def METHOD_NAME(config):
    """
    Load segmentation checkpoint and re-save it without optimizer (memory footprint is reduced).
    """
    model_builder = get_model_seg_builder(config)
    model = model_builder.build_model()
    compression_state = load_compression_state(config.ckpt_path)
    compression_ctrl, compress_model = create_compressed_model(model, config.nncf_config, compression_state)
    variables = get_variables(compress_model)
    checkpoint = tf.train.Checkpoint(
        variables=variables, compression_state=TFCompressionState(compression_ctrl), step=tf.Variable(0)
    )
    load_and_save_checkpoint(checkpoint, config)