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Deep Learning with PyTorch

You're reading from   Deep Learning with PyTorch A practical approach to building neural network models using PyTorch

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788624336
Length 262 pages
Edition 1st Edition
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Author (1):
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Vishnu Subramanian Vishnu Subramanian
Author Profile Icon Vishnu Subramanian
Vishnu Subramanian
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Table of Contents (11) Chapters Close

Preface 1. Getting Started with Deep Learning Using PyTorch FREE CHAPTER 2. Building Blocks of Neural Networks 3. Diving Deep into Neural Networks 4. Fundamentals of Machine Learning 5. Deep Learning for Computer Vision 6. Deep Learning with Sequence Data and Text 7. Generative Networks 8. Modern Network Architectures 9. What Next? 10. Other Books You May Enjoy

Visualizing weights of the CNN layer

Getting model weights for a particular layer is straightforward. All the model weights can be accessed through the state_dict function. The state_dict function returns a dictionary, with keys as its layers and weights as its values. The following code demonstrates how to pull weights for a particular layer and visualize them:

vgg.state_dict().keys()
cnn_weights = vgg.state_dict()['features.0.weight'].cpu()

The preceding code provides us with the following output:

Each box represents weights of a filter that is of size 3 x 3. Each filter is trained to identify certain patterns in the images.

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