class_docstr: Actor that acts according to the Q-function.
class_docstr_tok: ["Actor","that","acts","according","to","the","Q-function","."]
code: def _evaluate_model_and_update_recurrent_states(self, batch_obs):
      batch_xs = self.batch_states(batch_obs, self.device, self.phi)
      if self.recurrent:
          if self.training:
              self.train_prev_recurrent_states = (
                  self.train_recurrent_states
              )
              batch_av, self.train_recurrent_states = one_step_forward(
                  self.model, batch_xs, self.train_recurrent_states
              )
          else:
              batch_av, self.test_recurrent_states = one_step_forward(
                  self.model, batch_xs, self.test_recurrent_states
              )
      else:
          batch_av = self.model(batch_xs)
      return batch_av
  
file_path: pfrl/pfrl/agents/state_q_function_actor.py
imports: from logging import getLogger
  import torch
  from pfrl import agent
  from pfrl.utils import evaluating
  from pfrl.utils.batch_states import batch_states
  from pfrl.utils.recurrent import get_recurrent_state_at, one_step_forward, recurrent_state_as_numpy
label_desc: Use image node_id 3 for calling the StateQFunctionActor obj's underlying member method code with example usage: obj._evaluate_model_and_update_recurrent_states(batch_obs) and returns: batch_av