Fast Video

This is currently based on Open-Sora-1.2.0: https://github.com/PKU-YuanGroup/Open-Sora-Plan/tree/294993ca78bf65dec1c3b6fb25541432c545eda9

Envrironment

Change the index-url cuda version according to your system.

conda create -n fastvideo python=3.10.12
conda activate fastvideo
pip3 install torch==2.5.0 torchvision  --index-url https://download.pytorch.org/whl/cu121
pip3 install xformers==0.0.28.post2 --index-url https://download.pytorch.org/whl/cu121
pip install git+https://github.com/huggingface/diffusers.git@76b7d86a9a5c0c2186efa09c4a67b5f5666ac9e3
pip install packaging ninja && pip install flash-attn==2.7.0.post2 --no-build-isolation 

pip install -e . && pip install -e ".[train]"
sudo apt-get update && apt install screen && pip install watch gpustat

Prepare Data & Models

We've prepared some debug data to facilitate development. To make sure the training pipeline is correct, train on the debug data and make sure the model overfit on it (feed it the same text prompt and see if the output video is the same as the training data)

mkdir data && mkdir data/outputs/
python scripts/download_hf.py --repo_id=Stealths-Video/mochi_diffuser --local_dir=data/mochi --repo_type=model
python scripts/download_hf.py --repo_id=Stealths-Video/Merge-30k-Data --local_dir=data/Merge-30k-Data --repo_type=dataset
python scripts/download_hf.py --repo_id=Stealths-Video/validation_embeddings --local_dir=data/validation_embeddings --repo_type=dataset
cd data/Merge-30k-Data
cat Merged30K.tar.gz.part.* > Merged30K.tar.gz
rm Merged30K.tar.gz.part.*
tar --use-compress-program="pigz --processes 64" -xvf Merged30K.tar.gz
mv ephemeral/hao.zhang/codefolder/FastVideo-OSP/data/Merged-30K-Data/* .
rm -r ephemeral
rm Merged30K.tar.gz
cd ../..

Things Learned

1. shift8 clear but got structural artifacts
2. lq, 0.025 vague
3. adv not really helpful
4. shift8 euler steps 50 v.s. 100 very similar

Experiments

Scripts are located at scripts/experiment_N.sh

1. pcm_linear_quadratic， euler_steps 50, 0.025
2. pcm_linear_quadratic， euler_steps 50, 0.05
3. shift 8, euler_steps 100
4. shift 8, euler_steps 50
5. shift 8, euler_steps 100, adv
6. pcm_linear_quadratic， euler_steps 50, 0.025, adv
7. pcm_linear_quadratic， euler_steps 50, 0.05, multiphase 125
8. pcm_linear_quadratic， euler_steps 50, 0.1, linear_range 0.75
9. pcm_linear_quadratic， euler_steps 50, 0.05, range 0.75
10. pcm_linear_quadratic， euler_steps 50, 0.05, batchsize 32
11. pcm_linear_quadratic， euler_steps 50, learning rate,1e-7
12. shift1, euler_steps 50
13. pcm_linear_quadratic， euler_steps 50, 0.05, multiphase 250, ema 0.98, decay 0.1