code: def forward_layer(self, layer, graph, x, norm, state):
      if layer == 0:
          if self.drop_input:
              x = self.dropout_fn(x)
  
      h = self.convs[layer](graph, x, norm)
  
      if layer < self.num_layers - 1:
          h = paddle.nn.ReLU()(h)
  
      return h
  
file_path: PGL/apps/GNNAutoScale/gnn_models/gcn.py
imports: import paddle
  import pgl
  import paddle.nn
  from .base_model import ScalableGNN
label_desc: Use image node_id 3 for calling the GCN obj's underlying member method code with example usage: obj.forward_layer(layer, graph, x, norm, state) and returns: h