23 lines
967 B
Python
23 lines
967 B
Python
from __future__ import absolute_import, division, print_function, unicode_literals
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import tensorflow as tf
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mnist = tf.keras.datasets.mnist
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#需要从 https://storage.googleapis.com/tensorflow/tf-keras-datasets/ 下载，执行过程非常缓慢，或者报证书错误可以直接从浏览器下载 https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz
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#并保存到 ~/.kreas/datasets/ 目录下（c盘根目录）即可
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(x_train, y_train), (x_test, y_test) = mnist.load_data()
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x_train, x_test = x_train / 255.0, x_test / 255.0
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model = tf.keras.models.Sequential([
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tf.keras.layers.Flatten(input_shape=(28, 28)),
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tf.keras.layers.Dense(128, activation='relu'),
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tf.keras.layers.Dropout(0.2),
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tf.keras.layers.Dense(10, activation='softmax')
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])
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model.compile(optimizer='adam',
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loss='sparse_categorical_crossentropy',
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metrics=['accuracy'])
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model.fit(x_train, y_train, epochs=5)
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model.evaluate(x_test, y_test) |