code: def get_spectrogram(
      n_fft=400,
      win_len=None,
      hop_len=None,
      power=2.0,
  ):
      waveform, _ = get_speech_sample()
      spectrogram = T.Spectrogram(
          n_fft=n_fft,
          win_length=win_len,
          hop_length=hop_len,
          center=True,
          pad_mode="reflect",
          power=power,
      )
      return spectrogram(waveform)
  
file_path: audio/examples/tutorials/audio_feature_augmentation_tutorial.py
imports: import torch
  import torchaudio
  import torchaudio.transforms
  import librosa
  import matplotlib.pyplot
  from IPython.display import Audio
  from torchaudio.utils import download_asset
label_desc: Use image node_id 3 for calling a global function with example usage: get_spectrogram(n_fft, win_len, hop_len, power) and returns: spectrogram