code: def sample_action(
      self, scores: GaussianSamplerScore
  ) -> rlt.ActorOutput:
      self.actor_network.eval()
      unscaled_actions, log_prob = self._sample_action(
          scores.loc, scores.scale_log
      )
      self.actor_network.train()
  
      return rlt.ActorOutput(action=unscaled_actions, log_prob=log_prob)
  
file_path: ReAgent/reagent/gym/policies/samplers/continuous_sampler.py
imports: import reagent.core.types
  import torch
  from reagent.gym.types import GaussianSamplerScore, Sampler
label_desc: Use image node_id 3 for calling the GaussianSampler obj's underlying member method code with example usage: obj.sample_action(scores) and returns: rlt