INCLUDE_DIRS : = $ (PYTHON_INCLUDE ) /usr /local /include /usr /include /hdf5 /serial WITH_PYTHON_LAYER : = 1 # Whatever else you find you need goes here. #PYTHON_LIB := $(ANACONDA_HOME)/lib # Homebrew installs numpy in a non standard path (keg only) # PYTHON_INCLUDE += $(dir $(shell python -c 'import re print(re._file_)'))/include # PYTHON_LIB += $(shell brew -prefix numpy)/lib # Uncomment to support layers written in Python (will link against Python libs)
# We need to be able to find libpythonX.X.so or. PYTHON_INCLUDE : = /usr /include /python3. PYTHON_LIBRARIES : = boost_python -p圓6 python3. #ANACONDA_HOME := /home/yuyang/anaconda3/envs/caffe #PYTHON_LIBRARIES := boost_python3 python3.5m #PYTHON_INCLUDE := $(ANACONDA_HOME)/include \ # $(ANACONDA_HOME)/include/python3.5m \ # $(ANACONDA_HOME)/lib/python3.5/site-packages/numpy/core/include # Uncomment to use Python 3 (default is Python 2) Include path: # Verify anaconda location, sometimes it's in root. #PYTHON_INCLUDE := /usr/include/python2.7 \ # /usr/lib/python2.7/dist-packages/numpy/core/include # Anaconda Python distribution is quite popular. # We need to be able to find Python.h and numpy/arrayobject.h. # MATLAB_DIR := /usr/local # MATLAB_DIR := /Applications/MATLAB_R2012b.app # NOTE: this is required only if you will compile the python interface. # MATLAB directory should contain the mex binary in /bin. # 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. # Custom (MKL/ATLAS/OpenBLAS) include and lib directories. # BLAS choice: # atlas for ATLAS (default) # mkl for MKL # open for OpenBlas gencode arch =compute_61 ,code =compute_61 # For CUDA = 9.0, comment the *_20 and *_21 lines for compatibility.ĬUDA_ARCH : = -gencode arch =compute_61 ,code =sm_61 \
Caffe anaconda distribution install#
# 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. 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.
OPENCV_VERSION : = 3 # To customize your choice of compiler, uncomment and set the following.
Caffe anaconda distribution code#
# CPU_ONLY := 1 # uncomment to disable IO dependencies and corresponding data layers # USE_OPENCV := 0 # USE_LEVELDB := 0 # USE_LMDB := 0 # This code is taken from # USE_HDF5 := 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 USE_CUDNN : = 1 # CPU-only switch (uncomment to build without GPU support). # Refer to # Contributions simplifying and improving our build system are welcome! # cuDNN acceleration switch (uncomment to build with cuDNN).
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