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# 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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
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"]) | |
def from_config(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |
def from_pretrained(cls, *args, **kwargs): | |
requires_backends(cls, ["torch", "transformers"]) | |