code: def forward(self, inputs, targets):
      loss = self.nll_loss(F.log_softmax(inputs, dim=1), targets)
      return loss.mean(dim=2).mean(dim=1)
  
imports: import math
  import torch.utils.model_zoo
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn.modules.batchnorm import _BatchNorm
  from .None import settings
label_desc: Use image node_id 2 for calling the CrossEntropyLoss2d obj's underlying member method code with example usage: obj.forward(inputs, targets) and returns: loss