code: def step(self, observation, **extra_feed):
          
  
          a, v, state, neglogp = self._evaluate([self.action, self.vf, self.state, self.neglogp], observation, **extra_feed)
          if state.size == 0:
              state = None
          return a, v, state, neglogp
docs: Compute next action(s) given the observation(s)
  
          Parameters:
          ----------
  
          observation     observation data (either single or a batch)
  
          **extra_feed    additional data such as state or mask (names of the arguments should match the ones in constructor, see __init__)
  
          Returns:
          -------
          (action, value estimate, next state, negative log likelihood of the action under current policy parameters) tuple