caffe配置Makefile.config----ubuntu16.04--重点是matlab的编译

USE_OPENCV := 1
USE_LEVELDB := 1
USE_LMDB := 1
CUSTOM_CXX := g++
CUDA_DIR := /usr/local/cuda-7.5
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
BLAS := atlas
MATLAB_DIR := /home/eric/MATLAB2014/R2014a
PYTHON_INCLUDE := /usr/include/python2.7 \
/usr/lib/python2.7/dist-packages/numpy/core/include
PYTHON_LIB := /usr/local/lib
WITH_PYTHON_LAYER := 1
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu /usr/lib/x86_64-linux-gnu/hdf5/serial
BUILD_DIR := build
DISTRIBUTE_DIR := distribute

sudo make clean
sudo make all -j4
sudo make test -j4
sudo make runtest -j4
sudo make pycaffe -j4
sudo make matcaffe -j4

## Refer to http://caffe.berkeleyvision.org/installation.html
# Contributions simplifying and improving our build system are welcome!BUILD_PYTHON:=
BUILD_MATLAB:=
BUILD_docs:=
BUILD_SHARELIB:=# cuDNN acceleration switch (uncomment to build with cuDNN).
USE_CUDNN := # CPU-only switch (uncomment to build without GPU support).
# CPU_ONLY := # uncomment to disable IO dependencies and corresponding data layers
USE_OPENCV :=
USE_LEVELDB :=
USE_LMDB := # 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 := # 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 := /usr/include
BLAS_LIB := /usr/lib # 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/R2016b
# 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#PYTHON_LIB:=/usr/lib/x86_64-linux-gnu/libpython2.7.so
# 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 (default is Python )
# 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 /usr/local/lib /usr/lib/x86_64-linux-gnu/
# 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 := # 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 := # 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 := # 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 := # The ID of the GPU that 'make runtest' will use to run unit tests.
TEST_GPUID := # enable pretty build (comment to see full commands)
Q ?= @#INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial/
INCLUDE_DIRS := $(INCLUDE_DIRS) /usr/local/include /usr/include/hdf5/serial/
LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_serial_hl hdf5_serialLIBRARY_DIRS:=$(LIBRARIES_DIRS) /usr/lib/x86_64-linux-gnu/hdf5/serial

sea@sea-X550JK:~/caffeM/caffe$ ll matlab/+caffe/
总用量 76
drwxrwxr-x 5 sea sea 4096 11月 9 17:26 ./
drwxrwxr-x 5 sea sea 4096 11月 9 17:26 ../
-rw-rw-r-- 1 sea sea 2930 11月 9 17:26 Blob.m
-rw-rw-r-- 1 sea sea 1207 11月 9 17:26 get_net.m
-rw-rw-r-- 1 sea sea 298 11月 9 17:26 get_solver.m
drwxrwxr-x 2 sea sea 4096 11月 9 17:26 imagenet/
-rw-rw-r-- 1 sea sea 1742 11月 9 17:26 io.m
-rw-rw-r-- 1 sea sea 841 11月 9 17:26 Layer.m
-rw-rw-r-- 1 sea sea 4912 11月 9 17:26 Net.m
drwxrwxr-x 2 sea sea 4096 11月 10 19:48 private/
-rw-rw-r-- 1 sea sea 172 11月 9 17:26 reset_all.m
-rw-rw-r-- 1 sea sea 393 11月 9 17:26 run_tests.m
-rw-rw-r-- 1 sea sea 250 11月 9 17:26 set_device.m
-rw-rw-r-- 1 sea sea 97 11月 9 17:26 set_mode_cpu.m
-rw-rw-r-- 1 sea sea 97 11月 9 17:26 set_mode_gpu.m
-rw-rw-r-- 1 sea sea 1872 11月 9 17:26 Solver.m
drwxrwxr-x 2 sea sea 4096 11月 9 17:26 +test/
-rw-rw-r-- 1 sea sea 110 11月 9 17:26 version.m
sea@sea-X550JK:~/caffeM/caffe$

# /etc/profile: system-wide .profile file for the Bourne shell (sh(1))
# and Bourne compatible shells (bash(1), ksh(1), ash(1), ...).if [ "$PS1" ]; then
if [ "$BASH" ] && [ "$BASH" != "/bin/sh" ]; then
# The file bash.bashrc already sets the default PS1.
# PS1='\h:\w\$ '
if [ -f /etc/bash.bashrc ]; then
. /etc/bash.bashrc
fi
else
if [ "`id -u`" -eq 0 ]; then
PS1='# '
else
PS1='$ '
fi
fi
fiif [ -d /etc/profile.d ]; then
for i in /etc/profile.d/*.sh; do
if [ -r $i ]; then
. $i
fi
done
unset i
fiexport PYTHONPATH=/usr/local:$PYTHONPATH
export PYTHONPATH=$PYTHONPATH:/home/sea/caffe2/buildexport LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATHexport PYTHONPATH=/home/sea/caffeM/caffe/python:$PYTHONPATHexport PATH=$PATH:/home/sea/caffeM/caffe/build/tools/:/usr/local/cuda-8.0/bin
export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib:$LD_LIBRARY_PATHexport PYTHONPATH=$PYTHONPATH:/home/sea/caffeM/caffe/pythonexport PATH=$PATH:/usr/local/MATLAB/R2016b/binexport MATLABDIR=/usr/local/MATLAB/R2016b
export Matlab_mex=/usr/local/MATLAB/R2016b/bin/mex
export Matlab_mexext=/usr/local/MATLAB/R2016b/bin/mexext