code: def __init__(self, in_channels, hidden_channels, out_channels):
      super().__init__()
      self.conv1 = SAGEConv(in_channels, hidden_channels)
      self.conv2 = SAGEConv(hidden_channels, hidden_channels)
      self.conv3 = SAGEConv(hidden_channels, hidden_channels)
      self.lin = torch.nn.Linear(2 * hidden_channels, out_channels)
  
file_path: pytorch_geometric/examples/shadow.py
imports: import os.path
  import torch
  import torch.nn.functional
  from torch_geometric.datasets import Flickr
  from torch_geometric.loader import ShaDowKHopSampler
  from torch_geometric.nn import SAGEConv, global_mean_pool
label_desc: Use image node_id 1 to create a new GNN object from inherited base classes: torch.nn with example: obj = GNN(in_channels, hidden_channels, out_channels)