class_docstr: Abstract base class representing a dataset.
code: def in_memory_dataset(cls, x, y, shuffle=None, repeat=True):
      assert x.shape[0] == y.shape[0]
      d = tf.data.Dataset.range(x.shape[0])
      if repeat:
          d = d.repeat()
      if shuffle:
          d = d.shuffle(shuffle)
  
      def lookup(p):
          return x[p], y[p]
  
      d = d.map(lambda i: tf.py_func(lookup, [i], [tf.float32] * 2))
      return d
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import array
  import functools
  import gzip
  import operator
  import os
  import struct
  import tempfile
  import sys
  import warnings
  import numpy
  import tensorflow
  from cleverhans import utils
label_desc: Use image node_id 5 for calling the Dataset obj's underlying member method code with example usage: obj.in_memory_dataset(cls, x, y, shuffle, repeat) and returns: d, x,  y