code: def video_l1_top(body_output, targets, model_hparams, vocab_size):
    
    del targets, vocab_size  # unused arg
    num_channels = model_hparams.problem.num_channels
    num_frames = model_hparams.video_num_target_frames
    with tf.variable_scope("rgb"):
      body_output_shape = common_layers.shape_list(body_output)
      res = tf.layers.dense(body_output, num_channels * num_frames, name="cast")
      res = tf.reshape(res, body_output_shape[:3] + [num_channels, num_frames])
      res = tf.transpose(res, [0, 4, 1, 2, 3])  # Move frames next to batch.
      if not tf.get_variable_scope().reuse:
        res_argmax = res[:, -1, :, :, :]
        tf.summary.image(
            "result",
            common_layers.tpu_safe_image_summary(res_argmax),
            max_outputs=1)
      return tf.expand_dims(res, axis=-1)
docs: Top transformation for video.