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fix: Loras not working correctly with Inpainting
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16f53228c2
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@ -154,18 +154,20 @@ class InpaintInvocation(BaseInvocation):
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@contextmanager
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@contextmanager
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def load_model_old_way(self, context, scheduler):
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def load_model_old_way(self, context, scheduler):
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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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yield (lora_info.context.model, lora.weight)
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del lora_info
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return
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unet_info = context.services.model_manager.get_model(**self.unet.unet.dict())
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unet_info = context.services.model_manager.get_model(**self.unet.unet.dict())
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vae_info = context.services.model_manager.get_model(**self.vae.vae.dict())
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vae_info = context.services.model_manager.get_model(**self.vae.vae.dict())
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#unet = unet_info.context.model
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#vae = vae_info.context.model
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with ExitStack() as stack:
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loras = [(stack.enter_context(context.services.model_manager.get_model(**lora.dict(exclude={"weight"}))), lora.weight) for lora in self.unet.loras]
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with vae_info as vae,\
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with vae_info as vae,\
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unet_info as unet,\
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ModelPatcher.apply_lora_unet(unet_info.context.model, _lora_loader()),\
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ModelPatcher.apply_lora_unet(unet, loras):
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unet_info as unet:
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device = context.services.model_manager.mgr.cache.execution_device
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device = context.services.model_manager.mgr.cache.execution_device
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dtype = context.services.model_manager.mgr.cache.precision
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dtype = context.services.model_manager.mgr.cache.precision
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