code: def forward(self, graph, x):
      h = th.zeros(1, x.shape[0], self.hid_dim).to(x.device)
      c = th.zeros(1, x.shape[0], self.hid_dim).to(x.device)
  
      x = self.linear1(x)
      h_tmps = []
      for layer in self.breaths:
          h_tmps.append(th.mean(th.tanh(layer(graph, x)), dim=1))
      x = x.unsqueeze(0)
      for h_tmp, layer in zip(h_tmps, self.depths):
          in_cat = th.cat((h_tmp.unsqueeze(0), x), -1)
          x, (h, c) = layer(in_cat, (h, c))
      x = self.linear2(x[0])
  
      return x
  
file_path: dgl/examples/pytorch/geniepath/model.py
imports: import torch
  import torch.nn
  from dgl.nn import GATConv
  from torch.nn import LSTM
label_desc: Use image node_id 2 for calling the GeniePathLazy obj's underlying member method code with example usage: obj.forward(graph, x) and returns: x