SolitaryThinker
f51497ee6d
Mirrors fastvideo.entrypoints.VideoGenerator (from_config(GeneratorConfig) -> generate( GenerationRequest) -> GenerationResult.video_path), reusing the OFFICIAL fastvideo.api config classes so a basic_dmd_new_api.py-style script differs only by importing VideoGenerator from v2. - model_path -> v2 card registry (Wan2.1 / FastWan -> wan21; SFWan -> wan_causal; LTX2 -> ltx2); snapshot_download + stamp_wan21_checkpoints + Engine(cuda) + program; generate maps SamplingConfig -> DiffusionParams -> make_request -> eng.run, saves the [C,T,H,W] decode as an mp4. - Lazy v2.__getattr__ keeps 'import v2' torch-free (verified) so the CPU mini stays green (202+2). - examples/inference/basic/v2_basic_new_api.py runs all three GPU models through this API. - Single-GPU, resident, TORCH_SDPA (EngineConfig offload/num_gpus>1/VSA accepted for parity, not applied). verified: wan21 from_config->generate->mp4 (frames (5,256,256,3) uint8, video_path written).
Basic Video Generation Tutorial
The VideoGenerator class provides the primary Python interface for doing offline video generation, which is interacting with a diffusion pipeline without using a separate inference api server.
Requirements
- At least a single NVIDIA GPU with CUDA 12.4.
- Python 3.10-3.12
Installation
If you have not installed FastVideo, please following these instructions first.
Usage
The first script in this example shows the most basic usage of FastVideo. If you are new to Python and FastVideo, you should start here.
# if you have not cloned the directory:
git clone https://github.com/hao-ai-lab/FastVideo.git && cd FastVideo
python examples/inference/basic/basic.py
For an example on Apple silicon:
python examples/inference/basic/basic_mps.py
For an example running DMD+VSA inference:
python examples/inference/basic/basic_dmd.py
For the typed config/request path added during the inference API refactor:
python examples/inference/basic/basic_dmd_new_api.py
Basic Walkthrough
All you need to generate videos using multi-gpus from state-of-the-art diffusion pipelines is the following few lines!
from fastvideo import VideoGenerator
def main():
generator = VideoGenerator.from_pretrained(
"Wan-AI/Wan2.1-T2V-1.3B-Diffusers",
num_gpus=1,
)
prompt = ("A curious raccoon peers through a vibrant field of yellow sunflowers, its eyes "
"wide with interest. The playful yet serene atmosphere is complemented by soft "
"natural light filtering through the petals. Mid-shot, warm and cheerful tones.")
video = generator.generate_video(prompt)
if __name__ == "__main__":
main()