class_docstr: LeakyDiceLoss on binary,
  MaskL1Loss on thresh,
  DiceLoss on thresh_binary.
code: def forward(self, pred, batch):
      main_loss, metrics = self.main_loss(
          pred["binary"], batch["gt"], batch["mask"]
      )
      thresh_loss = self.thresh_loss(
          pred["thresh_binary"], batch["gt"], batch["mask"]
      )
      l1_loss, l1_metric = self.l1_loss(
          pred["thresh"], batch["thresh_map"], batch["thresh_mask"]
      )
      metrics.update(**l1_metric, thresh_loss=thresh_loss)
      loss = main_loss + thresh_loss + l1_loss * self.l1_scale
      return loss, metrics
  
imports: import sys
  import torch
  import torch.nn
label_desc: Use image node_id 2 for calling the L1LeakyDiceLoss obj's underlying member method code with example usage: obj.forward(pred, batch) and returns: loss,  metrics