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DN6
2025-04-17 00:29:31 +05:30
parent 59f1b7b1c8
commit c68db8014f
85 changed files with 1090 additions and 374 deletions
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76
src/diffusers/pipelines/__init__.py
View File

@@ -115,10 +115,43 @@ else:
"VersatileDiffusionImageVariationPipeline",
"VersatileDiffusionPipeline",
"VersatileDiffusionTextToImagePipeline",
"AmusedImg2ImgPipeline",
"AmusedInpaintPipeline",
"AmusedPipeline",
"StableDiffusionControlNetXSPipeline",
"StableDiffusionXLControlNetXSPipeline",
"I2VGenXLPipeline",
"LattePipeline",
"MusicLDMPipeline",
"PaintByExamplePipeline",
"PIAPipeline",
"SemanticStableDiffusionPipeline",
"ShapEImg2ImgPipeline",
"ShapEPipeline",
"StableDiffusionAttendAndExcitePipeline",
"StableDiffusionPipelineSafe",
"StableDiffusionSAGPipeline",
"StableDiffusionGLIGENPipeline",
"StableDiffusionGLIGENTextImagePipeline",
"StableDiffusionDiffEditPipeline",
"StableDiffusionLDM3DPipeline",
"StableDiffusionPanoramaPipeline",
"TextToVideoSDPipeline",
"TextToVideoZeroPipeline",
"TextToVideoZeroSDXLPipeline",
"VideoToVideoSDPipeline",
"UnCLIPImageVariationPipeline",
"UnCLIPPipeline",
"ImageTextPipelineOutput",
"UniDiffuserModel",
"UniDiffuserPipeline",
"UniDiffuserTextDecoder",
"WuerstchenCombinedPipeline",
"WuerstchenDecoderPipeline",
"WuerstchenPriorPipeline",
]
)
_import_structure["allegro"] = ["AllegroPipeline"]
_import_structure["amused"] = ["AmusedImg2ImgPipeline", "AmusedInpaintPipeline", "AmusedPipeline"]
_import_structure["animatediff"] = [
"AnimateDiffPipeline",
"AnimateDiffControlNetPipeline",
@@ -191,12 +224,6 @@ else:
"SanaPAGPipeline",
]
)
_import_structure["controlnet_xs"].extend(
[
"StableDiffusionControlNetXSPipeline",
"StableDiffusionXLControlNetXSPipeline",
]
)
_import_structure["controlnet_hunyuandit"].extend(
[
"HunyuanDiTControlNetPipeline",
@@ -264,7 +291,6 @@ else:
"LEditsPPPipelineStableDiffusionXL",
]
)
_import_structure["latte"] = ["LattePipeline"]
_import_structure["ltx"] = ["LTXPipeline", "LTXImageToVideoPipeline", "LTXConditionPipeline"]
_import_structure["lumina"] = ["LuminaPipeline", "LuminaText2ImgPipeline"]
_import_structure["lumina2"] = ["Lumina2Pipeline", "Lumina2Text2ImgPipeline"]
@@ -276,14 +302,9 @@ else:
]
)
_import_structure["mochi"] = ["MochiPipeline"]
_import_structure["musicldm"] = ["MusicLDMPipeline"]
_import_structure["omnigen"] = ["OmniGenPipeline"]
_import_structure["paint_by_example"] = ["PaintByExamplePipeline"]
_import_structure["pia"] = ["PIAPipeline"]
_import_structure["pixart_alpha"] = ["PixArtAlphaPipeline", "PixArtSigmaPipeline"]
_import_structure["sana"] = ["SanaPipeline", "SanaSprintPipeline", "SanaControlNetPipeline"]
_import_structure["semantic_stable_diffusion"] = ["SemanticStableDiffusionPipeline"]
_import_structure["shap_e"] = ["ShapEImg2ImgPipeline", "ShapEPipeline"]
_import_structure["stable_audio"] = [
"StableAudioProjectionModel",
"StableAudioPipeline",
@@ -315,13 +336,6 @@ else:
"StableDiffusion3Img2ImgPipeline",
"StableDiffusion3InpaintPipeline",
]
_import_structure["stable_diffusion_attend_and_excite"] = ["StableDiffusionAttendAndExcitePipeline"]
_import_structure["stable_diffusion_safe"] = ["StableDiffusionPipelineSafe"]
_import_structure["stable_diffusion_sag"] = ["StableDiffusionSAGPipeline"]
_import_structure["stable_diffusion_gligen"] = [
"StableDiffusionGLIGENPipeline",
"StableDiffusionGLIGENTextImagePipeline",
]
_import_structure["stable_video_diffusion"] = ["StableVideoDiffusionPipeline"]
_import_structure["stable_diffusion_xl"].extend(
[
@@ -331,32 +345,10 @@ else:
"StableDiffusionXLPipeline",
]
)
_import_structure["stable_diffusion_diffedit"] = ["StableDiffusionDiffEditPipeline"]
_import_structure["stable_diffusion_ldm3d"] = ["StableDiffusionLDM3DPipeline"]
_import_structure["stable_diffusion_panorama"] = ["StableDiffusionPanoramaPipeline"]
_import_structure["t2i_adapter"] = [
"StableDiffusionAdapterPipeline",
"StableDiffusionXLAdapterPipeline",
]
_import_structure["text_to_video_synthesis"] = [
"TextToVideoSDPipeline",
"TextToVideoZeroPipeline",
"TextToVideoZeroSDXLPipeline",
"VideoToVideoSDPipeline",
]
_import_structure["i2vgen_xl"] = ["I2VGenXLPipeline"]
_import_structure["unclip"] = ["UnCLIPImageVariationPipeline", "UnCLIPPipeline"]
_import_structure["unidiffuser"] = [
"ImageTextPipelineOutput",
"UniDiffuserModel",
"UniDiffuserPipeline",
"UniDiffuserTextDecoder",
]
_import_structure["wuerstchen"] = [
"WuerstchenCombinedPipeline",
"WuerstchenDecoderPipeline",
"WuerstchenPriorPipeline",
]
_import_structure["wan"] = ["WanPipeline", "WanImageToVideoPipeline", "WanVideoToVideoPipeline"]
try:
if not is_onnx_available():

120
src/diffusers/pipelines/deprecated/__init__.py
View File

@@ -1,4 +1,8 @@
from typing import TYPE_CHECKING
import functools
import inspect
import warnings
import sys
from ...utils import (
DIFFUSERS_SLOW_IMPORT,
@@ -12,6 +16,27 @@ from ...utils import (
)
# Custom Lazy Module for deprecated pipelines that shows a warning
class _DeprecatedLazyModule(_LazyModule):
"""
Module class that surfaces all objects but only performs associated imports when the objects are requested,
and shows deprecation warnings when any of its attributes are accessed.
"""
def __getattr__(self, name):
# Regular attribute access - first check if it's supposed to be loaded
if name in self._modules or name in self._class_to_module:
# Only warn for actual pipeline components, not utility functions
warnings.warn(
f"{name} is deprecated and will no longer be maintained.",
FutureWarning,
stacklevel=2,
)
# Use the standard lazy module behavior to load the attribute
return super().__getattr__(name)
_dummy_objects = {}
_import_structure = {}
@@ -23,6 +48,7 @@ except OptionalDependencyNotAvailable:
_dummy_objects.update(get_objects_from_module(dummy_pt_objects))
else:
_import_structure["dance_diffusion"] = ["DanceDiffusionPipeline"]
_import_structure["latent_diffusion_uncond"] = ["LDMPipeline"]
_import_structure["pndm"] = ["PNDMPipeline"]
_import_structure["repaint"] = ["RePaintPipeline"]
@@ -42,6 +68,55 @@ else:
"AltDiffusionPipeline",
"AltDiffusionPipelineOutput",
]
_import_structure["amused"] = ["AmusedPipeline", "AmusedImg2ImgPipeline", "AmusedInpaintPipeline"]
_import_structure["audioldm"] = ["AudioLDMPipeline"]
_import_structure["controlnet_xs"] = [
"StableDiffusionControlNetXSPipeline",
"StableDiffusionXLControlNetXSPipeline",
]
_import_structure["i2vgen_xl"] = ["I2VGenXLPipeline"]
_import_structure["latte"] = ["LattePipeline"]
_import_structure["musicldm"] = ["MusicLDMPipeline"]
_import_structure["paint_by_example"] = ["PaintByExamplePipeline"]
_import_structure["pia"] = ["PIAPipeline"]
_import_structure["semantic_stable_diffusion"] = ["SemanticStableDiffusionPipeline"]
_import_structure["shap_e"] = [
"ShapEPipeline",
"ShapEImg2ImgPipeline",
]
_import_structure["stable_diffusion_attend_and_excite"] = ["StableDiffusionAttendAndExcitePipeline"]
_import_structure["stable_diffusion_diffedit"] = ["StableDiffusionDiffEditPipeline"]
_import_structure["stable_diffusion_gligen"] = [
"StableDiffusionGLIGENPipeline",
"StableDiffusionGLIGENTextImagePipeline",
]
_import_structure["stable_diffusion_k_diffusion"] = [
"StableDiffusionKDiffusionPipeline",
"StableDiffusionXLKDiffusionPipeline",
]
_import_structure["stable_diffusion_ldm3d"] = ["StableDiffusionLDM3DPipeline"]
_import_structure["stable_diffusion_panorama"] = ["StableDiffusionPanoramaPipeline"]
_import_structure["stable_diffusion_safe"] = ["StableDiffusionPipelineSafe"]
_import_structure["stable_diffusion_sag"] = ["StableDiffusionSAGPipeline"]
_import_structure["stable_diffusion_variants"] = [
"CycleDiffusionPipeline",
"StableDiffusionInpaintPipelineLegacy",
"StableDiffusionPix2PixZeroPipeline",
"StableDiffusionParadigmsPipeline",
"StableDiffusionModelEditingPipeline",
]
_import_structure["text_to_video_synthesis"] = [
"TextToVideoSDPipeline",
"TextToVideoZeroPipeline",
"TextToVideoZeroSDXLPipeline",
]
_import_structure["unclip"] = [
"UnCLIPPipeline",
"UnCLIPImageVariationPipeline",
]
_import_structure["unidiffuser"] = [
"UniDiffuserPipeline",
]
_import_structure["versatile_diffusion"] = [
"VersatileDiffusionDualGuidedPipeline",
"VersatileDiffusionImageVariationPipeline",
@@ -49,12 +124,10 @@ else:
"VersatileDiffusionTextToImagePipeline",
]
_import_structure["vq_diffusion"] = ["VQDiffusionPipeline"]
_import_structure["stable_diffusion_variants"] = [
"CycleDiffusionPipeline",
"StableDiffusionInpaintPipelineLegacy",
"StableDiffusionPix2PixZeroPipeline",
"StableDiffusionParadigmsPipeline",
"StableDiffusionModelEditingPipeline",
_import_structure["wuerstchen"] = [
"WuerstchenCombinedPipeline",
"WuerstchenDecoderPipeline",
"WuerstchenPriorPipeline",
]
try:
@@ -88,6 +161,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
from ...utils.dummy_pt_objects import *
else:
from .dance_diffusion import DanceDiffusionPipeline
from .latent_diffusion_uncond import LDMPipeline
from .pndm import PNDMPipeline
from .repaint import RePaintPipeline
@@ -102,8 +176,26 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
else:
from .alt_diffusion import AltDiffusionImg2ImgPipeline, AltDiffusionPipeline, AltDiffusionPipelineOutput
from .audio_diffusion import AudioDiffusionPipeline, Mel
from .spectrogram_diffusion import SpectrogramDiffusionPipeline
from .audioldm import AudioLDMPipeline
from .controlnet_xs import StableDiffusionControlNetXSPipeline, StableDiffusionXLControlNetXSPipeline
from .i2vgen_xl import I2VGenXLPipeline
from .latte import LattePipeline
from .musicldm import MusicLDMPipeline
from .paint_by_example import PaintByExamplePipeline
from .pia import PIAPipeline
from .semantic_stable_diffusion import SemanticStableDiffusionPipeline
from .shap_e import ShapEPipeline, ShapEImg2ImgPipeline
from .stable_diffusion_attend_and_excite import StableDiffusionAttendAndExcitePipeline
from .stable_diffusion_diffedit import StableDiffusionDiffEditPipeline
from .stable_diffusion_gligen import StableDiffusionGLIGENPipeline, StableDiffusionGLIGENTextImagePipeline
from .stable_diffusion_k_diffusion import (
StableDiffusionKDiffusionPipeline,
StableDiffusionXLKDiffusionPipeline,
)
from .stable_diffusion_ldm3d import StableDiffusionLDM3DPipeline
from .stable_diffusion_panorama import StableDiffusionPanoramaPipeline
from .stable_diffusion_safe import StableDiffusionPipelineSafe
from .stable_diffusion_sag import StableDiffusionSAGPipeline
from .stable_diffusion_variants import (
CycleDiffusionPipeline,
StableDiffusionInpaintPipelineLegacy,
@@ -111,7 +203,13 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
StableDiffusionParadigmsPipeline,
StableDiffusionPix2PixZeroPipeline,
)
from .stochastic_karras_ve import KarrasVePipeline
from .text_to_video_synthesis import (
TextToVideoSDPipeline,
TextToVideoZeroPipeline,
TextToVideoZeroSDXLPipeline,
)
from .unclip import UnCLIPPipeline, UnCLIPImageVariationPipeline
from .unidiffuser import UniDiffuserPipeline
from .versatile_diffusion import (
VersatileDiffusionDualGuidedPipeline,
VersatileDiffusionImageVariationPipeline,
@@ -119,6 +217,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
VersatileDiffusionTextToImagePipeline,
)
from .vq_diffusion import VQDiffusionPipeline
from .wuerstchen import WuerstchenCombinedPipeline, WuerstchenDecoderPipeline, WuerstchenPriorPipeline
try:
if not (is_torch_available() and is_librosa_available()):
@@ -143,7 +242,8 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
else:
import sys
sys.modules[__name__] = _LazyModule(
# Use the custom deprecated lazy module instead of the standard one
sys.modules[__name__] = _DeprecatedLazyModule(
__name__,
globals()["__file__"],
_import_structure,

4
src/diffusers/pipelines/deprecated/alt_diffusion/pipeline_alt_diffusion.py
View File

@@ -39,8 +39,8 @@ from ....utils import (
unscale_lora_layers,
)
from ....utils.torch_utils import randn_tensor
from ...pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ...stable_diffusion.safety_checker import StableDiffusionSafetyChecker
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker
from .modeling_roberta_series import RobertaSeriesModelWithTransformation
from .pipeline_output import AltDiffusionPipelineOutput

4
src/diffusers/pipelines/deprecated/alt_diffusion/pipeline_alt_diffusion_img2img.py
View File

@@ -42,8 +42,8 @@ from ....utils import (
unscale_lora_layers,
)
from ....utils.torch_utils import randn_tensor
from ...pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ...stable_diffusion.safety_checker import StableDiffusionSafetyChecker
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker
from .modeling_roberta_series import RobertaSeriesModelWithTransformation
from .pipeline_output import AltDiffusionPipelineOutput

6
src/diffusers/pipelines/amused/__init__.py → src/diffusers/pipelines/deprecated/amused/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -16,7 +16,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import (
from ....utils.dummy_torch_and_transformers_objects import (
AmusedImg2ImgPipeline,
AmusedInpaintPipeline,
AmusedPipeline,
@@ -40,7 +40,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import (
from ....utils.dummy_torch_and_transformers_objects import (
AmusedPipeline,
)
else:

10
src/diffusers/pipelines/amused/pipeline_amused.py → src/diffusers/pipelines/deprecated/amused/pipeline_amused.py
View File

@@ -17,11 +17,11 @@ from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModelWithProjection, CLIPTokenizer
from ...image_processor import VaeImageProcessor
from ...models import UVit2DModel, VQModel
from ...schedulers import AmusedScheduler
from ...utils import is_torch_xla_available, replace_example_docstring
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from ....image_processor import VaeImageProcessor
from ....models import UVit2DModel, VQModel
from ....schedulers import AmusedScheduler
from ....utils import is_torch_xla_available, replace_example_docstring
from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
if is_torch_xla_available():

10
src/diffusers/pipelines/amused/pipeline_amused_img2img.py → src/diffusers/pipelines/deprecated/amused/pipeline_amused_img2img.py
View File

@@ -17,11 +17,11 @@ from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModelWithProjection, CLIPTokenizer
from ...image_processor import PipelineImageInput, VaeImageProcessor
from ...models import UVit2DModel, VQModel
from ...schedulers import AmusedScheduler
from ...utils import is_torch_xla_available, replace_example_docstring
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from ....image_processor import PipelineImageInput, VaeImageProcessor
from ....models import UVit2DModel, VQModel
from ....schedulers import AmusedScheduler
from ....utils import is_torch_xla_available, replace_example_docstring
from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
if is_torch_xla_available():

10
src/diffusers/pipelines/amused/pipeline_amused_inpaint.py → src/diffusers/pipelines/deprecated/amused/pipeline_amused_inpaint.py
View File

@@ -18,11 +18,11 @@ from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModelWithProjection, CLIPTokenizer
from ...image_processor import PipelineImageInput, VaeImageProcessor
from ...models import UVit2DModel, VQModel
from ...schedulers import AmusedScheduler
from ...utils import is_torch_xla_available, replace_example_docstring
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from ....image_processor import PipelineImageInput, VaeImageProcessor
from ....models import UVit2DModel, VQModel
from ....schedulers import AmusedScheduler
from ....utils import is_torch_xla_available, replace_example_docstring
from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
if is_torch_xla_available():

2
src/diffusers/pipelines/deprecated/audio_diffusion/pipeline_audio_diffusion.py
View File

@@ -23,7 +23,7 @@ from PIL import Image
from ....models import AutoencoderKL, UNet2DConditionModel
from ....schedulers import DDIMScheduler, DDPMScheduler
from ....utils.torch_utils import randn_tensor
from ...pipeline_utils import AudioPipelineOutput, BaseOutput, DiffusionPipeline, ImagePipelineOutput
from ..pipeline_utils import AudioPipelineOutput, BaseOutput, DiffusionPipeline, ImagePipelineOutput
from .mel import Mel

51
src/diffusers/pipelines/deprecated/audioldm/__init__.py Normal file
View File

@@ -0,0 +1,51 @@
from typing import TYPE_CHECKING
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
_dummy_objects = {}
_import_structure = {}
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.27.0")):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ....utils.dummy_torch_and_transformers_objects import (
AudioLDMPipeline,
)
_dummy_objects.update({"AudioLDMPipeline": AudioLDMPipeline})
else:
_import_structure["pipeline_audioldm"] = ["AudioLDMPipeline"]
if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.27.0")):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ....utils.dummy_torch_and_transformers_objects import (
AudioLDMPipeline,
)
else:
from .pipeline_audioldm import AudioLDMPipeline
else:
import sys
sys.modules[__name__] = _LazyModule(
__name__,
globals()["__file__"],
_import_structure,
module_spec=__spec__,
)
for name, value in _dummy_objects.items():
setattr(sys.modules[__name__], name, value)

563
src/diffusers/pipelines/deprecated/audioldm/pipeline_audioldm.py Normal file
View File

@@ -0,0 +1,563 @@
# Copyright 2024 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import inspect
from typing import Any, Callable, Dict, List, Optional, Union
import numpy as np
import torch
import torch.nn.functional as F
from transformers import ClapTextModelWithProjection, RobertaTokenizer, RobertaTokenizerFast, SpeechT5HifiGan
from ....models import AutoencoderKL, UNet2DConditionModel
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import is_torch_xla_available, logging, replace_example_docstring
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline, StableDiffusionMixin
if is_torch_xla_available():
import torch_xla.core.xla_model as xm
XLA_AVAILABLE = True
else:
XLA_AVAILABLE = False
logger = logging.get_logger(__name__) # pylint: disable=invalid-name
EXAMPLE_DOC_STRING = """
Examples:
```py
>>> from diffusers import AudioLDMPipeline
>>> import torch
>>> import scipy
>>> repo_id = "cvssp/audioldm-s-full-v2"
>>> pipe = AudioLDMPipeline.from_pretrained(repo_id, torch_dtype=torch.float16)
>>> pipe = pipe.to("cuda")
>>> prompt = "Techno music with a strong, upbeat tempo and high melodic riffs"
>>> audio = pipe(prompt, num_inference_steps=10, audio_length_in_s=5.0).audios[0]
>>> # save the audio sample as a .wav file
>>> scipy.io.wavfile.write("techno.wav", rate=16000, data=audio)
```
"""
class AudioLDMPipeline(DiffusionPipeline, StableDiffusionMixin):
r"""
Pipeline for text-to-audio generation using AudioLDM.
This model inherits from [`DiffusionPipeline`]. Check the superclass documentation for the generic methods
implemented for all pipelines (downloading, saving, running on a particular device, etc.).
Args:
vae ([`AutoencoderKL`]):
Variational Auto-Encoder (VAE) model to encode and decode images to and from latent representations.
text_encoder ([`~transformers.ClapTextModelWithProjection`]):
Frozen text-encoder (`ClapTextModelWithProjection`, specifically the
[laion/clap-htsat-unfused](https://huggingface.co/laion/clap-htsat-unfused) variant.
tokenizer ([`PreTrainedTokenizer`]):
A [`~transformers.RobertaTokenizer`] to tokenize text.
unet ([`UNet2DConditionModel`]):
A `UNet2DConditionModel` to denoise the encoded audio latents.
scheduler ([`SchedulerMixin`]):
A scheduler to be used in combination with `unet` to denoise the encoded audio latents. Can be one of
[`DDIMScheduler`], [`LMSDiscreteScheduler`], or [`PNDMScheduler`].
vocoder ([`~transformers.SpeechT5HifiGan`]):
Vocoder of class `SpeechT5HifiGan`.
"""
model_cpu_offload_seq = "text_encoder->unet->vae"
def __init__(
self,
vae: AutoencoderKL,
text_encoder: ClapTextModelWithProjection,
tokenizer: Union[RobertaTokenizer, RobertaTokenizerFast],
unet: UNet2DConditionModel,
scheduler: KarrasDiffusionSchedulers,
vocoder: SpeechT5HifiGan,
):
super().__init__()
logger.warning(f"{self.__class__.__name__} is deprecated and will no longer be actively maintained")
logger.warning(
f"{self.__class__.__name__} is deprecated and will no longer be actively maintained"
)
self.register_modules(
vae=vae,
text_encoder=text_encoder,
tokenizer=tokenizer,
unet=unet,
scheduler=scheduler,
vocoder=vocoder,
)
self.vae_scale_factor = 2 ** (len(self.vae.config.block_out_channels) - 1) if getattr(self, "vae", None) else 8
def _encode_prompt(
self,
prompt,
device,
num_waveforms_per_prompt,
do_classifier_free_guidance,
negative_prompt=None,
prompt_embeds: Optional[torch.Tensor] = None,
negative_prompt_embeds: Optional[torch.Tensor] = None,
):
r"""
Encodes the prompt into text encoder hidden states.
Args:
prompt (`str` or `List[str]`, *optional*):
prompt to be encoded
device (`torch.device`):
torch device
num_waveforms_per_prompt (`int`):
number of waveforms that should be generated per prompt
do_classifier_free_guidance (`bool`):
whether to use classifier free guidance or not
negative_prompt (`str` or `List[str]`, *optional*):
The prompt or prompts not to guide the audio generation. If not defined, one has to pass
`negative_prompt_embeds` instead. Ignored when not using guidance (i.e., ignored if `guidance_scale` is
less than `1`).
prompt_embeds (`torch.Tensor`, *optional*):
Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
provided, text embeddings will be generated from `prompt` input argument.
negative_prompt_embeds (`torch.Tensor`, *optional*):
Pre-generated negative text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt
weighting. If not provided, negative_prompt_embeds will be generated from `negative_prompt` input
argument.
"""
if prompt is not None and isinstance(prompt, str):
batch_size = 1
elif prompt is not None and isinstance(prompt, list):
batch_size = len(prompt)
else:
batch_size = prompt_embeds.shape[0]
if prompt_embeds is None:
text_inputs = self.tokenizer(
prompt,
padding="max_length",
max_length=self.tokenizer.model_max_length,
truncation=True,
return_tensors="pt",
)
text_input_ids = text_inputs.input_ids
attention_mask = text_inputs.attention_mask
untruncated_ids = self.tokenizer(prompt, padding="longest", return_tensors="pt").input_ids
if untruncated_ids.shape[-1] >= text_input_ids.shape[-1] and not torch.equal(
text_input_ids, untruncated_ids
):
removed_text = self.tokenizer.batch_decode(
untruncated_ids[:, self.tokenizer.model_max_length - 1 : -1]
)
logger.warning(
"The following part of your input was truncated because CLAP can only handle sequences up to"
f" {self.tokenizer.model_max_length} tokens: {removed_text}"
)
prompt_embeds = self.text_encoder(
text_input_ids.to(device),
attention_mask=attention_mask.to(device),
)
prompt_embeds = prompt_embeds.text_embeds
# additional L_2 normalization over each hidden-state
prompt_embeds = F.normalize(prompt_embeds, dim=-1)
prompt_embeds = prompt_embeds.to(dtype=self.text_encoder.dtype, device=device)
(
bs_embed,
seq_len,
) = prompt_embeds.shape
# duplicate text embeddings for each generation per prompt, using mps friendly method
prompt_embeds = prompt_embeds.repeat(1, num_waveforms_per_prompt)
prompt_embeds = prompt_embeds.view(bs_embed * num_waveforms_per_prompt, seq_len)
# get unconditional embeddings for classifier free guidance
if do_classifier_free_guidance and negative_prompt_embeds is None:
uncond_tokens: List[str]
if negative_prompt is None:
uncond_tokens = [""] * batch_size
elif type(prompt) is not type(negative_prompt):
raise TypeError(
f"`negative_prompt` should be the same type to `prompt`, but got {type(negative_prompt)} !="
f" {type(prompt)}."
)
elif isinstance(negative_prompt, str):
uncond_tokens = [negative_prompt]
elif batch_size != len(negative_prompt):
raise ValueError(
f"`negative_prompt`: {negative_prompt} has batch size {len(negative_prompt)}, but `prompt`:"
f" {prompt} has batch size {batch_size}. Please make sure that passed `negative_prompt` matches"
" the batch size of `prompt`."
)
else:
uncond_tokens = negative_prompt
max_length = prompt_embeds.shape[1]
uncond_input = self.tokenizer(
uncond_tokens,
padding="max_length",
max_length=max_length,
truncation=True,
return_tensors="pt",
)
uncond_input_ids = uncond_input.input_ids.to(device)
attention_mask = uncond_input.attention_mask.to(device)
negative_prompt_embeds = self.text_encoder(
uncond_input_ids,
attention_mask=attention_mask,
)
negative_prompt_embeds = negative_prompt_embeds.text_embeds
# additional L_2 normalization over each hidden-state
negative_prompt_embeds = F.normalize(negative_prompt_embeds, dim=-1)
if do_classifier_free_guidance:
# duplicate unconditional embeddings for each generation per prompt, using mps friendly method
seq_len = negative_prompt_embeds.shape[1]
negative_prompt_embeds = negative_prompt_embeds.to(dtype=self.text_encoder.dtype, device=device)
negative_prompt_embeds = negative_prompt_embeds.repeat(1, num_waveforms_per_prompt)
negative_prompt_embeds = negative_prompt_embeds.view(batch_size * num_waveforms_per_prompt, seq_len)
# For classifier free guidance, we need to do two forward passes.
# Here we concatenate the unconditional and text embeddings into a single batch
# to avoid doing two forward passes
prompt_embeds = torch.cat([negative_prompt_embeds, prompt_embeds])
return prompt_embeds
def decode_latents(self, latents):
latents = 1 / self.vae.config.scaling_factor * latents
mel_spectrogram = self.vae.decode(latents).sample
return mel_spectrogram
def mel_spectrogram_to_waveform(self, mel_spectrogram):
if mel_spectrogram.dim() == 4:
mel_spectrogram = mel_spectrogram.squeeze(1)
waveform = self.vocoder(mel_spectrogram)
# we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
waveform = waveform.cpu().float()
return waveform
# Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.prepare_extra_step_kwargs
def prepare_extra_step_kwargs(self, generator, eta):
# prepare extra kwargs for the scheduler step, since not all schedulers have the same signature
# eta (η) is only used with the DDIMScheduler, it will be ignored for other schedulers.
# eta corresponds to η in DDIM paper: https://arxiv.org/abs/2010.02502
# and should be between [0, 1]
accepts_eta = "eta" in set(inspect.signature(self.scheduler.step).parameters.keys())
extra_step_kwargs = {}
if accepts_eta:
extra_step_kwargs["eta"] = eta
# check if the scheduler accepts generator
accepts_generator = "generator" in set(inspect.signature(self.scheduler.step).parameters.keys())
if accepts_generator:
extra_step_kwargs["generator"] = generator
return extra_step_kwargs
def check_inputs(
self,
prompt,
audio_length_in_s,
vocoder_upsample_factor,
callback_steps,
negative_prompt=None,
prompt_embeds=None,
negative_prompt_embeds=None,
):
min_audio_length_in_s = vocoder_upsample_factor * self.vae_scale_factor
if audio_length_in_s < min_audio_length_in_s:
raise ValueError(
f"`audio_length_in_s` has to be a positive value greater than or equal to {min_audio_length_in_s}, but "
f"is {audio_length_in_s}."
)
if self.vocoder.config.model_in_dim % self.vae_scale_factor != 0:
raise ValueError(
f"The number of frequency bins in the vocoder's log-mel spectrogram has to be divisible by the "
f"VAE scale factor, but got {self.vocoder.config.model_in_dim} bins and a scale factor of "
f"{self.vae_scale_factor}."
)
if (callback_steps is None) or (
callback_steps is not None and (not isinstance(callback_steps, int) or callback_steps <= 0)
):
raise ValueError(
f"`callback_steps` has to be a positive integer but is {callback_steps} of type"
f" {type(callback_steps)}."
)
if prompt is not None and prompt_embeds is not None:
raise ValueError(
f"Cannot forward both `prompt`: {prompt} and `prompt_embeds`: {prompt_embeds}. Please make sure to"
" only forward one of the two."
)
elif prompt is None and prompt_embeds is None:
raise ValueError(
"Provide either `prompt` or `prompt_embeds`. Cannot leave both `prompt` and `prompt_embeds` undefined."
)
elif prompt is not None and (not isinstance(prompt, str) and not isinstance(prompt, list)):
raise ValueError(f"`prompt` has to be of type `str` or `list` but is {type(prompt)}")
if negative_prompt is not None and negative_prompt_embeds is not None:
raise ValueError(
f"Cannot forward both `negative_prompt`: {negative_prompt} and `negative_prompt_embeds`:"
f" {negative_prompt_embeds}. Please make sure to only forward one of the two."
)
if prompt_embeds is not None and negative_prompt_embeds is not None:
if prompt_embeds.shape != negative_prompt_embeds.shape:
raise ValueError(
"`prompt_embeds` and `negative_prompt_embeds` must have the same shape when passed directly, but"
f" got: `prompt_embeds` {prompt_embeds.shape} != `negative_prompt_embeds`"
f" {negative_prompt_embeds.shape}."
)
# Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.prepare_latents with width->self.vocoder.config.model_in_dim
def prepare_latents(self, batch_size, num_channels_latents, height, dtype, device, generator, latents=None):
shape = (
batch_size,
num_channels_latents,
int(height) // self.vae_scale_factor,
int(self.vocoder.config.model_in_dim) // self.vae_scale_factor,
)
if isinstance(generator, list) and len(generator) != batch_size:
raise ValueError(
f"You have passed a list of generators of length {len(generator)}, but requested an effective batch"
f" size of {batch_size}. Make sure the batch size matches the length of the generators."
)
if latents is None:
latents = randn_tensor(shape, generator=generator, device=device, dtype=dtype)
else:
latents = latents.to(device)
# scale the initial noise by the standard deviation required by the scheduler
latents = latents * self.scheduler.init_noise_sigma
return latents
@torch.no_grad()
@replace_example_docstring(EXAMPLE_DOC_STRING)
def __call__(
self,
prompt: Union[str, List[str]] = None,
audio_length_in_s: Optional[float] = None,
num_inference_steps: int = 10,
guidance_scale: float = 2.5,
negative_prompt: Optional[Union[str, List[str]]] = None,
num_waveforms_per_prompt: Optional[int] = 1,
eta: float = 0.0,
generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None,
latents: Optional[torch.Tensor] = None,
prompt_embeds: Optional[torch.Tensor] = None,
negative_prompt_embeds: Optional[torch.Tensor] = None,
return_dict: bool = True,
callback: Optional[Callable[[int, int, torch.Tensor], None]] = None,
callback_steps: Optional[int] = 1,
cross_attention_kwargs: Optional[Dict[str, Any]] = None,
output_type: Optional[str] = "np",
):
r"""
The call function to the pipeline for generation.
Args:
prompt (`str` or `List[str]`, *optional*):
The prompt or prompts to guide audio generation. If not defined, you need to pass `prompt_embeds`.
audio_length_in_s (`int`, *optional*, defaults to 5.12):
The length of the generated audio sample in seconds.
num_inference_steps (`int`, *optional*, defaults to 10):
The number of denoising steps. More denoising steps usually lead to a higher quality audio at the
expense of slower inference.
guidance_scale (`float`, *optional*, defaults to 2.5):
A higher guidance scale value encourages the model to generate audio that is closely linked to the text
`prompt` at the expense of lower sound quality. Guidance scale is enabled when `guidance_scale > 1`.
negative_prompt (`str` or `List[str]`, *optional*):
The prompt or prompts to guide what to not include in audio generation. If not defined, you need to
pass `negative_prompt_embeds` instead. Ignored when not using guidance (`guidance_scale < 1`).
num_waveforms_per_prompt (`int`, *optional*, defaults to 1):
The number of waveforms to generate per prompt.
eta (`float`, *optional*, defaults to 0.0):
Corresponds to parameter eta (η) from the [DDIM](https://arxiv.org/abs/2010.02502) paper. Only applies
to the [`~schedulers.DDIMScheduler`], and is ignored in other schedulers.
generator (`torch.Generator` or `List[torch.Generator]`, *optional*):
A [`torch.Generator`](https://pytorch.org/docs/stable/generated/torch.Generator.html) to make
generation deterministic.
latents (`torch.Tensor`, *optional*):
Pre-generated noisy latents sampled from a Gaussian distribution, to be used as inputs for image
generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
tensor is generated by sampling using the supplied random `generator`.
prompt_embeds (`torch.Tensor`, *optional*):
Pre-generated text embeddings. Can be used to easily tweak text inputs (prompt weighting). If not
provided, text embeddings are generated from the `prompt` input argument.
negative_prompt_embeds (`torch.Tensor`, *optional*):
Pre-generated negative text embeddings. Can be used to easily tweak text inputs (prompt weighting). If
not provided, `negative_prompt_embeds` are generated from the `negative_prompt` input argument.
return_dict (`bool`, *optional*, defaults to `True`):
Whether or not to return a [`~pipelines.AudioPipelineOutput`] instead of a plain tuple.
callback (`Callable`, *optional*):
A function that calls every `callback_steps` steps during inference. The function is called with the
following arguments: `callback(step: int, timestep: int, latents: torch.Tensor)`.
callback_steps (`int`, *optional*, defaults to 1):
The frequency at which the `callback` function is called. If not specified, the callback is called at
every step.
cross_attention_kwargs (`dict`, *optional*):
A kwargs dictionary that if specified is passed along to the [`AttentionProcessor`] as defined in
[`self.processor`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py).
output_type (`str`, *optional*, defaults to `"np"`):
The output format of the generated image. Choose between `"np"` to return a NumPy `np.ndarray` or
`"pt"` to return a PyTorch `torch.Tensor` object.
Examples:
Returns:
[`~pipelines.AudioPipelineOutput`] or `tuple`:
If `return_dict` is `True`, [`~pipelines.AudioPipelineOutput`] is returned, otherwise a `tuple` is
returned where the first element is a list with the generated audio.
"""
# 0. Convert audio input length from seconds to spectrogram height
vocoder_upsample_factor = np.prod(self.vocoder.config.upsample_rates) / self.vocoder.config.sampling_rate
if audio_length_in_s is None:
audio_length_in_s = self.unet.config.sample_size * self.vae_scale_factor * vocoder_upsample_factor
height = int(audio_length_in_s / vocoder_upsample_factor)
original_waveform_length = int(audio_length_in_s * self.vocoder.config.sampling_rate)
if height % self.vae_scale_factor != 0:
height = int(np.ceil(height / self.vae_scale_factor)) * self.vae_scale_factor
logger.info(
f"Audio length in seconds {audio_length_in_s} is increased to {height * vocoder_upsample_factor} "
f"so that it can be handled by the model. It will be cut to {audio_length_in_s} after the "
f"denoising process."
)
# 1. Check inputs. Raise error if not correct
self.check_inputs(
prompt,
audio_length_in_s,
vocoder_upsample_factor,
callback_steps,
negative_prompt,
prompt_embeds,
negative_prompt_embeds,
)
# 2. Define call parameters
if prompt is not None and isinstance(prompt, str):
batch_size = 1
elif prompt is not None and isinstance(prompt, list):
batch_size = len(prompt)
else:
batch_size = prompt_embeds.shape[0]
device = self._execution_device
# here `guidance_scale` is defined analog to the guidance weight `w` of equation (2)
# of the Imagen paper: https://arxiv.org/pdf/2205.11487.pdf . `guidance_scale = 1`
# corresponds to doing no classifier free guidance.
do_classifier_free_guidance = guidance_scale > 1.0
# 3. Encode input prompt
prompt_embeds = self._encode_prompt(
prompt,
device,
num_waveforms_per_prompt,
do_classifier_free_guidance,
negative_prompt,
prompt_embeds=prompt_embeds,
negative_prompt_embeds=negative_prompt_embeds,
)
# 4. Prepare timesteps
self.scheduler.set_timesteps(num_inference_steps, device=device)
timesteps = self.scheduler.timesteps
# 5. Prepare latent variables
num_channels_latents = self.unet.config.in_channels
latents = self.prepare_latents(
batch_size * num_waveforms_per_prompt,
num_channels_latents,
height,
prompt_embeds.dtype,
device,
generator,
latents,
)
# 6. Prepare extra step kwargs
extra_step_kwargs = self.prepare_extra_step_kwargs(generator, eta)
# 7. Denoising loop
num_warmup_steps = len(timesteps) - num_inference_steps * self.scheduler.order
with self.progress_bar(total=num_inference_steps) as progress_bar:
for i, t in enumerate(timesteps):
# expand the latents if we are doing classifier free guidance
latent_model_input = torch.cat([latents] * 2) if do_classifier_free_guidance else latents
latent_model_input = self.scheduler.scale_model_input(latent_model_input, t)
# predict the noise residual
noise_pred = self.unet(
latent_model_input,
t,
encoder_hidden_states=None,
class_labels=prompt_embeds,
cross_attention_kwargs=cross_attention_kwargs,
).sample
# perform guidance
if do_classifier_free_guidance:
noise_pred_uncond, noise_pred_text = noise_pred.chunk(2)
noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_text - noise_pred_uncond)
# compute the previous noisy sample x_t -> x_t-1
latents = self.scheduler.step(noise_pred, t, latents, **extra_step_kwargs).prev_sample
# call the callback, if provided
if i == len(timesteps) - 1 or ((i + 1) > num_warmup_steps and (i + 1) % self.scheduler.order == 0):
progress_bar.update()
if callback is not None and i % callback_steps == 0:
step_idx = i // getattr(self.scheduler, "order", 1)
callback(step_idx, t, latents)
if XLA_AVAILABLE:
xm.mark_step()
# 8. Post-processing
mel_spectrogram = self.decode_latents(latents)
audio = self.mel_spectrogram_to_waveform(mel_spectrogram)
audio = audio[:, :original_waveform_length]
if output_type == "np":
audio = audio.numpy()
if not return_dict:
return (audio,)
return AudioPipelineOutput(audios=audio)

10
src/diffusers/pipelines/controlnet_xs/__init__.py → src/diffusers/pipelines/deprecated/controlnet_xs/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -18,7 +18,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_objects # noqa F403
from ....utils import dummy_torch_and_transformers_objects # noqa F403
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
@@ -28,7 +28,7 @@ try:
if not (is_transformers_available() and is_flax_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_flax_and_transformers_objects # noqa F403
from ....utils import dummy_flax_and_transformers_objects # noqa F403
_dummy_objects.update(get_objects_from_module(dummy_flax_and_transformers_objects))
else:
@@ -41,7 +41,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import *
from ....utils.dummy_torch_and_transformers_objects import *
else:
from .pipeline_controlnet_xs import StableDiffusionControlNetXSPipeline
from .pipeline_controlnet_xs_sd_xl import StableDiffusionXLControlNetXSPipeline
@@ -50,7 +50,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
if not (is_transformers_available() and is_flax_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_flax_and_transformers_objects import * # noqa F403
from ....utils.dummy_flax_and_transformers_objects import * # noqa F403
else:
pass # from .pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline

22
src/diffusers/pipelines/controlnet_xs/pipeline_controlnet_xs.py → src/diffusers/pipelines/deprecated/controlnet_xs/pipeline_controlnet_xs.py
View File

@@ -21,13 +21,13 @@ import torch
import torch.nn.functional as F
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from ...callbacks import MultiPipelineCallbacks, PipelineCallback
from ...image_processor import PipelineImageInput, VaeImageProcessor
from ...loaders import FromSingleFileMixin, StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, ControlNetXSAdapter, UNet2DConditionModel, UNetControlNetXSModel
from ...models.lora import adjust_lora_scale_text_encoder
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import (
from ....callbacks import MultiPipelineCallbacks, PipelineCallback
from ....image_processor import PipelineImageInput, VaeImageProcessor
from ....loaders import FromSingleFileMixin, StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL, ControlNetXSAdapter, UNet2DConditionModel, UNetControlNetXSModel
from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import (
USE_PEFT_BACKEND,
deprecate,
is_torch_xla_available,
@@ -36,10 +36,10 @@ from ...utils import (
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import is_compiled_module, is_torch_version, randn_tensor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ..stable_diffusion.pipeline_output import StableDiffusionPipelineOutput
from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker
from ....utils.torch_utils import is_compiled_module, is_torch_version, randn_tensor
from ...pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ...stable_diffusion.pipeline_output import StableDiffusionPipelineOutput
from ...stable_diffusion.safety_checker import StableDiffusionSafetyChecker
if is_torch_xla_available():

24
src/diffusers/pipelines/controlnet_xs/pipeline_controlnet_xs_sd_xl.py → src/diffusers/pipelines/deprecated/controlnet_xs/pipeline_controlnet_xs_sd_xl.py
View File

@@ -28,33 +28,33 @@ from transformers import (
from diffusers.utils.import_utils import is_invisible_watermark_available
from ...callbacks import MultiPipelineCallbacks, PipelineCallback
from ...image_processor import PipelineImageInput, VaeImageProcessor
from ...loaders import FromSingleFileMixin, StableDiffusionXLLoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, ControlNetXSAdapter, UNet2DConditionModel, UNetControlNetXSModel
from ...models.attention_processor import (
from ....callbacks import MultiPipelineCallbacks, PipelineCallback
from ....image_processor import PipelineImageInput, VaeImageProcessor
from ....loaders import FromSingleFileMixin, StableDiffusionXLLoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL, ControlNetXSAdapter, UNet2DConditionModel, UNetControlNetXSModel
from ....models.attention_processor import (
AttnProcessor2_0,
XFormersAttnProcessor,
)
from ...models.lora import adjust_lora_scale_text_encoder
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import (
from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import (
USE_PEFT_BACKEND,
logging,
replace_example_docstring,
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import is_compiled_module, is_torch_version, randn_tensor
from ..pipeline_utils import DiffusionPipeline
from ..stable_diffusion_xl.pipeline_output import StableDiffusionXLPipelineOutput
from ....utils.torch_utils import is_compiled_module, is_torch_version, randn_tensor
from ...pipeline_utils import DiffusionPipeline
from ...stable_diffusion_xl.pipeline_output import StableDiffusionXLPipelineOutput
if is_invisible_watermark_available():
from ..stable_diffusion_xl.watermark import StableDiffusionXLWatermarker
from ...utils import is_torch_xla_available
from ....utils import is_torch_xla_available
if is_torch_xla_available():

2
src/diffusers/pipelines/dance_diffusion/__init__.py → src/diffusers/pipelines/deprecated/dance_diffusion/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import DIFFUSERS_SLOW_IMPORT, _LazyModule
from ....utils import DIFFUSERS_SLOW_IMPORT, _LazyModule
_import_structure = {"pipeline_dance_diffusion": ["DanceDiffusionPipeline"]}

8
src/diffusers/pipelines/dance_diffusion/pipeline_dance_diffusion.py → src/diffusers/pipelines/deprecated/dance_diffusion/pipeline_dance_diffusion.py
View File

@@ -17,10 +17,10 @@ from typing import List, Optional, Tuple, Union
import torch
from ...models import UNet1DModel
from ...schedulers import SchedulerMixin
from ...utils import is_torch_xla_available, logging
from ...utils.torch_utils import randn_tensor
from ....models import UNet1DModel
from ....schedulers import SchedulerMixin
from ....utils import is_torch_xla_available, logging
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline

6
src/diffusers/pipelines/i2vgen_xl/__init__.py → src/diffusers/pipelines/deprecated/i2vgen_xl/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -17,7 +17,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_objects # noqa F403
from ....utils import dummy_torch_and_transformers_objects # noqa F403
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
@@ -29,7 +29,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import * # noqa F403
from ....utils.dummy_torch_and_transformers_objects import * # noqa F403
else:
from .pipeline_i2vgen_xl import I2VGenXLPipeline

14
src/diffusers/pipelines/i2vgen_xl/pipeline_i2vgen_xl.py → src/diffusers/pipelines/deprecated/i2vgen_xl/pipeline_i2vgen_xl.py
View File

@@ -21,18 +21,18 @@ import PIL
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer, CLIPVisionModelWithProjection
from ...image_processor import PipelineImageInput, VaeImageProcessor
from ...models import AutoencoderKL
from ...models.unets.unet_i2vgen_xl import I2VGenXLUNet
from ...schedulers import DDIMScheduler
from ...utils import (
from ....image_processor import PipelineImageInput, VaeImageProcessor
from ....models import AutoencoderKL
from ....models.unets.unet_i2vgen_xl import I2VGenXLUNet
from ....schedulers import DDIMScheduler
from ....utils import (
BaseOutput,
is_torch_xla_available,
logging,
replace_example_docstring,
)
from ...utils.torch_utils import randn_tensor
from ...video_processor import VideoProcessor
from ....utils.torch_utils import randn_tensor
from ....video_processor import VideoProcessor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin

6
src/diffusers/pipelines/latte/__init__.py → src/diffusers/pipelines/deprecated/latte/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -18,7 +18,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_objects # noqa F403
from ....utils import dummy_torch_and_transformers_objects # noqa F403
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
@@ -30,7 +30,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import *
from ....utils.dummy_torch_and_transformers_objects import *
else:
from .pipeline_latte import LattePipeline

14
src/diffusers/pipelines/latte/pipeline_latte.py → src/diffusers/pipelines/deprecated/latte/pipeline_latte.py
View File

@@ -23,11 +23,11 @@ from typing import Callable, Dict, List, Optional, Tuple, Union
import torch
from transformers import T5EncoderModel, T5Tokenizer
from ...callbacks import MultiPipelineCallbacks, PipelineCallback
from ...models import AutoencoderKL, LatteTransformer3DModel
from ...pipelines.pipeline_utils import DiffusionPipeline
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import (
from ....callbacks import MultiPipelineCallbacks, PipelineCallback
from ....models import AutoencoderKL, LatteTransformer3DModel
from ...pipeline_utils import DiffusionPipeline
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import (
BACKENDS_MAPPING,
BaseOutput,
deprecate,
@@ -37,8 +37,8 @@ from ...utils import (
logging,
replace_example_docstring,
)
from ...utils.torch_utils import is_compiled_module, randn_tensor
from ...video_processor import VideoProcessor
from ....utils.torch_utils import is_compiled_module, randn_tensor
from ....video_processor import VideoProcessor
if is_torch_xla_available():

6
src/diffusers/pipelines/musicldm/__init__.py → src/diffusers/pipelines/deprecated/musicldm/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -18,7 +18,7 @@ try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.27.0")):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_objects # noqa F403
from ....utils import dummy_torch_and_transformers_objects # noqa F403
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
@@ -31,7 +31,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import *
from ....utils.dummy_torch_and_transformers_objects import *
else:
from .pipeline_musicldm import MusicLDMPipeline

10
src/diffusers/pipelines/musicldm/pipeline_musicldm.py → src/diffusers/pipelines/deprecated/musicldm/pipeline_musicldm.py
View File

@@ -26,16 +26,16 @@ from transformers import (
SpeechT5HifiGan,
)
from ...models import AutoencoderKL, UNet2DConditionModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import (
from ....models import AutoencoderKL, UNet2DConditionModel
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import (
is_accelerate_available,
is_accelerate_version,
is_librosa_available,
logging,
replace_example_docstring,
)
from ...utils.torch_utils import randn_tensor
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline, StableDiffusionMixin
@@ -43,7 +43,7 @@ if is_librosa_available():
import librosa
from ...utils import is_torch_xla_available
from ....utils import is_torch_xla_available
if is_torch_xla_available():

6
src/diffusers/pipelines/paint_by_example/__init__.py → src/diffusers/pipelines/deprecated/paint_by_example/__init__.py
View File

@@ -5,7 +5,7 @@ import numpy as np
import PIL
from PIL import Image
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -22,7 +22,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_objects # noqa F403
from ....utils import dummy_torch_and_transformers_objects # noqa F403
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
@@ -36,7 +36,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import *
from ....utils.dummy_torch_and_transformers_objects import *
else:
from .image_encoder import PaintByExampleImageEncoder
from .pipeline_paint_by_example import PaintByExamplePipeline

2
src/diffusers/pipelines/paint_by_example/image_encoder.py → src/diffusers/pipelines/deprecated/paint_by_example/image_encoder.py
View File

@@ -16,7 +16,7 @@ from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
from ....utils import logging
logger = logging.get_logger(__name__) # pylint: disable=invalid-name

10
src/diffusers/pipelines/paint_by_example/pipeline_paint_by_example.py → src/diffusers/pipelines/deprecated/paint_by_example/pipeline_paint_by_example.py
View File

@@ -20,11 +20,11 @@ import PIL.Image
import torch
from transformers import CLIPImageProcessor
from ...image_processor import VaeImageProcessor
from ...models import AutoencoderKL, UNet2DConditionModel
from ...schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
from ...utils import deprecate, is_torch_xla_available, logging
from ...utils.torch_utils import randn_tensor
from ....image_processor import VaeImageProcessor
from ....models import AutoencoderKL, UNet2DConditionModel
from ....schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
from ....utils import deprecate, is_torch_xla_available, logging
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ..stable_diffusion import StableDiffusionPipelineOutput
from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker

6
src/diffusers/pipelines/pia/__init__.py → src/diffusers/pipelines/deprecated/pia/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -17,7 +17,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_objects
from ....utils import dummy_torch_and_transformers_objects
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
@@ -28,7 +28,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import *
from ....utils.dummy_torch_and_transformers_objects import *
else:
from .pipeline_pia import PIAPipeline, PIAPipelineOutput

26
src/diffusers/pipelines/pia/pipeline_pia.py → src/diffusers/pipelines/deprecated/pia/pipeline_pia.py
View File

@@ -21,12 +21,17 @@ import PIL
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer, CLIPVisionModelWithProjection
from ...image_processor import PipelineImageInput
from ...loaders import FromSingleFileMixin, IPAdapterMixin, StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, ImageProjection, UNet2DConditionModel, UNetMotionModel
from ...models.lora import adjust_lora_scale_text_encoder
from ...models.unets.unet_motion_model import MotionAdapter
from ...schedulers import (
from ....image_processor import PipelineImageInput
from ....loaders import (
FromSingleFileMixin,
IPAdapterMixin,
StableDiffusionLoraLoaderMixin,
TextualInversionLoaderMixin,
)
from ....models import AutoencoderKL, ImageProjection, UNet2DConditionModel, UNetMotionModel
from ....models.lora import adjust_lora_scale_text_encoder
from ....models.unets.unet_motion_model import MotionAdapter
from ....schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
@@ -34,7 +39,7 @@ from ...schedulers import (
LMSDiscreteScheduler,
PNDMScheduler,
)
from ...utils import (
from ....utils import (
USE_PEFT_BACKEND,
BaseOutput,
is_torch_xla_available,
@@ -43,12 +48,11 @@ from ...utils import (
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import randn_tensor
from ...video_processor import VideoProcessor
from ....utils.torch_utils import randn_tensor
from ....video_processor import VideoProcessor
from ..free_init_utils import FreeInitMixin
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
if is_torch_xla_available():
import torch_xla.core.xla_model as xm
@@ -191,6 +195,8 @@ class PIAPipeline(
image_encoder: CLIPVisionModelWithProjection = None,
):
super().__init__()
logger.warning(f"{self.__class__.__name__} is deprecated and will no longer be actively maintained")
if isinstance(unet, UNet2DConditionModel):
unet = UNetMotionModel.from_unet2d(unet, motion_adapter)

6
src/diffusers/pipelines/semantic_stable_diffusion/__init__.py → src/diffusers/pipelines/deprecated/semantic_stable_diffusion/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -17,7 +17,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_objects # noqa F403
from ....utils import dummy_torch_and_transformers_objects # noqa F403
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
@@ -31,7 +31,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import *
from ....utils.dummy_torch_and_transformers_objects import *
else:
from .pipeline_semantic_stable_diffusion import SemanticStableDiffusionPipeline

2
src/diffusers/pipelines/semantic_stable_diffusion/pipeline_output.py → src/diffusers/pipelines/deprecated/semantic_stable_diffusion/pipeline_output.py
View File

@@ -4,7 +4,7 @@ from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...utils import BaseOutput
from ....utils import BaseOutput
@dataclass

10
src/diffusers/pipelines/semantic_stable_diffusion/pipeline_semantic_stable_diffusion.py → src/diffusers/pipelines/deprecated/semantic_stable_diffusion/pipeline_semantic_stable_diffusion.py
View File

@@ -5,12 +5,12 @@ from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from ...image_processor import VaeImageProcessor
from ...models import AutoencoderKL, UNet2DConditionModel
from ....image_processor import VaeImageProcessor
from ....models import AutoencoderKL, UNet2DConditionModel
from ...pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import deprecate, is_torch_xla_available, logging
from ...utils.torch_utils import randn_tensor
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import deprecate, is_torch_xla_available, logging
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from .pipeline_output import SemanticStableDiffusionPipelineOutput

6
src/diffusers/pipelines/shap_e/__init__.py → src/diffusers/pipelines/deprecated/shap_e/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -17,7 +17,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_objects # noqa F403
from ....utils import dummy_torch_and_transformers_objects # noqa F403
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
@@ -41,7 +41,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import *
from ....utils.dummy_torch_and_transformers_objects import *
else:
from .camera import create_pan_cameras
from .pipeline_shap_e import ShapEPipeline

0
src/diffusers/pipelines/shap_e/camera.py → src/diffusers/pipelines/deprecated/shap_e/camera.py
View File

8
src/diffusers/pipelines/shap_e/pipeline_shap_e.py → src/diffusers/pipelines/deprecated/shap_e/pipeline_shap_e.py
View File

@@ -21,15 +21,15 @@ import PIL.Image
import torch
from transformers import CLIPTextModelWithProjection, CLIPTokenizer
from ...models import PriorTransformer
from ...schedulers import HeunDiscreteScheduler
from ...utils import (
from ....models import PriorTransformer
from ....schedulers import HeunDiscreteScheduler
from ....utils import (
BaseOutput,
is_torch_xla_available,
logging,
replace_example_docstring,
)
from ...utils.torch_utils import randn_tensor
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline
from .renderer import ShapERenderer

8
src/diffusers/pipelines/shap_e/pipeline_shap_e_img2img.py → src/diffusers/pipelines/deprecated/shap_e/pipeline_shap_e_img2img.py
View File

@@ -20,15 +20,15 @@ import PIL.Image
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...schedulers import HeunDiscreteScheduler
from ...utils import (
from ....models import PriorTransformer
from ....schedulers import HeunDiscreteScheduler
from ....utils import (
BaseOutput,
is_torch_xla_available,
logging,
replace_example_docstring,
)
from ...utils.torch_utils import randn_tensor
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline
from .renderer import ShapERenderer

2
src/diffusers/pipelines/shap_e/renderer.py → src/diffusers/pipelines/deprecated/shap_e/renderer.py
View File

@@ -23,7 +23,7 @@ from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
from ...utils import BaseOutput
from ....utils import BaseOutput
from .camera import create_pan_cameras

2
src/diffusers/pipelines/deprecated/spectrogram_diffusion/pipeline_spectrogram_diffusion.py
View File

@@ -28,7 +28,7 @@ from ....utils.torch_utils import randn_tensor
if is_onnx_available():
from ...onnx_utils import OnnxRuntimeModel
from ...pipeline_utils import AudioPipelineOutput, DiffusionPipeline
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
from .continuous_encoder import SpectrogramContEncoder
from .notes_encoder import SpectrogramNotesEncoder

6
src/diffusers/pipelines/stable_diffusion_attend_and_excite/__init__.py → src/diffusers/pipelines/deprecated/stable_diffusion_attend_and_excite/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -18,7 +18,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_objects # noqa F403
from ....utils import dummy_torch_and_transformers_objects # noqa F403
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
@@ -30,7 +30,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import *
from ....utils.dummy_torch_and_transformers_objects import *
else:
from .pipeline_stable_diffusion_attend_and_excite import StableDiffusionAttendAndExcitePipeline

16
src/diffusers/pipelines/stable_diffusion_attend_and_excite/pipeline_stable_diffusion_attend_and_excite.py → src/diffusers/pipelines/deprecated/stable_diffusion_attend_and_excite/pipeline_stable_diffusion_attend_and_excite.py
View File

@@ -21,13 +21,13 @@ import torch
from torch.nn import functional as F
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from ...image_processor import VaeImageProcessor
from ...loaders import StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, UNet2DConditionModel
from ...models.attention_processor import Attention
from ...models.lora import adjust_lora_scale_text_encoder
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import (
from ....image_processor import VaeImageProcessor
from ....loaders import StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL, UNet2DConditionModel
from ....models.attention_processor import Attention
from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import (
USE_PEFT_BACKEND,
deprecate,
is_torch_xla_available,
@@ -36,7 +36,7 @@ from ...utils import (
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import randn_tensor
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ..stable_diffusion import StableDiffusionPipelineOutput
from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker

6
src/diffusers/pipelines/stable_diffusion_diffedit/__init__.py → src/diffusers/pipelines/deprecated/stable_diffusion_diffedit/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -18,7 +18,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_objects # noqa F403
from ....utils import dummy_torch_and_transformers_objects # noqa F403
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
@@ -30,7 +30,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import *
from ....utils.dummy_torch_and_transformers_objects import *
else:
from .pipeline_stable_diffusion_diffedit import StableDiffusionDiffEditPipeline

14
src/diffusers/pipelines/stable_diffusion_diffedit/pipeline_stable_diffusion_diffedit.py → src/diffusers/pipelines/deprecated/stable_diffusion_diffedit/pipeline_stable_diffusion_diffedit.py
View File

@@ -23,12 +23,12 @@ from packaging import version
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from ...configuration_utils import FrozenDict
from ...image_processor import VaeImageProcessor
from ...loaders import StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, UNet2DConditionModel
from ...models.lora import adjust_lora_scale_text_encoder
from ...schedulers import DDIMInverseScheduler, KarrasDiffusionSchedulers
from ...utils import (
from ....image_processor import VaeImageProcessor
from ....loaders import StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL, UNet2DConditionModel
from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import DDIMInverseScheduler, KarrasDiffusionSchedulers
from ....utils import (
PIL_INTERPOLATION,
USE_PEFT_BACKEND,
BaseOutput,
@@ -39,7 +39,7 @@ from ...utils import (
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import randn_tensor
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ..stable_diffusion import StableDiffusionPipelineOutput
from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker

6
src/diffusers/pipelines/stable_diffusion_gligen/__init__.py → src/diffusers/pipelines/deprecated/stable_diffusion_gligen/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -18,7 +18,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_objects # noqa F403
from ....utils import dummy_torch_and_transformers_objects # noqa F403
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
@@ -31,7 +31,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import *
from ....utils.dummy_torch_and_transformers_objects import *
else:
from .pipeline_stable_diffusion_gligen import StableDiffusionGLIGENPipeline
from .pipeline_stable_diffusion_gligen_text_image import StableDiffusionGLIGENTextImagePipeline

16
src/diffusers/pipelines/stable_diffusion_gligen/pipeline_stable_diffusion_gligen.py → src/diffusers/pipelines/deprecated/stable_diffusion_gligen/pipeline_stable_diffusion_gligen.py
View File

@@ -20,13 +20,13 @@ import PIL.Image
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from ...image_processor import VaeImageProcessor
from ...loaders import StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, UNet2DConditionModel
from ...models.attention import GatedSelfAttentionDense
from ...models.lora import adjust_lora_scale_text_encoder
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import (
from ....image_processor import VaeImageProcessor
from ....loaders import StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL, UNet2DConditionModel
from ....models.attention import GatedSelfAttentionDense
from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import (
USE_PEFT_BACKEND,
deprecate,
is_torch_xla_available,
@@ -35,7 +35,7 @@ from ...utils import (
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import randn_tensor
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ..stable_diffusion import StableDiffusionPipelineOutput
from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker

16
src/diffusers/pipelines/stable_diffusion_gligen/pipeline_stable_diffusion_gligen_text_image.py → src/diffusers/pipelines/deprecated/stable_diffusion_gligen/pipeline_stable_diffusion_gligen_text_image.py
View File

@@ -26,13 +26,13 @@ from transformers import (
CLIPVisionModelWithProjection,
)
from ...image_processor import VaeImageProcessor
from ...loaders import StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, UNet2DConditionModel
from ...models.attention import GatedSelfAttentionDense
from ...models.lora import adjust_lora_scale_text_encoder
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import (
from ....image_processor import VaeImageProcessor
from ....loaders import StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL, UNet2DConditionModel
from ....models.attention import GatedSelfAttentionDense
from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import (
USE_PEFT_BACKEND,
is_torch_xla_available,
logging,
@@ -40,7 +40,7 @@ from ...utils import (
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import randn_tensor
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ..stable_diffusion import StableDiffusionPipelineOutput
from ..stable_diffusion.clip_image_project_model import CLIPImageProjection

6
src/diffusers/pipelines/stable_diffusion_k_diffusion/__init__.py → src/diffusers/pipelines/deprecated/stable_diffusion_k_diffusion/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -25,7 +25,7 @@ try:
):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_and_k_diffusion_objects # noqa F403
from ....utils import dummy_torch_and_transformers_and_k_diffusion_objects # noqa F403
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_and_k_diffusion_objects))
else:
@@ -43,7 +43,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_and_k_diffusion_objects import *
from ....utils.dummy_torch_and_transformers_and_k_diffusion_objects import *
else:
from .pipeline_stable_diffusion_k_diffusion import StableDiffusionKDiffusionPipeline
from .pipeline_stable_diffusion_xl_k_diffusion import StableDiffusionXLKDiffusionPipeline

16
src/diffusers/pipelines/stable_diffusion_k_diffusion/pipeline_stable_diffusion_k_diffusion.py → src/diffusers/pipelines/deprecated/stable_diffusion_k_diffusion/pipeline_stable_diffusion_k_diffusion.py
View File

@@ -26,22 +26,22 @@ from transformers import (
CLIPTokenizerFast,
)
from ...image_processor import VaeImageProcessor
from ...loaders import (
from ....image_processor import VaeImageProcessor
from ....loaders import (
StableDiffusionLoraLoaderMixin,
TextualInversionLoaderMixin,
)
from ...models import AutoencoderKL, UNet2DConditionModel
from ...models.lora import adjust_lora_scale_text_encoder
from ...schedulers import KarrasDiffusionSchedulers, LMSDiscreteScheduler
from ...utils import (
from ....models import AutoencoderKL, UNet2DConditionModel
from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import KarrasDiffusionSchedulers, LMSDiscreteScheduler
from ....utils import (
USE_PEFT_BACKEND,
deprecate,
logging,
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import randn_tensor
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ..stable_diffusion import StableDiffusionPipelineOutput, StableDiffusionSafetyChecker
@@ -122,6 +122,8 @@ class StableDiffusionKDiffusionPipeline(
):
super().__init__()
logger.warning(f"{self.__class__.__name__} is deprecated and will no longer be actively maintained")
logger.info(
f"{self.__class__} is an experimntal pipeline and is likely to change in the future. We recommend to use"
" this pipeline for fast experimentation / iteration if needed, but advice to rely on existing pipelines"

18
src/diffusers/pipelines/stable_diffusion_k_diffusion/pipeline_stable_diffusion_xl_k_diffusion.py → src/diffusers/pipelines/deprecated/stable_diffusion_k_diffusion/pipeline_stable_diffusion_xl_k_diffusion.py
View File

@@ -25,29 +25,29 @@ from transformers import (
CLIPTokenizer,
)
from ...image_processor import VaeImageProcessor
from ...loaders import (
from ....image_processor import VaeImageProcessor
from ....loaders import (
FromSingleFileMixin,
IPAdapterMixin,
StableDiffusionXLLoraLoaderMixin,
TextualInversionLoaderMixin,
)
from ...models import AutoencoderKL, UNet2DConditionModel
from ...models.attention_processor import (
from ....models import AutoencoderKL, UNet2DConditionModel
from ....models.attention_processor import (
AttnProcessor2_0,
FusedAttnProcessor2_0,
XFormersAttnProcessor,
)
from ...models.lora import adjust_lora_scale_text_encoder
from ...schedulers import KarrasDiffusionSchedulers, LMSDiscreteScheduler
from ...utils import (
from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import KarrasDiffusionSchedulers, LMSDiscreteScheduler
from ....utils import (
USE_PEFT_BACKEND,
logging,
replace_example_docstring,
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import randn_tensor
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ..stable_diffusion_xl.pipeline_output import StableDiffusionXLPipelineOutput
@@ -158,6 +158,8 @@ class StableDiffusionXLKDiffusionPipeline(
):
super().__init__()
logger.warning(f"{self.__class__.__name__} is deprecated and will no longer be actively maintained")
# get correct sigmas from LMS
scheduler = LMSDiscreteScheduler.from_config(scheduler.config)
self.register_modules(

6
src/diffusers/pipelines/stable_diffusion_ldm3d/__init__.py → src/diffusers/pipelines/deprecated/stable_diffusion_ldm3d/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -18,7 +18,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_objects # noqa F403
from ....utils import dummy_torch_and_transformers_objects # noqa F403
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
@@ -30,7 +30,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import *
from ....utils.dummy_torch_and_transformers_objects import *
else:
from .pipeline_stable_diffusion_ldm3d import StableDiffusionLDM3DPipeline

14
src/diffusers/pipelines/stable_diffusion_ldm3d/pipeline_stable_diffusion_ldm3d.py → src/diffusers/pipelines/deprecated/stable_diffusion_ldm3d/pipeline_stable_diffusion_ldm3d.py
View File

@@ -21,12 +21,12 @@ import PIL.Image
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer, CLIPVisionModelWithProjection
from ...image_processor import PipelineImageInput, VaeImageProcessorLDM3D
from ...loaders import FromSingleFileMixin, IPAdapterMixin, StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, ImageProjection, UNet2DConditionModel
from ...models.lora import adjust_lora_scale_text_encoder
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import (
from ....image_processor import PipelineImageInput, VaeImageProcessorLDM3D
from ....loaders import FromSingleFileMixin, IPAdapterMixin, StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL, ImageProjection, UNet2DConditionModel
from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import (
USE_PEFT_BACKEND,
BaseOutput,
deprecate,
@@ -36,7 +36,7 @@ from ...utils import (
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import randn_tensor
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker

6
src/diffusers/pipelines/stable_diffusion_panorama/__init__.py → src/diffusers/pipelines/deprecated/stable_diffusion_panorama/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -18,7 +18,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_objects # noqa F403
from ....utils import dummy_torch_and_transformers_objects # noqa F403
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
@@ -30,7 +30,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import *
from ....utils.dummy_torch_and_transformers_objects import *
else:
from .pipeline_stable_diffusion_panorama import StableDiffusionPanoramaPipeline

14
src/diffusers/pipelines/stable_diffusion_panorama/pipeline_stable_diffusion_panorama.py → src/diffusers/pipelines/deprecated/stable_diffusion_panorama/pipeline_stable_diffusion_panorama.py
View File

@@ -18,12 +18,12 @@ from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer, CLIPVisionModelWithProjection
from ...image_processor import PipelineImageInput, VaeImageProcessor
from ...loaders import IPAdapterMixin, StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, ImageProjection, UNet2DConditionModel
from ...models.lora import adjust_lora_scale_text_encoder
from ...schedulers import DDIMScheduler
from ...utils import (
from ....image_processor import PipelineImageInput, VaeImageProcessor
from ....loaders import IPAdapterMixin, StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL, ImageProjection, UNet2DConditionModel
from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import DDIMScheduler
from ....utils import (
USE_PEFT_BACKEND,
deprecate,
is_torch_xla_available,
@@ -32,7 +32,7 @@ from ...utils import (
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import randn_tensor
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ..stable_diffusion import StableDiffusionPipelineOutput
from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker

6
src/diffusers/pipelines/stable_diffusion_safe/__init__.py → src/diffusers/pipelines/deprecated/stable_diffusion_safe/__init__.py
View File

@@ -6,7 +6,7 @@ import numpy as np
import PIL
from PIL import Image
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
BaseOutput,
OptionalDependencyNotAvailable,
@@ -59,7 +59,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_objects
from ....utils import dummy_torch_and_transformers_objects
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
@@ -77,7 +77,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import *
from ....utils.dummy_torch_and_transformers_objects import *
else:
from .pipeline_output import StableDiffusionSafePipelineOutput
from .pipeline_stable_diffusion_safe import StableDiffusionPipelineSafe

2
src/diffusers/pipelines/stable_diffusion_safe/pipeline_output.py → src/diffusers/pipelines/deprecated/stable_diffusion_safe/pipeline_output.py
View File

@@ -4,7 +4,7 @@ from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...utils import (
from ....utils import (
BaseOutput,
)

12
src/diffusers/pipelines/stable_diffusion_safe/pipeline_stable_diffusion_safe.py → src/diffusers/pipelines/deprecated/stable_diffusion_safe/pipeline_stable_diffusion_safe.py
View File

@@ -8,12 +8,12 @@ from packaging import version
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer, CLIPVisionModelWithProjection
from ...configuration_utils import FrozenDict
from ...image_processor import PipelineImageInput
from ...loaders import IPAdapterMixin
from ...models import AutoencoderKL, ImageProjection, UNet2DConditionModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import deprecate, is_torch_xla_available, logging
from ...utils.torch_utils import randn_tensor
from ....image_processor import PipelineImageInput
from ....loaders import IPAdapterMixin
from ....models import AutoencoderKL, ImageProjection, UNet2DConditionModel
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import deprecate, is_torch_xla_available, logging
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from . import StableDiffusionSafePipelineOutput
from .safety_checker import SafeStableDiffusionSafetyChecker

2
src/diffusers/pipelines/stable_diffusion_safe/safety_checker.py → src/diffusers/pipelines/deprecated/stable_diffusion_safe/safety_checker.py
View File

@@ -16,7 +16,7 @@ import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
from ....utils import logging
logger = logging.get_logger(__name__)

6
src/diffusers/pipelines/stable_diffusion_sag/__init__.py → src/diffusers/pipelines/deprecated/stable_diffusion_sag/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -18,7 +18,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_objects # noqa F403
from ....utils import dummy_torch_and_transformers_objects # noqa F403
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
@@ -30,7 +30,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import *
from ....utils.dummy_torch_and_transformers_objects import *
else:
from .pipeline_stable_diffusion_sag import StableDiffusionSAGPipeline

14
src/diffusers/pipelines/stable_diffusion_sag/pipeline_stable_diffusion_sag.py → src/diffusers/pipelines/deprecated/stable_diffusion_sag/pipeline_stable_diffusion_sag.py
View File

@@ -19,12 +19,12 @@ import torch
import torch.nn.functional as F
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer, CLIPVisionModelWithProjection
from ...image_processor import PipelineImageInput, VaeImageProcessor
from ...loaders import IPAdapterMixin, StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, ImageProjection, UNet2DConditionModel
from ...models.lora import adjust_lora_scale_text_encoder
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import (
from ....image_processor import PipelineImageInput, VaeImageProcessor
from ....loaders import IPAdapterMixin, StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL, ImageProjection, UNet2DConditionModel
from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import (
USE_PEFT_BACKEND,
deprecate,
is_torch_xla_available,
@@ -33,7 +33,7 @@ from ...utils import (
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import randn_tensor
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ..stable_diffusion import StableDiffusionPipelineOutput
from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker

6
src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_cycle_diffusion.py
View File

@@ -29,9 +29,9 @@ from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import DDIMScheduler
from ....utils import PIL_INTERPOLATION, USE_PEFT_BACKEND, deprecate, logging, scale_lora_layers, unscale_lora_layers
from ....utils.torch_utils import randn_tensor
from ...pipeline_utils import DiffusionPipeline
from ...stable_diffusion.pipeline_output import StableDiffusionPipelineOutput
from ...stable_diffusion.safety_checker import StableDiffusionSafetyChecker
from ..pipeline_utils import DiffusionPipeline
from ..stable_diffusion.pipeline_output import StableDiffusionPipelineOutput
from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker
logger = logging.get_logger(__name__) # pylint: disable=invalid-name

4
src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_onnx_stable_diffusion_inpaint_legacy.py
View File

@@ -10,8 +10,8 @@ from ....configuration_utils import FrozenDict
from ....schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
from ....utils import deprecate, logging
from ...onnx_utils import ORT_TO_NP_TYPE, OnnxRuntimeModel
from ...pipeline_utils import DiffusionPipeline
from ...stable_diffusion.pipeline_output import StableDiffusionPipelineOutput
from ..pipeline_utils import DiffusionPipeline
from ..stable_diffusion.pipeline_output import StableDiffusionPipelineOutput
logger = logging.get_logger(__name__) # pylint: disable=invalid-name

6
src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_stable_diffusion_inpaint_legacy.py
View File

@@ -29,9 +29,9 @@ from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import PIL_INTERPOLATION, USE_PEFT_BACKEND, deprecate, logging, scale_lora_layers, unscale_lora_layers
from ....utils.torch_utils import randn_tensor
from ...pipeline_utils import DiffusionPipeline
from ...stable_diffusion import StableDiffusionPipelineOutput
from ...stable_diffusion.safety_checker import StableDiffusionSafetyChecker
from ..pipeline_utils import DiffusionPipeline
from ..stable_diffusion import StableDiffusionPipelineOutput
from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker
logger = logging.get_logger(__name__)

6
src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_stable_diffusion_model_editing.py
View File

@@ -26,9 +26,9 @@ from ....schedulers import PNDMScheduler
from ....schedulers.scheduling_utils import SchedulerMixin
from ....utils import USE_PEFT_BACKEND, deprecate, logging, scale_lora_layers, unscale_lora_layers
from ....utils.torch_utils import randn_tensor
from ...pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ...stable_diffusion.pipeline_output import StableDiffusionPipelineOutput
from ...stable_diffusion.safety_checker import StableDiffusionSafetyChecker
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ..stable_diffusion.pipeline_output import StableDiffusionPipelineOutput
from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker
logger = logging.get_logger(__name__) # pylint: disable=invalid-name

6
src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_stable_diffusion_paradigms.py
View File

@@ -32,9 +32,9 @@ from ....utils import (
unscale_lora_layers,
)
from ....utils.torch_utils import randn_tensor
from ...pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ...stable_diffusion.pipeline_output import StableDiffusionPipelineOutput
from ...stable_diffusion.safety_checker import StableDiffusionSafetyChecker
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ..stable_diffusion.pipeline_output import StableDiffusionPipelineOutput
from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker
logger = logging.get_logger(__name__) # pylint: disable=invalid-name

6
src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_stable_diffusion_pix2pix_zero.py
View File

@@ -46,9 +46,9 @@ from ....utils import (
unscale_lora_layers,
)
from ....utils.torch_utils import randn_tensor
from ...pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ...stable_diffusion.pipeline_output import StableDiffusionPipelineOutput
from ...stable_diffusion.safety_checker import StableDiffusionSafetyChecker
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ..stable_diffusion.pipeline_output import StableDiffusionPipelineOutput
from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker
logger = logging.get_logger(__name__) # pylint: disable=invalid-name

6
src/diffusers/pipelines/text_to_video_synthesis/__init__.py → src/diffusers/pipelines/deprecated/text_to_video_synthesis/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -17,7 +17,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_objects # noqa F403
from ....utils import dummy_torch_and_transformers_objects # noqa F403
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
@@ -33,7 +33,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import * # noqa F403
from ....utils.dummy_torch_and_transformers_objects import * # noqa F403
else:
from .pipeline_output import TextToVideoSDPipelineOutput
from .pipeline_text_to_video_synth import TextToVideoSDPipeline

2
src/diffusers/pipelines/text_to_video_synthesis/pipeline_output.py → src/diffusers/pipelines/deprecated/text_to_video_synthesis/pipeline_output.py
View File

@@ -5,7 +5,7 @@ import numpy as np
import PIL
import torch
from ...utils import (
from ....utils import (
BaseOutput,
)

14
src/diffusers/pipelines/text_to_video_synthesis/pipeline_text_to_video_synth.py → src/diffusers/pipelines/deprecated/text_to_video_synthesis/pipeline_text_to_video_synth.py
View File

@@ -18,11 +18,11 @@ from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...loaders import StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, UNet3DConditionModel
from ...models.lora import adjust_lora_scale_text_encoder
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import (
from ....loaders import StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL, UNet3DConditionModel
from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import (
USE_PEFT_BACKEND,
deprecate,
is_torch_xla_available,
@@ -31,8 +31,8 @@ from ...utils import (
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import randn_tensor
from ...video_processor import VideoProcessor
from ....utils.torch_utils import randn_tensor
from ....video_processor import VideoProcessor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from . import TextToVideoSDPipelineOutput

14
src/diffusers/pipelines/text_to_video_synthesis/pipeline_text_to_video_synth_img2img.py → src/diffusers/pipelines/deprecated/text_to_video_synthesis/pipeline_text_to_video_synth_img2img.py
View File

@@ -19,11 +19,11 @@ import numpy as np
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...loaders import StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, UNet3DConditionModel
from ...models.lora import adjust_lora_scale_text_encoder
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import (
from ....loaders import StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL, UNet3DConditionModel
from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import (
USE_PEFT_BACKEND,
deprecate,
is_torch_xla_available,
@@ -32,8 +32,8 @@ from ...utils import (
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import randn_tensor
from ...video_processor import VideoProcessor
from ....utils.torch_utils import randn_tensor
from ....video_processor import VideoProcessor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from . import TextToVideoSDPipelineOutput

14
src/diffusers/pipelines/text_to_video_synthesis/pipeline_text_to_video_zero.py → src/diffusers/pipelines/deprecated/text_to_video_synthesis/pipeline_text_to_video_zero.py
View File

@@ -10,12 +10,12 @@ import torch.nn.functional as F
from torch.nn.functional import grid_sample
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from ...image_processor import VaeImageProcessor
from ...loaders import FromSingleFileMixin, StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, UNet2DConditionModel
from ...models.lora import adjust_lora_scale_text_encoder
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import (
from ....image_processor import VaeImageProcessor
from ....loaders import FromSingleFileMixin, StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL, UNet2DConditionModel
from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import (
USE_PEFT_BACKEND,
BaseOutput,
is_torch_xla_available,
@@ -23,7 +23,7 @@ from ...utils import (
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import randn_tensor
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
from ..stable_diffusion import StableDiffusionSafetyChecker

18
src/diffusers/pipelines/text_to_video_synthesis/pipeline_text_to_video_zero_sdxl.py → src/diffusers/pipelines/deprecated/text_to_video_synthesis/pipeline_text_to_video_zero_sdxl.py
View File

@@ -16,17 +16,17 @@ from transformers import (
CLIPVisionModelWithProjection,
)
from ...image_processor import VaeImageProcessor
from ...loaders import StableDiffusionXLLoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, UNet2DConditionModel
from ...models.attention_processor import (
from ....image_processor import VaeImageProcessor
from ....loaders import StableDiffusionXLLoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL, UNet2DConditionModel
from ....models.attention_processor import (
AttnProcessor2_0,
FusedAttnProcessor2_0,
XFormersAttnProcessor,
)
from ...models.lora import adjust_lora_scale_text_encoder
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import (
from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import (
USE_PEFT_BACKEND,
BaseOutput,
is_invisible_watermark_available,
@@ -34,7 +34,7 @@ from ...utils import (
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import randn_tensor
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, StableDiffusionMixin
@@ -42,7 +42,7 @@ if is_invisible_watermark_available():
from ..stable_diffusion_xl.watermark import StableDiffusionXLWatermarker
from ...utils import is_torch_xla_available
from ....utils import is_torch_xla_available
if is_torch_xla_available():

6
src/diffusers/pipelines/unclip/__init__.py → src/diffusers/pipelines/deprecated/unclip/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -17,7 +17,7 @@ try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import UnCLIPImageVariationPipeline, UnCLIPPipeline
from ....utils.dummy_torch_and_transformers_objects import UnCLIPImageVariationPipeline, UnCLIPPipeline
_dummy_objects.update(
{"UnCLIPImageVariationPipeline": UnCLIPImageVariationPipeline, "UnCLIPPipeline": UnCLIPPipeline}
@@ -33,7 +33,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import * # noqa F403
from ....utils.dummy_torch_and_transformers_objects import * # noqa F403
else:
from .pipeline_unclip import UnCLIPPipeline
from .pipeline_unclip_image_variation import UnCLIPImageVariationPipeline

10
src/diffusers/pipelines/unclip/pipeline_unclip.py → src/diffusers/pipelines/deprecated/unclip/pipeline_unclip.py
View File

@@ -20,11 +20,11 @@ from torch.nn import functional as F
from transformers import CLIPTextModelWithProjection, CLIPTokenizer
from transformers.models.clip.modeling_clip import CLIPTextModelOutput
from ...models import PriorTransformer, UNet2DConditionModel, UNet2DModel
from ...schedulers import UnCLIPScheduler
from ...utils import is_torch_xla_available, logging
from ...utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from ....models import PriorTransformer, UNet2DConditionModel, UNet2DModel
from ....schedulers import UnCLIPScheduler
from ....utils import is_torch_xla_available, logging
from ....utils.torch_utils import randn_tensor
from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from .text_proj import UnCLIPTextProjModel

10
src/diffusers/pipelines/unclip/pipeline_unclip_image_variation.py → src/diffusers/pipelines/deprecated/unclip/pipeline_unclip_image_variation.py
View File

@@ -25,11 +25,11 @@ from transformers import (
CLIPVisionModelWithProjection,
)
from ...models import UNet2DConditionModel, UNet2DModel
from ...schedulers import UnCLIPScheduler
from ...utils import is_torch_xla_available, logging
from ...utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from ....models import UNet2DConditionModel, UNet2DModel
from ....schedulers import UnCLIPScheduler
from ....utils import is_torch_xla_available, logging
from ....utils.torch_utils import randn_tensor
from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from .text_proj import UnCLIPTextProjModel

0
src/diffusers/pipelines/unclip/text_proj.py → src/diffusers/pipelines/deprecated/unclip/text_proj.py
View File

6
src/diffusers/pipelines/unidiffuser/__init__.py → src/diffusers/pipelines/deprecated/unidiffuser/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -16,7 +16,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import (
from ....utils.dummy_torch_and_transformers_objects import (
ImageTextPipelineOutput,
UniDiffuserPipeline,
)
@@ -35,7 +35,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import (
from ....utils.dummy_torch_and_transformers_objects import (
ImageTextPipelineOutput,
UniDiffuserPipeline,
)

0
src/diffusers/pipelines/unidiffuser/modeling_text_decoder.py → src/diffusers/pipelines/deprecated/unidiffuser/modeling_text_decoder.py
View File

2
src/diffusers/pipelines/unidiffuser/modeling_uvit.py → src/diffusers/pipelines/deprecated/unidiffuser/modeling_uvit.py
View File

@@ -11,7 +11,7 @@ from ...models.attention_processor import Attention
from ...models.embeddings import TimestepEmbedding, Timesteps, get_2d_sincos_pos_embed
from ...models.modeling_outputs import Transformer2DModelOutput
from ...models.normalization import AdaLayerNorm
from ...utils import logging
from ....utils import logging
logger = logging.get_logger(__name__) # pylint: disable=invalid-name

24
src/diffusers/pipelines/unidiffuser/pipeline_unidiffuser.py → src/diffusers/pipelines/deprecated/unidiffuser/pipeline_unidiffuser.py
View File

@@ -13,12 +13,12 @@ from transformers import (
GPT2Tokenizer,
)
from ...image_processor import VaeImageProcessor
from ...loaders import StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL
from ...models.lora import adjust_lora_scale_text_encoder
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import (
from ....image_processor import VaeImageProcessor
from ....loaders import StableDiffusionLoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL
from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import (
USE_PEFT_BACKEND,
deprecate,
is_torch_xla_available,
@@ -26,8 +26,8 @@ from ...utils import (
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.outputs import BaseOutput
from ...utils.torch_utils import randn_tensor
from ....utils.outputs import BaseOutput
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline
from .modeling_text_decoder import UniDiffuserTextDecoder
from .modeling_uvit import UniDiffuserModel
@@ -225,7 +225,7 @@ class UniDiffuserPipeline(DiffusionPipeline):
return mode
# Copied from diffusers.pipelines.pipeline_utils.StableDiffusionMixin.enable_vae_slicing
# Copied from ..pipeline_utils.StableDiffusionMixin.enable_vae_slicing
def enable_vae_slicing(self):
r"""
Enable sliced VAE decoding. When this option is enabled, the VAE will split the input tensor in slices to
@@ -233,7 +233,7 @@ class UniDiffuserPipeline(DiffusionPipeline):
"""
self.vae.enable_slicing()
# Copied from diffusers.pipelines.pipeline_utils.StableDiffusionMixin.disable_vae_slicing
# Copied from ..pipeline_utils.StableDiffusionMixin.disable_vae_slicing
def disable_vae_slicing(self):
r"""
Disable sliced VAE decoding. If `enable_vae_slicing` was previously enabled, this method will go back to
@@ -241,7 +241,7 @@ class UniDiffuserPipeline(DiffusionPipeline):
"""
self.vae.disable_slicing()
# Copied from diffusers.pipelines.pipeline_utils.StableDiffusionMixin.enable_vae_tiling
# Copied from ..pipeline_utils.StableDiffusionMixin.enable_vae_tiling
def enable_vae_tiling(self):
r"""
Enable tiled VAE decoding. When this option is enabled, the VAE will split the input tensor into tiles to
@@ -250,7 +250,7 @@ class UniDiffuserPipeline(DiffusionPipeline):
"""
self.vae.enable_tiling()
# Copied from diffusers.pipelines.pipeline_utils.StableDiffusionMixin.disable_vae_tiling
# Copied from ..pipeline_utils.StableDiffusionMixin.disable_vae_tiling
def disable_vae_tiling(self):
r"""
Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to

2
src/diffusers/pipelines/deprecated/versatile_diffusion/pipeline_versatile_diffusion.py
View File

@@ -8,7 +8,7 @@ from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer, CLIPV
from ....models import AutoencoderKL, UNet2DConditionModel
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import logging
from ...pipeline_utils import DiffusionPipeline
from ..pipeline_utils import DiffusionPipeline
from .pipeline_versatile_diffusion_dual_guided import VersatileDiffusionDualGuidedPipeline
from .pipeline_versatile_diffusion_image_variation import VersatileDiffusionImageVariationPipeline
from .pipeline_versatile_diffusion_text_to_image import VersatileDiffusionTextToImagePipeline

6
src/diffusers/pipelines/wuerstchen/__init__.py → src/diffusers/pipelines/deprecated/wuerstchen/__init__.py
View File

@@ -1,6 +1,6 @@
from typing import TYPE_CHECKING
from ...utils import (
from ....utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
@@ -17,7 +17,7 @@ try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_torch_and_transformers_objects
from ....utils import dummy_torch_and_transformers_objects
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
@@ -34,7 +34,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import * # noqa F403
from ....utils.dummy_torch_and_transformers_objects import * # noqa F403
else:
from .modeling_paella_vq_model import PaellaVQModel
from .modeling_wuerstchen_diffnext import WuerstchenDiffNeXt

2
src/diffusers/pipelines/wuerstchen/modeling_paella_vq_model.py → src/diffusers/pipelines/deprecated/wuerstchen/modeling_paella_vq_model.py
View File

@@ -22,7 +22,7 @@ from ...configuration_utils import ConfigMixin, register_to_config
from ...models.autoencoders.vae import DecoderOutput, VectorQuantizer
from ...models.modeling_utils import ModelMixin
from ...models.vq_model import VQEncoderOutput
from ...utils.accelerate_utils import apply_forward_hook
from ....utils.accelerate_utils import apply_forward_hook
class MixingResidualBlock(nn.Module):

0
src/diffusers/pipelines/wuerstchen/modeling_wuerstchen_common.py → src/diffusers/pipelines/deprecated/wuerstchen/modeling_wuerstchen_common.py
View File

0
src/diffusers/pipelines/wuerstchen/modeling_wuerstchen_diffnext.py → src/diffusers/pipelines/deprecated/wuerstchen/modeling_wuerstchen_diffnext.py
View File

0
src/diffusers/pipelines/wuerstchen/modeling_wuerstchen_prior.py → src/diffusers/pipelines/deprecated/wuerstchen/modeling_wuerstchen_prior.py
View File

8
src/diffusers/pipelines/wuerstchen/pipeline_wuerstchen.py → src/diffusers/pipelines/deprecated/wuerstchen/pipeline_wuerstchen.py
View File

@@ -18,10 +18,10 @@ import numpy as np
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...schedulers import DDPMWuerstchenScheduler
from ...utils import deprecate, is_torch_xla_available, logging, replace_example_docstring
from ...utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from ....schedulers import DDPMWuerstchenScheduler
from ....utils import deprecate, is_torch_xla_available, logging, replace_example_docstring
from ....utils.torch_utils import randn_tensor
from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from .modeling_paella_vq_model import PaellaVQModel
from .modeling_wuerstchen_diffnext import WuerstchenDiffNeXt

4
src/diffusers/pipelines/wuerstchen/pipeline_wuerstchen_combined.py → src/diffusers/pipelines/deprecated/wuerstchen/pipeline_wuerstchen_combined.py
View File

@@ -16,8 +16,8 @@ from typing import Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...schedulers import DDPMWuerstchenScheduler
from ...utils import deprecate, replace_example_docstring
from ....schedulers import DDPMWuerstchenScheduler
from ....utils import deprecate, replace_example_docstring
from ..pipeline_utils import DiffusionPipeline
from .modeling_paella_vq_model import PaellaVQModel
from .modeling_wuerstchen_diffnext import WuerstchenDiffNeXt

8
src/diffusers/pipelines/wuerstchen/pipeline_wuerstchen_prior.py → src/diffusers/pipelines/deprecated/wuerstchen/pipeline_wuerstchen_prior.py
View File

@@ -20,10 +20,10 @@ import numpy as np
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...loaders import StableDiffusionLoraLoaderMixin
from ...schedulers import DDPMWuerstchenScheduler
from ...utils import BaseOutput, deprecate, is_torch_xla_available, logging, replace_example_docstring
from ...utils.torch_utils import randn_tensor
from ....loaders import StableDiffusionLoraLoaderMixin
from ....schedulers import DDPMWuerstchenScheduler
from ....utils import BaseOutput, deprecate, is_torch_xla_available, logging, replace_example_docstring
from ....utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline
from .modeling_wuerstchen_prior import WuerstchenPrior