code: def plot_prediction(
      predict_y: Callable[[tf.Tensor], Tuple[tf.Tensor, tf.Tensor]]
  ) -> None:
      Xplot = np.linspace(0.0, 1.0, 200)[:, None]
  
      y_mean, y_var = predict_y(Xplot)
      y_lower = y_mean - 1.96 * np.sqrt(y_var)
      y_upper = y_mean + 1.96 * np.sqrt(y_var)
  
      _, ax = plt.subplots(nrows=1, ncols=1)
      ax.plot(X, Y, "kx", mew=2)
      (mean_line,) = ax.plot(Xplot, y_mean, "-")
      color = mean_line.get_color()
      ax.plot(Xplot, y_lower, lw=0.1, color=color)
      ax.plot(Xplot, y_upper, lw=0.1, color=color)
      ax.fill_between(
          Xplot[:, 0],
          y_lower[:, 0],
          y_upper[:, 0],
          color=color,
          alpha=0.1,
      )
  
file_path: GPflow/doc/sphinx/notebooks/getting_started/saving_and_loading.pct.py
imports: import os
  import warnings
  from typing import Callable, Tuple
  import matplotlib.pyplot
  import numpy
  import tensorflow
  import gpflow
label_desc: Use image node_id 1 for calling a global function with example usage: plot_prediction(predict_y) without return types