DEHB and non-async DE optimiser update design about dehb HOT 5 CLOSED

# DE related variables
self.mutation_factor = mutation_factor
self.crossover_prob = crossover_prob
self.strategy = strategy
self.fix_type = boundary_fix_type
self.max_age = max_age
self.de_params = {
    "mutation_factor": self.mutation_factor,
    "crossover_prob": self.crossover_prob,
    "strategy": self.strategy,
    "configspace": self.configspace,
    "boundary_fix_type": self.fix_type,
    "max_age": self.max_age,
    "cs": self.cs,
    "dimensions": self.dimensions,
    "f": f
}

self.de[b] = AsyncDE(**self.de_params, budget=b, pop_size=self._max_pop_size[b])

class AsyncDE(DE):
    def __init__(self, cs=None, f=None, dimensions=None, pop_size=None, max_age=np.inf,
                 mutation_factor=None, crossover_prob=None, strategy='rand1_bin',
                 budget=None, async_strategy='deferred', **kwargs):                 

class DEHBBase:
    def __init__(self, cs=None, f=None, dimensions=None, mutation_factor=None,
                 crossover_prob=None, strategy=None, min_budget=None,
                 max_budget=None, eta=None, min_clip=None, max_clip=None,
                 boundary_fix_type='random', max_age=np.inf, async_strategy='deferred', **kwargs):
        # Benchmark related variables
        self.cs = cs
        self.configspace = True if isinstance(self.cs, ConfigSpace.ConfigurationSpace) else False
        if self.configspace:
            self.dimensions = len(self.cs.get_hyperparameters())
        elif dimensions is None or not isinstance(dimensions, (int, np.int)):
            assert "Need to specify `dimensions` as an int when `cs` is not available/specified!"
        else:
            self.dimensions = dimensions
        self.f = f

        # DE related variables
        self.mutation_factor = mutation_factor
        self.crossover_prob = crossover_prob
        self.strategy = strategy
        self.fix_type = boundary_fix_type
        self.max_age = max_age
        self.async_strategy = async_strategy
        self.de_params = {
            "mutation_factor": self.mutation_factor,
            "crossover_prob": self.crossover_prob,
            "strategy": self.strategy,
            "configspace": self.configspace,
            "boundary_fix_type": self.fix_type,
            "max_age": self.max_age,
            "cs": self.cs,
            "dimensions": self.dimensions,
            "f": f,
            "async_strategy": self.async_strategy
        }

class DEHB(DEHBBase):
    def __init__(self, cs=None, f=None, dimensions=None, mutation_factor=0.5,
                 crossover_prob=0.5, strategy='rand1_bin', min_budget=None,
                 max_budget=None, eta=3, min_clip=None, max_clip=None, configspace=True,
                 boundary_fix_type='random', max_age=np.inf, n_workers=None, client=None, async_strategy='deferred', **kwargs):
        super().__init__(cs=cs, f=f, dimensions=dimensions, mutation_factor=mutation_factor,
                         crossover_prob=crossover_prob, strategy=strategy, min_budget=min_budget,
                         max_budget=max_budget, eta=eta, min_clip=min_clip, max_clip=max_clip,
                         configspace=configspace, boundary_fix_type=boundary_fix_type,
                         max_age=max_age, async_strategy=async_strategy, **kwargs)