code: def learn(
      self,
      obs,
      act,
      reward,
      next_obs,
      terminal,
      actor_lr,
      critic_lr,
      model_id,
  ):
      feed = {
          "obs": obs,
          "act": act,
          "reward": reward,
          "next_obs": next_obs,
          "terminal": terminal,
          "actor_lr": actor_lr,
          "critic_lr": critic_lr,
      }
  
      feed = [feed]
      critic_loss = self.learn_pe[model_id].run(
          feed=feed, fetch_list=self.learn_programs_output[model_id]
      )[0]
      self.alg.sync_target(
          model_id=model_id,
          share_vars_parallel_executor=self.learn_pe[model_id],
      )
      return critic_loss
  
file_path: PARL/examples/NeurIPS2018-AI-for-Prosthetics-Challenge/opensim_agent.py
imports: import numpy
  import re
  import parl
  from parl import layers
  from paddle import fluid
  from paddle.fluid.executor import _fetch_var
  from parl.utils import logger
label_desc: Use image node_id 5 for calling the OpenSimAgent obj's underlying member method code with example usage: obj.learn(obs, act, reward, next_obs, terminal, actor_lr, critic_lr, model_id) and returns: critic_loss