ubuntu18配置深度学习环境

1 安装nvidia驱动

1.1 设置root

1	`sudo` `passwd` `123`

1.2 检测nvidia显卡

ubuntu-drivers devices

(base) dxs@dxs-ubuntu:~$ ubuntu-drivers devices
== /sys/devices/pci0000:00/0000:00:01.0/0000:01:00.0 ==
modalias : pci:v000010DEd00002184sv00001458sd00003FC7bc03sc00i00
vendor   : NVIDIA Corporation
driver   : nvidia-driver-430 - distro non-free recommended
driver   : xserver-xorg-video-nouveau - distro free builtin

(base) dxs@dxs-ubuntu:~$

1.3 安装nvidia驱动

sudo apt install nvidia-driver-430

1.4 安装完成后 reboot

--------------------------------------------------------

2 安装anaconda3

2.1 下载Anaconda3-5.2.0-Linux-x86_64.sh

2.2 安装：sudo sh Anaconda3-5.2.0-Linux-x86_64.sh

2.3 设置conda镜像

conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/
conda config --set show_channel_urls yes

-----------------------------------------------------------------------------

3 安装cuda cudnn

conda install cudatoolkit=10.0
conda install cudnn=7.6.0

------------------------------------------------------------------------------

4 安装tensorflow-gpu

conda install tensorflow-gpu=1.13.1

5 安装pytorch

在线安装： conda install pytorch torchvision cudatoolkit=10.0 -c pytorch
离线安装： 先去 https://download.pytorch.org/whl/cu100/torch_stable.html 下载 torch-1.2.0-cp36-cp36m-manylinux1_x86_64.whl 和 torchvision-0.4.0-cp36-cp36m-manylinux1_x86_64.whl ， 然后安装

6 安装caffe

conda install -c defaults caffe-gpu

7 安装jupyter notebook

conda install jupyter notebook
# 若不生效则需要执行以下命令
sudo apt install jupyter-core

8 配置jupyter notebook

1 生成配合文件 jupyter_notebook_config.py
jupyter notebook --generate-config --allow-root
 
2 进入ipython环境，生成pwd
 
(base) dxs@dxs-ubuntu:~$ ipython
Python 3.6.9 |Anaconda, Inc.| (default, Jul 30 2019, 19:07:31) 
Type 'copyright', 'credits' or 'license' for more information
IPython 6.4.0 -- An enhanced Interactive Python. Type '?' for help.
 
In [1]: from notebook.auth import passwd
 
In [2]: passwd()
Enter password: 
Verify password: 
Out[2]: 'sha1:5171a0b47bc4:c4efffb3c7973b480a4612cb7a457c7d5da0970b'
 
In [3]: quit()
 
3 打开配置文件：/home/dxs/.jupyter/jupyter_notebook_config.py
修改以下位置：
 
203 行
## notebook服务会监听的IP地址.  
c.NotebookApp.ip = '0.0.0.0'
 
257行
## 用于笔记本和内核的目录。
c.NotebookApp.notebook_dir = u'/media/dxs/E/Project/AI'
 
263行
#  configuration option.
c.NotebookApp.open_browser = True
 
272行
#  The string should be of the form type:salt:hashed-password.
c.NotebookApp.password = u'sha1:5171a0b47bc4:c4efffb3c7973b480a4612cb7a457c7d5da0970b'
 
283行
## notebook服务会监听的IP端口.
c.NotebookApp.port = 8888
 
保存即可

9 给conda每个虚拟环境配置jupyter notebook

(base) dxs@dxs-ubuntu:~$ conda env list
# conda environments:
#
base                  *  /home/dxs/anaconda3
caffe                    /home/dxs/anaconda3/envs/caffe
tf2                      /home/dxs/anaconda3/envs/tf2
 
(base) dxs@dxs-ubuntu:~$ conda activate base
(base) dxs@dxs-ubuntu:~$ conda install ipykernel
Collecting package metadata (repodata.json): done
Solving environment: done
 
## Package Plan ##
 
  environment location: /home/dxs/anaconda3
 
  added / updated specs:
    - ipykernel
 
 
The following packages will be downloaded:
 
    package                    |            build
    ---------------------------|-----------------
    ipykernel-5.1.2            |   py36h39e3cac_0         165 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
    ------------------------------------------------------------
                                           Total:         165 KB
 
The following packages will be UPDATED:
 
  ipykernel               pkgs/main::ipykernel-4.8.2-py36_0 --> anaconda/pkgs/main::ipykernel-5.1.2-py36h39e3cac_0
 
 
Proceed ([y]/n)? y
 
 
Downloading and Extracting Packages
ipykernel-5.1.2      | 165 KB    | ##################################### | 100% 
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
(base) dxs@dxs-ubuntu:~$ python -m ipykernel install --user --name base --display-name "base_tf_pytorch"
Installed kernelspec base in /home/dxs/.local/share/jupyter/kernels/base　　<br><br>

(caffe) dxs@dxs-ubuntu:~$ conda activate tf2
(tf2) dxs@dxs-ubuntu:~$ conda install ipykernel<br>### 假如不行，还需要回来再执行：  (tf2) dxs@dxs-ubuntu:~$ conda install jupyter
Collecting package metadata (repodata.json): done
Solving environment: done
 
## Package Plan ##
 
  environment location: /home/dxs/anaconda3/envs/tf2
 
  added / updated specs:
    - ipykernel
 
 
The following NEW packages will be INSTALLED:
 
  ipykernel          anaconda/pkgs/main/linux-64::ipykernel-5.1.2-py36h39e3cac_0
  jupyter_client     anaconda/pkgs/main/linux-64::jupyter_client-5.3.3-py36_1
  jupyter_core       anaconda/pkgs/main/noarch::jupyter_core-4.5.0-py_0
  libsodium          anaconda/pkgs/main/linux-64::libsodium-1.0.16-h1bed415_0
  pyzmq              anaconda/pkgs/main/linux-64::pyzmq-18.1.0-py36he6710b0_0
  zeromq             anaconda/pkgs/main/linux-64::zeromq-4.3.1-he6710b0_3
 
 
Proceed ([y]/n)? y
 
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
(tf2) dxs@dxs-ubuntu:~$ python -m ipykernel install --user --name tf2 --display-name "tf2.0"
Installed kernelspec tf2 in /home/dxs/.local/share/jupyter/kernels/tf2                                                                                                                                                                   <br>==========================================================================<br><br>启动服务后效果如下：