class_docstr: Distribution Focal Loss (DFL) is a variant of `Generalized Focal Loss:
  Learning Qualified and Distributed Bounding Boxes for Dense Object
  Detection <https://arxiv.org/abs/2006.04388>`_.
  
  Args:
      reduction (str): Options are `'none'`, `'mean'` and `'sum'`.
      loss_weight (float): Loss weight of current loss.
code: def __init__(self, reduction="mean", loss_weight=1.0):
      super(DistributionFocalLoss, self).__init__()
      self.reduction = reduction
      self.loss_weight = loss_weight
  
file_path: insightface/detection/scrfd/mmdet/models/losses/gfocal_loss.py
imports: import torch.nn
  import torch.nn.functional
  from ..builder import LOSSES
  from .utils import weighted_loss
label_desc: Use image node_id 1 to create a new DistributionFocalLoss object from inherited base classes: nn with example: obj = DistributionFocalLoss(reduction, loss_weight)