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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 evaluate(model_path: str, stream_name: str, config_path: Optional[str], cl_arguments: Iterable[str], output_root: str) -> None: """ Evaluate the given model on the specified data stream. Configuration is updated by the respective predict.stream_name section, in particular: - hooks section is entirely replaced - model and dataset sections are updated :param model_path: path to the model to be evaluated :param stream_name: data stream name to be evaluated :param config_path: path to the config to be used, if not specified infer the path from ``model_path`` :param cl_arguments: additional command line arguments which will update the configuration :param output_root: output root in which the training directory will be created """

    config = None

    try:
        model_dir = path.dirname(model_path) if not path.isdir(model_path) else model_path
        config_path = find_config(model_dir if config_path is None else config_path)
        config = load_config(config_file=config_path, additional_args=cl_arguments)

        if stream_name == CXF_PREDICT_STREAM and stream_name in config:  # old style ``cxflow predict ...``
            logging.warning('Old style ``predict`` configuration section is deprecated and will not be supported, '
                            'use ``eval.predict`` section instead.')
            config['eval'] = {'predict': config['predict']}

        if 'eval' in config and stream_name in config['eval']:
            update_section = config['eval'][stream_name]
            for subsection in ['dataset', 'model', 'main_loop']:
                if subsection in update_section:
                    config[subsection].update(update_section[subsection])
            if 'hooks' in update_section:
                config['hooks'] = update_section['hooks']
            else:
                logging.warning('Config does not contain `eval.%s.hooks` section. '
                                'No hook will be employed during the evaluation.', stream_name)
                config['hooks'] = []

        validate_config(config)

        logging.debug('\tLoaded config: %s', config)
    except Exception as ex:  # pylint: disable=broad-except
        fallback('Loading config failed', ex)

    run(config=config, output_root=output_root, restore_from=model_path, eval=stream_name)