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 = self.learn_pe.run(
          feed=[feed], fetch_list=[self.critic_cost.name]
      )[0]
      self.alg.sync_target(share_vars_parallel_executor=self.learn_pe)
      return critic_cost
  
file_path: PARL/examples/NeurIPS2019-Learn-to-Move-Challenge/opensim_agent.py
imports: import parl
  import numpy
  from parl import layers
  from parl.utils import machine_info
  from paddle import fluid
label_desc: Use image node_id 4 for calling the OpenSimAgent obj's underlying member method code with example usage: obj.learn(obs, act, reward, next_obs, terminal) and returns: critic_cost