code: def learn(self, obs, act, reward, next_obs, terminal):
      feed = {
          "obs": obs,
          "act": act,
          "reward": reward,
          "next_obs": next_obs,
          "terminal": terminal,
      }
      [critic_cost, actor_cost] = self.fluid_executor.run(
          self.learn_program,
          feed=feed,
          fetch_list=[self.critic_cost, self.actor_cost],
      )
      self.alg.sync_target()
      return critic_cost[0], actor_cost[0]
  
file_path: PARL/benchmark/fluid/SAC/mujoco_agent.py
imports: import numpy
  import parl
  from parl import layers
  from paddle import fluid
label_desc: Use image node_id 5 for calling the MujocoAgent obj's underlying member method code with example usage: obj.learn(obs, act, reward, next_obs, terminal) and returns: critic_cost,  actor_cost