安装nvidia driver
game ready driver 或者studio driver都行
安装WSL
nvidia wsl安装文档 或者 Install WSL | Microsoft Learn
默认安装ubuntu
查看可安装linux版本命令：wsl -l -o
wsl --install
wsl --update
启动 wsl --distribution Ubuntu --user <username>
停止 wsl --terminate Ubuntu
在wsl命令控制台内执行下列操作，不是在windows环境内
安装cuda toolkit
CUDA Toolkit 12.3 Downloads | NVIDIA Developer
wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-wsl-ubuntu.pin
sudo mv cuda-wsl-ubuntu.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget https://developer.download.nvidia.com/compute/cuda/12.3.0/local_installers/cuda-repo-wsl-ubuntu-12-3-local_12.3.0-1_amd64.deb
sudo dpkg -i cuda-repo-wsl-ubuntu-12-3-local_12.3.0-1_amd64.deb
sudo cp /var/cuda-repo-wsl-ubuntu-12-3-local/cuda-*-keyring.gpg /usr/share/keyrings/
sudo apt-get update
sudo apt-get -y install cuda-toolkit-12-3
配置环境变量
在~/.bashrc添加
export PATH=/usr/local/cuda-12.3/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
安装cudnn
下载链接: cuDNN Download | NVIDIA Developer
安装手册：Installation Guide - NVIDIA Docs
运行nvidia-smi命令查看cuda版本
下载对应cudnn版本
开始安装
sudo dpkg -i cudnn-local-repo-$distro-8.x.x.x_1.0-1_amd64.deb
例如：sudo dpkg -i cudnn-local-repo-ubuntu2204-8.9.5.29_1.0-1_amd64.deb
sudo cp /var/cudnn-local-repo-*/cudnn-local-*-keyring.gpg /usr/share/keyrrings/
例如：sudo cp /var/cudnn-local-repo-ubuntu2204-8.9.5.29/cudnn-local-275FA572-keyring.gpg /usr/share/keyrings/
sudo apt-get update
sudo apt-get install libcudnn8=8.x.x.x-1+cudaX.Y
例如：sudo apt-get install libcudnn8=8.9.5.29-1+cuda12.2
sudo apt-get install libcudnn8-dev=8.x.x.x-1+cudaX.Y
例如：sudo apt-get install libcudnn8-dev=8.9.5.29-1+cuda12.2
sudo apt-get install libcudnn8-samples=8.x.x.x-1+cudaX.Y
例如：sudo apt-get install libcudnn8-samples=8.9.5.29-1+cuda12.2
安装tensorflow
没有pip命令，先安装
sudo apt-get install -y pip
pip install --upgrade pip
pip install tensorflow[and-cuda]
切换源安装：
pip install --upgrade pip -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install tensorflow[and-cuda] -i https://pypi.tuna.tsinghua.edu.cn/simple
验证安装
python3 -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([1000, 1000])))"
python3 -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"
注意：本文归作者所有，未经作者允许，不得转载
