code: def _patch_difflib_sequence_matcher_init():
      """Context patching `difflib.SequenceMatcher` for fx readable graph.
  
      Under this context, the `autojunk` argument of `difflib.SequenceMatcher` will always
      be considered as `False`. This is to prevent `difflib.SequenceMatcher` recognizing
      stacktrace messages in fx readable graph as junk, as these messages tend to be long (>200)
      and repeat multiple times, which falls under the junk filter criteria.
  
      `difflib.SequenceMatcher` is used underneath by all sorts of diffing functions
      in `difflib`, including `difflib.unified_diff`, `difflib.ndiff`, `difflib.context_diff`.
      Unfortunately, there is no way to pass `autojunk` argument to these functions, and
      they all default to `True`. This context patching will affect all of them.
  
      `Reference: Automatic junk heuristic <https://docs.python.org/3/library/difflib.html>`_
      """
      original_init = difflib.SequenceMatcher.__init__
  
      def patched_init(self, isjunk=None, a="", b="", autojunk=True):
          original_init(self, isjunk, a, b, autojunk=False)
  
      difflib.SequenceMatcher.__init__ = patched_init  # type: ignore[assignment]
      try:
          yield
      finally:
          difflib.SequenceMatcher.__init__ = original_init
  
imports: from __future__ import annotations
  import abc
  import contextlib
  import dataclasses
  import difflib
  import io
  import logging
  import sys
  from typing import Any, Callable, Optional, Tuple
  import torch
  import torch.fx
  from torch._subclasses import fake_tensor
  from torch.fx.experimental.proxy_tensor import maybe_disable_fake_tensor_mode
  from torch.onnx._internal import _beartype
  from torch.onnx._internal.fx import diagnostics, onnxfunction_dispatcher
label_desc: Use image node_id 1 for calling a global function with example usage: _patch_difflib_sequence_matcher_init() without return types