code: def save_wav_file(filename, wav_data, sample_rate):
      """Saves audio sample data to a .wav audio file.
  
      Args:
        filename: Path to save the file to.
        wav_data: 2D array of float PCM-encoded audio data.
        sample_rate: Samples per second to encode in the file.
      """
      with tf.compat.v1.Session(graph=tf.Graph()) as sess:
          wav_filename_placeholder = tf.compat.v1.placeholder(
              tf.string, []
          )
          sample_rate_placeholder = tf.compat.v1.placeholder(
              tf.int32, []
          )
          wav_data_placeholder = tf.compat.v1.placeholder(
              tf.float32, [None, 1]
          )
          wav_encoder = tf.audio.encode_wav(
              wav_data_placeholder, sample_rate_placeholder
          )
          wav_saver = io_ops.write_file(
              wav_filename_placeholder, wav_encoder
          )
          sess.run(
              wav_saver,
              feed_dict={
                  wav_filename_placeholder: filename,
                  sample_rate_placeholder: sample_rate,
                  wav_data_placeholder: np.reshape(wav_data, (-1, 1)),
              },
          )
  
imports: import hashlib
  import math
  import os.path
  import random
  import re
  import sys
  import tarfile
  import numpy
  import urllib
  import tensorflow
  from tensorflow.python.ops import gen_audio_ops
  from tensorflow.python.ops import io_ops
  from tensorflow.python.platform import gfile
  from tensorflow.python.util import compat
label_desc: Use image node_id 4 for calling a global function with example usage: save_wav_file(filename, wav_data, sample_rate) without return types