conda install pytorch=0.4.0 cuda90 -c pytorch
conda install pytorch=0.4.0 torchvision cudatoolkit=9.0 -c pytorch
難受,卸載ubuntu的時候,這些天的筆記都沒有保存,直接刪除了,心痛
以後這些東西還是儘量保存在windows上比較好。
python
import torch
torch.__version__
lspci | grep -i nvidia
查看物理cpu個數
grep 'physical id' /proc/cpuinfo | sort -u
查看核心數量
grep 'core id' /proc/cpuinfo | sort -u | wc -l
查看線程數
grep 'processor' /proc/cpuinfo | sort -u | wc -l
(torch) twinkle@twinkle-ubuntu:~/Myments$ grep 'physical id' /proc/cpuinfo | sort -u
physical id : 0
(torch) twinkle@twinkle-ubuntu:~/Myments$ grep 'core id' /proc/cpuinfo | sort -u | wc -l
6
(torch) twinkle@twinkle-ubuntu:~/Myments$ grep 'processor' /proc/cpuinfo | sort -u | wc -l
12
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
====================================================================
二是:先官網下載好對應驅動編譯
Nvidia中文官網是 http://www.nvidia.cn/page/home.html
1)打開終端,先刪除舊的驅動:
sudo apt-get purge nvidia*
2)禁用自帶的 nouveau nvidia驅動
sudo apt-get install vim-gtk
sudo vim /etc/vim/vimrc
在這個文件中可以看到有下面這個if判斷,意思是語法高亮,如果是被註釋掉狀態,可以將其放開:
if has("syntax")
syntax on
endif
然後請在您的VIM的最後一行,輸入下面這些內容,可以讓您的VIM變得更漂亮、舒服。
"設置左側行號
set nu
"設置tab鍵長度爲4
set tabstop=4
"突出顯示當前行
set cursorline
"在右下角顯示光標位置的狀態行
set ruler
"自動縮進
set autoindent
"覆蓋文件時不備份
set nobackup
編輯完成後使用 :wq 進行保存退出
說明: 冒號結束編輯 ,w爲保存 q爲退出 如果你想放棄也可以 q!爲強制退出
---------------------
原文:https://blog.csdn.net/zht741322694/article/details/78959338
創建一個文件通過命令 sudo vim /etc/modprobe.d/blacklist-nouveau.conf
並添加如下內容:
blacklist nouveau
options nouveau modeset=0
再更新一下
sudo update-initramfs -u
修改後需要重啓系統。確認下Nouveau是已經被你幹掉,使用命令: lsmod | grep nouveau
3)重啓系統至init 3(文本模式),也可先進入圖形桌面再運行init 3進入文本模式,再安裝下載的驅動就無問題,
首先我們需要結束x-window的服務,否則驅動將無法正常安裝
關閉X-Window,很簡單:sudo service lightdm stop,然後切換tty1控制檯:Ctrl+Alt+F1即可
4)接下來就是最關鍵的一步了:sudo./NVIDIA.run開始安裝,安裝過程比較快,根據提示選擇即可最後安裝完畢後,重新啓動X-Window:sudo service lightdm start,然後Ctrl+Alt+F7進入圖形界面;
最後測試一下是否安裝成功
nvidia-smi
nvidia-settings
==========================================================================
sudo apt-get update
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update
sudo apt-get install nvidia-418
sudo apt-get install mesa-common-dev
sudo apt-get install freeglut3-dev
sudo reboot
nvidia-settings
--------------------------------------
sudo cp -i bxt_guc_ver8_7.bin /lib/firmware/i915
sudo cp -i kbl_guc_ver9_14.bin /lib/firmware/i915
三是:添加官方ppa源
快捷鍵ctrl+alt+T打開命令終端,加入官方ppa源。
$ sudo add-apt-repository ppa:graphics-drivers/ppa
需要輸入密碼並按enter鍵確認。之後刷新軟件庫並安裝最新驅動。
$ sudo apt-get update
$ sudo apt-get install nvidia-367 nvidia-settings nvidia-prime
安裝完成後通過下面命令查看是否安裝成功。
$ nvidia-settings
注意安裝完成後要重啓,有如下效果則安裝完成,否則就說明安裝有問題,嘗試關閉UEFI保護試試。
==========================================================================
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
===========================================================================
sudo sh cuda_9.0.176_384.81_linux.run --no-opengl-libs
Do you accept the previously read EULA?
2 accept/decline/quit: accept
3 Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 384.81?
4 (y)es/(n)o/(q)uit: n
5 Install the CUDA 9.0 Toolkit?
6 (y)es/(n)o/(q)uit: y
7 Enter Toolkit Location
8 [ default is /usr/local/cuda-9.0 ]:
9 Do you want to install a symbolic link at /usr/local/cuda?
10 (y)es/(n)o/(q)uit: y
11 Install the CUDA 9.0 Samples?
12 (y)es/(n)o/(q)uit: y
13 Enter CUDA Samples Location
14 [ default is /home/pertor ]:
15 Installing the CUDA Toolkit in /usr/local/cuda-9.0 ...
16 Missing recommended library: libXmu.so
sudo gedit ~/.bashrc
export PATH=/usr/local/cuda-9.0/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
source ~/.bashrc
cd /usr/local/cuda-9.0/samples/1_Utilities/deviceQuery
sudo make
./deviceQuery
tar -zxvf cudnn-9.0-linux-x64-v7.6.2.24.tgz
sudo cp cuda/include/cudnn.h /usr/local/cuda/include/
sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64/ -d
sudo chmod a+r /usr/local/cuda/include/cudnn.h
sudo chmod a+r /usr/local/cuda/lib64/libcudnn*
nvcc -V
https://www.cnblogs.com/pertor/p/8733010.html
====================================================================
import torch
print(torch.cuda.is_available())
====================================================================
tar -zxvf linux-x64.tar.gz