Some notes on the Makefile.config in 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
"CuDNN is a set of GPU computing acceleration libraries specially designed by NVIDIA for the Deep Learning framework. It is used to achieve high-performance parallel computing. You can open and remove comments when you have a GPU and CuDNN installed.

# CPU-only switch (uncomment to build without GPU support).
#CPU_ONLY: = 1
"Indicates whether to use GPU, if only CPU is turned on here"

# uncomment to disable IO dependencies and corresponding data layers
USE_OPENCV: = 1
"Because you want to use the OpenCV library, you have to open it. The following two options indicate that you choose the third-party library for data management in Caffe. Library. "
# 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
"You can uncomment when you need to read the LMDB file, it is not opened by default."

# Uncomment if you're using OpenCV 3
OPENCV_VERSION: = 2.4.10
"View the opencv version with the pkg-config --modversion opencv command"

# 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 systems use the g ++ compiler by default, and OSX uses clang ++."

# CUDA directory contains bin / and lib / directories that we need.
CUDA_DIR: = / usr / local / cuda
"CUDA installation directory"
# 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
"These parameters need to be based on the computing power of the GPU
(http://blog.csdn.net/jiajunlee/article/details/52067962) to set, the version below 6.0 does not support the computing power of × _50. "

# BLAS choice:
# atlas for ATLAS (default)
# mkl for MKL
# open for OpenBlas
BLAS: = open
"If using the ATLAS calculation library, assign atlas, the MKL calculation library assigns mkl, and OpenBlas assigns 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 library installation directory"

# 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
"Indicate if not installed in standard path"

# 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 installation library directory"

# 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 installation directory"
# 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 library location </ 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
"ID number of GPU used"

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