code: def get_learning_rate(init_learning_rate, train_batch):
      global_step = tf.train.get_or_create_global_step()
      learning_rate = tf.train.exponential_decay(
          init_learning_rate,
          global_step * train_batch,
          60000,
          0.95,
          staircase=True,
      )
      return learning_rate
  
file_path: attributionpriors/attributionpriors/mnist/mnist_train.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  import numpy
  import tensorflow.contrib.slim
  import datetime
  import mnist_model
  import mnist_reader
  from attributionpriors.ops import AttributionPriorExplainer
label_desc: Use image node_id 4 for calling a global function with example usage: get_learning_rate(init_learning_rate, train_batch) and returns: learning_rate