rmer model for image-like data. Takes either discrete (classes of vector embeddings) or continuous (actual
embeddings) inputs.
When input is continuous: First, project the input (aka embedding) and reshape to b, t, d. Then apply standard
transformer action. Finally, reshape to image.
When input is discrete: First, input (classes of latent pixels) is converted to embeddings and has positional
embeddings applied, see ImagePositionalEmbeddings. Th