original_docstring: Iterate a set of wavs and write the corresponding csv file.
  
      Arguments
      ---------
      folder : str
          The folder relative to which the files in the list are listed.
      filelist : str
          The location of a file listing the files to be used.
      csvfile : str
          The location to use for writing the csv file.
      max_length : float
          The maximum length in seconds. Waveforms longer
          than this will be cut into pieces.
      
docstring: Iterate a set of wavs and write the corresponding csv file.
  Arguments
  
  folder : str
  The folder relative to which the files in the list are listed.
  filelist : str
  The location of a file listing the files to be used.
  csvfile : str
  The location to use for writing the csv file.
  max_length : float
  The maximum length in seconds. Waveforms longer
  than this will be cut into pieces.
docstring_tokens: Iterate a set of wavs and write the corresponding csv file . Arguments folder : str The folder relative to which the files in the list are listed . filelist : str The location of a file listing the files to be used . csvfile : str The location to use for writing the csv file . max_length : float The maximum length in seconds . Waveforms longer than this will be cut into pieces .
code: def _prepare_csv(folder, filelist, csv_file, max_length=None):
      """Iterate a set of wavs and write the corresponding csv file.
  
      Arguments
      ---------
      folder : str
          The folder relative to which the files in the list are listed.
      filelist : str
          The location of a file listing the files to be used.
      csvfile : str
          The location to use for writing the csv file.
      max_length : float
          The maximum length in seconds. Waveforms longer
          than this will be cut into pieces.
      """
      try:
          if if_main_process():
              with open(csv_file, "w") as w:
                  w.write("ID,duration,wav,wav_format,wav_opts\n\n")
                  for line in open(filelist):
  
                      # Read file for duration/channel info
                      filename = os.path.join(folder, line.split()[-1])
                      signal, rate = torchaudio.load(filename)
  
                      # Ensure only one channel
                      if signal.shape[0] > 1:
                          signal = signal[0].unsqueeze(0)
                          torchaudio.save(filename, signal, rate)
  
                      ID, ext = os.path.basename(filename).split(".")
                      duration = signal.shape[1] / rate
  
                      # Handle long waveforms
                      if max_length is not None and duration > max_length:
                          # Delete old file
                          os.remove(filename)
                          for i in range(int(duration / max_length)):
                              start = int(max_length * i * rate)
                              stop = int(
                                  min(max_length * (i + 1), duration) * rate
                              )
                              new_filename = (
                                  filename[: -len(f".{ext}")] + f"_{i}.{ext}"
                              )
                              torchaudio.save(
                                  new_filename, signal[:, start:stop], rate
                              )
                              csv_row = (
                                  f"{ID}_{i}",
                                  str((stop - start) / rate),
                                  new_filename,
                                  ext,
                                  "\n",
                              )
                              w.write(",".join(csv_row))
                      else:
                          w.write(
                              ",".join((ID, str(duration), filename, ext, "\n"))
                          )
      finally:
          ddp_barrier()
code_tokens: def _prepare_csv ( folder , filelist , csv_file , max_length = None ) : try : if if_main_process ( ) : with open ( csv_file , "w" ) as w : w . write ( "ID,duration,wav,wav_format,wav_opts\n\n" ) for line in open ( filelist ) : filename = os . path . join ( folder , line . split ( ) [ - 1 ] ) signal , rate = torchaudio . load ( filename ) if signal . shape [ 0 ] > 1 : signal = signal [ 0 ] . unsqueeze ( 0 ) torchaudio . save ( filename , signal , rate ) ID , ext = os . path . basename ( filename ) . split ( "." ) duration = signal . shape [ 1 ] / rate if max_length is not None and duration > max_length : os . remove ( filename ) for i in range ( int ( duration / max_length ) ) : start = int ( max_length * i * rate ) stop = int ( min ( max_length * ( i + 1 ) , duration ) * rate ) new_filename = ( filename [ : - len ( f".{ext}" ) ] + f"_{i}.{ext}" ) torchaudio . save ( new_filename , signal [ : , start : stop ] , rate ) csv_row = ( f"{ID}_{i}" , str ( ( stop - start ) / rate ) , new_filename , ext , "\n" , ) w . write ( "," . join ( csv_row ) ) else : w . write ( "," . join ( ( ID , str ( duration ) , filename , ext , "\n" ) ) ) finally : ddp_barrier ( )
short_docstring: Iterate a set of wavs and write the corresponding csv file.
short_docstring_tokens: Iterate a set of wavs and write the corresponding csv file .
comment: """Iterate a set of wavs and write the corresponding csv file.
  
      Arguments
      ---------
      folder : str
          The folder relative to which the files in the list are listed.
      filelist : str
          The location of a file listing the files to be used.
      csvfile : str
          The location to use for writing the csv file.
      max_length : float
          The maximum length in seconds. Waveforms longer
          than this will be cut into pieces.
      """$SEP$# Read file for duration/channel info$SEP$# Ensure only one channel$SEP$# Handle long waveforms$SEP$# Delete old file