code: def mini_gcnii(self, i, graph, x, norm, x0):
      beta_i = np.log(1.0 * self.lambda_l / i + 1)
      if norm is not None:
          x = x * norm
      x = graph.send_recv(x)
      if norm is not None:
          x = x * norm
      x = self.alpha * x0 + (1 - self.alpha) * x
  
      x_transed = self.mlps[i - 1](x)
      x = beta_i * x_transed + (1 - beta_i) * x
      return x
  
file_path: PGL/apps/GNNAutoScale/gnn_models/gcnii.py
imports: import numpy
  import paddle
  import pgl
  import paddle.nn
  from .base_model import ScalableGNN
label_desc: Use image node_id 2 for calling the GCNII obj's underlying member method code with example usage: obj.mini_gcnii(i, graph, x, norm, x0) and returns: x