code: def degree_norm(self, g):
      degree = g.indegree() + 1  # self loop
      norm = paddle.cast(degree, dtype=paddle.get_default_dtype())
      norm = paddle.clip(norm, min=1.0)
      norm = paddle.pow(norm, -0.5)
      norm = paddle.reshape(norm, [-1, 1])
      return norm
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  import pgl
  import pgl.nn
  from pgl.nn import functional
  from mol_encoder import AtomEncoder, BondEncoder
label_desc: Use image node_id 3 for calling the ClassifierNetwork obj's underlying member method code with example usage: obj.degree_norm(g) and returns: norm