Pass callbacks kwarg to study.optimize() in run_hp_search_optuna()

[milos7250]

What does this PR do?

This PR allows the user to specify additional callbacks for optuna's study.optimize(). Previously, the callbacks kwarg would be passed to optuna.create_study() and would cause an Exception.

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[LysandreJik]

Is it possible to add an example of callback usage to make it clearer how this should be used?

[milos7250]

A general example of setting up a callback can be found on the optuna readthedocs. The idea is to allow users to have greater control over results in individual trials (e.g. adding more pruning conditions or further logging).

This PR allows the user to pass a callbacks argument to trainer.hyperparameter_search() containing list of callbacks to be used in the study. For example:

class StopWhenTrialKeepBeingPrunedCallback:
    def __init__(self, threshold: int):
        self.threshold = threshold
        self._consequtive_pruned_count = 0

    def __call__(self, study: optuna.study.Study, trial: [optuna.trial.FrozenTrial](https://docs.python.org/3/library/abc.html#abc.ABC)) -> None:
        if trial.state == optuna.trial.TrialState.PRUNED:
            self._consequtive_pruned_count += 1
        else:
            self._consequtive_pruned_count = 0

        if self._consequtive_pruned_count >= self.threshold:
            study.stop()

trainer.hyperparameter_search(
    n_trials=25,
    direction="minimize",
    backend="optuna",
    hp_space=hyperparameter_search_ranges,
    study_name="my_study",
    storage=f"sqlite:///optuna.db",
    callbacks=[StopWhenTrialKeepBeingPrunedCallback(5)],
)

[milos7250]

One more thing I've realized, the docstring for hyperparameter_search currently only mentions that **kwargs are passed to optuna.create_study(), this would need to be updated for this PR as callbacks are passed to study.optimize(). I am also not sure how this change would affect other hp search backends