code: def __init__(self, hidden_channels):
      super().__init__()
      self.encoder = GNNEncoder(hidden_channels, hidden_channels)
      self.encoder = to_hetero(
          self.encoder, data.metadata(), aggr="sum"
      )
      self.decoder = EdgeDecoder(hidden_channels)
  
file_path: pytorch_geometric/examples/explain/captum_explainer_hetero_link.py
imports: import os.path
  import torch
  import torch.nn.functional
  from torch.nn import Linear
  import torch_geometric.transforms
  from torch_geometric.datasets import MovieLens
  from torch_geometric.explain import CaptumExplainer, Explainer
  from torch_geometric.nn import SAGEConv, to_hetero
label_desc: Use image node_id 1 to create a new Model object from inherited base classes: torch.nn with example: obj = Model(hidden_channels)