code: def _convert_csv_data_to_raw_data_impl(
      self, audio_url, transcript, audio_length
  ):
      if audio_url == "audio_url":
          return pd.Series(
              ["wav_filename", "wav_filesize", "transcript"]
          )
      mp3_filename = os.path.basename(audio_url)
      wav_relative_filename = os.path.join(
          "wav",
          os.path.splitext(os.path.basename(mp3_filename))[0] + ".wav",
      )
      wav_filesize = os.path.getsize(
          os.path.join(self.target_dir, wav_relative_filename)
      )
      transcript = validate_label(transcript)
      if None == transcript:
          transcript = ""
      return pd.Series(
          [wav_relative_filename, wav_filesize, transcript]
      )
  
imports: import csv
  import logging
  import math
  import os
  import subprocess
  import urllib
  from pathlib import Path
  import pandas
  from sox import Transformer
  import swifter
  from deepspeech_training.util.importers import get_importers_parser, get_validate_label
label_desc: Use image node_id 4 for calling the GramVaaniDataSets obj's underlying member method code with example usage: obj._convert_csv_data_to_raw_data_impl(audio_url, transcript, audio_length) and returns: pd, pd