import tensorflow as tf

      (common_image_attention.DistributionType.CAT, None, 256),
  )
  def testPostProcessImageInferMode(self, likelihood, num_mixtures, depth):
    batch = 1
    rows = 8
    cols = 24
    block_length = 4
    block_width = 2
    hparams = tf.contrib.training.HParams(
        block_raster_scan=True,
        hidden_size=2,
        likelihood=likelihood,
        mode=tf.estimator.ModeKeys.PREDICT,
        num_mixtures=num_mixtures,
        query_shape=[block_length, block_width],
    )
