code: def check_validation(self):
      for _, ts in self._target_spaces.items():
          for _, target_space in ts.items():
              if target_space.quant_dtype is not None:
                  warn_msg = "BNNQuantizer will only quantize the value to 1 or -1; the quant_dtype value will not work"
                  _logger.warning(warn_msg)
              if target_space._scaler is not None:
                  raise ValueError(
                      "BNNQauntizer doesn't support for granularity, please set it to False"
                  )
  
imports: from __future__ import annotations
  import logging
  from typing import List, Dict, overload
  import torch
  from torch import Tensor
  from ..base.compressor import Compressor, Quantizer
  from ..base.wrapper import ModuleWrapper
  from ..base.target_space import TargetType
  from ..utils import Evaluator, _EVALUATOR_DOCSTRING
label_desc: Use image node_id 5 for calling the BNNQuantizer obj's underlying member method code with example usage: obj.check_validation() without return types