code: def plot_specgram(
      waveform, sample_rate, title="Spectrogram", xlim=None
  ):
      waveform = waveform.numpy()
  
      num_channels, _ = waveform.shape
  
      figure, axes = plt.subplots(num_channels, 1)
      if num_channels == 1:
          axes = [axes]
      for c in range(num_channels):
          axes[c].specgram(waveform[c], Fs=sample_rate)
          if num_channels > 1:
              axes[c].set_ylabel(f"Channel {c+1}")
          if xlim:
              axes[c].set_xlim(xlim)
      figure.suptitle(title)
  
file_path: audio/examples/tutorials/audio_data_augmentation_tutorial.py
imports: import torch
  import torchaudio
  import torchaudio.functional
  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: plot_specgram(waveform, sample_rate, title, xlim) without return types