Programmatic way to get available training/inference containers.

**Describe the feature you'd like**
It would be very helpful to be able to programmatically get all available framerworks, py versions etc, prior to `sagemaker.image_uris.retrieve(...)`.
This would allow people to see what containers are available, without having to dig through repositories and try to find supported images or continuously hit errors until the right permutation of framework, framework version, and py version are achieved.

**How would this feature be used? Please describe.**
Something like `sagemaker.image_uris.show_images()` or something like that would be desired. This ideally would take no parameters and show maybe a dictionary of all the frameworks, framework versions, and respective py verisons.

**Describe alternatives you've considered**
Considering programmatically parsing: https://github.com/aws/deep-learning-containers/blob/master/available_images.md

But this does not feel like a good solution at all.

Start by reading the sagemaker.image_uris.retrieve(...) entry point and compare its supported framework, framework-version, and Python-version combinations with deep-learning-containers/available_images.md. Define how a parameterless show_images()-style API should represent all available combinations, and consider how completion can be verified against the listed containers without requiring repeated failed retrievals.

Written by the indexing model from the issue text.