.com/caffe2/caffe2/issues/1810
一、下載源代碼通過網盤
https://blog.csdn.net/Gpwner/article/details/80068251?tdsourcetag=s_pctim_aiomsg
二、解壓文件，二次解壓。
$xz -d pytorch.tar.xz
$tar -xvf pytorch.tar
或者通過以下命令解壓：
tar xvJf pytorch.tar.xz
三、安裝依賴
sudo apt-get update sudo apt-get install -y --no-install-recommends \ build-essential \ cmake \ git \ libgoogle-glog-dev \ libgtest-dev \ libiomp-dev \ libleveldb-dev \ liblmdb-dev \ libopencv-dev \ libopenmpi-dev \ libsnappy-dev \ libprotobuf-dev \ openmpi-bin \ openmpi-doc \ protobuf-compiler \ python-dev \ python-pip # for Ubuntu 14.04 sudo apt-get install -y --no-install-recommends libgflags2 # for Ubuntu 16.04 sudo apt-get install -y --no-install-recommends libgflags-dev sudo pip install \ future \ numpy \ protobuf
四、
構建與安裝
獲取源碼
從 這里 （或終端輸入命令 git clone --recursive https://github.com/caffe2/caffe2.git && cd caffe2 ）下載 caffe2 源碼並解壓進入 caffe2 文件夾。
修改配置文件
caffe需要自己配置，對於caffe2，使用 cmake 配置，可 參考下面的構建安裝部分。
添加環境變量
終端輸入 sudo gedit ~/.bashrc 打開 “.bashrc” 文件，在文件末尾加入如下代碼並保存：
#caffe2 #echo $PYTHONPATH export PYTHONPATH=/usr/local:$PYTHONPATH export PYTHONPATH=$PYTHONPATH:/home/cow/pytorch/build #echo $LD_LIBRARY_PATH export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH
輸入 source ~/.bashrc 加載新的環境變量.
五、
構建安裝
進入caffe2的根目錄，終端執行如下命令，不報錯誤，代表安裝成功！( -j$(nproc) 代表使用最大的線程編譯，當然也可以手動指定，如 make -j4 )
# This will build Caffe2 in an isolated directory so that Caffe2 source is # unaffected mkdir build && cd build # This configures the build and finds which libraries it will include in the # Caffe2 installation. The output of this command is very helpful in debugging cmake .. -DBUILD_TEST # This actually builds and installs Caffe2 from makefiles generated from the # above configuration step sudo make install -j$(nproc)
執行完 cmake .. 終端輸出：
$ echo $PYTHONPATH /usr/local:/home/cow/pytorch/build $ mkdir build && cd build $ cmake .. -- The CXX compiler identification is GNU 5.4.0 -- The C compiler identification is GNU 5.4.0 -- Check for working CXX compiler: /usr/bin/c++ -- Check for working CXX compiler: /usr/bin/c++ -- works -- Detecting CXX compiler ABI info -- Detecting CXX compiler ABI info - done -- Detecting CXX compile features -- Detecting CXX compile features - done -- Check for working C compiler: /usr/bin/cc -- Check for working C compiler: /usr/bin/cc -- works -- Detecting C compiler ABI info -- Detecting C compiler ABI info - done -- Detecting C compile features -- Detecting C compile features - done -- Performing Test CAFFE2_LONG_IS_INT32_OR_64 -- Performing Test CAFFE2_LONG_IS_INT32_OR_64 - Success -- Does not need to define long separately. -- Performing Test CAFFE2_EXCEPTION_PTR_SUPPORTED -- Performing Test CAFFE2_EXCEPTION_PTR_SUPPORTED - Success -- std::exception_ptr is supported. -- Performing Test CAFFE2_IS_NUMA_AVAILABLE -- Performing Test CAFFE2_IS_NUMA_AVAILABLE - Success -- NUMA is available -- Performing Test CAFFE2_NEED_TO_TURN_OFF_DEPRECATION_WARNING -- Performing Test CAFFE2_NEED_TO_TURN_OFF_DEPRECATION_WARNING - Success -- Performing Test CAFFE2_COMPILER_SUPPORTS_AVX2_EXTENSIONS -- Performing Test CAFFE2_COMPILER_SUPPORTS_AVX2_EXTENSIONS - Success -- Current compiler supports avx2 extention. Will build perfkernels. -- Build type not set - defaulting to Release -- Looking for pthread.h -- Looking for pthread.h - found -- Looking for pthread_create -- Looking for pthread_create - not found -- Looking for pthread_create in pthreads -- Looking for pthread_create in pthreads - not found -- Looking for pthread_create in pthread -- Looking for pthread_create in pthread - found -- Found Threads: TRUE -- Caffe2: Found protobuf with old-style protobuf targets. -- Caffe2 protobuf include directory: -- Found Git: /usr/bin/git (found version "2.7.4") -- The BLAS backend of choice:Eigen -- Could NOT find NNPACK (missing: NNPACK_INCLUDE_DIR NNPACK_LIBRARY PTHREADPOOL_LIBRARY CPUINFO_LIBRARY) -- Brace yourself, we are building NNPACK -- The ASM compiler identification is GNU -- Found assembler: /usr/bin/cc -- Found PythonInterp: /usr/bin/python (found version "2.7.12") -- Check if compiler accepts -pthread -- Check if compiler accepts -pthread - yes -- Caffe2: Cannot find gflags automatically. Using legacy find. -- Found gflags: /usr/include -- Caffe2: Found gflags (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/libgflags.so) -- Caffe2: Cannot find glog automatically. Using legacy find. -- Found glog: /usr/include -- Caffe2: Found glog (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/libglog.so) -- git Version: v0.0.0 -- Version: 0.0.0 -- Performing Test HAVE_CXX_FLAG_STD_CXX11 -- Performing Test HAVE_CXX_FLAG_STD_CXX11 - Success -- Performing Test HAVE_CXX_FLAG_WALL -- Performing Test HAVE_CXX_FLAG_WALL - Success -- Performing Test HAVE_CXX_FLAG_WEXTRA -- Performing Test HAVE_CXX_FLAG_WEXTRA - Success -- Performing Test HAVE_CXX_FLAG_WSHADOW -- Performing Test HAVE_CXX_FLAG_WSHADOW - Success -- Performing Test HAVE_CXX_FLAG_WERROR -- Performing Test HAVE_CXX_FLAG_WERROR - Success -- Performing Test HAVE_CXX_FLAG_PEDANTIC -- Performing Test HAVE_CXX_FLAG_PEDANTIC - Success -- Performing Test HAVE_CXX_FLAG_PEDANTIC_ERRORS -- Performing Test HAVE_CXX_FLAG_PEDANTIC_ERRORS - Success -- Performing Test HAVE_CXX_FLAG_WSHORTEN_64_TO_32 -- Performing Test HAVE_CXX_FLAG_WSHORTEN_64_TO_32 - Failed -- Performing Test HAVE_CXX_FLAG_WFLOAT_EQUAL -- Performing Test HAVE_CXX_FLAG_WFLOAT_EQUAL - Success -- Performing Test HAVE_CXX_FLAG_FSTRICT_ALIASING -- Performing Test HAVE_CXX_FLAG_FSTRICT_ALIASING - Success -- Performing Test HAVE_CXX_FLAG_WZERO_AS_NULL_POINTER_CONSTANT -- Performing Test HAVE_CXX_FLAG_WZERO_AS_NULL_POINTER_CONSTANT - Success -- Performing Test HAVE_CXX_FLAG_WSTRICT_ALIASING -- Performing Test HAVE_CXX_FLAG_WSTRICT_ALIASING - Success -- Performing Test HAVE_CXX_FLAG_WD654 -- Performing Test HAVE_CXX_FLAG_WD654 - Failed -- Performing Test HAVE_CXX_FLAG_WTHREAD_SAFETY -- Performing Test HAVE_CXX_FLAG_WTHREAD_SAFETY - Failed -- Performing Test HAVE_CXX_FLAG_COVERAGE -- Performing Test HAVE_CXX_FLAG_COVERAGE - Success -- Performing Test HAVE_STD_REGEX -- Performing Test HAVE_STD_REGEX -- Performing Test HAVE_STD_REGEX -- success -- Performing Test HAVE_GNU_POSIX_REGEX -- Performing Test HAVE_GNU_POSIX_REGEX -- Performing Test HAVE_GNU_POSIX_REGEX -- failed to compile -- Performing Test HAVE_POSIX_REGEX -- Performing Test HAVE_POSIX_REGEX -- Performing Test HAVE_POSIX_REGEX -- success -- Performing Test HAVE_STEADY_CLOCK -- Performing Test HAVE_STEADY_CLOCK -- Performing Test HAVE_STEADY_CLOCK -- success -- Found LMDB: /usr/include -- Found lmdb (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/liblmdb.so) -- Found LevelDB: /usr/include -- Found LevelDB (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/libleveldb.so) -- Found Snappy: /usr/include -- Found Snappy (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/libsnappy.so) -- Found Numa: /usr/include -- Found Numa (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/libnuma.so) -- OpenCV found (/usr/share/OpenCV) CMake Warning at cmake/Dependencies.cmake:270 (find_package): By not providing "FindEigen3.cmake" in CMAKE_MODULE_PATH this project has asked CMake to find a package configuration file provided by "Eigen3", but CMake did not find one. Could not find a package configuration file provided by "Eigen3" with any of the following names: Eigen3Config.cmake eigen3-config.cmake Add the installation prefix of "Eigen3" to CMAKE_PREFIX_PATH or set "Eigen3_DIR" to a directory containing one of the above files. If "Eigen3" provides a separate development package or SDK, be sure it has been installed. Call Stack (most recent call first): CMakeLists.txt:101 (include) -- Did not find system Eigen. Using third party subdirectory. -- Found PythonInterp: /usr/bin/python (found suitable version "2.7.12", minimum required is "2.7") -- Found PythonLibs: /usr/lib/x86_64-linux-gnu/libpython2.7.so (found suitable version "2.7.12", minimum required is "2.7") -- Found NumPy: /usr/local/lib/python2.7/dist-packages/numpy/core/include (found version "1.13.3") -- NumPy ver. 1.13.3 found (include: /usr/local/lib/python2.7/dist-packages/numpy/core/include) -- Could NOT find pybind11 (missing: pybind11_INCLUDE_DIR) -- Found MPI_C: /usr/lib/openmpi/lib/libmpi.so -- Found MPI_CXX: /usr/lib/openmpi/lib/libmpi_cxx.so;/usr/lib/openmpi/lib/libmpi.so -- MPI support found -- MPI compile flags: -- MPI include path: /usr/lib/openmpi/include/openmpi/opal/mca/event/libevent2021/libevent/usr/lib/openmpi/include/openmpi/opal/mca/event/libevent2021/libevent/include/usr/lib/openmpi/include/usr/lib/openmpi/include/openmpi -- MPI LINK flags path: -Wl,-rpath -Wl,/usr/lib/openmpi/lib -Wl,--enable-new-dtags -- MPI libraries: /usr/lib/openmpi/lib/libmpi_cxx.so/usr/lib/openmpi/lib/libmpi.so CMake Warning at cmake/Dependencies.cmake:324 (message): OpenMPI found, but it is not built with CUDA support. Call Stack (most recent call first): CMakeLists.txt:101 (include) -- Found CUDA: /usr/local/cuda-8.0 (found suitable version "8.0", minimum required is "7.0") -- Found CUDNN: /usr/local/cuda-8.0/include -- Caffe2: CUDA detected: 8.0 -- Found cuDNN: v6.0.21 (include: /usr/local/cuda-8.0/include, library: /usr/local/cuda-8.0/lib64/libcudnn.so) -- Automatic GPU detection failed. Building for all known architectures. -- Added CUDA NVCC flags for: sm_20 sm_21 sm_30 sm_35 sm_50 sm_52 sm_60 sm_61 -- Could NOT find NCCL (missing: NCCL_INCLUDE_DIRS NCCL_LIBRARIES) -- Could NOT find CUB (missing: CUB_INCLUDE_DIR) -- Could NOT find Gloo (missing: Gloo_INCLUDE_DIR Gloo_LIBRARY) -- MPI include path: /usr/lib/openmpi/include/openmpi/opal/mca/event/libevent2021/libevent/usr/lib/openmpi/include/openmpi/opal/mca/event/libevent2021/libevent/include/usr/lib/openmpi/include/usr/lib/openmpi/include/openmpi -- MPI libraries: /usr/lib/openmpi/lib/libmpi_cxx.so/usr/lib/openmpi/lib/libmpi.so -- CUDA detected: 8.0 -- Found libcuda: /usr/local/cuda-8.0/lib64/stubs/libcuda.so -- Found libnvrtc: /usr/local/cuda-8.0/lib64/libnvrtc.so -- Found nccl: /home/liu/sfw/dlapp/caffe2/third_party/nccl/build/include CMake Warning at cmake/Dependencies.cmake:457 (message): mobile opengl is only used in android or ios builds. Call Stack (most recent call first): CMakeLists.txt:101 (include) CMake Warning at cmake/Dependencies.cmake:533 (message): Metal is only used in ios builds. Call Stack (most recent call first): CMakeLists.txt:101 (include) -- GCC 5.4.0: Adding gcc and gcc_s libs to link line -- Include NCCL operators -- Including image processing operators -- Excluding video processing operators due to no opencv -- Excluding mkl operators as we are not using mkl -- Include Observer library -- Using lib/python2.7/dist-packages as python relative installation path -- Automatically generating missing __init__.py files. -- -- ******** Summary ******** -- General: -- CMake version : 3.5.1 -- CMake command : /usr/bin/cmake -- Git version : v0.8.1-1314-gd8770f8 -- System : Linux -- C++ compiler : /usr/bin/c++ -- C++ compiler version : 5.4.0 -- Protobuf compiler : /usr/bin/protoc -- Protobuf include path : /usr/include -- Protobuf libraries : optimized;/usr/lib/x86_64-linux-gnu/libprotobuf.so;debug;/usr/lib/x86_64-linux-gnu/libprotobuf.so;-lpthread -- BLAS : Eigen -- CXX flags : -O2 -fPIC -Wno-narrowing -Wno-invalid-partial-specialization -- Build type : Release -- Compile definitions : -- -- BUILD_BINARY : ON -- BUILD_DOCS : OFF -- BUILD_PYTHON : ON -- Python version : 2.7.12 -- Python includes : /usr/include/python2.7 -- BUILD_SHARED_LIBS : ON -- BUILD_TEST : ON -- USE_ATEN : OFF -- USE_ASAN : OFF -- USE_CUDA : ON -- CUDA version : 8.0 -- CuDNN version : 6.0.21 -- CUDA root directory : /usr/local/cuda-8.0 -- CUDA library : /usr/local/cuda-8.0/lib64/stubs/libcuda.so -- CUDA NVRTC library : /usr/local/cuda-8.0/lib64/libnvrtc.so -- CUDA runtime library: /usr/local/cuda-8.0/lib64/libcudart.so -- CUDA include path : /usr/local/cuda-8.0/include -- NVCC executable : /usr/local/cuda-8.0/bin/nvcc -- CUDA host compiler : /usr/bin/cc -- USE_EIGEN_FOR_BLAS : 1 -- USE_FFMPEG : OFF -- USE_GFLAGS : ON -- USE_GLOG : ON -- USE_GLOO : ON -- USE_LEVELDB : ON -- LevelDB version : 1.18 -- Snappy version : 1.1.3 -- USE_LITE_PROTO : OFF -- USE_LMDB : ON -- LMDB version : 0.9.17 -- USE_METAL : OFF -- USE_MKL : -- USE_MOBILE_OPENGL : OFF -- USE_MPI : ON -- USE_NCCL : ON -- USE_NERVANA_GPU : OFF -- USE_NNPACK : ON -- USE_OBSERVERS : ON -- USE_OPENCV : ON -- OpenCV version : 2.4.9.1 -- USE_OPENMP : OFF -- USE_PROF : OFF -- USE_REDIS : OFF -- USE_ROCKSDB : OFF -- USE_THREADS : ON -- USE_ZMQ : OFF -- Configuring done -- Generating done -- Build files have been written to: /home/cow/pytorch/build
caffe2默認被安裝在根目錄下/usr/local/，當然你也可以在配置時修改安裝目錄。
六、
6.1. Verify that the Caffe2 python module can be properly invoked$ python -c 'from caffe2.python import core' 2>/dev/null && echo "Success" || echo "Failure"
6.2 Verify that Caffe2 can run with GPU support$ python2 -c 'from caffe2.python import workspace; print(workspace.NumCudaDevices())'
The installation is now complete. We can now start using Caffe2 for deep learning modeling and implementation. If you have problem with your Caffe2 installation, simply write it in the comment section.
6.3測試caffe2是否安裝成功
cd ~ && python -c 'from caffe2.python import core' 2>/dev/null && echo "Success" || echo "Failure"
如果是failure，試着cd到.../pytorch/build的文件夾里，然后執行
python -c 'from caffe2.python import core' 2>/dev/null
如果successful，說明是環境變量的設置問題，如果還是失敗，則會有具體的提示。
配置環境變量，編輯~/.bashrc
sudo gedit ~/.bashrc
添加以下內容：
export PYTHONPATH=/usr/local:/usr/local/lib:$PYTHONPATH
export PYTHONPATH=$PYTHONPATH:/home/....../pytorch/build (后面路徑為caffe2的編譯路徑，在pytorch/build中，命令行輸入pwd可以得到這個路徑)
export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH
七、sudo make install 時報錯:
problem1：
mpi_test.cc.o: undefined reference to symbol '_ZN3MPI8Datatype4FreeEv
Solved：
You should also change 'option(USE_MPI "Use MPI" ON)' to'option(USE_MPI "Use MPI" OFF)' in the file 'CMakeLists.txt'。And run the commend:
cmake .. -DBUILD_TEST=OFF
Reference：
安裝caffe2的文件
https://blog.csdn.net/enjoyyl/article/details/79521685
官網：
https://caffe2.ai/docs/getting-started.html?platform=ubuntu&configuration=compile#install-with-gpu-support
https://caffe2.ai/docs/faq.html
https://tech.amikelive.com/node-706/comprehensive-guide-installing-caffe2-with-gpu-support-by-building-from-source-on-ubuntu-16-04/
首先安裝依賴及GLOG
https://github.com/caffe2/caffe2/issues/1810
測試caffe2
https://blog.csdn.net/cym1990/article/details/79409476
錯誤解決
https://blog.csdn.net/xiangxianghehe/article/details/70171342
python2.7換python3.5
https://blog.csdn.net/u013842516/article/details/80604409
libcudnn問題
https://askubuntu.com/questions/1025928/why-do-i-get-sbin-ldconfig-real-usr-local-cuda-lib64-libcudnn-so-7-is-not-a
https://devtalk.nvidia.com/default/topic/1032114/tensorrt-4-installation-libcudnn-so-7-is-not-a-symbolic-link/
install cuda TK8 and tensorflow in clean Ubuntu16.04
http://queirozf.com/entries/installing-cuda-tk-and-tensorflow-on-a-clean-ubuntu-16-04-install#-sbin-ldconfig-real-usr-local-cuda-lib64-libcudnn-so-5-is-not-a-symbolic-link
u盤安裝ubuntu16.04
https://blog.csdn.net/chy555chy/article/details/61191771