docs: def _add_loss_summaries(total_loss):
    """Add summaries for losses in CIFAR-10 model.
  
    Generates moving average for all losses and associated summaries for
    visualizing the performance of the network.
  
    Args:
      total_loss: Total loss from loss().
    Returns:
      loss_averages_op: op for generating moving averages of losses.
    """
    # Compute the moving average of all individual losses and the total loss.
    loss_averages = tf.train.ExponentialMovingAverage(0.9, name='avg')
    losses = tf.get_collection('losses')
    loss_averages_op = loss_averages.apply(losses + [total_loss])
  
    # Attach a scalar summary to all individual losses and the total loss; do the
    # same for the averaged version of the losses.
    for l in losses + [total_loss]:
      # Name each loss as '(raw)' and name the moving average version of the loss
      # as the original loss name.
      tf.summary.scalar(l.op.name + ' (raw)', l)
      tf.summary.scalar(l.op.name, loss_averages.average(l))
  
    return loss_averages_op