在 Jetson-TK1 板上构建 caffe 的错误
Errors in building caffe on Jetson-TK1 board
我正在我的 Jetson-TK1 板上构建咖啡。主板运行s Ubuntu Linux 32bit。我的Makefile.config如下
## 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-6.5
# 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 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_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
# 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/lib
# 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 /usr/local/hdf5/include
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/local/hdf5/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 $LIBRARY_DIRS.)
# USE_PKG_CONFIG := 1
BUILD_DIR := build
DISTRIBUTE_DIR := distribute
# Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171
DEBUG := 1
# The ID of the GPU that 'make runtest' will use to run unit tests.
TEST_GPUID := 0
# enable pretty build (comment to see full commands)
Q ?= @
我可以 make all 成功。
当我 运行 make test 时，错误就来了。
错误是
ubuntu@tegra-ubuntu:/opt/caffee$ make test
CXX/LD -o .build_debug/test/test_all.testbin src/caffe/test/test_caffe_main.cpp
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<float>::forward_gpu_bias(float*, float const*)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<double>::backward_gpu_gemm(double const*, double const*, double*)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<double>::backward_gpu_bias(double*, double const*)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<float>::forward_gpu_gemm(float const*, float const*, float*, bool)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<float>::backward_gpu_bias(float*, float const*)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<double>::weight_gpu_gemm(double const*, double const*, double*)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::curandGetErrorString(curandStatus)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<double>::forward_gpu_bias(double*, double const*)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<float>::backward_gpu_gemm(float const*, float const*, float*)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::cublasGetErrorString(cublasStatus_t)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<double>::forward_gpu_gemm(double const*, double const*, double*, bool)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<float>::weight_gpu_gemm(float const*, float const*, float*)'
collect2: error: ld returned 1 exit status
make: *** [.build_debug/test/test_all.testbin] Error 1
ubuntu@tegra-ubuntu:/opt/caffee$
我用的是CUDA-6.5。
这个版本可能有什么问题？
编辑 1：
@Klaus Prinoth 提到的 link 很有用。现在我可以建造了。我还可以为 CPU 和 GPU 测试 build/tools/caffe time --model=models/bvlc_alexnet/deploy.prototxt --gpu=0。但是当我执行 make -j 8 runtest 时，我得到的消息是 Check Failed。我不确定哪里出了问题。消息是
[----------] 5 tests from DBTest/1, where TypeParam = caffe::TypeLMDB
[ RUN ] DBTest/1.TestNext
[ OK ] DBTest/1.TestNext (63 ms)
[ RUN ] DBTest/1.TestSeekToFirst
[ OK ] DBTest/1.TestSeekToFirst (119 ms)
[ RUN ] DBTest/1.TestKeyValue
[ OK ] DBTest/1.TestKeyValue (118 ms)
[ RUN ] DBTest/1.TestWrite
F0807 23:14:56.323696 19992 db.hpp:109] Check failed: mdb_status == 0 (-30792 vs. 0) MDB_MAP_FULL: Environment mapsize limit reached
*** Check failure stack trace: ***
@ 0x4330f060 (unknown)
@ 0x4330ef5c (unknown)
@ 0x4330eb78 (unknown)
@ 0x43310f98 (unknown)
@ 0x43cc2386 caffe::db::LMDBTransaction::Put()
@ 0x155a36 caffe::DBTest_TestWrite_Test<>::TestBody()
@ 0x248d00 testing::internal::HandleExceptionsInMethodIfSupported<>()
@ 0x242124 testing::Test::Run()
@ 0x2421b6 testing::TestInfo::Run()
@ 0x24228a testing::TestCase::Run()
@ 0x242438 testing::internal::UnitTestImpl::RunAllTests()
@ 0x248a88 testing::internal::HandleExceptionsInMethodIfSupported<>()
@ 0x241c26 testing::UnitTest::Run()
@ 0x81314 main
@ 0x43f5f632 (unknown)
make: *** [runtest] Aborted
ubuntu@tegra-ubuntu:/opt/caffe$
这条消息是什么意思？
我按照以下步骤解决了问题。这些是本 link 中提到的步骤。
(1)需要确保安装了所有依赖项。他们是
sudo apt-get install \
libprotobuf-dev protobuf-compiler gfortran \
libboost-dev cmake libleveldb-dev libsnappy-dev \
libboost-thread-dev libboost-system-dev \
libatlas-base-dev libhdf5-serial-dev libgflags-dev \
libgoogle-glog-dev liblmdb-dev gcc-4.7 g++-4.7
因为我不使用 Python，所以我跳过 Python 接口所需的步骤。
(2)获取caffe源
sudo apt-get install git
git clone https://github.com/BVLC/caffe.git
cd caffe
cp Makefile.config.example Makefile.config
(3)需要在make -j 8 runtest之前的src/caffe/util/db.cpp中将1099511627776修改为536870912，否则会导致MDB_MAP_FULL error in runtest。
我的Makefile.config显示在原来的post。
那么你就可以
make -j 8 all
make -j 8 test
make -j 8 runtest
可以使用
测试 CPU 和 GPU 处理的性能差异
对于 GPU：“run build/tools/caffe time --model=models/bvlc_alexnet/deploy.prototxt --gpu=0”
对于CPU：“run build/tools/caffe time --model=models/bvlc_alexnet/deploy.prototxt”
感谢@Klaus Prinoth，给了我 link.
我正在我的 Jetson-TK1 板上构建咖啡。主板运行s Ubuntu Linux 32bit。我的Makefile.config如下
## 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-6.5
# 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 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_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
# 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/lib
# 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 /usr/local/hdf5/include
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/local/hdf5/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 $LIBRARY_DIRS.)
# USE_PKG_CONFIG := 1
BUILD_DIR := build
DISTRIBUTE_DIR := distribute
# Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171
DEBUG := 1
# The ID of the GPU that 'make runtest' will use to run unit tests.
TEST_GPUID := 0
# enable pretty build (comment to see full commands)
Q ?= @
我可以 make all 成功。
当我 运行 make test 时，错误就来了。
错误是
ubuntu@tegra-ubuntu:/opt/caffee$ make test
CXX/LD -o .build_debug/test/test_all.testbin src/caffe/test/test_caffe_main.cpp
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<float>::forward_gpu_bias(float*, float const*)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<double>::backward_gpu_gemm(double const*, double const*, double*)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<double>::backward_gpu_bias(double*, double const*)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<float>::forward_gpu_gemm(float const*, float const*, float*, bool)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<float>::backward_gpu_bias(float*, float const*)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<double>::weight_gpu_gemm(double const*, double const*, double*)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::curandGetErrorString(curandStatus)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<double>::forward_gpu_bias(double*, double const*)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<float>::backward_gpu_gemm(float const*, float const*, float*)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::cublasGetErrorString(cublasStatus_t)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<double>::forward_gpu_gemm(double const*, double const*, double*, bool)'
.build_debug/lib/libcaffe.so: undefined reference to `caffe::BaseConvolutionLayer<float>::weight_gpu_gemm(float const*, float const*, float*)'
collect2: error: ld returned 1 exit status
make: *** [.build_debug/test/test_all.testbin] Error 1
ubuntu@tegra-ubuntu:/opt/caffee$
我用的是CUDA-6.5。
这个版本可能有什么问题？
编辑 1：
@Klaus Prinoth 提到的 link 很有用。现在我可以建造了。我还可以为 CPU 和 GPU 测试 build/tools/caffe time --model=models/bvlc_alexnet/deploy.prototxt --gpu=0。但是当我执行 make -j 8 runtest 时，我得到的消息是 Check Failed。我不确定哪里出了问题。消息是
[----------] 5 tests from DBTest/1, where TypeParam = caffe::TypeLMDB
[ RUN ] DBTest/1.TestNext
[ OK ] DBTest/1.TestNext (63 ms)
[ RUN ] DBTest/1.TestSeekToFirst
[ OK ] DBTest/1.TestSeekToFirst (119 ms)
[ RUN ] DBTest/1.TestKeyValue
[ OK ] DBTest/1.TestKeyValue (118 ms)
[ RUN ] DBTest/1.TestWrite
F0807 23:14:56.323696 19992 db.hpp:109] Check failed: mdb_status == 0 (-30792 vs. 0) MDB_MAP_FULL: Environment mapsize limit reached
*** Check failure stack trace: ***
@ 0x4330f060 (unknown)
@ 0x4330ef5c (unknown)
@ 0x4330eb78 (unknown)
@ 0x43310f98 (unknown)
@ 0x43cc2386 caffe::db::LMDBTransaction::Put()
@ 0x155a36 caffe::DBTest_TestWrite_Test<>::TestBody()
@ 0x248d00 testing::internal::HandleExceptionsInMethodIfSupported<>()
@ 0x242124 testing::Test::Run()
@ 0x2421b6 testing::TestInfo::Run()
@ 0x24228a testing::TestCase::Run()
@ 0x242438 testing::internal::UnitTestImpl::RunAllTests()
@ 0x248a88 testing::internal::HandleExceptionsInMethodIfSupported<>()
@ 0x241c26 testing::UnitTest::Run()
@ 0x81314 main
@ 0x43f5f632 (unknown)
make: *** [runtest] Aborted
ubuntu@tegra-ubuntu:/opt/caffe$
这条消息是什么意思？
我按照以下步骤解决了问题。这些是本 link 中提到的步骤。
(1)需要确保安装了所有依赖项。他们是
sudo apt-get install \
libprotobuf-dev protobuf-compiler gfortran \
libboost-dev cmake libleveldb-dev libsnappy-dev \
libboost-thread-dev libboost-system-dev \
libatlas-base-dev libhdf5-serial-dev libgflags-dev \
libgoogle-glog-dev liblmdb-dev gcc-4.7 g++-4.7
因为我不使用 Python，所以我跳过 Python 接口所需的步骤。
(2)获取caffe源
sudo apt-get install git
git clone https://github.com/BVLC/caffe.git
cd caffe
cp Makefile.config.example Makefile.config
(3)需要在make -j 8 runtest之前的src/caffe/util/db.cpp中将1099511627776修改为536870912，否则会导致MDB_MAP_FULL error in runtest。
我的Makefile.config显示在原来的post。
那么你就可以
make -j 8 all
make -j 8 test
make -j 8 runtest
可以使用
测试 CPU 和 GPU 处理的性能差异对于 GPU：“run build/tools/caffe time --model=models/bvlc_alexnet/deploy.prototxt --gpu=0”
对于CPU：“run build/tools/caffe time --model=models/bvlc_alexnet/deploy.prototxt”
感谢@Klaus Prinoth，给了我 link.