code: def criterion(inputs, target):
      losses = [
          F.binary_cross_entropy_with_logits(inputs[i], target)
          for i in range(len(inputs))
      ]
      total_loss = sum(losses)
  
      return total_loss
  
file_path: deep-learning-for-image-processing/pytorch_segmentation/u2net/train_utils/train_and_eval.py
imports: import math
  import torch
  from torch.nn import functional
  import train_utils.distributed_utils
label_desc: Use image node_id 1 for calling a global function with example usage: criterion(inputs, target) and returns: total_loss