code: def universal_image_quality_index() -> tuple:
      """Plot universal image quality index example."""
      from torchmetrics.image.uqi import UniversalImageQualityIndex
  
      p = lambda: torch.rand([16, 1, 16, 16])
      t = lambda: p() * 0.75
  
      # plot single value
      metric = UniversalImageQualityIndex()
      metric.update(p(), t())
      fig, ax = metric.plot()
  
      # plot multiple values
      metric = UniversalImageQualityIndex()
      vals = [metric(p(), t()) for _ in range(10)]
      fig, ax = metric.plot(vals)
  
      return fig, ax
  
imports: import argparse
  import matplotlib.pyplot
  import torch
label_desc: Use image node_id 17 for calling a global function with example usage: universal_image_quality_index() and returns: fig,  ax