code: def reinterpret(tensor, dtype):
      if isinstance(tensor, TensorWrapper):
          if dtype == tensor.base.dtype:
              # Reinterpreting to the original interpretation; return the base.
              return tensor.base
          else:
              # Reinterpreting a wrapped tensor to a different type.
              return TensorWrapper(tensor.base, dtype)
      elif hasattr(tensor, "data_ptr"):
          # A new wrapper is needed around an unwrapped tensor.
          return TensorWrapper(tensor, dtype)
      else:
          raise TypeError(f"Cannot reinterpret a {type(tensor)}.")
  
imports: from __future__ import annotations, division
  import ast
  import hashlib
  import inspect
  import os
  import textwrap
  from collections import defaultdict, namedtuple
  from functools import cached_property
  from typing import Callable, Generic, Iterable, List, Optional, TypeVar, Union, cast, overload
  from ..runtime.driver import driver
label_desc: Use image node_id 5 for calling a global function with example usage: reinterpret(tensor, dtype) and returns: tensor, TensorWrapper, TensorWrapper