DistributedDiffusion

This repository contains a demo implementation of the algorithm as presented in:

"Exploring Collaborative Distributed Diffusion-Based AI-Generated Content (AIGC) in Wireless Networks" Download Paper

📝 Table of Contents

Environment Setup
Activate Environment
Install Required Packages
Locate StableDiffusionPipeline
Replace with Project File
Run the Program
Cite Our Work

🔧 Environment Setup

To create a new conda environment, run the following command:

conda create --name disdiff python==3.9

⚡Activate Environment

Activate the created environment with:

conda activate disdiff

📦 Install Required Packages

You need to install the following packages using pip:

pip install diffusers==0.13.1
pip install torch==2.0.1
pip install transformers==4.29.2
pip install accelerate==0.20.0

Then you should get an env like mine:

(disdiff) Hongyang_Du@MacBook-Pro-3 ~ % conda list
# packages in environment at /Users/Hongyang_Du/opt/anaconda3/envs/disdiff:
#
# Name                    Version                   Build  Channel
accelerate                0.20.0                   pypi_0    pypi
ca-certificates           2023.01.10           hecd8cb5_0  
certifi                   2023.5.7                 pypi_0    pypi
charset-normalizer        3.1.0                    pypi_0    pypi
diffusers                 0.13.1                   pypi_0    pypi
filelock                  3.12.0                   pypi_0    pypi
fsspec                    2023.5.0                 pypi_0    pypi
huggingface-hub           0.15.1                   pypi_0    pypi
idna                      3.4                      pypi_0    pypi
importlib-metadata        6.6.0                    pypi_0    pypi
jinja2                    3.1.2                    pypi_0    pypi
libcxx                    14.0.6               h9765a3e_0  
libffi                    3.3                  hb1e8313_2  
markupsafe                2.1.3                    pypi_0    pypi
mpmath                    1.3.0                    pypi_0    pypi
ncurses                   6.4                  hcec6c5f_0  
networkx                  3.1                      pypi_0    pypi
numpy                     1.24.3                   pypi_0    pypi
openssl                   1.1.1t               hca72f7f_0  
packaging                 23.1                     pypi_0    pypi
pillow                    9.5.0                    pypi_0    pypi
pip                       23.0.1           py39hecd8cb5_0  
psutil                    5.9.5                    pypi_0    pypi
python                    3.9.0                h88f2d9e_2  
pyyaml                    6.0                      pypi_0    pypi
readline                  8.2                  hca72f7f_0  
regex                     2023.6.3                 pypi_0    pypi
requests                  2.31.0                   pypi_0    pypi
setuptools                67.8.0           py39hecd8cb5_0  
sqlite                    3.41.2               h6c40b1e_0  
sympy                     1.12                     pypi_0    pypi
tk                        8.6.12               h5d9f67b_0  
tokenizers                0.13.3                   pypi_0    pypi
torch                     2.0.1                    pypi_0    pypi
tqdm                      4.65.0                   pypi_0    pypi
transformers              4.29.2                   pypi_0    pypi
typing-extensions         4.6.3                    pypi_0    pypi
tzdata                    2023c                h04d1e81_0  
urllib3                   2.0.3                    pypi_0    pypi
wheel                     0.38.4           py39hecd8cb5_0  
xz                        5.4.2                h6c40b1e_0  
zipp                      3.15.0                   pypi_0    pypi
zlib                      1.2.13               h4dc903c_0

🔍 Locate StableDiffusionPipeline

Open offloading.py in your code editor. Hold ctrl key if you are on Windows or command key if you are on Mac, and click on StableDiffusionPipeline

This will navigate to the file pipeline_stable_diffusion.py. To locate this file in your directory, right-click on the filename and choose 'open in' -> 'finder'.

🔄 Replace with Project File

Replace pipeline_stable_diffusion.py with the file of the same name from this repository.

🏃‍♀️ Run the Program

Finally, run offloading.py to start the program.

Please note that the model will be downloaded automatically if you are running this code for the first time.

🔍 Check the results

The parameter "tt" is the offloading processing point

The parameter "ss" is the total denosing steps

For more details, please check the offloading.py

📚 Cite Our Work

If our code proves useful in your research, please consider citing our work:

@article{du2023exploring,
  title={Exploring Collaborative Distributed Diffusion-Based AI-Generated Content (AIGC) in Wireless Networks},
  author={Du, Hongyang and Zhang, Ruichen and Niyato, Dusit and Kang, Jiawen and Xiong, Zehui and Kim, Dong In and Poor, H Vincent},
  journal={arXiv preprint arXiv:2304.03446},
  year={2023}
}

Hcheng-ya/DistributedDiffusion