LIB_BASE:= /u/amo-d0/projects/caffe_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# 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-7.0
# 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
# BLAS choice:# atlas for ATLAS (default)# mkl for MKL# open for OpenBlasBLAS:= 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# 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.appMATLAB_DIR:= /u/osp-d1/matlab2014a
# 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:=$(HOME)/anaconda
PYTHON_INCLUDE:=$(ANACONDA_HOME)/include \$(ANACONDA_HOME)/include/python2.7
# $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include \# We need to be able to find libpythonX.X.so or .dylib.# PYTHON_LIB := /usr/libPYTHON_LIB:=$(ANACONDA_HOME)/lib
# Whatever else you find you need goes here.INCLUDE_DIRS:=$(PYTHON_INCLUDE) /usr/local/include
LIBRARY_DIRS:=$(PYTHON_LIB) /usr/local/lib /usr/lib /u/amo-d0/projects/caffe_lib/lib
INCLUDE_DIRS+=$(LIB_BASE)/include
LIBRARY_DIRS+=$(LIB_BASE)/lib
LIBRARY_DIRS+=$(ANACONDA_HOME)/lib
INCLUDE_DIRS+=$(ANACONDA_HOME)/include/python2.7
INCLUDE_DIRS+=$(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include
# 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 := 1BUILD_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 := 1# enable pretty build (comment to see full commands)Q?= @
NOTE: Until we get CUDA 7 access on our standard lab machines, this will only run from Osprey.
- create a new repo on bitbucket
- clone down the empty repo
- git remote add bvlc https://github.com/BVLC/caffe.git
- git pull bvlc master
- git push -u origin master
- copy attached Makefile.config and setup_paths.sh into root of repository
- update ANACONDA_HOME in Makefile.config
- update CAFFE_DIST and ANACONDA_HOME in setup_paths.sh
From Osprey:
- source setup_paths.sh (if not in your .bashrc)
- make dist -j 20
- make matcaffe
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