class_docstr: Generates model graph, each node is created from single or multiple jit trace nodes.
docstr: Find successor nodes of the given node
  
  Parameters
  ----------
  unique_name : str
      The unique name of the node
  
  Returns
  -------
  list
      a list of nodes who are the given node's successor
code: def find_successors(self, unique_name):
      """
      Find successor nodes of the given node
  
      Parameters
      ----------
      unique_name : str
          The unique name of the node
  
      Returns
      -------
      list
          a list of nodes who are the given node's successor
      """
      successors = []
      for output in self.name_to_node[unique_name].outputs:
          if output not in self.input_to_node:
              # may reach the output of the whole graph
              continue
          nodes_py = self.input_to_node[output]
          for node_py in nodes_py:
              successors.append(node_py.unique_name)
      return successors
  
imports: import logging
  import queue
  import re
  from collections import defaultdict
  import torch
  from torch.utils.tensorboard._pytorch_graph import NodePy, NodePyIO, NodePyOP, GraphPy
label_desc: Use image node_id 15 for calling the TorchModuleGraph obj's underlying member method code with example usage: obj.find_successors(unique_name) and returns: successors