一、首先下载anaconda,下载:Anaconda2-4.3.1-Linux-x86_64.sh(https://repo.continuum.io/archive/)参考网址:https://www.cnblogs.com/willnote/p/6746499.html
二、安装anaconda,进入下载目录
如果没有修改的话,默认的下载目录是在 /home/下载/下,Ctrl+Alt+T打开终端,输入 cd /home,然后按两次Tab键,终端会自动补上用户名以及该用户名下的文件目录:
可以看到排列出的所有文件夹,继续输入 cd/home/dcrmg/下载 ,进入下载目录:
三. 安装Anaconda
下载的文件是以 .sh 为后缀的,名称比较长,我这里先给它给改名称为 Anaconda.sh。
在终端继续输入 sudo bash Anaconda.sh ,开始执行Anaconda安装。
会要求先输入用户密码,然后是许可文件,直接按Enter继续:
接受许可,输入yes,按回车:
提示默认安装路径是 /home/dcrmg/anaconda2 ,按回车确认,开始安装:
四. 添加环境变量
安装完成之后,会提示是否添加环境变量,输入 yes 后回车:
这样Anaconda安装成功了。终端窗口提示要使环境变量生效,需要重新打开一个终端。在一个新开的终端里输入python,提示信息显示已经不是Linux系统自带的python了:
或者也可以在当前的终端里让刚配置的环境变量生效,方法是在安装Anaconda的终端中输入:
source ~/.bashrc
五、打开jupyter notebook
在终端输入jupyter notebook即可,如下图:

官方下载更新工具包的速度很慢,所以继续添加清华大学 TUNA提供的Anaconda仓库镜像,在终端或cmd中输入如下命令进行添加
|
1
2
|
$ conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/$ conda config --set show_channel_urls yes |
备注:如果出现conda命令未找到,查看:https://www.cnblogs.com/chamie/p/10009193.html
在终端或cmd中输入以下命令搜索当前可用的tensorflow版本
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
|
(可以略掉)$ anaconda search -t conda tensorflowUsing Anaconda API: https://api.anaconda.orgRun ‘anaconda show <USER/PACKAGE>‘ to get more details:Packages: Name | Version | Package Types | Platforms ------------------------- | ------ | --------------- | --------------- HCC/tensorflow | 1.0.0 | conda | linux-64 HCC/tensorflow-cpucompat | 1.0.0 | conda | linux-64 HCC/tensorflow-fma | 1.0.0 | conda | linux-64 SentientPrime/tensorflow | 0.6.0 | conda | osx-64 : TensorFlow helps the tensors flow acellera/tensorflow-cuda | 0.12.1 | conda | linux-64 anaconda/tensorflow | 1.0.1 | conda | linux-64 anaconda/tensorflow-gpu | 1.0.1 | conda | linux-64 conda-forge/tensorflow | 1.0.0 | conda | linux-64, win-64, osx-64 : TensorFlow helps the tensors flow creditx/tensorflow | 0.9.0 | conda | linux-64 : TensorFlow helps the tensors flow derickl/tensorflow | 0.12.1 | conda | osx-64 dhirschfeld/tensorflow | 0.12.0rc0 | conda | win-64 dseuss/tensorflow | | conda | osx-64 guyanhua/tensorflow | 1.0.0 | conda | linux-64 ijstokes/tensorflow | 2017.03.03.1349 | conda, ipynb | linux-64 jjh_cio_testing/tensorflow | 1.0.1 | conda | linux-64 jjh_cio_testing/tensorflow-gpu | 1.0.1 | conda | linux-64 jjh_ppc64le/tensorflow | 1.0.1 | conda | linux-ppc64le jjh_ppc64le/tensorflow-gpu | 1.0.1 | conda | linux-ppc64le jjhelmus/tensorflow | 0.12.0rc0 | conda, pypi | linux-64, osx-64 : TensorFlow helps the tensors flow jjhelmus/tensorflow-gpu | 1.0.1 | conda | linux-64 kevin-keraudren/tensorflow | 0.9.0 | conda | linux-64 lcls-rhel7/tensorflow | 0.12.1 | conda | linux-64 marta-sd/tensorflow | 1.0.1 | conda | linux-64 : TensorFlow helps the tensors flow memex/tensorflow | 0.5.0 | conda | linux-64, osx-64 : TensorFlow helps the tensors flow mhworth/tensorflow | 0.7.1 | conda | osx-64 : TensorFlow helps the tensors flow miovision/tensorflow | 0.10.0.gpu | conda | linux-64, osx-64 msarahan/tensorflow | 1.0.0rc2 | conda | linux-64 mutirri/tensorflow | 0.10.0rc0 | conda | linux-64 mwojcikowski/tensorflow | 1.0.1 | conda | linux-64 rdonnelly/tensorflow | 0.9.0 | conda | linux-64 rdonnellyr/r-tensorflow | 0.4.0 | conda | osx-64 test_org_002/tensorflow | 0.10.0rc0 | conda | Found 32 packages |
选择一个较新的CPU或GPU版本,如jjh_cio_testing/tensorflow-gpu的1.0.1版本,输入如下命令查询安装命令
|
1
2
3
4
5
6
7
8
9
10
11
12
|
(可以略掉)$ anaconda show jjh_cio_testing/tensorflow-gpuUsing Anaconda API: https://api.anaconda.orgName: tensorflow-gpuSummary:Access: publicPackage Types: condaVersions: + 1.0.1To install this package with conda run: conda install --channel https://conda.anaconda.org/jjh_cio_testing tensorflow-gpu |
使用最后一行的提示命令进行安装
|
1
2
3
4
5
6
7
8
9
10
11
12
|
$ conda install --channel https://conda.anaconda.org/jjh_cio_testing tensorflow-gpu==1.3.0Fetching package metadata .............Solving package specifications: .Package plan for installation in environment /home/will/anaconda2:The following packages will be SUPERSEDED by a higher-priority channel: tensorflow-gpu: 1.0.1-py27_4 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free --> 1.0.1-py27_4 jjh_cio_testingProceed ([y]/n)? |
conda会自动检测安装此版本的Tensorflow所依赖的库,如果你的Anaconda缺少这些依赖库,会提示你安装。因为我之前已经安装过了,所以这里只提示我安装Tensorflow。输入y并回车之后等待安装结束即可
进入python,输入
|
1
|
import tensorflow as tf |
如果没有报错说明安装成功。
安装完CUDA 8 和 cuDNN 5后, 在终端输入 sudo apt-get install libcupti-dev(参考:https://www.cnblogs.com/zengcv/p/6564517.html)
Ubuntu14.04默认安装的Python2.7.6
先安装Python库
|
1
|
sudo apt-get install python-pip python-dev |
安装tensorflow:
(1)在线安装
sudo pip install https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.0.1-cp27-none-linux_x86_64.whl
(2)下载安装(由于Ubuntu系统下,网上比较慢,可以在windows下载。推荐这种安装方法)
sudo pip install tensorflow_gpu-1.0.1-cp27-none-linux_x86_64.whl
(下载地址:https://pypi.org/project/tensorflow-gpu/1.0.1/#files)
参考文献:
1.https://www.cnblogs.com/chamie/p/8876271.html
2.https://www.cnblogs.com/hezhiyao/p/8328634.html
原文:https://www.cnblogs.com/happystudyeveryday/p/10808439.html