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TensorFlow 2.0 Quick Start Guide

You're reading from   TensorFlow 2.0 Quick Start Guide Get up to speed with the newly introduced features of TensorFlow 2.0

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789530759
Length 196 pages
Edition 1st Edition
Languages
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Author (1):
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Tony Holdroyd Tony Holdroyd
Author Profile Icon Tony Holdroyd
Tony Holdroyd
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Table of Contents (15) Chapters Close

Preface 1. Section 1: Introduction to TensorFlow 2.00 Alpha FREE CHAPTER
2. Introducing TensorFlow 2 3. Keras, a High-Level API for TensorFlow 2 4. ANN Technologies Using TensorFlow 2 5. Section 2: Supervised and Unsupervised Learning in TensorFlow 2.00 Alpha
6. Supervised Machine Learning Using TensorFlow 2 7. Unsupervised Learning Using TensorFlow 2 8. Section 3: Neural Network Applications of TensorFlow 2.00 Alpha
9. Recognizing Images with TensorFlow 2 10. Neural Style Transfer Using TensorFlow 2 11. Recurrent Neural Networks Using TensorFlow 2 12. TensorFlow Estimators and TensorFlow Hub 13. Converting from tf1.12 to tf2
14. Other Books You May Enjoy

Creating the model

There now follows a series of functions leading eventually up to the main function that performs the style transfer (run_style_transfer()).

The first function in this sequence, get_model(), creates the model we are going to use.

It first loads trained vgg_model (which has been trained on ImageNet) without its classification layer (include_top=False). Next, it freezes the loaded model (vgg_model.trainable = False).

The style and content layer output values are then acquired using list comprehensions, which iterate over the names of the layers that we specified in the previous section.

These output values are then used, together with the VGG input to create our new model with access to VGG layers, that is, get_model() returns a Keras model that outputs the style and content intermediate layers of the trained VGG19 model. It is unnecessary to use the top layer...

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