code: def __init__(self, aggr="add", flow="source_to_target"):
      super(MessagePassing, self).__init__()
  
      self.aggr = aggr
      assert self.aggr in ["add", "mean", "max"]
  
      self.flow = flow
      assert self.flow in ["source_to_target", "target_to_source"]
  
      self.__message_args__ = getargspec(self.message)[0][1:]
      self.__special_args__ = [
          (i, arg)
          for i, arg in enumerate(self.__message_args__)
          if arg in special_args
      ]
      self.__message_args__ = [
          arg
          for arg in self.__message_args__
          if arg not in special_args
      ]
      self.__update_args__ = getargspec(self.update)[0][2:]
  
imports: from torch_geometric.nn import GATConv, GCNConv, ChebConv, SAGEConv, GatedGraphConv, ARMAConv, SGConv
  import torch_geometric.nn
  import torch
  from torch import nn
  import torch.nn.functional
  import inspect
  import sys
  from torch_scatter import scatter_add
  import torch_scatter
  from torch.nn import Parameter
  from torch_geometric.nn.inits import glorot, zeros
  from torch_geometric.utils import remove_self_loops, add_self_loops, add_remaining_self_loops, softmax
label_desc: Use image node_id 1 to create a new MessagePassing object from inherited base classes: torch.nn with example: obj = MessagePassing(aggr, flow)