标签：tensorflow安装
简介tensorflow的安装分cpu版本和gpu版本，
这里只讨论cpu版本。
google提供了很多种安装方式，
主要分三种，
一种是pip安装，非常简单，重要的是它在各个平台都是可以用的，包括windows，但是CentOS6需升级glibc和gcc（CXXABI_）版本
第二种是通过docker安装，也差不多是一键安装，内核版本低于3.10不能安装docker，具体的介绍可以看https://github.com/tensorflow/tensorflow/tree/master/tensorflow/tools/docker
最后一种，就是源码编译安装，最麻烦。
Linux系统官方推荐安装在ubuntu-14及以上
本文采用pip安装Linux下默认系统自带python2.6的版本，这个版本被系统很多程序所依赖，所以不建议删除，
如果使用最新的Python3那么我们知道编译安装源码包和系统默认包之间是没有任何影响的，所以可以安装python3和python2共存$ yum install wget gcc automake autoconf libtool make xz$ yum install zlib-devel openssl-devel bzip2-devel
依赖关系解决
===============================================================================================================================================================================================
软件包 架构 版本 仓库 大小
===============================================================================================================================================================================================
正在安装:
bzip2-devel x86_64 1.0.5-7.el6_0 base 250 k
openssl-devel x86_64 1.0.1e-57.el6 base 1.2 M
zlib-devel x86_64 1.2.3-29.el6 base 44 k
为依赖而安装:
keyutils-libs-devel x86_64 1.4-5.el6 base 29 k
krb5-devel x86_64 1.10.3-65.el6 base 504 k
libcom_err-devel x86_64 1.41.12-23.el6 base 33 k
libkadm5 x86_64 1.10.3-65.el6 base 143 k
libselinux-devel x86_64 2.0.94-7.el6 base 137 k
libsepol-devel x86_64 2.0.41-4.el6 base 64 k
为依赖而更新:
e2fsprogs x86_64 1.41.12-23.el6 base 554 k
e2fsprogs-libs x86_64 1.41.12-23.el6 base 121 k
krb5-libs x86_64 1.10.3-65.el6 base 675 k
libcom_err x86_64 1.41.12-23.el6 base 38 k
libss x86_64 1.41.12-23.el6 base 42 k
openssl x86_64 1.0.1e-57.el6 base 1.5 M
事务概要
===============================================================================================================================================================================================
$ yum install -y tkinter tk-devel tk # 在Linux中python默认是不安装Tkinter模块，matplotlib依赖Tkinter模块
依赖关系解决
===============================================================================================================================================================================================
软件包 架构 版本 仓库 大小
===============================================================================================================================================================================================
正在安装:
tk x86_64 1:8.5.7-5.el6 base 1.4 M
tk-devel x86_64 1:8.5.7-5.el6 base 496 k
tkinter x86_64 2.6.6-66.el6_8 base 258 k
为依赖而安装:
fontconfig-devel x86_64 2.8.0-5.el6 base 209 k
freetype-devel x86_64 2.3.11-17.el6 base 365 k
libX11-devel x86_64 1.6.4-3.el6 base 983 k
libXau-devel x86_64 1.0.6-4.el6 base 14 k
libXft-devel x86_64 2.3.2-1.el6 base 19 k
libXrender-devel x86_64 0.9.10-1.el6 base 17 k
libxcb-devel x86_64 1.12-4.el6 base 1.1 M
tcl x86_64 1:8.5.7-6.el6 base 1.9 M
tcl-devel x86_64 1:8.5.7-6.el6 base 162 k
tix x86_64 1:8.4.3-5.el6 base 252 k
xorg-x11-proto-devel noarch 7.7-14.el6 base 288 k
为依赖而更新:
libX11 x86_64 1.6.4-3.el6 base 587 k
libX11-common noarch 1.6.4-3.el6 base 171 k
libXrender x86_64 0.9.10-1.el6 base 24 k
libxcb x86_64 1.12-4.el6 base 180 k
python x86_64 2.6.6-66.el6_8 base 76 k
python-libs x86_64 2.6.6-66.el6_8 base 5.3 M
事务概要
===============================================================================================================================================================================================
Install 14 Package(s)
Upgrade 6 Package(s)
$ yum install readline-devel.x86_64 #解决python3退格功能
依赖关系解决
================================================================================================================================================================================================
软件包 架构 版本 仓库 大小
================================================================================================================================================================================================
正在安装:
readline-devel x86_64 6.0-4.el6 base 134 k
为依赖而安装:
ncurses-devel x86_64 5.7-4.20090207.el6 base 641 k
事务概要
================================================================================================================================================================================================
Install 2 Package(s)$ wget https://www.python.org/ftp/python/3.5.4/Python-3.5.4.tar.xz
$ tar xf Python-3.5.4.tar.xz
$ cd Python-3.5.4
$ ./configure --enable-unicode=ucs2 --enable-shared // --enable-optimizations
$echo $?
0
$ make && make install
Collecting setuptools
Collecting pip
Installing collected packages: setuptools, pip
Successfully installed pip-9.0.1 setuptools-28.8.0
$echo $?
0
如果提示：Ignoring ensurepip failure: pip 8.1.1 requires SSL/TLS；原因没有安装或升级oenssl:
$ echo -e "/usr/local/lib/\n/usr/local/lib64/" > /etc/ld.so.conf.d/local-lib-x86_64.conf
$ ldconfig
$ python3 -V
Python 3.5.4
$ pip3 -V #或:pip -V 强烈建议使用8.1或更高版本的pip或pip3
pip 9.0.1 from /usr/local/lib/python3.5/site-packages (python 3.5)
$ which pip3
/usr/local/bin/pip3
升级pip
$ python3 -m pip install -U pip
Requirement already up-to-date: pip in /usr/local/lib/python3.5/site-packages
如果发现没有安装pip，请单独安装pip：
$ wget https://link.jianshu.com/?t=https://bootstrap.pypa.io/get-pip.py
$ mv index.html\?t\=https\:%2F%2Fbootstrap.pypa.io%2Fget-pip.py get-pip.py
$ python3 get-pip.py$ pip3 install tensorflow-gpu #Python 3.n; GPU支持（须有英伟达显卡）
$ pip3 install tensorflow #Python 3.n; CPU支持（不支持GPU）
Collecting tensorflow
Downloading tensorflow-1.4.0-cp35-cp35m-manylinux1_x86_64.whl (40.7MB)
100% |████████████████████████████████| 40.7MB 7.8kB/s
Collecting numpy>=1.12.1 (from tensorflow)
Downloading numpy-1.13.3-cp35-cp35m-manylinux1_x86_64.whl (16.9MB)
100% |████████████████████████████████| 16.9MB 9.1kB/s
Collecting six>=1.10.0 (from tensorflow)
Downloading six-1.11.0-py2.py3-none-any.whl
Collecting protobuf>=3.3.0 (from tensorflow)
Downloading protobuf-3.5.0.post1-cp35-cp35m-manylinux1_x86_64.whl (6.4MB)
100% |████████████████████████████████| 6.4MB 11kB/s
Collecting wheel>=0.26 (from tensorflow)
Downloading wheel-0.30.0-py2.py3-none-any.whl (49kB)
100% |████████████████████████████████| 51kB 36kB/s
Collecting tensorflow-tensorboard<0.5.0,>=0.4.0rc1 (from tensorflow)
Downloading tensorflow_tensorboard-0.4.0rc3-py3-none-any.whl (1.7MB)
100% |████████████████████████████████| 1.7MB 14kB/s
Collecting enum34>=1.1.6 (from tensorflow)
Downloading enum34-1.1.6-py3-none-any.whl
Requirement already satisfied: setuptools in /usr/local/lib/python3.5/site-packages (from protobuf>=3.3.0->tensorflow)
Collecting markdown>=2.6.8 (from tensorflow-tensorboard<0.5.0,>=0.4.0rc1->tensorflow)
Downloading Markdown-2.6.9.tar.gz (271kB)
100% |████████████████████████████████| 276kB 23kB/s
Collecting bleach==1.5.0 (from tensorflow-tensorboard<0.5.0,>=0.4.0rc1->tensorflow)
Downloading bleach-1.5.0-py2.py3-none-any.whl
Collecting html5lib==0.9999999 (from tensorflow-tensorboard<0.5.0,>=0.4.0rc1->tensorflow)
Downloading html5lib-0.9999999.tar.gz (889kB)
100% |████████████████████████████████| 890kB 18kB/s
Collecting werkzeug>=0.11.10 (from tensorflow-tensorboard<0.5.0,>=0.4.0rc1->tensorflow)
Downloading Werkzeug-0.12.2-py2.py3-none-any.whl (312kB)
100% |████████████████████████████████| 317kB 18kB/s
Installing collected packages: numpy, six, protobuf, wheel, markdown, html5lib, bleach, werkzeug, tensorflow-tensorboard, enum34, tensorflow
Running setup.py install for markdown ... done
Running setup.py install for html5lib ... done
Successfully installed bleach-1.5.0 enum34-1.1.6 html5lib-0.9999999 markdown-2.6.9 numpy-1.13.3 protobuf-3.5.0.post1 six-1.11.0 tensorflow-1.4.0 tensorflow-tensorboard-0.4.0rc3 werkzeug-0.12.2 wheel-0.30.0$ pip3 uninstall tensorflow # for Python 3.n$ pip3 install matplotlib
Collecting matplotlib
Downloading matplotlib-2.1.0-cp35-cp35m-manylinux1_x86_64.whl (15.0MB)
100% |████████████████████████████████| 15.0MB 13kB/s
Collecting pytz (from matplotlib)
Downloading pytz-2017.3-py2.py3-none-any.whl (511kB)
100% |████████████████████████████████| 512kB 37kB/s
Requirement already satisfied: six>=1.10 in /usr/local/lib/python3.5/site-packages (from matplotlib)
Collecting python-dateutil>=2.0 (from matplotlib)
Downloading python_dateutil-2.6.1-py2.py3-none-any.whl (194kB)
100% |████████████████████████████████| 194kB 41kB/s
Collecting pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 (from matplotlib)
Downloading pyparsing-2.2.0-py2.py3-none-any.whl (56kB)
100% |████████████████████████████████| 61kB 24kB/s
Requirement already satisfied: numpy>=1.7.1 in /usr/local/lib/python3.5/site-packages (from matplotlib)
Collecting cycler>=0.10 (from matplotlib)
Downloading cycler-0.10.0-py2.py3-none-any.whl
Installing collected packages: pytz, python-dateutil, pyparsing, cycler, matplotlib
Successfully installed cycler-0.10.0 matplotlib-2.1.0 pyparsing-2.2.0 python-dateutil-2.6.1 pytz-2017.3
$ pip3 install Pillow
Collecting Pillow
Downloading Pillow-4.3.0-cp35-cp35m-manylinux1_x86_64.whl (5.8MB)
100% |████████████████████████████████| 5.8MB 10kB/s
Collecting olefile (from Pillow)
Downloading olefile-0.44.zip (74kB)
100% |████████████████████████████████| 81kB 15kB/s
Building wheels for collected packages: olefile
Running setup.py bdist_wheel for olefile ... done
Stored in directory: /root/.cache/pip/wheels/20/58/49/cc7bd00345397059149a10b0259ef38b867935ea2ecff99a9b
Successfully built olefile
Installing collected packages: olefile, Pillow
Successfully installed Pillow-4.3.0 olefile-0.44bleach-1.5.0
enum34-1.1.6
html5lib-0.9999999
markdown-2.6.9
numpy-1.13.3 # TensorFlow要求的数字处理软件包。
protobuf-3.5.0.post1
six-1.11.0
tensorflow-1.4.0
tensorflow-tensorboard-0.4.0rc3
werkzeug-0.12.2
wheel-0.30.0 # 管理（.whl）格式的Python压缩包。
Pillow-4.3.0
olefile-0.44
cycler-0.10.0
matplotlib-2.1.0
pyparsing-2.2.0
python-dateutil-2.6.1
pytz-2017.3
dev-0.4.0 # 添加Python的扩展。
pip3-9.0.1 # 安装和管理某些Python包。
注：如果无法在线安装，请到https://www.pypi-mirrors.org/上的网址下载，
例如http://pypi.pubyun.com/simple/ ；http://mirrors.163.com/pypi/simple等等由于centos6.x上glibc最多到2.12，而强行使用高版本的glibc会导致程序意外崩溃，因此，我们采用本机源码编译安装。
$ strings /lib64/libc.so.6 |grep GLIBC #查看当前glibc支持的版本
GLIBC_2.2.5
GLIBC_2.2.6
GLIBC_2.3
GLIBC_2.3.2
GLIBC_2.3.3
GLIBC_2.3.4
GLIBC_2.4
GLIBC_2.5
GLIBC_2.6
GLIBC_2.7
GLIBC_2.8
GLIBC_2.9
GLIBC_2.10
GLIBC_2.11
GLIBC_2.12
GLIBC_PRIVATE
$ wget http://ftp.gnu.org/gnu/libc/glibc-2.17.tar.gz
$ tar -zxvf glibc-2.17.tar.gz && cd glibc-2.17
$ mkdir build && cd build
$ ../configure --prefix=/usr --with-headers=/usr/include --with-binutils=/usr/bin
$ make && make install
$ strings /lib64/libc.so.6 |grep GLIBC
GLIBC_2.2.5
GLIBC_2.2.6
GLIBC_2.3
GLIBC_2.3.2
GLIBC_2.3.3
GLIBC_2.3.4
GLIBC_2.4
GLIBC_2.5
GLIBC_2.6
GLIBC_2.7
GLIBC_2.8
GLIBC_2.9
GLIBC_2.10
GLIBC_2.11
GLIBC_2.12
GLIBC_2.13
GLIBC_2.14
GLIBC_2.15
GLIBC_2.16
GLIBC_2.17
GLIBC_PRIVATE$ yum install bzip2 gcc-c++
$ wget http://ftp.gnu.org/gnu/gcc/gcc-4.8.3/gcc-4.8.3.tar.gz
$ tar -zxvf gcc-4.8.3.tar.gz
$ cd gcc-4.8.3
$ ./contrib/download_prerequisites # 脚本文件会帮我们下载、配置、安装依赖库
注：如果服务器无法连接外网，需单独下载这三个包到当前目录下，解压，并做链接；
$ wget ftp://gcc.gnu.org/pub/gcc/infrastructure/mpfr-2.4.2.tar.bz2
$ wget ftp://gcc.gnu.org/pub/gcc/infrastructure/gmp-4.3.2.tar.bz2
$ wget ftp://gcc.gnu.org/pub/gcc/infrastructure/mpc-0.8.1.tar.gz
$ tar xf mpfr-2.4.2.tar.bz2
$ tar xf gmp-4.3.2.tar.bz2
$ tar xf mpc-0.8.1.tar.gz
$ ln -s mpc-0.8.1 mpc
$ ln -s mpfr-2.4.2 mpfr
$ ln -s gmp-4.3.2 gmp
$ll gmp* mpc* mpfr* -d
lrwxrwxrwx 1 root root 9 12月 7 15:23 gmp -> gmp-4.3.2
drwxrwxrwx 15 1001 wheel 4096 1月 8 2010 gmp-4.3.2
lrwxrwxrwx 1 root root 9 12月 7 15:23 mpc -> mpc-0.8.1
drwxrwxrwx 5 1000 1000 4096 12月 8 2009 mpc-0.8.1
lrwxrwxrwx 1 root root 10 12月 7 15:23 mpfr -> mpfr-2.4.2
drwxrwxrwx 5 1114 1114 8192 11月 30 2009 mpfr-2.4.2
$ mkdir build && cd build
$ ../configure -enable-checking=release -enable-languages=c,c++ -disable-multilib
$ make && make install # 测试时make相当慢，大概走了3个小时，一般服务器30分钟
$ gcc -v # 不需要修改环境变量
使用内建 specs。
COLLECT_GCC=gcc
COLLECT_LTO_WRAPPER=/usr/local/libexec/gcc/x86_64-unknown-linux-gnu/4.8.3/lto-wrapper
目标：x86_64-unknown-linux-gnu
配置为：../configure -enable-checking=release -enable-languages=c,c++ -disable-multilib
线程模型：posix
gcc 版本 4.8.3 (GCC)
$ echo -e "/usr/local/lib\n/usr/local/lib64" >/etc/ld.so.conf.d/local_libs.conf
$ ldconfig
如果报：ldconfig: /usr/local/lib64/libstdc++.so.6.0.19-gdb.py 不是 ELF 文件 - 它起始的魔数错误。
ldconfig: /usr/local/lib64/libstdc++.so.6.0.19-gdb.py is not an ELF file - it has the wrong magic bytes at the start.
$ mv /usr/local/lib64/{,bak_}libstdc++.so.6.0.19-gdb.py #改名
$ ldconfig
修改libstdc++.so.6的链接:
$ rm -f /usr/lib64/libstdc++.so.6
$ cp -a /usr/local/lib64/libstdc++.so.6.0.19 /usr/lib64/
$ ln -s /usr/lib64/libstdc++.so.6.0.19 /usr/lib64/libstdc++.so.6
$ strings /usr/lib64/libstdc++.so.6 |grep CXXABI_
CXXABI_1.3
CXXABI_1.3.1
CXXABI_1.3.2
CXXABI_1.3.3
CXXABI_1.3.4
CXXABI_1.3.5
CXXABI_1.3.6
CXXABI_1.3.7
CXXABI_TM_1$ python3 #验证
>>> import tensorflow as tf
>>> hello = tf.constant(‘Hello, TensorFlow!‘)
>>> sess = tf.Session()
>>> print(sess.run(hello))
Hello, TensorFlow!
$ python3
>>> import tensorflow as tf
>>> a = tf.constant(10)
>>> b = tf.constant(32)
>>> print(sess.run(a + b))
42
$ python3
>>> import tensorflow as tf
>>> import os
>>> import shutil
>>> import numpy as np
>>> from PIL import Image
>>> import matplotlib.pyplot as plt
>>>http://blog.csdn.net/numen27/article/details/75332833
http://www.jianshu.com/p/fdb7b54b616e
http://blog.csdn.net/lenbow/article/details/51203526#1
https://www.tensorflow.org/install/install_linux #需×××google使用bazel构建tensorflow，因此我们需要编译之。首先安装64位jdk1.8，因为bazel需要java8来编译，
上传JDK1.8（jdk-8u66-linux-x64.tar.gz）安装包到/data/tools、
$ tar xf jdk-8u66-linux-x64.tar.gz
$ vim /etc/profile.d/java.sh
export JAVA_HOME=/data/tools/jdk1.8.0_66
export PATH=$JAVA_HOME/bin:$JAVA_HOME/jre/bin:$PATH
export CLASSPATH=$JAVA_HOME/lib:$JAVA_HOME/jre/lib
$ source /etc/profile.d/java_pwdx_grep.sh
$ java -version
java version "1.8.0_66"
java(TM) SE Runtime Environment (build 1.8.0_66-b17)
java HotSpot(TM) 64-Bit Server VM (build 25.66-b17, mixed mode)$ git clone https://github.com/bazelbuild/bazel.git
$ cd bazel
$ git checkout -b dev 0.8.0
$ ./compile.shglibc是GNU发布的libc库，即c运行库。 glibc是linux系统中最底层的api，几乎其它任何运行库都会依赖于glibc。 glibc除了封装linux操作系统所提供的系统服务外，它本身也提供了许多其它一些必要功能服务的实现。
由此可见，问题的根源是系统不兼容，ubuntu上用的libc 版本较高，而 CentOS 上用的版本太低导致不能执行。。
解决这个问题有三种方法：
第一种：升级Glibc，这个风险非常大，很多时候升完了发现好多东西都不能用了；
第二种：外链Glibc，也就是在其他目录建一个Glibc，然后添加一个环境变量，这个在网上看貌似是可行的，但我这么做的时候依然报错。
第三种：更换linux系统，这个问题很多时候是CentOS安装tf环境时候造成的，可以尝试更换容器LD_LIBRARY_PATH不能包含当前目录，需要修改环境变量并重新执行configure
echo $LD_LIBRARY_PATH # 查看
export LD_LIBRARY_PATH= # 定义
echo $LD_LIBRARY_PATH # 检查
./glibc-2.14/configure yum install gcc
wget http://ftp.gnu.org/pub/gnu/glibc/glibc-2.17.tar.xz
tar -xvf glibc-2.17.tar.xz
cd glibc-2.17
mkdir build
cd build
../configure --prefix=/usr --disable-profile --enable-add-ons --with-headers=/usr/include --with-binutils=/usr/bin
make && make install
需要等大概10分钟下载Glibc2.14：
http://ftp.gnu.org/gnu/glibc/或者http://www.gnu.org/software/libc/
安装：
xz -d glibc-2.14.tar.xz
tar -xvf glibc-2.14.tar
进入源码目录 建立构建目录，并cd进入构建目录：
cd glibc-2.14
mkdir build
配置：
../configure --prefix=/opt/glibc-2.14
编译安装：
make -j4
sudo make install
临时修改环境变量：
LD_LIBRARY_PATH=/opt/glibc-2.14/lib:$LD_LIBRARY_PATH安装过程中，因为修改/etc/ld.so.conf文件，ldconfig后导致输入命令后，连最基本的命令也会报错：
ls
ls: error while loading shared libraries: __vdso_time: invalid mode for dlopen(): Invalid argument
解决方法：
千万不要断开ssh，不然就远程不上去了
vi /etc/profile 加入
export LD_LIBRARY_PATH=/usr/lib:/usr/lib64:/lib:/lib64:/usr/local/lib:/usr/local/lib64
链接完了之后，Glibc2的问题是没有了，但import tensorflow的时候出现 Segmentation fault (core dumped)因为升级了Glibc，导致系统出问题了，把环境变量改回去就可以了。参考http://blog.csdn.net/rznice/article/details/51090966
其实和找不到glibc2的性质差不多
strings /usr/lib64/libstdc++.so.6.0.13 |grep GLIBCyum install git-core
要是不能联网有没有git都一样，所有包都需要手动下载从以下目录下载binutils：ftp.gnu.org/gnu/binutils/binutils-2.28.tar.bz2
tar jxvf binutils-2.28.tar.bz2
mkdir binutils-build
cd binutils-build
../binutils-2.28/configure
make -j4
make install下载地址1：git clone https://github.com/bazelbuild/bazel（非常之慢）
下载地址2：git clone https://github.com/CStzdong/bazel
发现报错：
INFO: You can skip this first step by providing a path to the bazel binary as second argument:
INFO: ./compile.sh compile /path/to/bazel
?? Building Bazel from scratch
ERROR: Must specify PROTOC if not bootstrapping from the distribution artifact
--------------------------------------------------------------------------------
NOTE: This failure is likely occuring if you are trying to bootstrap bazel from
a developer checkout. Those checkouts do not include the generated output of
the protoc compiler (as we prefer not to version generated files).
* To build a developer version of bazel, do
bazel build //src:bazel
* To bootstrap your first bazel binary, please download a dist archive from our
release page at https://github.com/bazelbuild/bazel/releases and run
compile.sh on the unpacked archive.
The full install instructions to install a release version of bazel can be found
at https://docs.bazel.build/install-compile-source.html
For a rationale, why the bootstrap process is organized in this way, see
https://bazel.build/designs/2016/10/11/distribution-artifact.html
进入错误信息中提到的https://github.com/bazelbuild/bazel/releases网站，选择最近版本的链接，进去后发现有一堆安装包。选择其中的一个直接下载https://github.com/bazelbuild/bazel/releases/download/0.5.3/bazel-0.5.3-installer-linux-x86_64.sh运行安装成功，执行时报错：
/usr/local/bin/bazel: /usr/lib64/libstdc++.so.6: version `GLIBCXX_3.4.19‘ not found (required by /usr/local/bin/bazel)
这个错误会在下文提到
重新运行./compile.sh
运行到一半报错
再执行一次，发现两次运行./compile.sh出现的错误不一致！疑似安装程序bug
尝试低版本bazel0.5.2，仍出现错误
尝试更低版本0.4.5，下载解压缩运行./compile.sh后安装成功！！！
下载地址：https://github.com/bazelbuild/bazel/releases/download/0.4.5/bazel-0.4.5-dist.zip
然后执行：
mkdir bazel-0.4.5-dist
cd bazel-0.4.5-dist
unzip ../bazel-0.4.5-dist.zip
./compile.sh
cp ./output/bazel /usr/local/bin（复制bazel的Binary文件至/usr/local/bin，使得全局都能找到该文件）不建议完全手动安**azel，全程有100多个包的依赖，。，，，，，，依赖的包：
scipy-0.11.0
numpy-1.6.2
nose-1.2.1
lapack-3.4.2
atlas-3.10.0
参考：http://blog.chinaunix.net/uid-22488454-id-3978860.html如果没有pip，就到PIP官网下载get-pip.py。
参考链接：http://www.jianshu.com/p/81b648b1d572
最后从python官网下载p3安装包就好了
如果公司有自己的镜像，可以修改pip的配置文件：
cd ~/.pip/pip.conf(如果没有，就自己建一个；如果不能保存，说明没有.pip目录，需要进入~目录mkdir .pip）
然后加入下面的内容
[global]
index-url = XXX
trusted-host = pypi.douban.com
disable-pip-version-check = true
timeout = 120
注：XXX为国内或企业内部镜像，国内用https://pypi.douban.com/simple，公司内部就用自己的。依据链接http://www.jianshu.com/p/308a4e803c81的说法，先用readelf -s 文件路径|grep GLIBC_2.14查看so里到底哪部分依赖了glibc2.14，发现readelf: command not found，没有readelf命令。。。
（readelf用来显示一个或多个elf格式的目标文件信息）
依据链接http://pkgs.loginroot.com/errors/notFound/readelf，需要添加环境变量：export PATH="/usr/local/sbin:/usr/local/bin:/sbin:/bin:/usr/sbin:/usr/bin:/root/bin"直接强制退出Python了
根据链接https://github.com/tensorflow/tensorflow/issues/8197的解释，原因是gcc的版本过低，更新gcc在前文已经提过了。
还有文章提到是scipy和tensorflow冲突
根据http://blog.csdn.net/shouwangzhelv/article/details/51851155提到的解决方案，重新手工编译了scipy，依然不行。参考：http://www.jianshu.com/p/03d757283339
如果机器不能联网，anaconda基本就废掉了。。。
如果不能用ananconda，只好自己下载包然后上传了，单台机器就rz和sz，多台机器之间传文件就scp xxx root@abc:url首先yum list installed | grep ^tk ；查看是否存在相应模块，通常原因是tkinter和tk-devel缺失。
通过yum install -y tkinter和yum install -y tk-devel下载相应模块，再重新编译Python即可。
或者编译python的时候选择添加参数--enable-unicode=ucs2
$ python3
>>> import matplotlib.pyplot as plt
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/lib/python3.5/site-packages/matplotlib/pyplot.py", line 113, in <module>
_backend_mod, new_figure_manager, draw_if_interactive, _show = pylab_setup()
File "/usr/local/lib/python3.5/site-packages/matplotlib/backends/__init__.py", line 60, in pylab_setup
[backend_name], 0)
File "/usr/local/lib/python3.5/site-packages/matplotlib/backends/backend_tkagg.py", line 6, in <module>
from six.moves import tkinter as Tk
File "/usr/local/lib/python3.5/site-packages/six.py", line 92, in __get__
result = self._resolve()
File "/usr/local/lib/python3.5/site-packages/six.py", line 115, in _resolve
return _import_module(self.mod)
File "/usr/local/lib/python3.5/site-packages/six.py", line 82, in _import_module
__import__(name)
File "/usr/local/lib/python3.5/tkinter/__init__.py", line 35, in <module>
import _tkinter # If this fails your Python may not be configured for Tk
ImportError: No module named ‘_tkinter‘
或者参照：http://www.qttc.net/201304306.html
正确安装新版Python（在Linux中python默认是不安装Tkinter模块，）
1 首先修改Setup.dist文件
$ cd Python-3.5.4
$ cp Modules/Setup.dist{,_$(date +%F)}
$ vim Modules/Setup.dist # 把下面相应行的注释去掉，修改具体版本
_tkinter _tkinter.c tkappinit.c -DWITH_APPINIT -L/usr/local/lib -I/usr/local/include -ltk8.5 -ltcl8.5 -lX11
以上第四行-ltk8.5 -ltcl8.5 默认是 8.2 ，请你系统实际tcl/tk版本修改:我系统中装的是8.5，所以这里我改成了8.5
$ rpm -qa | grep ^tk
tk-8.5.7-5.el6.x86_64
tk-devel-8.5.7-5.el6.x86_64
tkinter-2.6.6-66.el6_8.x86_64
$ rpm -qa | grep ^tcl
tcl-8.5.7-6.el6.x86_64
tcl-devel-8.5.7-6.el6.x86_64
2 安装tck-devel、tk-devel
$ yum install tcl-devel tk-devel -y
3 开始配置安装python
$ ldconfig
$ ./configure
$ make && make install
4 验证
新版Python是否可以使用tkinter模块
$ python3
>>> import tkinter
>>>
旧版Python是否可以使用tkinter模块
$ python
>>> import Tkinter
>>> 执行ldconfig报错：ldconfig: /usr/local/lib64/libstdc++.so.6.0.19-gdb.py is not an ELF file - it has the wrong magic bytes at the start.
不是 ELF 文件 - 它起始的魔数错误。 File "<string>", line 1, in <module>
ImportError: No module named numpy.distutils
-- Found PythonInterp: /usr/local/bin/python3 (found suitable version "3.5.4", minimum required is "3.4")
-- Found PythonLibs: /usr/local/lib/libpython3.5m.so (found suitable exact version "3.5.4")
-- Found JNI: /usr/java/jdk1.8.0_66/jre/lib/amd64/libjawt.so
-- Could NOT find Matlab (missing: MATLAB_MEX_SCRIPT MATLAB_INCLUDE_DIRS MATLAB_ROOT_DIR MATLAB_LIBRARIES MATLAB_LIBRARY_DIRS MATLAB_MEXEXT MATLAB_ARCH MATLAB_BIN)
-- VTK is not found. Please set -DVTK_DIR in CMake to VTK build directory, or to VTK install subdirectory with VTKConfig.cmake file
pytesseract
Collecting pytesseract
Downloading pytesseract-0.1.7.tar.gz (150kB)
100% |████████████████████████████████| 153kB 470kB/s
Collecting Pillow (from pytesseract)
Downloading Pillow-4.3.0-cp35-cp35m-manylinux1_x86_64.whl (5.8MB)
100% |████████████████████████████████| 5.8MB 73kB/s
Collecting olefile (from Pillow->pytesseract)
Downloading olefile-0.44.zip (74kB)
100% |████████████████████████████████| 81kB 95kB/s
安装这三个依赖包
tar -xvf pytesseract-0.1.7.tar.gz
cd pytesseract-0.1.7.tar.gz
python3 setup.py install
pip3 install Pillow-4.3.0-cp35-cp35m-manylinux1_x86_64.whl
unzip olefile-0.44.zip
cd olefile-0.44.zip
python3 setup.py install
参考：
https://m.2cto.com/kf/201610/557136.html
http://techieroop.com/install-opencv-in-centos/
http://blog.csdn.net/zl18310999566/article/details/77880862 yum install gcc gcc-c++ make
yum groupinstall "Development Tools"
yum install autoconf automake libtool
yum install libjpeg-devel libpng-devel libtiff-devel zlib-devel 3.04
版本tar -xvf leptonica-1.72.tar.gz
cd leptonica-1.72
./configure && make && make install 3.04版本
mv 3.04.00.tar.gz Tesseract3.04.00.tar.gz
tar -xvf Tesseract3.04.00.tar.gz
cd tesseract-3.04.00/
./autogen.sh
./configure
make && make install 3.04版本
wget --no-check-certificate https://github.com/tesseract-ocr/tessdata/raw/master/eng.traineddata
wget --no-check-certificate https://github.com/tesseract-ocr/tessdata/raw/master/chi_sim.traineddata
下载这两个语言识别包eng.traineddata，chi_sim.traineddata cp *.traineddata /usr/local/share/tessdata/ export TESSDATA_PREFIX=/usr/local/share/ cp /usr/local/lib/*.so.* /usr/lib64/ CentOS-6.x系统基于python-3.5安装tensorflow-1.4
标签：tensorflow安装
原文地址：http://blog.51cto.com/moerjinrong/2121645
