无虚拟环境，进不同的python版本
python2 \\进Python2
python3 \\进python3.5
python3.6 \\进python3.6
升级ubuntu中自带的3.5，新安装3.6
$sudo add-apt-repository ppa:jonathonf/python-3.6
$ sudo apt update
$ sudo apt install python3.6
pip3 //python3安装
pip //python安装
首先，安装virtualenv，在默认的python2下的pip就行：
$ [sudo] pip install virtualenv
创建虚拟环境:
$ virtualenv -p /usr/bin/python3.6 py36
激活虚拟环境：
$ source py36/bin/activate
你会注意到shell的提示符行前多了(py36)字样，这样你就可以放心的使用python3做开发了。先下载个三方库试试吧
pip install httplib2
大功告成了！
如果要退出python3虚拟环境，输入命令
$ deactivate
即可。
source:
https://my.oschina.net/xiaoiaozi/blog/129769
安装cuda8.0
下载地址：https://developer.nvidia.com/cuda-80-ga2-download-archive
我们下载好cuda后直接放在home目录下，直接使用：
sudosh cuda_8.0.27_linux.run
之后一直按空格到100%后输入accept接受条款，
输入no不安装NVIDIA驱动，因为我们已经在上面安装过了；
输入y安装cuda8.0工具，回车使用默认路径安装cuda8.0工具，
输入y使用’sudo’命令，接着输入密码；
输入n不安装指向/usr/local/cuda的符号连接（也可选择y安装符号连接）；
输入y安装cuda8.0的实例，我们可以用此来检验cuda是否安装成功，回车选择默认路径安装；
接着我们就等待cuda安装成功。
cuda环境配置
建立软连接；
设置环境变量，终端输入
sudo gedit /etc/profile (一般使用gedit来修改，很方便，如果你喜欢vim也可以用vim)
在末尾加入
PATH=/usr/local/cuda-8.0/bin:$PATH
export PATH
保存后，创建链接文件
sudo gedit /etc/ld.so.conf.d/cuda.conf
增加下面一行
/usr/local/cuda-8.0/lib64
最后在终端输入sudo ldconfig使链接生效。
安装cudnn
cudnn下载地址：https://developer.nvidia.com/cudnn
(py36) haoran@haoran-Inspiron-7447:~$ sudo tar xvf cudnn-8.0-linux-x64-v7.1.tgz
cuda/include/cudnn.h
cuda/NVIDIA_SLA_cuDNN_Support.txt
cuda/lib64/libcudnn.so
cuda/lib64/libcudnn.so.7
cuda/lib64/libcudnn.so.7.1.3
cuda/lib64/libcudnn_static.a
(py36) haoran@haoran-Inspiron-7447:~$ cd cuda/include
(py36) haoran@haoran-Inspiron-7447:~/cuda/include$ sudo cp *.h /usr/local/include/
(py36) haoran@haoran-Inspiron-7447:~/cuda/include$ cd ../lib64
(py36) haoran@haoran-Inspiron-7447:~/cuda/lib64$ sudo cp lib* /usr/local/lib/
(py36) haoran@haoran-Inspiron-7447:~/cuda/lib64$ cd /usr/local/lib# sudo chmod +r libcudnn.so.7.1.3
bash: cd: /usr/local/lib#: No such file or directory
(py36) haoran@haoran-Inspiron-7447:~/cuda/lib64$ cd /usr/local/lib
(py36) haoran@haoran-Inspiron-7447:/usr/local/lib$ sudo chmod +r libcudnn.so.7.1.3
(py36) haoran@haoran-Inspiron-7447:/usr/local/lib$ sudo ln -sf libcudnn.so.7.1.3 libcudnn.so.7
(py36) haoran@haoran-Inspiron-7447:/usr/local/lib$ sudo ln -sf libcudnn.so.5 libcudnn.so
(py36) haoran@haoran-Inspiron-7447:/usr/local/lib$ sudo ldconfig
(py36) haoran@haoran-Inspiron-7447:~/NVIDIA_CUDA-8.0_Samples$ sudo make all -j8
cudnn对应版本不对
参考tensorflow网页：https://www.tensorflow.org/install/install_sources#common_installation_problems
这不坑爹嘛
cudnn6 对应 cuda8.0
haoran@haoran-Inspiron-7447:~/Downloads$ sudo tar xvf cudnn-8.0-linux-x64-v6.0.tgz
[sudo] password for haoran:
cuda/include/cudnn.h
cuda/lib64/libcudnn.so
cuda/lib64/libcudnn.so.6
cuda/lib64/libcudnn.so.6.0.21
cuda/lib64/libcudnn_static.a
haoran@haoran-Inspiron-7447:~/Downloads$ cd cuda/include
haoran@haoran-Inspiron-7447:~/Downloads/cuda/include$ sudo cp *.h /usr/local/include/
haoran@haoran-Inspiron-7447:~/Downloads/cuda/include$ cd ../lib64
haoran@haoran-Inspiron-7447:~/Downloads/cuda/lib64$ sudo cp lib* /usr/local/lib/cp: not writing through dangling symlink '/usr/local/lib/libcudnn.so'
haoran@haoran-Inspiron-7447:~/Downloads/cuda/lib64$ sudo cp cuda/include/cudnn.h/usr/local/cuda-8.0/include/
cp: missing destination file operand after 'cuda/include/cudnn.h/usr/local/cuda-8.0/include/'
Try 'cp --help' for more information.
haoran@haoran-Inspiron-7447:~/Downloads/cuda/lib64$ sudo cp cuda/include/cudnn.h /usr/local/cuda-8.0/include/
cp: cannot stat 'cuda/include/cudnn.h': No such file or directory
haoran@haoran-Inspiron-7447:~/Downloads/cuda/lib64$ cd /usr/local/lib
haoran@haoran-Inspiron-7447:/usr/local/lib$ sudo chmod +r libcudnn.so.6.0
chmod: cannot access 'libcudnn.so.6.0': No such file or directory
haoran@haoran-Inspiron-7447:/usr/local/lib$ ls
libcudnn.so libcudnn.so.6.0.21 libcudnn.so.7.1.3 python2.7 python3.6
libcudnn.so.6 libcudnn.so.7 libcudnn_static.a python3.5
haoran@haoran-Inspiron-7447:/usr/local/lib$ sudo chmod +r libcudnn.so.6.0.21
haoran@haoran-Inspiron-7447:/usr/local/lib$ sudo ln -sf libcudnn.so.6.0.21 libcudnn.so.6
haoran@haoran-Inspiron-7447:/usr/local/lib$ sudo ldconfig
haoran@haoran-Inspiron-7447:/usr/local/lib$
cuda sample 测试
打开CUDA 8.0 Samples默认安装路径，终端输入
cd /home/its/NVIDIA_CUDA-8.0_Samples （its是我的用户名）
sudo make all –j16 （16核，根据你的电脑配置，核越多运行越快）
- 下面的错误我没有出
出现“unsupported GNU version! gcc versions later than 5.3 arenot supported!”的错误，这是由于GCC版本过高，在终端输入
cd /usr/local/cuda-8.0/include
sudo gedit host_config.h
ctrl+f寻找有“5.3”的地方，只有一处，如下
# if __GNUC__ > 5 || (__GNUC__ == 5 && __GNUC_MINOR__ > 3)
#error -- unsupported GNU version! gcc versions later than 5.3 are notsupported!
将3改成9，这样在GCC版本大于5.9的时候才报错，即
# if __GNUC__ > 5 || (__GNUC__ == 5 && __GNUC_MINOR__ > 9)
- 从这开始继续make
保存退出，继续在终端输入
sudo make all –j16 （16核）
完成后继续向终端输入
cd bin/x86_64/linux/release
./deviceQuery
出现下图的输出则说明cuda配置正常
source:
http://www.linuxdiyf.com/linux/32118.html
https://www.jianshu.com/p/69a10d0a24b9
https://blog.csdn.net/u012436149/article/details/74171047
anaconda 环境下获取包内容
anaconda search -t conda keras
jupyter notebook 安装
pip3 install jupyter
运行
jupyter notebook