class_docstr: Applies the provided loss to the list of outputs (or single output) and sums
  up the losses.
code: def forward(self, output, target):
      if torch.is_tensor(output):
          output = [output]
  
      loss = 0
      for pred in output:
          loss += self._loss(pred, target)
  
      return loss
  
file_path: ClassyVision/classy_vision/losses/multi_output_sum_loss.py
imports: from typing import Any, Dict
  import torch
  from .None import build_loss, ClassyLoss, register_loss
label_desc: Use image node_id 3 for calling the MultiOutputSumLoss obj's underlying member method code with example usage: obj.forward(output, target) and returns: loss