WSL中安装cuda

安装gcc

sudo apt update
sudo apt install -y gcc g++

安装cuda，不装驱动：

#下载 CUDA 13.2 for WSL-Ubuntu
wget https://developer.download.nvidia.com/compute/cuda/13.2.0/local_installers/cuda-repo-wsl-ubuntu-13-2-local_13.2.0-1_amd64.deb

#安装
sudo dpkg -i cuda-repo-wsl-ubuntu-13-2-local_13.2.0-1_amd64.deb
sudo cp /var/cuda-repo-wsl-ubuntu-13-2-local/cuda-*-keyring.gpg /usr/share/keyrings/
sudo apt-get update
sudo apt-get -y install cuda-toolkit-13-2

配置环境变量：

echo 'export PATH=/usr/local/cuda/bin:$PATH' >> ~/.bashrc
echo 'export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc
echo 'export CUDA_HOME=/usr/local/cuda' >> ~/.bashrc
source ~/.bashrc

安装python环境：

apt update
apt install -y python3.12-venv python3-pip
python3 -m venv myenv
source myenv/bin/activate
pip install torch torchvision torchaudio

验证 CUDA 加速是否成功

python -c "import torch; print('CUDA:', torch.cuda.is_available()); print('GPU:', torch.cuda.get_device_name(0) if torch.cuda.is_available() else '失败')"

设置pip源：

pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple
pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
pip config set global.index-url https://mirrors.cloud.tencent.com/pypi/simple