nvidia-docker运行pytorch-gpu
1.宿主机器安装显卡驱动和cuda 11.8, cudnn 11.8
2.拉镜像（基于ubuntu）:
docker pull anibali/pytorch:2.0.1-cuda11.8
运行容器：
docker run -it --init --gpus=all --ipc=host --name pytorch -p 1778:8888 --volume="$PWD:/app" [镜像id] python3
运行一下脚本检查cuda是否可用:
import torch
flag = torch.cuda.is_available()
print(flag)
ngpu= 1
# Decide which device we want to run on
device = torch.device("cuda:0" if (torch.cuda.is_available() and ngpu > 0) else "cpu")
print(device)
print(torch.cuda.get_device_name(0))
print(torch.rand(3,3).cuda())
正确输出结果类似：
True
cuda:0
GeForce GTX 1080
tensor([[0.9530, 0.4746, 0.9819],
[0.7192, 0.9427, 0.6768],
[0.8594, 0.9490, 0.6551]], device='cuda:0')