code: def vq_discrete_unbottleneck(x, hparams):
    
    x_shape = common_layers.shape_list(x)
    bottleneck_size = 2**hparams.bottleneck_bits
    means = hparams.means
    x_flat = tf.reshape(x, [-1, bottleneck_size])
    result = tf.matmul(x_flat, means)
    result = tf.reshape(result, x_shape[:-1] + [hparams.hidden_size])
    return result
docs: Simple undiscretization from vector quantized representation.