Book Image

Hands-On Neural Networks with TensorFlow 2.0

By : Paolo Galeone
Book Image

Hands-On Neural Networks with TensorFlow 2.0

By: Paolo Galeone

Overview of this book

TensorFlow, the most popular and widely used machine learning framework, has made it possible for almost anyone to develop machine learning solutions with ease. With TensorFlow (TF) 2.0, you'll explore a revamped framework structure, offering a wide variety of new features aimed at improving productivity and ease of use for developers. This book covers machine learning with a focus on developing neural network-based solutions. You'll start by getting familiar with the concepts and techniques required to build solutions to deep learning problems. As you advance, you’ll learn how to create classifiers, build object detection and semantic segmentation networks, train generative models, and speed up the development process using TF 2.0 tools such as TensorFlow Datasets and TensorFlow Hub. By the end of this TensorFlow book, you'll be ready to solve any machine learning problem by developing solutions using TF 2.0 and putting them into production.
Table of Contents (15 chapters)
Free Chapter
Section 1: Neural Network Fundamentals
Section 2: TensorFlow Fundamentals
Section 3: The Application of Neural Networks

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...