code: def forward(self, data):
      x = data["graph"].ndata["feat"]
      graph = data["graph"]
      x = self.linear_pre(x)
      x_position, x = self.conv_first(
          graph, x, data["anchor_eid"], data["dists_max"]
      )
  
      x = self.dropout(x)
      x_position, x = self.conv_out(
          graph, x, data["anchor_eid"], data["dists_max"]
      )
      x_position = F.normalize(x_position, p=2, dim=-1)
      return x_position
  
file_path: dgl/examples/pytorch/P-GNN/model.py
imports: import dgl.function
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the PGNN obj's underlying member method code with example usage: obj.forward(data) and returns: x_position