# Docker tutorial

Created on Wed, 02 Dec 2019, 06:00PM

Last changed on Wed, 04 Dec 2019, 05:58PM

> `Docker`常用命令手册

* 运行Nvidia-docker

```bash
sudo nvidia-docker run --runtime=nvidia -it -d -p 8888:8888 -p 6006:6006 -v $(pwd):/tf/ tensorflow/tensorflow:latest-gpu-py3-jupyter
--rm # 停止后即删除
```

```bash
sudo docker pull tensorflow/tensorflow:latest-gpu-py3-jupyter
# docker pull 
sudo docker images
docker run --help
docker run [-it] some-image # 创建某个镜像的容器。注意，同一个镜像可以通过这种方式创建任意多个container. 加上-it之后，可以创建之后，马上进入交互模式。
docker rm container-id # 删除某个容器
docker start [-i] container-id # 启动某个容器，必须是已经创建的。 加上-i 参数之后，可以直接进入交互模式：
docker attach container-id # 进入交互模式的另一种方式
# 进入交互模式之后，想退出但是保持容器运行，按CTRL+Q+P三个键
# 退出，并关闭停止容器，按CTRL+D或者输入exit再回车
```

* 容器备份

先通过`docker ps`或者`docker ps -a`来查看你想备份的容器的id， 然后通过：

```
docker commit -p [your-container-id] [your-backup-name]
```

来将id为your-container-id的容器创建成一个镜像快照。

接着，你通过`docker images`就可以查看到刚刚创建好的镜像快照了。 然后，通过：

```
docker save -o [path-you-want-to-save/your-backup-name.tar]] [your-backup-name]
```

把那个镜像打包成tar文件，保存到服务器上。 后面就可以把服务器上打包好的tar文件，下载到本地了。

恢复： `docker load -i your-backup-name.tar`

`docker run -d -p 80:80 your-backup-name`

* 其他

```bash
docker run \
    --interactive \
    --tty \
    --volume $(pwd):/federated \
    --workdir /federated \
    tensorflow_federated \
    bash
    
sudo nvidia-docker run --runtime=nvidia \
    --interactive \
    -p 8896:8888 \
    -p 6003:6006 \
    --tty \
    --volume $(pwd):/federated \
    --workdir /federated \
    tensorflow_federated:v0.11-py3-jupyter \
    bash
```


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