class_docstr: The GripNet model.
  
  Args:
      supergraph (SuperGraph): the supergraph.
  
  Reference:
      Xu, H., Sang, S., Bai, P., Li, R., Yang, L. and Lu, H., 2022. GripNet: Graph Information
      Propagation on Supergraph for Heterogeneous Graphs. Pattern Recognition, p.108973.
class_docstr_tok: ["The","GripNet","model",".","Args",":","supergraph","(","SuperGraph",")",":","the","supergraph",".","Reference",":","Xu",",","H.",",","Sang",",","S.",",","Bai",",","P.",",","Li",",","R.",",","Yang",",","L.","and","Lu",",","H.",",","2022",".","GripNet",":","Graph","Information","Propagation","on","Supergraph","for","Heterogeneous","Graphs",".","Pattern","Recognition",",","p.108973","."]
code: def __init_supervertex_module_dict__(self):
      self.supervertex_module_dict: Dict[str, torch.nn.ModuleList] = {}
      for supervertex_name in self.supergraph.topological_order:
          supervertex = self.supergraph.supervertex_dict[
              supervertex_name
          ]
          setting = self.supergraph.supervertex_setting_dict[
              supervertex_name
          ]
          self.__init_module_supervertex__(supervertex, setting)
  
imports: import logging
  from typing import Dict
  import torch
  import torch.nn.functional
  from torch.nn import Module
  from kale.embed.gcn import GCNEncoderLayer, RGCNEncoderLayer
  from kale.prepdata.supergraph_construct import SuperGraph, SuperVertex, SuperVertexParaSetting
label_desc: Use image node_id 3 for calling the GripNet obj's underlying member method code with example usage: obj.__init_supervertex_module_dict__() without return types