code: def generate_cluster_labels(
      segment_ranges: List[str], cluster_labels: List[int]
  ):
      """
      Generate cluster (speaker labels) from the segment_range list and cluster label list.
  
      Args:
          segment_ranges (list):
              List containing intervals (start and end timestapms, ranges) of each segment
          cluster_labels (list):
              List containing a cluster label sequence
  
      Returns:
          diar_hyp (list):
              List containing merged speaker-turn-level timestamps and labels in string format
              Example:
                  >>>  diar_hyp = ['0.0 4.375 speaker_1', '4.375 5.125 speaker_0', ...]
  
          lines (list)
              List containing raw segment-level timestamps and labels in raw digits
                  >>>  diar_hyp = ['0.0 0.25 speaker_1', '0.25 0.5 speaker_1', ..., '4.125 4.375 speaker_1']
      """
      lines = []
      for idx, label in enumerate(cluster_labels):
          tag = "speaker_" + str(label)
          stt, end = segment_ranges[idx]
          lines.append(f"{stt} {end} {tag}")
      cont_lines = get_contiguous_stamps(lines)
      diar_hyp = merge_stamps(cont_lines)
      return diar_hyp, lines
  
imports: import gc
  import json
  import math
  import os
  import shutil
  from copy import deepcopy
  from typing import Dict, List, Tuple, Union
  import numpy
  import omegaconf
  import soundfile
  import torch
  from pyannote.core import Annotation, Segment
  from tqdm import tqdm
  from nemo.collections.asr.data.audio_to_label import repeat_signal
  from nemo.collections.asr.parts.utils.longform_clustering import LongFormSpeakerClustering
  from nemo.collections.asr.parts.utils.offline_clustering import SpeakerClustering, get_argmin_mat, split_input_data
  from nemo.utils import logging
label_desc: Use image node_id 16 for calling a global function with example usage: generate_cluster_labels(segment_ranges, cluster_labels) and returns: diar_hyp,  lines