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Hands-On Neural Networks with TensorFlow 2.0

You're reading from  Hands-On Neural Networks with TensorFlow 2.0

Product type Book
Published in Sep 2019
Publisher Packt
ISBN-13 9781789615555
Pages 358 pages
Edition 1st Edition
Languages
Author (1):
Paolo Galeone Paolo Galeone
Profile icon Paolo Galeone

Table of Contents (15) Chapters

Preface Section 1: Neural Network Fundamentals
What is Machine Learning? Neural Networks and Deep Learning Section 2: TensorFlow Fundamentals
TensorFlow Graph Architecture TensorFlow 2.0 Architecture Efficient Data Input Pipelines and Estimator API Section 3: The Application of Neural Networks
Image Classification Using TensorFlow Hub Introduction to Object Detection Semantic Segmentation and Custom Dataset Builder Generative Adversarial Networks Bringing a Model to Production Other Books You May Enjoy

Codebase migration

As we have already seen, TensorFlow 2.0 brings a lot of breaking changes, which means that we have to relearn how to use the framework. TensorFlow 1.x is the most widely used machine learning framework and so there is a lot of existing code that needs to be upgraded.

The TensorFlow engineers developed a conversion tool that can help in the conversion process: unfortunately, it relies on the tf.compat.v1 module, and it does not remove the graph nor the session execution. Instead, it just rewrites the code, prefixing it using tf.compat.v1, and applies some source code transformations to fix some easy API changes.

However, it is a good starting point to migrate a whole codebase. In fact, the suggested migration process is as follows:

  1. Run the migration script.
  2. Manually remove every tf.contrib symbol, looking for the new location of the project that was used in...
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