January 2018
Intermediate to advanced
474 pages
10h 23m
English
Content preview from Mastering TensorFlow 1.x
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Deep Convolutional GAN with TensorFlow and Keras
You can follow along with the code in the Jupyter notebook ch-14b_DCGAN.
In DCGAN, both the discriminator and generator are implemented using a Deep Convolutional Network:
- In this example, we decided to implement the generator as the following network:
Generator: _________________________________________________________________ Layer (type) Output Shape Param # ================================================================= g_in (Dense) (None, 3200) 822400 _________________________________________________________________ g_in_act (Activation) (None, 3200) 0 _________________________________________________________________ g_in_reshape (Reshape) (None, 5, 5, 128) 0 _________________________________________________________________ ...
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