code: def forward(self, x, features):
      if self.mode == "cat":
          return torch.cat((x, features), 1)
      if self.mode == "catc":
          return self.reduce_conv(torch.cat((x, features), 1))
      if self.mode == "sum":
          return self.reduce_conv(features) + x
      return x
  
imports: import torch
  import torch.nn
label_desc: Use image node_id 2 for calling the FeaturesConnector obj's underlying member method code with example usage: obj.forward(x, features) and returns: x, torch, self, unknown