code: def forward(self, h):
      h = self.input_drop(h)
  
      h_last = None
  
      for i in range(self.n_layers):
          h = self.linears[i](h)
  
          if self.residual and 0 < i < self.n_layers - 1:
              h += h_last
  
          h_last = h
  
          if i < self.n_layers - 1:
              h = self.norms[i](h)
              h = self.activation(h, inplace=True)
              h = self.dropout(h)
  
      return h
  
file_path: dgl/examples/pytorch/ogb/ogbn-products/gat/models.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from dgl import function
  from dgl.ops import edge_softmax
  from dgl.utils import expand_as_pair
label_desc: Use image node_id 2 for calling the MLP obj's underlying member method code with example usage: obj.forward(h) and returns: h