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View Code? Open in Web Editor NEW完善的MNIST实现
完善的MNIST实现
该程序时按照《TensorFlow实现Goole深度学习框架》一书中的5.5节代码。 该项目将训练和测试分成两个独立的程序,这可以使得每一个组件更加灵活。比如训练神经网络的程序可以持续训练出好的模型,而测试程序可以每隔一段时间检验新模型的正确率, 如果模型效果更好,则将这个模型提供给产品使用。除了将不同功能模块分开,该项目还将前向传播的过程抽象成一个单独的库函数。因为神经网络的前向传播过程在训练和测试的过程都会用到, 所以通过库函数的方式使用起来可以更加方便,又可以保证训练和测试过程中使用的前向传播方法一定时一致的。 该项目主要分为三个程序: 第一个是mnist_inference.py,它定义了前向传播的过程以及神经网络中的参数。 第二个是mnist_train.py,它定义了神经网络的训练过程。 第三个是mnist_eval.py,它定义了测试过程。
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