TensorFlow > link > mnist.train.next_batch()の定義 @ github

mnist_with_summaries.py
にある以下の定義。

xs, ys = mnist.train.next_batch(100, fake_data=FLAGS.fake_data)

QMCを組込むにはこのあたりを改変する必要がある。
関連 http://qiita.com/7of9/items/f9e243d23240c3316f28

githubでは以下でnext_batch()のdefを見つけた。
tensorflow/tensorflow/contrib/learn/python/learn/datasets/mnist.py
https://github.com/tensorflow/tensorflow/blob/754048a0453a04a761e112ae5d99c149eb9910dd/tensorflow/contrib/learn/python/learn/datasets/mnist.py

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] * 784
      if self.one_hot:
        fake_label = [1] + [0] * 9
      else:
        fake_label = 0
      return [fake_image for _ in xrange(batch_size)], [
          fake_label for _ in xrange(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]

fake_dataでない時はstartとendを計算して、tupleで返している。