基于Ubuntu14.04搭建caffe训练环境
各种教学视频或文档资料 +QQ：635992897
一、基础环境配置
0、apt-get update
1、sshd安装
sudo apt-get install openssh-server
2、Vi重装
apt-get install vim
3、Samba 安装及配置
3.1 sudo apt-get install samba samba-common
3.2 配置如下：
# Cap the size of the individual log files (in KiB).
max log size = 1000
这些下面加
security = user
配置文件最下面加
[myshare]
comment = this is Linux share directory
path = /home/share
# public = yes
browseable = yes
writable = yes
user = system,ubuntu
create mask = 0755
force create mode = 0755
directory mask = 0755
force directory mode = 0755
available = yes
3.3.添加smb用户
sudo smbpasswd -a smbuser
这里一定要保证在linux系统中也有smbuser用户，名称可以自己定
3.4 错误处理
ubuntu14.04中文版装好samba后，报各种错，查看/var/log/samba日志，发现也是报各种错，最后处理发现linux 下使用smbclient 访问正常，Windows下访问报如下：
"无法访问。您可能没有权限使用网络资源，请与这台服务器的管理员联系以查明您是否有访问权限。指定的网络名不再可用。"
日志中有如下错误：
[2016/12/21 08:43:18.450576, 0] ../source3/lib/dumpcore.c:303(dump_core)
dumping core in /var/log/samba/cores/smbd
[2016/12/21 08:43:18.614643, 0] ../source3/lib/popt_common.c:68(popt_s3_talloc_log_fn)
talloc: access after free error - first free may be at ../source3/smbd/open.c:3715
[2016/12/21 08:43:18.614690, 0] ../source3/lib/popt_common.c:68(popt_s3_talloc_log_fn)
Bad talloc magic value - access after free
[2016/12/21 08:43:18.614710, 0] ../source3/lib/util.c:789(smb_panic_s3)
PANIC (pid 5348): Bad talloc magic value - access after free
[2016/12/21 08:43:18.615376, 0] ../source3/lib/util.c:900(log_stack_trace)
BACKTRACE: 26 stack frames:
#0 /usr/lib/x86_64-linux-gnu/samba/libsmbregistry.so.0(log_stack_trace+0x1a) [0x7f24d91e914a]
处理方式：
sudo apt-get install libtalloc2 升级 libtalloc2，参考：http://blog.csdn.net/merlinholland/article/details/52822501
4、sudo自动切换
visudo
插入如下信息：
## Allows people in group wheel to run all commands
# %wheel ALL=(ALL) ALL
## Same thing without a password
%wheel ALL=(ALL) NOPASSWD: ALL
system ALL=(ALL) NOPASSWD: ALL
ubuntu ALL=(ALL) NOPASSWD: ALL
其中 system ubuntu 是你想支持用户
5、安装nvidia 驱动，这里是安装Tesla k20c的驱动，也支持k40c 、k80，具体如下：
Tesla K80, Tesla K40c, Tesla K40m, Tesla K40s, Tesla K40st, Tesla K40t, Tesla K20Xm, Tesla K20m, Tesla K20s, Tesla K20c, Tesla K10
5.1 安装 bumblebee
sudo add-apt-repository ppa:bumblebee/stable
sudo apt-get update
sudo apt-get install bumblebee bumblebee-nvidia
5.2 安装nvidia驱动
参考：http://blog.csdn.net/TriLoo/article/details/52678033?locationNum=14
备用： http://blog.163.com/zhao_en_peng/blog/static/12740422420131202110539/
5.2.1.查看电脑的显卡信息以及正在使用的显卡驱动
查看电脑显卡信息命令：lspci | grep VGA
lspci会显示所有的PCI接口设备，然后从中提取处显示相关的设备（VGA）。
执行命令会得到类似下面的信息：
01:00.0 VGA compatible controller: NVIDIA Corporation GM107 [GeForce GTX 745] (rev a2)
从上面的信息可以看出：显卡型号为GTX745。显卡型号会在后面下载显卡驱动时用到。
得到显卡型号后，可以利用下面的命令查看关于显卡的更详细信息：
lspci -v -s 01:00.01
-v ： 显示详细信息
-s ： 后面接PCI设备的ID
执行命令会得到类似下面的信息：
01:00.0 VGA compatible controller: NVIDIA Corporation GM107 [GeForce GTX 745] (rev a2) (prog-if 00 [VGA controller])
Subsystem: NVIDIA Corporation Device 1065
Flags: bus master, fast devsel, latency 0, IRQ 34
Memory at f6000000 (32-bit, non-prefetchable) [size=16M]
Memory at e0000000 (64-bit, prefetchable) [size=256M]
Memory at f0000000 (64-bit, prefetchable) [size=32M]
I/O ports at e000 [size=128]
[virtual] Expansion ROM at f7000000 [disabled] [size=512K]
Capabilities:
Kernel driver in use: nvidias
其中在最后一行显示正在使用的驱动是nvidias。这是安装Nvidia显卡后的显示，最开始会显示nouveau。
在倒数第二行显示access denied，是因为权限问题，可以sudo解决。
好了现在我们知道了显卡型号以及显卡驱动信息了下一步是去Nvidia官网下载相应的显卡驱动程序。
1.下载驱动
Nvidia驱动下载链接：Nvidia。
http://cn.download.nvidia.com/XFree86/Linux-x86_64/346.96/NVIDIA-Linux-x86_64-346.96.run
#http://cn.download.nvidia.com/Ubuntu/346.96/nvidia-driver-repo-ubuntu1404_7.0-346.96_ppc64el.deb
在打开的界面中（界面如下图），建议选用手动根据自己的系统、显卡型号等选择相关的驱动。
5.2.2.禁止nouveau驱动
通过网上的相关信息，如果之前显卡驱动是用的nouveau，那么在安装自己下载的驱动的时候会显示错误。
所以在安装驱动之前，需要先在/etc/modprobe.d/blacklist.conf文件中加入下面内容：
blacklist nouveau
然后重新启动。
sudo reboot
5.2.3.安装显卡
重启后，在登陆界面时同时按下：Ctrl + Alt + F1~F6进入字符界面。
也可以在登陆界面登陆后，在终端输入init 3来改变run level.
需要说明的是，重启后，会发现字体变大，这属于正常显现。
登陆tt1终端，然后关闭Ubuntu的Unity：
sudo service lightdm stop
其中lightdm根据自己使用的桌面做相应的调整：
[KDM（KDE），GDM（GNOME）
然后进入之前下载的驱动文件所在的目录，运行下载的脚本文件即可：
sudo sh NVIDIA-Linux-x86_64-346.96.run
#sudo dpkg -i nvidia-driver-repo-ubuntu1404_7.0-346.96_ppc64el.deb 错误
后面根据程序的提示操作即可。
5.2.4.重启
安装完成后，重启即可。
sudo service lightdm start
问题处理：
（1） 安装完成后重启可能会出现循环登录的情况，解决方法是重启前先按照下面教程安装一个管理软件：
http://blog.csdn.net/triloo/article/details/52767412
见5.1安装 bumblebee
（2）错误信息：
软件包的体系架构(ppc64el)与本机系统的架构(amd64)不符
在处理时有错误发生：
nvidia-driver-repo-ubuntu1404_7.0-346.96_ppc64el.deb
下载安装包错误，重新下载适合你机器的安装包即可
安装检查工具
sudo apt-get install mesa-utils
6、安装CUDA7.0
下载CUDA7.0
6.1安装 cuda
6.1.1安装依赖库
sudo apt-get install freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libgl1-mesa-glx libglu1-mesa libglu1-mesa-dev
6.1.2安装CUDA7.0 参考：http://blog.csdn.net/a350203223/article/details/50262535
(1) sudo dpkg -i cuda-repo-ubuntu1404-7-0-local_7.0-28_amd64.deb
Selecting previously unselected package cuda-repo-ubuntu1404-7-0-local.
(正在读取数据库 ... 系统当前共安装有 171979 个文件和目录。)
Preparing to unpack cuda-repo-ubuntu1404-7-0-local_7.0-28_amd64.deb ...
Unpacking cuda-repo-ubuntu1404-7-0-local (7.0-28) ...
正在设置 cuda-repo-ubuntu1404-7-0-local (7.0-28) ...
OK
(1.5) sudo apt-get update
(2)sudo apt-get install cuda
正在读取软件包列表... 完成
正在分析软件包的依赖关系树
正在读取状态信息... 完成
下列软件包是自动安装的并且现在不需要了：
libcublas5.5 libcudart5.5 libcufft5.5 libcufftw5.5 libcuinj64-5.5
libcurand5.5 libcusparse5.5 libnppc5.5 libnppi5.5 libnpps5.5 libnvtoolsext1
libnvvm2 libthrust-dev libvdpau-dev nvidia-cuda-dev nvidia-cuda-doc
nvidia-cuda-gdb nvidia-profiler nvidia-visual-profiler opencl-headers
Use 'apt-get autoremove' to remove them.
将会安装下列额外的软件包：
cuda-7-0 cuda-command-line-tools-7-0 cuda-core-7-0 cuda-cublas-7-0
cuda-cublas-dev-7-0 cuda-cudart-7-0 cuda-cudart-dev-7-0 cuda-cufft-7-0
cuda-cufft-dev-7-0 cuda-curand-7-0 cuda-curand-dev-7-0 cuda-cusolver-7-0
cuda-cusolver-dev-7-0 cuda-cusparse-7-0 cuda-cusparse-dev-7-0
cuda-documentation-7-0 cuda-driver-dev-7-0 cuda-drivers cuda-license-7-0
cuda-misc-headers-7-0 cuda-npp-7-0 cuda-npp-dev-7-0 cuda-nvrtc-7-0
cuda-nvrtc-dev-7-0 cuda-runtime-7-0 cuda-samples-7-0 cuda-toolkit-7-0
cuda-visual-tools-7-0 libcuda1-346 libcuda1-352 libcuda1-367 nvidia-346
nvidia-346-dev nvidia-346-uvm nvidia-352 nvidia-352-dev nvidia-367
nvidia-367-dev nvidia-modprobe nvidia-opencl-icd-346 nvidia-opencl-icd-352
nvidia-opencl-icd-367 nvidia-settings ocl-icd-libopencl1
下列软件包将被【卸载】：
libcuda1-340 nvidia-340 nvidia-340-uvm nvidia-cuda-toolkit
nvidia-libopencl1-331 nvidia-libopencl1-340 nvidia-opencl-dev
nvidia-opencl-icd-340
下列【新】软件包将被安装：
cuda cuda-7-0 cuda-command-line-tools-7-0 cuda-core-7-0 cuda-cublas-7-0
cuda-cublas-dev-7-0 cuda-cudart-7-0 cuda-cudart-dev-7-0 cuda-cufft-7-0
cuda-cufft-dev-7-0 cuda-curand-7-0 cuda-curand-dev-7-0 cuda-cusolver-7-0
cuda-cusolver-dev-7-0 cuda-cusparse-7-0 cuda-cusparse-dev-7-0
cuda-documentation-7-0 cuda-driver-dev-7-0 cuda-drivers cuda-license-7-0
cuda-misc-headers-7-0 cuda-npp-7-0 cuda-npp-dev-7-0 cuda-nvrtc-7-0
cuda-nvrtc-dev-7-0 cuda-runtime-7-0 cuda-samples-7-0 cuda-toolkit-7-0
cuda-visual-tools-7-0 libcuda1-346 libcuda1-352 libcuda1-367 nvidia-346
nvidia-346-dev nvidia-346-uvm nvidia-352 nvidia-352-dev nvidia-367
nvidia-367-dev nvidia-modprobe nvidia-opencl-icd-346 nvidia-opencl-icd-352
nvidia-opencl-icd-367 ocl-icd-libopencl1
下列软件包将被升级：
nvidia-settings
升级了 1 个软件包，新安装了 44 个软件包，要卸载 8 个软件包，有 590 个软件包未被升级。
需要下载 75.5 MB/1,042 MB 的软件包。
解压缩后会消耗掉 1,556 MB 的额外空间。
您希望继续执行吗？ [Y/n] y
获取：1 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-352 amd64 367.57-0ubuntu0.14.04.1 [4,802 B]
获取：2 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-346 amd64 352.63-0ubuntu0.14.04.1 [4,802 B]
获取：3 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-367 amd64 367.57-0ubuntu0.14.04.1 [69.8 MB]
获取：4 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted libcuda1-367 amd64 367.57-0ubuntu0.14.04.1 [2,708 kB]
获取：5 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-346-uvm amd64 346.96-0ubuntu0.0.1 [4,762 B]
获取：6 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-367-dev amd64 367.57-0ubuntu0.14.04.1 [80.8 kB]
获取：7 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-352-dev amd64 367.57-0ubuntu0.14.04.1 [4,806 B]
获取：8 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-346-dev amd64 352.63-0ubuntu0.14.04.1 [4,812 B]
获取：9 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted libcuda1-352 amd64 367.57-0ubuntu0.14.04.1 [4,814 B]
获取：10 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted libcuda1-346 amd64 352.63-0ubuntu0.14.04.1 [4,810 B]
获取：11 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-opencl-icd-367 amd64 367.57-0ubuntu0.14.04.1 [2,901 kB]
获取：12 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-opencl-icd-352 amd64 367.57-0ubuntu0.14.04.1 [4,818 B]
获取：13 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-opencl-icd-346 amd64 352.63-0ubuntu0.14.04.1 [4,822 B]
下载 75.5 MB，耗时 13分 13秒 (95.2 kB/s)
正在从软件包中解出模板：100%
Selecting previously unselected package nvidia-352.
(正在读取数据库 ... 系统当前共安装有 179276 个文件和目录。)
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Unpacking nvidia-352 (367.57-0ubuntu0.14.04.1) ...
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Preparing to unpack .../nvidia-346_352.63-0ubuntu0.14.04.1_amd64.deb ...
Unpacking nvidia-346 (352.63-0ubuntu0.14.04.1) ...
(正在读取数据库 ... 系统当前共安装有 179281 个文件和目录。)
Removing nvidia-opencl-icd-340 (340.98-0ubuntu0.14.04.1) ...
Removing nvidia-cuda-toolkit (5.5.22-3ubuntu1) ...
Removing nvidia-opencl-dev:amd64 (5.5.22-3ubuntu1) ...
Removing nvidia-libopencl1-331 (340.98-0ubuntu0.14.04.1) ...
Removing nvidia-libopencl1-340 (340.98-0ubuntu0.14.04.1) ...
Removing nvidia-340-uvm (340.98-0ubuntu0.14.04.1) ...
dpkg: nvidia-340: dependency problems, but removing anyway as you requested:
bumblebee-nvidia 依赖于 nvidia-driver | nvidia-glx | nvidia-kernel-dkms | nvidia-kernel-amd64 | nvidia-kernel-686-pae | nvidia-kernel-486 | nvidia | nvidia-current | nvidia-current-updates | nvidia-driver-binary | nvidia-304 | nvidia-304-updates | nvidia-experimental-304 | nvidia-310 | nvidia-310-updates | nvidia-experimental-310 | nvidia-313 | nvidia-313-updates | nvidia-experimental-313 | nvidia-319 | nvidia-319-updates | nvidia-experimental-319 | nvidia-325 | nvidia-325-updates | nvidia-experimental-325 | nvidia-331 | nvidia-331-updates | nvidia-experimental-331 | nvidia-334 | nvidia-334-updates | nvidia-experimental-334 | nvidia-337 | nvidia-337-updates | nvidia-experimental-337 | nvidia-340 | nvidia-340-updates | nvidia-experimental-340 | nvidia-343 | nvidia-343-updates | nvidia-experimental-343 | nvidia-346 | nvidia-346-updates | nvidia-experimental-346 | nvidia-349 | nvidia-349-updates | nvidia-experimental-349 | nvidia-352 | n
Removing nvidia-340 (340.98-0ubuntu0.14.04.1) ...
Stopping nvidia-persistenced
nvidia-persistenced：没有发现操作
Done.
Removing all DKMS Modules
Done.
INFO:Disable nvidia-340
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/put_your_quirks_here
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/dell_latitude
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/lenovo_thinkpad
update-initramfs: deferring update (trigger activated)
Processing triggers for libc-bin (2.19-0ubuntu6) ...
Processing triggers for man-db (2.6.7.1-1) ...
Processing triggers for initramfs-tools (0.103ubuntu4.2) ...
update-initramfs: Generating /boot/initrd.img-3.13.0-32-generic
Selecting previously unselected package nvidia-367.
(正在读取数据库 ... 系统当前共安装有 178942 个文件和目录。)
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Unpacking nvidia-367 (367.57-0ubuntu0.14.04.1) ...
Processing triggers for ureadahead (0.100.0-16) ...
Processing triggers for man-db (2.6.7.1-1) ...
dpkg: libcuda1-340: dependency problems, but removing anyway as you requested:
libcuinj64-5.5:amd64 依赖于 libcuda-5.5-1；然而：
未安装软件包 libcuda-5.5-1。
提供了 libcuda-5.5-1 的软件包 libcuda1-340 即将被删除。
nvidia-profiler 依赖于 libcuda-5.5-1；然而：
未安装软件包 libcuda-5.5-1。
提供了 libcuda-5.5-1 的软件包 libcuda1-340 即将被删除。
(正在读取数据库 ... 系统当前共安装有 179508 个文件和目录。)
Removing libcuda1-340 (340.98-0ubuntu0.14.04.1) ...
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Unpacking nvidia-settings (346.46-0ubuntu1) over (331.20-0ubuntu8) ...
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Unpacking libcuda1-346 (352.63-0ubuntu0.14.04.1) ...
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Unpacking cuda (7.0-28) ...
Processing triggers for man-db (2.6.7.1-1) ...
Processing triggers for doc-base (0.10.5) ...
Processing 1 added doc-base file...
Processing triggers for gnome-menus (3.10.1-0ubuntu2) ...
Processing triggers for desktop-file-utils (0.22-1ubuntu1) ...
Processing triggers for bamfdaemon (0.5.1+14.04.20140409-0ubuntu1) ...
Rebuilding /usr/share/applications/bamf-2.index...
Processing triggers for mime-support (3.54ubuntu1) ...
正在设置 nvidia-367 (367.57-0ubuntu0.14.04.1) ...
update-alternatives: using /usr/lib/nvidia-367/ld.so.conf to provide /etc/ld.so.conf.d/x86_64-linux-gnu_EGL.conf (x86_64-linux-gnu_egl_conf) in 自动模式
update-alternatives: using /usr/lib/nvidia-367/alt_ld.so.conf to provide /etc/ld.so.conf.d/i386-linux-gnu_EGL.conf (i386-linux-gnu_egl_conf) in 自动模式
update-alternatives: using /usr/share/nvidia-367/glamor.conf to provide /usr/share/X11/xorg.conf.d/glamoregl.conf (glamor_conf) in 自动模式
INFO:Enable nvidia-367
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/put_your_quirks_here
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/dell_latitude
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/lenovo_thinkpad
正在添加系统用户"nvidia-persistenced" (UID 117)...
正在添加新组"nvidia-persistenced" (GID 125)...
正在将新用户"nvidia-persistenced" (UID 117)添加到组"nvidia-persistenced"...
无法创建主目录"/"
Loading new nvidia-367-367.57 DKMS files...
First Installation: checking all kernels...
Building only for 3.13.0-32-generic
Building for architecture x86_64
Building initial module for 3.13.0-32-generic
Done.
nvidia_367:
Running module version sanity check.
- Original module
- No original module exists within this kernel
- Installation
- Installing to /lib/modules/3.13.0-32-generic/updates/dkms/
nvidia_367_modeset.ko:
Running module version sanity check.
- Original module
- No original module exists within this kernel
- Installation
- Installing to /lib/modules/3.13.0-32-generic/updates/dkms/
nvidia_367_drm.ko:
Running module version sanity check.
- Original module
- No original module exists within this kernel
- Installation
- Installing to /lib/modules/3.13.0-32-generic/updates/dkms/
nvidia_367_uvm.ko:
Running module version sanity check.
- Original module
- No original module exists within this kernel
- Installation
- Installing to /lib/modules/3.13.0-32-generic/updates/dkms/
depmod....
DKMS: install completed.
正在设置 nvidia-352 (367.57-0ubuntu0.14.04.1) ...
正在设置 nvidia-346 (352.63-0ubuntu0.14.04.1) ...
正在设置 libcuda1-367 (367.57-0ubuntu0.14.04.1) ...
正在设置 ocl-icd-libopencl1:amd64 (2.1.3-4) ...
正在设置 cuda-license-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-misc-headers-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-core-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-cudart-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-driver-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-cudart-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-command-line-tools-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-nvrtc-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-nvrtc-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-cusolver-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-cusolver-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-cublas-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-cublas-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-cufft-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-cufft-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-curand-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-curand-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-cusparse-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-cusparse-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-npp-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-npp-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-samples-7-0 (7.0-28) ...
正在设置 cuda-documentation-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-visual-tools-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 cuda-toolkit-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在设置 nvidia-346-uvm (346.96-0ubuntu0.0.1) ...
正在设置 nvidia-367-dev (367.57-0ubuntu0.14.04.1) ...
正在设置 nvidia-352-dev (367.57-0ubuntu0.14.04.1) ...
正在设置 nvidia-346-dev (352.63-0ubuntu0.14.04.1) ...
正在设置 nvidia-modprobe (346.46-0ubuntu1) ...
正在设置 nvidia-settings (346.46-0ubuntu1) ...
正在设置 libcuda1-352 (367.57-0ubuntu0.14.04.1) ...
正在设置 libcuda1-346 (352.63-0ubuntu0.14.04.1) ...
正在设置 nvidia-opencl-icd-367 (367.57-0ubuntu0.14.04.1) ...
正在设置 nvidia-opencl-icd-352 (367.57-0ubuntu0.14.04.1) ...
正在设置 nvidia-opencl-icd-346 (352.63-0ubuntu0.14.04.1) ...
正在设置 cuda-drivers (346.46-1) ...
正在设置 cuda-runtime-7-0 (7.0-28) ...
正在设置 cuda-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
*****************************************************************************************
*** Please reboot your computer and verify that the nvidia graphics driver is loaded. ***
*** If the driver fails to load, please use the NVIDIA graphics driver .run installer ***
*** to get into a stable state. ***
*****************************************************************************************
正在设置 cuda (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
Processing triggers for libc-bin (2.19-0ubuntu6) ...
(3) 配置CUDA
sudo vi /etc/profile 添加
export PATH=/usr/local/cuda-7.0/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-7.0/lib64:$LD_LIBRARY_PATH
添加cuda.conf
sudo vim /etc/ld.so.conf.d/cuda.conf
/usr/local/cuda/lib64
/lib
6.2 安装 cuda-toolkit
好像没装，装了toolkit，检查一下
nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2015 NVIDIA Corporation
Built on Mon_Feb_16_22:59:02_CST_2015
Cuda compilation tools, release 7.0, V7.0.27
如果有上述信息不用操做，否则执行：
sudo apt-get install nvidia-cuda-toolkit
安装失败，nvidia-cuda-toolkit : 依赖: nvidia-opencl-dev (= 5.5.22-3ubuntu1) 但是它将不
重新执行一下， 6.3.1 问题处理，执行 nvcc --version，
system@ubunt:~$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2015 NVIDIA Corporation
Built on Mon_Feb_16_22:59:02_CST_2015
Cuda compilation tools, release 7.0, V7.0.27
一切正常
6.3 安装sample(如果安装的是8.0需要先sudo apt-get remove --purge nvidia-375 nvidia-modprobe nvidia-settings 再sudo ./cuda_8.0.61_375.26_linux.run)
cd /usr/local/cuda-7.0/bin
$ cuda-install-samples-7.0.sh <dir>
这样，就将cuda的sample拷贝到dir文件夹下了。该命令只是一个拷贝操作。
我的执行如下:
$ cuda-install-samples-7.0.sh /home/cudaSamples/
cd /home/cudaSamples/
$ make
然后进入该文件夹，执行make命令进行编译，编译时间较长，需要等待。
/usr/bin/ld: cannot find -lnvcuvid
collect2: error: ld returned 1 exit status
sudo sed -i "s/nvidia-346/nvidia-367/g" `grep nvidia-346 -rl ./`
执行成功再次make 完成
执行 /home/cuda7_sample/NVIDIA_CUDA-7.0_Samples/bin/x86_64/linux/release下的
./deviceQuery
CUDA Device Query (Runtime API) version (CUDART static linking)
modprobe: FATAL: Module nvidia-uvm not found.
cudaGetDeviceCount returned 30
-> unknown error
Result = FAIL
重启发现，系统不能正常显示，只出现log界面，崩溃！！！！
6.3.1 问题处理如下：
首先，之前使用bumblebee解决双显卡问题的需要卸载bumblebee。
(1) sudo apt-get purge bumblebee*
安装nvidia-367驱动和nvidia prime，这里先不管驱动的版本问题
(2). sudo stop lightdm
(3). sudo apt-get install nvidia-367 nvidia-prime 重装驱动 因该是
切换到nvidia独显下安装CUDA
(3.5). sudo prime-select nvidia 应该是这步起作用了
(3.8).sudo dpkg -i cuda-repo-ubuntu1404-7-0-local_7.0-28_amd64.deb 这步估计没用
(4).sudo reboot 重启，
(5).系统启动还报错，忽略
./deviceQuery
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 2 CUDA Capable device(s)
Device 0: "Tesla K20c"
CUDA Driver Version / Runtime Version 8.0 / 7.0
CUDA Capability Major/Minor version number: 3.5
Total amount of global memory: 4742 MBytes (4972412928 bytes)
(13) Multiprocessors, (192) CUDA Cores/MP: 2496 CUDA Cores
GPU Max Clock rate: 706 MHz (0.71 GHz)
Memory Clock rate: 2600 Mhz
Memory Bus Width: 320-bit
L2 Cache Size: 1310720 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 2048
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 2 copy engine(s)
Run time limit on kernels: No
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Enabled
Device supports Unified Addressing (UVA): Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 4 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
Device 1: "Quadro K420"
CUDA Driver Version / Runtime Version 8.0 / 7.0
CUDA Capability Major/Minor version number: 3.0
Total amount of global memory: 972 MBytes (1019215872 bytes)
( 1) Multiprocessors, (192) CUDA Cores/MP: 192 CUDA Cores
GPU Max Clock rate: 876 MHz (0.88 GHz)
Memory Clock rate: 891 Mhz
Memory Bus Width: 128-bit
L2 Cache Size: 262144 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 2048
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 1 copy engine(s)
Run time limit on kernels: Yes
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Disabled
Device supports Unified Addressing (UVA): Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 3 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
> Peer access from Tesla K20c (GPU0) -> Quadro K420 (GPU1) : No
> Peer access from Quadro K420 (GPU1) -> Tesla K20c (GPU0) : No
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 8.0, CUDA Runtime Version = 7.0, NumDevs = 2, Device0 = Tesla K20c, Device1 = Quadro K420
Result = PASS
先看驱动检测
system@Ubuntu14:/var/cache/apt/archives$ nvidia-smi
Mon Dec 26 16:36:52 2016
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 367.57 Driver Version: 367.57 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Quadro K420 Off | 0000:03:00.0 On | N/A |
| 25% 43C P8 N/A / N/A | 220MiB / 972MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 1 Tesla K20c Off | 0000:04:00.0 Off | 0 |
| 30% 33C P8 17W / 225W | 0MiB / 4742MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 1457 G /usr/bin/X 132MiB |
| 0 2696 G compiz 86MiB |
+-----------------------------------------------------------------------------+
6.43，安装cuDNN
下载 cudnn-7.0-linux-x64-v3.0-prod.tgz，官网申请不到，网上自己找的，就不给地址了。
[plain] view plain copy print?在CODE上查看代码片派生到我的代码片
tar -zxvf cudnn-7.0-linux-x64-v3.0-prod.tgz
cd cuda
sudo cp lib64/lib* /usr/local/cuda/lib64/
sudo cp include/cudnn.h /usr/local/cuda/include/
不用操作以下：
sudo chmod u=rwx,g=rx,o=rx libcudnn.so.7.0.64
sudo ln -s libcudnn.so.7.0.64 libcudnn.so.7.0
sudo ln -s libcudnn.so.7.0 libcudnn.so
同时需要添加lib库路径： 在 /etc/ld.so.conf.d/加入文件 cuda.conf, 内容如下
/usr/local/cuda/lib64
保存后，执行下列命令使之立刻生效
sudo ldconfig
7、安装python
7.1 不再安装python管理工具pyenv，跳过##错误##
(1)安装git
sudo apt-get install git
###### (2)安装python管理工具pyenv,这里我假设用用户system安装
###### sudo git clone git://github.com/yyuu/pyenv.git ~/.pyenv
###### 切换到root用户
###### echo 'export PYENV_ROOT="/home/system/.pyenv"' >> /etc/profile
###### echo 'export PATH="/home/system/.pyenv/bin:$PATH"' >> /etc/profile
###### echo 'eval "$(pyenv init -)"' >> /etc/profile
###### source /etc/profile
7.2python 编译安装
(1)安装依赖库
安装git
sudo apt-get install git
sudo apt-get install -y make build-essential libssl-dev zlib1g-dev libbz2-dev libreadline-dev libsqlite3-dev wget curl llvm
sudo apt-get install libc6-dev gcc
(2)编译python
pyenv install 2.7.12 -v 下载失败
拷贝下载的源码安装
XX sudo ./configure --enable-unicode=ucs4 --enable-shared cxxflags=-fPIC cflags=-fPIC --prefix=/usr/local/python
XX sudo ./configure --enable-unicode=ucs4 --enable-shared cxxflags=-fPIC cflags=-fPIC --prefix=/usr
sudo ./configure --enable-unicode=ucs4 --enable-shared cxxflags=-fPIC cflags=-fPIC
所以通常我们./configure的时候，默认是--prefix=/usr，这样的话，本程序的配置文件就会装到/usr/etc,应用文件就会安装到/usr/bin,本程序的私有库也会安装到/usr/lib等等，，我们也不用设置PATH就可以直接用了，，
sudo make install
(2.5)修改链接
sudo mv /usr/bin/python /usr/bin/python2.7.6
sudo ln -s /usr/local/bin/python2.7 /usr/bin/python
a.需要编辑/etc/ld.so.conf增加一行/usr/local/lib
sudo vim /etc/ld.so.conf
include ld.so.conf.d/*.conf #原有的
/usr/local/lib
b. ld.so.conf文件配置完毕后，我们需要执行如下命令：
sudo /sbin/ldconfig
sudo /sbin/ldconfig -v
c. 然后再执行python -V命令，查看python版本如下
Python 2.7.12
(3)安装python的pip和easy_install（工具包 setuptools-32.3.0.zip ），方便安装软件包
wget --no-check-certificate https://bootstrap.pypa.io/ez_setup.py
python ez_setup.py --insecure
wget https://bootstrap.pypa.io/get-pip.py
sudo python get-pip.py
(4)安装其他包
a. numpy 安装
tar -xzvf numpy-1.12.0b1.tar.gz
cd numpy-1.12.0b1
sudo python setup.py install
b. mock安装
tar -xzvf mock-2.0.0.tar.gz
cd mock-2.0.0/
sudo python setup.py install
c. six安装
tar -xvzf six-1.10.0.tar.gz
cd six-1.10.0/
sudo python setup.py install
d. pbr.version安装
tar -xzvf pbr-1.10.0.tar.gz
cd pbr-1.10.0/
sudo python setup.py install
e. funcsigs 安装
tar -xvzf funcsigs-1.0.2.tar.gz
cd funcsigs-1.0.2/
sudo python setup.py install
f. atlas3 安装(没装)
tar -jxvf
tar -jxvf atlas3.10.3.tar.bz2
cd ATLAS/
**************************************************
mkdir build ; cd build
./ATLAS/configure [flags]
make ! tune and compile library
make check ! perform sanity tests
make ptcheck ! checks of threaded code for multiprocessor systems
make time ! provide performance summary as % of clock rate
make install ! Copy library and include files to other directories
**************************************************
编译过程出错，提示be due to shut off throttling ,放弃安装，可以通过进入bois修改对应选项再安装
g. boost_1_57_0 安装
#sudo apt-get remove libboost-dev
tar -jxvf boost_1_57_0.tar.bz2
cd boost_1_57_0/
sudo ./bootstrap.sh
修改tools/build/boost-build.jam 在最后面加上一行“using mpi ;”(注意mpi后面有个空格，然后一个分号 )
sudo ./b2
sudo ./b2 install --prefix=/usr
h. dask安装
tar -xzvf dask-0.12.0.tar.gz
cd dask-0.12.0/
sudo python setup.py install
i. easydict 安装
unzip easydict-1.6.zip
cd easydict-1.6/
sudo python setup.py install
j. Cython 安装
tar -xzvf Cython-0.25.1.tar.gz
cd Cython-0.25.1/
sudo python setup.py install
k. h5py 安装
tar -xvzf h5py-2.6.0.tar.gz
cd h5py-2.6.0/
sudo python setup.py install
缺少 hdf5.h 文件，下载 anaconda 安装
bash Anaconda-2.1.0-Linux-x86_64.sh
chmod +x Anaconda-2.1.0-Linux-x86_64.sh
./Anaconda-2.1.0-Linux-x86_64.sh
m. ipython安装
tar -xvzf ipython-5.1.0.tar.gz
cd ipython-5.1.0/
sudo python setup.py install
n. lapack安装
sudo apt-get install gfortran
tar -xzvf lapack-3.5.0.tgz
cd lapack-3.5.0/
cp make.inc.example make.inc
cd lapack-3.5.0/
编辑Makefile 文件内容， 把
lib: lapacklib tmglib
#lib: blaslib variants lapacklib tmglib
改为：
#lib: lapacklib tmglib
lib: blaslib variants lapacklib tmglib
将生成的liblapack.a，librefblas.a，libtmglib.a 三个库拷贝到/usr/lib
sudo cp liblapack.a /usr/lib
sudo cp librefblas.a /usr/lib
sudo cp libtmglib.a /usr/lib
o. leveldb安装
tar -xvzf leveldb-0.194.tar.gz
cd leveldb-0.194/
sudo python setup.py install
p. matplotlib安装 ..... Math跳过去没装
tar -xzvf matplotlib-1.4.2.tar.gz
cd matplotlib-1.4.2/
sudo python setup.py install
报如下错误：
* The following required packages can not be built:
* freetype, png
采用如下方法安装：
安装 ：sudo apt-get install libpng-dev
下载 freetype-2.3.10.tar.bz2
tar -xjvf freetype-2.3.10.tar.bz2
cd freetype-2.3.10
sudo ./configure --prefix=/usr
sudo make
sudo make install
再次执行:
sudo python setup.py install , 另一种安装方式: sudo pip install matplotlib
测试安装成功 import matplotlib.pyplot as plt
配置matploatlib
cd /usr/local/lib/python2.7/site-packages/matplotlib-1.4.2-py2.7-linux-x86_64.egg/matplotlib/mpl-data
vi matplotlibrc
#### CONFIGURATION BEGINS HERE
# The default backend; one of GTK GTKAgg GTKCairo GTK3Agg GTK3Cairo
# CocoaAgg MacOSX Qt4Agg Qt5Agg TkAgg WX WXAgg Agg Cairo GDK PS PDF SVG
# Template.
# You can also deploy your own backend outside of matplotlib by
# referring to the module name (which must be in the PYTHONPATH) as
# 'module://my_backend'.
backend : agg
修改为：backend : Qt4Agg
在Ubuntu系统上安装PySide
sudo add-apt-repository ppa:pyside
sudo apt-get update
sudo apt-get install python-pyside
如果想只装某个模块：
sudo apt-get install python-pyside.qtgui
cd /usr/lib/python2.7/dist-packages
sudo cp -rf PyQt4 /usr/local/lib/python2.7/site-packages/
sudo cp -rf PySide/ /usr/local/lib/python2.7/site-packages/
使用下面的方法测试是否安装成功：
>>> from PySide.QtCore import *
>>> print QT_VERSION_STR 运行错误，忽略
4.7.0
q. networkx 安装
tar -xzvf networkx-1.11.tar.gz
cd networkx-1.11/
sudo python setup.py install
自动安装了decorator库
Best match: decorator 4.0.11
Processing decorator-4.0.11.tar.gz
Writing /tmp/easy_install-kCHNjB/decorator-4.0.11/setup.cfg
Running decorator-4.0.11/setup.py -q bdist_egg --dist-dir /tmp/easy_install-kCHNjB/decorator-4.0.11/egg-dist-tmp-5NBa3d
creating /usr/local/lib/python2.7/site-packages/decorator-4.0.11-py2.7.egg
Extracting decorator-4.0.11-py2.7.egg to /usr/local/lib/python2.7/site-packages
Adding decorator 4.0.11 to easy-install.pth file
Installed /usr/local/lib/python2.7/site-packages/decorator-4.0.11-py2.7.egg
Finished processing dependencies for networkx==1.11
r. nose 安装
tar -xvzf nose-1.3.7.tar.gz
cd nose-1.3.7/
sudo python setup.py install
s. pandas 安装
tar -xzvf pandas-0.19.1.tar.gz
cd pandas-0.19.1/
sudo python setup.py install
t. pip 安装
tar -xzvf pip-9.0.1.tar.gz
cd pip-9.0.1/
sudo python setup.py install
u. pkgconfig安装
tar -xvzf pkgconfig-1.1.0.tar.gz
cd pkgconfig-1.1.0/
sudo python setup.py install
v. protobuf安装
unzip protobuf-2.5.0.zip
cd protobuf-2.5.0/
sudo ./configure --prefix=/usr #漏掉了 --prefix 安装到/usr/local/lib有报错，将前一次安装的/usr/local/lib下的文件拷贝到/usr/lib****************************
************************************
sudo make
sudo make check
sudo make install
sudo ldconfig
安装protobuf的Python支持
cd python # 位于protobuf下
python setup.py build
sudo python setup.py test
sudo python setup.py install
验证 protoc --version
#python
>>>import google.protobuf
w. pyparsing安装
tar -xzvf pyparsing-2.1.10.tar.gz
cd pyparsing-2.1.10/
sudo python setup.py install
x. python-dateutil安装
tar -xvf python-dateutil-1.4.tar
cd python-dateutil-1.4/
sudo python setup.py install
y. python-gflags安装
tar -xzvf python-gflags-3.1.0.tar.gz
cd python-gflags-3.1.0/
sudo python setup.py install
z. pytz
tar -xvzf pytz-2016.7.tar.gz
cd pytz-2016.7/
sudo python setup.py install
a1. scikit-image
tar -xvzf scikit-image-0.12.3.tar.gz
cd scikit-image-0.12.3/
sudo python setup.py install
b1. scipy
tar -xvzf scipy-0.14.0.tar.gz
cd scipy-0.14.0/
#sudo python setup.py install #LD_LIBRARY_PATH 报错，采用下面方式安装
sudo apt-get install -y python-scipy
cd /usr/lib/python2.7/dist-packages
sudo cp -rf scipy* /usr/local/lib/python2.7/site-packages/
python
>>> from scipy import *
c1. opencv 安装
sudo pip install opencv-python
也可直接执行opencv_python-3.2.0.6-cp27-cp27mu-manylinux1_x86_64.whl，注意是cp27mu而不是m
sudo pip install opencv_python-3.2.0.6-cp27-cp27mu-manylinux1_x86_64.whl
测试安装
python
>>> import cv2
d1. Wx图形库安装
tar -jxvf wxPython-src-3.0.2.0.tar.bz2
cd wxPython-src-3.0.2.0/
sudo ./configure --prefix=/usr --with-gtk
sudo make
sudo make install
sudo vi /etc/profile
修改或添加上/home/system/source/wxPython-src-3.0.2.0
PATH=$PATH:/home/system/source/wxPython-src-3.0.2.0
LD_LIBRARY_PATH=/home/system/source/wxPython-src-3.0.2.0/lib:$LD_LIBRARY_PATH
cd /usr/lib
sudo ln -s /usr/local/lib/libwx_gtk2u_core-3.0.so.0.2.0
cd wxPython
sudo python setup.py build
sudo python setup.py install
cd /usr/include
cp /home/system/source/wxPython-src-3.0.2.0/lib/wx/include/gtk2-unicode-3.0/wx/setup.h ./wx
sudo cp -rf wx-3.0/wx ./
如果有报错，记得安装以下包：
sudo python setup.py install
sudo apt-get install libghc-gstreamer-dev
gtk2，gtk2-devel，python-devel，tk，tk-devel，gstreamer，gstreamer-devel，mesa-libGL-devel，
mesa-libGLU-devel，mesa-libGLU，mesa-libGL，libSM，libSM-devel，gstreamer-plugins-base-devel
错误的步骤，安装2.8.12.1，好像编译后ansi，不是unicode的
tar -jxvf wxPython-src-2.8.12.1.tar.bz2
cd wxPython-src-2.8.12.1/
sudo ./configure --prefix=/usr --with-gtk --unicode=yes
sudo make
sudo make install
cd wxPython
sudo python setup.py build
sudo python setup.py install
sudo apt-get install python-wxtools
checking for GST... configure: WARNING: GStreamer 0.10 not available, falling back to 0.8
checking for GST... configure: WARNING: GStreamer 0.8/0.10 not available.
configure: error: GStreamer not available
Error running configure
ERROR: failed building wxWidgets
Traceback (most recent call last):
File "build.py", line 1184, in cmd_build_wx
wxbuild.main(wxDir(), build_options)
File "/home/system/source/wxPython_Phoenix-3.0.3/buildtools/build_wxwidgets.py", line 368, in main
"Error running configure")
File "/home/system/source/wxPython_Phoenix-3.0.3/buildtools/build_wxwidgets.py", line 85, in exitIfError
raise builder.BuildError(msg)
BuildError
/usr/include/wx/gtk/clipbrd.h:59:5: error: ‘GtkWidget’ does not name a type
该报错网上提示是自带bug，改为安装3.0.2.0，但是由于安装了2.8，所以需要删除原有2.8，折腾了
下面的安装包错误：
tar -xzvf wx-3.0.3.tar.gz
cd wxPython_Phoenix-3.0.3
以下不对
tar -xzvf wxWidgets-2.8.12.tar.gz
cd wxWidgets-2.8.12/
sudo ./configure --prefix=/usr --with-gtk
sudo make
sudo make install
安装出错：
checking for GST... configure: WARNING: GStreamer 0.10 not available, falling back to 0.8
checking for GST... configure: WARNING: GStreamer 0.8/0.10 not available.
configure: error: GStreamer not available
Error running configure
ERROR: failed building wxWidgets
Traceback (most recent call last):
File "build.py", line 1184, in cmd_build_wx
wxbuild.main(wxDir(), build_options)
File "/home/system/source/wxPython_Phoenix-3.0.3/buildtools/build_wxwidgets.py", line 368, in main
"Error running configure")
File "/home/system/source/wxPython_Phoenix-3.0.3/buildtools/build_wxwidgets.py", line 85, in exitIfError
raise builder.BuildError(msg)
BuildError
wx-config --list
Default config is gtk2-unicode-2.8
Default config will be used for output
Also available in /usr:
wx-config
删除所有与gtk2-unicode-2.8有关的文件和文件夹，重新安装 sudo make install
其他错误处理
configure: error: GStreamer not available
ubuntu14.04安装GStreamer插件
sudo apt-get install libghc-gstreamer-dev
以下不对，记录下走错的路：
sudo add-apt-repository ppa:mc3man/trusty-media
sudo apt-get update
sudo apt-get install gstreamer0.10-ffmpeg
e1. mysql-connector-python安装
也折腾了一下，不知道怎么搞的以前pip install mysql-connector-python-rf==2.1.3和deb包安装都可以，没办法下载一个2.1.4安装
unzip mysql-connector-2.1.4.zip
cd mysql-connector-2.1.4/
sudo python setup.py install
测试：
python
>>>
import mysql.connector
f1. 安装yaml
前面包安装中，已经安装
(5)更改环境变量
export PYTHONPATH=/usr/local/lib/python2.7:/usr/local/lib/python2.7/site-packages:/usr/local/lib/python2.7/plat-linux2:/usr/local/lib/python2.7/lib-tk:/usr/local/lib/python2.7/lib-dynload
export PYTHONHOME=/usr/local/lib/python2.7
错误： ImportError: No module named _io
sudo pip install virtualenv --upgrade
这次还会报错首先会报一个PIC的错误还有/usr/local/lib/libboost_python.so: undefined reference to `PyUnicodeUCS4_AsWideChar'
这时因为caffe需要用UCS4编码格式，但是我们的Python环境是UCS2的所以需要卸载掉我们环境里的所有Python，sudo apt-get remove Python（如果卸载失败需要手动删除比较麻烦），然后手动下载Python的源码包进行编译安装
进入源码目录
./configure --enable-unicode=ucs4 --enable-shared cxxflags=-fPIC cflags=-fPIC
Make;sudo make install
进入Python环境 >>>import sys >>>print(sys.maxunicode)看下打印是不是1114111
（6）安装完Python我们还需要重装boost
sudo apt-get remove libboost-dev
tar -jxvf boost_1_57_0.tar.bz2
sudo ./bootstrap.sh
修改tools/build/boost-build.jam 在最后面加上一行“using mpi ;”(注意mpi后面有个空格，然后一个分号 )
sudo ./b2
mock安装
matplotlib安装
sudo python setup.py install
python删除
sudo apt-get remove Python 卸载的是2.7.6
python3.4删除
sudo rm -rf /usr/local/lib/python3.4/
sudo rm -rf /usr/lib/python3*
sudo rm -rf /usr/bin/python*
如上操作后，报 /usr/bin/python3: 坏的解释器: 没有那个文件或目录
残暴处理
mkdir /usr/bin/bakpython
sudo mv -rf /usr/bin/python /usr/bin/bakpython
sudo cp -rf /usr/local/bin/python* /usr/bin/
sudo ln -s /usr/bin/python2.7 /usr/bin/python3
pyenv global 2.7.12 报错，说没安装 ,放弃
Fatal Python error: Py_Initialize: Unable to get the locale encoding
File "/usr/local/lib/python2.7/encodings/__init__.py", line 123
raise CodecRegistryError,\
^
SyntaxError: invalid syntax
vi /etc/grub.d10_linux
linux ${rel_dirname}/${basename} root=${LINUX_HOST_DEVICE} loop=${loop_file_relative} ro ${args} //修改前
linux ${rel_dirname}/${basename} root=${LINUX_HOST_DEVICE} loop=${loop_file_relative} rw ${args}
sudo update-grub
7.3安装 Tkinter
sudo easy_install Tkinter
sudo pip install Tkinter
sudo apt-get install aptitude
sudo apt-get install python-tk
8、安装caffe
http://www.cnblogs.com/kunyuanjushi/p/5947066.html
http://blog.csdn.net/lu597203933/article/details/46742199
http://www.cnblogs.com/CarryPotMan/p/5392284.html
我参考网址：https://www.zybuluo.com/hanxiaoyang/note/364737
8.1 安装依赖包
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 libgflags-dev libgoogle-glog-dev liblmdb-dev
sudo apt-get install OpenBLAS* #本人忘记按这个了
8.2下载
git clone https://github.com/BVLC/caffe
8.3 安装python依赖(路径根据自己的目录可能要调一下)
切换到root用户下执行，否则可能出现类似如下错误：
IOError: [Errno 13] 权限不够: '/usr/local/lib/python2.7/site-packages/cython.py'的错误，当然也可以对 /usr/local/lib/python2.7/site-packages权限进行调整
cd caffe/python
执行
for req in $(cat requirements.txt); do pip install $req; done
这步安装也有点慢，别急，等会儿，先去干点别的 ^_^
8.4编辑caffe所需的Makefile文件
cd caffe
cp Makefile.config.example Makefile.config
vim Makefile.config
Makefile.config里面有依赖库的路径，及各种编译配置，如果是没有GPU的情况下，可以参照我下面帮你改的配置文件内容:
## 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
# uncomment to disable IO dependencies and corresponding data layers
# USE_OPENCV := 0
# USE_LEVELDB := 0
# USE_LMDB := 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
# OPENCV_VERSION := 3
# 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
# 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
BLAS := open
# Custom (MKL/ATLAS/OpenBLAS) include and lib directories.
# 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
BLAS_INCLUDE := /usr/include/openblas
# 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
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/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 ?= @
8.4 编译caffe
make -j8
报如下错误
/usr/bin/ld: cannot find -lcblas /usr/bin/ld: cannot find -latlas。
这是由于atlas安装在/usr/lib和/usr/include里面，cd到这个路径下，如果发现只有libblas.so，没有libatlas.so和libcblas.so，那就需要输入以下命令手动建立链接：
sudo ln -sf ./libblas.so.3 ./libatlas.so
sudo ln -sf ./libblas.so.3 ./libcblas.so
?测试一下编译结果
sudo make test -j16
sudo make runtest -j16
[----------] 1 test from HDF5OutputLayerTest/0, where TypeParam = caffe::CPUDevice<float>
[ RUN ] HDF5OutputLayerTest/0.TestForward
[ OK ] HDF5OutputLayerTest/0.TestForward (1 ms)
[----------] 1 test from HDF5OutputLayerTest/0 (1 ms total)
[----------] Global test environment tear-down
[==========] 2037 tests from 267 test cases ran. (596193 ms total)
[ PASSED ] 2037 tests.
8.5.编译pycaffe
sudo make pycaffe -j16
/home/caffe/build/tools/caffe train \
--solver=/home//mnist_solver.prototxt 2>&1 | tee ./mnist_model/cy.txt
/home/system/caffe/build/tools/caffe train --solver=/home/mnist_solver.prototxt 2>&1 | tee ./mnist_model/cy.txt
cd /home/system/caffe/
./data/mnist/get_mnist.sh # 下载数据
/home/system/caffe/examples/mnist/train_lenet.sh
注意下载数据
8.6 安装fast-rcnn
参考
http://blog.csdn.net/u014696921/article/details/52703586
git clone --recursive https://github.com/rbgirshick/fast-rcnn.git
'bcd9b4eadc7d8fbc433aeefd564e82ec63aaf69c'
‘0dcd397b29507b8314e252e850518c5695efbb83’
~/source/caffe-fast-rcnn
cp Makefile.config.example Makefile.config
sudo make -j8 2>&1|tee make.log
sudo make pycaffe 2>&1|tee make.log
下载Fast RCNN检测器
./data/scripts/fetch_fast_rcnn_models.sh
9、安装mysql-connetor（连接mysql 数据库使用，可以不安装）
1、使用pip install mysql-connector-python-rf==2.1.3进行安装
2、使用下载的离线文件（本次使用该方法安装失败，建议使用方法1，应该是python不认）
mysql-connector-python_2.2.0-1ubuntu14.04_all.deb
dpkg -i mysql-connector-python_2.2.0-1ubuntu14.04_all.deb
或
mysql-connector-python-2.1.3-1.el6.x86_64.rpm
rpm -ivh mysql-connector-python-2.1.3-1.el6.x86_64.rpm
离线安装完成后,执行如下命令：
cp -r /usr/lib/python2.7/dist-packages/*mysql* /usr/local/lib/python2.7/site-packages/
cd /usr/local/lib/python2.7/site-packages/
ls -l *mysq*
一定要有如下信息，mysql 和 mysql_connector_python_rf-2.1.3.dist-info 文件夹
mysql:
total 8
drwxr-sr-x 5 root staff 4096 Aug 25 16:20 connector
-rw-r--r-- 1 root staff 0 Aug 25 16:20 __init__.py
-rw-r--r-- 1 root staff 197 Aug 25 16:20 __init__.pyc
mysql_connector_python_rf-2.1.3.dist-info:
total 32
-rw-r--r-- 1 root staff 139 Aug 25 16:20 DESCRIPTION.rst
-rw-r--r-- 1 root staff 4 Aug 25 16:20 INSTALLER
-rw-r--r-- 1 root staff 1466 Aug 25 16:20 METADATA
-rw-r--r-- 1 root staff 1363 Aug 25 16:20 metadata.json
-rw-r--r-- 1 root staff 5568 Aug 25 16:20 RECORD
-rw-r--r-- 1 root staff 6 Aug 25 16:20 top_level.txt
-rw-r--r-- 1 root staff 104 Aug 25 16:20 WHEEL
10、解决ubuntu新建用户后，tab键不能使用的问题
时间:2015-11-12来源:linux网站 作者:期待一片自己的蓝天
一、新建用户 support
adduser 新建用户的名字
passwd 新建用户的名字即可添加新用户
二、创建家目录
# cd /home
1.创建家目录：
# mkdir 新建用户的名字
2.拷贝环境变量模板文件：
# cp /etc/skel/.b* support
# cp /etc/skel/.p* support
3.修改权限
# chown -R support:support support
# chmod 770 support
三、赋予ROOT权限
方法一： 修改 /etc/sudoers 文件，找到下面一行，把前面的注释（#）去掉
## Allows people in group wheel to run all commands
%wheel ALL=(ALL) ALL
然后修改用户，使其属于root组（wheel），命令如下：
#usermod -g root 用户名
修改完毕，现在可以用新建的用户名帐号登录，然后用命令 su - ，即可获得root权限进行操作。
方法二： 修改 /etc/sudoers 文件，找到下面一行，在root下面添加一行，如下所示：
## Allow root to run any commands anywhere
root ALL=(ALL) ALL
新建用户的名字 ALL=(ALL) ALL
修改完毕，现在可以用新建的用户名字帐号登录，然后用命令 sudo su -，即可获得root权限进行操作。
四、不能使用TAB键、上下键，命令行不显示当前路径的解决
因默认ubuntu创建的普通帐号，默认shell为/bin/sh，而这不支持tab等键的，所以将「指定用户」帐号的shell改为/bin/bash就可以了。
1.查看当前的shell：
# echo $SHELL
/bin/sh
2.修改shell为/bin/bash：
# usermod -s /bin/bash 用户名
11、查看系统驱动和信息
11.1显卡驱动
lspci | grep -i nvidia
11.2系统信息
uname -m && cat /etc/*release
12.ubuntu开机只有桌面，没有菜单栏和任务栏，只有壁纸
sudo apt-get install unity --fix-missing
13、修改IP地址和机器名称
修改机器名和IP地址
1、gedit /etc/hostname
2、gedit /etc/hosts
3、gedit /etc/network/interfaces
添加内容如下（根据自己的需要修改）：
auto lo
iface lo inet loopback
auto eth0
iface eth0 inet static
address 10.1.132.233
netmask 255.255.255.0
gateway 10.1.132.1
dns-nameservers 10.36.8.40 10.36.8.41
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