keras和tf.keras有什么区别? [英] What is the difference between keras and tf.keras?

问题描述

我正在学习TensorFlow和Keras.我想尝试 https://www.amazon. com/Deep-Learning-Python-Francois-Chollet/dp/1617294438/，它似乎是用Keras编写的.

I'm learning TensorFlow and Keras. I'd like to try https://www.amazon.com/Deep-Learning-Python-Francois-Chollet/dp/1617294438/, and it seems to be written in Keras.

将代码转换为tf.keras是否相当简单?

Would it be fairly straightforward to convert code to tf.keras?

我对代码的可移植性并不感兴趣，而不是两者之间的真正区别.

I'm not more interested in the portability of the code, rather than the true difference between the two.

推荐答案

在这一点上，tensorflow几乎完全采用了keras API，并且有一个很好的理由-它简单，易用且易于学习，而纯" tensorflow带有很多样板代码.是的，您可以使用tf.keras而不会出现任何问题，尽管您可能必须在代码中重新处理导入.例如

At this point tensorflow has pretty much entirely adopted the keras API and for a good reason - it's simple, easy to use and easy to learn, whereas "pure" tensorflow comes with a lot of boilerplate code. And yes, you can use tf.keras without any issues, though you might have to re-work your imports in the code. For instance

from keras.layers.pooling import MaxPooling2D

将变成:

from tensorflow.keras.layers import MaxPooling2D

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