据说tensorflow 2.0版本集成了keras风格的api，貌似对程序员更友好；本文参考官方文档编写测试程序，采用tensoeflow 2.0构建深度学习模型，编写手写数字识别程序
手写数字数据集大概是这样的，
下面是程序代码：1
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28# 安装 TensorFlow
import tensorflow as tf
mnist = tf.keras.datasets.mnist
(x_train, y_train), (x_test, y_test) = mnist.load_data()
print(type(x_train))
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.summary()
model.fit(x_train, y_train, epochs=5)
model.evaluate(x_test, y_test, verbose=2)
