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Published in:
2021 | OriginalPaper | Chapter
3. Deep Dive in tf.keras
Author : Poornachandra Sarang
Published in: Artificial Neural Networks with TensorFlow 2
Publisher: Apress
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Abstract
Keras is a high-level neural networks API that runs on top of TensorFlow. Last many years, you were using Keras API with TensorFlow running at the backend. With TensorFlow 2.x, this has changed. TensorFlow has now integrated Keras in tf.keras API. The tf.keras is the TensorFlow’s implementation of the Keras API specification. This change is mainly done to bring consistency in using Keras with TF. It also resulted in taking advantage of several TensorFlow features such as eager execution, distributed training and others while using Keras. The latest Keras release as of this writing is 2.3.0. This release adds support for TensorFlow 2.x and is also the last major release of multi-backend Keras. Henceforth, you will be using only tf.keras in all your deep learning applications. You have already used tf.keras in chapter 2 while getting started on TensorFlow. This chapter will take you deeper in the use of tf.keras.