code: def write_stdout(data, filename=None, sampling_rate=None):
      """Write data to standard output.
  
      Arguments
      ---------
      data : str, list, torch.tensor, numpy.ndarray
          The data to write in the text file.
      filename : None
          Not used, just here for compatibility.
      sampling_rate : None
          Not used, just here for compatibility.
  
      Returns
      -------
      None
  
      Example
      -------
      >>> tmpdir = getfixture('tmpdir')
      >>> signal = torch.tensor([[1,2,3,4]])
      >>> write_stdout(signal, tmpdir / 'example.txt')
      [1, 2, 3, 4]
      """
      # Managing Torch.Tensor
      if isinstance(data, torch.Tensor):
          data = data.tolist()
      # Managing np.ndarray
      if isinstance(data, np.ndarray):
          data = data.tolist()
      if isinstance(data, list):
          for line in data:
              print(line)
      if isinstance(data, str):
          print(data)
  
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 15 for calling a global function with example usage: write_stdout(data, filename, sampling_rate) without return types