message: [tfdbg] Fix logic issues in tf v1 mnist example
  The mnist example had been breaking because the placeholders had
  an incorrectly defined shape, and the model was being trained on
  the incorrect dataset.
diff: @@ -126,7 +126,8 @@ def main(_):
  return imgs, labels
  ds_train = tf.data.Dataset.from_tensor_slices(mnist_train)
  - ds_train = ds_train.shuffle(1000).repeat().batch(FLAGS.train_batch_size)
  + ds_train = ds_train.shuffle(
  + 1000, seed=RAND_SEED).repeat().batch(FLAGS.train_batch_size)
  ds_train = ds_train.map(format_example)
  it_train = ds_train.make_initializable_iterator()
  @@ -143,7 +144,8 @@ def main(_):
  handle = tf.placeholder(tf.string, shape=())
  iterator = tf.data.Iterator.from_string_handle(
  - handle, (tf.float32, tf.float32), ((None, IMAGE_SIZE * IMAGE_SIZE), ()))
  + handle, (tf.float32, tf.float32),
  + ((None, IMAGE_SIZE * IMAGE_SIZE), (None, 10)))
  x, y_ = iterator.get_next()
  @@ -224,10 +226,10 @@ def main(_):
  # Add this point, sess is a debug wrapper around the actual Session if
  # FLAGS.debug is true. In that case, calling run() will launch the CLI.
  for i in range(FLAGS.max_steps):
  - acc = sess.run(accuracy, feed_dict={handle: train_handle})
  + acc = sess.run(accuracy, feed_dict={handle: test_handle})
  print("Accuracy at step %d: %s" % (i, acc))
  - sess.run(train_step, feed_dict={handle: test_handle})
  + sess.run(train_step, feed_dict={handle: train_handle})
  if __name__ == "__main__":
  