code: def transform_wav_data_op(
      wav_data_tensor, hparams, jitter_amount_sec
  ):
      """Transforms with audio for data augmentation. Only for training."""
  
      def transform_wav_data(wav_data):
          """Transforms with sox."""
          if jitter_amount_sec:
              wav_data = audio_io.jitter_wav_data(
                  wav_data, hparams.sample_rate, jitter_amount_sec
              )
          wav_data = audio_transform.transform_wav_audio(
              wav_data, hparams
          )
  
          return [wav_data]
  
      return tf.py_func(
          transform_wav_data,
          [wav_data_tensor],
          tf.string,
          name="transform_wav_data_op",
      )
  
imports: import collections
  import functools
  import io
  import re
  import wave
  import zlib
  import librosa
  from magenta.models.onsets_frames_transcription import audio_transform
  from magenta.models.onsets_frames_transcription import constants
  from magenta.models.onsets_frames_transcription import drum_mappings
  from magenta.models.onsets_frames_transcription import melspec_input
  from note_seq import audio_io
  from note_seq import sequences_lib
  from note_seq.protobuf import music_pb2
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 13 for calling a global function with example usage: transform_wav_data_op(wav_data_tensor, hparams, jitter_amount_sec) and returns: tf, list