Hands-On Deep Learning with R

Passing input to the discriminator model

Now, we will pass the inputs to the discriminator model using the following steps:

1. Next, we pass our combined images, containing a mix of real and fake images, as input to our discriminator model and we pass along the labels as the target variable for the model. We feed our independent and dependent variables to the input and output layers of our discriminator model using the following code:

d_loss <- discriminator %>% train_on_batch(combined_images, labels)d_loss

2. The result of running this code is the error rate for the discriminator. We can just run the name of the object to have this value printed to our console. After running the preceding code, your console will look as in the following screenshot, ...