%matplotlib
from tensorflow.examples.tutorials.mnist import input_data
import matplotlib.pyplot as plt

mnist = input_data.read_data_sets('MNIST_data', one_hot=True)

print('Training data size: ', mnist.train.num_examples)
print('Validation data size: ', mnist.validation.num_examples)
print('Test data size: ', mnist.test.num_examples)

img0 = mnist.train.images[0].reshape(28,28)
img1 = mnist.train.images[1].reshape(28,28)
img2 = mnist.train.images[2].reshape(28,28)
img3 = mnist.train.images[3].reshape(28,28)

fig = plt.figure(figsize=(10,10))
ax0 = fig.add_subplot(221)
ax1 = fig.add_subplot(222)
ax2 = fig.add_subplot(223)
ax3 = fig.add_subplot(224)

ax0.imshow(img0)
ax1.imshow(img1)
ax2.imshow(img2)
ax3.imshow(img3)
fig.show()