import tensorflow as tf

      for i in range(hparams.num_compress_steps):
        with tf.variable_scope("latent_downstride%d" % i):
          x = common_layers.make_even_size(x)
          if i < hparams.filter_double_steps:
            filters *= 2
          x = common_attention.add_timing_signal_nd(x)
          x = tf.layers.conv2d(x, filters, kernel,
                               activation=common_layers.belu,
                               strides=(2, 2), padding="SAME")
          x = common_layers.layer_norm(x)
    else:
      x = common_layers.double_discriminator(x)
