Caffe在Mac上用Python 3.6編譯錯誤

Question

除了this other question，我還嘗試在Mac OS Sierra Sierra 10.12.6 上安裝Caffe，但沒有Anaconda。我按照official instructions來安裝它。

輸入make all時出現問題。終端拋出了8個左右的錯誤，都與boost庫和文件「shared_ptr.hpp」有關。這是其中的一個錯誤：

1 error generated. 
make: *** [.build_release/src/caffe/layers/accuracy_layer.o] Error 1 
In file included from src/caffe/data_transformer.cpp:8: 
In file included from ./include/caffe/data_transformer.hpp:6: 
In file included from ./include/caffe/blob.hpp:8: 
./include/caffe/common.hpp:4:10: fatal error: 'boost/shared_ptr.hpp' file not found 
#include <boost/shared_ptr.hpp> 

我通過Brew安裝了boost。這裏是我的Makefile.config文件。我只想爲Caffe使用CPU。

## 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 := atlas 
# 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/lib/python2.7/dist-packages/numpy/core/include 
# Anaconda Python distribution is quite popular. Include path: 
# Verify anaconda location, sometimes it's in root. 
# ANACONDA_HOME := /Applications/anaconda 
# PYTHON_INCLUDE := $(ANACONDA_HOME)/include \ 
#  $(ANACONDA_HOME)/include/python3.6m \ 
#  $(ANACONDA_HOME)/lib/python3.6/site-packages/numpy/core/include 

# Uncomment to use Python 3 (default is Python 2) 
PYTHON_LIBRARIES := boost_python3 python3.6m 
PYTHON_INCLUDE := /Library/Frameworks/Python.framework/Versions/3.6/include/python3.6m \ 
       /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/numpy/core/include 

# We need to be able to find libpythonX.X.so or .dylib. 
PYTHON_LIB := /usr/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 ?= @ 

我在做什麼錯？任何線索？謝謝。

Answer 1

我還沒有與Mac + CMake的工作，但作爲一種解決方法，你可以簡單地添加你的加速直接向包括：

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

在Makefile.config （您可能會需要增加升壓庫路徑：

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

）