PyTorch 安装指南（CPU/GPU 版本）
环境准备
确保已安装 Python（推荐 3.8-3.10 版本）和 pip 包管理工具。可通过以下命令验证：
python --version pip --version对于 GPU 版本，需提前安装 CUDA 工具包（推荐 CUDA 11.8）和 cuDNN。通过以下命令检查 CUDA 是否可用：
nvidia-smi安装 PyTorch
访问 PyTorch 官网获取最新安装命令（https://pytorch.org/get-started/locally/），或直接使用以下通用命令：
CPU 版本
pip install torch torchvision torchaudiohttps://www.zhihu.com/zvideo/1994565209331885213/
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GPU（CUDA 11.8）版本
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118验证安装
运行 Python 解释器执行以下代码：
import torch print(torch.__version__) # 查看版本 print(torch.cuda.is_available()) # GPU 是否可用常见问题解决
- CUDA 不匹配：卸载现有版本后重新安装指定 CUDA 版本的 PyTorch。
- 权限问题：添加
--user参数或使用虚拟环境。 - 下载慢：更换 pip 源（如
-i https://pypi.tuna.tsinghua.edu.cn/simple）。
虚拟环境推荐
使用 conda 或 venv 创建独立环境：
conda create -n pytorch_env python=3.9 conda activate pytorch_env
