Part I: Defining text-to-image with Stable Diffusion

We will explore at a very low level the main Python files of the Keras version of Stable Diffusion, as shown in Figure 17.2. The complete code can be found at: https://github.com/keras-team/keras-cv/tree/master/keras_cv/models/stable_diffusion:

Figure 17.2: Stable Diffusion, Keras implementation

Figure 17.2 shows the Stable Diffusion architecture of the code we will explore that can be summed up in five phases:

1. Text embedding.
2. Random image creation.
3. Stable Diffusion downsampling.
4. Decoder upsampling.
5. Output image.

The Keras Stable Diffusion code itself is only 500 lines long!

We will describe each function’s function, make a high-level mathematical representation, and find the Python classes that execute the process.

We will end the analysis by running a Keras notebook illustrating their talented compact code approach.

1. Text embedding using a transformer...