code: def testQuantizedSaveRestore(self):
      save_path = os.path.join(
          self.get_temp_dir(), "quantized_save_restore"
      )
  
      g = ops.Graph()
      with session.Session(graph=g) as sess:
          a = constant_op.constant(6.0, shape=[1, 1], name="a")
          b = variable_v1.VariableV1(
              constant_op.constant(7.0, shape=[1, 1]), name="b"
          )
          c = math_ops.matmul(a, b, name="matmul")
  
          init_op = variables.global_variables_initializer()
  
          saver = saver_module.Saver({"b": b})
  
          result = quantize_training.do_quantize_training_on_graphdef(
              sess.graph_def, 8
          )
  
      with ops.Graph().as_default() as g, session.Session(
          graph=g
      ) as sess:
          _ = importer.import_graph_def(result, name="")
  
          # Initialize the variable.
          self.evaluate(g.get_operation_by_name(init_op.name))
  
          # Run the graph for one step to assign values to the quantization min/max
          # variables.
          self.evaluate(g.get_tensor_by_name(c.name))
  
          saver.save(sess, save_path)
  
      with ops.Graph().as_default() as g, session.Session(
          graph=g
      ) as sess:
          _ = importer.import_graph_def(result, name="")
  
          # When we restore the saved variabled, the quantization variables should
          # be restored as well.
          saver.restore(sess, save_path)
          self.assertEqual(7.0, sess.run(g.get_tensor_by_name("b:0")))
          self.assertEqual(
              6.0, sess.run(g.get_tensor_by_name("a/Min/Variable:0"))
          )
          self.assertEqual(
              6.0, sess.run(g.get_tensor_by_name("a/Max/Variable:0"))
          )
          self.assertEqual(
              7.0,
              sess.run(g.get_tensor_by_name("b/read/Min/Variable:0")),
          )
          self.assertEqual(
              7.0,
              sess.run(g.get_tensor_by_name("b/read/Max/Variable:0")),
          )
  
file_path: tensorflow-upstream/tensorflow/python/training/quantize_training_test.py
imports: import os
  from tensorflow.python.client import session
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import importer
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import variable_v1
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
  from tensorflow.python.training import quantize_training
  from tensorflow.python.training import saver
label_desc: Use image node_id 2 for calling the PywrapQuantizeTrainingTest obj's underlying member method code with example usage: obj.testQuantizedSaveRestore() without return types