code: def _check_padding_mode_arg(
      padding_mode: Literal["constant", "edge", "reflect", "symmetric"]
  ) -> None:
      if padding_mode not in [
          "constant",
          "edge",
          "reflect",
          "symmetric",
      ]:
          raise ValueError(
              "Padding mode should be either constant, edge, reflect or symmetric"
          )
  
imports: from __future__ import annotations
  import collections.abc
  import numbers
  from contextlib import suppress
  from typing import Any, Callable, Dict, List, Literal, Optional, Sequence, Tuple, Type, Union
  import PIL.Image
  import torch
  from torchvision import tv_tensors
  from torchvision._utils import sequence_to_str
  from torchvision.transforms.transforms import _check_sequence_input, _setup_angle, _setup_size
  from torchvision.transforms.v2.functional import get_dimensions, get_size, is_pure_tensor
  from torchvision.transforms.v2.functional._utils import _FillType, _FillTypeJIT
label_desc: Use image node_id 7 for calling a global function with example usage: _check_padding_mode_arg(padding_mode) without return types