class_docstr: Smooth L1 loss.
  
  Args:
      beta (float, optional): The threshold in the piecewise function.
          Defaults to 1.0.
      reduction (str, optional): The method to reduce the loss.
          Options are "none", "mean" and "sum". Defaults to "mean".
      loss_weight (float, optional): The weight of loss.
code: def __init__(self, beta=1.0, reduction="mean", loss_weight=1.0):
      super(SmoothL1Loss, self).__init__()
      self.beta = beta
      self.reduction = reduction
      self.loss_weight = loss_weight
  
file_path: insightface/detection/scrfd/mmdet/models/losses/smooth_l1_loss.py
imports: import torch
  import torch.nn
  from ..builder import LOSSES
  from .utils import weighted_loss
label_desc: Use image node_id 1 to create a new SmoothL1Loss object from inherited base classes: nn with example: obj = SmoothL1Loss(beta, reduction, loss_weight)