code: def forward(self, pred, labels):
      pred = pred.sigmoid()
      total_loss = (
          self.weight1.pow(-2) * cross_entropy_per_image(pred, labels)
          + self.weight2.pow(-2)
          * self.cfg_c
          * dice_loss_per_image(pred, labels)
          + (1 + self.weight1 * self.weight2).log()
      )
  
      return total_loss
  
imports: import torch.nn.functional
  from .utils import *
  from .backbone import *
label_desc: Use image node_id 2 for calling the DRCLoss obj's underlying member method code with example usage: obj.forward(pred, labels) and returns: total_loss