text: import matplotlib.pyplot as plt
  import tensorflow as tf
  import numpy as np
  
  layers = tf.keras.layers
  mnist = tf.keras.datasets.fashion_mnist
  
  (x_train, y_train), (x_test, y_test) = mnist.load_data()
  x_train, x_test = x_train / 255.0, x_test / 255.0
  
  class_names = ['T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat', 'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot']
  plt.figure(figsize=(10,10))
  for i in range(25):
   plt.subplot(5,5,i+1)
   plt.xticks([])
   plt.yticks([])
   plt.grid(False)
   plt.imshow(x_train[i], cmap=plt.cm.binary)
   plt.xlabel(class_names[y_train[i]])
  plt.show()