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Denoising Diffusion Probabilistic Model (DDPM) Implementation (PyTorch)

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DDPM Implementation with PyTorch

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Description

  • DDPM Implementation with PyTorch.
  • The tests directory is created to check if the functions of DDPM are working properly and for analysis purposes.

Setting

# Create Virtual Environment
python -m venv .venv

# Activate Virtual Environment
.venv\Scripts\activate # Windows
source .venv/bin/activate # Linux

# Install Packages
pip install -r requirements.txt

# Train
python train.py --config=base

# Sampling
python infer.py --config=base

References

  1. DPM: Sohl-Dickstein, Jascha, et al. "Deep unsupervised learning using nonequilibrium thermodynamics." International conference on machine learning. PMLR, 2015.
  2. DDPM: Ho, Jonathan, Ajay Jain, and Pieter Abbeel. "Denoising diffusion probabilistic models." Advances in neural information processing systems 33 (2020): 6840-6851.
  3. Original Repository: @lucidrains, denoising-diffusion-pytorch

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Denoising Diffusion Probabilistic Model (DDPM) Implementation (PyTorch)

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