code: def forward(self, x, edge_index):
      x = F.dropout(x, p=0.5, training=self.training)
      x = self.conv1(x, edge_index).relu()
      # Move data to the second device:
      x, edge_index = x.to(self.device2), edge_index.to(self.device2)
      x = F.dropout(x, p=0.5, training=self.training)
      x = self.conv2(x, edge_index)
      return x
  
file_path: pytorch_geometric/examples/multi_gpu/model_parallel.py
imports: import os.path
  import torch
  import torch.nn.functional
  from torch_geometric.datasets import Planetoid
  from torch_geometric.nn import GCNConv
  from torch_geometric.transforms import NormalizeFeatures
label_desc: Use image node_id 2 for calling the GCN obj's underlying member method code with example usage: obj.forward(x, edge_index) and returns: x