code: def _not_requiring_metadata(ret):
      return isinstance(
          ret,
          (
              int,
              str,
              bytes,
              torch.Size,
              torch.dtype,
              torch.device,
              np.ndarray,
          ),
      ) or not (
          isinstance(ret, MetaTensor)
          or (
              isinstance(ret, Sequence)
              and any(isinstance(x, MetaTensor) for x in ret)
          )
      )
  
imports: from __future__ import annotations
  import functools
  import warnings
  from copy import deepcopy
  from typing import Any, Sequence
  import numpy
  import torch
  import monai
  from monai.config.type_definitions import NdarrayTensor
  from monai.data.meta_obj import MetaObj, get_track_meta
  from monai.data.utils import affine_to_spacing, decollate_batch, list_data_collate, remove_extra_metadata
  from monai.utils import look_up_option
  from monai.utils.enums import LazyAttr, MetaKeys, PostFix, SpaceKeys
  from monai.utils.type_conversion import convert_data_type, convert_to_dst_type, convert_to_numpy, convert_to_tensor
label_desc: Use image node_id 2 for calling a global function with example usage: _not_requiring_metadata(ret) and returns: unknown