July 2019
Intermediate to advanced
512 pages
19h 39m
English
Content preview from Hands-On Deep Learning Algorithms with Python
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Defining generator
Generator 
which takes the noise, 
, and also a variable, 
, as an input and returns an image. Instead of using a fully connected layer in the generator, we use a deconvolutional network, just like when we studied DCGANs:
def generator(c, z,reuse=None):
First, concatenate the noise, z, and the variable, 
:
input_combined = tf.concat([c, ...
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