code: def __flow__(self):
      for module in self.model.modules():
          if isinstance(module, MessagePassing):
              return module.flow
      return "source_to_target"
  
imports: from typing import List, Tuple, Dict
  from math import sqrt
  import torch
  from torch import Tensor
  import torch.nn
  import matplotlib.pyplot
  import networkx
  from torch_geometric.nn import MessagePassing
  from torch_geometric.utils.loop import add_self_loops, remove_self_loops
  from torch_geometric.data import Data, Batch
  from torch_geometric.utils import to_networkx
  from ..models.utils import subgraph
  from rdkit import Chem
  from matplotlib.axes import Axes
  import numpy
  from ..models import GNNPool
label_desc: Use image node_id 5 for calling the ExplainerBase obj's underlying member method code with example usage: obj.__flow__() and returns: str, module