code: def _mark_strict_experimental(cls):
      def call(self, *args):
          return strict_mode(self, args)
  
      cls.__call__ = call
      return cls
  
file_path: pytorch/torch/_export/wrappers.py
imports: from contextlib import contextmanager
  import torch
  import torch._custom_ops
  from torch._C import DispatchKey
  from torch._higher_order_ops.strict_mode import strict_mode
  from torch._higher_order_ops.utils import autograd_not_implemented
  from torch._ops import HigherOrderOperator
  from torch._subclasses.fake_tensor import FakeTensorMode
  from torch.fx.experimental.proxy_tensor import ProxyTorchDispatchMode, track_tensor_tree
  from torch.utils import _pytree
label_desc: Use image node_id 7 for calling a global function with example usage: _mark_strict_experimental(cls) and returns: cls, strict_mode