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Ubuntu 16.04+CUDA7.5+Caffe深度學習環境搭建

2020-06-16 17:04:49

詳細介紹在Ubuntu 16.04下搭建CUDA7.5+Caffe深度學習環境的過程步驟。

1.安裝Ubuntu 16.04

 省略。不懂可以自行百度,系統安裝後安裝必要的更新和工具。

sudo apt update
sudo apt-get upgrade
sudo apt-get install vim
sudo apt-get install cmake

2.安裝顯示卡驅動

進入all setting->Software Update,更換英偉達361.42驅動,重新啟動電腦,使用nvidia-smi測試是否成功。

3.安裝cuda

(1)安裝必要的依賴庫

ca-certificates-java 
default-jre 
default-jre-headless
fonts-dejavu-extra 
freeglut3 
freeglut3-dev 
java-common 
libatk-wrapper-java 
libatk-wrapper-java-jni
libdrm-dev 
libgl1-mesa-dev 
libglu1-mesa-dev 
libgnomevfs2-0 
libgnomevfs2-common 
libice-dev 
libpthread-stubs0-dev 
libsctp1 
libsm-dev 
libx11-dev 
libx11-doc 
libx11-xcb-dev 
libxau-dev 
libxcb-dri2-0-dev 
libxcb-dri3-dev 
libxcb-glx0-dev 
libxcb-present-dev 
libxcb-randr0-dev 
libxcb-render0-dev 
libxcb-shape0-dev 
libxcb-sync-dev 
libxcb-xfixes0-dev 
libxcb1-dev 
libxdamage-dev 
libxdmcp-dev 
libxext-dev 
libxfixes-dev 
libxi-dev 
libxmu-dev 
libxmu-headers 
libxshmfence-dev 
libxt-dev 
libxxf86vm-dev 
lksctp-tools 
mesa-common-dev 
openjdk-7-jre 
openjdk-7-jre-headless 
tzdata-java 
x11proto-core-dev 
x11proto-damage-dev
x11proto-dri2-dev 
x11proto-fixes-dev 
x11proto-gl-dev 
x11proto-input-dev 
x11proto-kb-dev 
x11proto-xext-dev 
x11proto-xf86vidmode-dev 
xorg-sgml-doctools 
xtrans-dev 
libgles2-mesa-dev 
nvidia-modprobe 
build-essential

(2)安裝cuda-toolkit

① 安裝cuda_7.5.18_linux.run

sudo ./cuda_7.5.18_linux.run --override

安裝過程如下:

Do you accept the previously read EULA? (accept/decline/quit): accept
You are attempting to install on an unsupported configuration. Do you wish to continue? ((y)es/(n)o) [ default is no ]: y
Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 352.39? ((y)es/(n)o/(q)uit): n
Install the CUDA 7.5 Toolkit? ((y)es/(n)o/(q)uit): y
Enter Toolkit Location [ default is /usr/local/cuda-7.5 ]:
Do you want to install a symbolic link at /usr/local/cuda? ((y)es/(n)o/(q)uit): y
Install the CUDA 7.5 Samples? ((y)es/(n)o/(q)uit): y
Enter CUDA Samples Location [ default is /home/kinghorn ]: /usr/local/cuda-7.5
Installing the CUDA Toolkit in /usr/local/cuda-7.5 ...
Finished copying samples.

===========
= Summary =
===========

Driver:   Not Selected
Toolkit:  Installed in /usr/local/cuda-7.5
Samples:  Installed in /usr/local/cuda-7.5

② 設定環境變數

vi /home/xxx/.bashrc

新增如下內容:

export PATH=/usr/local/cuda/bin:$PATH

執行如下命令使環境變數生效

source /home/xxx/.bashrc

將cuda動態庫新增到動態庫管理器

sudo vi /etc/ld.so.conf.d/cuda.conf

新增:

/usr/local/cuda/lib64

執行ldconfig使新加的庫生效

sudo ldconfig

③ 強制使用gcc5
編輯/usr/local/cuda/include/host_config.h檔案,注釋掉115行

#error -- unsupported GNU version! gcc versions later than 4.9 are not supported! 

改為:

//#error -- unsupported GNU version! gcc versions later than 4.9 are not supported! 

(3)編譯cuda例子與測試

進入到/usr/local/cuda/NVIDIA_CUDA-7.5_Samples/1_Utilities/deviceQuery目錄執行:

sudo make
./deviceQuery

4.安裝cudnn庫

(1)解壓

tar xzvf cudnn-xxx-ga.tgz

得到cuda資料夾裡面含有的lib64和include兩個資料夾

(2)拷貝到cuda安裝目錄

sudo cp cuda/cudnn.h /usr/local/cuda/include/
sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64

注意:拷貝後將連結刪除重新建立連結,否則,拷貝是多個多個不同名字的相同檔案,連結關係參見cudnn解壓後的資料夾。也可以分別拷貝每一個文??,連結檔案拷貝使用cp -d命令。

5.安裝opencv3.1.0

(1)安裝基本必要庫

sudo apt-get install build-essential cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev

(2)設定opencv,生成Makefile

cd opencv-3.1.0
mkdir build
cd build
cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local ..

在configure過程中過程中,可能會出現下面的錯誤:

– ICV: Downloading ippicv_linux_20151201.tgz

在直接下載該檔案的過程中,會因為超時而失敗,需要收到下載,將其拷貝至opencv-3.1.0/3rdparty/ippicv/downloads/linux-8b449a536a2157bcad08a2b9f266828b目錄內,重新執行設定命令。

(3)編譯opencv

make -j8

此時可能會出現另一個錯誤:

/usr/include/string.h: In functionvoid* __mempcpy_inline(void*, const void*, size_t)’: /usr/include/string.h:652:42: error: ‘memcpy’ was not declared in this scope return (char *) memcpy (__dest, __src, __n) + __n;

這是因為ubuntu的g++版本過高造成的,只需要在opencv-3.1.0目錄下的CMakeList.txt 檔案的開頭加入:

set(CMAKE_CXX_FLAGS “${CMAKE_CXX_FLAGS} -D_FORCE_INLINES”)

新增之後再次進行編譯連結即可。

(4)檢視版本號

pkg-config --modversion opencv 

(5)安裝

sudo make install

6.安裝caffe與設定

(1)安裝必要的依賴庫

sudo apt-get install build-essential
sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler
sudo apt-get install --no-install-recommends libboost-all-dev
sudo apt-get install libatlas-base-dev
sudo apt-get install Python-dev
sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev

如果這些庫都能順利安裝,會大大減少後面遇到的問題。

(2)下載caffe-master並解壓得到原始碼包

解壓:

unzip caffe-master.zip 

(3)修改組態檔Make.config

cd caffe-master
cp Makefile.config.example Makefile.config
vi Makefile.config

將# USE_CUDNN := 1前得#注釋去掉,表示使用cuDNN,如果不是使用GPU,可以將# CPU_ONLY := 1前得注釋去掉。這裡我使用cuDNN來加速。

(4)編譯caffe

方法1:使用cmake編譯

mkdir build 
cd build
cmake ..
make all -j8

這種方法一般不會出現問題。

方法2:直接使用gcc編譯

make -j8

錯誤1:

src/caffe/net.cpp:8:18: fatal error: hdf5.h: No such file or directory

參考方法

cd /usr/lib/x86_64-linux-gnu
sudo ln -s libhdf5_serial.so.10.1.0 libhdf5_serial.so
sudo ln -s libhdf5_serial_hl.so.10.0.2 libhdf5_serial_hl.so

修改Makefile.config

INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu/hdf5/serial

錯誤2:

error -- unsupported GNU version! gcc versions later than 5.3 are not supported!

目前caffe不支援高於5.3的gcc,理論上可通過對gcc,g++降級解決,但是降級後還會引起其他相容性問題,因此並不能解決實際問題,下面附上降級方法。解決方法在後面。

① 安裝低版本gcc、g++

sudo apt-get install gcc-4.7 gcc-4.7-multilib
sudo apt-get install g++-4.7 g++-4.7-multilib

② 設定優先順序

sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-4.7 40
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-5 50
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-4.7 40
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-5 50

③ 選擇版本

sudo update-alternatives --config gcc
There are 2 choices for the alternative gcc (providing /usr/bin/gcc)
Selection    Path              Priority   Status
------------------------------------------------------------
  0            /usr/bin/gcc-5     50        auto mode
* 1            /usr/bin/gcc-4.7   40        manual mode
  2            /usr/bin/gcc-5     50        manual mode

 

sudo update-alternatives --config g++
There are 2 choices for the alternative g++ (providing /usr/bin/g++).
  Selection    Path              Priority   Status
------------------------------------------------------------
  0            /usr/bin/g++-5     50        auto mode
* 1            /usr/bin/g++-4.7   40        manual mode
  2            /usr/bin/g++-5     50        manual mode

錯誤3:

/usr/include/string.h: In functionvoid* __mempcpy_inline(void*, const void*, size_t)’: /usr/include/string.h:652:42: error: ‘memcpy’ was not declared in this scope return (char *) memcpy (__dest, __src, __n) + __n;
NVCCFLAGS += -ccbin=$(CXX) -Xcompiler -fPIC $(COMMON_FLAGS)

改為:

NVCCFLAGS += -D_FORCE_INLINES -ccbin=$(CXX) -Xcompiler -fPIC $(COMMON_FLAGS)

錯誤3:

/usr/bin/ld: cannot find -lippicv
cp opencv-3.1.0/3rdparty/ippicv/unpack/ippicv_lnx/lib/intel64/libippicv.a /usr/local/lib

再次編譯即可。

至此,gcc、g++降級完成。

 


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