code: def image_channel_embeddings_top(body_output,
                                   targets,
                                   model_hparams,
                                   vocab_size):
    
    del targets  # unused arg
    with tf.variable_scope("image_channel_embeddings_bottom"):
      img_len = model_hparams.img_len
      channels = model_hparams.num_channels
      x = tf.layers.dense(
          body_output, 256, use_bias=True, activation=None, name="output_conv")
      x = tf.reshape(x,
                     [-1, img_len, img_len, channels, vocab_size])
      return x
docs: Top transformation for images.