class_docstr: Quantized Layer interface
class_docstr_tok: ["Quantized","Layer","interface"]
docstr: hook to be registered to module when exporting the model to 8bit, can be overrided             to customize to layer behaviour
code: def _state_dict_hook(module, state_dict, prefix, local_metadata):
      """hook to be registered to module when exporting the model to 8bit, can be overrided\
               to customize to layer behaviour"""
      if module.mode_8bit and module.mode != QuantizationMode.NONE:
          state_dict.pop(prefix + "weight", None)
          state_dict.pop(prefix + "_step", None)
          state_dict[prefix + "quantized_weight"] = state_dict[
              prefix + "quantized_weight"
          ].char()
      else:
          state_dict.pop(prefix + "quantized_weight", None)
          state_dict.pop(prefix + "_weight_scale", None)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  from enum import Enum, auto
  import logging
  from abc import ABC, abstractmethod
  import torch
  from torch import nn
  from torch.nn import functional
  from nlp_architect.common import Config
label_desc: Use image node_id 12 for calling the QuantizedLayer obj's underlying member method code with example usage: obj._state_dict_hook(module, state_dict, prefix, local_metadata) without return types