def METHOD_NAME(predictor_params: networks_lib.Params,
                       target_params: networks_lib.Params,
                       transitions: types.Transition,
                       networks: RNDNetworks) -> jnp.ndarray:
  """Computes the intrinsic RND reward for a given transition.
  Args:
    predictor_params: Parameters of the predictor network.
    target_params: Parameters of the target network.
    transitions: The sample to compute rewards for.
    networks: RND networks
  Returns:
    The rewards as an ndarray.
  """
  target_output = networks.target.apply(target_params, transitions.observation,
                                        transitions.action)
  predictor_output = networks.predictor.apply(predictor_params,
                                              transitions.observation,
                                              transitions.action)
  return networks.get_reward(predictor_output, target_output,
                             transitions.reward)