SolitaryThinker
fa40553afb
checkpoint ode checkpoint fix t2v to i2v lint chekpt checkpoint hacked but working ode_init scripts WIP fixing time embedding WIP fixing time embedding checkpoint update fix revert revert revert update update visualize
47 lines
1.9 KiB
Python
47 lines
1.9 KiB
Python
from fastvideo import VideoGenerator
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from fastvideo.configs.sample import SamplingParam
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OUTPUT_PATH = "video_samples"
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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_pretrained(
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"Wan-AI/Wan2.1-T2V-1.3B-Diffusers",
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# FastVideo will automatically handle distributed setup
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num_gpus=1,
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use_fsdp_inference=True,
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dit_cpu_offload=False,
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vae_cpu_offload=False,
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text_encoder_cpu_offload=True,
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pin_cpu_memory=True, # set to false if low CPU RAM or hit obscure "CUDA error: Invalid argument"
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ti2v_task=True,
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# image_encoder_cpu_offload=False,
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)
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sampling_param = SamplingParam.from_pretrained("Wan-AI/Wan2.1-T2V-1.3B-Diffusers")
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# sampling_param.num_frames = 45
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sampling_param.image_path = "test.jpg"
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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 girl is packing a suitcase when stuff suddently starts flying around the room."
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)
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video = generator.generate_video(prompt, output_path=OUTPUT_PATH, save_video=True)
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# video = generator.generate_video(prompt, sampling_param=sampling_param, output_path="wan_t2v_videos/")
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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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# video2 = generator.generate_video(prompt2, output_path=OUTPUT_PATH, save_video=True)
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if __name__ == "__main__":
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main()
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