Generative Adversarial Networks Projects

Training the generator network

To train the generator network, we have to train the adversarial model. When we train the adversarial model, it trains the generator network only but freezes the discriminator network. We won't train the discriminator network, as we have already trained it. Perform the following steps to train the adversarial model:

1. Start by creating a batch of noise vectors again. Sample these noise vectors from a Gaussian/Normal distribution:

z_noise = np.random.normal(0, 1, size=(batch_size, z_shape))

2. Next, train the adversarial model on this batch of noise vectors, as follows:

g_loss = adversarial_model.train_on_batch(z_noise, [1] * batch_size)

We train the adversarial model on the batch of noise vectors and real labels. ...