--Find HDD

python

$ sudo parted -l

-Because it exceeds 2TB, attach a disc label with "GPT"

python

$ sudo parted /dev/sdb
(parted) mklabel gpt
(parted) p

--All capacity is ext4, 1 partition

python

(parted) mkpart primary ext4 0% 100%
(parted) p

--Since the partition is created, close parted.

python

(parted) quit

--Format with "ext4"

python

$ sudo mkfs.ext4 /dev/sdb1

--Create a mount point and mount the HDD (The mount point was just a directory / I wasn't sure if this location was good, so I did chmod777.)

python

$ sudo mkdir /home/Hdd_2nd
$ sudo mount -t ext4 /dev/sdb1 /home/Hdd_2nd
$ sudo mount

--Automount settings (write information to / etc / fstab)

python

$ sudo nano /etc/fstab

--Added the following line to the opened file ([tab], not Space between characters. I was addicted to it here)

python

/dev/sdb1       /home/Hdd_2nd   ext4    defaults        0       0

4. Mac-like basic settings and keyboard settings </ summary>

4.1. Keyboard settings: Compatible with US keyboards

--Try until it matches the keyboard (By the way, it is strange that the settings are different between [Apple Wireless Keyboard] and [MacBook Pro]. Even though the key layout is exactly the same)

python

$ sudo dpkg-reconfigure keyboard-configuration

--Write keyboard settings

python

$ sudo nano /usr/share/ibus/component/mozc.xml
<layout>us</layout>

4.2. Make the directory in your home English

――When accessing from the terminal, it is troublesome if it is Japanese, so return to English

python

$ LANG=C xdg-user-dirs-gtk-update

--If it doesn't work, edit `` `$ sudo nano ~ / .config / user-dirs.dirs``` as follows

python

$ sudo nano ~/.config/user-dirs.dirs
＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿
XDG_DESKTOP_DIR="$HOME/Desktop"
XDG_DOWNLOAD_DIR="$HOME/Downloads"
XDG_TEMPLATES_DIR="$HOME/Templates"
XDG_PUBLICSHARE_DIR="$HOME/Share"
XDG_DOCUMENTS_DIR="$HOME/Documents"
XDG_MUSIC_DIR="$HOME/Music"
XDG_PICTURES_DIR="$HOME/Pictures"
XDG_VIDEOS_DIR="$HOME/Videos"
＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿

--Rename the actual folder

python

$ mv $HOME/desktop$HOME/Desktop
$ mv $HOME/download$HOME/Downloads
$ mv $HOME/template$HOME/Templates
$ mv $HOME/Release$HOME/Share
$ mv $HOME/document$HOME/Documents
$ mv $HOME/musics$HOME/Music
$ mv $HOME/image$HOME/Pictures
$ mv $HOME/video$HOME/Videos

--It's OK to log in again (sometimes the sidebar display is mixed English / Japanese, but I gave up)

4.3. Match key bindings to Mac

4.3.1 Change "Left super (alt) key" and "Caps lock key" to "Ctrl key"

--Install Gnome Tweaks --Install from Ubuntu Software / [Tweaks] is the program name -[Tweaks]> Keyboard and mouse --Change the shortcut of the activity screen from "left super" to "right super" (to open the "left super key") -[Tweaks]> Keyboard and mouse> Additional layout options> Ctrl position> Select "Treat Caps Lock as Control" (change "Caps lock key" to "Ctrl key") -Please [Restart]

4.3.2 Change "Left super key" to Ctrl key

--Keep a backup of your key assignments

python

$ xmodmap -pke > ~/.Xmodmap_default

--Find the key number of the "left super key" --When you type the following command, a square window will open, so if you "key in" while you can see it, the key number will be displayed (in my case, it was "133").

python

$ xev | grep keycode

Photoshop is the display when you press the "Return key" Change key binding Basic setting method of Xmodmap

--Add the following to the opened file

python

$ nano ~/.Xmodmap
＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿
clear control
clear mod4

! Command_L -> Control_L
keycode 133 = Control_L

add control = Control_L Control_R
add mod4 = Super_L Super_R Super_L Hyper_L
＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿

--Reflect the settings

python

$ xmodmap ~/.Xmodmap

--If you make a mistake, restore the backup file

python

$ xmodmap ~/.Xmodmap_default

-Please [Restart]

** The Ctrl key on the left half of the keyboard has a gorgeous keyboard layout of "3 (left Super (alt) / Caps Lock / original ctrl key)" ** ** Now you can copy with "Left Super (alt) key" + "c" **

4.3.3 Convert to "half-width English" with "Option (Start) key" + "s"

--mozc settings: GUI tool installation --By default, the "mozc" GUI tool is not installed, so install it.

python

$ sudo apt install mozc-utils-gui

--Settings ＞ Region and Language ＞ Input Source ＞ Mozc Gear Icon ＞ Select Key Settings ＞ Select Kotoeri

** With this alone, "Option (Start) key" + "s / a / c / x / z" will give you a familiar feeling of "half-width katakana / half-width English / hiragana / full-width katakana / full-width English". Mozc, Elai **

4.3.4. English / Japanese input source switching with "Left Super (alt) key" + "Space key" (for US keyboard)

--Change input source switching shortcut key (US keyboard compatible) --Settings ＞ Keyboard shortcuts ＞ Set both "Switch to previous input source" and "Switch to next input source" to [Disable] in the typing window.

--Mozc property window ＞ Select key setting ＞ Edit ＞ Mozc key setting screen ＞ "Hankaku / Zenkaku" input key (4 places) ＞ Change to [Ctrl + Space]

** Now you can switch between English and Japanese with "Left Super (alt) key" + "Space key" **

5. Installation of basic software </ summary>

$ sudo apt install copyq

$ sudo apt install dump

$ sudo dump -0 -u -j /dev/sda2 -f /home/hdd_2nd/Sys_Backup/backup_2020_08_08.dump

$ cd Downloads
$ sudo apt install -y ./google-chrome-stable_current_amd64.deb

$ echo $LANG

$ export LANG=ja_JP.utf8

$ echo $LANG

$ sudo apt-get install manpages-ja

$ sudo apt-add-repository ppa:fish-shell/release-3
$ sudo apt-get update
$ sudo apt-get install -y fish

$ sudo apt install curl　/Not required if curl is already installed
$ curl https://git.io/fisher --create-dirs -sLo ~/.config/fish/functions/fisher.fish
$ fisher add oh-my-fish/theme-bobthefish

$ sudo apt install terminator

$ git clone https://github.com/powerline/fonts.git --depth=1
$ cd fonts
$ ./install.sh
$ cd ..
$ rm -rf fonts

$ sudo apt install git

$ git config --global user.name "username"
$ git config --global user.email email address
$ git config --global core.editor nvim

$ sudo apt install xclip "Not required if installed"
$ bash
$ ssh-keygen -t rsa -b 4096 -C "mail address"
~ If you don't use the passphrase, enter repeatedly ~
$ eval "$(ssh-agent -s)"
$ ssh-add ~/.ssh/id_rsa
$ cat ~/.ssh/id_rsa.pub | xclip -selection c "Copy to clipboard"
~ Register SSH KEY from Settings page on github ~
Paste the public key copied to the clipboard with the xclip command

$ sudo dump -0 -u -j /dev/sda2 -f /home/inata/hdd_2nd/Sys_Backup/backup_2020_08_08.dump

$ lsmod | grep -i nouveau

$ nvidia-smi
$ Failed to initialize NVML: Driver/library version mismatch

$ sudo ubuntu-drivers autoinstall

$ sudo apt install nvidia-cuda-toolkit

$ sudo apt install -y curl (not required if installed)
$ curl -s https://raw.githubusercontent.com/karaage0703/ubuntu-setup/master/install-docker.sh | /bin/bash

$ sudo docker run hello-world
OK if there are no errors

$ docker container prune
$ docker image rm hello-world:latest

$ curl -s https://raw.githubusercontent.com/karaage0703/ubuntu-setup/master/install-nvidia-container-toolkit.sh | /bin/bash

$ docker run --gpus all --rm nvidia/cuda nvidia-smi

$ docker run --gpus all -it --rm --name tensorflow-gpu -p 8888:8888 tensorflow/tensorflow:latest-gpu-py3
（-p 8888:8888 is for the port of jupyter notebook)

# nvidia-smi

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.100      Driver Version: 440.100      CUDA Version: 10.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:1Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GTX 166...  Off  | 00000000:01:00.0  On |                  N/A |
| 42%   36C    P8     8W / 125W |    342MiB /  5936MiB |      2%      Default |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
+-----------------------------------------------------------------------------+

# jupyter notebook

http://127.0.0.1:8888/?token=xxxxxxxxxxxxxx`

from tensorflow.python.client import device_lib
device_lib.list_local_devices()

# exit

$ docker container prune
$ docker image rm tensorflow/tensorflow:latest-gpu-py3

$ nvcc -V

$ sudo dpkg -i libcudnn7_7.6.5.32-1+cuda10.1_amd64.deb
$ sudo dpkg -i libcudnn8-dev_8.0.2.39-1+cuda10.1_amd64.deb
$ sudo dpkg -i libcudnn8-doc_8.0.2.39-1+cuda10.1_amd64.deb

$ nvcc -V

$ cat /usr/include/cudnn.h | grep CUDNN_MAJOR -A 2
#define CUDNN_MAJOR 7
#define CUDNN_MINOR 6
#define CUDNN_PATCHLEVEL 5
--
#define CUDNN_VERSION (CUDNN_MAJOR * 1000 + CUDNN_MINOR * 100 + CUDNN_PATCHLEVEL)

$ docker image pull nvcr.io/nvidia/tensorflow:20.03-tf1-py3

$ docker run --name tensor_keras --gpus all -it -p 8888:8888 nvcr.io/nvidia/tensorflow:20.03-tf1-py3

# pip list

# pip install --upgrade pip
# pip install Keras
# pip install pandas
# pip install pandas_datareader

# exit

$ docker container ls -a
CONTAINER ID        IMAGE                         COMMAND                  CREATED             STATUS                     PORTS               NAMES
70d0795d84e8        inata/my_tensorflow_img:1.0   "/usr/local/bin/nvid…"   3 weeks ago         Exited (0) 4 seconds ago                       tensor_keras

$ docker container commit -a "INA-Ta" tensor_keras inata/my_tensorflow_img:1.0

$ docker container commit tensor_keras my_tensorflow_img:1.0

$ docker run --name tensor_keras --gpus all -it -p 8888:8888 inata/my_tensorflow_img:1.0

$ docker login

$ docker image push inata/my_tensorflow_img:1.0

docker logout

$ docker image save -o /home/Hdd_2nd/Docker_Image/my_tensorflow_img_1.0.tar inata/my_tensorflow_img:1.0

$ docker image load -i /home/Hdd_2nd/Docker_Image/my_tensorflow_img_1.0.tar