code: def forward_layer(self, layer, graph, x, norm, state):
      if layer == 0:
          if self.drop_input:
              x = self.dropout_fn(x)
          x = self.linears[0](x)
          x = x0 = paddle.nn.ReLU()(x)
          state["x0"] = x0
  
      x = self.dropout_fn(x)
      x = self.mini_gcnii(layer + 1, graph, x, norm, state["x0"])
      x = paddle.nn.ReLU()(x)
  
      if layer == self.num_layers - 1:
          x = self.dropout_fn(x)
          x = self.linears[1](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 4 for calling the GCNII obj's underlying member method code with example usage: obj.forward_layer(layer, graph, x, norm, state) and returns: x