Ubuntu-安装-theano+caffe-超详细教程

一、说明

二、安装Theano

1. 安装各种包

# 安装gfortran,后面编译过程中会用到

sudo apt-get install gfortran

# 安装blas,Ubuntu下对应的是libopenblas，其它操作系统可能需要安装其它版本的blas——这是个OS相关的。

sudo apt-get install libopenblas-dev

# 安装lapack，Ubuntu下对应的是liblapack-dev，和OS相关。

sudo apt-get install liblapack-dev

# 安装atlas，Ubuntu下对应的是libatlas-base-dev，和OS相关。

sudo apt-get install libatlas-base-dev

# 安装pip

sudo apt-get install python-pip
sudo apt-get install python-dev
sudo apt-get install python-nose
sudo apt-get install g++
sudo apt-get install git

2. 安装numpy和scipy

#安装numpy和scipy

sudo apt-get install python-numpy
sudo apt-get install python-scipy
sudo apt-get install python-sklearn

#卸载numpy和scipy

sudo apt-get remove python-numpy
sudo apt-get remove python-scipy

# 安装numpy

sudo pip install numpy

# 测试numpy

# 如果没有安装python-nose，测试会出错！

python -c "import numpy;numpy.test()"

# 安装scipy

sudo pip install scipy

# 测试scipy

python -c "import scipy;scipy.test()"

3. 安装Theano

# 安装Theano

sudo pip install Theano

# 测试Theano

python -c "import theano;theano.test()"

4. 安装pyCUDA

#安装boost

sudo apt-get install libboost-all-dev

git clone --recursive http://git.tiker.net/trees/pycuda.git cd pycuda
sudo ./configure.py --cuda-root=/usr/local/cuda --cudadrv-lib-dir=/usr/lib/x86_64-linux-gnu --boost-inc-dir=/usr/include --boost-lib-dir=/usr/lib --boost-python-libname=boost_python --boost-thread-libname=boost_thread --no-use-shipped-boost
make -j 4 #电脑核数
sudo python setup.py install

5. 解决cuda_ndarray.cu错误

sudo ldconfig /usr/local/cuda-7.0/lib64

6. 配置Theano

cd ~
vi .theanorc

[cuda]
root=/usr/local/cuda/bin/
[global]
floatX = float32
device = gpu0
[nvcc]
fastmath = True

7. 测试Theano是否在使用GPU

from theano import function, config, shared, sandbox
import theano.tensor as T
import numpy
import time

vlen = 10 * 30 * 768  # 10 x #cores x # threads per core
iters = 1000

rng = numpy.random.RandomState(22)
x = shared(numpy.asarray(rng.rand(vlen), config.floatX))
f = function([], T.exp(x))
print f.maker.fgraph.toposort()
t0 = time.time()
for i in xrange(iters):
r = f()
t1 = time.time()
print 'Looping %d times took' % iters, t1 - t0, 'seconds'
print 'Result is', r
if numpy.any([isinstance(x.op, T.Elemwise) for x in f.maker.fgraph.toposort()]):
print 'Used the cpu'
else:
print 'Used the gpu'

.theanorc

python useGPU.py

sudo ldconfig /usr/local/cuda-7.0/lib64

#错误信息

ERROR (theano.sandbox.cuda): Failed to compile cuda_ndarray.cu: libcublas.so.7.0: cannot open shared object file: No such file or directory

Theano相关资料

/usr/local/cuda/

/usr/local/cuda/bin/

CUDA_ROOT=/usr/local/cuda/bin/

THEANO_FLAGS='cuda.root=/usr/local/cuda/bin/'

[cuda]
root=/usr/local/cuda/bin/

.theanorc

[cuda]
root=/usr/local/cuda/bin/[global]
device = gpu
floatX = float32

gpu0

安装OpenCV

下载OpenCV

#切换路径
cd ~/Downloads/Install-OpenCV-master/Ubuntu
#安装OpenCV的依赖项
sudo ./dependencies.sh

#切换路径
cd 2.4
#修改opencv2_4_9.sh, 添加CUDA_GENERATION
#根据显卡支持Fermi或Kepler做相应的修改。此处以Fermi为例。
sudo gedit opencv2_4_9.sh

cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_TBB=ON -D BUILD_NEW_PYTHON_SUPPORT=ON -D WITH_V4L=ON -D INSTALL_C_EXAMPLES=ON -D INSTALL_PYTHON_EXAMPLES=ON -D BUILD_EXAMPLES=ON -D WITH_QT=ON -D WITH_OPENGL=ON -D ..

cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_TBB=ON -D BUILD_NEW_PYTHON_SUPPORT=ON -D WITH_V4L=ON -D INSTALL_C_EXAMPLES=ON -D INSTALL_PYTHON_EXAMPLES=ON -D BUILD_EXAMPLES=ON -D WITH_QT=ON -D WITH_OPENGL=ON -D CUDA_GENERATION=Fermi ..

..

CUDA_GENERATION=Fermi

#添加执行权限
sudo chmod +x opencv2_4_9.sh
#安装OpenCV
sudo ./opencv2_4_9.sh

安装其它依赖项

安装glog

安装caffe

下载caffe

编辑Makefile.config

unzip caffe-master.zip #本地解压caffe-master
cd /caffe-master #切换路径
vi Makefile.config #编辑Makefile.config

配置Python相关选项

cd python #切换到./caffe-master/python/路径下
for req in $(cat requirements.txt); do sudo pip install $req; done

sudo vi /etc/profile # 编辑profile文件
#在最后面添加以下语句，注意将path换成你的系统下的路径
export PYTHONPATH=/path/to/caffe/python:$PYTHONPATH

安装Matlab

$ chmod a+x Matlab -R

$ sudo ./install

参考文章