code: def get_dtype_bound_value(
      dtype: DtypeLike | torch.dtype,
  ) -> tuple[float, float]:
      """
      Get dtype bound value
      Args:
          dtype: dtype to get bound value
      Returns:
          (bound_min_value, bound_max_value)
      """
      if dtype in UNSUPPORTED_TYPES:
          is_floating_point = False
      else:
          is_floating_point = get_equivalent_dtype(
              dtype, torch.Tensor
          ).is_floating_point
      dtype = get_equivalent_dtype(dtype, np.array)
      if is_floating_point:
          return (np.finfo(dtype).min, np.finfo(dtype).max)  # type: ignore
      else:
          return (np.iinfo(dtype).min, np.iinfo(dtype).max)
  
imports: from __future__ import annotations
  import re
  from collections.abc import Sequence
  from typing import Any
  import numpy
  import torch
  import monai
  from monai.config.type_definitions import DtypeLike, NdarrayTensor
  from monai.utils import optional_import
label_desc: Use image node_id 13 for calling a global function with example usage: get_dtype_bound_value(dtype) and returns: np,  np, np,  np