code: def _quant_min_max_bounds_check(quant_min, quant_max, dtype):
      if dtype not in _DTYPE_TO_QVALUE_BOUNDS:
          raise ValueError(f"Unsupported dtype: {dtype}")
      (
          quant_min_lower_bound,
          quant_max_upper_bound,
      ) = _DTYPE_TO_QVALUE_BOUNDS[dtype]
  
      assert quant_min >= quant_min_lower_bound, (
          "quant_min out of bound for dtype, "
          f"quant_min_lower_bound: {quant_min_lower_bound} quant_min: {quant_min}"
      )
  
      assert quant_max <= quant_max_upper_bound, (
          "quant_max out of bound for dtype, "
          f"quant_max_upper_bound: {quant_max_upper_bound} quant_max: {quant_max}"
      )
  
imports: import torch
  from torch.library import Library, impl
  from torch.ao.quantization.utils import determine_qparams, validate_qmin_qmax
  from typing import Tuple
label_desc: Use image node_id 1 for calling a global function with example usage: _quant_min_max_bounds_check(quant_min, quant_max, dtype) without return types