tf2_mnist.py

# curl -O https://gist.githubusercontent.com/xagano/1ba3caabd6d1c40d0fe85058a7294222/raw/b2ea3934cfeec110aaf74ca8f5bbdd07fae628fe/TF2_MNIST.py
import time
import tensorflow as tf

mnist = tf.keras.datasets.mnist

(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0

model = tf.keras.models.Sequential([
  tf.keras.layers.Flatten(input_shape=(28, 28)),
  tf.keras.layers.Dense(128, activation='relu'),
  tf.keras.layers.Dropout(0.2),
  tf.keras.layers.Dense(10, activation='softmax')
])

model.compile(optimizer='adam',
              loss='sparse_categorical_crossentropy',
              metrics=['accuracy'])

start = time.time()
model.fit(x_train, y_train, epochs=5)
print("trianing time ", time.time()-start, "[s]")

model.evaluate(x_test,  y_test, verbose=2)