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Hands-On Generative Adversarial Networks with PyTorch 1.x

You're reading from   Hands-On Generative Adversarial Networks with PyTorch 1.x Implement next-generation neural networks to build powerful GAN models using Python

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Product type Paperback
Published in Dec 2019
Publisher Packt
ISBN-13 9781789530513
Length 312 pages
Edition 1st Edition
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Authors (2):
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John Hany John Hany
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John Hany
Greg Walters Greg Walters
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Greg Walters
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Table of Contents (15) Chapters Close

Preface 1. Section 1: Introduction to GANs and PyTorch
2. Generative Adversarial Networks Fundamentals FREE CHAPTER 3. Getting Started with PyTorch 1.3 4. Best Practices for Model Design and Training 5. Section 2: Typical GAN Models for Image Synthesis
6. Building Your First GAN with PyTorch 7. Generating Images Based on Label Information 8. Image-to-Image Translation and Its Applications 9. Image Restoration with GANs 10. Training Your GANs to Break Different Models 11. Image Generation from Description Text 12. Sequence Synthesis with GANs 13. Reconstructing 3D models with GANs 14. Other Books You May Enjoy

Installing PyTorch on Windows and Linux

To install and use PyTorch, we need to properly set up the Python development environment first. So, in this section, we will first talk about how to set up the Python environment, then how to install PyTorch either with official release binaries or by building from source. At the end of this section, we will introduce you to a lightweight, yet extremely powerful code editor tool, Microsoft VS Code, and show you how to configure it for PyTorch programming.

Setting up the Python environment

In the following sections, we will walk you through how to set up the Python environment and how to install or build PyTorch on Windows 10 and Ubuntu 18.04. We assume that, of course, you have successfully...

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