code: def _parse_single_video(self, example_proto):
      
      context_features = {
          "game_duration_loops": tf.io.FixedLenFeature([1], tf.int64),
          "game_duration_seconds": tf.io.FixedLenFeature([1], tf.float32),
          "n_steps": tf.io.FixedLenFeature([1], tf.int64),
          "screen_size": tf.io.FixedLenFeature([2], tf.int64),
      }
  
      sequence_features = {
          "rgb_screen": tf.io.FixedLenSequenceFeature([], tf.string),
      }
  
      _, seq_feat = tf.io.parse_single_sequence_example(
          example_proto,
          context_features=context_features,
          sequence_features=sequence_features)
  
      video_frames = tf.map_fn(
          tf.image.decode_png, seq_feat["rgb_screen"], dtype=tf.uint8)
      return video_frames
docs: Parses single video from the input tfrecords.
  
      Args:
        example_proto: tfExample proto with a single video.
  
      Returns:
        dict with all frames, positions and actions.