code: def forward(self, g, inputs):
      h = inputs
      for l in range(self.num_layers):
          h = self.gatv2_layers[l](g, h).flatten(1)
      # output projection
      logits = self.gatv2_layers[-1](g, h).mean(1)
      return logits
  
imports: import torch
  import torch.nn
  from dgl.nn import GATv2Conv
label_desc: Use image node_id 2 for calling the GATv2 obj's underlying member method code with example usage: obj.forward(g, inputs) and returns: logits