code: def fit_sampler(self, score: float):
      # if it's in Initialize stage, add to the population with random models.
      if len(self.population) < self.population_size:
          model = Model()
          model.arch = self.current_arch_micro
          model.score = score
          self.population.append(model)
          self.population_model_ids.append(self.current_arch_id)
  
      # if it's in mutation stage
      else:
          child = Model()
          child.arch = self.current_arch_micro
          child.score = score
  
          self.population.append(child)
          self.population_model_ids.append(self.current_arch_id)
          # Remove the oldest model.
          self.population.popleft()
          self.population_model_ids.popleft()
  
file_path: singa/examples/model_selection/TRAILS-Database-Native-Model-Selection/internal/ml/model_selection/src/controller/sampler_ea/regularized_ea.py
imports: import collections
  from src.search_space.core.model_params import ModelMicroCfg
  from src.controller.core.sample import Sampler
  import random
  from src.search_space.core.space import SpaceWrapper
label_desc: Use image node_id 3 for calling the RegularizedEASampler obj's underlying member method code with example usage: obj.fit_sampler(score) without return types