code: def _initialize_edge_repr(self, g, src_list, dest_list):
      # For untyped edges, we only add 1 to indicate its existence.
      # For multiple edge types, we can use a one hot representation
      # or an embedding module.
      edge_repr = torch.ones(len(src_list), 1)
      g.edges[src_list, dest_list].data["he"] = edge_repr
  
imports: from functools import partial
  import dgl
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.distributions import Bernoulli, Categorical
label_desc: Use image node_id 2 for calling the ChooseDestAndUpdate obj's underlying member method code with example usage: obj._initialize_edge_repr(g, src_list, dest_list) without return types