class_docstr: DiceLoss on binary.
  For SegDetector without adaptive module.
code: def forward(self, pred, batch):
      loss = self.loss(pred["binary"], batch["gt"], batch["mask"])
      return loss, dict(dice_loss=loss)
  
imports: import sys
  import torch
  import torch.nn
label_desc: Use image node_id 2 for calling the BalanceBCELoss obj's underlying member method code with example usage: obj.forward(pred, batch) and returns: loss,  dict