January 2019
Intermediate to advanced
316 pages
8h 16m
English
The architecture of the discriminator network is similar to the architecture of the discriminator in a PatchGAN network. It is a deep convolutional neural network and contains several convolution blocks. Basically, it takes an image of a shape of (128, 128, 3) and predicts whether the image is real or fake. It contains several ZeroPadding2D layers, the documentation for which is available at the following link: https://keras.io/layers/convolutional/#zeropadding2d. The following table shows the architecture of the discriminator network in detail:
|
Layer name |
Hyperparameters |
Input shape |
Output shape |
|
Input layer |
none |
(128, 128, 3) |
(128, 128, 3) |
|
ZeroPadding2D layer |
padding(1, 1) |
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