docstr: Return the next `batch_size` examples from this data set.
docstr_tok: ["Return","the","next","`","batch_size","`","examples","from","this","data","set","."]
code: def next_batch(self, batch_size, fake_data=False):
      """Return the next `batch_size` examples from this data set."""
      if fake_data:
          fake_image = [1.0 for _ in range(784)]
          fake_label = 0
          return [fake_image for _ in range(batch_size)], [
              fake_label for _ in range(batch_size)
          ]
      start = self._index_in_epoch
      self._index_in_epoch += batch_size
      if self._index_in_epoch > self._num_examples:
          # Finished epoch
          self._epochs_completed += 1
          # Shuffle the data
          perm = numpy.arange(self._num_examples)
          numpy.random.shuffle(perm)
          self._images = self._images[perm]
          self._labels = self._labels[perm]
          # Start next epoch
          start = 0
          self._index_in_epoch = batch_size
          assert batch_size <= self._num_examples
      end = self._index_in_epoch
      return self._images[start:end], self._labels[start:end]
  
file_path: tflearn/tflearn/datasets/fashion_mnist.py
imports: from __future__ import print_function
  import gzip
  import os
  from six.moves import urllib
  import numpy
label_desc: Use image node_id 6 for calling the DataSet obj's underlying member method code with example usage: obj.next_batch(batch_size, fake_data) and returns: self,  self, unknown,  unknown