AI ubantu 环境安装

ubantu安装记录

apt install python3-pip

anaconda安装

https://repo.anaconda.com/archive/Anaconda3-2020.11-Linux-x86_64.sh

ai@ubuntu:~/Downloads$ sh Anaconda3-2020.11-Linux-x86_64.sh 

Welcome to Anaconda3 2020.11

In order to continue the installation process, please review the license
agreement.
Please, press ENTER to continue
>>> 

按下 ENTER 回车键，开始阅读license，按空格键翻页，然后输入yes同意

Do you accept the license terms? [yes|no]
[no] >>>   yes

确认安装目录，该目录不能提前存在

Anaconda3 will now be installed into this location:
/home/ai/anaconda3

  - Press ENTER to confirm the location
  - Press CTRL-C to abort the installation
  - Or specify a different location below

[/home/ai/anaconda3] >>> /opt/app/anaconda3

选择初始化

Preparing transaction: done
Executing transaction: done
installation finished.
Do you wish the installer to initialize Anaconda3
by running conda init? [yes|no]
[no] >>> yes

==> For changes to take effect, close and re-open your current shell. <==

If you'd prefer that conda's base environment not be activated on startup,
   set the auto_activate_base parameter to false: 

conda config --set auto_activate_base false

Thank you for installing Anaconda3!

===========================================================================

Working with Python and Jupyter notebooks is a breeze with PyCharm Pro,
designed to be used with Anaconda. Download now and have the best data
tools at your fingertips.

PyCharm Pro for Anaconda is available at: https://www.anaconda.com/pycharm

重启ubantu后自动应用anaconda

(base) ai@ubuntu:~$ python
Python 3.8.5 (default, Sep  4 2020, 07:30:14)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> 

应用的标志是前面加了一个(base)

python3.8.5是ubantu20.4自带的python3环境，anaconda自动关联了该版本的python

自带的环境下有一系列机器学习的python模块，如果是新建的python环境，是没有的

 验证

原来的python3.8.5是没有算法相关的模块的

$ python3
Python 3.8.5 (default, Jan 27 2021, 15:41:15)
[GCC 9.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ModuleNotFoundError: No module named 'numpy'

而anaconda环境下的python3.8.5默认有大量的算法相关的模块，其中就包括numpy,sklearn,matplotlib等

(base) ai@ubuntu:~$ python
Python 3.8.5 (default, Sep  4 2020, 07:30:14)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
>>> import sklearn
>>> import matplotlib
>>> 

最后,anaconda环境是不AI的刚需，但会给新手带来方便；高手可安装原始python，用到哪个算法模块时再安装

vscode安装

https://az764295.vo.msecnd.net/stable/cfa2e218100323074ac1948c885448fdf4de2a7f/code_1.56.0-1620166262_amd64.deb

插件安装
python
pylance   代码提示
jupyter notebook
markdown
markdown preview
chinese

常用设置

Auto Save 选择 AfterDelay

Font Size 16

python路径设置：由于前面的安装的anaconda，默认的打开的环境就是anaconda环境，而该环境下的python实际指向的是ubantu默认的3.8.5

所以下面的python指的就是anaconda环境下的python，这样在vscode中就可以直接引用相关算法的模块

Ctrl + Shift + P 

Python: Select Interpreter

然后选择具体的Python路径

该方式优先级较高，通常设置了这个，其他就不用设置了

设置完成后，可以看到vscode使用的解释器

验证

在vscode中创建py文件，引用numpy包，可以看到直接就提示出来了，说明anacode与vscode环境配合成功

提示功能是由pylance插件提供的

jupyter notebook

该功能提供数学公式的编排，并且能与代码文档混排，兼容markdown，可以生成自己ipynb格式的文件，还可以转PDF等文件，便于写 代码＋数学公式的类型文档

个人尝试了五种以上可以提供数学公式的相关工具，其中jupyter notebook最棒，如果你没有时间一一去尝试其他工具能否提供优雅的数学公式，那么就推荐先从notebook开始编写数学公式

(base) ai@db:~$ jupyter notebook

可以看到jupyter notebook中的数学公式的样子，插入数学公式需要将code改为Markdown；

保存PDF目前直接保存报错，解决办法：

先将文档保存为html，然后使用浏览器的打印功能，保存为PDF格式，效果如下：

HTML

PDF

jupyter在写文档时非常棒，如果是纯代码还是要使用工具的，比如vscode

 conda环境查看

(base) ai@db:~$ conda env list
# conda environments:
#
base                  *  /opt/app/anaconda3

这里共有一个conda环境

conda创建一个python3.6的环境

conda create --name tf36 python=3.6

## Package Plan ##

  environment location: /opt/app/anaconda3/envs/tf36

  added / updated specs:
    - python=3.6

注意默认环境是Python3.8.5，并没有python3.6，于是在创建环境时，提示会下载python3.6.13

The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    ca-certificates-2021.4.13  |       h06a4308_1         114 KB
    certifi-2020.12.5          |   py36h06a4308_0         140 KB
    openssl-1.1.1k             |       h27cfd23_0         2.5 MB
    pip-21.0.1                 |   py36h06a4308_0         1.8 MB
    python-3.6.13              |       hdb3f193_0        29.7 MB
    readline-8.1               |       h27cfd23_0         362 KB
    setuptools-52.0.0          |   py36h06a4308_0         724 KB
    sqlite-3.35.4              |       hdfb4753_0         981 KB
    wheel-0.36.2               |     pyhd3eb1b0_0          33 KB
    ------------------------------------------------------------
                                           Total:        36.4 MB

同意后，就开始安装了

Proceed ([y]/n)? y

最后给出了切换与退出环境的命令

# To activate this environment, use
#
#     $ conda activate tf36
#
# To deactivate an active environment, use
#
#     $ conda deactivate

现在再看，就有两个环境

(base) ai@db:/opt/app/conda$ conda env list
# conda environments:
#
base                  *  /opt/app/anaconda3
tf36                     /opt/app/anaconda3/envs/tf36

不同环境切换如下

(base) ai@db:/opt/app/conda$ python
Python 3.8.5 (default, Sep  4 2020, 07:30:14)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> exit()
(base) ai@db:/opt/app/conda$ conda activate tf36
(tf36) ai@db:/opt/app/conda$ python
Python 3.6.13 |Anaconda, Inc.| (default, Feb 23 2021, 21:15:04)
[GCC 7.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> exit()
(tf36) ai@db:/opt/app/conda$ conda activate base
(base) ai@db:/opt/app/conda$ python
Python 3.8.5 (default, Sep  4 2020, 07:30:14)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>>

如此就可以通过conda创建多个不同的python的环境，也可以达到同版本不同模块的分离；

只安装需要的包，不安装多余的包，能隔离就隔离，以减少环境间的相互影响；

conda安装tensorflow

目前Python3.8下默认安装的2.4.1版本

conda install tensorflow

conda install keras

(tf38) ai@db:/opt/app/conda$ python
Python 3.8.8 (default, Apr 13 2021, 19:58:26)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> tf.__version__
'2.4.1'

指定版本安装

conda install tensorflow=1.15.0

python36环境中的keras

The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    keras-2.3.1                |                0          12 KB
    keras-base-2.3.1           |           py36_0         495 KB
    pyyaml-5.4.1               |   py36h27cfd23_1         170 KB
    ------------------------------------------------------------
                                           Total:         676 KB

(tf36) ai@db:~$ python
Python 3.6.13 |Anaconda, Inc.| (default, Feb 23 2021, 21:15:04)
[GCC 7.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import keras
Using TensorFlow backend.
kera>>> keras.__version__
'2.3.1'

python38环境中的keras

The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    conda-4.10.1               |   py38h06a4308_1         2.9 MB
    gast-0.3.3                 |             py_0          14 KB
    google-auth-1.28.0         |     pyhd3eb1b0_0          72 KB
    google-auth-oauthlib-0.4.2 |     pyhd3eb1b0_2          18 KB
    grpcio-1.31.0              |   py38hf8bcb03_0         2.0 MB
    keras-2.4.3                |                0          12 KB
    keras-base-2.4.3           |             py_0          37 KB
    tensorflow-2.2.0           |mkl_py38h6d3daf0_0           4 KB
    tensorflow-base-2.2.0      |mkl_py38h5059a2d_0       127.2 MB
    tensorflow-estimator-2.2.0 |     pyh208ff02_0         254 KB
    typing-extensions-3.7.4.3  |                0          12 KB
    ------------------------------------------------------------
                                           Total:       132.6 MB

(base) ai@db:~$ python
Python 3.8.5 (default, Sep  4 2020, 07:30:14)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import keras
>>> keras.__version__
'2.4.3'

其他设置

conda config --set auto_activate_base false  #默认不启动conda环境

conda config --set auto_activate_base true   #默认启动conda环境