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https://github.com/modelscope/DiffSynth-Studio.git
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minor fix
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@@ -141,7 +141,6 @@ model_loader_configs = [
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(None, "ac6a5aa74f4a0aab6f64eb9a72f19901", ["wan_video_dit"], [WanModel], "civitai"),
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(None, "b61c605c2adbd23124d152ed28e049ae", ["wan_video_dit"], [WanModel], "civitai"),
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(None, "1f5ab7703c6fc803fdded85ff040c316", ["wan_video_dit"], [WanModel], "civitai"),
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(None, "aafcfd9672c3a2456dc46e1cb6e52c70", ["wan_video_dit"], [WanModel], "civitai"),
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(None, "5b013604280dd715f8457c6ed6d6a626", ["wan_video_dit"], [WanModel], "civitai"),
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(None, "a61453409b67cd3246cf0c3bebad47ba", ["wan_video_dit", "wan_video_vace"], [WanModel, VaceWanModel], "civitai"),
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(None, "7a513e1f257a861512b1afd387a8ecd9", ["wan_video_dit", "wan_video_vace"], [WanModel, VaceWanModel], "civitai"),
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@@ -619,7 +619,6 @@ class WanVideoPipeline(BasePipeline):
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for progress_id, timestep in enumerate(progress_bar_cmd(self.scheduler.timesteps)):
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# switch high_noise DiT to low_noise DiT
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if models.get("dit2") is not None and timestep.item() < boundary * self.scheduler.num_train_timesteps:
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print("switching to low noise DiT")
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self.load_models_to_device(["dit2", "motion_controller", "vace"])
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models["dit"] = models.pop("dit2")
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timestep = timestep.unsqueeze(0).to(dtype=self.torch_dtype, device=self.device)
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