code: def distribution_focal_loss(
      self, pred_corners, target_corners, weight_targets=None
  ):
      target_corners_label = F.softmax(target_corners, axis=-1)
      loss_dfl = F.cross_entropy(
          pred_corners,
          target_corners_label,
          soft_label=True,
          reduction="none",
      )
      loss_dfl = loss_dfl.sum(1)
  
      if weight_targets is not None:
          loss_dfl = loss_dfl * (
              weight_targets.expand([-1, 4]).reshape([-1])
          )
          loss_dfl = loss_dfl.sum(-1) / weight_targets.sum()
      else:
          loss_dfl = loss_dfl.mean(-1)
      return loss_dfl / 4.0
  
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 4 for calling the DistillPPYOLOELoss obj's underlying member method code with example usage: obj.distribution_focal_loss(pred_corners, target_corners, weight_targets) and returns: unknown