code: def combine_manifests(manifest_save_path: str, num_split: int):
      """
      Args:
          manifest_save_path: absolute path to save the combined manifest
          num_splits: number of splits of manifest
  
      Returns:
          num_samples_combined: the total number of samples in the generated dataset
      """
      num_samples_combined = 0
      base_directory = os.path.dirname(manifest_save_path)
  
      with open(manifest_save_path, "w") as outfile:
          for i in range(num_split):
              split_manifest_path = (
                  base_directory + "/temp_" + str(i) + ".json"
              )
              data_split = read_manifest(split_manifest_path)
  
              for elem in data_split:
                  s = json.dumps(elem)
                  outfile.write(s + "\n")
                  num_samples_combined += 1
  
              # removing the intermediate file
              os.remove(split_manifest_path)
  
      return num_samples_combined
  
file_path: NeMo/scripts/speech_recognition/code_switching/code_switching_audio_data_creation.py
imports: import argparse
  import json
  import logging
  import os
  import librosa
  import numpy
  from joblib import Parallel, delayed
  from scipy.io import wavfile
  from tqdm import tqdm
  from nemo.collections.asr.parts.utils.manifest_utils import read_manifest
label_desc: Use image node_id 2 for calling a global function with example usage: combine_manifests(manifest_save_path, num_split) and returns: num_samples_combined