code: def _actor_learn(self, obs):
      act, log_pi = self.sample(obs)
      q1_pi, q2_pi = self.model.value(obs, act)
      min_q_pi = paddle.minimum(q1_pi, q2_pi)
      actor_loss = ((self.alpha * log_pi) - min_q_pi).mean()
  
      self.actor_optimizer.clear_grad()
      actor_loss.backward()
      self.actor_optimizer.step()
      return actor_loss
  
file_path: PARL/parl/algorithms/paddle/oac.py
imports: import parl
  import paddle
  from paddle.distribution import Normal
  import paddle.nn.functional
  from parl.utils.utils import check_model_method
  from copy import deepcopy
  import math
label_desc: Use image node_id 7 for calling the OAC obj's underlying member method code with example usage: obj._actor_learn(obs) and returns: actor_loss