code: def swap_tensors(t1, t2):
      """
      This function swaps the content of the two Tensor objects.
      At a high level, this will make t1 have the content of t2 while preserving
      its identity.
  
      This will not work if t1 and t2 have different slots.
      """
      # Ensure there are no weakrefs
      if weakref.getweakrefs(t1):
          raise RuntimeError(
              "Cannot swap t1 because it has weakref associated with it"
          )
      if weakref.getweakrefs(t2):
          raise RuntimeError(
              "Cannot swap t2 because it has weakref associated with it"
          )
      t1_slots = set(copyreg._slotnames(t1.__class__))  # type: ignore[attr-defined]
      t2_slots = set(copyreg._slotnames(t2.__class__))  # type: ignore[attr-defined]
      if t1_slots != t2_slots:
          raise RuntimeError(
              "Cannot swap t1 and t2 if they have different slots"
          )
  
      def swap_attr(name):
          tmp = getattr(t1, name)
          setattr(t1, name, (getattr(t2, name)))
          setattr(t2, name, tmp)
  
      # Swap the types
      # Note that this will fail if there are mismatched slots
      swap_attr("__class__")
  
      # Swap the dynamic attributes
      swap_attr("__dict__")
  
      # Swap the slots
      for slot in t1_slots:
          if hasattr(t1, slot) and hasattr(t2, slot):
              swap_attr(slot)
          elif hasattr(t1, slot):
              setattr(t2, slot, (getattr(t1, slot)))
              delattr(t1, slot)
          elif hasattr(t2, slot):
              setattr(t1, slot, (getattr(t2, slot)))
              delattr(t2, slot)
  
      # Swap the at::Tensor they point to
      torch._C._swap_tensor_impl(t1, t2)
  
file_path: pytorch/torch/utils/__init__.py
imports: import os.path
  import torch
  from .throughput_benchmark import ThroughputBenchmark
  from .cpp_backtrace import get_cpp_backtrace
  from .backend_registration import rename_privateuse1_backend, generate_methods_for_privateuse1_backend
  from .None import deterministic
  from .None import collect_env
  import weakref
  import copyreg
label_desc: Use image node_id 2 for calling a global function with example usage: swap_tensors(t1, t2) without return types