code: def forward(self, x):
      x = self.lin1(x).relu()
      x = self.lin2(x).relu()
      return self.lin3(x)
  
imports: import os.path
  import matplotlib.pyplot
  import torch
  from sklearn.cluster import KMeans
  from sklearn.manifold import TSNE
  from sklearn.metrics.cluster import completeness_score, homogeneity_score, v_measure_score
  from torch.nn import Linear
  import torch_geometric.transforms
  from torch_geometric.datasets import Planetoid
  from torch_geometric.nn import ARGVA, GCNConv
label_desc: Use image node_id 2 for calling the Discriminator obj's underlying member method code with example usage: obj.forward(x) and returns: self