Save Suggestion state after deployment is deleted

[andreyvelich]

/kind feature

Katib should have functionality to save Suggestion state somewhere besides Suggestion pod.
Some users would like to resume Experiments, but they don't want to have always running Suggestion deployment. For example we can use PV.

We can use ResumeExperiment flag from here: #1061 to specify resuming experiment mechanism.

/cc @johnugeorge @gaocegege @hougangliu @richardsliu

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[andreyvelich]

/priority p0

[andreyvelich]

@johnugeorge @gaocegege What do you think about saving Suggestion states using object serialisation, e.g pickle in Python: https://docs.python.org/3/library/pickle.html.
I believe Fairing also uses pickle to serialise training code.

In that case, if ResumeExperiment: Always, after each GetSuggestion call, Suggestion can create pickle file with the current object state. Each suggestion has <AlgorithmNameService> class. For example:

katib/pkg/suggestion/v1alpha3/hyperopt/service.py

Line 15 in 58e0764

class HyperoptService(api_pb2_grpc.SuggestionServicer, HealthServicer):

.

Then, we can save this pickle file in PV and use it to resume experiment with appropriate state for the Suggestion service class

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[gaocegege]

The approach LGTM if the suggestion is implemented in Python. But I prefer a general solution for different languages.

[andreyvelich]

Let's discuss implementation here: #1250.