def build_input_pipeline(x, y, batch_size):
  """
  """
  training_dataset = tf.data.Dataset.from_tensor_slices((x, y))
  training_batches = training_dataset.repeat().batch(batch_size)
  training_iterator = tf.compat.v1.data.make_one_shot_iterator(training_batches)
  batch_features, batch_labels = training_iterator.get_next()
  return batch_features, batch_labels