Note:
 This decorator may reduce the performance of your code.
 Generally, it's enough to express your code as a series of
 functions that, themselves, support __torch_function__. If you
 find yourself in the rare situation where this is not the case,
 e.g. if you're wrapping a low-level library and you also need it
 to work for Tensor-likes, then this function is available.

-[ Examples ]-



def dispatcher(a): # Must have the same signature as func
   ...     return (a,)
@torch.overrides.wrap_torch_function(dispatcher)
def func(a): # This will make func dispatchable by torch_function
   ...     return a + 0


