class_docstr: Generates model graph, each node is created from single or multiple jit trace nodes.
class_docstr_tok: ["Generates","model","graph",",","each","node","is","created","from","single","or","multiple","jit","trace","nodes","."]
code: def __init__(self, model=None, dummy_input=None, traced_model=None):
      super().__init__(model, dummy_input, traced_model)
      self.name_to_node: Dict[str, NodePyOP]
      self.global_count = 0
      self.reused_module = set()
      (
          self.name_to_node,
          self.input_to_node,
          self.output_to_node,
      ) = self._build_graph()
      self._extract_auxiliary_info()
  
imports: import logging
  import queue
  import re
  from collections import defaultdict
  from typing import List, Dict
  import torch
  from torch.utils.tensorboard._pytorch_graph import NodePy, NodePyIO, NodePyOP, GraphPy
label_desc: Use image node_id 1 to create a new TorchModuleGraph object from inherited base classes: TorchGraph with example: obj = TorchModuleGraph(model, dummy_input, traced_model)