版权声明：本文为博主原创文章，未经博主允许不得转载。 https://blog.csdn.net/zongza/article/details/88389074
1 首先查看有哪些image以及有哪些container
sudo docker image ls
# 结果
REPOSITORY TAG IMAGE ID CREATED SIZE
currycode/tf_serving_vc v1.0 26fdfe329859 2 months ago 3.85GB
currycode/tf_serving_vc 1.0 d6957b0caf48 2 months ago 3.79GB
ubuntu 18.04 93fd78260bd1 3 months ago 86.2MB
tensorflow/serving latest d42952c6f8a6 4 months ago 230MB
hello-world latest 4ab4c602aa5e 6 months ago 1.84kB
sudo docker ps -a
# 结果
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
2effa7569ce3 currycode/tf_serving_vc:1.0 "/bin/bash" 2 months ago Exited (0) 7 weeks ago tf_container_vc
a01e03520497 tensorflow/serving "/usr/bin/tf_serving…" 2 months ago Exited (137) 2 months ago determined_morse
ea05fb751b1a hello-world "/hello" 2 months ago Exited (0) 2 months ago dazzling_kirch
2 启动container
2.1 如果你之前没有创建container，则需要基于image新创建一个container
docker run --name=tf_container_vc2 -it currycode/tf_serving_vc
# 也就是从上面的currycode/tf_serving_vc镜像中启动一个container
# i表示获得一个交互式的连接，通过 standard in (STDIN)获取container的输入，也就是让容器的标准输入保持打开。
# t表示让Docker分配一个伪终端（pseudo-tty）并绑定到容器的标准输入上
# 如果想指定端口和ip映射关系，可以使用-p参数(选项指定Container到Host之间的端口映射关系)，默认映射到'172.17.0.2:9000'
# docker run: runs a container.
# tf_container_vc2: is the image you would like to run.
# -t: flag assigns a pseudo-tty or terminal inside the new container.
# -i: flag allows you to make an interactive connection by grabbing the standard in (STDIN) of the container.
# /bin/bash: launches a Bash shell inside our container.创建成功后会进入container的终端(因为-it参数)
参考：
http://www.runoob.com/docker/docker-image-usage.html
https://docs.docker.com/engine/reference/commandline/run/
2.2 如果你之前已经创建过container（比如上面docker ps 命令中显示有三个container），则可以直接启动container，不需要从image创建一个新的container了
docker start -i tf_container_vc
# -i表示Attach container’s STDIN
# 成功后如下面第二行所显示会直接进入container的终端
[currycode@mjrc-server11 ~]$ sudo docker start -i tf_container_vc
root@2effa7569ce3:/tensorflow-serving#
如果使用docker start tf_container_vc 则是在后台运行container
[currycode@mjrc-server11 ~]$ sudo docker start tf_container_vc
tf_container_vc
[currycode@mjrc-server11 ~]$ 参考：
https://docs.docker.com/engine/reference/commandline/start/
http://www.runoob.com/docker/docker-start-stop-restart-command.html
如果container此时运行在后台（没有使用-i参数），那么需要使用docker attach命令或者docker exec命令进入 他的终端
2.2.1 docker attach
[currycode@mjrc-server11 ~]$ sudo docker attach tf_container_vc
root@2effa7569ce3:/tensorflow-serving#但是attach方法有个缺点，exit后container也跟着退出了
root@2effa7569ce3:/tensorflow-serving# exit
exit
[currycode@mjrc-server11 ~]$ sudo docker ps -a
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
2effa7569ce3 currycode/tf_serving_vc:1.0 "/bin/bash" 2 months ago Exited (0) 3 seconds ago tf_container_vc
a01e03520497 tensorflow/serving "/usr/bin/tf_serving…" 2 months ago Exited (137) 2 months ago determined_morse
ea05fb751b1a hello-world "/hello" 2 months ago Exited (0) 2 months ago dazzling_kirch
要想退出container时，让container仍然在后台运行着，可以使用“docker exec -it”命令。每次使用这个命令进入container，当退出container后，container仍然在后台运行，命令使用方法如下：
2.2.2 docker exec
[currycode@mjrc-server11 ~]$ sudo docker exec -it tf_container_vc /bin/bash
root@2effa7569ce3:/tensorflow-serving#
# tf_container_vc ：要启动的container的名称
# /bin/bash：在container中启动一个bash shell这样输入“exit”或者按键“Ctrl + C”退出container时，这个container仍然在后台运行：
root@2effa7569ce3:/tensorflow-serving# exit
exit
[currycode@mjrc-server11 ~]$ sudo docker ps -a
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
2effa7569ce3 currycode/tf_serving_vc:1.0 "/bin/bash" 2 months ago Up 4 minutes tf_container_vc
a01e03520497 tensorflow/serving "/usr/bin/tf_serving…" 2 months ago Exited (137) 2 months ago determined_morse
ea05fb751b1a hello-world "/hello" 2 months ago Exited (0) 2 months ago dazzling_kirch
参考：
最后查看container IP address:
[currycode@mjrc-server11 ~]$ sudo docker network inspect bridge | grep IPv4Address
"IPv4Address": "172.17.0.2/16",
其他方法：
[currycode@mjrc-server11 ~]$ sudo docker exec -it tf_container_vc ip addr | grep global
[currycode@mjrc-server11 ~]$ sudo docker port tf_container_vc当对container进行了一下修改后，想要永久保存这些修改，需要使用docker commit命令：
[currycode@mjrc-server11 ~]$ sudo docker commit 2effa7569ce3 currycode/tf_serving_vc:v2.0
sha256:90a90c637f62a6819e14f3e6c256926921d4d6f661d941d114d7990b3473c231
[currycode@mjrc-server11 ~]$ sudo docker ps -a
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
2effa7569ce3 currycode/tf_serving_vc:1.0 "/bin/bash" 2 months ago Up 10 hours tf_container_vc
a01e03520497 tensorflow/serving "/usr/bin/tf_serving…" 2 months ago Exited (137) 2 months ago determined_morse
ea05fb751b1a hello-world "/hello" 2 months ago Exited (0) 2 months ago dazzling_kirch
[currycode@mjrc-server11 ~]$ sudo docker images
REPOSITORY TAG IMAGE ID CREATED SIZE
currycode/tf_serving_vc v2.0 90a90c637f62 11 seconds ago 4GB
currycode/tf_serving_vc v1.0 26fdfe329859 2 months ago 3.85GB
currycode/tf_serving_vc 1.0 d6957b0caf48 2 months ago 3.79GB
ubuntu 18.04 93fd78260bd1 3 months ago 86.2MB
tensorflow/serving latest d42952c6f8a6 4 months ago 230MB
hello-world latest 4ab4c602aa5e 6 months ago 1.84kB
参考：