code: def testCallableLearningRate(self):
      def lr():
          return 0.01
  
      opt = adafactor.AdafactorOptimizer(learning_rate=lr)
      v1 = tf.Variable([1.0, 2.0])
      v2 = tf.Variable([3.0, 4.0])
      with tf.GradientTape() as tape:
          tape.watch([v1, v2])
          loss = v1 * v2
      v1_grad, v2_grad = tape.gradient(loss, [v1, v2])
      opt.apply_gradients(((v1_grad, v1), (v2_grad, v2)))
  
file_path: tensor2tensor/tensor2tensor/utils/adafactor_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from tensor2tensor.utils import adafactor
  import tensorflow
label_desc: Use image node_id 1 for calling the AdafactorTest obj's underlying member method code with example usage: obj.testCallableLearningRate() and returns: int