About the size of the compiled Docker image

[JCCVW]

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Feature Request

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Bug Report

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System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04):ubuntu 18.04
• TensorFlow Serving installed from (source or binary):source
• TensorFlow Serving version:tfserving 2.4.1

Describe the problem

Because we modified the source code, we recompiled it and packaged it as a Docker image. Here are my steps:

1. Make a Devel image. Copy the source code into the container for compilation, and then use Docker Commit to package the container as an image. The size of this mirror image is 8 G.

2. Use the dockerfile.gpu file under /tensorflow_serving/tools/docker and change the base image to the devel image you just generated:

change:

ARG TF_SERVING_BUILD_IMAGE=tensorflow/serving:${TF_SERVING_VERSION}-devel-gpu

to:

ARG TF_SERVING_BUILD_IMAGE=tensorflow/serving:my_new_devel

But the resulting image is 5.35 gigabytes, compared with just 200 megabytes pulled away

docker pull tensorflow/serving

So what's the problem?

Exact Steps to Reproduce

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[JCCVW]

@arghyaganguly @lilao @ewilderj @kchodorow Any suggestions?

This is my instruction：

sudo docker build -f /home/WorkSpace/gProject/tfserving/tensorflow_serving/tensorflow_serving/tools/docker/Dockerfile.gpu -t tfserving_runntime_2.4.1_official .

No changes have been made to Dockerfile.gpu，But the result is 5.13G

[UsharaniPagadala]

@JCCVW

Could you please confirm if this is still an issue.Thanks

[singhniraj08]

@JCCVW,

The devel GPU image for TF Serving which looks to be about 5GB, of which ~1GB is TF Serving and it's build artifacts, with the rest being dependencies pulled in from apt-get. :latest-devel-gpu include all source dependencies/toolchain (cuda9/cudnn7) to develop, along with a compiled binary that works on NVIDIA GPUs which leads to larger size of images.

Thank you!

[github-actions[bot]]

This issue was closed due to lack of activity after being marked stale for past 14 days.