code: def aggregating_observers(self):
      ret = super().aggregating_observers
      ret.update(
          {
              name: IntervalAggregatingObserver(1, aggregator)
              for name, aggregator in [
                  (
                      f"{key}_tb",
                      agg.TensorBoardHistogramAndMeanAggregator(
                          key, log_key
                      ),
                  )
                  for key, log_key in [
                      ("q1_loss", "loss/q1_loss"),
                      ("actor_loss", "loss/actor_loss"),
                      ("q1_value", "q_value/q1_value"),
                      ("next_q_value", "q_value/next_q_value"),
                      ("target_q_value", "q_value/target_q_value"),
                      ("actor_q1_value", "q_value/actor_q1_value"),
                      ("q2_loss", "loss/q2_loss"),
                      ("q2_value", "q_value/q2_value"),
                  ]
              ]
          }
      )
      return ret
  
imports: import logging
  from reagent.core import aggregators
  from reagent.core.observers import IntervalAggregatingObserver
  from reagent.reporting.actor_critic_reporter import ActorCriticReporter
label_desc: Use image node_id 1 for calling the TD3Reporter obj's underlying member method code with example usage: obj.aggregating_observers() and returns: ret