nuc (1) install env

 

nuc i7

ubuntu18.05

 

0-01更新
sudo apt-get update && sudo apt-get upgrade


0-1修改python默认版本 python3	
echo alias python=python3 >> ~/.bashrc
source ~/.bashrc
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update


#1 install and updata gcc
#cuda10.2 need gcc 8
sudo apt update
sudo apt install build-essential
sudo apt-get install manpages-dev
gcc --version
sudo apt install gcc-8 g++-8

sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-8 80 --slave /usr/bin/g++ g++ /usr/bin/g++-8 --slave /usr/bin/gcov gcov /usr/bin/gcov-8

sudo update-alternatives --config gcc

#2 install xianka driver

2-0添加驱动源（默认自带的驱动版本比较低） 
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update
然后，寻找合适的驱动版本，选择带有 推荐的
#2-1find drivers-version
ubuntu-drivers device
== /sys/devices/pci0000:00/0000:00:1c.5/0000:3a:00.0 ==
modalias : pci:v00008086d000024FDsv00008086sd00009010bc02sc80i00
vendor   : Intel Corporation
model    : Wireless 8265 / 8275
manual_install: True
driver   : backport-iwlwifi-dkms - distro free

#2-2 install  device
sudo apt install backport-iwlwifi-dkms


#3 install cuda10.2
sudo sh cuda_10.2.89_440.33.01_linux.run
--accept
--- don't install  Driver 440.33.01    
│ CUDA Installer                                                               │
│ - [ ] Driver                                                                 │
│      [ ] 440.33.01                                                           │
│ + [X] CUDA Toolkit 10.2                                                      │
│   [X] CUDA Samples 10.2                                                      │
│   [X] CUDA Demo Suite 10.2                                                   │
│   [X] CUDA Documentation 10.2                                                │
│   Options                                                                    │
│   Install

# add cuda10.2 to path
sudo gedit ~/.bashrc

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-10.2/lib64
export PATH=$PATH:/usr/local/cuda-10.2/bin
export CUDA_HOME=$CUDA_HOME:/usr/local/cuda-10.2

source ~/.bashrc

nvcc --version
# check is ok cuda
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Wed_Oct_23_19:24:38_PDT_2019
Cuda compilation tools, release 10.2, V10.2.89


#4 install cudnn
https://developer.nvidia.com/rdp/cudnn-archive

cuDNN Runtime Library for Ubuntu18.04 (Deb)

cuDNN Developer Library for Ubuntu18.04 (Deb)

cuDNN Code Samples and User Guide for Ubuntu18.04 (Deb)


#5 aconda
sudo sh Anaconda3-2021.05-Linux-x86_64.sh
sudo chmod -R 777 anaconda3/

#6 pytorch
https://pytorch.org/

sudo chown 1000:1000 /home/nuc/.conda/pkgs/urls.txt

conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch-lts

pip3 install torch torchvision torchaudio -f https://download.pytorch.org/whl/lts/1.8/torch_lts.html

wang ye  dowmnload

torch-1.8.1+cu102-cp38-cp38-linux_x86_64.whl
torchvision-0.9.1+cu102-cp38-cp38-linux_x86_64.whl
torchaudio-0.8.1-cp38-cp38-linux_x86_64.whl
torchtext-0.9.1-cp38-cp38-linux_x86_64.whl

pip install xxx

import torch

torch.cuda.is_available()
>>> True

torch.cuda.current_device()
>>> 0

torch.cuda.device(0)
>>> <torch.cuda.device at 0x7efce0b03be0>

torch.cuda.device_count()
>>> 1

torch.cuda.get_device_name(0)
>>> 'GeForce GTX 950M'

#7 opencv
pip install opencv-contrib-python
pip install opencv-python