I'm learning about AutoRegressive Models used on images, and I've studied the training phase, where you model each pixel on the basis of the previous ones using a certain model architecture.
My question is about generating new images (sampling).
I've seen that the sampling is usually done setting manually the value of the first pixel and calculating the following pixels using the model, i.e. for every pixel you want to generate, you take the previous n pixels and give them to the model which outputs the most likely value, where here "likely" is to be intended as the value which is output given the parameters fitted on the training dataset.
But since the model parameters are fixed, and since you set only the first pixel, does this mean that all pixels except the first one are deterministic and hence you can only generate 256 images (256 is the number of possible values of the first pixel in grayscale)?