code: def tf_preprocess(self, states, actions, reward):
          
          # States preprocessing
          for name in sorted(self.states_preprocessing):
              states[name] = self.states_preprocessing[name].process(tensor=states[name])
  
          # Reward preprocessing
          if self.reward_preprocessing is not None:
              reward = self.reward_preprocessing.process(tensor=reward)
  
          return states, actions, reward
docs: Applies preprocessing ops to the raw states/action/reward inputs.
  
          Args:
              states (dict): Dict of raw state tensors.
              actions (dict): Dict or raw action tensors.
              reward: 1D (float) raw rewards tensor.
  
          Returns: The preprocessed versions of the input tensors.