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Unverified Commit a0c54828 authored by Dhruv Nair's avatar Dhruv Nair Committed by GitHub
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Deprecate Pipelines (#6169) 



* deprecate pipe

* make style

* update

* add deprecation message

* format

* remove tests for deprecated pipelines

* remove deprecation message

* make style

* fix copies

* clean up

* clean

* clean

* clean

* clean up

* clean up

* clean up toctree

* clean up

---------
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
parent 8d891e6e
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Showing with 109 additions and 386 deletions
src/diffusers/pipelines/stable_diffusion/pipeline_cycle_diffusion.py → src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_cycle_diffusion.py
View file @ a0c54828
......@@ -21,17 +21,17 @@ import torch
from packaging import version
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from ...configuration_utils import FrozenDict
from ...image_processor import PipelineImageInput, VaeImageProcessor
from ...loaders import LoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, UNet2DConditionModel
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 .pipeline_output import StableDiffusionPipelineOutput
from .safety_checker import StableDiffusionSafetyChecker
from ....configuration_utils import FrozenDict
from ....image_processor import PipelineImageInput, VaeImageProcessor
from ....loaders import LoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL, UNet2DConditionModel
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
logger = logging.get_logger(__name__) # pylint: disable=invalid-name
......
src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_inpaint_legacy.py → src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_onnx_stable_diffusion_inpaint_legacy.py
View file @ a0c54828
......@@ -6,12 +6,12 @@ import PIL.Image
import torch
from transformers import CLIPImageProcessor, CLIPTokenizer
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 . import StableDiffusionPipelineOutput
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
logger = logging.get_logger(__name__) # pylint: disable=invalid-name
......
src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint_legacy.py → src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_stable_diffusion_inpaint_legacy.py
View file @ a0c54828
......@@ -21,17 +21,17 @@ import torch
from packaging import version
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from ...configuration_utils import FrozenDict
from ...image_processor import VaeImageProcessor
from ...loaders import FromSingleFileMixin, LoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, UNet2DConditionModel
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 . import StableDiffusionPipelineOutput
from .safety_checker import StableDiffusionSafetyChecker
from ....configuration_utils import FrozenDict
from ....image_processor import VaeImageProcessor
from ....loaders import FromSingleFileMixin, LoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL, UNet2DConditionModel
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
logger = logging.get_logger(__name__)
......
src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_model_editing.py → src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_stable_diffusion_model_editing.py
View file @ a0c54828
......@@ -18,17 +18,17 @@ from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
from ...image_processor import VaeImageProcessor
from ...loaders import LoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, UNet2DConditionModel
from ...models.lora import adjust_lora_scale_text_encoder
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
from . import StableDiffusionPipelineOutput
from .safety_checker import StableDiffusionSafetyChecker
from ....image_processor import VaeImageProcessor
from ....loaders import LoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL, UNet2DConditionModel
from ....models.lora import adjust_lora_scale_text_encoder
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
from ...stable_diffusion.pipeline_output import StableDiffusionPipelineOutput
from ...stable_diffusion.safety_checker import StableDiffusionSafetyChecker
logger = logging.get_logger(__name__) # pylint: disable=invalid-name
......
src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_paradigms.py → src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_stable_diffusion_paradigms.py
View file @ a0c54828
......@@ -18,12 +18,12 @@ from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from ...image_processor import VaeImageProcessor
from ...loaders import FromSingleFileMixin, LoraLoaderMixin, 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, LoraLoaderMixin, 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,
deprecate,
logging,
......@@ -31,10 +31,10 @@ from ...utils import (
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline
from . import StableDiffusionPipelineOutput
from .safety_checker import StableDiffusionSafetyChecker
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
logger = logging.get_logger(__name__) # pylint: disable=invalid-name
......
src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_pix2pix_zero.py → src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_stable_diffusion_pix2pix_zero.py
View file @ a0c54828
......@@ -28,14 +28,14 @@ from transformers import (
CLIPTokenizer,
)
from ...image_processor import PipelineImageInput, VaeImageProcessor
from ...loaders import LoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, UNet2DConditionModel
from ...models.attention_processor import Attention
from ...models.lora import adjust_lora_scale_text_encoder
from ...schedulers import DDIMScheduler, DDPMScheduler, EulerAncestralDiscreteScheduler, LMSDiscreteScheduler
from ...schedulers.scheduling_ddim_inverse import DDIMInverseScheduler
from ...utils import (
from ....image_processor import PipelineImageInput, VaeImageProcessor
from ....loaders import LoraLoaderMixin, TextualInversionLoaderMixin
from ....models import AutoencoderKL, UNet2DConditionModel
from ....models.attention_processor import Attention
from ....models.lora import adjust_lora_scale_text_encoder
from ....schedulers import DDIMScheduler, DDPMScheduler, EulerAncestralDiscreteScheduler, LMSDiscreteScheduler
from ....schedulers.scheduling_ddim_inverse import DDIMInverseScheduler
from ....utils import (
PIL_INTERPOLATION,
USE_PEFT_BACKEND,
BaseOutput,
......@@ -45,10 +45,10 @@ from ...utils import (
scale_lora_layers,
unscale_lora_layers,
)
from ...utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline
from . import StableDiffusionPipelineOutput
from .safety_checker import StableDiffusionSafetyChecker
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
logger = logging.get_logger(__name__) # pylint: disable=invalid-name
......
src/diffusers/pipelines/stochastic_karras_ve/__init__.py → src/diffusers/pipelines/deprecated/stochastic_karras_ve/__init__.py
View file @ a0c54828
from typing import TYPE_CHECKING
from ...utils import DIFFUSERS_SLOW_IMPORT, _LazyModule
from ....utils import DIFFUSERS_SLOW_IMPORT, _LazyModule
_import_structure = {"pipeline_stochastic_karras_ve": ["KarrasVePipeline"]}
......
src/diffusers/pipelines/stochastic_karras_ve/pipeline_stochastic_karras_ve.py → src/diffusers/pipelines/deprecated/stochastic_karras_ve/pipeline_stochastic_karras_ve.py
View file @ a0c54828
......@@ -16,10 +16,10 @@ from typing import List, Optional, Tuple, Union
import torch
from ...models import UNet2DModel
from ...schedulers import KarrasVeScheduler
from ...utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from ....models import UNet2DModel
from ....schedulers import KarrasVeScheduler
from ....utils.torch_utils import randn_tensor
from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class KarrasVePipeline(DiffusionPipeline):
......
src/diffusers/pipelines/versatile_diffusion/__init__.py → src/diffusers/pipelines/deprecated/versatile_diffusion/__init__.py
View file @ a0c54828
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 (
from ....utils.dummy_torch_and_transformers_objects import (
VersatileDiffusionDualGuidedPipeline,
VersatileDiffusionImageVariationPipeline,
VersatileDiffusionPipeline,
......@@ -45,7 +45,7 @@ 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 (
from ....utils.dummy_torch_and_transformers_objects import (
VersatileDiffusionDualGuidedPipeline,
VersatileDiffusionImageVariationPipeline,
VersatileDiffusionPipeline,
......
src/diffusers/pipelines/versatile_diffusion/modeling_text_unet.py → src/diffusers/pipelines/deprecated/versatile_diffusion/modeling_text_unet.py
View file @ a0c54828
......@@ -7,10 +7,10 @@ import torch.nn.functional as F
from diffusers.utils import deprecate
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
from ...models.activations import get_activation
from ...models.attention_processor import (
from ....configuration_utils import ConfigMixin, register_to_config
from ....models import ModelMixin
from ....models.activations import get_activation
from ....models.attention_processor import (
ADDED_KV_ATTENTION_PROCESSORS,
CROSS_ATTENTION_PROCESSORS,
Attention,
......@@ -19,8 +19,8 @@ from ...models.attention_processor import (
AttnAddedKVProcessor2_0,
AttnProcessor,
)
from ...models.dual_transformer_2d import DualTransformer2DModel
from ...models.embeddings import (
from ....models.dual_transformer_2d import DualTransformer2DModel
from ....models.embeddings import (
GaussianFourierProjection,
ImageHintTimeEmbedding,
ImageProjection,
......@@ -31,10 +31,10 @@ from ...models.embeddings import (
TimestepEmbedding,
Timesteps,
)
from ...models.transformer_2d import Transformer2DModel
from ...models.unet_2d_condition import UNet2DConditionOutput
from ...utils import USE_PEFT_BACKEND, is_torch_version, logging, scale_lora_layers, unscale_lora_layers
from ...utils.torch_utils import apply_freeu
from ....models.transformer_2d import Transformer2DModel
from ....models.unet_2d_condition import UNet2DConditionOutput
from ....utils import USE_PEFT_BACKEND, is_torch_version, logging, scale_lora_layers, unscale_lora_layers
from ....utils.torch_utils import apply_freeu
logger = logging.get_logger(__name__) # pylint: disable=invalid-name
......
src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion.py → src/diffusers/pipelines/deprecated/versatile_diffusion/pipeline_versatile_diffusion.py
View file @ a0c54828
......@@ -5,10 +5,10 @@ import PIL.Image
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer, CLIPVisionModel
from ...models import AutoencoderKL, UNet2DConditionModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import logging
from ..pipeline_utils import DiffusionPipeline
from ....models import AutoencoderKL, UNet2DConditionModel
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import logging
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
......
src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_dual_guided.py → src/diffusers/pipelines/deprecated/versatile_diffusion/pipeline_versatile_diffusion_dual_guided.py
View file @ a0c54828
......@@ -26,12 +26,12 @@ from transformers import (
CLIPVisionModelWithProjection,
)
from ...image_processor import VaeImageProcessor
from ...models import AutoencoderKL, DualTransformer2DModel, Transformer2DModel, UNet2DConditionModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import deprecate, logging
from ...utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from ....image_processor import VaeImageProcessor
from ....models import AutoencoderKL, DualTransformer2DModel, Transformer2DModel, UNet2DConditionModel
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import deprecate, logging
from ....utils.torch_utils import randn_tensor
from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from .modeling_text_unet import UNetFlatConditionModel
......
src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_image_variation.py → src/diffusers/pipelines/deprecated/versatile_diffusion/pipeline_versatile_diffusion_image_variation.py
View file @ a0c54828
......@@ -21,12 +21,12 @@ import torch
import torch.utils.checkpoint
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from ...image_processor import VaeImageProcessor
from ...models import AutoencoderKL, UNet2DConditionModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import deprecate, logging
from ...utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from ....image_processor import VaeImageProcessor
from ....models import AutoencoderKL, UNet2DConditionModel
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import deprecate, logging
from ....utils.torch_utils import randn_tensor
from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
logger = logging.get_logger(__name__) # pylint: disable=invalid-name
......
src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_text_to_image.py → src/diffusers/pipelines/deprecated/versatile_diffusion/pipeline_versatile_diffusion_text_to_image.py
View file @ a0c54828
......@@ -19,12 +19,12 @@ import torch
import torch.utils.checkpoint
from transformers import CLIPImageProcessor, CLIPTextModelWithProjection, CLIPTokenizer
from ...image_processor import VaeImageProcessor
from ...models import AutoencoderKL, Transformer2DModel, UNet2DConditionModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import deprecate, logging
from ...utils.torch_utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from ....image_processor import VaeImageProcessor
from ....models import AutoencoderKL, Transformer2DModel, UNet2DConditionModel
from ....schedulers import KarrasDiffusionSchedulers
from ....utils import deprecate, logging
from ....utils.torch_utils import randn_tensor
from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from .modeling_text_unet import UNetFlatConditionModel
......
src/diffusers/pipelines/vq_diffusion/__init__.py → src/diffusers/pipelines/deprecated/vq_diffusion/__init__.py
View file @ a0c54828
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 (
LearnedClassifierFreeSamplingEmbeddings,
VQDiffusionPipeline,
)
......@@ -36,7 +36,7 @@ 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 (
LearnedClassifierFreeSamplingEmbeddings,
VQDiffusionPipeline,
)
......
src/diffusers/pipelines/vq_diffusion/pipeline_vq_diffusion.py → src/diffusers/pipelines/deprecated/vq_diffusion/pipeline_vq_diffusion.py
View file @ a0c54828
......@@ -17,11 +17,11 @@ from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, Transformer2DModel, VQModel
from ...schedulers import VQDiffusionScheduler
from ...utils import logging
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from ....configuration_utils import ConfigMixin, register_to_config
from ....models import ModelMixin, Transformer2DModel, VQModel
from ....schedulers import VQDiffusionScheduler
from ....utils import logging
from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
logger = logging.get_logger(__name__) # pylint: disable=invalid-name
......
src/diffusers/pipelines/stable_diffusion/__init__.py
View file @ a0c54828
......@@ -134,7 +134,6 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
else:
from .clip_image_project_model import CLIPImageProjection
from .pipeline_cycle_diffusion import CycleDiffusionPipeline
from .pipeline_stable_diffusion import (
StableDiffusionPipeline,
StableDiffusionPipelineOutput,
......@@ -149,9 +148,6 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
)
from .pipeline_stable_diffusion_img2img import StableDiffusionImg2ImgPipeline
from .pipeline_stable_diffusion_inpaint import StableDiffusionInpaintPipeline
from .pipeline_stable_diffusion_inpaint_legacy import (
StableDiffusionInpaintPipelineLegacy,
)
from .pipeline_stable_diffusion_instruct_pix2pix import (
StableDiffusionInstructPix2PixPipeline,
)
......@@ -159,13 +155,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
StableDiffusionLatentUpscalePipeline,
)
from .pipeline_stable_diffusion_ldm3d import StableDiffusionLDM3DPipeline
from .pipeline_stable_diffusion_model_editing import (
StableDiffusionModelEditingPipeline,
)
from .pipeline_stable_diffusion_panorama import StableDiffusionPanoramaPipeline
from .pipeline_stable_diffusion_paradigms import (
StableDiffusionParadigmsPipeline,
)
from .pipeline_stable_diffusion_sag import StableDiffusionSAGPipeline
from .pipeline_stable_diffusion_upscale import StableDiffusionUpscalePipeline
from .pipeline_stable_unclip import StableUnCLIPPipeline
......@@ -199,9 +189,6 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
StableDiffusionDepth2ImgPipeline,
)
from .pipeline_stable_diffusion_diffedit import StableDiffusionDiffEditPipeline
from .pipeline_stable_diffusion_pix2pix_zero import (
StableDiffusionPix2PixZeroPipeline,
)
try:
if not (
......@@ -234,9 +221,6 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
from .pipeline_onnx_stable_diffusion_inpaint import (
OnnxStableDiffusionInpaintPipeline,
)
from .pipeline_onnx_stable_diffusion_inpaint_legacy import (
OnnxStableDiffusionInpaintPipelineLegacy,
)
from .pipeline_onnx_stable_diffusion_upscale import (
OnnxStableDiffusionUpscalePipeline,
)
......
src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_diffedit.py
View file @ a0c54828
......@@ -788,7 +788,6 @@ class StableDiffusionDiffEditPipeline(DiffusionPipeline, TextualInversionLoaderM
latents = latents * self.scheduler.init_noise_sigma
return latents
# Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_pix2pix_zero.StableDiffusionPix2PixZeroPipeline.prepare_image_latents
def prepare_image_latents(self, image, batch_size, dtype, device, generator=None):
if not isinstance(image, (torch.Tensor, PIL.Image.Image, list)):
raise ValueError(
......
tests/pipelines/altdiffusion/test_alt_diffusion.py deleted 100644 → 0
View file @ 8d891e6e
# coding=utf-8
# Copyright 2023 HuggingFace Inc.
#
# 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 gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, XLMRobertaTokenizer
from diffusers import AltDiffusionPipeline, AutoencoderKL, DDIMScheduler, PNDMScheduler, UNet2DConditionModel
from diffusers.pipelines.alt_diffusion.modeling_roberta_series import (
RobertaSeriesConfig,
RobertaSeriesModelWithTransformation,
)
from diffusers.utils.testing_utils import enable_full_determinism, nightly, require_torch_gpu, torch_device
from ..pipeline_params import (
TEXT_TO_IMAGE_BATCH_PARAMS,
TEXT_TO_IMAGE_CALLBACK_CFG_PARAMS,
TEXT_TO_IMAGE_IMAGE_PARAMS,
TEXT_TO_IMAGE_PARAMS,
)
from ..test_pipelines_common import PipelineKarrasSchedulerTesterMixin, PipelineLatentTesterMixin, PipelineTesterMixin
enable_full_determinism()
class AltDiffusionPipelineFastTests(
PipelineLatentTesterMixin, PipelineKarrasSchedulerTesterMixin, PipelineTesterMixin, unittest.TestCase
):
pipeline_class = AltDiffusionPipeline
params = TEXT_TO_IMAGE_PARAMS
batch_params = TEXT_TO_IMAGE_BATCH_PARAMS
image_params = TEXT_TO_IMAGE_IMAGE_PARAMS
image_latents_params = TEXT_TO_IMAGE_IMAGE_PARAMS
callback_cfg_params = TEXT_TO_IMAGE_CALLBACK_CFG_PARAMS
def get_dummy_components(self):
torch.manual_seed(0)
unet = UNet2DConditionModel(
block_out_channels=(32, 64),
layers_per_block=2,
sample_size=32,
in_channels=4,
out_channels=4,
down_block_types=("DownBlock2D", "CrossAttnDownBlock2D"),
up_block_types=("CrossAttnUpBlock2D", "UpBlock2D"),
cross_attention_dim=32,
)
scheduler = DDIMScheduler(
beta_start=0.00085,
beta_end=0.012,
beta_schedule="scaled_linear",
clip_sample=False,
set_alpha_to_one=False,
)
torch.manual_seed(0)
vae = AutoencoderKL(
block_out_channels=[32, 64],
in_channels=3,
out_channels=3,
down_block_types=["DownEncoderBlock2D", "DownEncoderBlock2D"],
up_block_types=["UpDecoderBlock2D", "UpDecoderBlock2D"],
latent_channels=4,
)
# TODO: address the non-deterministic text encoder (fails for save-load tests)
# torch.manual_seed(0)
# text_encoder_config = RobertaSeriesConfig(
# hidden_size=32,
# project_dim=32,
# intermediate_size=37,
# layer_norm_eps=1e-05,
# num_attention_heads=4,
# num_hidden_layers=5,
# vocab_size=5002,
# )
# text_encoder = RobertaSeriesModelWithTransformation(text_encoder_config)
torch.manual_seed(0)
text_encoder_config = CLIPTextConfig(
bos_token_id=0,
eos_token_id=2,
hidden_size=32,
projection_dim=32,
intermediate_size=37,
layer_norm_eps=1e-05,
num_attention_heads=4,
num_hidden_layers=5,
pad_token_id=1,
vocab_size=5002,
)
text_encoder = CLIPTextModel(text_encoder_config)
tokenizer = XLMRobertaTokenizer.from_pretrained("hf-internal-testing/tiny-xlm-roberta")
tokenizer.model_max_length = 77
components = {
"unet": unet,
"scheduler": scheduler,
"vae": vae,
"text_encoder": text_encoder,
"tokenizer": tokenizer,
"safety_checker": None,
"feature_extractor": None,
"image_encoder": None,
}
return components
def get_dummy_inputs(self, device, seed=0):
if str(device).startswith("mps"):
generator = torch.manual_seed(seed)
else:
generator = torch.Generator(device=device).manual_seed(seed)
inputs = {
"prompt": "A painting of a squirrel eating a burger",
"generator": generator,
"num_inference_steps": 2,
"guidance_scale": 6.0,
"output_type": "numpy",
}
return inputs
def test_attention_slicing_forward_pass(self):
super().test_attention_slicing_forward_pass(expected_max_diff=3e-3)
def test_inference_batch_single_identical(self):
super().test_inference_batch_single_identical(expected_max_diff=3e-3)
def test_alt_diffusion_ddim(self):
device = "cpu" # ensure determinism for the device-dependent torch.Generator
components = self.get_dummy_components()
torch.manual_seed(0)
text_encoder_config = RobertaSeriesConfig(
hidden_size=32,
project_dim=32,
intermediate_size=37,
layer_norm_eps=1e-05,
num_attention_heads=4,
num_hidden_layers=5,
vocab_size=5002,
)
# TODO: remove after fixing the non-deterministic text encoder
text_encoder = RobertaSeriesModelWithTransformation(text_encoder_config)
components["text_encoder"] = text_encoder
alt_pipe = AltDiffusionPipeline(**components)
alt_pipe = alt_pipe.to(device)
alt_pipe.set_progress_bar_config(disable=None)
inputs = self.get_dummy_inputs(device)
inputs["prompt"] = "A photo of an astronaut"
output = alt_pipe(**inputs)
image = output.images
image_slice = image[0, -3:, -3:, -1]
assert image.shape == (1, 64, 64, 3)
expected_slice = np.array(
[0.5748162, 0.60447145, 0.48821217, 0.50100636, 0.5431185, 0.45763683, 0.49657696, 0.48132733, 0.47573093]
)
assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
def test_alt_diffusion_pndm(self):
device = "cpu" # ensure determinism for the device-dependent torch.Generator
components = self.get_dummy_components()
components["scheduler"] = PNDMScheduler(skip_prk_steps=True)
torch.manual_seed(0)
text_encoder_config = RobertaSeriesConfig(
hidden_size=32,
project_dim=32,
intermediate_size=37,
layer_norm_eps=1e-05,
num_attention_heads=4,
num_hidden_layers=5,
vocab_size=5002,
)
# TODO: remove after fixing the non-deterministic text encoder
text_encoder = RobertaSeriesModelWithTransformation(text_encoder_config)
components["text_encoder"] = text_encoder
alt_pipe = AltDiffusionPipeline(**components)
alt_pipe = alt_pipe.to(device)
alt_pipe.set_progress_bar_config(disable=None)
inputs = self.get_dummy_inputs(device)
output = alt_pipe(**inputs)
image = output.images
image_slice = image[0, -3:, -3:, -1]
assert image.shape == (1, 64, 64, 3)
expected_slice = np.array(
[0.51605093, 0.5707241, 0.47365507, 0.50578886, 0.5633877, 0.4642503, 0.5182081, 0.48763484, 0.49084237]
)
assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
@nightly
@require_torch_gpu
class AltDiffusionPipelineIntegrationTests(unittest.TestCase):
def tearDown(self):
# clean up the VRAM after each test
super().tearDown()
gc.collect()
torch.cuda.empty_cache()
def test_alt_diffusion(self):
# make sure here that pndm scheduler skips prk
alt_pipe = AltDiffusionPipeline.from_pretrained("BAAI/AltDiffusion", safety_checker=None)
alt_pipe = alt_pipe.to(torch_device)
alt_pipe.set_progress_bar_config(disable=None)
prompt = "A painting of a squirrel eating a burger"
generator = torch.manual_seed(0)
output = alt_pipe([prompt], generator=generator, guidance_scale=6.0, num_inference_steps=20, output_type="np")
image = output.images
image_slice = image[0, -3:, -3:, -1]
assert image.shape == (1, 512, 512, 3)
expected_slice = np.array([0.1010, 0.0800, 0.0794, 0.0885, 0.0843, 0.0762, 0.0769, 0.0729, 0.0586])
assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
def test_alt_diffusion_fast_ddim(self):
scheduler = DDIMScheduler.from_pretrained("BAAI/AltDiffusion", subfolder="scheduler")
alt_pipe = AltDiffusionPipeline.from_pretrained("BAAI/AltDiffusion", scheduler=scheduler, safety_checker=None)
alt_pipe = alt_pipe.to(torch_device)
alt_pipe.set_progress_bar_config(disable=None)
prompt = "A painting of a squirrel eating a burger"
generator = torch.manual_seed(0)
output = alt_pipe([prompt], generator=generator, num_inference_steps=2, output_type="numpy")
image = output.images
image_slice = image[0, -3:, -3:, -1]
assert image.shape == (1, 512, 512, 3)
expected_slice = np.array([0.4019, 0.4052, 0.3810, 0.4119, 0.3916, 0.3982, 0.4651, 0.4195, 0.5323])
assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
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