code: def forward(self, input, target, **kwargs):
      added_arguments = OrderedDict()
      for key in self.search_for_args:
          added_arguments[key] = kwargs.get(key, None)
      input, target = filter_valid(input, target)
      return self._loss_func(
          input, target, **added_arguments, **self.special_args
      )
  
imports: from typing import Any
  from collections import OrderedDict
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.autograd import Variable
  from torch_points3d.datasets.segmentation import IGNORE_LABEL
  from .metric_losses import *
label_desc: Use image node_id 2 for calling the LossFactory obj's underlying member method code with example usage: obj.forward(input, target) and returns: self