class_docstr: Quantized Layer interface
class_docstr_tok: ["Quantized","Layer","interface"]
docstr: function to be called by self.train(mode=False), or eval() which modifies modules             attributes according to the model
code: def _eval(self):
      """function to be called by self.train(mode=False), or eval() which modifies modules\
               attributes according to the model"""
      self._weight_scale = self.weight_scale
      self.quantized_weight = quantize(
          self.weight, self.weight_scale, self.weight_bits
      )
  
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 10 for calling the QuantizedLayer obj's underlying member method code with example usage: obj._eval() without return types