# 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 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 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 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 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 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 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 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 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"])
