Hello @markhirsch, what we basically do in the generator is, generate an image of required size from a random sample. In our GAN template, we are starting with a a random tensor of size 100 and then upsampling it using dense layers to a size 784 in a gradual manner. Here 784 is same as the shape of the data we want to learn from(28 * 28 * 1), before reshaping.
Because you have images of shape 28 * 28 * 3, you would basically need your generator to produce images of same size and then we reshape using the reshape layer. Since, 28 * 28 * 3 = 2352, we want the generated image to have same number of pixels. Here is one way I chose to do it in gradual steps from 100 to 2352. Here 100 is also arbitrary. You can choose a random sample of your choice. It can be of any shape and size.
Hope this helps you in building the model successfully! Let us know, if you have any more questions.