CentOS7服务器上部署深度/机器学习环境推荐首选anaconda3

CentOS7服务器上部署深度/机器学习环境推荐首选anaconda3，亲测~~ 因为可以创建不同的环境版本或虚拟环境

CentOS7服务器安装anaconda3后，CentOS7服务器开启后自动将anaconda3自身的root(或base)环境开启。
用Xshell打开CentOS7服务器后，可以看见 (base)
WARNING! The remote SSH server rejected X11 forwarding request.
Last login: Tue Mar 12 22:11:51 2019 from 192.168.1.72
(base) [jiangshan@localhost ~]$
查看环境，发现anaconda3自身的root(或base)环境处于活动状态 ============== 默认开机启动（在指定的用户下）
(base) [jiangshan@localhost ~]$ conda info -e
# conda environments:
#
base * /home/jiangshan/anaconda3
（ * 代表活动状态）
===================试验=======================================================
(base) [jiangshan@localhost ~]$ source deactivate
DeprecationWarning: 'source deactivate' is deprecated. Use 'conda deactivate'.
[jiangshan@localhost ~]$
===================试验=======================================================

# TenssorFlow目前还不支持Python 3.7，使用Anaconda3创建Python 3.6虚拟环境
# 创建基于python 3.6 的tensorflow环境：
(base) [jiangshan@localhost ~]$ conda create --name tensorflow python=3.6
==========================================================================
## Package Plan ##

environment location: /home/jiangshan/anaconda3/envs/tensorflow

added / updated specs:
- python=3.6
==========================================================================
查看创建的tensorflow环境
(base) [jiangshan@localhost ~]$ conda info -e
# conda environments:
#
base * /home/jiangshan/anaconda3
tensorflow /home/jiangshan/anaconda3/envs/tensorflow

已经创建tensorflow环境，暂未进入激活
激活 tensorflow
(base) [jiangshan@localhost ~]$ source activate tensorflow

查看已激活的tensorflow环境
(tensorflow) [jiangshan@localhost ~]$ conda info -e
# conda environments:
#
base /home/jiangshan/anaconda3
tensorflow * /home/jiangshan/anaconda3/envs/tensorflow 【有 * 号】

在 tensorflow环境安装 tensorflow
(tensorflow) [jiangshan@localhost ~]$ conda install tensorflow

留意以下信息
==============================================================================================
## Package Plan ##

environment location: /home/jiangshan/anaconda3/envs/tensorflow

added / updated specs:
- tensorflow

The following NEW packages will be INSTALLED:

absl-py anaconda/cloud/conda-forge/linux-64::absl-py-0.7.0-py36_1000
astor anaconda/cloud/conda-forge/noarch::astor-0.7.1-py_0
blas anaconda/pkgs/free/linux-64::blas-1.0-mkl
c-ares anaconda/cloud/conda-forge/linux-64::c-ares-1.15.0-h14c3975_1001
gast anaconda/cloud/conda-forge/noarch::gast-0.2.2-py_0
grpcio pkgs/main/linux-64::grpcio-1.16.1-py36hf8bcb03_1
libgfortran-ng anaconda/cloud/conda-forge/linux-64::libgfortran-ng-7.2.0-hdf63c60_3
libprotobuf anaconda/cloud/conda-forge/linux-64::libprotobuf-3.7.0-hdbcaa40_1
markdown anaconda/cloud/conda-forge/noarch::markdown-2.6.11-py_0
mkl anaconda/pkgs/free/linux-64::mkl-2017.0.3-0
numpy pkgs/main/linux-64::numpy-1.14.2-py36hdbf6ddf_0
protobuf anaconda/cloud/conda-forge/linux-64::protobuf-3.7.0-py36hf484d3e_0
six anaconda/cloud/conda-forge/linux-64::six-1.12.0-py36_1000
tensorboard anaconda/cloud/conda-forge/linux-64::tensorboard-1.10.0-py36_0
tensorflow anaconda/cloud/conda-forge/linux-64::tensorflow-1.10.0-py36_0
termcolor anaconda/cloud/conda-forge/noarch::termcolor-1.1.0-py_2
werkzeug anaconda/cloud/conda-forge/noarch::werkzeug-0.14.1-py_0
==============================================================================================

# 查看虚拟环境已经安装的包
(tensorflow) [jiangshan@localhost ~]$ conda list
==============================================================================================
# packages in environment at /home/jiangshan/anaconda3/envs/tensorflow:
#
# Name Version Build Channel
absl-py 0.7.0 py36_1000 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
astor 0.7.1 py_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
blas 1.0 mkl https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
c-ares 1.15.0 h14c3975_1001 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
ca-certificates 2019.3.9 hecc5488_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
certifi 2019.3.9 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
gast 0.2.2 py_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
grpcio 1.16.1 py36hf8bcb03_1 defaults
libffi 3.2.1 hf484d3e_1005 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libgcc-ng 7.3.0 hdf63c60_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libgfortran-ng 7.2.0 hdf63c60_3 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libprotobuf 3.7.0 hdbcaa40_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libstdcxx-ng 7.3.0 hdf63c60_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
markdown 2.6.11 py_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
mkl 2017.0.3 0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
ncurses 6.1 hf484d3e_1002 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
numpy 1.14.2 py36hdbf6ddf_0 defaults
openssl 1.1.1b h14c3975_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
pip 19.0.3 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
protobuf 3.7.0 py36hf484d3e_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
python 3.6.7 h381d211_1004 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
readline 7.0 hf8c457e_1001 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
setuptools 40.8.0 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
six 1.12.0 py36_1000 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
sqlite 3.26.0 h67949de_1001 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
tensorboard 1.10.0 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
tensorflow 1.10.0 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
termcolor 1.1.0 py_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
tk 8.6.9 h84994c4_1000 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
werkzeug 0.14.1 py_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
wheel 0.33.1 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
xz 5.2.4 h14c3975_1001 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
zlib 1.2.11 h14c3975_1004 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
==============================================================================================
# 测试
(tensorflow) [jiangshan@localhost ~]$ python
Python 3.6.7 | packaged by conda-forge | (default, Feb 28 2019, 09:07:38)
[GCC 7.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf 【不报错就表示安装成功】
>>> quit()