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ReVision support: unclip nodes can now be used with SDXL.
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76d53c4622
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@ -148,13 +148,20 @@ class SDInpaint(BaseModel):
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super().__init__(model_config, model_type, device=device)
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self.concat_keys = ("mask", "masked_image")
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def sdxl_pooled(args, noise_augmentor):
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if "unclip_conditioning" in args:
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return unclip_adm(args.get("unclip_conditioning", None), args["device"], noise_augmentor)[:,:1280]
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else:
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return args["pooled_output"]
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class SDXLRefiner(BaseModel):
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def __init__(self, model_config, model_type=ModelType.EPS, device=None):
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super().__init__(model_config, model_type, device=device)
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self.embedder = Timestep(256)
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self.noise_augmentor = CLIPEmbeddingNoiseAugmentation(**{"noise_schedule_config": {"timesteps": 1000, "beta_schedule": "squaredcos_cap_v2"}, "timestep_dim": 1280})
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def encode_adm(self, **kwargs):
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clip_pooled = kwargs["pooled_output"]
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clip_pooled = sdxl_pooled(kwargs, self.noise_augmentor)
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width = kwargs.get("width", 768)
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height = kwargs.get("height", 768)
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crop_w = kwargs.get("crop_w", 0)
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@ -178,9 +185,10 @@ class SDXL(BaseModel):
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def __init__(self, model_config, model_type=ModelType.EPS, device=None):
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super().__init__(model_config, model_type, device=device)
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self.embedder = Timestep(256)
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self.noise_augmentor = CLIPEmbeddingNoiseAugmentation(**{"noise_schedule_config": {"timesteps": 1000, "beta_schedule": "squaredcos_cap_v2"}, "timestep_dim": 1280})
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def encode_adm(self, **kwargs):
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clip_pooled = kwargs["pooled_output"]
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clip_pooled = sdxl_pooled(kwargs, self.noise_augmentor)
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width = kwargs.get("width", 768)
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height = kwargs.get("height", 768)
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crop_w = kwargs.get("crop_w", 0)
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