code: def image_grid():
      """Return a 5x5 grid of the MNIST images as a matplotlib figure."""
      # Create a figure to contain the plot.
      figure = plt.figure(figsize=(10, 10))
      for i in range(25):
          # Start next subplot.
          plt.subplot(5, 5, i + 1, title=class_names[train_labels[i]])
          plt.xticks([])
          plt.yticks([])
          plt.grid(False)
          plt.imshow(train_images[i], cmap=plt.cm.binary)
  
      return figure
  
file_path: guildai/examples/tensorboard/images.py
imports: import os
  from datetime import datetime
  import io
  import itertools
  from packaging import version
  import tensorflow
  from tensorflow import keras
  import matplotlib.pyplot
  import numpy
  import sklearn.metrics
label_desc: Use image node_id 2 for calling a global function with example usage: image_grid() and returns: figure