code: def __init__(self, space: SpaceWrapper, args):
      super().__init__(space)
  
      self.policy = self.space.get_reinforcement_learning_policy(
          args.rl_learning_rate
      )
      # update policy's parameters
      self.baseline = ExponentialMovingAverage(args.rl_EMA_momentum)
      self.log_prob = 0
  
file_path: singa/examples/model_selection/TRAILS-Database-Native-Model-Selection/internal/ml/model_selection/src/controller/sampler_rl/reinforcement_learning.py
imports: from src.controller.core.sample import Sampler
  from src.search_space.core.space import SpaceWrapper
  from src.search_space.core.model_params import ModelMicroCfg
  from src.third_pkg.models import CellStructure
label_desc: Use image node_id 1 to create a new RLSampler object from inherited base classes: Sampler with example: obj = RLSampler(space, args)