code: def printable_node(
      node: NodeProto, prefix: str = "", subgraphs: bool = False
  ) -> Union[str, Tuple[str, List[GraphProto]]]:
      content = []
      if len(node.output):
          content.append(
              ", ".join([f"%{name}" for name in node.output])
          )
          content.append("=")
      # To deal with nested graphs
      graphs: List[GraphProto] = []
      printed_attrs = []
      for attr in node.attribute:
          if subgraphs:
              printed_attr_subgraphs = printable_attribute(
                  attr, subgraphs
              )
              if not isinstance(printed_attr_subgraphs[1], list):
                  raise TypeError(
                      f"printed_attr_subgraphs[1] must be an instance of {list}."
                  )
              graphs.extend(printed_attr_subgraphs[1])
              printed_attrs.append(printed_attr_subgraphs[0])
          else:
              printed = printable_attribute(attr)
              if not isinstance(printed, str):
                  raise TypeError(
                      f"printed must be an instance of {str}."
                  )
              printed_attrs.append(printed)
      printed_attributes = ", ".join(sorted(printed_attrs))
      printed_inputs = ", ".join([f"%{name}" for name in node.input])
      if node.attribute:
          content.append(
              f"{node.op_type}[{printed_attributes}]({printed_inputs})"
          )
      else:
          content.append(f"{node.op_type}({printed_inputs})")
      if subgraphs:
          return prefix + " ".join(content), graphs
      return prefix + " ".join(content)
  
imports: import collections.abc
  import numbers
  import struct
  from cmath import isnan
  from typing import Any, Callable, Dict, KeysView, List, Optional, Sequence, Tuple, TypeVar, Union, cast
  import google.protobuf.message
  import numpy
  from onnx import IR_VERSION, AttributeProto, FunctionProto, GraphProto, MapProto, ModelProto, NodeProto, OperatorSetIdProto, OptionalProto, SequenceProto, SparseTensorProto, TensorProto, TensorShapeProto, TrainingInfoProto, TypeProto, ValueInfoProto, defs, mapping
label_desc: Use image node_id 40 for calling a global function with example usage: printable_node(node, prefix, subgraphs) and returns: unknown, unknown,  graphs