class_docstr: A class that enables online (streaming) clustering based diarization.
  
  - The instance created from `OnlineClusteringDiarizer` sets aside a certain amount of memory
    to provide the upcoming inference with history information
  
  - There are two major modules involved: `OnlineSegmentor` and `OnlineSpeakerClustering`.
      OnlineSegmentor: Take the VAD-timestamps and generate segments for each scale
      OnlineSpeakerClustering: Update the entire speaker labels of the given online session
                               while updating the speaker labels of the streaming inputs.
  
  - The overall diarization process is done by calling `diarize_step` function.
    `diarize_step` function goes through the following steps:
      (1) Segmentation (`OnlineSegmentor` class)
      (2) Embedding extraction (`_extract_online_embeddings` function call)
      (3) Online speaker counting and speaker clustering (`OnlineClusteringDiarizer` class)
      (4) Label generation (`generate_cluster_labels` function call)
docstr: Initialize an online segmentor module
  
  Attributes:
      online_segmentor (OnlineSegmentor):
          online segmentation module that generates short speech segments from the VAD input
docstr_tok: ["Initialize","an","online","segmentor","module","Attributes",":","online_segmentor","(","OnlineSegmentor",")",":","online","segmentation","module","that","generates","short","speech","segments","from","the","VAD","input"]
code: def _init_online_segmentor_module(self, sample_rate):
      """
      Initialize an online segmentor module
  
      Attributes:
          online_segmentor (OnlineSegmentor):
              online segmentation module that generates short speech segments from the VAD input
      """
      self.online_segmentor = OnlineSegmentor(sample_rate)
  
imports: import os
  import time
  from copy import deepcopy
  from typing import Dict
  import torch
  from omegaconf import DictConfig
  from nemo.collections.asr.models import ClusteringDiarizer
  from nemo.collections.asr.parts.utils.offline_clustering import get_scale_interpolated_embs, split_input_data
  from nemo.collections.asr.parts.utils.online_clustering import OnlineSpeakerClustering
  from nemo.collections.asr.parts.utils.speaker_utils import OnlineSegmentor, audio_rttm_map, generate_cluster_labels, get_embs_and_timestamps
  from nemo.utils import logging, model_utils
label_desc: Use image node_id 3 for calling the OnlineClusteringDiarizer obj's underlying member method code with example usage: obj._init_online_segmentor_module(sample_rate) without return types