docstr: Returns local and sorted random search as acquisition maximizer.
docstr_tok: ["Returns","local","and","sorted","random","search","as","acquisition","maximizer","."]
code: def get_acquisition_maximizer(  # type: ignore
      scenario: Scenario,
  ) -> LocalAndSortedRandomSearch:
      """Returns local and sorted random search as acquisition maximizer."""
      optimizer = LocalAndSortedRandomSearch(
          scenario.configspace,
          seed=scenario.seed,
      )
  
      return optimizer
  
imports: from __future__ import annotations
  from ConfigSpace import Configuration
  from smac.acquisition.function.expected_improvement import EI
  from smac.acquisition.maximizer.local_and_random_search import LocalAndSortedRandomSearch
  from smac.facade.abstract_facade import AbstractFacade
  from smac.initial_design.default_design import DefaultInitialDesign
  from smac.intensifier.intensifier import Intensifier
  from smac.model.random_forest.random_forest import RandomForest
  from smac.multi_objective.aggregation_strategy import MeanAggregationStrategy
  from smac.random_design.probability_design import ProbabilityRandomDesign
  from smac.runhistory.encoder.encoder import RunHistoryEncoder
  from smac.scenario import Scenario
  from smac.utils.logging import get_logger
label_desc: Use image node_id 3 for calling the AlgorithmConfigurationFacade obj's underlying member method code with example usage: obj.get_acquisition_maximizer(scenario) and returns: optimizer