code: def forward(self, graph, feature):
      norm = GF.degree_norm(graph)
      output = feature * norm
      output = graph.send_recv(output, "sum")
      output = output * norm
      return output
  
imports: import paddle
  import paddle.nn
  from dataloader import BasicDataset
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  import pgl
  from pgl.nn import functional
  from tqdm import tqdm
label_desc: Use image node_id 2 for calling the LightGCNConv obj's underlying member method code with example usage: obj.forward(graph, feature) and returns: output