import tensorflow as tf


  locs, scales = tf.map_fn(loop_hyper_deocder, zs, dtype=(tf.float32, tf.float32),
                          parallel_iterations=1, back_prop=False)
  lower_bound = 1e-9# TODO
  scales = tf.maximum(scales, lower_bound)
  print("Hyper Decoder")

  ys = conditional_entropy_model.decompress(y_strings, locs, scales, y_min_v, y_max_v, y_shape)
