code: def forward(self, g, inputs):
      h = inputs
      for i, layer in enumerate(self.gat_layers):
          h = layer(g, h)
          if i == 1:  # last layer
              h = h.mean(1)
          else:  # other layer(s)
              h = h.flatten(1)
      return h
  
file_path: dgl/examples/pytorch/gat/train.py
imports: import argparse
  import dgl
  import dgl.nn
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl import AddSelfLoop
  from dgl.data import CiteseerGraphDataset, CoraGraphDataset, PubmedGraphDataset
label_desc: Use image node_id 2 for calling the GAT obj's underlying member method code with example usage: obj.forward(g, inputs) and returns: h