DeepCache: Accelerating Diffusion Models for Free
(Results on Stable Diffusion v1.5. Left: 50 PLMS steps. Right: 2.3x acceleration upon 50 PLMS steps)
DeepCache: Accelerating Diffusion Models for Free
Xinyin Ma, Gongfan Fang, Xinchao Wang
Learning and Vision Lab, National University of Singapore
π₯―[Arxiv]π[Project Page]
Why DeepCache
- π Training-free and almost lossless
- π Support Stable Diffusion, Stable Diffusion XL, Stable Video Diffusion, DDPM
- π Compatible with sampling algorithms like DDIM and PLMS
Updates
- December 26, 2023: π₯Update a plug-and-play implementation of DeepCache, no longer requiring any modifications of the diffuser's code! Check here for the detailed usage! Big thanks to @yuanshi9815 for contributing the code!
- December 25, 2023: A demo is available via Colab
- December 21, 2023: Release the code for Stable Video Diffusion and Text2Video-Zero. In the figure below, the upper row shows the original videos generated by SVD-XT, and the lower row is accelerated by DeepCache. For Text2Video-Zero, the results can be found here
(1.7x acceleration of SVD-XT)
-
December 20, 2023: Release the code for DDPM. See here for the experimental code and instructions.
-
December 6, 2023: Release the code for Stable Diffusion XL. The results of the
stabilityai/stable-diffusion-xl-base-1.0are shown in the below figure, with the same prompts from the first figure.
(2.6x acceleration of Stable Diffusion XL)
Introduction
We introduce DeepCache, a novel training-free and almost lossless paradigm that accelerates diffusion models from the perspective of model architecture. Utilizing the property of the U-Net, we reuse the high-level features while updating the low-level features in a very cheap way. DeepCache accelerates Stable Diffusion v1.5 by 2.3x with only a 0.05 decline in CLIP Score, and LDM-4-G(ImageNet) by 4.1x with a 0.22 decrease in FID.
Quick Start
Requirements
pip install transformers diffusersUsage
from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained('runwayml/stable-diffusion-v1-5', torch_dtype=torch.float16).to("cuda:0")
from DeepCache import DeepCacheSDHelper
helper = DeepCacheSDHelper(pipe=pipe)
helper.set_params(
cache_interval=3,
cache_branch_id=0,
)
helper.enable()
deepcache_image = pipe(
prompt,
output_type='pt'
).images[0]
helper.disable()We here take the Stable Diffusion pipeline as an example. You can replace pipe with any variants of the Stable Diffusion pipeline, including choices like SDXL, SVD, and more. The argument cache_branch_id specifies the selected skip branch. For the skip branches that are deeper, the model will engage them only during the caching steps, and exclude them during the retrieval steps.
You can explore DeepCache by using the command provided below:
python main.py --model_type sdxl #Support [sdxl, sd1.5, svd]Scripts
Stable Diffusion XL
python stable_diffusion_xl.py --model stabilityai/stable-diffusion-xl-base-1.0Output:
Loading pipeline components...: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 7/7 [00:01<00:00, 6.62it/s]
2023-12-06 01:44:28,578 - INFO - Running baseline...
100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 50/50 [00:17<00:00, 2.93it/s]
2023-12-06 01:44:46,095 - INFO - Baseline: 17.52 seconds
Loading pipeline components...: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 7/7 [00:00<00:00, 8.06it/s]
2023-12-06 01:45:02,865 - INFO - Running DeepCache...
100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 50/50 [00:06<00:00, 8.01it/s]
2023-12-06 01:45:09,573 - INFO - DeepCache: 6.71 seconds
2023-12-06 01:45:10,678 - INFO - Saved to output.png. Done!You can add --refine at the end of the command to activate the refiner model for SDXL.
Stable Diffusion v1.5
python stable_diffusion.py --model runwayml/stable-diffusion-v1-5Output:
2023-12-03 16:18:13,636 - INFO - Loaded safety_checker as StableDiffusionSafetyChecker from `safety_checker` subfolder of runwayml/stable-diffusion-v1-5.
2023-12-03 16:18:13,699 - INFO - Loaded vae as AutoencoderKL from `vae` subfolder of runwayml/stable-diffusion-v1-5.
Loading pipeline components...: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 7/7 [00:01<00:00, 5.88it/s]
2023-12-03 16:18:22,837 - INFO - Running baseline...
100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 50/50 [00:03<00:00, 15.33it/s]
2023-12-03 16:18:26,174 - INFO - Baseline: 3.34 seconds
2023-12-03 16:18:26,174 - INFO - Running DeepCache...
100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 50/50 [00:01<00:00, 34.06it/s]
2023-12-03 16:18:27,718 - INFO - DeepCache: 1.54 seconds
2023-12-03 16:18:27,935 - INFO - Saved to output.png. Done!Stable Diffusion v2.1
python stable_diffusion.py --model stabilityai/stable-diffusion-2-1Output:
2023-12-03 16:21:17,858 - INFO - Loaded feature_extractor as CLIPImageProcessor from `feature_extractor` subfolder of stabilityai/stable-diffusion-2-1.
2023-12-03 16:21:17,864 - INFO - Loaded scheduler as DDIMScheduler from `scheduler` subfolder of stabilityai/stable-diffusion-2-1.
Loading pipeline components...: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 6/6 [00:01<00:00, 5.35it/s]
2023-12-03 16:21:49,770 - INFO - Running baseline...
100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 50/50 [00:14<00:00, 3.42it/s]
2023-12-03 16:22:04,551 - INFO - Baseline: 14.78 seconds
2023-12-03 16:22:04,551 - INFO - Running DeepCache...
100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 50/50 [00:08<00:00, 6.10it/s]
2023-12-03 16:22:12,911 - INFO - DeepCache: 8.36 seconds
2023-12-03 16:22:13,417 - INFO - Saved to output.png. Done!Currently, our code supports the models that can be loaded by StableDiffusionPipeline. You can specify the model name by the argument --model, which by default, is runwayml/stable-diffusion-v1-5.
Stable Video Diffusion
python stable_video_diffusion.pyOutput:
Loading pipeline components...: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 5/5 [00:00<00:00, 8.36it/s]
2023-12-21 04:56:47,329 - INFO - Running baseline...
100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 25/25 [01:27<00:00, 3.49s/it]
2023-12-21 04:58:26,121 - INFO - Origin: 98.66 seconds
Loading pipeline components...: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 5/5 [00:00<00:00, 10.59it/s]
2023-12-21 04:58:27,202 - INFO - Running DeepCache...
100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 25/25 [00:49<00:00, 1.96s/it]
2023-12-21 04:59:26,607 - INFO - DeepCache: 59.31 secondsDDPM and LDM
Please check here for the experimental code of DDPM. The code for LDM will be released soon.
Visualization
Images in the upper line are the baselines, and the images in the lower line are accelerated by DeepCache.
Stable Diffusion v1.5 (2.15x Acceleration)
LDM-4-G for ImageNet (6.96x Acceleration)
DDPM for LSUN Church & Bedroom (1.48x Acceleration)
Quantitative Results
ImageNet
Stable Diffusion v1.5
More results can be found in our paper
Other Implementations and Plugins
We sincerely thank the authors listed below who implemented DeepCache in plugins or other contexts.
- OneDiff Integration: https://github.com/Oneflow-Inc/onediff?tab=readme-ov-file#easy-to-use by @Oneflow-Inc. OneDiff also has implementations for DeepCache on SVD, check this for details.
- Comfyui: https://gist.github.com/laksjdjf/435c512bc19636e9c9af4ee7bea9eb86 by @laksjdjf
- Colab & Gradio: https://github.com/camenduru/DeepCache-colab by @camenduru
- WebUI: AUTOMATIC1111/stable-diffusion-webui#14210 by @aria1th
We warmly welcome contributions from everyone. Please feel free to reach out to us.
Bibtex
@article{ma2023deepcache,
title={DeepCache: Accelerating Diffusion Models for Free},
author={Ma, Xinyin and Fang, Gongfan and Wang, Xinchao},
journal={arXiv preprint arXiv:2312.00858},
year={2023}
}