code: def graph(model, args, verbose=False):
      """
      This method processes a PyTorch model and produces a `GraphDef` proto
      that can be logged to TensorBoard.
      Args:
        model (PyTorch module): The model to be parsed.
        args (tuple): input tensor[s] for the model.
        verbose (bool): Whether to print out verbose information while
          processing.
      """
      with torch.onnx.set_training(
          model, False
      ):  # TODO: move outside of torch.onnx?
          try:
              trace = torch.jit.trace(model, args)
              graph = trace.graph
          except RuntimeError as e:
              print(e)
              print("Error occurs, No graph saved")
              raise e
  
      if verbose:
          print(graph)
      return parse(graph, args)
  
imports: from torch.utils.tensorboard._pytorch_graph import GraphPy, NodePyIO, NodePyOP
  import torch
  from .None import transforms
  from collections import abc
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: graph(model, args, verbose) and returns: parse