Ubuntu-Installations-Grafiktreiber und CUDA-Tutorial

#Zeigen Sie die apt-Liste der installierten Pakete an --installed|grep -i nvidia
#Paket apt-get purge nvidia deinstallieren*

#Laden Sie wget herunter https://cn.download.nvidia.cn/tesla/470.57.02/NVIDIA-Linux-x86_64-470.57.02.run
#install sudo sh NVIDIA-Linux-x86_64-470.57.02.run

wget https://developer.nvidia.com/compute/cuda/10.0/Prod/local_installers/cuda_10.0.130_410.48_linux
sudo sh cuda_10.0.130_410.48_linux

vim ~/.bashrc
#Pfad hinzufügen export PATH=$PATH:/usr/local/cuda-11.4/bin
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-11.4/lib64
#Machen Sie die Umgebung effektivsource ~/.bashrc

sudo apt installiere nvidia-cuda-toolkit

wget https://developer.download.nvidia.cn/compute/machine-learning/cudnn/secure/8.2.2/11.4_07062021/Ubuntu18_04-x64/libcudnn8_8.2.2.26-1%2Bcuda11.4_amd64.deb?aJLLhXbzztwE4iizwf68uvg1s73kk4KKBGqv6B0UkO9HhnOhOsGHlyo1Br5CWc0nAIJLmc6C5SkLYqbdQqdZBoAdcVQgBTmWKXJXigR7roUeXd0VIKUuM57UKWMp3BUQgr6SQ4kkGnRRtUJ5mJt
dpkg -i libcudnn8_8.2.2.26-1+cuda11.4_amd64.deb

wget https://mirror.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-2021.05-Linux-x86_64.sh

vim ~/.bashrc
export PATH="/usr/local/anaconda3/bin:$PATH"
Quelle ~/.bashrc

"""Tsinghua-Conda-Quelle ändern"""
conda config – Kanäle hinzufügen https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
conda config – Kanäle hinzufügen https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
conda config --set show_channel_urls yes
conda config – Kanäle hinzufügen https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/

pip install tensorflow-gpu==2.2.0 -i https://pypi.tuna.tsinghua.edu.cn/simple

Tensorflow als tf importieren
drucken(tf.test.is_gpu_available())
tf.__version__
tf.__Pfad__

apt-get installiere python3.7
sudo update-alternatives --install /usr/bin/python python /usr/bin/python2 100
sudo update-alternatives --install /usr/bin/python python /usr/bin/python3 150

sudo apt installiere python3-pip