# This file is autogenerated by the command `make fix-copies`, do not edit. # flake8: noqa 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 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 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 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 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 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 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 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"])