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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _parse_single_video(self, example_proto):
 """Parses single video from the input tfrecords. Args: example_proto: tfExample proto with a single video. Returns: dict with all frames, positions and actions. """

    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