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__init__.py
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1170 lines (1093 loc) · 42.7 KB
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__version__ = "0.33.0.dev0"
from typing import TYPE_CHECKING
from .utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
is_accelerate_available,
is_bitsandbytes_available,
is_flax_available,
is_gguf_available,
is_k_diffusion_available,
is_librosa_available,
is_note_seq_available,
is_onnx_available,
is_optimum_quanto_available,
is_scipy_available,
is_sentencepiece_available,
is_torch_available,
is_torchao_available,
is_torchsde_available,
is_transformers_available,
)
# Lazy Import based on
# https://github.com/huggingface/transformers/blob/main/src/transformers/__init__.py
# When adding a new object to this init, please add it to `_import_structure`. The `_import_structure` is a dictionary submodule to list of object names,
# and is used to defer the actual importing for when the objects are requested.
# This way `import diffusers` provides the names in the namespace without actually importing anything (and especially none of the backends).
_import_structure = {
"configuration_utils": ["ConfigMixin"],
"hooks": [],
"loaders": ["FromOriginalModelMixin"],
"models": [],
"pipelines": [],
"quantizers.quantization_config": [],
"schedulers": [],
"utils": [
"OptionalDependencyNotAvailable",
"is_flax_available",
"is_inflect_available",
"is_invisible_watermark_available",
"is_k_diffusion_available",
"is_k_diffusion_version",
"is_librosa_available",
"is_note_seq_available",
"is_onnx_available",
"is_scipy_available",
"is_torch_available",
"is_torchsde_available",
"is_transformers_available",
"is_transformers_version",
"is_unidecode_available",
"logging",
],
}
try:
if not is_torch_available() and not is_accelerate_available() and not is_bitsandbytes_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils import dummy_bitsandbytes_objects
_import_structure["utils.dummy_bitsandbytes_objects"] = [
name for name in dir(dummy_bitsandbytes_objects) if not name.startswith("_")
]
else:
_import_structure["quantizers.quantization_config"].append("BitsAndBytesConfig")
try:
if not is_torch_available() and not is_accelerate_available() and not is_gguf_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils import dummy_gguf_objects
_import_structure["utils.dummy_gguf_objects"] = [
name for name in dir(dummy_gguf_objects) if not name.startswith("_")
]
else:
_import_structure["quantizers.quantization_config"].append("GGUFQuantizationConfig")
try:
if not is_torch_available() and not is_accelerate_available() and not is_torchao_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils import dummy_torchao_objects
_import_structure["utils.dummy_torchao_objects"] = [
name for name in dir(dummy_torchao_objects) if not name.startswith("_")
]
else:
_import_structure["quantizers.quantization_config"].append("TorchAoConfig")
try:
if not is_torch_available() and not is_accelerate_available() and not is_optimum_quanto_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils import dummy_optimum_quanto_objects
_import_structure["utils.dummy_optimum_quanto_objects"] = [
name for name in dir(dummy_optimum_quanto_objects) if not name.startswith("_")
]
else:
_import_structure["quantizers.quantization_config"].append("QuantoConfig")
try:
if not is_onnx_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils import dummy_onnx_objects # noqa F403
_import_structure["utils.dummy_onnx_objects"] = [
name for name in dir(dummy_onnx_objects) if not name.startswith("_")
]
else:
_import_structure["pipelines"].extend(["OnnxRuntimeModel"])
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils import dummy_pt_objects # noqa F403
_import_structure["utils.dummy_pt_objects"] = [name for name in dir(dummy_pt_objects) if not name.startswith("_")]
else:
_import_structure["hooks"].extend(
[
"FasterCacheConfig",
"HookRegistry",
"PyramidAttentionBroadcastConfig",
"apply_faster_cache",
"apply_pyramid_attention_broadcast",
]
)
_import_structure["models"].extend(
[
"AllegroTransformer3DModel",
"AsymmetricAutoencoderKL",
"AuraFlowTransformer2DModel",
"AutoencoderDC",
"AutoencoderKL",
"AutoencoderKLAllegro",
"AutoencoderKLCogVideoX",
"AutoencoderKLHunyuanVideo",
"AutoencoderKLLTXVideo",
"AutoencoderKLMagvit",
"AutoencoderKLMochi",
"AutoencoderKLTemporalDecoder",
"AutoencoderKLWan",
"AutoencoderOobleck",
"AutoencoderTiny",
"CacheMixin",
"CogVideoXTransformer3DModel",
"CogView3PlusTransformer2DModel",
"CogView4Transformer2DModel",
"ConsisIDTransformer3DModel",
"ConsistencyDecoderVAE",
"ControlNetModel",
"ControlNetUnionModel",
"ControlNetXSAdapter",
"DiTTransformer2DModel",
"EasyAnimateTransformer3DModel",
"FluxControlNetModel",
"FluxMultiControlNetModel",
"FluxTransformer2DModel",
"HunyuanDiT2DControlNetModel",
"HunyuanDiT2DModel",
"HunyuanDiT2DMultiControlNetModel",
"HunyuanVideoTransformer3DModel",
"I2VGenXLUNet",
"Kandinsky3UNet",
"LatteTransformer3DModel",
"LTXVideoTransformer3DModel",
"Lumina2Transformer2DModel",
"LuminaNextDiT2DModel",
"MochiTransformer3DModel",
"ModelMixin",
"MotionAdapter",
"MultiAdapter",
"MultiControlNetModel",
"OmniGenTransformer2DModel",
"PixArtTransformer2DModel",
"PriorTransformer",
"SanaTransformer2DModel",
"SD3ControlNetModel",
"SD3MultiControlNetModel",
"SD3Transformer2DModel",
"SparseControlNetModel",
"StableAudioDiTModel",
"StableCascadeUNet",
"T2IAdapter",
"T5FilmDecoder",
"Transformer2DModel",
"UNet1DModel",
"UNet2DConditionModel",
"UNet2DModel",
"UNet3DConditionModel",
"UNetControlNetXSModel",
"UNetMotionModel",
"UNetSpatioTemporalConditionModel",
"UVit2DModel",
"VQModel",
"WanTransformer3DModel",
]
)
_import_structure["optimization"] = [
"get_constant_schedule",
"get_constant_schedule_with_warmup",
"get_cosine_schedule_with_warmup",
"get_cosine_with_hard_restarts_schedule_with_warmup",
"get_linear_schedule_with_warmup",
"get_polynomial_decay_schedule_with_warmup",
"get_scheduler",
]
_import_structure["pipelines"].extend(
[
"AudioPipelineOutput",
"AutoPipelineForImage2Image",
"AutoPipelineForInpainting",
"AutoPipelineForText2Image",
"ConsistencyModelPipeline",
"DanceDiffusionPipeline",
"DDIMPipeline",
"DDPMPipeline",
"DiffusionPipeline",
"DiTPipeline",
"ImagePipelineOutput",
"KarrasVePipeline",
"LDMPipeline",
"LDMSuperResolutionPipeline",
"PNDMPipeline",
"RePaintPipeline",
"ScoreSdeVePipeline",
"StableDiffusionMixin",
]
)
_import_structure["quantizers"] = ["DiffusersQuantizer"]
_import_structure["schedulers"].extend(
[
"AmusedScheduler",
"CMStochasticIterativeScheduler",
"CogVideoXDDIMScheduler",
"CogVideoXDPMScheduler",
"DDIMInverseScheduler",
"DDIMParallelScheduler",
"DDIMScheduler",
"DDPMParallelScheduler",
"DDPMScheduler",
"DDPMWuerstchenScheduler",
"DEISMultistepScheduler",
"DPMSolverMultistepInverseScheduler",
"DPMSolverMultistepScheduler",
"DPMSolverSinglestepScheduler",
"EDMDPMSolverMultistepScheduler",
"EDMEulerScheduler",
"EulerAncestralDiscreteScheduler",
"EulerDiscreteScheduler",
"FlowMatchEulerDiscreteScheduler",
"FlowMatchHeunDiscreteScheduler",
"HeunDiscreteScheduler",
"IPNDMScheduler",
"KarrasVeScheduler",
"KDPM2AncestralDiscreteScheduler",
"KDPM2DiscreteScheduler",
"LCMScheduler",
"PNDMScheduler",
"RePaintScheduler",
"SASolverScheduler",
"SchedulerMixin",
"SCMScheduler",
"ScoreSdeVeScheduler",
"TCDScheduler",
"UnCLIPScheduler",
"UniPCMultistepScheduler",
"VQDiffusionScheduler",
]
)
_import_structure["training_utils"] = ["EMAModel"]
try:
if not (is_torch_available() and is_scipy_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils import dummy_torch_and_scipy_objects # noqa F403
_import_structure["utils.dummy_torch_and_scipy_objects"] = [
name for name in dir(dummy_torch_and_scipy_objects) if not name.startswith("_")
]
else:
_import_structure["schedulers"].extend(["LMSDiscreteScheduler"])
try:
if not (is_torch_available() and is_torchsde_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils import dummy_torch_and_torchsde_objects # noqa F403
_import_structure["utils.dummy_torch_and_torchsde_objects"] = [
name for name in dir(dummy_torch_and_torchsde_objects) if not name.startswith("_")
]
else:
_import_structure["schedulers"].extend(["CosineDPMSolverMultistepScheduler", "DPMSolverSDEScheduler"])
try:
if not (is_torch_available() and is_transformers_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils import dummy_torch_and_transformers_objects # noqa F403
_import_structure["utils.dummy_torch_and_transformers_objects"] = [
name for name in dir(dummy_torch_and_transformers_objects) if not name.startswith("_")
]
else:
_import_structure["pipelines"].extend(
[
"AllegroPipeline",
"AltDiffusionImg2ImgPipeline",
"AltDiffusionPipeline",
"AmusedImg2ImgPipeline",
"AmusedInpaintPipeline",
"AmusedPipeline",
"AnimateDiffControlNetPipeline",
"AnimateDiffPAGPipeline",
"AnimateDiffPipeline",
"AnimateDiffSDXLPipeline",
"AnimateDiffSparseControlNetPipeline",
"AnimateDiffVideoToVideoControlNetPipeline",
"AnimateDiffVideoToVideoPipeline",
"AudioLDM2Pipeline",
"AudioLDM2ProjectionModel",
"AudioLDM2UNet2DConditionModel",
"AudioLDMPipeline",
"AuraFlowPipeline",
"BlipDiffusionControlNetPipeline",
"BlipDiffusionPipeline",
"CLIPImageProjection",
"CogVideoXFunControlPipeline",
"CogVideoXImageToVideoPipeline",
"CogVideoXPipeline",
"CogVideoXVideoToVideoPipeline",
"CogView3PlusPipeline",
"CogView4ControlPipeline",
"CogView4Pipeline",
"ConsisIDPipeline",
"CycleDiffusionPipeline",
"EasyAnimateControlPipeline",
"EasyAnimateInpaintPipeline",
"EasyAnimatePipeline",
"FluxControlImg2ImgPipeline",
"FluxControlInpaintPipeline",
"FluxControlNetImg2ImgPipeline",
"FluxControlNetInpaintPipeline",
"FluxControlNetPipeline",
"FluxControlPipeline",
"FluxFillPipeline",
"FluxImg2ImgPipeline",
"FluxInpaintPipeline",
"FluxPipeline",
"FluxPriorReduxPipeline",
"HunyuanDiTControlNetPipeline",
"HunyuanDiTPAGPipeline",
"HunyuanDiTPipeline",
"HunyuanSkyreelsImageToVideoPipeline",
"HunyuanVideoImageToVideoPipeline",
"HunyuanVideoPipeline",
"I2VGenXLPipeline",
"IFImg2ImgPipeline",
"IFImg2ImgSuperResolutionPipeline",
"IFInpaintingPipeline",
"IFInpaintingSuperResolutionPipeline",
"IFPipeline",
"IFSuperResolutionPipeline",
"ImageTextPipelineOutput",
"Kandinsky3Img2ImgPipeline",
"Kandinsky3Pipeline",
"KandinskyCombinedPipeline",
"KandinskyImg2ImgCombinedPipeline",
"KandinskyImg2ImgPipeline",
"KandinskyInpaintCombinedPipeline",
"KandinskyInpaintPipeline",
"KandinskyPipeline",
"KandinskyPriorPipeline",
"KandinskyV22CombinedPipeline",
"KandinskyV22ControlnetImg2ImgPipeline",
"KandinskyV22ControlnetPipeline",
"KandinskyV22Img2ImgCombinedPipeline",
"KandinskyV22Img2ImgPipeline",
"KandinskyV22InpaintCombinedPipeline",
"KandinskyV22InpaintPipeline",
"KandinskyV22Pipeline",
"KandinskyV22PriorEmb2EmbPipeline",
"KandinskyV22PriorPipeline",
"LatentConsistencyModelImg2ImgPipeline",
"LatentConsistencyModelPipeline",
"LattePipeline",
"LDMTextToImagePipeline",
"LEditsPPPipelineStableDiffusion",
"LEditsPPPipelineStableDiffusionXL",
"LTXConditionPipeline",
"LTXImageToVideoPipeline",
"LTXPipeline",
"Lumina2Pipeline",
"Lumina2Text2ImgPipeline",
"LuminaPipeline",
"LuminaText2ImgPipeline",
"MarigoldDepthPipeline",
"MarigoldIntrinsicsPipeline",
"MarigoldNormalsPipeline",
"MochiPipeline",
"MusicLDMPipeline",
"OmniGenPipeline",
"PaintByExamplePipeline",
"PIAPipeline",
"PixArtAlphaPipeline",
"PixArtSigmaPAGPipeline",
"PixArtSigmaPipeline",
"ReduxImageEncoder",
"SanaPAGPipeline",
"SanaPipeline",
"SanaSprintPipeline",
"SemanticStableDiffusionPipeline",
"ShapEImg2ImgPipeline",
"ShapEPipeline",
"StableAudioPipeline",
"StableAudioProjectionModel",
"StableCascadeCombinedPipeline",
"StableCascadeDecoderPipeline",
"StableCascadePriorPipeline",
"StableDiffusion3ControlNetInpaintingPipeline",
"StableDiffusion3ControlNetPipeline",
"StableDiffusion3Img2ImgPipeline",
"StableDiffusion3InpaintPipeline",
"StableDiffusion3PAGImg2ImgPipeline",
"StableDiffusion3PAGImg2ImgPipeline",
"StableDiffusion3PAGPipeline",
"StableDiffusion3Pipeline",
"StableDiffusionAdapterPipeline",
"StableDiffusionAttendAndExcitePipeline",
"StableDiffusionControlNetImg2ImgPipeline",
"StableDiffusionControlNetInpaintPipeline",
"StableDiffusionControlNetPAGInpaintPipeline",
"StableDiffusionControlNetPAGPipeline",
"StableDiffusionControlNetPipeline",
"StableDiffusionControlNetXSPipeline",
"StableDiffusionDepth2ImgPipeline",
"StableDiffusionDiffEditPipeline",
"StableDiffusionGLIGENPipeline",
"StableDiffusionGLIGENTextImagePipeline",
"StableDiffusionImageVariationPipeline",
"StableDiffusionImg2ImgPipeline",
"StableDiffusionInpaintPipeline",
"StableDiffusionInpaintPipelineLegacy",
"StableDiffusionInstructPix2PixPipeline",
"StableDiffusionLatentUpscalePipeline",
"StableDiffusionLDM3DPipeline",
"StableDiffusionModelEditingPipeline",
"StableDiffusionPAGImg2ImgPipeline",
"StableDiffusionPAGInpaintPipeline",
"StableDiffusionPAGPipeline",
"StableDiffusionPanoramaPipeline",
"StableDiffusionParadigmsPipeline",
"StableDiffusionPipeline",
"StableDiffusionPipelineSafe",
"StableDiffusionPix2PixZeroPipeline",
"StableDiffusionSAGPipeline",
"StableDiffusionUpscalePipeline",
"StableDiffusionXLAdapterPipeline",
"StableDiffusionXLControlNetImg2ImgPipeline",
"StableDiffusionXLControlNetInpaintPipeline",
"StableDiffusionXLControlNetPAGImg2ImgPipeline",
"StableDiffusionXLControlNetPAGPipeline",
"StableDiffusionXLControlNetPipeline",
"StableDiffusionXLControlNetUnionImg2ImgPipeline",
"StableDiffusionXLControlNetUnionInpaintPipeline",
"StableDiffusionXLControlNetUnionPipeline",
"StableDiffusionXLControlNetXSPipeline",
"StableDiffusionXLImg2ImgPipeline",
"StableDiffusionXLInpaintPipeline",
"StableDiffusionXLInstructPix2PixPipeline",
"StableDiffusionXLPAGImg2ImgPipeline",
"StableDiffusionXLPAGInpaintPipeline",
"StableDiffusionXLPAGPipeline",
"StableDiffusionXLPipeline",
"StableUnCLIPImg2ImgPipeline",
"StableUnCLIPPipeline",
"StableVideoDiffusionPipeline",
"TextToVideoSDPipeline",
"TextToVideoZeroPipeline",
"TextToVideoZeroSDXLPipeline",
"UnCLIPImageVariationPipeline",
"UnCLIPPipeline",
"UniDiffuserModel",
"UniDiffuserPipeline",
"UniDiffuserTextDecoder",
"VersatileDiffusionDualGuidedPipeline",
"VersatileDiffusionImageVariationPipeline",
"VersatileDiffusionPipeline",
"VersatileDiffusionTextToImagePipeline",
"VideoToVideoSDPipeline",
"VQDiffusionPipeline",
"WanImageToVideoPipeline",
"WanPipeline",
"WuerstchenCombinedPipeline",
"WuerstchenDecoderPipeline",
"WuerstchenPriorPipeline",
]
)
try:
if not (is_torch_available() and is_transformers_available() and is_k_diffusion_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils import dummy_torch_and_transformers_and_k_diffusion_objects # noqa F403
_import_structure["utils.dummy_torch_and_transformers_and_k_diffusion_objects"] = [
name for name in dir(dummy_torch_and_transformers_and_k_diffusion_objects) if not name.startswith("_")
]
else:
_import_structure["pipelines"].extend(["StableDiffusionKDiffusionPipeline", "StableDiffusionXLKDiffusionPipeline"])
try:
if not (is_torch_available() and is_transformers_available() and is_sentencepiece_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils import dummy_torch_and_transformers_and_sentencepiece_objects # noqa F403
_import_structure["utils.dummy_torch_and_transformers_and_sentencepiece_objects"] = [
name for name in dir(dummy_torch_and_transformers_and_sentencepiece_objects) if not name.startswith("_")
]
else:
_import_structure["pipelines"].extend(["KolorsImg2ImgPipeline", "KolorsPAGPipeline", "KolorsPipeline"])
try:
if not (is_torch_available() and is_transformers_available() and is_onnx_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils import dummy_torch_and_transformers_and_onnx_objects # noqa F403
_import_structure["utils.dummy_torch_and_transformers_and_onnx_objects"] = [
name for name in dir(dummy_torch_and_transformers_and_onnx_objects) if not name.startswith("_")
]
else:
_import_structure["pipelines"].extend(
[
"OnnxStableDiffusionImg2ImgPipeline",
"OnnxStableDiffusionInpaintPipeline",
"OnnxStableDiffusionInpaintPipelineLegacy",
"OnnxStableDiffusionPipeline",
"OnnxStableDiffusionUpscalePipeline",
"StableDiffusionOnnxPipeline",
]
)
try:
if not (is_torch_available() and is_librosa_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils import dummy_torch_and_librosa_objects # noqa F403
_import_structure["utils.dummy_torch_and_librosa_objects"] = [
name for name in dir(dummy_torch_and_librosa_objects) if not name.startswith("_")
]
else:
_import_structure["pipelines"].extend(["AudioDiffusionPipeline", "Mel"])
try:
if not (is_transformers_available() and is_torch_available() and is_note_seq_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils import dummy_transformers_and_torch_and_note_seq_objects # noqa F403
_import_structure["utils.dummy_transformers_and_torch_and_note_seq_objects"] = [
name for name in dir(dummy_transformers_and_torch_and_note_seq_objects) if not name.startswith("_")
]
else:
_import_structure["pipelines"].extend(["SpectrogramDiffusionPipeline"])
try:
if not is_flax_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils import dummy_flax_objects # noqa F403
_import_structure["utils.dummy_flax_objects"] = [
name for name in dir(dummy_flax_objects) if not name.startswith("_")
]
else:
_import_structure["models.controlnets.controlnet_flax"] = ["FlaxControlNetModel"]
_import_structure["models.modeling_flax_utils"] = ["FlaxModelMixin"]
_import_structure["models.unets.unet_2d_condition_flax"] = ["FlaxUNet2DConditionModel"]
_import_structure["models.vae_flax"] = ["FlaxAutoencoderKL"]
_import_structure["pipelines"].extend(["FlaxDiffusionPipeline"])
_import_structure["schedulers"].extend(
[
"FlaxDDIMScheduler",
"FlaxDDPMScheduler",
"FlaxDPMSolverMultistepScheduler",
"FlaxEulerDiscreteScheduler",
"FlaxKarrasVeScheduler",
"FlaxLMSDiscreteScheduler",
"FlaxPNDMScheduler",
"FlaxSchedulerMixin",
"FlaxScoreSdeVeScheduler",
]
)
try:
if not (is_flax_available() and is_transformers_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils import dummy_flax_and_transformers_objects # noqa F403
_import_structure["utils.dummy_flax_and_transformers_objects"] = [
name for name in dir(dummy_flax_and_transformers_objects) if not name.startswith("_")
]
else:
_import_structure["pipelines"].extend(
[
"FlaxStableDiffusionControlNetPipeline",
"FlaxStableDiffusionImg2ImgPipeline",
"FlaxStableDiffusionInpaintPipeline",
"FlaxStableDiffusionPipeline",
"FlaxStableDiffusionXLPipeline",
]
)
try:
if not (is_note_seq_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils import dummy_note_seq_objects # noqa F403
_import_structure["utils.dummy_note_seq_objects"] = [
name for name in dir(dummy_note_seq_objects) if not name.startswith("_")
]
else:
_import_structure["pipelines"].extend(["MidiProcessor"])
if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
from .configuration_utils import ConfigMixin
try:
if not is_bitsandbytes_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils.dummy_bitsandbytes_objects import *
else:
from .quantizers.quantization_config import BitsAndBytesConfig
try:
if not is_gguf_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils.dummy_gguf_objects import *
else:
from .quantizers.quantization_config import GGUFQuantizationConfig
try:
if not is_torchao_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils.dummy_torchao_objects import *
else:
from .quantizers.quantization_config import TorchAoConfig
try:
if not is_optimum_quanto_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils.dummy_optimum_quanto_objects import *
else:
from .quantizers.quantization_config import QuantoConfig
try:
if not is_onnx_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils.dummy_onnx_objects import * # noqa F403
else:
from .pipelines import OnnxRuntimeModel
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils.dummy_pt_objects import * # noqa F403
else:
from .hooks import (
FasterCacheConfig,
HookRegistry,
PyramidAttentionBroadcastConfig,
apply_faster_cache,
apply_pyramid_attention_broadcast,
)
from .models import (
AllegroTransformer3DModel,
AsymmetricAutoencoderKL,
AuraFlowTransformer2DModel,
AutoencoderDC,
AutoencoderKL,
AutoencoderKLAllegro,
AutoencoderKLCogVideoX,
AutoencoderKLHunyuanVideo,
AutoencoderKLLTXVideo,
AutoencoderKLMagvit,
AutoencoderKLMochi,
AutoencoderKLTemporalDecoder,
AutoencoderKLWan,
AutoencoderOobleck,
AutoencoderTiny,
CacheMixin,
CogVideoXTransformer3DModel,
CogView3PlusTransformer2DModel,
CogView4Transformer2DModel,
ConsisIDTransformer3DModel,
ConsistencyDecoderVAE,
ControlNetModel,
ControlNetUnionModel,
ControlNetXSAdapter,
DiTTransformer2DModel,
EasyAnimateTransformer3DModel,
FluxControlNetModel,
FluxMultiControlNetModel,
FluxTransformer2DModel,
HunyuanDiT2DControlNetModel,
HunyuanDiT2DModel,
HunyuanDiT2DMultiControlNetModel,
HunyuanVideoTransformer3DModel,
I2VGenXLUNet,
Kandinsky3UNet,
LatteTransformer3DModel,
LTXVideoTransformer3DModel,
Lumina2Transformer2DModel,
LuminaNextDiT2DModel,
MochiTransformer3DModel,
ModelMixin,
MotionAdapter,
MultiAdapter,
MultiControlNetModel,
OmniGenTransformer2DModel,
PixArtTransformer2DModel,
PriorTransformer,
SanaTransformer2DModel,
SD3ControlNetModel,
SD3MultiControlNetModel,
SD3Transformer2DModel,
SparseControlNetModel,
StableAudioDiTModel,
T2IAdapter,
T5FilmDecoder,
Transformer2DModel,
UNet1DModel,
UNet2DConditionModel,
UNet2DModel,
UNet3DConditionModel,
UNetControlNetXSModel,
UNetMotionModel,
UNetSpatioTemporalConditionModel,
UVit2DModel,
VQModel,
WanTransformer3DModel,
)
from .optimization import (
get_constant_schedule,
get_constant_schedule_with_warmup,
get_cosine_schedule_with_warmup,
get_cosine_with_hard_restarts_schedule_with_warmup,
get_linear_schedule_with_warmup,
get_polynomial_decay_schedule_with_warmup,
get_scheduler,
)
from .pipelines import (
AudioPipelineOutput,
AutoPipelineForImage2Image,
AutoPipelineForInpainting,
AutoPipelineForText2Image,
BlipDiffusionControlNetPipeline,
BlipDiffusionPipeline,
CLIPImageProjection,
ConsistencyModelPipeline,
DanceDiffusionPipeline,
DDIMPipeline,
DDPMPipeline,
DiffusionPipeline,
DiTPipeline,
ImagePipelineOutput,
KarrasVePipeline,
LDMPipeline,
LDMSuperResolutionPipeline,
PNDMPipeline,
RePaintPipeline,
ScoreSdeVePipeline,
StableDiffusionMixin,
)
from .quantizers import DiffusersQuantizer
from .schedulers import (
AmusedScheduler,
CMStochasticIterativeScheduler,
CogVideoXDDIMScheduler,
CogVideoXDPMScheduler,
DDIMInverseScheduler,
DDIMParallelScheduler,
DDIMScheduler,
DDPMParallelScheduler,
DDPMScheduler,
DDPMWuerstchenScheduler,
DEISMultistepScheduler,
DPMSolverMultistepInverseScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
EDMDPMSolverMultistepScheduler,
EDMEulerScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
FlowMatchEulerDiscreteScheduler,
FlowMatchHeunDiscreteScheduler,
HeunDiscreteScheduler,
IPNDMScheduler,
KarrasVeScheduler,
KDPM2AncestralDiscreteScheduler,
KDPM2DiscreteScheduler,
LCMScheduler,
PNDMScheduler,
RePaintScheduler,
SASolverScheduler,
SchedulerMixin,
SCMScheduler,
ScoreSdeVeScheduler,
TCDScheduler,
UnCLIPScheduler,
UniPCMultistepScheduler,
VQDiffusionScheduler,
)
from .training_utils import EMAModel
try:
if not (is_torch_available() and is_scipy_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils.dummy_torch_and_scipy_objects import * # noqa F403
else:
from .schedulers import LMSDiscreteScheduler
try:
if not (is_torch_available() and is_torchsde_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils.dummy_torch_and_torchsde_objects import * # noqa F403
else:
from .schedulers import CosineDPMSolverMultistepScheduler, DPMSolverSDEScheduler
try:
if not (is_torch_available() and is_transformers_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from .utils.dummy_torch_and_transformers_objects import * # noqa F403
else:
from .pipelines import (
AllegroPipeline,
AltDiffusionImg2ImgPipeline,
AltDiffusionPipeline,
AmusedImg2ImgPipeline,
AmusedInpaintPipeline,
AmusedPipeline,
AnimateDiffControlNetPipeline,
AnimateDiffPAGPipeline,
AnimateDiffPipeline,
AnimateDiffSDXLPipeline,
AnimateDiffSparseControlNetPipeline,
AnimateDiffVideoToVideoControlNetPipeline,
AnimateDiffVideoToVideoPipeline,
AudioLDM2Pipeline,
AudioLDM2ProjectionModel,
AudioLDM2UNet2DConditionModel,
AudioLDMPipeline,
AuraFlowPipeline,
CLIPImageProjection,
CogVideoXFunControlPipeline,
CogVideoXImageToVideoPipeline,
CogVideoXPipeline,
CogVideoXVideoToVideoPipeline,
CogView3PlusPipeline,
CogView4ControlPipeline,
CogView4Pipeline,
ConsisIDPipeline,
CycleDiffusionPipeline,
EasyAnimateControlPipeline,
EasyAnimateInpaintPipeline,
EasyAnimatePipeline,
FluxControlImg2ImgPipeline,
FluxControlInpaintPipeline,
FluxControlNetImg2ImgPipeline,
FluxControlNetInpaintPipeline,
FluxControlNetPipeline,
FluxControlPipeline,
FluxFillPipeline,
FluxImg2ImgPipeline,
FluxInpaintPipeline,
FluxPipeline,
FluxPriorReduxPipeline,
HunyuanDiTControlNetPipeline,
HunyuanDiTPAGPipeline,
HunyuanDiTPipeline,
HunyuanSkyreelsImageToVideoPipeline,
HunyuanVideoImageToVideoPipeline,
HunyuanVideoPipeline,
I2VGenXLPipeline,
IFImg2ImgPipeline,
IFImg2ImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
ImageTextPipelineOutput,
Kandinsky3Img2ImgPipeline,
Kandinsky3Pipeline,
KandinskyCombinedPipeline,
KandinskyImg2ImgCombinedPipeline,
KandinskyImg2ImgPipeline,
KandinskyInpaintCombinedPipeline,
KandinskyInpaintPipeline,
KandinskyPipeline,
KandinskyPriorPipeline,
KandinskyV22CombinedPipeline,
KandinskyV22ControlnetImg2ImgPipeline,
KandinskyV22ControlnetPipeline,
KandinskyV22Img2ImgCombinedPipeline,
KandinskyV22Img2ImgPipeline,
KandinskyV22InpaintCombinedPipeline,
KandinskyV22InpaintPipeline,
KandinskyV22Pipeline,
KandinskyV22PriorEmb2EmbPipeline,
KandinskyV22PriorPipeline,
LatentConsistencyModelImg2ImgPipeline,
LatentConsistencyModelPipeline,
LattePipeline,
LDMTextToImagePipeline,
LEditsPPPipelineStableDiffusion,
LEditsPPPipelineStableDiffusionXL,
LTXConditionPipeline,
LTXImageToVideoPipeline,
LTXPipeline,
Lumina2Pipeline,
Lumina2Text2ImgPipeline,
LuminaPipeline,
LuminaText2ImgPipeline,
MarigoldDepthPipeline,
MarigoldIntrinsicsPipeline,
MarigoldNormalsPipeline,
MochiPipeline,
MusicLDMPipeline,
OmniGenPipeline,
PaintByExamplePipeline,
PIAPipeline,
PixArtAlphaPipeline,
PixArtSigmaPAGPipeline,
PixArtSigmaPipeline,
ReduxImageEncoder,
SanaPAGPipeline,
SanaPipeline,
SanaSprintPipeline,
SemanticStableDiffusionPipeline,
ShapEImg2ImgPipeline,
ShapEPipeline,
StableAudioPipeline,
StableAudioProjectionModel,
StableCascadeCombinedPipeline,
StableCascadeDecoderPipeline,
StableCascadePriorPipeline,
StableDiffusion3ControlNetInpaintingPipeline,
StableDiffusion3ControlNetPipeline,
StableDiffusion3Img2ImgPipeline,
StableDiffusion3InpaintPipeline,
StableDiffusion3PAGImg2ImgPipeline,
StableDiffusion3PAGPipeline,
StableDiffusion3Pipeline,
StableDiffusionAdapterPipeline,
StableDiffusionAttendAndExcitePipeline,