code: def main_kd(self, mask_positive, pred_scores, soft_cls, num_classes):
      num_pos = mask_positive.sum()
      if num_pos > 0:
          cls_mask = mask_positive.unsqueeze(-1).tile(
              [1, 1, num_classes]
          )
          pred_scores_pos = paddle.masked_select(
              pred_scores, cls_mask
          ).reshape([-1, num_classes])
          soft_cls_pos = paddle.masked_select(
              soft_cls, cls_mask
          ).reshape([-1, num_classes])
          loss_kd = self.loss_kd(
              pred_scores_pos, soft_cls_pos, avg_factor=num_pos
          )
      else:
          loss_kd = paddle.zeros([1])
      return loss_kd
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from ppdet.core.workspace import register
  from ppdet.modeling import ops
  from ppdet.modeling.losses.iou_loss import GIoULoss
  from ppdet.utils.logger import setup_logger
label_desc: Use image node_id 5 for calling the DistillPPYOLOELoss obj's underlying member method code with example usage: obj.main_kd(mask_positive, pred_scores, soft_cls, num_classes) and returns: loss_kd