code: def plot(waveform, title, sample_rate=16000):
      wav_numpy = waveform.numpy()
  
      sample_size = waveform.shape[1]
      time_axis = torch.arange(0, sample_size) / sample_rate
  
      figure, axes = plt.subplots(2, 1)
      axes[0].plot(time_axis, wav_numpy[0], linewidth=1)
      axes[0].grid(True)
      axes[1].specgram(wav_numpy[0], Fs=sample_rate)
      figure.suptitle(title)
  
file_path: audio/examples/tutorials/squim_tutorial.py
imports: import torch
  import torchaudio
  import matplotlib.pyplot
  import torchaudio.functional
  from IPython.display import Audio
  from torchaudio.utils import download_asset
label_desc: Use image node_id 2 for calling a global function with example usage: plot(waveform, title, sample_rate) without return types