 are loaded and passed to the __init__ function of the pipeline. You shouldn’t use the DiffusionPipeline class for training. Individual components (for example, UNet2DModel and UNet2DConditionModel) of diffusion pipelines are usually trained individually, so we suggest directly working with them instead.  Pipelines do not offer any training functionality. You’ll notice PyTorch’s autograd is disabled by decorating the __call__() method with a to