code: def forward(self, fsp, fcp):
      fcat = torch.cat([fsp, fcp], dim=1)
      feat = self.convblk(fcat)
      atten = F.avg_pool2d(feat, feat.size()[2:])
      atten = self.conv1(atten)
      atten = self.relu(atten)
      atten = self.conv2(atten)
      atten = self.sigmoid(atten)
      feat_atten = torch.mul(feat, atten)
      feat_out = feat_atten + feat
      return feat_out
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from ParsingResnet import Resnet18
label_desc: Use image node_id 2 for calling the FeatureFusionModule obj's underlying member method code with example usage: obj.forward(fsp, fcp) and returns: feat_out