AI/diffusers
1
0
Fork 0
mirror of https://github.com/huggingface/diffusers.git synced 2026-01-29 07:22:12 +03:00
Code Activity

move all the sequential pipelines & auto pipelines to the blocks_presets.py

Browse Source
This commit is contained in:
yiyixuxu
2025-06-26 12:43:14 +02:00
parent 84f4b27dfa
commit 449f299c63
8 changed files with 59 additions and 249 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
src/diffusers/__init__.py
View File

@@ -358,7 +358,7 @@ except OptionalDependencyNotAvailable:
else:
_import_structure["modular_pipelines"].extend(
[
"StableDiffusionXLAutoPipeline",
"StableDiffusionXLAutoBlocks",
"StableDiffusionXLModularLoader",
]
)
@@ -979,7 +979,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
from .utils.dummy_torch_and_transformers_objects import * # noqa F403
else:
from .modular_pipelines import (
StableDiffusionXLAutoPipeline,
StableDiffusionXLAutoBlocks,
StableDiffusionXLModularLoader,
)
from .pipelines import (

4
src/diffusers/modular_pipelines/__init__.py
View File

@@ -39,7 +39,7 @@ else:
"InputParam",
"OutputParam",
]
_import_structure["stable_diffusion_xl"] = ["StableDiffusionXLAutoPipeline", "StableDiffusionXLModularLoader"]
_import_structure["stable_diffusion_xl"] = ["StableDiffusionXLAutoBlocks", "StableDiffusionXLModularLoader"]
_import_structure["components_manager"] = ["ComponentsManager"]
if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
@@ -68,7 +68,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
OutputParam,
)
from .stable_diffusion_xl import (
StableDiffusionXLAutoPipeline,
StableDiffusionXLAutoBlocks,
StableDiffusionXLModularLoader,
)
else:

26
src/diffusers/modular_pipelines/stable_diffusion_xl/__init__.py
View File

@@ -21,24 +21,21 @@ except OptionalDependencyNotAvailable:
_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
_import_structure["decoders"] = ["StableDiffusionXLAutoDecodeStep"]
_import_structure["encoders"] = [
"StableDiffusionXLAutoIPAdapterStep",
"StableDiffusionXLAutoVaeEncoderStep",
"StableDiffusionXLTextEncoderStep",
]
_import_structure["modular_block_mappings"] = [
_import_structure["encoders"] = ["StableDiffusionXLTextEncoderStep"]
_import_structure["modular_blocks_presets"] = [
"AUTO_BLOCKS",
"CONTROLNET_BLOCKS",
"CONTROLNET_UNION_BLOCKS",
"IMAGE2IMAGE_BLOCKS",
"INPAINT_BLOCKS",
"IP_ADAPTER_BLOCKS",
"SDXL_SUPPORTED_BLOCKS",
"TEXT2IMAGE_BLOCKS",
"StableDiffusionXLAutoDecodeStep",
"StableDiffusionXLAutoIPAdapterStep",
"StableDiffusionXLAutoVaeEncoderStep",
"StableDiffusionXLAutoBlocks",
]
_import_structure["modular_loader"] = ["StableDiffusionXLModularLoader"]
_import_structure["modular_pipeline_presets"] = ["StableDiffusionXLAutoPipeline"]
if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
try:
@@ -47,24 +44,23 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import * # noqa F403
else:
from .decoders import StableDiffusionXLAutoDecodeStep
from .encoders import (
StableDiffusionXLAutoIPAdapterStep,
StableDiffusionXLAutoVaeEncoderStep,
StableDiffusionXLTextEncoderStep,
)
from .modular_block_mappings import (
from .modular_blocks_presets import (
AUTO_BLOCKS,
CONTROLNET_BLOCKS,
CONTROLNET_UNION_BLOCKS,
IMAGE2IMAGE_BLOCKS,
INPAINT_BLOCKS,
IP_ADAPTER_BLOCKS,
SDXL_SUPPORTED_BLOCKS,
TEXT2IMAGE_BLOCKS,
StableDiffusionXLAutoDecodeStep,
StableDiffusionXLAutoIPAdapterStep,
StableDiffusionXLAutoVaeEncoderStep,
StableDiffusionXLAutoBlocks,
)
from .modular_loader import StableDiffusionXLModularLoader
from .modular_pipeline_presets import StableDiffusionXLAutoPipeline
else:
import sys

109
src/diffusers/modular_pipelines/stable_diffusion_xl/before_denoise.py
View File

@@ -26,10 +26,8 @@ from ...schedulers import EulerDiscreteScheduler
from ...utils import logging
from ...utils.torch_utils import randn_tensor, unwrap_module
from ..modular_pipeline import (
AutoPipelineBlocks,
PipelineBlock,
PipelineState,
SequentialPipelineBlocks,
)
from ..modular_pipeline_utils import ComponentSpec, ConfigSpec, InputParam, OutputParam
from .modular_loader import StableDiffusionXLModularLoader
@@ -1909,110 +1907,3 @@ class StableDiffusionXLControlNetUnionInputStep(PipelineBlock):
self.add_block_state(state, block_state)
return components, state
class StableDiffusionXLControlNetAutoInput(AutoPipelineBlocks):
block_classes = [StableDiffusionXLControlNetUnionInputStep, StableDiffusionXLControlNetInputStep]
block_names = ["controlnet_union", "controlnet"]
block_trigger_inputs = ["control_mode", "control_image"]
@property
def description(self):
return (
"Controlnet Input step that prepare the controlnet input.\n"
+ "This is an auto pipeline block that works for both controlnet and controlnet_union.\n"
+ " - `StableDiffusionXLControlNetUnionInputStep` is called to prepare the controlnet input when `control_mode` and `control_image` are provided.\n"
+ " - `StableDiffusionXLControlNetInputStep` is called to prepare the controlnet input when `control_image` is provided."
)
# Before denoise
class StableDiffusionXLBeforeDenoiseStep(SequentialPipelineBlocks):
block_classes = [
StableDiffusionXLInputStep,
StableDiffusionXLSetTimestepsStep,
StableDiffusionXLPrepareLatentsStep,
StableDiffusionXLPrepareAdditionalConditioningStep,
StableDiffusionXLControlNetAutoInput,
]
block_names = ["input", "set_timesteps", "prepare_latents", "prepare_add_cond", "controlnet_input"]
@property
def description(self):
return (
"Before denoise step that prepare the inputs for the denoise step.\n"
+ "This is a sequential pipeline blocks:\n"
+ " - `StableDiffusionXLInputStep` is used to adjust the batch size of the model inputs\n"
+ " - `StableDiffusionXLSetTimestepsStep` is used to set the timesteps\n"
+ " - `StableDiffusionXLPrepareLatentsStep` is used to prepare the latents\n"
+ " - `StableDiffusionXLPrepareAdditionalConditioningStep` is used to prepare the additional conditioning\n"
+ " - `StableDiffusionXLControlNetAutoInput` is used to prepare the controlnet input"
)
class StableDiffusionXLImg2ImgBeforeDenoiseStep(SequentialPipelineBlocks):
block_classes = [
StableDiffusionXLInputStep,
StableDiffusionXLImg2ImgSetTimestepsStep,
StableDiffusionXLImg2ImgPrepareLatentsStep,
StableDiffusionXLImg2ImgPrepareAdditionalConditioningStep,
StableDiffusionXLControlNetAutoInput,
]
block_names = ["input", "set_timesteps", "prepare_latents", "prepare_add_cond", "controlnet_input"]
@property
def description(self):
return (
"Before denoise step that prepare the inputs for the denoise step for img2img task.\n"
+ "This is a sequential pipeline blocks:\n"
+ " - `StableDiffusionXLInputStep` is used to adjust the batch size of the model inputs\n"
+ " - `StableDiffusionXLImg2ImgSetTimestepsStep` is used to set the timesteps\n"
+ " - `StableDiffusionXLImg2ImgPrepareLatentsStep` is used to prepare the latents\n"
+ " - `StableDiffusionXLImg2ImgPrepareAdditionalConditioningStep` is used to prepare the additional conditioning\n"
+ " - `StableDiffusionXLControlNetAutoInput` is used to prepare the controlnet input"
)
class StableDiffusionXLInpaintBeforeDenoiseStep(SequentialPipelineBlocks):
block_classes = [
StableDiffusionXLInputStep,
StableDiffusionXLImg2ImgSetTimestepsStep,
StableDiffusionXLInpaintPrepareLatentsStep,
StableDiffusionXLImg2ImgPrepareAdditionalConditioningStep,
StableDiffusionXLControlNetAutoInput,
]
block_names = ["input", "set_timesteps", "prepare_latents", "prepare_add_cond", "controlnet_input"]
@property
def description(self):
return (
"Before denoise step that prepare the inputs for the denoise step for inpainting task.\n"
+ "This is a sequential pipeline blocks:\n"
+ " - `StableDiffusionXLInputStep` is used to adjust the batch size of the model inputs\n"
+ " - `StableDiffusionXLImg2ImgSetTimestepsStep` is used to set the timesteps\n"
+ " - `StableDiffusionXLInpaintPrepareLatentsStep` is used to prepare the latents\n"
+ " - `StableDiffusionXLImg2ImgPrepareAdditionalConditioningStep` is used to prepare the additional conditioning\n"
+ " - `StableDiffusionXLControlNetAutoInput` is used to prepare the controlnet input"
)
class StableDiffusionXLAutoBeforeDenoiseStep(AutoPipelineBlocks):
block_classes = [
StableDiffusionXLInpaintBeforeDenoiseStep,
StableDiffusionXLImg2ImgBeforeDenoiseStep,
StableDiffusionXLBeforeDenoiseStep,
]
block_names = ["inpaint", "img2img", "text2img"]
block_trigger_inputs = ["mask", "image_latents", None]
@property
def description(self):
return (
"Before denoise step that prepare the inputs for the denoise step.\n"
+ "This is an auto pipeline block that works for text2img, img2img and inpainting tasks as well as controlnet, controlnet_union.\n"
+ " - `StableDiffusionXLInpaintBeforeDenoiseStep` (inpaint) is used when both `mask` and `image_latents` are provided.\n"
+ " - `StableDiffusionXLImg2ImgBeforeDenoiseStep` (img2img) is used when only `image_latents` is provided.\n"
+ " - `StableDiffusionXLBeforeDenoiseStep` (text2img) is used when both `image_latents` and `mask` are not provided.\n"
+ " - `StableDiffusionXLControlNetUnionInputStep` is called to prepare the controlnet input when `control_mode` and `control_image` are provided.\n"
+ " - `StableDiffusionXLControlNetInputStep` is called to prepare the controlnet input when `control_image` is provided."
)

31
src/diffusers/modular_pipelines/stable_diffusion_xl/decoders.py
View File

@@ -24,10 +24,8 @@ from ...models import AutoencoderKL
from ...models.attention_processor import AttnProcessor2_0, XFormersAttnProcessor
from ...utils import logging
from ..modular_pipeline import (
AutoPipelineBlocks,
PipelineBlock,
PipelineState,
SequentialPipelineBlocks,
)
from ..modular_pipeline_utils import ComponentSpec, InputParam, OutputParam
@@ -219,32 +217,3 @@ class StableDiffusionXLInpaintOverlayMaskStep(PipelineBlock):
self.add_block_state(state, block_state)
return components, state
class StableDiffusionXLInpaintDecodeStep(SequentialPipelineBlocks):
block_classes = [StableDiffusionXLDecodeStep, StableDiffusionXLInpaintOverlayMaskStep]
block_names = ["decode", "mask_overlay"]
@property
def description(self):
return (
"Inpaint decode step that decode the denoised latents into images outputs.\n"
+ "This is a sequential pipeline blocks:\n"
+ " - `StableDiffusionXLDecodeStep` is used to decode the denoised latents into images\n"
+ " - `StableDiffusionXLInpaintOverlayMaskStep` is used to overlay the mask on the image"
)
class StableDiffusionXLAutoDecodeStep(AutoPipelineBlocks):
block_classes = [StableDiffusionXLInpaintDecodeStep, StableDiffusionXLDecodeStep]
block_names = ["inpaint", "non-inpaint"]
block_trigger_inputs = ["padding_mask_crop", None]
@property
def description(self):
return (
"Decode step that decode the denoised latents into images outputs.\n"
+ "This is an auto pipeline block that works for inpainting and non-inpainting tasks.\n"
+ " - `StableDiffusionXLInpaintDecodeStep` (inpaint) is used when `padding_mask_crop` is provided.\n"
+ " - `StableDiffusionXLDecodeStep` (non-inpaint) is used when `padding_mask_crop` is not provided."
)

101
src/diffusers/modular_pipelines/stable_diffusion_xl/denoise.py
View File

@@ -23,7 +23,6 @@ from ...models import ControlNetModel, UNet2DConditionModel
from ...schedulers import EulerDiscreteScheduler
from ...utils import logging
from ..modular_pipeline import (
AutoPipelineBlocks,
BlockState,
LoopSequentialPipelineBlocks,
PipelineBlock,
@@ -49,7 +48,11 @@ class StableDiffusionXLLoopBeforeDenoiser(PipelineBlock):
@property
def description(self) -> str:
return "step within the denoising loop that prepare the latent input for the denoiser. This block should be used to compose the `blocks` attribute of a `LoopSequentialPipelineBlocks` object (e.g. `StableDiffusionXLDenoiseLoopWrapper`)"
return (
"step within the denoising loop that prepare the latent input for the denoiser. "
"This block should be used to compose the `blocks` attribute of a `LoopSequentialPipelineBlocks` "
"object (e.g. `StableDiffusionXLDenoiseLoopWrapper`)"
)
@property
def intermediates_inputs(self) -> List[str]:
@@ -82,7 +85,10 @@ class StableDiffusionXLInpaintLoopBeforeDenoiser(PipelineBlock):
@property
def description(self) -> str:
return "step within the denoising loop that prepare the latent input for the denoiser (for inpainting workflow only). This block should be used to compose the `blocks` attribute of a `LoopSequentialPipelineBlocks` object"
return (
"step within the denoising loop that prepare the latent input for the denoiser (for inpainting workflow only). "
"This block should be used to compose the `blocks` attribute of a `LoopSequentialPipelineBlocks` object"
)
@property
def intermediates_inputs(self) -> List[str]:
@@ -155,7 +161,11 @@ class StableDiffusionXLLoopDenoiser(PipelineBlock):
@property
def description(self) -> str:
return "Step within the denoising loop that denoise the latents with guidance. This block should be used to compose the `blocks` attribute of a `LoopSequentialPipelineBlocks` object (e.g. `StableDiffusionXLDenoiseLoopWrapper`)"
return (
"Step within the denoising loop that denoise the latents with guidance. "
"This block should be used to compose the `blocks` attribute of a `LoopSequentialPipelineBlocks` "
"object (e.g. `StableDiffusionXLDenoiseLoopWrapper`)"
)
@property
def inputs(self) -> List[Tuple[str, Any]]:
@@ -257,7 +267,11 @@ class StableDiffusionXLControlNetLoopDenoiser(PipelineBlock):
@property
def description(self) -> str:
return "step within the denoising loop that denoise the latents with guidance (with controlnet). This block should be used to compose the `blocks` attribute of a `LoopSequentialPipelineBlocks` object (e.g. `StableDiffusionXLDenoiseLoopWrapper`)"
return (
"step within the denoising loop that denoise the latents with guidance (with controlnet). "
"This block should be used to compose the `blocks` attribute of a `LoopSequentialPipelineBlocks` "
"object (e.g. `StableDiffusionXLDenoiseLoopWrapper`)"
)
@property
def inputs(self) -> List[Tuple[str, Any]]:
@@ -446,7 +460,11 @@ class StableDiffusionXLLoopAfterDenoiser(PipelineBlock):
@property
def description(self) -> str:
return "step within the denoising loop that update the latents. This block should be used to compose the `blocks` attribute of a `LoopSequentialPipelineBlocks` object (e.g. `StableDiffusionXLDenoiseLoopWrapper`)"
return (
"step within the denoising loop that update the latents. "
"This block should be used to compose the `blocks` attribute of a `LoopSequentialPipelineBlocks` "
"object (e.g. `StableDiffusionXLDenoiseLoopWrapper`)"
)
@property
def inputs(self) -> List[Tuple[str, Any]]:
@@ -514,7 +532,11 @@ class StableDiffusionXLInpaintLoopAfterDenoiser(PipelineBlock):
@property
def description(self) -> str:
return "step within the denoising loop that update the latents (for inpainting workflow only). This block should be used to compose the `blocks` attribute of a `LoopSequentialPipelineBlocks` object (e.g. `StableDiffusionXLDenoiseLoopWrapper`)"
return (
"step within the denoising loop that update the latents (for inpainting workflow only). "
"This block should be used to compose the `blocks` attribute of a `LoopSequentialPipelineBlocks` "
"object (e.g. `StableDiffusionXLDenoiseLoopWrapper`)"
)
@property
def inputs(self) -> List[Tuple[str, Any]]:
@@ -619,7 +641,10 @@ class StableDiffusionXLDenoiseLoopWrapper(LoopSequentialPipelineBlocks):
@property
def description(self) -> str:
return "Pipeline block that iteratively denoise the latents over `timesteps`. The specific steps with each iteration can be customized with `blocks` attributes"
return (
"Pipeline block that iteratively denoise the latents over `timesteps`. "
"The specific steps with each iteration can be customized with `blocks` attributes"
)
@property
def loop_expected_components(self) -> List[ComponentSpec]:
@@ -679,7 +704,7 @@ class StableDiffusionXLDenoiseLoopWrapper(LoopSequentialPipelineBlocks):
# composing the denoising loops
class StableDiffusionXLDenoiseLoop(StableDiffusionXLDenoiseLoopWrapper):
class StableDiffusionXLDenoiseStep(StableDiffusionXLDenoiseLoopWrapper):
block_classes = [
StableDiffusionXLLoopBeforeDenoiser,
StableDiffusionXLLoopDenoiser,
@@ -696,11 +721,12 @@ class StableDiffusionXLDenoiseLoop(StableDiffusionXLDenoiseLoopWrapper):
" - `StableDiffusionXLLoopBeforeDenoiser`\n"
" - `StableDiffusionXLLoopDenoiser`\n"
" - `StableDiffusionXLLoopAfterDenoiser`\n"
"This block supports both text2img and img2img tasks."
)
# control_cond
class StableDiffusionXLControlNetDenoiseLoop(StableDiffusionXLDenoiseLoopWrapper):
class StableDiffusionXLControlNetDenoiseStep(StableDiffusionXLDenoiseLoopWrapper):
block_classes = [
StableDiffusionXLLoopBeforeDenoiser,
StableDiffusionXLControlNetLoopDenoiser,
@@ -717,11 +743,12 @@ class StableDiffusionXLControlNetDenoiseLoop(StableDiffusionXLDenoiseLoopWrapper
" - `StableDiffusionXLLoopBeforeDenoiser`\n"
" - `StableDiffusionXLControlNetLoopDenoiser`\n"
" - `StableDiffusionXLLoopAfterDenoiser`\n"
"This block supports using controlnet for both text2img and img2img tasks."
)
# mask
class StableDiffusionXLInpaintDenoiseLoop(StableDiffusionXLDenoiseLoopWrapper):
class StableDiffusionXLInpaintDenoiseStep(StableDiffusionXLDenoiseLoopWrapper):
block_classes = [
StableDiffusionXLInpaintLoopBeforeDenoiser,
StableDiffusionXLLoopDenoiser,
@@ -738,11 +765,12 @@ class StableDiffusionXLInpaintDenoiseLoop(StableDiffusionXLDenoiseLoopWrapper):
" - `StableDiffusionXLInpaintLoopBeforeDenoiser`\n"
" - `StableDiffusionXLLoopDenoiser`\n"
" - `StableDiffusionXLInpaintLoopAfterDenoiser`\n"
"This block onlysupports inpainting tasks."
)
# control_cond + mask
class StableDiffusionXLInpaintControlNetDenoiseLoop(StableDiffusionXLDenoiseLoopWrapper):
class StableDiffusionXLInpaintControlNetDenoiseStep(StableDiffusionXLDenoiseLoopWrapper):
block_classes = [
StableDiffusionXLInpaintLoopBeforeDenoiser,
StableDiffusionXLControlNetLoopDenoiser,
@@ -759,52 +787,5 @@ class StableDiffusionXLInpaintControlNetDenoiseLoop(StableDiffusionXLDenoiseLoop
" - `StableDiffusionXLInpaintLoopBeforeDenoiser`\n"
" - `StableDiffusionXLControlNetLoopDenoiser`\n"
" - `StableDiffusionXLInpaintLoopAfterDenoiser`\n"
)
# all task without controlnet
class StableDiffusionXLDenoiseStep(AutoPipelineBlocks):
block_classes = [StableDiffusionXLInpaintDenoiseLoop, StableDiffusionXLDenoiseLoop]
block_names = ["inpaint_denoise", "denoise"]
block_trigger_inputs = ["mask", None]
@property
def description(self) -> str:
return (
"Denoise step that iteratively denoise the latents. "
"This is a auto pipeline block that works for text2img, img2img and inpainting tasks."
" - `StableDiffusionXLDenoiseStep` (denoise) is used when no mask is provided."
" - `StableDiffusionXLInpaintDenoiseStep` (inpaint_denoise) is used when mask is provided."
)
# all task with controlnet
class StableDiffusionXLControlNetDenoiseStep(AutoPipelineBlocks):
block_classes = [StableDiffusionXLInpaintControlNetDenoiseLoop, StableDiffusionXLControlNetDenoiseLoop]
block_names = ["inpaint_controlnet_denoise", "controlnet_denoise"]
block_trigger_inputs = ["mask", None]
@property
def description(self) -> str:
return (
"Denoise step that iteratively denoise the latents with controlnet. "
"This is a auto pipeline block that works for text2img, img2img and inpainting tasks."
" - `StableDiffusionXLControlNetDenoiseStep` (controlnet_denoise) is used when no mask is provided."
" - `StableDiffusionXLInpaintControlNetDenoiseStep` (inpaint_controlnet_denoise) is used when mask is provided."
)
# all task with or without controlnet
class StableDiffusionXLAutoDenoiseStep(AutoPipelineBlocks):
block_classes = [StableDiffusionXLControlNetDenoiseStep, StableDiffusionXLDenoiseStep]
block_names = ["controlnet_denoise", "denoise"]
block_trigger_inputs = ["controlnet_cond", None]
@property
def description(self) -> str:
return (
"Denoise step that iteratively denoise the latents. "
"This is a auto pipeline block that works for text2img, img2img and inpainting tasks. And can be used with or without controlnet."
" - `StableDiffusionXLDenoiseStep` (denoise) is used when no controlnet_cond is provided (work for text2img, img2img and inpainting tasks)."
" - `StableDiffusionXLControlNetDenoiseStep` (controlnet_denoise) is used when controlnet_cond is provided (work for text2img, img2img and inpainting tasks)."
"This block only supports using controlnet for inpainting tasks."
)

31
src/diffusers/modular_pipelines/stable_diffusion_xl/encoders.py
View File

@@ -26,7 +26,7 @@ from transformers import (
from ...configuration_utils import FrozenDict
from ...guiders import ClassifierFreeGuidance
from ...image_processor import PipelineImageInput, VaeImageProcessor
from ...loaders import ModularIPAdapterMixin, StableDiffusionXLLoraLoaderMixin, TextualInversionLoaderMixin
from ...loaders import StableDiffusionXLLoraLoaderMixin, TextualInversionLoaderMixin
from ...models import AutoencoderKL, ImageProjection, UNet2DConditionModel
from ...models.lora import adjust_lora_scale_text_encoder
from ...utils import (
@@ -35,7 +35,7 @@ from ...utils import (
scale_lora_layers,
unscale_lora_layers,
)
from ..modular_pipeline import AutoPipelineBlocks, PipelineBlock, PipelineState
from ..modular_pipeline import PipelineBlock, PipelineState
from ..modular_pipeline_utils import ComponentSpec, ConfigSpec, InputParam, OutputParam
from .modular_loader import StableDiffusionXLModularLoader
@@ -893,30 +893,3 @@ class StableDiffusionXLInpaintVaeEncoderStep(PipelineBlock):
self.add_block_state(state, block_state)
return components, state
# auto blocks (YiYi TODO: maybe move all the auto blocks to a separate file)
# Encode
class StableDiffusionXLAutoVaeEncoderStep(AutoPipelineBlocks):
block_classes = [StableDiffusionXLInpaintVaeEncoderStep, StableDiffusionXLVaeEncoderStep]
block_names = ["inpaint", "img2img"]
block_trigger_inputs = ["mask_image", "image"]
@property
def description(self):
return (
"Vae encoder step that encode the image inputs into their latent representations.\n"
+ "This is an auto pipeline block that works for both inpainting and img2img tasks.\n"
+ " - `StableDiffusionXLInpaintVaeEncoderStep` (inpaint) is used when both `mask_image` and `image` are provided.\n"
+ " - `StableDiffusionXLVaeEncoderStep` (img2img) is used when only `image` is provided."
)
class StableDiffusionXLAutoIPAdapterStep(AutoPipelineBlocks, ModularIPAdapterMixin):
block_classes = [StableDiffusionXLIPAdapterStep]
block_names = ["ip_adapter"]
block_trigger_inputs = ["ip_adapter_image"]
@property
def description(self):
return "Run IP Adapter step if `ip_adapter_image` is provided."

2
src/diffusers/utils/dummy_torch_and_transformers_objects.py
View File

@@ -2,7 +2,7 @@
from ..utils import DummyObject, requires_backends
class StableDiffusionXLAutoPipeline(metaclass=DummyObject):
class StableDiffusionXLAutoBlocks(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):