feat: Added the VertexAiResourceNoun.to_dict() method

[Ark-kun]

This method allows getting the resource metadata as a standard Python dictionary.
Without this method, any user who would want to do this would have to access private fields.

Thank you for opening a Pull Request! Before submitting your PR, there are a few things you can do to make sure it goes smoothly:

• Make sure to open an issue as a bug/issue before writing your code! That way we can discuss the change, evaluate designs, and agree on the general idea
• Ensure the tests and linter pass
• Code coverage does not decrease (if any source code was changed)
• Appropriate docs were updated (if necessary)

Fixes #<issue_number_goes_here> 🦕

[ivanmkc]

LGTM

Just wondering, what are the use cases are for exposing the internal resource metadata like this. Would it be better to create getters for each field we want to expose?

[Ark-kun]

Just wondering, what are the use cases are for exposing the internal resource metadata like this. Would it be better to create getters for each field we want to expose?

The aiplatform module is higher-level compared to the underlying API and gapic. Not everything is exposed.
I'm not sure manually adding all properties is fully maintainable.
In my case I wanted to return the full resource description in an industry standard JSON format that can easily be parsed and queried by any downstream tools.
When you want to "pass" a small resource description between different containers or components, using a format like JSON has many portability benefits. Adding .to_dict() makes it easy to "export" and serialize the resource description.

[gcf-merge-on-green]

Merge-on-green attempted to merge your PR for 6 hours, but it was not mergeable because either one of your required status checks failed, one of your required reviews was not approved, or there is a do not merge label. Learn more about your required status checks here: https://help.github.com/en/github/administering-a-repository/enabling-required-status-checks. You can remove and reapply the label to re-run the bot.

[Ark-kun]

It looks like one of the tests has flaked. Is it possible to retry it?