How to use the spleeter.utils.configuration.load_configuration function in spleeter

:param argv: Provided command line arguments.
    """
    try:
        parser = create_argument_parser()
        arguments = parser.parse_args(argv[1:])
        enable_logging()
        if arguments.verbose:
            enable_tensorflow_logging()
        if arguments.command == 'separate':
            from .commands.separate import entrypoint
        elif arguments.command == 'train':
            from .commands.train import entrypoint
        elif arguments.command == 'evaluate':
            from .commands.evaluate import entrypoint
        params = load_configuration(arguments.configuration)
        entrypoint(arguments, params)
    except SpleeterError as e:
        get_logger().error(e)

def __init__(self, params_descriptor, MWF=False):
        """ Default constructor.

        :param params_descriptor: Descriptor for TF params to be used.
        :param MWF: (Optional) True if MWF should be used, False otherwise.
        """
        self._params = load_configuration(params_descriptor)
        self._sample_rate = self._params['sample_rate']
        self._MWF = MWF
        self._predictor = None
        self._pool = Pool()
        self._tasks = []