code: def get_overlap_stamps(
      cont_stamps: List[str], ovl_spk_idx: List[str]
  ):
      """
      Generate timestamps that include overlap speech. Overlap-including timestamps are created based on the segments that are
      created for clustering diarizer. Overlap speech is assigned to the existing speech segments in `cont_stamps`.
  
      Args:
          cont_stamps (list):
              Non-overlapping (single speaker per segment) diarization output in string format.
              Each line contains the start and end time of segments and corresponding speaker labels.
          ovl_spk_idx (list):
              List containing segment index of the estimated overlapped speech. The start and end of segments are based on the
              single-speaker (i.e., non-overlap-aware) RTTM generation.
      Returns:
          total_ovl_cont_list (list):
              Rendered diarization output in string format. Each line contains the start and end time of segments and
              corresponding speaker labels. This format is identical to `cont_stamps`.
      """
      ovl_spk_cont_list = [[] for _ in range(len(ovl_spk_idx))]
      for spk_idx in range(len(ovl_spk_idx)):
          for idx, cont_a_line in enumerate(cont_stamps):
              start, end, speaker = cont_a_line.split()
              if idx in ovl_spk_idx[spk_idx]:
                  ovl_spk_cont_list[spk_idx].append(
                      f"{start} {end} speaker_{spk_idx}"
                  )
      total_ovl_cont_list = []
      for ovl_cont_list in ovl_spk_cont_list:
          if len(ovl_cont_list) > 0:
              total_ovl_cont_list.extend(merge_stamps(ovl_cont_list))
      return total_ovl_cont_list
  
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 41 for calling a global function with example usage: get_overlap_stamps(cont_stamps, ovl_spk_idx) and returns: total_ovl_cont_list