我正在尝试复制需要我遵循this particular tutorial on setting up Jupyter + Tensorflow + Nvidia GPU + Docker + Google Compute Engine的工作/实验。 “
我能够成功安装nvidia-docker。然而，在tutorial，在Verify the GPU is Visible from a Docker Container部分，当我试图跑
sudo nvidia-docker-plugin
我收到以下错误（请参阅最后一行）：
nvidia-docker-plugin | 2019/04/23 15:17:47 Loading NVIDIA unified memory
nvidia-docker-plugin | 2019/04/23 15:17:47 Loading NVIDIA management library
nvidia-docker-plugin | 2019/04/23 15:17:47 Discovering GPU devices
nvidia-docker-plugin | 2019/04/23 15:17:47 Provisioning volumes at /var/lib/nvidia-docker/volumes
nvidia-docker-plugin | 2019/04/23 15:17:47 Serving plugin API at /run/docker/plugins
nvidia-docker-plugin | 2019/04/23 15:17:47 Serving remote API at localhost:3476
nvidia-docker-plugin | 2019/04/23 15:17:47 Error: listen tcp 127.0.0.1:3476: bind: address already in use
当我跑
sudo nvidia-docker run --rm nvidia/cuda nvidia-smi
我碰巧得到以下executable file not found in $PATH": unknown错误：
docker: Error response from daemon: OCI runtime create failed: container_linux.go:345: starting container process caused "exec: \"nvidia-smi\": executable file not found in $PATH": unknown.
ERRO[0000] error waiting for container: context canceled
我是码头工人的新手;因此，如果有人能帮助我完成解决方案，那就太好了。我试过搜索for answers，但解决这个问题的实际过程避开了我。任何帮助将受到高度赞赏。
编辑：我按照教程中的规定设置了GCE实例（即Ubuntu 16.04 LTS，50GB启动盘，1个GPU，带有jupyter和tensorboard）
要解决第一个问题，看起来nvidia-docker-plugin已经在运行了。要查找此服务，请使用：
sudo netstat -tlpn | grep 3476
用以下方法杀死它：
sudo pkill nvidia-docker
第二步，安装nvidia-docker2并重新加载Docker守护进程配置：
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | \
sudo apt-key add -
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | \
sudo tee /etc/apt/sources.list.d/nvidia-docker.list
sudo apt-get update
# Install nvidia-docker2 and reload the Docker daemon configuration
sudo apt-get install -y nvidia-docker2
sudo pkill -SIGHUP dockerd
链接了解更多详情：