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.
80 lines
2.6 KiB
Python
80 lines
2.6 KiB
Python
import os
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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, SamplingConfig)
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OUTPUT_PATH = os.getenv("DREAMX_WORLD_OUTPUT_PATH", "video_samples_dreamx_world")
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def _env_int(name: str, default: int) -> int:
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return int(os.getenv(name, str(default)))
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def _env_float(name: str, default: float) -> float:
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return float(os.getenv(name, str(default)))
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def main():
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model_name = os.getenv("DREAMX_WORLD_MODEL_DIR", "FastVideo/DreamX-World-5B-Cam-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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engine=EngineConfig(
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num_gpus=1,
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use_fsdp_inference=False,
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offload=OffloadConfig(
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dit=False,
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vae=True,
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text_encoder=True,
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pin_cpu_memory=False,
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),
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),
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pipeline=PipelineSelection(
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components=ComponentConfig(override_pipeline_cls_name="DreamXWorldPipeline"), ),
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))
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prompt = os.getenv(
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"DREAMX_WORLD_PROMPT",
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"A cinematic first-person drive through a futuristic coastal city at "
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"sunrise, reflective glass towers, clean streets, soft volumetric light.",
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)
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image_path = os.getenv(
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"DREAMX_WORLD_IMAGE_PATH",
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"https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/wan_i2v_input.JPG",
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)
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request = GenerationRequest(
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prompt=prompt,
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inputs=InputConfig(image_path=image_path or None),
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sampling=SamplingConfig(
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height=_env_int("DREAMX_WORLD_HEIGHT", 480),
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width=_env_int("DREAMX_WORLD_WIDTH", 832),
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num_frames=_env_int("DREAMX_WORLD_NUM_FRAMES", 161),
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num_inference_steps=_env_int("DREAMX_WORLD_STEPS", 30),
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guidance_scale=_env_float("DREAMX_WORLD_GUIDANCE", 5.0),
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),
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output=OutputConfig(
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output_path=OUTPUT_PATH,
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save_video=os.getenv("DREAMX_WORLD_SAVE_VIDEO", "1") != "0",
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),
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extensions={
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"action_list": os.getenv("DREAMX_WORLD_ACTIONS", "w,d,w").split(","),
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"action_speed_list": [
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float(value)
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for value in os.getenv("DREAMX_WORLD_ACTION_SPEEDS", "4.0,2.0,4.0").split(",")
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],
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},
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)
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try:
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generator.generate(request)
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finally:
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generator.shutdown()
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if __name__ == "__main__":
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main()
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