code: def merge_csvs(data_folder, csv_lst, merged_csv):
      """Merging several csv files into one file.
  
      Arguments
      ---------
      data_folder : string
          The folder to store csv files to be merged and after merging.
      csv_lst : list
          Filenames of csv file to be merged.
      merged_csv : string
          The filename to write the merged csv file.
  
      Example
      -------
      >>> tmpdir = getfixture('tmpdir')
      >>> os.symlink(os.path.realpath("tests/samples/annotation/speech.csv"), tmpdir / "speech.csv")
      >>> merge_csvs(tmpdir,
      ... ["speech.csv", "speech.csv"],
      ... "test_csv_merge.csv")
      """
      write_path = os.path.join(data_folder, merged_csv)
      if os.path.isfile(write_path):
          logger.info("Skipping merging. Completed in previous run.")
      with open(os.path.join(data_folder, csv_lst[0])) as f:
          header = f.readline()
      lines = []
      for csv_file in csv_lst:
          with open(os.path.join(data_folder, csv_file)) as f:
              for i, line in enumerate(f):
                  if i == 0:
                      # Checking header
                      if line != header:
                          raise ValueError(
                              "Different header for "
                              f"{csv_lst[0]} and {csv}."
                          )
                      continue
                  lines.append(line)
      with open(write_path, "w") as f:
          f.write(header)
          for line in lines:
              f.write(line)
      logger.info(f"{write_path} is created.")
  
imports: import os
  import torch
  import logging
  import numpy
  import pickle
  import hashlib
  import csv
  import time
  import torchaudio
  import json
  import re
  from speechbrain.utils.torch_audio_backend import check_torchaudio_backend
label_desc: Use image node_id 25 for calling a global function with example usage: merge_csvs(data_folder, csv_lst, merged_csv) without return types