code: def __init__(self, hidden_size, depth):
      super(JTMPN, self).__init__()
      self.hidden_size = hidden_size
      self.depth = depth
  
      self.W_i = nn.Linear(
          ATOM_FDIM + BOND_FDIM, hidden_size, bias=False
      )
      self.W_h = nn.Linear(hidden_size, hidden_size, bias=False)
      self.W_o = nn.Linear(ATOM_FDIM + hidden_size, hidden_size)
  
file_path: DIG/dig/ggraph/method/JTVAE/fast_jtnn/jtmpn.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  import rdkit.Chem
  from .nnutils import create_var, index_select_ND
label_desc: Use image node_id 1 to create a new JTMPN object from inherited base classes: nn with example: obj = JTMPN(hidden_size, depth)