code: def plot_kernel_samples(
      ax: Axes, kernel: gpflow.kernels.Kernel
  ) -> None:
      X = np.zeros((0, 1))
      Y = np.zeros((0, 1))
      model = gpflow.models.GPR((X, Y), kernel=deepcopy(kernel))
      Xplot = np.linspace(-0.6, 0.6, 100)[:, None]
      tf.random.set_seed(20220903)
      n_samples = 3
      # predict_f_samples draws n_samples examples of the function f, and returns their values at Xplot.
      fs = model.predict_f_samples(Xplot, n_samples)
      ax.plot(
          Xplot, fs[:, :, 0].numpy().T, label=kernel.__class__.__name__
      )
      ax.set_ylim(bottom=-2.0, top=2.0)
      ax.set_title("Example $f$s")
  
file_path: GPflow/doc/sphinx/notebooks/getting_started/kernels.pct.py
imports: import os
  import warnings
  from copy import deepcopy
  import matplotlib.pyplot
  import numpy
  import tensorflow
  from matplotlib.axes import Axes
  from matplotlib.cm import coolwarm
  import gpflow
label_desc: Use image node_id 2 for calling a global function with example usage: plot_kernel_samples(ax, kernel) without return types