code: def prepare_subset_json(full_meta_data, rec_id, out_meta_file):
      """Prepares metadata for a given recording ID.
  
      Arguments
      ---------
      full_meta_data : json
          Full meta (json) containing all the recordings
      rec_id : str
          The recording ID for which meta (json) has to be prepared
      out_meta_file : str
          Path of the output meta (json) file.
      """
  
      subset = {}
      for key in full_meta_data:
          k = str(key)
          if k.startswith(rec_id):
              subset[key] = full_meta_data[key]
  
      with open(out_meta_file, mode="w") as json_f:
          json.dump(subset, json_f, indent=2)
  
imports: import os
  import sys
  import torch
  import logging
  import pickle
  import json
  import glob
  import shutil
  import numpy
  import speechbrain
  from tqdm.contrib import tqdm
  from hyperpyyaml import load_hyperpyyaml
  from speechbrain.utils.distributed import run_on_main
  from speechbrain.processing.PLDA_LDA import StatObject_SB
  from speechbrain.processing import diarization
  from speechbrain.utils.DER import DER
  from speechbrain.dataio.dataio import read_audio
  from speechbrain.dataio.dataio import read_audio_multichannel
label_desc: Use image node_id 3 for calling a global function with example usage: prepare_subset_json(full_meta_data, rec_id, out_meta_file) without return types