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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
2. Introducing TensorFlow 2 FREE CHAPTER 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

Performing the style transfer

The function that performs style_transfer is quite long so we will present it in sections. Its signature is as follows:

def run_style_transfer(content_path,
style_path,
number_of_iterations=1000,
content_weight=1e3,
style_weight=1e-2):

Since we don't want to actually train any layers in our model, just use the output values from the layers as described previously; we set their trainable properties accordingly:

model = get_model() 
for layer in model.layers:
layer.trainable = False

Next, we get the style_features and content_features representations from the layers of our model, using the function previously defined:

style_features, content_features = get_feature_representations(model, content_path, style_path)

And gram_style_features, using a loop over style_features...

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