对前期深度学习环境配置过程中遇到的错误，进行简要总结，会不定时更新。由于时间紧迫，总结的不是很详细，待有时间回来补充，望大佬轻喷。
1.安装tensorflow版本一定要与cuda版本对应，否则后期会报错；
2.anaconda创建的虚拟环境下，尽量使用conda安装相关包，pip有时会出错；
3.有时无法使用GPU进行TF训练，默认使用了CPU，此时可以选择升级GPU版本的TF，单纯试图卸载掉CPU版本TF，并不能解决问题，除非重新创建虚拟环境；
4.不同conda虚拟环境中可以共存不同版本的cuda，但是显卡驱动只有一个，显卡驱动版本不能过低，其版本应与高版本的cuda版本对应；
一. ubuntu下anaconda安装及虚拟环境创建
1. 清华大学Anaconda 镜像网站：清华镜像
2. 安装anaconda：
下载自己需要版本后，根据以下提示，enter键继续向下：
nuc@nuc:~/Downloads$ bash Anaconda3-5.1.0-Linux-x86_64.sh
Welcome to Anaconda3 5.1.0
In order to continue the installation process, please review the license
agreement.
Please, press ENTER to continue
>>>
阅读完信息后，输入yes，回车继续：
Do you accept the license terms? [yes|no]
[no] >>> Please answer 'yes' or 'no':'
Anaconda3 will now be installed into this location:
/home/nuc/anaconda3
- Press ENTER to confirm the location
- Press CTRL-C to abort the installation
- Or specify a different location below
[/home/nuc/anaconda3] >>>
一系列安装完成后，输入yes，加入环境变量即可，在之后会提示是否安装VScode，选择no；
完成后开启新的终端，查看 conda 的版本号：
nuc@nuc:~$ conda -V
conda 4.4.10
nuc@nuc:~$
打开 Jupyter Notebook：
nuc@nuc:~$ jupyter notebook
[I 01:48:14.486 NotebookApp] The port 8888 is already in use, trying another port.
[I 01:48:14.711 NotebookApp] JupyterLab beta preview extension loaded from /home/nuc/anaconda3/lib/python3.6/site-packages/jupyterlab
[I 01:48:14.712 NotebookApp] JupyterLab application directory is /home/nuc/anaconda3/share/jupyter/lab
[I 01:48:14.759 NotebookApp] Serving notebooks from local directory: /home/nuc
[I 01:48:14.759 NotebookApp] 0 active kernels
[I 01:48:14.759 NotebookApp] The Jupyter Notebook is running at:
[I 01:48:14.760 NotebookApp] http://localhost:8889/?token=605b46819a7dd5e99d71a07c7f3a53ea4a789b62c6c38764
[I 01:48:14.760 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[C 01:48:14.761 NotebookApp]
Copy/paste this URL into your browser when you connect for the first time,
to login with a token:
http://localhost:8889/?token=605b46819a7dd5e99d71a07c7f3a53ea4a789b62c6c38764
[I 01:48:22.437 NotebookApp] Accepting one-time-token-authenticated connection from 127.0.0.1
3. 设置清华镜像：
由于anaconda.org的服务器在国外，有时下载很慢，故可以配置为国内镜像：
# 添加Anaconda的TUNA镜像
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
# TUNA的help中镜像地址加有引号，需要去掉
# 设置搜索时显示通道地址
conda config --set show_channel_urls yes
4. 创建自己需要的虚拟环境
查看系统中已有的虚拟环境：
nuc@nuc:~$ conda info --envs
# conda environments:
#
base * /home/nuc/anaconda3
创建名为python36的python3.6的虚拟环境：
conda create --name python36 python=3.6 #环境名为python36,python版本为3.6
# 安装好后，使用activate激活某个环境
~$ source activate python36 # for Linux & Mac
# 激活后，会发现terminal输入的地方多了python36的字样，实际上，此时系统做的事情就是把默认2.7环境从PATH中去除，再把3.6对应的命令加入PATH
# 此时，再次输入
~$ python --version
# 有提示：Python 3.6.10
# 如果想返回默认的python 2.7环境，运行
~$ source deactivate python36 # for Linux & Mac
# 删除一个已有的环境
~$ conda remove --name python36 --all #删除虚拟环境python36,也可以将“--name”改为“-n”
用户安装的不同python环境都会被放在目录 ~/anaconda/envs 下，可以在命令中运行conda info -e查看已安装的环境，当前被激活的环境会显示有一个星号或者括号。
5. 安装指定版本tensorflow，conda list可查看当前环境中已安装的包：
(python36) nuc@xnuc:~$ pip install tensorflow-gpu==1.14.0 -i https://pypi.tuna.tsinghua.edu.cn/simple
(python36) nuc@xnuc:~$ conda list
# packages in environment at /home/nuc/anaconda3/envs/python36:
#
# Name Version Build Channel
_libgcc_mutex 0.1 conda_forge https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
_openmp_mutex 4.5 0_gnu https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
ca-certificates 2020.4.5.1 hecc5488_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
certifi 2020.4.5.1 py36h9f0ad1d_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
ld_impl_linux-64 2.34 h53a641e_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libffi 3.2.1 he1b5a44_1007 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libgcc-ng 9.2.0 h24d8f2e_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libgomp 9.2.0 h24d8f2e_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libstdcxx-ng 9.2.0 hdf63c60_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
ncurses 6.1 hf484d3e_1002 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
openssl 1.1.1g h516909a_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
pip 20.1 pyh9f0ad1d_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
python 3.6.10 h8356626_1011_cpython https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
python_abi 3.6 1_cp36m https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
readline 8.0 hf8c457e_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
setuptools 46.3.1 py36h9f0ad1d_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
sqlite 3.30.1 hcee41ef_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
tk 8.6.10 hed695b0_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
wheel 0.34.2 py_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
xz 5.2.5 h516909a_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
zlib 1.2.11 h516909a_1006 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
二. BUG总结
- 使用turtlebot模型在gazebo仿真平台使用时，出现一下错误：
Invalid <arg> tag: environment variable 'TURTLEBOT3_MODEL' is not set.
Arg xml is <arg default="$(env TURTLEBOT3_MODEL)" doc="model type [burger, waffle, waffle_pi]" name="model"/>
The traceback for the exception was written to the log file
这是由于没有在 .bashrc 中加入相关声明，在其中加入以下语句并source即可：
#turtlebot gazebo
#export TURTLEBOT_3D_SENSOR=hokuyo
export TURTLEBOT3_MODEL=burger