ophy is reflected in multiple parts of the library: We follow PyTorch’s API with methods like DiffusionPipeline.to to let the user handle device management. Raising concise error messages is preferred to silently correct erroneous input. Diffusers aims at teaching the user, rather than making the library as easy to use as possible. Complex model vs. scheduler logic is exposed instead of magically handled inside. Schedulers/Samplers are separate