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Browse files- main/README.md +2 -0
- main/pipeline_faithdiff_stable_diffusion_xl.py +12 -0
- main/pipeline_flux_kontext_multiple_images.py +13 -0
- main/pipeline_flux_rf_inversion.py +25 -0
- main/pipeline_flux_semantic_guidance.py +13 -0
- main/pipeline_flux_with_cfg.py +25 -0
- main/pipeline_stable_diffusion_3_differential_img2img.py +1 -5
- main/pipeline_stable_diffusion_boxdiff.py +24 -0
- main/pipeline_stable_diffusion_pag.py +24 -0
- main/pipeline_stg_hunyuan_video.py +25 -1
- main/pipeline_stg_mochi.py +25 -5
main/README.md
CHANGED
@@ -88,6 +88,8 @@ PIXART-α Controlnet pipeline | Implementation of the controlnet model for pixar
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| FaithDiff Stable Diffusion XL Pipeline | Implementation of [(CVPR 2025) FaithDiff: Unleashing Diffusion Priors for Faithful Image Super-resolutionUnleashing Diffusion Priors for Faithful Image Super-resolution](https://huggingface.co/papers/2411.18824) - FaithDiff is a faithful image super-resolution method that leverages latent diffusion models by actively adapting the diffusion prior and jointly fine-tuning its components (encoder and diffusion model) with an alignment module to ensure high fidelity and structural consistency. | [FaithDiff Stable Diffusion XL Pipeline](#faithdiff-stable-diffusion-xl-pipeline) | [](https://huggingface.co/jychen9811/FaithDiff) | [Junyang Chen, Jinshan Pan, Jiangxin Dong, IMAG Lab, (Adapted by Eliseu Silva)](https://github.com/JyChen9811/FaithDiff) |
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| Stable Diffusion 3 InstructPix2Pix Pipeline | Implementation of Stable Diffusion 3 InstructPix2Pix Pipeline | [Stable Diffusion 3 InstructPix2Pix Pipeline](#stable-diffusion-3-instructpix2pix-pipeline) | [](https://huggingface.co/BleachNick/SD3_UltraEdit_freeform) [](https://huggingface.co/CaptainZZZ/sd3-instructpix2pix) | [Jiayu Zhang](https://github.com/xduzhangjiayu) and [Haozhe Zhao](https://github.com/HaozheZhao)|
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| Flux Kontext multiple images | A modified version of the `FluxKontextPipeline` that supports calling Flux Kontext with multiple reference images.| [Flux Kontext multiple input Pipeline](#flux-kontext-multiple-images) | - | [Net-Mist](https://github.com/Net-Mist) |
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To load a custom pipeline you just need to pass the `custom_pipeline` argument to `DiffusionPipeline`, as one of the files in `diffusers/examples/community`. Feel free to send a PR with your own pipelines, we will merge them quickly.
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```py
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| FaithDiff Stable Diffusion XL Pipeline | Implementation of [(CVPR 2025) FaithDiff: Unleashing Diffusion Priors for Faithful Image Super-resolutionUnleashing Diffusion Priors for Faithful Image Super-resolution](https://huggingface.co/papers/2411.18824) - FaithDiff is a faithful image super-resolution method that leverages latent diffusion models by actively adapting the diffusion prior and jointly fine-tuning its components (encoder and diffusion model) with an alignment module to ensure high fidelity and structural consistency. | [FaithDiff Stable Diffusion XL Pipeline](#faithdiff-stable-diffusion-xl-pipeline) | [](https://huggingface.co/jychen9811/FaithDiff) | [Junyang Chen, Jinshan Pan, Jiangxin Dong, IMAG Lab, (Adapted by Eliseu Silva)](https://github.com/JyChen9811/FaithDiff) |
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| Stable Diffusion 3 InstructPix2Pix Pipeline | Implementation of Stable Diffusion 3 InstructPix2Pix Pipeline | [Stable Diffusion 3 InstructPix2Pix Pipeline](#stable-diffusion-3-instructpix2pix-pipeline) | [](https://huggingface.co/BleachNick/SD3_UltraEdit_freeform) [](https://huggingface.co/CaptainZZZ/sd3-instructpix2pix) | [Jiayu Zhang](https://github.com/xduzhangjiayu) and [Haozhe Zhao](https://github.com/HaozheZhao)|
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| Flux Kontext multiple images | A modified version of the `FluxKontextPipeline` that supports calling Flux Kontext with multiple reference images.| [Flux Kontext multiple input Pipeline](#flux-kontext-multiple-images) | - | [Net-Mist](https://github.com/Net-Mist) |
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+
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+
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To load a custom pipeline you just need to pass the `custom_pipeline` argument to `DiffusionPipeline`, as one of the files in `diffusers/examples/community`. Feel free to send a PR with your own pipelines, we will merge them quickly.
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```py
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main/pipeline_faithdiff_stable_diffusion_xl.py
CHANGED
@@ -1705,6 +1705,12 @@ class FaithDiffStableDiffusionXLPipeline(
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compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
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processing larger images.
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"""
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self.vae.enable_tiling()
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self.unet.denoise_encoder.enable_tiling()
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@@ -1713,6 +1719,12 @@ class FaithDiffStableDiffusionXLPipeline(
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Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
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computing decoding in one step.
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"""
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self.vae.disable_tiling()
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self.unet.denoise_encoder.disable_tiling()
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compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
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processing larger images.
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"""
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+
depr_message = f"Calling `enable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.enable_tiling()`."
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+
deprecate(
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"enable_vae_tiling",
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"0.40.0",
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+
depr_message,
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)
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self.vae.enable_tiling()
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self.unet.denoise_encoder.enable_tiling()
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Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
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computing decoding in one step.
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"""
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+
depr_message = f"Calling `disable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.disable_tiling()`."
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+
deprecate(
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"disable_vae_tiling",
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"0.40.0",
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+
depr_message,
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)
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self.vae.disable_tiling()
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self.unet.denoise_encoder.disable_tiling()
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main/pipeline_flux_kontext_multiple_images.py
CHANGED
@@ -35,6 +35,7 @@ from diffusers.pipelines.pipeline_utils import DiffusionPipeline
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from diffusers.schedulers import FlowMatchEulerDiscreteScheduler
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from diffusers.utils import (
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USE_PEFT_BACKEND,
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is_torch_xla_available,
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logging,
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replace_example_docstring,
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compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
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processing larger images.
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"""
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self.vae.enable_tiling()
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# Copied from diffusers.pipelines.flux.pipeline_flux.FluxPipeline.disable_vae_tiling
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Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
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computing decoding in one step.
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"""
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self.vae.disable_tiling()
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def preprocess_image(self, image: PipelineImageInput, _auto_resize: bool, multiple_of: int) -> torch.Tensor:
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from diffusers.schedulers import FlowMatchEulerDiscreteScheduler
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from diffusers.utils import (
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USE_PEFT_BACKEND,
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+
deprecate,
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is_torch_xla_available,
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logging,
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replace_example_docstring,
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compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
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processing larger images.
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"""
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+
depr_message = f"Calling `enable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.enable_tiling()`."
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+
deprecate(
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"enable_vae_tiling",
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+
"0.40.0",
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+
depr_message,
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+
)
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self.vae.enable_tiling()
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# Copied from diffusers.pipelines.flux.pipeline_flux.FluxPipeline.disable_vae_tiling
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Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
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computing decoding in one step.
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"""
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+
depr_message = f"Calling `disable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.disable_tiling()`."
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+
deprecate(
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"disable_vae_tiling",
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+
"0.40.0",
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+
depr_message,
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)
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self.vae.disable_tiling()
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def preprocess_image(self, image: PipelineImageInput, _auto_resize: bool, multiple_of: int) -> torch.Tensor:
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main/pipeline_flux_rf_inversion.py
CHANGED
@@ -30,6 +30,7 @@ from diffusers.pipelines.pipeline_utils import DiffusionPipeline
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from diffusers.schedulers import FlowMatchEulerDiscreteScheduler
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from diffusers.utils import (
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USE_PEFT_BACKEND,
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is_torch_xla_available,
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logging,
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replace_example_docstring,
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@@ -526,6 +527,12 @@ class RFInversionFluxPipeline(
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Enable sliced VAE decoding. When this option is enabled, the VAE will split the input tensor in slices to
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compute decoding in several steps. This is useful to save some memory and allow larger batch sizes.
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"""
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self.vae.enable_slicing()
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def disable_vae_slicing(self):
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@@ -533,6 +540,12 @@ class RFInversionFluxPipeline(
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Disable sliced VAE decoding. If `enable_vae_slicing` was previously enabled, this method will go back to
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computing decoding in one step.
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"""
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self.vae.disable_slicing()
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def enable_vae_tiling(self):
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@@ -541,6 +554,12 @@ class RFInversionFluxPipeline(
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compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
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processing larger images.
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"""
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self.vae.enable_tiling()
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def disable_vae_tiling(self):
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@@ -548,6 +567,12 @@ class RFInversionFluxPipeline(
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548 |
Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
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computing decoding in one step.
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550 |
"""
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self.vae.disable_tiling()
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def prepare_latents_inversion(
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from diffusers.schedulers import FlowMatchEulerDiscreteScheduler
|
31 |
from diffusers.utils import (
|
32 |
USE_PEFT_BACKEND,
|
33 |
+
deprecate,
|
34 |
is_torch_xla_available,
|
35 |
logging,
|
36 |
replace_example_docstring,
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|
527 |
Enable sliced VAE decoding. When this option is enabled, the VAE will split the input tensor in slices to
|
528 |
compute decoding in several steps. This is useful to save some memory and allow larger batch sizes.
|
529 |
"""
|
530 |
+
depr_message = f"Calling `enable_vae_slicing()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.enable_slicing()`."
|
531 |
+
deprecate(
|
532 |
+
"enable_vae_slicing",
|
533 |
+
"0.40.0",
|
534 |
+
depr_message,
|
535 |
+
)
|
536 |
self.vae.enable_slicing()
|
537 |
|
538 |
def disable_vae_slicing(self):
|
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|
540 |
Disable sliced VAE decoding. If `enable_vae_slicing` was previously enabled, this method will go back to
|
541 |
computing decoding in one step.
|
542 |
"""
|
543 |
+
depr_message = f"Calling `disable_vae_slicing()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.disable_slicing()`."
|
544 |
+
deprecate(
|
545 |
+
"disable_vae_slicing",
|
546 |
+
"0.40.0",
|
547 |
+
depr_message,
|
548 |
+
)
|
549 |
self.vae.disable_slicing()
|
550 |
|
551 |
def enable_vae_tiling(self):
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|
554 |
compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
|
555 |
processing larger images.
|
556 |
"""
|
557 |
+
depr_message = f"Calling `enable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.enable_tiling()`."
|
558 |
+
deprecate(
|
559 |
+
"enable_vae_tiling",
|
560 |
+
"0.40.0",
|
561 |
+
depr_message,
|
562 |
+
)
|
563 |
self.vae.enable_tiling()
|
564 |
|
565 |
def disable_vae_tiling(self):
|
|
|
567 |
Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
|
568 |
computing decoding in one step.
|
569 |
"""
|
570 |
+
depr_message = f"Calling `disable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.disable_tiling()`."
|
571 |
+
deprecate(
|
572 |
+
"disable_vae_tiling",
|
573 |
+
"0.40.0",
|
574 |
+
depr_message,
|
575 |
+
)
|
576 |
self.vae.disable_tiling()
|
577 |
|
578 |
def prepare_latents_inversion(
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main/pipeline_flux_semantic_guidance.py
CHANGED
@@ -35,6 +35,7 @@ from diffusers.pipelines.pipeline_utils import DiffusionPipeline
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35 |
from diffusers.schedulers import FlowMatchEulerDiscreteScheduler
|
36 |
from diffusers.utils import (
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37 |
USE_PEFT_BACKEND,
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|
38 |
is_torch_xla_available,
|
39 |
logging,
|
40 |
replace_example_docstring,
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@@ -702,6 +703,12 @@ class FluxSemanticGuidancePipeline(
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702 |
compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
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703 |
processing larger images.
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"""
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self.vae.enable_tiling()
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# Copied from diffusers.pipelines.flux.pipeline_flux.FluxPipeline.disable_vae_tiling
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@@ -710,6 +717,12 @@ class FluxSemanticGuidancePipeline(
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710 |
Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
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711 |
computing decoding in one step.
|
712 |
"""
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self.vae.disable_tiling()
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714 |
|
715 |
# Copied from diffusers.pipelines.flux.pipeline_flux.FluxPipeline.prepare_latents
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|
35 |
from diffusers.schedulers import FlowMatchEulerDiscreteScheduler
|
36 |
from diffusers.utils import (
|
37 |
USE_PEFT_BACKEND,
|
38 |
+
deprecate,
|
39 |
is_torch_xla_available,
|
40 |
logging,
|
41 |
replace_example_docstring,
|
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|
703 |
compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
|
704 |
processing larger images.
|
705 |
"""
|
706 |
+
depr_message = f"Calling `enable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.enable_tiling()`."
|
707 |
+
deprecate(
|
708 |
+
"enable_vae_tiling",
|
709 |
+
"0.40.0",
|
710 |
+
depr_message,
|
711 |
+
)
|
712 |
self.vae.enable_tiling()
|
713 |
|
714 |
# Copied from diffusers.pipelines.flux.pipeline_flux.FluxPipeline.disable_vae_tiling
|
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|
717 |
Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
|
718 |
computing decoding in one step.
|
719 |
"""
|
720 |
+
depr_message = f"Calling `disable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.disable_tiling()`."
|
721 |
+
deprecate(
|
722 |
+
"disable_vae_tiling",
|
723 |
+
"0.40.0",
|
724 |
+
depr_message,
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725 |
+
)
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726 |
self.vae.disable_tiling()
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727 |
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728 |
# Copied from diffusers.pipelines.flux.pipeline_flux.FluxPipeline.prepare_latents
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main/pipeline_flux_with_cfg.py
CHANGED
@@ -28,6 +28,7 @@ from diffusers.pipelines.pipeline_utils import DiffusionPipeline
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from diffusers.schedulers import FlowMatchEulerDiscreteScheduler
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29 |
from diffusers.utils import (
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30 |
USE_PEFT_BACKEND,
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31 |
is_torch_xla_available,
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32 |
logging,
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33 |
replace_example_docstring,
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@@ -503,6 +504,12 @@ class FluxCFGPipeline(DiffusionPipeline, FluxLoraLoaderMixin, FromSingleFileMixi
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503 |
Enable sliced VAE decoding. When this option is enabled, the VAE will split the input tensor in slices to
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504 |
compute decoding in several steps. This is useful to save some memory and allow larger batch sizes.
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505 |
"""
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self.vae.enable_slicing()
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def disable_vae_slicing(self):
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510 |
Disable sliced VAE decoding. If `enable_vae_slicing` was previously enabled, this method will go back to
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511 |
computing decoding in one step.
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"""
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513 |
self.vae.disable_slicing()
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515 |
def enable_vae_tiling(self):
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@@ -518,6 +531,12 @@ class FluxCFGPipeline(DiffusionPipeline, FluxLoraLoaderMixin, FromSingleFileMixi
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518 |
compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
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519 |
processing larger images.
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"""
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self.vae.enable_tiling()
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def disable_vae_tiling(self):
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@@ -525,6 +544,12 @@ class FluxCFGPipeline(DiffusionPipeline, FluxLoraLoaderMixin, FromSingleFileMixi
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525 |
Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
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526 |
computing decoding in one step.
|
527 |
"""
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self.vae.disable_tiling()
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529 |
|
530 |
def prepare_latents(
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|
28 |
from diffusers.schedulers import FlowMatchEulerDiscreteScheduler
|
29 |
from diffusers.utils import (
|
30 |
USE_PEFT_BACKEND,
|
31 |
+
deprecate,
|
32 |
is_torch_xla_available,
|
33 |
logging,
|
34 |
replace_example_docstring,
|
|
|
504 |
Enable sliced VAE decoding. When this option is enabled, the VAE will split the input tensor in slices to
|
505 |
compute decoding in several steps. This is useful to save some memory and allow larger batch sizes.
|
506 |
"""
|
507 |
+
depr_message = f"Calling `enable_vae_slicing()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.enable_slicing()`."
|
508 |
+
deprecate(
|
509 |
+
"enable_vae_slicing",
|
510 |
+
"0.40.0",
|
511 |
+
depr_message,
|
512 |
+
)
|
513 |
self.vae.enable_slicing()
|
514 |
|
515 |
def disable_vae_slicing(self):
|
|
|
517 |
Disable sliced VAE decoding. If `enable_vae_slicing` was previously enabled, this method will go back to
|
518 |
computing decoding in one step.
|
519 |
"""
|
520 |
+
depr_message = f"Calling `disable_vae_slicing()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.disable_slicing()`."
|
521 |
+
deprecate(
|
522 |
+
"disable_vae_slicing",
|
523 |
+
"0.40.0",
|
524 |
+
depr_message,
|
525 |
+
)
|
526 |
self.vae.disable_slicing()
|
527 |
|
528 |
def enable_vae_tiling(self):
|
|
|
531 |
compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
|
532 |
processing larger images.
|
533 |
"""
|
534 |
+
depr_message = f"Calling `enable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.enable_tiling()`."
|
535 |
+
deprecate(
|
536 |
+
"enable_vae_tiling",
|
537 |
+
"0.40.0",
|
538 |
+
depr_message,
|
539 |
+
)
|
540 |
self.vae.enable_tiling()
|
541 |
|
542 |
def disable_vae_tiling(self):
|
|
|
544 |
Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
|
545 |
computing decoding in one step.
|
546 |
"""
|
547 |
+
depr_message = f"Calling `disable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.disable_tiling()`."
|
548 |
+
deprecate(
|
549 |
+
"disable_vae_tiling",
|
550 |
+
"0.40.0",
|
551 |
+
depr_message,
|
552 |
+
)
|
553 |
self.vae.disable_tiling()
|
554 |
|
555 |
def prepare_latents(
|
main/pipeline_stable_diffusion_3_differential_img2img.py
CHANGED
@@ -29,11 +29,7 @@ from diffusers.models.transformers import SD3Transformer2DModel
|
|
29 |
from diffusers.pipelines.pipeline_utils import DiffusionPipeline
|
30 |
from diffusers.pipelines.stable_diffusion_3.pipeline_output import StableDiffusion3PipelineOutput
|
31 |
from diffusers.schedulers import FlowMatchEulerDiscreteScheduler
|
32 |
-
from diffusers.utils import
|
33 |
-
is_torch_xla_available,
|
34 |
-
logging,
|
35 |
-
replace_example_docstring,
|
36 |
-
)
|
37 |
from diffusers.utils.torch_utils import randn_tensor
|
38 |
|
39 |
|
|
|
29 |
from diffusers.pipelines.pipeline_utils import DiffusionPipeline
|
30 |
from diffusers.pipelines.stable_diffusion_3.pipeline_output import StableDiffusion3PipelineOutput
|
31 |
from diffusers.schedulers import FlowMatchEulerDiscreteScheduler
|
32 |
+
from diffusers.utils import is_torch_xla_available, logging, replace_example_docstring
|
|
|
|
|
|
|
|
|
33 |
from diffusers.utils.torch_utils import randn_tensor
|
34 |
|
35 |
|
main/pipeline_stable_diffusion_boxdiff.py
CHANGED
@@ -504,6 +504,12 @@ class StableDiffusionBoxDiffPipeline(
|
|
504 |
Enable sliced VAE decoding. When this option is enabled, the VAE will split the input tensor in slices to
|
505 |
compute decoding in several steps. This is useful to save some memory and allow larger batch sizes.
|
506 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
507 |
self.vae.enable_slicing()
|
508 |
|
509 |
def disable_vae_slicing(self):
|
@@ -511,6 +517,12 @@ class StableDiffusionBoxDiffPipeline(
|
|
511 |
Disable sliced VAE decoding. If `enable_vae_slicing` was previously enabled, this method will go back to
|
512 |
computing decoding in one step.
|
513 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
514 |
self.vae.disable_slicing()
|
515 |
|
516 |
def enable_vae_tiling(self):
|
@@ -519,6 +531,12 @@ class StableDiffusionBoxDiffPipeline(
|
|
519 |
compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
|
520 |
processing larger images.
|
521 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
522 |
self.vae.enable_tiling()
|
523 |
|
524 |
def disable_vae_tiling(self):
|
@@ -526,6 +544,12 @@ class StableDiffusionBoxDiffPipeline(
|
|
526 |
Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
|
527 |
computing decoding in one step.
|
528 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
529 |
self.vae.disable_tiling()
|
530 |
|
531 |
def _encode_prompt(
|
|
|
504 |
Enable sliced VAE decoding. When this option is enabled, the VAE will split the input tensor in slices to
|
505 |
compute decoding in several steps. This is useful to save some memory and allow larger batch sizes.
|
506 |
"""
|
507 |
+
depr_message = f"Calling `enable_vae_slicing()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.enable_slicing()`."
|
508 |
+
deprecate(
|
509 |
+
"enable_vae_slicing",
|
510 |
+
"0.40.0",
|
511 |
+
depr_message,
|
512 |
+
)
|
513 |
self.vae.enable_slicing()
|
514 |
|
515 |
def disable_vae_slicing(self):
|
|
|
517 |
Disable sliced VAE decoding. If `enable_vae_slicing` was previously enabled, this method will go back to
|
518 |
computing decoding in one step.
|
519 |
"""
|
520 |
+
depr_message = f"Calling `disable_vae_slicing()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.disable_slicing()`."
|
521 |
+
deprecate(
|
522 |
+
"disable_vae_slicing",
|
523 |
+
"0.40.0",
|
524 |
+
depr_message,
|
525 |
+
)
|
526 |
self.vae.disable_slicing()
|
527 |
|
528 |
def enable_vae_tiling(self):
|
|
|
531 |
compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
|
532 |
processing larger images.
|
533 |
"""
|
534 |
+
depr_message = f"Calling `enable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.enable_tiling()`."
|
535 |
+
deprecate(
|
536 |
+
"enable_vae_tiling",
|
537 |
+
"0.40.0",
|
538 |
+
depr_message,
|
539 |
+
)
|
540 |
self.vae.enable_tiling()
|
541 |
|
542 |
def disable_vae_tiling(self):
|
|
|
544 |
Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
|
545 |
computing decoding in one step.
|
546 |
"""
|
547 |
+
depr_message = f"Calling `disable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.disable_tiling()`."
|
548 |
+
deprecate(
|
549 |
+
"disable_vae_tiling",
|
550 |
+
"0.40.0",
|
551 |
+
depr_message,
|
552 |
+
)
|
553 |
self.vae.disable_tiling()
|
554 |
|
555 |
def _encode_prompt(
|
main/pipeline_stable_diffusion_pag.py
CHANGED
@@ -471,6 +471,12 @@ class StableDiffusionPAGPipeline(
|
|
471 |
Enable sliced VAE decoding. When this option is enabled, the VAE will split the input tensor in slices to
|
472 |
compute decoding in several steps. This is useful to save some memory and allow larger batch sizes.
|
473 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
474 |
self.vae.enable_slicing()
|
475 |
|
476 |
def disable_vae_slicing(self):
|
@@ -478,6 +484,12 @@ class StableDiffusionPAGPipeline(
|
|
478 |
Disable sliced VAE decoding. If `enable_vae_slicing` was previously enabled, this method will go back to
|
479 |
computing decoding in one step.
|
480 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
481 |
self.vae.disable_slicing()
|
482 |
|
483 |
def enable_vae_tiling(self):
|
@@ -486,6 +498,12 @@ class StableDiffusionPAGPipeline(
|
|
486 |
compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
|
487 |
processing larger images.
|
488 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
489 |
self.vae.enable_tiling()
|
490 |
|
491 |
def disable_vae_tiling(self):
|
@@ -493,6 +511,12 @@ class StableDiffusionPAGPipeline(
|
|
493 |
Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
|
494 |
computing decoding in one step.
|
495 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
496 |
self.vae.disable_tiling()
|
497 |
|
498 |
def _encode_prompt(
|
|
|
471 |
Enable sliced VAE decoding. When this option is enabled, the VAE will split the input tensor in slices to
|
472 |
compute decoding in several steps. This is useful to save some memory and allow larger batch sizes.
|
473 |
"""
|
474 |
+
depr_message = f"Calling `enable_vae_slicing()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.enable_slicing()`."
|
475 |
+
deprecate(
|
476 |
+
"enable_vae_slicing",
|
477 |
+
"0.40.0",
|
478 |
+
depr_message,
|
479 |
+
)
|
480 |
self.vae.enable_slicing()
|
481 |
|
482 |
def disable_vae_slicing(self):
|
|
|
484 |
Disable sliced VAE decoding. If `enable_vae_slicing` was previously enabled, this method will go back to
|
485 |
computing decoding in one step.
|
486 |
"""
|
487 |
+
depr_message = f"Calling `disable_vae_slicing()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.disable_slicing()`."
|
488 |
+
deprecate(
|
489 |
+
"disable_vae_slicing",
|
490 |
+
"0.40.0",
|
491 |
+
depr_message,
|
492 |
+
)
|
493 |
self.vae.disable_slicing()
|
494 |
|
495 |
def enable_vae_tiling(self):
|
|
|
498 |
compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
|
499 |
processing larger images.
|
500 |
"""
|
501 |
+
depr_message = f"Calling `enable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.enable_tiling()`."
|
502 |
+
deprecate(
|
503 |
+
"enable_vae_tiling",
|
504 |
+
"0.40.0",
|
505 |
+
depr_message,
|
506 |
+
)
|
507 |
self.vae.enable_tiling()
|
508 |
|
509 |
def disable_vae_tiling(self):
|
|
|
511 |
Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
|
512 |
computing decoding in one step.
|
513 |
"""
|
514 |
+
depr_message = f"Calling `disable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.disable_tiling()`."
|
515 |
+
deprecate(
|
516 |
+
"disable_vae_tiling",
|
517 |
+
"0.40.0",
|
518 |
+
depr_message,
|
519 |
+
)
|
520 |
self.vae.disable_tiling()
|
521 |
|
522 |
def _encode_prompt(
|
main/pipeline_stg_hunyuan_video.py
CHANGED
@@ -26,7 +26,7 @@ from diffusers.models import AutoencoderKLHunyuanVideo, HunyuanVideoTransformer3
|
|
26 |
from diffusers.pipelines.hunyuan_video.pipeline_output import HunyuanVideoPipelineOutput
|
27 |
from diffusers.pipelines.pipeline_utils import DiffusionPipeline
|
28 |
from diffusers.schedulers import FlowMatchEulerDiscreteScheduler
|
29 |
-
from diffusers.utils import is_torch_xla_available, logging, replace_example_docstring
|
30 |
from diffusers.utils.torch_utils import randn_tensor
|
31 |
from diffusers.video_processor import VideoProcessor
|
32 |
|
@@ -481,6 +481,12 @@ class HunyuanVideoSTGPipeline(DiffusionPipeline, HunyuanVideoLoraLoaderMixin):
|
|
481 |
Enable sliced VAE decoding. When this option is enabled, the VAE will split the input tensor in slices to
|
482 |
compute decoding in several steps. This is useful to save some memory and allow larger batch sizes.
|
483 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
484 |
self.vae.enable_slicing()
|
485 |
|
486 |
def disable_vae_slicing(self):
|
@@ -488,6 +494,12 @@ class HunyuanVideoSTGPipeline(DiffusionPipeline, HunyuanVideoLoraLoaderMixin):
|
|
488 |
Disable sliced VAE decoding. If `enable_vae_slicing` was previously enabled, this method will go back to
|
489 |
computing decoding in one step.
|
490 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
491 |
self.vae.disable_slicing()
|
492 |
|
493 |
def enable_vae_tiling(self):
|
@@ -496,6 +508,12 @@ class HunyuanVideoSTGPipeline(DiffusionPipeline, HunyuanVideoLoraLoaderMixin):
|
|
496 |
compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
|
497 |
processing larger images.
|
498 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
499 |
self.vae.enable_tiling()
|
500 |
|
501 |
def disable_vae_tiling(self):
|
@@ -503,6 +521,12 @@ class HunyuanVideoSTGPipeline(DiffusionPipeline, HunyuanVideoLoraLoaderMixin):
|
|
503 |
Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
|
504 |
computing decoding in one step.
|
505 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
506 |
self.vae.disable_tiling()
|
507 |
|
508 |
@property
|
|
|
26 |
from diffusers.pipelines.hunyuan_video.pipeline_output import HunyuanVideoPipelineOutput
|
27 |
from diffusers.pipelines.pipeline_utils import DiffusionPipeline
|
28 |
from diffusers.schedulers import FlowMatchEulerDiscreteScheduler
|
29 |
+
from diffusers.utils import deprecate, is_torch_xla_available, logging, replace_example_docstring
|
30 |
from diffusers.utils.torch_utils import randn_tensor
|
31 |
from diffusers.video_processor import VideoProcessor
|
32 |
|
|
|
481 |
Enable sliced VAE decoding. When this option is enabled, the VAE will split the input tensor in slices to
|
482 |
compute decoding in several steps. This is useful to save some memory and allow larger batch sizes.
|
483 |
"""
|
484 |
+
depr_message = f"Calling `enable_vae_slicing()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.enable_slicing()`."
|
485 |
+
deprecate(
|
486 |
+
"enable_vae_slicing",
|
487 |
+
"0.40.0",
|
488 |
+
depr_message,
|
489 |
+
)
|
490 |
self.vae.enable_slicing()
|
491 |
|
492 |
def disable_vae_slicing(self):
|
|
|
494 |
Disable sliced VAE decoding. If `enable_vae_slicing` was previously enabled, this method will go back to
|
495 |
computing decoding in one step.
|
496 |
"""
|
497 |
+
depr_message = f"Calling `disable_vae_slicing()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.disable_slicing()`."
|
498 |
+
deprecate(
|
499 |
+
"disable_vae_slicing",
|
500 |
+
"0.40.0",
|
501 |
+
depr_message,
|
502 |
+
)
|
503 |
self.vae.disable_slicing()
|
504 |
|
505 |
def enable_vae_tiling(self):
|
|
|
508 |
compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
|
509 |
processing larger images.
|
510 |
"""
|
511 |
+
depr_message = f"Calling `enable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.enable_tiling()`."
|
512 |
+
deprecate(
|
513 |
+
"enable_vae_tiling",
|
514 |
+
"0.40.0",
|
515 |
+
depr_message,
|
516 |
+
)
|
517 |
self.vae.enable_tiling()
|
518 |
|
519 |
def disable_vae_tiling(self):
|
|
|
521 |
Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
|
522 |
computing decoding in one step.
|
523 |
"""
|
524 |
+
depr_message = f"Calling `disable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.disable_tiling()`."
|
525 |
+
deprecate(
|
526 |
+
"disable_vae_tiling",
|
527 |
+
"0.40.0",
|
528 |
+
depr_message,
|
529 |
+
)
|
530 |
self.vae.disable_tiling()
|
531 |
|
532 |
@property
|
main/pipeline_stg_mochi.py
CHANGED
@@ -26,11 +26,7 @@ from diffusers.models import AutoencoderKLMochi, MochiTransformer3DModel
|
|
26 |
from diffusers.pipelines.mochi.pipeline_output import MochiPipelineOutput
|
27 |
from diffusers.pipelines.pipeline_utils import DiffusionPipeline
|
28 |
from diffusers.schedulers import FlowMatchEulerDiscreteScheduler
|
29 |
-
from diffusers.utils import
|
30 |
-
is_torch_xla_available,
|
31 |
-
logging,
|
32 |
-
replace_example_docstring,
|
33 |
-
)
|
34 |
from diffusers.utils.torch_utils import randn_tensor
|
35 |
from diffusers.video_processor import VideoProcessor
|
36 |
|
@@ -458,6 +454,12 @@ class MochiSTGPipeline(DiffusionPipeline, Mochi1LoraLoaderMixin):
|
|
458 |
Enable sliced VAE decoding. When this option is enabled, the VAE will split the input tensor in slices to
|
459 |
compute decoding in several steps. This is useful to save some memory and allow larger batch sizes.
|
460 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
461 |
self.vae.enable_slicing()
|
462 |
|
463 |
def disable_vae_slicing(self):
|
@@ -465,6 +467,12 @@ class MochiSTGPipeline(DiffusionPipeline, Mochi1LoraLoaderMixin):
|
|
465 |
Disable sliced VAE decoding. If `enable_vae_slicing` was previously enabled, this method will go back to
|
466 |
computing decoding in one step.
|
467 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
468 |
self.vae.disable_slicing()
|
469 |
|
470 |
def enable_vae_tiling(self):
|
@@ -473,6 +481,12 @@ class MochiSTGPipeline(DiffusionPipeline, Mochi1LoraLoaderMixin):
|
|
473 |
compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
|
474 |
processing larger images.
|
475 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
476 |
self.vae.enable_tiling()
|
477 |
|
478 |
def disable_vae_tiling(self):
|
@@ -480,6 +494,12 @@ class MochiSTGPipeline(DiffusionPipeline, Mochi1LoraLoaderMixin):
|
|
480 |
Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
|
481 |
computing decoding in one step.
|
482 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
483 |
self.vae.disable_tiling()
|
484 |
|
485 |
def prepare_latents(
|
|
|
26 |
from diffusers.pipelines.mochi.pipeline_output import MochiPipelineOutput
|
27 |
from diffusers.pipelines.pipeline_utils import DiffusionPipeline
|
28 |
from diffusers.schedulers import FlowMatchEulerDiscreteScheduler
|
29 |
+
from diffusers.utils import deprecate, is_torch_xla_available, logging, replace_example_docstring
|
|
|
|
|
|
|
|
|
30 |
from diffusers.utils.torch_utils import randn_tensor
|
31 |
from diffusers.video_processor import VideoProcessor
|
32 |
|
|
|
454 |
Enable sliced VAE decoding. When this option is enabled, the VAE will split the input tensor in slices to
|
455 |
compute decoding in several steps. This is useful to save some memory and allow larger batch sizes.
|
456 |
"""
|
457 |
+
depr_message = f"Calling `enable_vae_slicing()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.enable_slicing()`."
|
458 |
+
deprecate(
|
459 |
+
"enable_vae_slicing",
|
460 |
+
"0.40.0",
|
461 |
+
depr_message,
|
462 |
+
)
|
463 |
self.vae.enable_slicing()
|
464 |
|
465 |
def disable_vae_slicing(self):
|
|
|
467 |
Disable sliced VAE decoding. If `enable_vae_slicing` was previously enabled, this method will go back to
|
468 |
computing decoding in one step.
|
469 |
"""
|
470 |
+
depr_message = f"Calling `disable_vae_slicing()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.disable_slicing()`."
|
471 |
+
deprecate(
|
472 |
+
"disable_vae_slicing",
|
473 |
+
"0.40.0",
|
474 |
+
depr_message,
|
475 |
+
)
|
476 |
self.vae.disable_slicing()
|
477 |
|
478 |
def enable_vae_tiling(self):
|
|
|
481 |
compute decoding and encoding in several steps. This is useful for saving a large amount of memory and to allow
|
482 |
processing larger images.
|
483 |
"""
|
484 |
+
depr_message = f"Calling `enable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.enable_tiling()`."
|
485 |
+
deprecate(
|
486 |
+
"enable_vae_tiling",
|
487 |
+
"0.40.0",
|
488 |
+
depr_message,
|
489 |
+
)
|
490 |
self.vae.enable_tiling()
|
491 |
|
492 |
def disable_vae_tiling(self):
|
|
|
494 |
Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to
|
495 |
computing decoding in one step.
|
496 |
"""
|
497 |
+
depr_message = f"Calling `disable_vae_tiling()` on a `{self.__class__.__name__}` is deprecated and this method will be removed in a future version. Please use `pipe.vae.disable_tiling()`."
|
498 |
+
deprecate(
|
499 |
+
"disable_vae_tiling",
|
500 |
+
"0.40.0",
|
501 |
+
depr_message,
|
502 |
+
)
|
503 |
self.vae.disable_tiling()
|
504 |
|
505 |
def prepare_latents(
|