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  • caffe中Makefile.config详解

    ## Refer to http://caffe.berkeleyvision.org/installation.html 

    # Contributions simplifying and improving our build system are welcome! 

    # cuDNN acceleration switch (uncomment to build with cuDNN). 

    # USE_CUDNN := 1 

    "CuDNN是NVIDIA专门针对Deep Learning框架设计的一套GPU计算加速库,用于实现高性能的并行计算,在有GPU并且安装CuDNN的情况下可以打开即将注释去掉。" 

    # CPU-only switch (uncomment to build without GPU support). 

    #CPU_ONLY := 1 

    "表示是否用GPU,如果只有CPU这里要打开" 

    # uncomment to disable IO dependencies and corresponding data layers 

    USE_OPENCV := 1 

    "因为要用到OpenCV库所以要打开,下面这两个选项表示是选择Caffe的数据管理第三方库,两者都不打开 Caffe默认用的是LMDB,这两者均是嵌入式数据库管理系统编程库。" 

    # USE_LEVELDB := 0 

    # USE_LMDB := 0 

    # uncomment to allow MDB_NOLOCK when reading LMDB files (only if necessary) 

    #   You should not set this flag if you will be reading LMDBs with any 

    #   possibility of simultaneous read and write 

    # ALLOW_LMDB_NOLOCK := 1 

    "当需要读取LMDB文件时可以取消注释,默认不打开。" 

    # Uncomment if you're using OpenCV 3 

    OPENCV_VERSION := 2.4.10 

    "用pkg-config --modversion opencv命令查看opencv版本" 

    # To customize your choice of compiler, uncomment and set the following. 

    # N.B. the default for Linux is g++ and the default for OSX is clang++ 

    # CUSTOM_CXX := g++ 

    "linux系统默认使用g++编译器,OSX则是clang++。" 

    # CUDA directory contains bin/ and lib/ directories that we need. 

    CUDA_DIR := /usr/local/cuda 

    "CUDA的安装目录" 

    # On Ubuntu 14.04, if cuda tools are installed via 

    # "sudo apt-get install nvidia-cuda-toolkit" then use this instead: 

    # CUDA_DIR := /usr 

    # CUDA architecture setting: going with all of them. 

    # For CUDA < 6.0, comment the *_50 lines for compatibility. 

    CUDA_ARCH := -gencode arch=compute_20,code=sm_20  

            -gencode arch=compute_20,code=sm_21  

            -gencode arch=compute_30,code=sm_30  

            -gencode arch=compute_35,code=sm_35  

            -gencode arch=compute_50,code=sm_50  

            -gencode arch=compute_50,code=compute_50 

    "这些参数需要根据GPU的计算能力来进行设置,6.0以下的版本不支持×_50的计算能力。" 

    # BLAS choice: 

    # atlas for ATLAS (default) 

    # mkl for MKL 

    # open for OpenBlas 

    BLAS := open 

    "如果用的是ATLAS计算库则赋值atlas,MKL计算库则用mkl赋值,OpenBlas则赋值open。" 

    # Custom (MKL/ATLAS/OpenBLAS) include and lib directories. 

    # Leave commented to accept the defaults for your choice of BLAS 

    # (which should work)! 

    BLAS_INCLUDE := /usr/local/OpenBlas/include 

    BLAS_LIB := /usr/local/OpenBlas/lib 

    "blas库安装目录" 

    # Homebrew puts openblas in a directory that is not on the standard search path 

    # BLAS_INCLUDE := $(shell brew --prefix openblas)/include 

    # BLAS_LIB := $(shell brew --prefix openblas)/lib 

    "如果不是安装在标准路径则要指明" 

    # This is required only if you will compile the matlab interface. 

    # MATLAB directory should contain the mex binary in /bin. 

    # MATLAB_DIR := /usr/local 

    # MATLAB_DIR := /Applications/MATLAB_R2012b.app 

    "matlab安装库的目录" 

    # NOTE: this is required only if you will compile the python interface. 

    # We need to be able to find Python.h and numpy/arrayobject.h. 

    PYTHON_INCLUDE := /usr/include/python2.7  

            /usr/lib/python2.7/dist-packages/numpy/core/include 

    "python安装目录" 

    # Anaconda Python distribution is quite popular. Include path: 

    # Verify anaconda location, sometimes it's in root. 

    # ANACONDA_HOME := $(HOME)/anaconda 

    # PYTHON_INCLUDE := $(ANACONDA_HOME)/include  

            # $(ANACONDA_HOME)/include/python2.7  

            # $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include  

    # Uncomment to use Python 3 (default is Python 2) 

    # PYTHON_LIBRARIES := boost_python3 python3.5m 

    # PYTHON_INCLUDE := /usr/include/python3.5m  

    #                 /usr/lib/python3.5/dist-packages/numpy/core/include 

    # We need to be able to find libpythonX.X.so or .dylib. 

    PYTHON_LIB := /usr/lib 

    <font color="green">python库位置</font> 

    # PYTHON_LIB := $(ANACONDA_HOME)/lib 

    # Homebrew installs numpy in a non standard path (keg only) 

    # PYTHON_INCLUDE += $(dir $(shell python -c 'import numpy.core; print(numpy.core.__file__)'))/include 

    # PYTHON_LIB += $(shell brew --prefix numpy)/lib 

    # Uncomment to support layers written in Python (will link against Python libs) 

    WITH_PYTHON_LAYER := 1 

    # Whatever else you find you need goes here. 

    INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include 

    LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib 

    # If Homebrew is installed at a non standard location (for example your home directory) and you use it for general dependencies 

    # INCLUDE_DIRS += $(shell brew --prefix)/include 

    # LIBRARY_DIRS += $(shell brew --prefix)/lib 

    # Uncomment to use `pkg-config` to specify OpenCV library paths. 

    # (Usually not necessary -- OpenCV libraries are normally installed in one of the above $LIBRARY_DIRS.) 

    # USE_PKG_CONFIG := 1 

    # N.B. both build and distribute dirs are cleared on `make clean` 

    BUILD_DIR := build 

    DISTRIBUTE_DIR := distribute 

    # Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171 

    # DEBUG := 1 

    # The ID of the GPU that 'make runtest' will use to run unit tests. 

    TEST_GPUID := 0 

    "所用的GPU的ID编号" 

    # enable pretty build (comment to see full commands) 

    Q ?= @

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  • 原文地址:https://www.cnblogs.com/jxhd1/p/8465089.html
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