TeaCache/TeaCache4HunyuanVideo/README.md

TeaCache4HunyuanVideo

TeaCache can speedup HunyuanVideo 2x without much visual quality degradation, in a training-free manner.

📈 Inference Latency Comparisons on a Single A800 GPU

Resolution	HunyuanVideo	TeaCache (0.1)	TeaCache (0.15)
540p	~18 min	~11 min	~8 min
720p	~50 min	~30 min	~23 min

Usage

Follow HunyuanVideo to clone the repo and finish the installation, then copy 'teacache_sample_video.py' in this repo to the HunyuanVideo repo. You can modify the thresh in line 220 to obtain your desired trade-off between latency and visul quality.

For single-gpu inference, you can use the following command:

cd HunyuanVideo

python3 teacache_sample_video.py \
    --video-size 720 1280 \
    --video-length 129 \
    --infer-steps 50 \
    --prompt "A cat walks on the grass, realistic style." \
    --flow-reverse \
    --use-cpu-offload \
    --save-path ./teacache_results

To generate a video with 8 GPUs, you can use the following command:

cd HunyuanVideo

torchrun --nproc_per_node=8 teacache_sample_video.py \
    --video-size 1280 720 \
    --video-length 129 \
    --infer-steps 50 \
    --prompt "A cat walks on the grass, realistic style." \
    --flow-reverse \
    --seed 42 \
    --ulysses-degree 8 \
    --ring-degree 1 \
    --save-path ./teacache_results

Acknowledgements

We would like to thank the contributors to the HunyuanVideo.