SolitaryThinker
bbbb7ab021
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.
64 lines
2.5 KiB
Python
64 lines
2.5 KiB
Python
from fastvideo import VideoGenerator
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from fastvideo.api import (
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EngineConfig, GenerationRequest, GeneratorConfig, OffloadConfig,
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OutputConfig, SamplingConfig,
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)
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OUTPUT_PATH = "video_samples_wan2_2_14B_t2v"
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def main():
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# FastVideo will automatically use the optimal default arguments for the
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# model.
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# If a local path is provided, FastVideo will make a best effort
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# attempt to identify the optimal arguments.
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generator = VideoGenerator.from_config(
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GeneratorConfig(
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model_path="Wan-AI/Wan2.2-T2V-A14B-Diffusers",
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engine=EngineConfig(
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# FastVideo will automatically handle distributed setup
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num_gpus=2,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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offload=OffloadConfig(
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dit=True, # DiT need to be offloaded for MoE
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vae=False,
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text_encoder=True,
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# Set pin_cpu_memory to false if CPU RAM is limited and there're no frequent CPU-GPU transfer
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pin_cpu_memory=True,
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),
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),
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)
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)
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# Generate videos with the same simple API, regardless of GPU count
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prompt = (
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"A curious raccoon peers through a vibrant field of yellow sunflowers, its eyes "
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"wide with interest. The playful yet serene atmosphere is complemented by soft "
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"natural light filtering through the petals. Mid-shot, warm and cheerful tones."
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)
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_ = generator.generate(
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GenerationRequest(
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prompt=prompt,
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sampling=SamplingConfig(height=720, width=1280, num_frames=81),
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output=OutputConfig(output_path=OUTPUT_PATH, save_video=True),
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)
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)
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# Generate another video with a different prompt, without reloading the
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# model!
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prompt2 = (
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"A majestic lion strides across the golden savanna, its powerful frame "
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"glistening under the warm afternoon sun. The tall grass ripples gently in "
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"the breeze, enhancing the lion's commanding presence. The tone is vibrant, "
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"embodying the raw energy of the wild. Low angle, steady tracking shot, "
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"cinematic.")
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_ = generator.generate(
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GenerationRequest(
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prompt=prompt2,
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sampling=SamplingConfig(height=720, width=1280, num_frames=81),
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output=OutputConfig(output_path=OUTPUT_PATH, save_video=True),
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)
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)
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if __name__ == "__main__":
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main()
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