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.
61 lines
2.9 KiB
Python
61 lines
2.9 KiB
Python
from fastvideo import VideoGenerator
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from fastvideo.api import (ComponentConfig, EngineConfig, GenerationRequest,
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GeneratorConfig, InputConfig, OffloadConfig,
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OutputConfig, PipelineSelection, QuantizationConfig)
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import argparse
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OUTPUT_PATH = "video_samples_wan2_2_5B_ti2v"
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def main(text_encoder_path: str):
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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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model_name = "Wan-AI/Wan2.2-TI2V-5B-Diffusers"
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generator = VideoGenerator.from_config(
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GeneratorConfig(
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model_path=model_name,
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# FastVideo will automatically handle distributed setup
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engine=EngineConfig(
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num_gpus=1,
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use_fsdp_inference=True,
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offload=OffloadConfig(
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dit=True,
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vae=False,
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text_encoder=False,
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pin_cpu_memory=
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True, # set to false if low CPU RAM or hit obscure "CUDA error: Invalid argument"
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),
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# AbsMaxFP8 is the quantization method used by ComfyUI;
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# check fastvideo/layers/quantization/* for more quantization methods
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quantization=QuantizationConfig(text_encoder_quant="AbsMaxFP8"),
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),
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pipeline=PipelineSelection(
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components=ComponentConfig(
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# for Wan 2.2, this is the path to "umt5_xxl_fp8_e4m3fn_scaled.safetensors"
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text_encoder_weights=text_encoder_path, ), ),
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))
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# I2V is triggered just by passing in an image_path argument
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prompt = "Summer beach vacation style, a white cat wearing sunglasses sits on a surfboard. The fluffy-furred feline gazes directly at the camera with a relaxed expression. Blurred beach scenery forms the background featuring crystal-clear waters, distant green hills, and a blue sky dotted with white clouds. The cat assumes a naturally relaxed posture, as if savoring the sea breeze and warm sunlight. A close-up shot highlights the feline's intricate details and the refreshing atmosphere of the seaside."
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image_path = "https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/wan_i2v_input.JPG"
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video = generator.generate(
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GenerationRequest(
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prompt=prompt,
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inputs=InputConfig(image_path=image_path),
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output=OutputConfig(output_path=OUTPUT_PATH, save_video=True),
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))
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--text_encoder_path",
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type=str,
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required=True,
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help="Path to the quantized text encoder safetensors file.",
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)
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args = parser.parse_args()
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main(args.text_encoder_path)
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