code: def forward(self, x):
      # x: (B, 3, H, W)
      out = self.bn(self.conv(x))
      return {"loss": out.sum()}
  
imports: import torch
  from allennlp.data.vocabulary import Vocabulary
  from allennlp.models.model import Model
label_desc: Use image node_id 2 for calling the FakeModelForTestingNormalizationBiasVerification obj's underlying member method code with example usage: obj.forward(x) and returns: dict