code: def __torch_function__(cls, func, types, args=(), kwargs=None):
      if kwargs is None:
          kwargs = {}
      # Find an instance of this class in the arguments
      args_of_this_cls = []
      for a in args:
          if isinstance(a, cls):
              args_of_this_cls.append(a)
          elif isinstance(a, collections.abc.Sequence):
              args_of_this_cls.extend(
                  el for el in a if isinstance(el, cls)
              )
      # assert len(args_of_this_cls) > 0
      for a in args_of_this_cls:
          a.used_calls.add(func)
      args = unwrap(tuple(args))
      kwargs = {k: unwrap(v) for k, v in kwargs.items()}
  
      return wrap(func(*args, **kwargs), cls)
  
imports: import collections
  import torch
  from torch import Tensor
label_desc: Use image node_id 10 for calling the TensorWrapper obj's underlying member method code with example usage: obj.__torch_function__(cls, func, types, args, kwargs) and returns: wrap