# 编辑 /etc/modprobe.d/blacklist-nouveau.conf 文件
# 添加
blacklist nouveau
blacklist lbm-nouveau
options nouveau modeset=0
alias nouveau off
alias lbm-nouveau off

# 关闭nouveau
echo options nouveau modeset=0 | sudo tee -a /etc/modprobe.d/nouveau-kms.conf

sudo update-initramfs -u
sudo reboot

ubuntu-drivers devices

sudo apt install nvidia-driver-470-server

# cuda
wget https://developer.download.nvidia.com/compute/cuda/11.4.0/local_installers/cuda_11.4.0_470.42.01_linux.run
sudo sh cuda_11.4.0_470.42.01_linux.run

# tensorflow 2
mamba create -n tf2 python=3.8
mamba activate tf2
mamba install cudatoolkit=11.2 cudnn=8.1.0  -c conda-forge
mamba install cuda-nvcc -c nvidia
pip install tensorflow tensorflow-probability

# 设置激活后的环境变量
mamba env config vars set LD_LIBRARY_PATH=%LD_LIBRARY_PATH%;%CONDA_PREFIX%\lib\
mamba env config vars set XLA_FLAGS=--xla_gpu_cuda_data_dir=%CONDA_PREFIX%
# 也可以新建$mamba_PREFIX/etc/mamba/activate.d/env_vars.sh, 
# 然后手动编辑
# 查看变量
mamba env config vars list
# 验证
python -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"

# 其他包
mamba install matplotlib deepxde fire black

# 安装mambaforge, 如果最新版本安装失败，可以去找旧版本下载
wget "https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-$(uname)-$(uname -m).sh"
bash Mambaforge-$(uname)-$(uname -m).sh

# 
conda init
source ~/.bashrc

# 可选择其他源
conda config --set show_channel_urls yes
# 打开配置文件
vim ~/.condarc
# 然后添加下面的两行，阿里云的源
custom_channels:
  conda-forge: http://mirrors.aliyun.com/anaconda/cloud

# 创建环境
mamba create -n tf2 python=3.9
mamba activate tf2
mamba install cudatoolkit=11.2 cudnn=8.1.0
mamba install cuda-nvcc -c nvidia
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CONDA_PREFIX/lib/
pip install tensorflow==2.8 tensorflow-probability==0.16.0

# 设置激活后的环境变量
mkdir -p $CONDA_PREFIX/etc/conda/activate.d
echo 'export LD_LIBRARY_PATH=$CONDA_PREFIX/lib/:$LD_LIBRARY_PATH' > $CONDA_PREFIX/etc/conda/activate.d/env_vars.sh

echo 'export XLA_FLAGS=--xla_gpu_cuda_data_dir=$CONDA_PREFIX' >> $CONDA_PREFIX/etc/conda/activate.d/env_vars.sh

# 或者可使用下述设置变量
mamba env config vars set ... ...
mamba env config vars set XLA_FLAGS=--xla_gpu_cuda_data_dir=$CONDA_PREFIX
mamba env config vars list

# 验证
python -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"

# 可以手动编辑这个文件: $CONDA_PREFIX/etc/conda/activate.d/env_vars.sh
export OLD_LD_LIBRARY_PATH=${LD_LIBRARY_PATH}
export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:$CONDA_PREFIX/lib/

# in $CONDA_PREFIX/etc/conda/deactivate.d/env_vars.sh:
export LD_LIBRARY_PATH=${OLD_LD_LIBRARY_PATH}
unset OLD_LD_LIBRARY_PATH

# command 1
mkdir -p $CONDA_PREFIX/etc/conda/activate.d

echo -e "export OLD_LD_LIBRARY_PATH=\${LD_LIBRARY_PATH}\nexport LD_LIBRARY_PATH=\$CONDA_PREFIX/lib/:\${LD_LIBRARY_PATH}" >> $CONDA_PREFIX/etc/conda/activate.d/env_vars.sh

# command 2
mkdir -p $CONDA_PREFIX/etc/conda/deactivate.d

echo -e "export LD_LIBRARY_PATH=\${OLD_LD_LIBRARY_PATH}\nunset OLD_LD_LIBRARY_PATH" >> $CONDA_PREFIX/etc/conda/deactivate.d/env_vars.sh

pip install protobuf==3.20.*

CONDA_PKGS_DIRS=~/.conda/pkgs/ mamba create -p ~/.conda/envs/py2tf1/ python=2.7 -y

mamba install cudatoolkit=8.0 cudnn=5.1 -c free
# conda install cudatoolkit=8.0 cudnn=5.1 -c https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/linux-64/
mamba install cuda-nvcc -c nvidia
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CONDA_PREFIX/lib/

mamba create -n pytorch python=3.9 -y
mamba install pytorch torchvision torchaudio pytorch-cuda=11.6 -c pytorch -c nvidia

# 其他包
mamba install pandas matplotlib deepxde fire black pytorch-lightning

# cuda 运行时
conda install -y -c "nvidia/label/cuda-12.1.0" cuda-runtime