https://zhuanlan.zhihu.com/p/28494550
配置Ubuntu靜態(tài)地址
sudo gedit /etc/network/interfaces
interfaces(5) file used by ifup(8) and ifdown(8)
auto enp6s0
iface enp6s0 inet static
address 192.168.0.26
netmask 255.255.255.0
broadcast 192.168.0.255
gateway 192.168.0.1
sudo gedit /etc/resolv.conf
nameserver 114.114.114.114
sudo /etc/init.d/networking restart
sudo gedit /etc/resolvconf/resolv.conf.d/base(如無效使用)
掛載U盤
sudo mkdir /mnt/usb
df
sudo mount /dev/sda1 /mnt/usb
cd /mnt/usb
sudo umount /mnt/usb
sudo umount /dev/sda1 /mnt/usb
用戶名ubuntu不在sudoers文件中嘀韧，此事將被報告
sudo gedit /etc/sudoers添加：
ubuntu ALL=(ALL:ALL) ALL
Ubuntu16.04 下創(chuàng)建新用戶yang并賦予sudo權限
adduser username
sudo gedit /etc/sudoers
yang ALL=(ALL:ALL) ALL
修改root密碼
sudo passwd root
Ubuntu 16.04+CUDA 9.1+cuDNN v7+OpenCV 3.4.0+Caffe+PyCharm 完全安裝指南捻浦，國內最全虹茶！(適用CUDA 9.0)
https://blog.csdn.net/qq473179304/article/details/79444609
Ubuntu16.04 安裝 CUDA9.2
https://blog.csdn.net/EliminatedAcmer/article/details/80528980
tensorflow 安裝GPU版本撮奏，個人總結，步驟比較詳細
https://blog.csdn.net/gangeqian2/article/details/79358543
Ubutu16.04+Cuda9.2/9.0+Cudnn7.12/7.05+TensorFlow-gpu-1.8/1.6
http://www.cnblogs.com/wjy-lulu/p/9119905.html
Ubuntu 16.04 + Nvidia 顯卡驅動 + Cuda 8.0 （問題總結 + 解決方案）
https://blog.csdn.net/zafir_410/article/details/73188228?utm_source=itdadao&utm_medium=referral
Ubuntu+Tensorflow+CUDA8.0+cudnn
https://blog.csdn.net/icehui2012/article/details/62219008
http://www.52nlp.cn/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E4%B8%BB%E6%9C%BA%E7%8E%AF%E5%A2%83%E9%85%8D%E7%BD%AE-ubuntu16-04-geforce-gtx1080-tensorflow
Ubuntu + CUDA9.0 + tensorflow-gpu 安裝過程
https://blog.csdn.net/qq_35976351/article/details/79325476
1.安裝依賴包
sudo apt-get update
sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler
sudo apt-get install --no-install-recommends libboost-all-dev
sudo apt-get install libopenblas-dev liblapack-dev libatlas-base-dev
sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev
sudo apt-get install git cmake build-essential
2.安裝顯卡驅動
https://www.geforce.cn/drivers
sudo gedit /etc/modprobe.d/blacklist-nouveau.conf
blacklist nouveau
options nouveau modeset=0
sudo update-initramfs -u
lsmod | grep nouveau
sudo apt-get remove nvidia-*
sudo apt-get autoremove
sudo nvidia-uninstall
reboot
Ctrl+Alt+F1
sudo service lightdm stop
sudo bash NVIDIA-Linux-x86_64-390.48.run -no-x-check -no-nouveau-check -no-opengl-files
sudo service lightdm restart
nvidia-settings
Ubuntu開機無法進入系統(tǒng)問題（NVIDIA顯卡驅動相關）
https://blog.csdn.net/ezhchai/article/details/78788564
https://blog.csdn.net/ezhchai/article/details/80525207
sudo vim /etc/default/grub
GRUB_CMDLINE_LINUX_DEFAULT=”quiet splash”改成GRUB_CMDLINE_LINUX_DEFAULT=”quiet splash nomodeset”
sudo update-grub
3.配置環(huán)境變量
sudo gedit ~/.bashrc
export LD_LIBRARY_PATH=/usr/lib/x86_64-linux-gnu:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=/lib/x86_64-linux-gnu:$LD_LIBRARY_PATH
4.安裝 CUDA 9.1
sudo apt-get install freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libgl1-mesa-glx libglu1-mesa libglu1-mesa-dev
sudo sh cuda_9.1.85_387.26_linux.run --no-opengl-libs
sudo gedit ~/.bashrc
export PATH=/usr/local/cuda/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
source ~/.bashrc
cd /usr/local/cuda-9.1/samples/1_Utilities/deviceQuery
sudo make
./deviceQuery
安裝cuDNN v7
cd cuda/include
sudo cp cudnn.h /usr/local/cuda/include/ #復制頭文件
cd ../lib64
sudo cp lib* /usr/local/cuda/lib64/
cd /usr/local/cuda/lib64/
sudo rm -rf libcudnn.so libcudnn.so.7
sudo ln -s libcudnn.so.7.0.5 libcudnn.so.7
sudo ln -s libcudnn.so.7 libcudnn.so
sudo apt-get install vim-gtk
sudo vim /etc/ld.so.conf.d/cuda.conf
/usr/local/cuda/lib64
sudo ldconfig
sudo ldconfig -v
nvcc -V
Ubuntu16.04安裝Anaconda3.5
sudo bash Anaconda3-5.1.0-Linux-x86_64.sh
anaconda-navigator
sudo gedit /etc/profile
sudo vim /etc/profile
sudo vim ~/.bashrc
export PATH="/home/ubuntu/anaconda3/bin:$PATH"
source /etc/profile
source ~/.bashrc
echo $PATH
python --version
conda --version
conda list
conda info --envs
conda update -n base conda
conda update conda
conda create -n tensorflow36 python=3.6
conda remove -n tensorflow36 --all
conda config --add channels
https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
conda config --set show_channel_urls yes
conda install numpy
source activate tensorflow36
source deactivate
sudo apt install python3-pip
python3 -m pip install --upgrade pip --force-reinstall
pip install
-i https://pypi.tuna.tsinghua.edu.cn/simple/
https://mirrors.tuna.tsinghua.edu.cn/tensorflow/linux/gpu/
python
import tensorflow as tf
hello=tf.constant('hello,Tensorflow')
sess=tf.Session()
print(sess.run(hello))
pip3 install tf_nightly-1.6.0.dev20180114-cp36-cp36m-manylinux1_x86_64.whl
查看已安裝TensorFlow版本和安裝路徑
python
import tensorflow as tf
tf.\__version__
tf.\__path__
完全卸載tensorflow
查看tensorflow版本
sudo pip show tensorflow
卸載：
sudo pip uninstall protobuf
sudo pip uninstall tensorflow
安裝：
sudo pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.8.0-cp27-none-linux_x86_64.whl
安裝pip
sudo apt-get install python-pip python-dev build-essential
sudo pip install --upgrade pip
sudo -H python -m pip install --upgrade pip
問題：使用pip出現
Traceback (most recent call last):
File "/usr/bin/pip3", line 9, in <module>
from pip import main
ImportError: cannot import name 'main'
sudo python -m pip uninstall pip && sudo apt install python-pip --reinstall
在ubuntu中使用pip報一下錯誤:
/usr/bin/pip: No such file or directory pip can no longer be found:
可以采用以下方式解決
which pip
pip
type pip
hash -r
Anaconda的jupyter notebook中配置tensorflow
(解決ImportError : No Moduled Name "tensorflow)
在/home/ubuntu/anaconda3/lib/python3.6/site-packages
新建path.pth,添加：
/home/ubuntu/anaconda3/envs/tensorflow36/lib/python3.6/site-packages
jupyter notebook下python2和python3共存
https://www.cnblogs.com/pertor/p/8728291.html
如果安裝了python2和者python3：
python2 -m pip install ipykernel
python2 -m ipykernel install --user
python3 -m pip install ipykernel
python3 -m ipykernel install --user
Ubuntu16.04安裝Teamviewer
https://www.teamviewer.com/zhcn/download/linux/
sudo apt-get -f install
sudo dpkg -i teamviewer_13.1.8286_amd64.deb
teamviewer
Ubuntu16.04安裝搜狗拼音輸入法（中文輸入法）
https://www.cnblogs.com/darklights/p/7722861.html
Ubuntu 16.04安裝谷歌 Chrome 瀏覽器
https://blog.csdn.net/wql2014302721/article/details/78571362
Ubuntu16.04安裝pycharm
https://blog.csdn.net/yucicheung/article/details/79336258
http://www.jetbrains.com/pycharm/download/#section=linux
sh ./pycharm.sh #在解壓縮文件目錄的bin/下執(zhí)行
Ubuntu 16.04 用戶登錄界面死循環(huán)問題的解決
方法1：
CTRL+ALT+F1進入文本模式
sudo apt-get remove nvidia-*
sudo apt-get autoremove
sudo nvidia-uninstall
reboot
Ctrl+Alt+F1
sudo service lightdm stop
sudo bash NVIDIA-Linux-x86_64-390.48.run -no-x-check -no-nouveau-check -no-opengl-files
https://blog.csdn.net/miclover_feng/article/details/79201865
方法2：
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update
sudo apt-get remove --purge nvidia-*
sudo apt-get autoremove #特別重要
sudo apt-get install -f #特別重要
sudo reboot
sudo apt-get install nvidia-384
http://www.reibang.com/p/d45434f28ca0
ubuntu重裝系統(tǒng)
問題：nouveau 000:01:00.0: fifo: SCHED_ERROR 08
- BIOS選擇啟動項到U盤弯菊，華碩主板電腦啟動電腦纵势，按F8進入。
顯示Install Ubuntu管钳，先不要點install Ubuntu這個選項钦铁。按F6，再
按e鍵蹋嵌，進入編輯頁面育瓜，在倒數第二行中，ro quiet splash后面添加nomodeset栽烂，這樣進入系統(tǒng)后不會因為獨顯驅動問題而導致黑屏了躏仇。 - 重啟，狂按ESC腺办，進入到grub焰手，按e，進入編輯怀喉。導數第二行找到quiet splash书妻， 將quiet splash $vt_handoff改為quiet splash nomodeset，ctrl+x重啟躬拢。
查看顯卡驅動
lshw -c video
查看configurure有driver字樣
nvidia-smi
查看GPU型號
lspci | grep -i vga
查看NVIDIA驅動版本
sudo dpkg --list | grep nvidia-*
查看磁盤空間
sudo fdisk -l
df -h
ubuntu的which躲履、find、whereis聊闯、locate命令
which 只能尋找可執(zhí)行文件 工猜，并在PATH變量里面尋找。
find 是直接在硬盤上搜尋菱蔬，功能強大篷帅，但耗硬盤史侣，一般不要用魏身。
whereis 從linux文件數據庫（/var/lib/slocate/slocate.db）尋找，所以有可能找到剛剛刪除箭昵，或者沒有發(fā)現新建的文件税朴，全部匹配。
locate 同上,不過文件名是部分匹配家制。
1、查看內存的插槽數慰丛，已經使用多少插槽。每條內存多大瘾杭，已使用內存多大
sudo dmidecode|grep -P -A5 "Memory\s+Device"|grep Size|grep -v Range
2诅病、查看內存支持的最大內存容量
sudo dmidecode|grep -P 'Maximum\s+Capacity'
3、查看內存的頻率
sudo dmidecode|grep -A16 "Memory Device"
sudo dmidecode|grep -A16 "Memory Device"|grep 'Speed'
警告：Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
鏈接：https://blog.csdn.net/hq86937375/article/details/79696023
吳恩達deeplearning課程作業(yè)環(huán)境:
鏈接：https://blog.csdn.net/pkrobbie/article/details/79346722
Tensorflow Ubuntu16.04上安裝及CPU運行tensorboard粥烁、CNN贤笆、RNN圖文教程
https://blog.csdn.net/wizen641372472/article/details/72675549
