code: def add_quatization_variables(model):
      """Add to graph quantization variables"""
      with model.graph.as_default():
          for tsr in tf.trainable_variables():
              with tf.variable_scope(tsr.name.split(":")[0]):
                  output, min_range, max_range = tf.quantize(
                      tsr,
                      tf.reduce_min(tsr),
                      tf.reduce_max(tsr),
                      tf.qint8,
                      mode="SCALED",
                  )
                  tf.get_variable(
                      "quantized",
                      initializer=output,
                      trainable=False,
                      collections=[_QUANTIZATION_COLLECTION],
                  )
                  tf.get_variable(
                      "min_range",
                      initializer=min_range,
                      trainable=False,
                      collections=[_QUANTIZATION_COLLECTION],
                  )
                  tf.get_variable(
                      "max_range",
                      initializer=max_range,
                      trainable=False,
                      collections=[_QUANTIZATION_COLLECTION],
                  )
  
imports: from __future__ import print_function
  import collections
  import os
  import time
  import numpy
  import six
  import tensorflow
  from tensorflow.python.ops import lookup_ops
  from .utils import misc_utils, vocab_utils, iterator_utils
label_desc: Use image node_id 17 for calling a global function with example usage: add_quatization_variables(model) without return types