Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Hands-On Neural Networks with TensorFlow 2.0

You're reading from   Hands-On Neural Networks with TensorFlow 2.0 Understand TensorFlow, from static graph to eager execution, and design neural networks

Arrow left icon
Product type Paperback
Published in Sep 2019
Publisher Packt
ISBN-13 9781789615555
Length 358 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Paolo Galeone Paolo Galeone
Author Profile Icon Paolo Galeone
Paolo Galeone
Arrow right icon
View More author details
Toc

Table of Contents (15) Chapters Close

Preface 1. Section 1: Neural Network Fundamentals
2. What is Machine Learning? FREE CHAPTER 3. Neural Networks and Deep Learning 4. Section 2: TensorFlow Fundamentals
5. TensorFlow Graph Architecture 6. TensorFlow 2.0 Architecture 7. Efficient Data Input Pipelines and Estimator API 8. Section 3: The Application of Neural Networks
9. Image Classification Using TensorFlow Hub 10. Introduction to Object Detection 11. Semantic Segmentation and Custom Dataset Builder 12. Generative Adversarial Networks 13. Bringing a Model to Production 14. Other Books You May Enjoy

Relearning the framework

As we introduced in Chapter 3, TensorFlow Graph Architecture, TensorFlow works by building a computational graph first and then executing it. In TensorFlow 2.0, this graph definition is hidden and simplified; the execution and the definition can be mixed, and the flow of execution is always the one that's found in the source code—there's no need to worry about the order of execution in 2.0.

Prior to the 2.0 release, developers had to design the graph and the source by following this pattern:

  • How can I define the graph? Is my graph composed of multiple layers that are logically separated? If so, I have to define every logical block inside a different tf.variable_scope.
  • During the training or inference phase, do I have to use a part of the graph more than once in the same execution step? If so, I have to define this part by wrapping it...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime