Linux下Anaconda+Tensorflow环境安装与配置(超简单)
发布时间:2018-07-05 16:23,
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Linux
Anaconda
Tensorflow
Anaconda安装
在清华大学 TUNA 镜像源
选择对应的操作系统与所需的Python版本下载Anaconda安装包。Windows环境下的安装包直接执行.exe文件进行安装即可,Ubuntu环境下在终端执行
$ bash Anaconda2-4.3.1-Linux-x86_64.sh #Python 2.7版本
或者
$ bash Anaconda3-4.3.1-Linux-x86_64.sh #Python 3.5 版本
在安装的过程中,会询问安装路径,按回车即可。之后会询问是否将Anaconda安装路径加入到环境变量(.bashrc)中,输入yes,这样以后在终端中输入python即可直接进入Anaconda的Python版本(如果你的系统中之前安装过Python,自行选择yes
or no)。安装成功后,会有当前用户根目录下生成一个anaconda2的文件夹,里面就是安装好的内容
查询安装信息
$ conda info
查询当前已经安装的库
$ conda list
安装库(*代表库名称)
$ conda install ***
更新库
$ conda update ***
Anaconda仓库镜像
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
$ conda config --add channels https://mirrors.tuna.tsinghua.edu.cn
/anaconda/pkgs/free/ $ conda config --set show_channel_urls yes $ conda install
numpy#测试是否添加成功
之后会自动在用户根目录生成“.condarc”文件,Ubuntu环境下路径为~/.condarc,Windows环境下路径为C:\用户\your_user_name.condarc
channels: - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/ -
defaultsshow_channel_urls: yes
如果要删除镜像,直接删除“.condarc”文件即可
Tensorflow安装
在终端或cmd中输入以下命令搜索当前可用的tensorflow版本
$ anaconda search -t conda tensorflow Using Anaconda API: https:
//api.anaconda.org Run 'anaconda show ' 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
$ anaconda show jjh_cio_testing/tensorflow-gpu Using Anaconda API: https://api
.anaconda.org Name: tensorflow-gpu Summary: Access: public Package Types: conda
Versions: + 1.0.1 To 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
$ conda install --channel https://conda.anaconda.org/jjh_cio_testing
tensorflow-gpu Fetching package metadata ............. Solving package
specifications:. Package plan for installation in environment
/home/will/anaconda2: The following packages will be SUPERSEDEDby 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_testing Proceed ([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
可以选择次高版本的Tensorflow安装,因为最新版本可能清华 TUNA的仓库镜像库没有及时更新,而官方更新连接总是失败。
顺利安装成功,进入python,输入
import tensorflow as tf
如果没有报错说明安装成功。