e) —
The type of class embedding to use which is ultimately summed with the time embeddings. Choose from None,
"timestep", or "identity".   num_class_embeds (int, optional, defaults to None) —
Input dimension of the learnable embedding matrix to be projected to time_embed_dim when performing class
conditioning with class_embed_type equal to None.    A 2D UNet model that takes a noisy sample and a timestep and returns a sample shaped output. Thi