code: def __init__(self, emb_dim):
      super(BondEncoder, self).__init__()
  
      self.bond_embedding_list = torch.nn.ModuleList()
  
      for i, dim in enumerate(full_bond_feature_dims):
          emb = torch.nn.Embedding(dim, emb_dim)
          torch.nn.init.xavier_uniform_(emb.weight.data)
          self.bond_embedding_list.append(emb)
  
file_path: GraphGym/graphgym/models/feature_encoder_pyg.py
imports: import torch
  from ogb.utils.features import get_atom_feature_dims, get_bond_feature_dims
  import graphgym.register
label_desc: Use image node_id 1 to create a new BondEncoder object from inherited base classes: torch.nn with example: obj = BondEncoder(emb_dim)