How to use the networkml.utils.training_utils.get_labels function in networkml

def test(self, data_dir, save_path):
        # Initialize results dictionary
        results = {}
        results['labels'] = self.conf_labels

        # Get the true label assignments
        self.logger.info('Getting label assignments')
        label_assignments = get_labels(
            'networkml/configs/label_assignments.json', model_labels=self.model.labels)

        if not label_assignments:
            self.logger.warn(
                'Could not read label assignments; continuing anyway.')

        # Walk through testing directory and get all the pcaps
        self.logger.info('Getting pcaps')
        pcaps = get_pcap_paths(data_dir)
        if not pcaps:
            self.logger.error(
                'No pcaps were found in data directory; exiting.')
            return

        # Evaluate the model on each pcap
        file_size = 0

def test(self, data_dir, save_path):
        # Initialize results dictionary
        results = {}
        results['labels'] = self.conf_labels

        # Get the true label assignments
        self.logger.info('Getting label assignments')
        label_assignments = get_labels(
            'networkml/configs/label_assignments.json', model_labels=self.model.labels)
        if not label_assignments:
            self.logger.warn(
                'Could not read label assignments; continuing anyway.')

        # Walk through testing directory and get all the pcaps
        self.logger.info('Getting pcaps')
        pcaps = get_pcap_paths(data_dir)
        if not pcaps:
            self.logger.error(
                'No pcaps were found in data directory; exiting.')
            return

        # Evaluate the model on each pcap
        file_size = 0
        file_num = 0