ReVision support: unclip nodes can now be used with SDXL.

comfy/model_base.py

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