diffusers/utils/dummy_torch_and_transformers_objects.py

# This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends


class AltDiffusionImg2ImgPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class AltDiffusionPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class AmusedImg2ImgPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class AmusedInpaintPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class AmusedPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class AnimateDiffPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class AnimateDiffVideoToVideoPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class AudioLDM2Pipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class AudioLDM2ProjectionModel(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class AudioLDM2UNet2DConditionModel(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class AudioLDMPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class CLIPImageProjection(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class CycleDiffusionPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class I2VGenXLPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class IFImg2ImgPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class IFImg2ImgSuperResolutionPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class IFInpaintingPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class IFInpaintingSuperResolutionPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class IFPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class IFSuperResolutionPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class ImageTextPipelineOutput(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class Kandinsky3Img2ImgPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class Kandinsky3Pipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class KandinskyCombinedPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class KandinskyImg2ImgCombinedPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class KandinskyImg2ImgPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class KandinskyInpaintCombinedPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class KandinskyInpaintPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class KandinskyPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class KandinskyPriorPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class KandinskyV22CombinedPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class KandinskyV22ControlnetImg2ImgPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class KandinskyV22ControlnetPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class KandinskyV22Img2ImgCombinedPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class KandinskyV22Img2ImgPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class KandinskyV22InpaintCombinedPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class KandinskyV22InpaintPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class KandinskyV22Pipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class KandinskyV22PriorEmb2EmbPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class KandinskyV22PriorPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class LatentConsistencyModelImg2ImgPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class LatentConsistencyModelPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class LDMTextToImagePipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class LEditsPPPipelineStableDiffusion(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class LEditsPPPipelineStableDiffusionXL(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class MusicLDMPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class PaintByExamplePipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class PIAPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class PixArtAlphaPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class PixArtSigmaPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class SemanticStableDiffusionPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class ShapEImg2ImgPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class ShapEPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableCascadeCombinedPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableCascadeDecoderPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableCascadePriorPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionAdapterPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionAttendAndExcitePipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionControlNetImg2ImgPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionControlNetInpaintPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionControlNetPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionControlNetXSPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionDepth2ImgPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionDiffEditPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionGLIGENPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionGLIGENTextImagePipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionImageVariationPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionImg2ImgPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionInpaintPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionInpaintPipelineLegacy(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionInstructPix2PixPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionLatentUpscalePipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionLDM3DPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionModelEditingPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionPanoramaPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionParadigmsPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionPipelineSafe(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionPix2PixZeroPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionSAGPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionUpscalePipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionXLAdapterPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionXLControlNetImg2ImgPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionXLControlNetInpaintPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionXLControlNetPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionXLControlNetXSPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionXLImg2ImgPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionXLInpaintPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionXLInstructPix2PixPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableDiffusionXLPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableUnCLIPImg2ImgPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableUnCLIPPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class StableVideoDiffusionPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class TextToVideoSDPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class TextToVideoZeroPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class TextToVideoZeroSDXLPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class UnCLIPImageVariationPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class UnCLIPPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class UniDiffuserModel(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class UniDiffuserPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class UniDiffuserTextDecoder(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class VersatileDiffusionDualGuidedPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class VersatileDiffusionImageVariationPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class VersatileDiffusionPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class VersatileDiffusionTextToImagePipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class VideoToVideoSDPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class VQDiffusionPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class WuerstchenCombinedPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class WuerstchenDecoderPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])


class WuerstchenPriorPipeline(metaclass=DummyObject):
    _backends = ["torch", "transformers"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch", "transformers"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch", "transformers"])