class_docstr: This implements the `Barron loss <https://arxiv.org/pdf/1701.03077.pdf>`_.
code: def forward(self, prediction, target):
      diff = torch.add(prediction, -target)
      loss = self._forward(diff)
      loss = loss.sum(0, keepdim=True)
      if self.size_average:
          loss.div_(prediction.size(0))
      return loss
  
file_path: ClassyVision/classy_vision/losses/barron_loss.py
imports: from typing import Any, Dict
  import torch
  from .None import ClassyLoss, register_loss
label_desc: Use image node_id 3 for calling the BarronLoss obj's underlying member method code with example usage: obj.forward(prediction, target) and returns: loss