code: def hybrid_forward(self, F, x, *args, **kwargs):
      # Do message passing for `num_layers` times with learnable weights.
      for _ in range(self.num_layers):
          if self.use_mlp:
              x = x + self.gnn_layer(x)
              x = F.dot(x.swapaxes(-1, -2), self.adj_matrix).swapaxes(
                  -1, -2
              )
              x = F.relu(x)
          else:
              x = F.dot(x.swapaxes(-1, -2), self.adj_matrix).swapaxes(
                  -1, -2
              )
  
      return x
  
imports: import mxnet
  from gluonts.mx import Tensor
label_desc: Use image node_id 2 for calling the GNN obj's underlying member method code with example usage: obj.hybrid_forward(F, x) and returns: x