class_docstr: GaussianFocalLoss is a variant of focal loss.
  
  More details can be found in the `paper
  <https://arxiv.org/abs/1808.01244>`_
  Code is modified from `kp_utils.py
  <https://github.com/princeton-vl/CornerNet/blob/master/models/py_utils/kp_utils.py#L152>`_  # noqa: E501
  Please notice that the target in GaussianFocalLoss is a gaussian heatmap,
  not 0/1 binary target.
  
  Args:
      alpha (float): Power of prediction.
      gamma (float): Power of target for negtive samples.
      reduction (str): Options are "none", "mean" and "sum".
      loss_weight (float): Loss weight of current loss.
code: def __init__(
      self, alpha=2.0, gamma=4.0, reduction="mean", loss_weight=1.0
  ):
      super(GaussianFocalLoss, self).__init__()
      self.alpha = alpha
      self.gamma = gamma
      self.reduction = reduction
      self.loss_weight = loss_weight
  
file_path: insightface/detection/scrfd/mmdet/models/losses/gaussian_focal_loss.py
imports: import torch.nn
  from ..builder import LOSSES
  from .utils import weighted_loss
label_desc: Use image node_id 1 to create a new GaussianFocalLoss object from inherited base classes: nn with example: obj = GaussianFocalLoss(alpha, gamma, reduction, loss_weight)