code: def forward(self, x, edge_index):
      x = self.lin1(x)
      h = torch.zeros(1, x.shape[0], lstm_hidden, device=x.device)
      c = torch.zeros(1, x.shape[0], lstm_hidden, device=x.device)
      h_tmps = []
      for i, l in enumerate(self.breadths):
          h_tmps.append(self.breadths[i](x, edge_index))
      x = x[None, :]
      for i, l in enumerate(self.depths):
          in_cat = torch.cat((h_tmps[i][None, :], x), -1)
          x, (h, c) = self.depths[i](in_cat, h, c)
      x = self.lin2(x[0])
      return x
  
imports: import argparse
  import os.path
  import time
  import torch
  from sklearn.metrics import f1_score
  from torch_geometric.datasets import PPI
  from torch_geometric.loader import DataLoader
  from torch_geometric.nn import GATConv
label_desc: Use image node_id 2 for calling the GeniePathLazy obj's underlying member method code with example usage: obj.forward(x, edge_index) and returns: x