code: def forward(self, x, edge_index):
      for i, (conv, skip) in enumerate(zip(self.convs, self.skips)):
          x = conv(x, edge_index) + skip(x)
          if i != self.num_layers - 1:
              x = F.elu(x)
              x = F.dropout(x, p=0.5, training=self.training)
      return x
  
file_path: pytorch_geometric/examples/ogbn_products_gat.py
imports: import os.path
  import torch
  import torch.nn.functional
  from ogb.nodeproppred import Evaluator, PygNodePropPredDataset
  from torch.nn import Linear
  from tqdm import tqdm
  from torch_geometric.loader import NeighborLoader
  from torch_geometric.nn import GATConv
label_desc: Use image node_id 3 for calling the GAT obj's underlying member method code with example usage: obj.forward(x, edge_index) and returns: x