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  • 在Mac os 10.11 下编译Berkeley caffe

    安装各种补丁和组件,缺啥装啥。

    python 采用 2.7.13 最新版。

    安装工具  homebrew , pip

    很繁琐,但是没难度。

    由于本人macbook pro不支持CUDA,所以不用安装。

    $mvim Makefile.config

    尤其注意  PYTHON_INCLUDE,PYTHON_LIB

    ===

    ## 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

    # CPU-only switch (uncomment to build without GPU support).
    CPU_ONLY := 1

    # uncomment to disable IO dependencies and corresponding data layers
    USE_OPENCV := 0
    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

    # Uncomment if you're using OpenCV 3
    # OPENCV_VERSION := 3

    # 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++

    # CUDA directory contains bin/ and lib/ directories that we need.
    CUDA_DIR := /usr/local/cuda
    # 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 through *_61 lines for compatibility.
    # For CUDA < 8.0, comment the *_60 and *_61 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_52,code=sm_52
    -gencode arch=compute_60,code=sm_60
    -gencode arch=compute_61,code=sm_61
    -gencode arch=compute_61,code=compute_61

    # BLAS choice:
    # atlas for ATLAS (default)
    # mkl for MKL
    # open for OpenBlas
    BLAS := 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 := /path/to/your/blas
    # BLAS_LIB := /path/to/your/blas

    # 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

    # 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

    # 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/local/Cellar/numpy/1.12.1/lib/python2.7/site-packages/numpy/core/include
    # 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

    # We need to be able to find libpythonX.X.so or .dylib.
    PYTHON_LIB := /usr/local/Cellar/python/2.7.13/Frameworks/Python.framework/Versions/2.7/lib
    # 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

    # NCCL acceleration switch (uncomment to build with NCCL)
    # https://github.com/NVIDIA/nccl (last tested version: v1.2.3-1+cuda8.0)
    # USE_NCCL := 1

    # 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

    # enable pretty build (comment to see full commands)
    Q ?= @

    ===

    编译:

    make clean; make all -j8;

    make runtest

    make pytest;

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  • 原文地址:https://www.cnblogs.com/GrantYu/p/6642853.html
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