Refactor inpaint/ip2p code.

comfy/model_base.py

@@ -153,8 +153,7 @@ class BaseModel(torch.nn.Module):
     def encode_adm(self, **kwargs):
         return None
 
-    def extra_conds(self, **kwargs):
-        out = {}
+    def concat_cond(self, **kwargs):
         if len(self.concat_keys) > 0:
             cond_concat = []
             denoise_mask = kwargs.get("concat_mask", kwargs.get("denoise_mask", None))
@@ -193,7 +192,14 @@ class BaseModel(torch.nn.Module):
                     elif ck == "masked_image":
                         cond_concat.append(self.blank_inpaint_image_like(noise))
             data = torch.cat(cond_concat, dim=1)
-            out['c_concat'] = comfy.conds.CONDNoiseShape(data)
+            return data
+        return None
+
+    def extra_conds(self, **kwargs):
+        out = {}
+        concat_cond = self.concat_cond(**kwargs)
+        if concat_cond is not None:
+            out['c_concat'] = comfy.conds.CONDNoiseShape(concat_cond)
 
         adm = self.encode_adm(**kwargs)
         if adm is not None:
@@ -523,9 +529,7 @@ class SD_X4Upscaler(BaseModel):
         return out
 
 class IP2P:
-    def extra_conds(self, **kwargs):
-        out = {}
-
+    def concat_cond(self, **kwargs):
         image = kwargs.get("concat_latent_image", None)
         noise = kwargs.get("noise", None)
         device = kwargs["device"]
@@ -537,18 +541,15 @@ class IP2P:
             image = utils.common_upscale(image.to(device), noise.shape[-1], noise.shape[-2], "bilinear", "center")
 
         image = utils.resize_to_batch_size(image, noise.shape[0])
+        return self.process_ip2p_image_in(image)
 
-        out['c_concat'] = comfy.conds.CONDNoiseShape(self.process_ip2p_image_in(image))
-        adm = self.encode_adm(**kwargs)
-        if adm is not None:
-            out['y'] = comfy.conds.CONDRegular(adm)
-        return out
 
 class SD15_instructpix2pix(IP2P, BaseModel):
     def __init__(self, model_config, model_type=ModelType.EPS, device=None):
         super().__init__(model_config, model_type, device=device)
         self.process_ip2p_image_in = lambda image: image
 
+
 class SDXL_instructpix2pix(IP2P, SDXL):
     def __init__(self, model_config, model_type=ModelType.EPS, device=None):
         super().__init__(model_config, model_type, device=device)