Support `experiment_config` in HyperparameterTuner for unified lineage across training and tuning phases

Is there a way to pass experiment_config to HyperparameterTuner to have unified lineage tracking across all phases of the model?

What is the recommended way to track end-to-end lineage across training and tuning phases? Should we just manually create a Tracker and log the hyperparameters, objective metrics, and training result metrics?

I'd like to see symmetry between the Estimator and HyperparameterTuner APIs - and pass experiment_config to both.

Any guidance would be appreciated.