code: def __init__(self, in_channels, hidden_channels, out_channels):
      super().__init__()
      self.conv1 = GCNConv(in_channels, hidden_channels)
      self.conv2 = GCNConv(hidden_channels, out_channels)
  
file_path: pytorch_geometric/examples/link_pred.py
imports: import os.path
  import torch
  from sklearn.metrics import roc_auc_score
  import torch_geometric.transforms
  from torch_geometric.datasets import Planetoid
  from torch_geometric.nn import GCNConv
  from torch_geometric.utils import negative_sampling
label_desc: Use image node_id 1 to create a new Net object from inherited base classes: torch.nn with example: obj = Net(in_channels, hidden_channels, out_channels)