Remove old workaround

nodes.py

@@ -5,6 +5,8 @@ import collections
 
 import nodes
 import comfy.sd
+import comfy.lora
+import comfy.float
 import comfy.utils
 import comfy.model_patcher
 import comfy.model_management
@@ -37,17 +39,12 @@ class GGUFModelPatcher(comfy.model_patcher.ModelPatcher):
             return
         weight = comfy.utils.get_attr(self.model, key)
 
-        try:
-            from comfy.lora import calculate_weight
-        except Exception:
-            calculate_weight = self.calculate_weight
-
         patches = self.patches[key]
         if is_quantized(weight):
             out_weight = weight.to(device_to)
             patches = move_patch_to_device(patches, self.load_device if self.patch_on_device else self.offload_device)
             # TODO: do we ever have legitimate duplicate patches? (i.e. patch on top of patched weight)
-            out_weight.patches = [(calculate_weight, patches, key)]
+            out_weight.patches = [(patches, key)]
         else:
             inplace_update = self.weight_inplace_update or inplace_update
             if key not in self.backup:
@@ -60,7 +57,7 @@ class GGUFModelPatcher(comfy.model_patcher.ModelPatcher):
             else:
                 temp_weight = weight.to(torch.float32, copy=True)
 
-            out_weight = calculate_weight(patches, temp_weight, key)
+            out_weight = comfy.lora.calculate_weight(patches, temp_weight, key)
             out_weight = comfy.float.stochastic_rounding(out_weight, weight.dtype)
 
         if inplace_update:

ops.py

@@ -4,6 +4,7 @@ import torch
 import logging
 
 import comfy.ops
+import comfy.lora
 import comfy.model_management
 from .dequant import dequantize_tensor, is_quantized
 
@@ -169,7 +170,7 @@ class GGMLLayer(torch.nn.Module):
         # consolidate and load patches to GPU in async
         patch_list = []
         device = tensor.device
-        for function, patches, key in getattr(tensor, "patches", []):
+        for patches, key in getattr(tensor, "patches", []):
             patch_list += move_patch_to_device(patches, device)
 
         # dequantize tensor while patches load
@@ -180,13 +181,13 @@ class GGMLLayer(torch.nn.Module):
             weight = torch.Tensor(weight)
 
         # apply patches
-        if patch_list:
+        if len(patch_list) > 0:
             if self.patch_dtype is None:
-                weight = function(patch_list, weight, key)
+                weight = comfy.lora.calculate_weight(patch_list, weight, key)
             else:
                 # for testing, may degrade image quality
                 patch_dtype = dtype if self.patch_dtype == "target" else self.patch_dtype
-                weight = function(patch_list, weight, key, patch_dtype)
+                weight = comfy.lora.calculate_weight(patch_list, weight, key, patch_dtype)
         return weight
 
     @torch_compiler_disable()