def tf_preprocess(self, states, actions, reward):
<EOL>for name in sorted(self.states_preprocessing):<EOL><INDENT>states[name] = self.states_preprocessing[name].process(tensor=states[name])<EOL><DEDENT>if self.reward_preprocessing is not None:<EOL><INDENT>reward = self.reward_preprocessing.process(tensor=reward)<EOL><DEDENT>return states, actions, reward<EOL>
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.