code: def forward_layer(self, layer, graph, x, norm, state):
      if layer == 0:
          x = self.dropout_fn(x)
          x = self.linears[0](x)
          x = paddle.nn.ReLU()(x)
          x = self.dropout_fn(x)
          x = x0 = self.linears[1](x)
          state["x0"] = x0
  
      if norm is not None:
          x = x * norm
      x = graph.send_recv(x)
      if norm is not None:
          x = x * norm
      x = self.alpha * state["x0"] + (1 - self.alpha) * x
      return x
  
file_path: PGL/apps/GNNAutoScale/gnn_models/appnp.py
imports: import paddle
  import pgl
  import paddle.nn
  from .base_model import ScalableGNN
label_desc: Use image node_id 3 for calling the APPNP obj's underlying member method code with example usage: obj.forward_layer(layer, graph, x, norm, state) and returns: x