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What's New in TensorFlow 2.0

What's New in TensorFlow 2.0

By : Baranwal, Alizishaan Khatri
5 (2)
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What's New in TensorFlow 2.0

What's New in TensorFlow 2.0

5 (2)
By: Baranwal, Alizishaan Khatri

Overview of this book

TensorFlow is an end-to-end machine learning platform for experts as well as beginners, and its new version, TensorFlow 2.0 (TF 2.0), improves its simplicity and ease of use. This book will help you understand and utilize the latest TensorFlow features. What's New in TensorFlow 2.0 starts by focusing on advanced concepts such as the new TensorFlow Keras APIs, eager execution, and efficient distribution strategies that help you to run your machine learning models on multiple GPUs and TPUs. The book then takes you through the process of building data ingestion and training pipelines, and it provides recommendations and best practices for feeding data to models created using the new tf.keras API. You'll explore the process of building an inference pipeline using TF Serving and other multi-platform deployments before moving on to explore the newly released AIY, which is essentially do-it-yourself AI. This book delves into the core APIs to help you build unified convolutional and recurrent layers and use TensorBoard to visualize deep learning models using what-if analysis. By the end of the book, you'll have learned about compatibility between TF 2.0 and TF 1.x and be able to migrate to TF 2.0 smoothly.
Table of Contents (13 chapters)
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1
Section 1: TensorFlow 2.0 - Architecture and API Changes
4
Section 2: TensorFlow 2.0 - Data and Model Training Pipelines
7
Section 3: TensorFlow 2.0 - Model Inference and Deployment and AIY
10
Section 4: TensorFlow 2.0 - Migration, Summary

Making code TF 2.0-native

The simplest way to make TF 1.x code compatible with TF 2.0 code is to run the update script that's installed on your system, along with the TF 2.0 installation. The update script makes use of the tf.compat.v1 module.

As a way to provide backward compatibility for code written for TF 1.x, the tf.compat.v1 module was introduced in TF 2.0. The tf.compat.v1 module replaces all TF 1.x symbols, such as tf.foo and tf.compat.v1.foo. This module allows most of the code that's been written for TF 1.x to be converted so that it can be run in TF 2.0.

As a way to streamline this process, TensorFlow provides a tf_upgrade_v2 utility, which helps streamline the transition as much as possible. This utility is preinstalled with the TF 2.0 installation, along with any TF 1.x installation from r1.13 and onwards. To run this script, simply specify an infile and...

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