tensorflow2.0实现MNIST分类(二)

 下面是tensorflow2.0完全采用keras的API来实现的

from __future__ import absolute_import, division, print_function, unicode_literals

!pip install -q tensorflow==2.0.0-alpha0
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'])

 

model.fit(x_train, y_train, epochs=5)

model.evaluate(x_test, y_test)

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