i

modules/adm_patch.py

@@ -0,0 +1,33 @@
+import torch
+import comfy.model_base
+
+
+def sdxl_encode_adm_patched(self, **kwargs):
+    clip_pooled = kwargs["pooled_output"]
+    width = kwargs.get("width", 768)
+    height = kwargs.get("height", 768)
+    crop_w = kwargs.get("crop_w", 0)
+    crop_h = kwargs.get("crop_h", 0)
+    target_width = kwargs.get("target_width", width)
+    target_height = kwargs.get("target_height", height)
+
+    if kwargs.get("prompt_type", "") == "negative":
+        admk = 0.8
+        width *= admk
+        height *= admk
+        target_width *= admk
+        target_height *= admk
+
+    out = []
+    out.append(self.embedder(torch.Tensor([height])))
+    out.append(self.embedder(torch.Tensor([width])))
+    out.append(self.embedder(torch.Tensor([crop_h])))
+    out.append(self.embedder(torch.Tensor([crop_w])))
+    out.append(self.embedder(torch.Tensor([target_height])))
+    out.append(self.embedder(torch.Tensor([target_width])))
+    flat = torch.flatten(torch.cat(out))[None, ]
+    return torch.cat((clip_pooled.to(flat.device), flat), dim=1)
+
+
+def patch_negative_adm():
+    comfy.model_base.SDXL.encode_adm = sdxl_encode_adm_patched

modules/core.py

@@ -12,7 +12,10 @@ from comfy.sd import load_checkpoint_guess_config
 from nodes import VAEDecode, EmptyLatentImage, CLIPTextEncode
 from comfy.sample import prepare_mask, broadcast_cond, load_additional_models, cleanup_additional_models
 from modules.samplers_advanced import KSampler, KSamplerWithRefiner
+from modules.adm_patch import patch_negative_adm
 
+
+patch_negative_adm()
 opCLIPTextEncode = CLIPTextEncode()
 opEmptyLatentImage = EmptyLatentImage()
 opVAEDecode = VAEDecode()