different modes in two dimensions the training procedure shown in the bottom row of images actually visits one mode after another instead of learning to visit all of the different modes so what's going on is that the generator will identify some mode that the discriminator believes is highly likely and place all of its maps there and then the discriminator learns not to be fooled by the generator going to that one particular location and instead of learning that the generator ought to go to multiple locations the generator