code: def aggregate_key(self, aggregate_key):
          
          aggregation = self.data_dict[aggregate_key]  # List of dictionaries of numpy arrays/scalars
  
          # Aggregate sub batch data
          data_dict_keys = {y for x in aggregation for y in x.keys()}
  
          for key in data_dict_keys:
              # Just average all the statistics from the loss function
              stacked = np.stack([d[key] for d in aggregation], axis=0)
              self.data_dict[key] = np.mean(stacked, axis=0)
docs: Aggregate values from key and put them into the top-level dictionary