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Author: isidentical

src/diffusers/loaders.py

@@ -322,7 +322,7 @@ def load_attn_procs(self, pretrained_model_name_or_path_or_dict: Union[str, Dict
 
         # fill attn processors
         attn_processors = {}
-        ff_layers = []
+        non_attn_lora_layers = []
 
         is_lora = all("lora" in k for k in state_dict.keys())
         is_custom_diffusion = any("custom_diffusion" in k for k in state_dict.keys())
@@ -350,7 +350,7 @@ def load_attn_procs(self, pretrained_model_name_or_path_or_dict: Union[str, Dict
                 for sub_key in key.split("."):
                     attn_processor = getattr(attn_processor, sub_key)
 
-                # Process FF layers
+                # Process non-attention layers
                 if "lora.down.weight" in value_dict:
                     rank = value_dict["lora.down.weight"].shape[0]
                     hidden_size = value_dict["lora.up.weight"].shape[0]
@@ -366,7 +366,7 @@ def load_attn_procs(self, pretrained_model_name_or_path_or_dict: Union[str, Dict
 
                     value_dict = {k.replace("lora.", ""): v for k, v in value_dict.items()}
                     lora.load_state_dict(value_dict)
-                    ff_layers.append((attn_processor, lora))
+                    non_attn_lora_layers.append((attn_processor, lora))
                     continue
 
                 rank = value_dict["to_k_lora.down.weight"].shape[0]
@@ -428,13 +428,13 @@ def load_attn_procs(self, pretrained_model_name_or_path_or_dict: Union[str, Dict
 
         # set correct dtype & device
         attn_processors = {k: v.to(device=self.device, dtype=self.dtype) for k, v in attn_processors.items()}
-        ff_layers = [(t, l.to(device=self.device, dtype=self.dtype)) for t, l in ff_layers]
+        non_attn_lora_layers = [(t, l.to(device=self.device, dtype=self.dtype)) for t, l in non_attn_lora_layers]
 
         # set layers
         self.set_attn_processor(attn_processors)
 
         # set ff layers
-        for target_module, lora_layer in ff_layers:
+        for target_module, lora_layer in non_attn_lora_layers:
             if hasattr(target_module, "set_lora_layer"):
                 target_module.set_lora_layer(lora_layer)
 

src/diffusers/models/lora.py

@@ -17,7 +17,6 @@
 from torch import nn
 
 
-# moved from attention_processor.py
 class LoRALinearLayer(nn.Module):
     def __init__(self, in_features, out_features, rank=4, network_alpha=None, device=None, dtype=None):
         super().__init__()