code: def inputs(train_batch, train_epochs, vald_batch=50, test_batch=50):
      training_iterator = mnist_reader.inputs(
          "train", train_batch, train_epochs
      )
      validation_iterator = mnist_reader.inputs(
          "vald", vald_batch, None
      )
      test_iterator = mnist_reader.inputs("test", test_batch, None)
  
      handle = tf.placeholder(tf.string, shape=[])
      iterator = tf.data.Iterator.from_string_handle(
          handle, (tf.float32, tf.int32), ((None, 28, 28, 1), (None,))
      )
      x, y_ = iterator.get_next()
      return (
          training_iterator,
          validation_iterator,
          test_iterator,
          handle,
          x,
          y_,
      )
  
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 2 for calling a global function with example usage: inputs(train_batch, train_epochs, vald_batch, test_batch) and returns: training_iterator,  validation_iterator,  test_iterator,  handle,  x,  y_