code: def _engine_run_backward(t_outputs, *args, **kwargs):
      attach_logging_hooks = log.getEffectiveLevel() <= logging.DEBUG
      if attach_logging_hooks:
          unregister_hooks = _register_logging_hooks_on_whole_graph(
              t_outputs
          )
      try:
          return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
              t_outputs, *args, **kwargs
          )  # Calls into the C++ engine to run the backward pass
      finally:
          if attach_logging_hooks:
              unregister_hooks()
  
imports: import abc
  import collections
  import contextlib
  import logging
  import weakref
  from collections import defaultdict, namedtuple
  from typing import Any, Callable, Deque, Dict, List, Optional, Sequence, Set, Tuple
  import torch
  from torch.autograd.variable import Variable
  from torch.utils._python_dispatch import TorchDispatchMode
  from torch.utils.hooks import RemovableHandle
label_desc: Use image node_id 10 for calling a global function with example usage: _engine_run_backward(t_outputs) and returns: Variable