code: def forward(self, features, corrupt=False):
      if corrupt:
          perm = torch.randperm(self.g.num_nodes())
          features = features[perm]
      features = self.conv(features)
      return features
  
imports: import math
  import torch
  import torch.nn
  from gcn import GCN
label_desc: Use image node_id 2 for calling the Encoder obj's underlying member method code with example usage: obj.forward(features, corrupt) and returns: features