code: def confusion_matrix_example() -> tuple:
      """Plot confusion matrix example."""
      from torchmetrics.classification import MulticlassConfusionMatrix
  
      p = lambda: torch.randn(20, 5)
      t = lambda: torch.randint(5, (20,))
  
      # plot single value
      metric = MulticlassConfusionMatrix(num_classes=5)
      metric.update(p(), t())
      fig, ax = metric.plot()
      return fig, ax
  
imports: import argparse
  import matplotlib.pyplot
  import torch
label_desc: Use image node_id 10 for calling a global function with example usage: confusion_matrix_example() and returns: fig,  ax