Experimenting faster and effecient docker builds for projects including tensorflow ( which is large ).
REF: https://www.tensorflow.org/install/docker
Manual installation of tensorflow as a python package.
- Not implemented Due to size of the package better have a separate base image that is to be used in an application image
Using docker hub tensorflow docker images as base images.
Example:
FROM tensorflow/tensorflow:latest-gpu
# Add your application here
REF: https://hub.docker.com/r/tensorflow/tensorflow/
Tested tags:
- The base images are large. So, the final image size will be large.
- The base images are large. So, the builds will take reasonable time.
- The base images are large. So, the docker hub pulls will take reasonable time.
- No application is added to the base images. So, build time may vary depending on the application.
- Using docker hub tensorflow images as base images is fast ( Not tested Manual installation of tensorflow as a python package. ). Since the base images are already built and available in docker hub. Builds take reasonable time.
- latest tag
- 37s
- latest gpu tag
- 1m 0s
- nightly tag
- 24s
- nightly gpu tag
- 1m 7s
- latest tag
- All runs are done in Github Actions.