code: def sequential_encoding_layers(self) -> torch.nn.ModuleList:
      return self.__sequential_encoding_layers
  
file_path: AutoGL/autogl/module/model/pyg/graph_saint.py
imports: import typing
  import torch.nn.functional
  from torch_geometric.nn.conv import MessagePassing
  from torch_sparse import SparseTensor, matmul
  from .None import register_model
  from .base import ClassificationModel, ClassificationSupportedSequentialModel
label_desc: Use image node_id 4 for calling the GraphSAINTMultiOrderAggregationModel obj's underlying member method code with example usage: obj.sequential_encoding_layers() and returns: self