Building tensorflow-serving docker gpu from source with docker?

Question

I have followed these steps for building docker from source,

git clone https://github.com/tensorflow/serving
cd serving

docker build --pull -t $USER/tensorflow-serving-devel-gpu \
  -f tensorflow_serving/tools/docker/Dockerfile.devel-gpu .

docker build -t $USER/tensorflow-serving-gpu \
  --build-arg TF_SERVING_BUILD_IMAGE=$USER/tensorflow-serving-devel-gpu \
  -f tensorflow_serving/tools/docker/Dockerfile.gpu .

These took quite a long time for get compiled and it was completed successfully,

Now if I check docker images , I see this below response,

REPOSITORY                          TAG                             IMAGE ID       CREATED             SIZE
root/tensorflow-serving-gpu         latest                          42e221bb6bc9   About an hour ago   8.49GB
root/tensorflow-serving-devel-gpu   latest                          7fd974e5e0c5   2 hours ago         21.8GB
nvidia/cuda                         11.0-cudnn8-devel-ubuntu18.04   7c49b261611b   3 months ago        7.41GB

I have two doubts regarding this,

1. Building from source took a large amount of time, and now I want to backup /save these images or containers and save them so I can re-use them later on different machine with same arch. If you know how to do it, please help me with the commands.

2. Since I completed the build successfully, I need to free up some space by removing unnecessary docker development images used to build tensorflow-serving-gpu? I have three images here which are related to tensorflow serving and I don't know which one to delete?

Answer 1

If you want to save images:

docker save root/tensorflow-serving-gpu:latest  -o  tfs.tar

And if you want to load it:

docker load -i tfs.tar

root/tensorflow-serving-gpu and root/tensorflow-serving-devel-gpu are two different images. You can see the differences by looking at the details of Dockerfile.devel-gpu and Dockerfile.gpu .