Files
hao-ai-lab-FastVideo/examples/inference/basic/basic.py
T
SolitaryThinker bbbb7ab021 [refactor]: migrate examples/scripts to typed VideoGenerator API; rename api/compat.py to api/translation.py
Move all examples/inference and scripts off the legacy
VideoGenerator.from_pretrained(model, **kwargs) +
generate_video(prompt, **kwargs) surface onto the typed
from_config(GeneratorConfig(...)) + generate(GenerationRequest(...))
convention, including the Kandinsky-5 and DreamX-World examples added
on main after the original migration. git-mv api/compat.py to
api/translation.py ('compat' implied a temporary shim; the forward
translation is its honest permanent role) and repoint all importers,
tests, and doc links.
2026-07-11 03:26:24 -07:00

53 lines
2.2 KiB
Python

from fastvideo import VideoGenerator
from fastvideo.api import (
EngineConfig, GenerationRequest, GeneratorConfig, OffloadConfig, OutputConfig,
)
OUTPUT_PATH = "video_samples"
def main():
# FastVideo will automatically use the optimal default arguments for the
# model.
# If a local path is provided, FastVideo will make a best effort
# attempt to identify the optimal arguments.
generator = VideoGenerator.from_config(
GeneratorConfig(
model_path="Wan-AI/Wan2.1-T2V-1.3B-Diffusers",
# FastVideo will automatically handle distributed setup
engine=EngineConfig(
num_gpus=1,
use_fsdp_inference=False, # set to True if GPU is out of memory
offload=OffloadConfig(
dit=False,
vae=False,
text_encoder=True,
pin_cpu_memory=True, # set to false if low CPU RAM or hit obscure "CUDA error: Invalid argument"
# image_encoder=False,
),
),
)
)
# Generate videos with the same simple API, regardless of GPU count
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(
GenerationRequest(prompt=prompt, output=OutputConfig(output_path=OUTPUT_PATH, save_video=True)))
# Generate another video with a different prompt, without reloading the
# model!
prompt2 = (
"A majestic lion strides across the golden savanna, its powerful frame "
"glistening under the warm afternoon sun. The tall grass ripples gently in "
"the breeze, enhancing the lion's commanding presence. The tone is vibrant, "
"embodying the raw energy of the wild. Low angle, steady tracking shot, "
"cinematic.")
video2 = generator.generate(
GenerationRequest(prompt=prompt2, output=OutputConfig(output_path=OUTPUT_PATH, save_video=True)))
if __name__ == "__main__":
main()