CODEWITHSUNDEEP
tensorflowdeep-learningconv-neural-network
1001b
1001b

Reputation: 265

Visualizing DeepLearning CNN Layers

I came across an experimental use of Deep Learning using Tensorflow, https://github.com/asrivat1/DeepLearningVideoGames. The author trained CNNs to play Pong game. All seem straightforward to me, except the visualization to illustrate Q-value in the CNN layers. Here's the youtube video, https://www.youtube.com/watch?v=W9jGIzkVCsM. Anyone can explain how the graphs (heat map looking) are plotted?

Thx.

Upvotes: 0

Views: 757

Answers (1)

Olivier Moindrot
Olivier Moindrot

Reputation: 28198

I digged into the code and found this file from a previous commit, but it is not present anymore in the master version (weird).

Inside you will find the code to visualize, the important lines are:

self.l1.imshow(np.reshape(np.rollaxis(c1, 2, 1),(20,20*32)),aspect = 6)
self.l2.imshow(np.reshape(np.rollaxis(c2, 2, 1),(5,5*64)),aspect = 12)
self.l3.imshow(np.reshape(np.rollaxis(c3, 2, 1),(3,3*64)),aspect = 12)

Here they take the activation map of size (20, 20, 32) and plot all the activations. They reshape to (20, 20*32) to plot all the feature maps (32 in total) side by side. To make it fit into the screen, they use an aspect ratio of 6, which compresses the image horizontally.

To sum it up, they plot all the feature maps side by side, and compress it to fit into the screen. I would advise you to avoid changing the aspect ratio, and instead use little blocks for each activation (32 blocks in total) and arrange the blocks in a 8x4 layout for instance.

Upvotes: 3

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