Hands-On Deep Learning Algorithms with Python

Discriminator loss

The discriminator loss is given as follows:

First, we will implement the first term, that is, :

D_loss_real = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(logits=D_logits_real,               labels=tf.ones_like(D_logits_real)))

Now we will implement the second term, :

D_loss_fake = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(logits=D_logits_fake,                 labels=tf.zeros_like(D_logits_fake)))

The final loss can be written as ...