code: def lp_encode(self, data):
      x: torch.Tensor = getattr(data, "x")
      for i in range(len(self.__sequential_encoding_layers) - 2):
          x = self.__sequential_encoding_layers[i](
              autogl.data.Data(x, getattr(data, "edge_index"))
          )
      # _GCNLayer(
      #     (_convolution): GCNConv(1433, 128)
      #     (_dropout): Dropout(p=0.0, inplace=False)
      #     )
      # print(self.__sequential_encoding_layers)
      x = self.__sequential_encoding_layers[-2](
          autogl.data.Data(x, getattr(data, "edge_index")),
          enable_activation=False,
      )
      return x
  
imports: import torch
  import torch.nn.functional
  import typing
  from torch_geometric.nn.conv import GCNConv
  import autogl.data
  from .None import register_model
  from .base import BaseAutoModel, activate_func, ClassificationSupportedSequentialModel
  from ....utils import get_logger
label_desc: Use image node_id 7 for calling the GCN obj's underlying member method code with example usage: obj.lp_encode(data) and returns: x