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Add lora apply in sdxl l2l node
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@ -553,9 +553,19 @@ class SDXLLatentsToLatentsInvocation(BaseInvocation):
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context=context,
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)
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def _lora_loader():
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for lora in self.unet.loras:
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lora_info = context.services.model_manager.get_model(
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**lora.dict(exclude={"weight"}),
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context=context,
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)
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yield (lora_info.context.model, lora.weight)
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del lora_info
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return
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do_classifier_free_guidance = True
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cross_attention_kwargs = None
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with unet_info as unet:
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with ModelPatcher.apply_lora_unet(unet_info.context.model, _lora_loader()), unet_info as unet:
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# apply denoising_start
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num_inference_steps = self.steps
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scheduler.set_timesteps(num_inference_steps, device=unet.device)
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