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What's New in TensorFlow 2.0

You're reading from   What's New in TensorFlow 2.0 Use the new and improved features of TensorFlow to enhance machine learning and deep learning

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Product type Paperback
Published in Aug 2019
Publisher Packt
ISBN-13 9781838823856
Length 202 pages
Edition 1st Edition
Languages
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Authors (3):
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Tanish Baranwal Tanish Baranwal
Author Profile Icon Tanish Baranwal
Tanish Baranwal
Alizishaan Khatri Alizishaan Khatri
Author Profile Icon Alizishaan Khatri
Alizishaan Khatri
Ajay Baranwal Ajay Baranwal
Author Profile Icon Ajay Baranwal
Ajay Baranwal
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Toc

Table of Contents (13) Chapters Close

Preface 1. Section 1: TensorFlow 2.0 - Architecture and API Changes
2. Getting Started with TensorFlow 2.0 FREE CHAPTER 3. Keras Default Integration and Eager Execution 4. Section 2: TensorFlow 2.0 - Data and Model Training Pipelines
5. Designing and Constructing Input Data Pipelines 6. Model Training and Use of TensorBoard 7. Section 3: TensorFlow 2.0 - Model Inference and Deployment and AIY
8. Model Inference Pipelines - Multi-platform Deployments 9. AIY Projects and TensorFlow Lite 10. Section 4: TensorFlow 2.0 - Migration, Summary
11. Migrating From TensorFlow 1.x to 2.0 12. Other Books You May Enjoy

Running TFLite on mobile devices

In this section, we will cover how TFLite can be run on the two major mobile OSes: Android and iOS.

TFLite on Android

Using TFLite on Android is as easy as adding TFLite to the dependencies field in the build.gradle file in Android Studio, and importing it into Android Studio:

dependencies {
implementation 'org.tensorflow:tensorflow-lite:0.0.0-nightly'
}

import org.tensorflow.lite.Interpreter;

Once this is done, the next step is to create an instance of the interpreter and load the model. This can be done using a helper function from the TFLite sample on GitHub called getModelPath, and by using loadModelFile to load the converted TFLite file. Now, to run the model, simply use the...

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