2014-02-26 10:59:26 +04:00
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## Refer to http://caffe.berkeleyvision.org/installation.html
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# Contributions simplifying and improving our build system are welcome!
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2014-07-04 05:15:38 +04:00
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# To customize your choice of compiler, uncomment and set the following.
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# N.B. the default for Linux is g++ and the default for OSX is clang++
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# CUSTOM_CXX := g++
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2014-02-03 14:41:44 +04:00
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# CUDA directory contains bin/ and lib/ directories that we need.
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CUDA_DIR := /usr/local/cuda
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2014-06-16 05:07:04 +04:00
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# On Ubuntu 14.04, if cuda tools are installed via
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# "sudo apt-get install nvidia-cuda-toolkit" then use this instead:
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# CUDA_DIR := /usr
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2014-02-03 14:41:44 +04:00
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2014-06-27 19:47:42 +04:00
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# CUDA architecture setting: going with all of them (up to CUDA 5.5 compatible).
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# For the latest architecture, you need to install CUDA >= 6.0 and uncomment
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# the *_50 lines below.
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2014-02-03 14:41:44 +04:00
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CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \
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2014-04-09 02:25:04 +04:00
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-gencode arch=compute_20,code=sm_21 \
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-gencode arch=compute_30,code=sm_30 \
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2014-06-30 12:08:55 +04:00
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-gencode arch=compute_35,code=sm_35 \
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#-gencode arch=compute_50,code=sm_50 \
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#-gencode arch=compute_50,code=compute_50
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2014-02-03 14:41:44 +04:00
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2014-04-15 11:37:06 +04:00
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# BLAS choice:
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# atlas for ATLAS (default)
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# mkl for MKL
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# open for OpenBlas
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BLAS := atlas
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# Custom (MKL/ATLAS/OpenBLAS) include and lib directories.
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# Leave commented to accept the defaults for your choice of BLAS
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# (which should work)!
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# BLAS_INCLUDE := /path/to/your/blas
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# BLAS_LIB := /path/to/your/blas
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2014-02-03 14:41:44 +04:00
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2014-02-26 10:59:26 +04:00
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# This is required only if you will compile the matlab interface.
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# MATLAB directory should contain the mex binary in /bin.
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2014-04-09 03:42:03 +04:00
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# MATLAB_DIR := /usr/local
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2014-02-26 10:59:26 +04:00
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# MATLAB_DIR := /Applications/MATLAB_R2012b.app
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2014-02-03 14:41:44 +04:00
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# NOTE: this is required only if you will compile the python interface.
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# We need to be able to find Python.h and numpy/arrayobject.h.
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2014-04-21 00:38:30 +04:00
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PYTHON_INCLUDE := /usr/local/include/python2.7 \
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2014-04-09 02:41:29 +04:00
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/usr/local/lib/python2.7/dist-packages/numpy/core/include
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2014-02-26 10:59:26 +04:00
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# Anaconda Python distribution is quite popular. Include path:
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2014-04-15 11:36:18 +04:00
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# PYTHON_INCLUDE := $(HOME)/anaconda/include \
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2014-04-09 02:41:29 +04:00
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# $(HOME)/anaconda/include/python2.7 \
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# $(HOME)/anaconda/lib/python2.7/site-packages/numpy/core/include
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2014-02-26 10:59:26 +04:00
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2014-02-03 14:41:44 +04:00
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# We need to be able to find libpythonX.X.so or .dylib.
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PYTHON_LIB := /usr/local/lib
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2014-02-26 10:59:26 +04:00
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# PYTHON_LIB := $(HOME)/anaconda/lib
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2014-02-03 14:41:44 +04:00
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# Whatever else you find you need goes here.
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2014-04-15 11:36:18 +04:00
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INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include
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2014-04-21 00:38:30 +04:00
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LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib
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2014-02-03 14:41:44 +04:00
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2014-02-15 11:28:26 +04:00
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BUILD_DIR := build
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DISTRIBUTE_DIR := distribute
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2014-03-22 02:15:00 +04:00
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2014-06-17 11:00:01 +04:00
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# Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171
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2014-04-09 02:25:04 +04:00
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# DEBUG := 1
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2014-03-30 04:46:39 +04:00
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# The ID of the GPU that 'make runtest' will use to run unit tests.
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TEST_GPUID := 0
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