Caffe erreur de compilation avec Python 3.6 sur Mac

Question

Sinon, j'ai également essayé d'installer Caffe avec Python 3.6 sur Mac OS Sierra 10.12.6 mais sans Anaconda. J'ai suivi le official instructions pour l'installer. Le problème est survenu lors de la saisie make all. Le terminal a lancé 8 erreurs environ, toutes liées à la bibliothèque boost et au fichier "shared_ptr.hpp". C'est l'une de ces erreurs:

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> 

J'ai installé boost via Brew. Voici mon fichier Makefile.config. Je veux juste utiliser le CPU pour Caffe.

## 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 ?= @ 

Qu'est-ce que je fais mal? Une idée? THX.

Answer 1

Je n'ai pas travaillé avec Mac + CMake, mais comme une solution de contournement, vous pouvez simplement ajouter votre Boost incluent directement à:

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

En Makefile.config (vous aurez besoin probablement ajouter le coup de pouce bibliothèques chemin vers:

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

)